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  • v.9(31); 2021 Nov 6

Major depressive disorder: Validated treatments and future challenges

Rabie karrouri.

Department of Psychiatry, Moulay Ismaïl Military Hospital, Faculty of Medicine and Pharmacy, Sidi Mohamed Ben Abdellah University, Fez 30070, Morocco

Zakaria Hammani

Roukaya benjelloun.

Department of Psychiatry, Faculty of Medicine, Mohammed VI University of Health Sciences, Casablanca 20000, Morocco

Yassine Otheman

Department of Psychiatry, Moulay Ismaïl Military Hospital, Faculty of Medicine and Pharmacy, Sidi Mohamed Ben Abdellah University, Fez 30070, Morocco. [email protected]

Corresponding author: Yassine Otheman, MD, Associate Professor, Chief Doctor, Department of Psychiatry, Moulay Ismaïl Military Hospital, Faculty of Medicine and Pharmacy, Sidi Mohamed Ben Abdellah University, 1893, Km 2.2 road of Sidi Hrazem, Fez 30070, Morocco. [email protected]

Depression is a prevalent psychiatric disorder that often leads to poor quality of life and impaired functioning. Treatment during the acute phase of a major depressive episode aims to help the patient reach a remission state and eventually return to their baseline level of functioning. Pharmacotherapy, especially selective serotonin reuptake inhibitors antidepressants, remains the most frequent option for treating depression during the acute phase, while other promising pharmacological options are still competing for the attention of practitioners. Depression-focused psychotherapy is the second most common option for helping patients overcome the acute phase, maintain remission, and prevent relapses. Electroconvulsive therapy is the most effective somatic therapy for depression in some specific situations; meanwhile, other methods have limits, and their specific indications are still being studied. Combining medications, psychotherapy, and somatic therapies remains the most effective way to manage resistant forms of depression.

Core Tip: Depression is a persistent public health problem for which treatments must be codified and simplified to enhance current practice. Several therapies have been suggested worldwide, with varying levels of validity. This article explores effective and valid therapies for treating depression by addressing current and future research topics for different treatment categories.

INTRODUCTION

Depression is a common psychiatric disorder and a major contributor to the global burden of diseases. According to the World Health Organization, depression is the second-leading cause of disability in the world and is projected to rank first by 2030[ 1 ]. Depression is also associated with high rates of suicidal behavior and mortality[ 2 ].

Treatments administered during the acute phase of a major depressive episode aim to help the patient reach a remission state and eventually return to their baseline level of functioning[ 3 ]. Acute-phase treatment options include pharmacotherapy, depression-focused psychotherapy, combinations of medications and psychotherapy, and somatic therapies such as electroconvulsive therapy (ECT). Nevertheless, managing the acute phase of depression is only the first step in a long therapy process that aims to maintain remission and prevent relapses. In this article, we discuss various treatment options implemented by clinicians, highlighting the role that each option plays in actual psychiatric practice.

PHARMACOTHERAPY

While selective serotonin reuptake inhibitors (SSRIs) remain the gold-standard treatment for depression, new antidepressants are always being developed and tested. The ultimate goal is to discover a molecule that exhibits quick effectiveness with as few side effects as possible.

Daniel Bovet studied the structure of histamine (the causative agent in allergic responses) to find an antagonist, which was finally synthesized in 1937[ 4 ]. Since then, many researchers have studied the link between the structures and activities of different antihistaminic agents, contributing to the discovery of almost all antidepressants[ 5 ].

In the following subsections, we list the main classes of antidepressants in chronological order of apparition, highlighting the most widely used molecules in daily psychiatric practice.

Monoamine oxidase inhibitors

Iproniazid was the first drug defined as an antidepressant; it was later classified as a monoamine oxidase inhibitor (MAOI)[ 6 , 7 ]. Several other MAOIs have been introduced since 1957[ 8 ]. Due to their irreversible inhibition of monoamine oxidase, MOAIs have numerous side effects, such as hepatotoxicity and hypertensive crises, that can lead to lethal intracranial hemorrhages. Consequently, MAOIs have become less commonly used over time[ 9 ].

Trials have demonstrated that MAOIs’ efficacy is comparable to that of tricyclic antidepressants (TCAs)[ 10 , 11 ]. However, considering MAOIs’ drug interactions, dietary restrictions, and potentially dangerous side effects, they are now almost exclusively prescribed for patients who have not responded to several other pharmacotherapies, including TCAs[ 9 ]. Furthermore, MAOIs have demonstrated specific efficacy in treating depression with atypical features, such as reactive moods, reverse neuro-vegetative symptoms, and sensitivity to rejection[ 12 ].

MAOIs are also a potential therapeutic option when ECT is contraindicated[ 13 ]. MAOIs’ effectiveness is still unclear for treating depression in patients who are resistant to multiple sequential trials with SSRIs and serotonin-norepinephrine reuptake inhibitors (SNRIs)[ 14 ]. Nevertheless, psychiatrists’ use of MAOIs has declined over the years[ 15 , 16 ]. The use of MAOIs is generally restricted to patients who do not respond to other treatments.

The first TCA was discovered and released for clinical use in 1957 under the brand name Tofranil[ 5 , 17 ]. Since then, TCAs have remained among the most frequently prescribed drugs worldwide[ 9 ]. TCAs-such as amitriptyline, nortriptyline, protriptyline, imipramine, desipramine, doxepin, and trimipramine-are about as effective as other classes of antidepressants-including SSRIs, SNRIs, and MAOIs-in treating major depression[ 18 , 19 ].

However, some TCAs can be more effective than SSRIs when used to treat hospitalized patients[ 20 ]. This efficacy can be explained by the superiority of TCAs over SSRIs for patients with severe major depressive disorder (MDD) symptoms who require hospitalization[ 21 - 24 ]. However, no differences have been detected in outpatients who are considered less severely ill[ 18 , 20 ]. In most cases, TCAs should generally be reserved for situations when first-line drug treatments have failed[ 25 ].

In December 1987, a series of clinical studies confirmed that an SSRI called fluoxetine was as effective as TCAs for treating depression while causing fewer adverse effects[ 26 ]. After being released onto the market, its use expanded more quickly than that of any other psychotropic in history. In 1994, it was the second-best-selling drug in the world[ 7 ].

Currently available SSRIs include fluoxetine, sertraline, paroxetine, fluvoxamine, citalopram, and escitalopram. They have elicited different tolerance rates and side effects-mostly sexual and digestive (nausea and loss of appetite), as well as irritability, anxiety, insomnia, and headaches[ 27 ]. Nevertheless, SSRIs have a good tolerability profile[ 28 ].

In most systematic reviews and meta-analyses, SSRIs have demonstrated comparable efficacy to TCAs[ 18 , 19 , 29 ], and there is no significant evidence indicating the superiority of any other class or agent over SSRIs[ 29 - 31 ]. Furthermore, studies show no differences in efficacy among individual SSRIs[ 29 , 31 - 34 ]. Therefore, most guidelines currently recommend SSRIs as the first-line treatment for patients with major depression[ 25 ].

Norepinephrine reuptake inhibitors

Other monoamine (norepinephrine, serotonin, and dopamine) neurotransmitter reuptake inhibitors called SNRIs emerged during the 1990s to protect patients against the adverse effects of SSRIs[ 35 ]. Currently available SNRIs are venlafaxine, desvenlafaxine (the principal metabolite of venlafaxine), and duloxetine. The extended-release form of venlafaxine is the most commonly used drug in this class. Clinical guidelines commonly recommend prescribing SNRI to patients who do not respond to SSRIs[ 25 ].

In individual studies, venlafaxine and duloxetine are generally considered effective as SSRIs[ 36 ]. Also, venlafaxine’s efficacy is comparable to that of TCAs[ 37 , 38 ].

According to some meta-analyses, reboxetine (a selective noradrenaline reuptake inhibitor) seems less efficacious than SSRIs[ 39 ]. However, these findings could be due to the relatively poor tolerance of reboxetine[ 40 ].

Other antidepressants

Trazodone is the oldest medication of the so-called “other antidepressants” group that is still in wide use[ 41 , 42 ]. It has been shown to be an effective antidepressant in placebo-controlled research. However, in contemporary practice, it is much more likely to be used in low doses as a sedative-hypnotic than as an antidepressant[ 41 , 42 ].

Nefazodone’s structure is analogous to that of trazodone, though it has different pharmacological properties[ 43 ]. Its efficacy and overall tolerability are comparable to those of SSRIs, as indicated by comparative trials[ 43 ]. However, its use is associated with rare (but fatal) cases of clinical idiosyncratic hepatotoxicity[ 44 ].

Bupropion’s mechanism of action remains unclear, though it is classified as a norepinephrine and dopamine reuptake inhibitor[ 45 ]. It appears to have a more activating profile than SSRIs that are modestly superior to bupropion in patients with MDD[ 46 ]. However, for individuals with low to moderate levels of anxiety, the efficacy of bupropion in treating MDD is comparable to that of SSRIs[ 46 ]. Moreover, bupropion has a better tolerability profile than SSRIs, with minimal weight gain (or even leading to weight loss)[ 46 ]. In addition, bupropion is more likely than some SSRIs to improve symptoms of fatigue and sleepiness[ 47 ].

Mirtazapine and mianserin are tetracyclic compounds believed to increase the availability of serotonin or norepinephrine (or both), at least initially. Mirtazapine’s ability to antagonize serotoninergic subtypes receptors, <5-HT2A> and <5-HT2C>, could also increase norepinephrine and dopamine release in cortical regions[ 25 ]. Mirtazapine is about as effective as SSRIs[ 48 ].

Recently, drugs have been developed that block serotonin reuptake while affecting a variety of 5-HT receptor subtypes. The advantages of these agents ( e.g. , vilazodone and vortioxetine) over SSRIs are not fully clear. However, they appear to produce less sexual dysfunction and, in the specific case of vortioxetine, have particular benefits in depression-related cognitive impairment[ 49 ]. Indeed, vortioxetine is a very recent antidepressant with a multimodal mechanism that is thought to have a high affinity for serotonin transporters and 5-HT3, 5HT1A, 5HT7 receptors. Such a specific profile seems to indicate a level of efficacy to other antidepressants with a specific action on cognitive impairments[ 50 , 51 ].

In conclusion, no significant differences have been found between different classes of antidepressants in terms of their efficacy[ 52 ], though some drugs show some weak-to-moderate evidence indicating they are more effective than some other drugs[ 53 ]. Concerning the acceptability of these drugs, citalopram, escitalopram, fluoxetine, sertraline, and vortioxetine have been deemed more tolerable than other antidepressants, whereas amitriptyline, clomipramine, duloxetine, fluvoxamine, trazodone, and venlafaxine had the highest dropout rates[ 53 ] because of their more frequent and severe side effects. Nausea and vomiting were the most common reasons for treatment discontinuation; sexual dysfunction, sedation, priapism, and cardiotoxicity were also reported[ 31 , 41 ].

Ketamine and related molecules

In intravenous sub-anesthetic doses, ketamine has very quick effects on resistant unipolar (and, possibly, bipolar) depression and acute suicidal ideation[ 54 , 55 ]. The antidepressant effect of ketamine can persist for several days but eventually wanes. A few reports are have cited oral and intranasal formulations of ketamine for treatment-resistant depression[ 56 , 57 ], but there is still no data about the potential link between the onset of action and the route of administration.

Common adverse effects of ketamine include dizziness, neurotoxicity, cognitive dysfunction, blurred vision, psychosis, dissociation, urological dysfunction, restlessness, headache, nausea, vomiting, and cardiovascular symptoms[ 58 ]. Such adverse effects tend to be brief in acute, low-dose treatments[ 36 ], whereas prolonged exposure may predispose patients to neurotoxicity and drug dependence[ 56 ]. Lastly, since ketamine is associated with a higher risk of drug abuse and addiction, it cannot be recommended in daily clinical practice[ 59 , 60 ].

Ketamine is not a miracle drug, and many important factors still need to be defined, such as the most effective dose and the optimal administration route[ 61 , 62 ]. The current lack of guidelines about the therapeutic monitoring of ketamine treatment for depression further complicates the expanding use of this treatment[ 56 ]. Even though ketamine might never reach the market, it has stimulated research in the neurobiology of depression, including studies on potential fast and long-lasting antidepressants.

Ketamine has an active metabolite (hydroxynorketamine) that can produce rapid and sustained glutamatergic stimulation. It also seems to be free of many of the safety problems associated with ketamine and, thus, should be studied.

Research on the S-enantiomer of ketamine (S-ketamine, or esketamine, especially intranasal) could also be valuable, as it has a 3 to 4 times greater affinity than ketamine for the N-methyl-D-aspartate (NMDA) receptor[ 40 ]. It was approved by the United States Food and Drug Administration in March 2019 for treatment-resistant depression. However, current knowledge about the effects of prolonged esketamine therapy is still preliminary. In addition, regarding the potential risk of abuse, esketamine use must be carefully monitored[ 63 - 65 ].

Other glutamate receptor modulators have been evaluated in small studies as monotherapy agents or as adjuncts to other antidepressants. Examples include noncompetitive NMDA receptor antagonists (memantine, dextromethorphan/quinidi-ne, dextromethorphan/bupropion, and lanicemine), NR2B subunit-specific NMDA receptor antagonists (traxoprodil), NMDA receptor glycine site partial agonists (D-cycloserine, rapastinel), and metabotropic glutamate receptor antagonists (basimglurant, declogurant)[ 66 - 68 ] (Table ​ (Table1). 1 ).

Main classes of antidepressants with their date of approval, contributions, and disadvantages

NMDA: N-methyl-D-aspartate; SSRI: DSelective serotonin reuptake inhibitors; MDD: Major depressive disorder; MAOI: Monoamine oxidase inhibitor.

Perspectives

A purely neurotransmitter-based explanation for antidepressant drug action-especially serotonin-inhibiting drugs-is challenged by the significant percentage of patients who never achieve full remission[ 6 ] and the delayed clinical onset, which varies from two to four weeks. Moreover, studies show an acute increase in monoamines in the synaptic cleft immediately following treatment[ 69 ], even when the depletion of tryptophan (serotonin’s precursor) does not induce depressive-like behavior in healthy humans[ 70 , 71 ].

This finding shows that research on the pharmacological options for treating depression must go beyond monoaminergic neurotransmission systems. Research on the development of new antidepressants should explore several mechanisms of action on several types of receptors: Antagonism, inhibition of the reuptake of neurotransmitters, and modulators of glutamate receptors, as well as interactions with α-amino-3-acid receptors, hydroxy-5-methyl-4-isoxazolepropionic, brain-derived neurotrophic factor, tyrosine kinase B receptor (the mechanistic target of rapamycin), and glycogen synthase kinase-3[ 72 ].

Identifying the cellular targets of rapid-acting agents like ketamine could help practitioners develop more effective antidepressant molecules by revealing other receptors involved in gamma-aminobutyric acid regulation and glutamate transmission[ 73 ].

PSYCHOTHERAPY

Psychotherapeutic interventions are widely used to treat and prevent most psychiatric disorders. Such interventions are common in cases of depression, psychosocial difficulties, interpersonal problems, and intra-psychic conflicts. The specific psychotherapy approach chosen for any given case depends on the patient’s preference, as well as on the clinician’s background and availability[ 74 ] . Psychotherapy for patients with depression strengthens the therapeutic alliance and enables the patient to monitor their mood, improve their functioning, understand their symptoms better, and master the practical tools they need to cope with stressful events[ 75 ]. The following subsections briefly describe psychotherapeutic interventions that have been designed specifically for patients with depression.

Overview of psychotherapy in depression

Depression-focused psychotherapy is typically considered the initial treatment method for mild to moderate MDD. Based on significant clinical evidence, two specific psychotherapeutic methods are recommended: Cognitive-behavioral therapy (CBT) and interpersonal therapy (IPT). Supportive therapy (ST) and psychoeducational intervention (PEI) have also been recommended, those the evidence supporting these methods s not as strong. In more cases of severe depression, ST and PEI are used only to augment pharmacological treatments.

After remission, CBT, PEI, and mindfulness-based cognitive therapy (MBCT) are proposed to maintain and prevent depression. However, when psychotherapy has been effective during the initial phases of a depressive episode, it should be continued to maintain remission and prevent relapses while reducing the frequency of sessions[ 25 , 75 , 76 ].

Specific and intensive psychotherapeutic support is recommended for patients with chronic depression because of high rates of comorbidity with personality disorders, early trauma, and attachment deficits. The European Psychiatric Association recommends using the Cognitive Behavioral Analysis System of Psychotherapy (CBASP) for treating chronic depression and utilizing specific approaches suited to each patient’s preferences[ 77 ]. All these therapeutic options are summarized in Figure ​ Figure1 1 .

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Overview of psychotherapy in different clinical situations of depression. MDD: Major depressive disorder; CBT: Cognitive-behavioral therapy; IPT: Interpersonal therapy; ST: Supportive therapy; PEI: Psycho-educational intervention; MBCT: Mindfulness based cognitive therapy; SIPS: Specific and intensive psychotherapeutic support; CBASP: Cognitive Behavioral Analysis System of Psychotherapy.

Structured psychotherapies

Cognitive and behavioral therapies: Based on robust evidence, CBT is one of the most well-documented and validated psychotherapeutic methods available. Interventional strategies are based on modifying dysfunctional behaviors and cognitions[ 77 ]. CBT targets depressed patients’ irrational beliefs and distorted cognitions that perpetuate depressive symptoms by challenging and reversing them[ 3 ]. Thus, CBT is a well-known effective treatment method for MDD[ 78 ] and has been recommended in most guidelines as a first-line treatment[ 79 - 81 ].

However, the effectiveness of CBT depends on patient’s capacity to observe and change their own beliefs and behaviors. Some simple techniques were developed to overcome this issue, especially in primary care management. Behavioral activation is one such technique, consisting of integrating pleasant activities into daily life to increase the number and intensity of the positive interactions that the patient has with their environment[ 82 , 83 ].

Acceptance and commitment therapy is another form of CBT. This type of therapy, which is based on functional contextualism, can help patients accept and adjusting to persistent problems. It appears to be effective in reducing depressive symptoms and preventing relapses[ 77 , 84 ].

Another form of CBT is computerized CBT (CCBT), implemented via a computer with a CD-ROM, DVD, or online CCBT, allowing patients to benefit from this therapy under conditions of reduced mobility, remoteness, confinement, or quarantine[ 79 ] .

CCBT and guided bibliotherapy based on CBT could be considered for self-motivated patients with mild to moderate major depression or as a complementary treatment to pharmacotherapy[ 25 ]. CBT is also recommended for patients with resistant depression in combination with antidepressants[ 85 ].

Schema therapy is another CBT-derived therapy that can be used in patients who have failed classical CBT, like patients with personality disorder comorbidity. Schema therapy is about as effective as CBT for treating depression[ 86 ]. In adolescent patients with depression, CBT is also a recommended option with plenty of evidence from multiple trials. Meanwhile, it remains the first-line treatment in children despite mixed findings across trials[ 87 ] . CBT is also a promising option for elderly depressed patients, though substantial evidence is still lacking because of the limited data on the subject[ 88 ] .

IPT: The goal of IPT is to identify the triggers of depressive symptoms or episodes. These triggers may include losses, social isolation, or difficulties in social interactions. The role of the intervention is to facilitate mourning (in the case of bereavement), help the patient recognize their own affect, and resolve social interaction dysfunction by building their social skills and social supports[ 89 ]. IPT, like CBT, is a first-line treatment for mild to moderate major depressive episodes in adults; it is also a well-established intervention for adolescents with depression[ 25 ] .

Problem-solving therapy: The problem-solving therapy (PST) approach combines cognitive and interpersonal elements, focusing on negative assessments of situations and problem-solving strategies. PST has been used in different clinical situations, like preventing depression among the elderly and treating patients with mild depressive symptoms, especially in primary care. Despite its small effect sizes, PST is comparable to other psychotherapeutic methods used to treat depression[ 88 , 90 ].

Marital and family therapy: Marital and family therapy (MFT) is effective in treating some aspects of depression. Family therapy has also been used to treat severe forms of depression associated with medications and hospitalization[ 91 ]. Marital and family problems can make people more vulnerable to depression, and MFT addresses these issues[ 92 ]. Marital therapy includes both members of the couple, as depression is considered in an interpersonal context in such cases. Some of the goals of this therapy are to facilitate communication and resolve different types of marital conflict. Family therapy uses similar principles as other forms of therapy while involving all family members and considering depression within the context of pathological family dynamics[ 93 ].

ST: Although ST is not as well-structured or well-evaluated as CBT or IPT, it is still commonly used to support depressed patients. In addition to sympathetic listening and expressing concern for the patient’s problems, ST requires emotionally attuned listening, empathic paraphrasing, explaining the nature of the patient’s suffering, and reassuring and encouraging them. These practices allow the patient to ventilate and accept their feelings, increase their self-esteem, and enhance their adaptive coping skills[ 94 ].

Psychodynamic therapy: Psychodynamic therapy encompasses a range of brief to long-term psychological interventions derived from psychoanalytic theories. This type of therapy focuses on intrapsychic conflicts related to shame, repressed impulses, problems in early childhood with one’s emotional caretakers that lead to low self-esteem and poor emotional self-regulation[ 93 , 95 ]. Psychodynamic therapy’s efficacy in the acute phase of MDD is well-established compared to other forms of psychotherapy.

Group therapy: The application of group therapy (GT) to MDD remains limited. Some data support the efficacy of specific types of GT inspired by CBT and IPT[ 96 - 98 ]. Group CBT for patients with subthreshold depression is an effective post-depressive-symptomatology treatment but not during the follow-up period[ 99 ]. Supportive GT and group CBT reduce depressive symptoms[ 96 ], especially in patients with common comorbid conditions[ 100 ]. However, studies are still lacking in this domain.

MBCT: MBCT is a relatively recent technique that combines elements of CBT with mindfulness-based stress reduction[ 101 ]. Studies have shown that eight weeks of MBCT treatment during remission reduces relapse. Thus, it is a potential alternative to reduce, or even stop, antidepressant treatment without increasing the risk of depressive recurrence, especially for patients at a high risk of relapse ( i.e. , patients with more than two previous episodes and patients who have experienced childhood abuse or trauma)[ 102 ].

Other psycho-interventions

Psycho-education: This type of intervention educates depressed patients and (with their permission) family members involved in the patient’s life about depression symptoms and management. This education should be provided in a language that the patient understands. Issues such as misperceptions about medication, treatment duration, the risk of relapse, and prodromes of depression should be addressed. Moreover, patients should be encouraged to maintain healthy lifestyles and enhance their social skills to prevent depression and boost their overall mental health. Many studies have highlighted the role of psycho-education in improving the clinical course, treatment adherence, and psychosocial functioning in patients with depression[ 103 ].

Physical exercise: Most guidelines for treating depression, including the National Institute for Health and Care Excellence, the American Psychiatric Association, and the Royal Australian and New Zealand College of Psychiatrists, recommend that depressed patients perform regular physical activity to alleviate symptoms and prevent relapses[ 104 ] . Exercise also promotes improvements in one’s quality of life in general[ 105 ] . However, exercise is considered an adjunct to other anti-depressive treatments[ 25 ] .

Although psychotherapy is effective for treating depression and improving patients’ quality of life, its direct actions against depressive symptoms are not fully understood[ 106 ]. Identifying factors ( e.g. , interpersonal variables) linked to treatment responses can help therapists choose the right therapeutic strategy for each patient and guide research to modify existing therapies and develop new ones[ 107 ].

Since depression is a primary care problematic, simplifying psychotherapy procedures will increase the use of psychological interventions for depression, especially in general practice. Brief forms (six to eight sessions) of CBT and PST have already shown their effectiveness for treating depression[ 108 ]. Nevertheless, simpler solutions must be made available to practitioners to help them manage and prevent depression.

SOMATIC TREATMENTS

In many situations, depression can also be managed via somatic treatments. ECT is the most well-known treatment for resistant depression, and solid evidence supports its effectiveness and safety. In recent decades, various innovative techniques have been proposed, such as repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), vagus nerve stimulation (VNS), deep brain stimulation (DBS), and magnetic seizure therapy, with varying efficiency levels[ 109 ].

ECT is arguably the most effective treatment modality in psychiatry, and its superiority over pharmacotherapy for major unipolar depression is widely supported[ 110 ]. ECT reduces the number of hospital readmissions and lightens the burden of depression, leading to a better quality of life[ 111 , 112 ].

Moreover, ECT is considered safe[ 113 ]. Advances in anesthesia and ECT techniques have decreased complications related to ECT while also improving cognitive outcomes and patient satisfaction.

However, the stigma surrounding ECT limits its use. Most misconceptions date back to early ECT techniques (when it was performed without muscle relaxants or anesthesia). Nevertheless, some people still consider ECT as the last option for treating depression, even though most studies indicate that ECT is more beneficial in patients with fewer pharmacological treatments[ 114 - 116 ].

ECT is typically recommended for patients with severe and psychotic depression, a high risk of suicide, or Parkinson’s disease, as well as pregnant patients[ 117 - 119 ]. The maintenance ECT also appears to prevent relapses[ 120 ]. The current practice of ECT continues to improve as protocols become more advanced, mainly owing to bioinformatics, and as more research is carried out in this domain[ 121 - 125 ].

This method, which is a type of biological stimulation that affects brain metabolism and neuronal electrical activity, has been widely used in research on depression[ 126 ]. Recent literature shows a significant difference between rTMS and fictitious stimulation regarding its improvements in depressive symptoms[ 127 ]. Preliminary research has revealed synergistic ( e.g. , rTMS/quetiapine) and antagonizing ( e.g. , rTMS/cannabinoid receptor (CB1) antagonist) interactions between neuro-modulation and pharmacotherapy[ 128 ]. Treatments combining rTMS and antidepressants are significantly more effective than placebo conditions, with mild side effects and good acceptability[ 129 ]. Although these results are encouraging, they remain inconsistent due to differences in rTMS treatment frequencies, parameters, and stimulation sites[ 129 ]. Therefore, clinical trials with large sample sizes are needed to specify which factors promote favorable therapeutic responses. Also, additional preclinical research should investigate the synergistic effects of other pharmacological molecules and guide integrated approaches (rTMS plus pharmacotherapy).

This technique delivers weak currents to the brain via electrodes placed on the scalp[ 130 ]. It is easy to use, safe, and tolerable[ 131 ]. The tDCS technique significantly outperforms the simulator in terms of the rate of response and remission[ 132 ]. However, its effect remains lower than that of antidepressants[ 133 ] and rTMS[ 134 ]. It can be used as a complementary intervention or as monotherapy to reduce depressive symptoms in unipolar or bipolar depression patients[ 135 ]. The antidepressant effects of tDCS may involve long-term neuroplastic changes that continue to occur even after the acute phase of treatment, which explains its delayed efficacy[ 135 ].

Recently, neurophysiological studies have shown that the clinical effects of tDCS do not have a direct linear relationship with the dose of stimulation[ 136 ]. tDCS, as a relatively simple and portable technology, is well-suited for remote supervised treatment and assessment at home, thus facilitating long treatment durations[ 136 ].

Since the optimal clinical effects of tDCS are delayed, future clinical trials should use longer evaluation periods and aim to identify responsive patients using algorithms[ 137 ].

VNS is a therapeutic method that has been used for the last sixteen years to treat resistant unilateral or bipolar depression. However, despite several clinical studies attesting to its favorable benefit-risk ratio and its approval by the Food Drug Administration in 2005, it is not used very often[ 138 ].

VNS involves the implantation of a pacemaker under the collarbone that is connected to an electrode surrounding the left vagus nerve. The left vagus nerve is preferred because it exposes the patient to fewer potential adverse cardiac effects. Indeed, most cardiac afferent fibers originate from the right vagus nerve[ 139 ]. Since the turn of the century, numerous studies have demonstrated the efficacy of VNS in resistant depression[ 140 - 142 ].

However, only one randomized, double-blind, controlled trial comparing VNS with usual medical treatment has been conducted over a short period of 10 wk[ 141 ]. Moreover, the results of this study did not indicate that the combination of VNS with typical medical treatments was better than the typical medical treatment on its own.

However, VNS has demonstrated progressively increasing improvements in depressive symptoms, with significant positive outcomes observed after six to 12 mo; these benefits can last for up to two years[ 143 ].

More long-term studies are needed to fully determine the predictors of the correct response.

According to the literature, DBS of the subgenual cingulate white matter (Brodmann area = BA 25) elicited a clinical response in 60% of resistant depression patients after six months and clinical remission in 35% of patients, with benefits maintained for over 12 mo[ 144 ]. The stimulation of other targets, in particular the nucleus accumbens, to treat resistant depression has gained interest recently. Behavioral effects indicate the quick and favorable impact of stimulation on anhedonia, with significant effects on mood appearing as early as week one after treatment begins[ 145 ].

Magnetic seizure therapy

Magnetic seizure therapy involves inducing a therapeutic seizure by applying magnetic stimulation to the brain while the patient is under anesthesia. This technique is still being investigated as a viable alternative to ECT to treat many psychiatric disorders. Evidence supporting its effectiveness on depressive symptoms continues to grow, and it appears to induce fewer neurocognitive effects than ECT[ 146 , 147 ].

Luxtherapy (phototherapy)

The first description of reduced depression symptoms due to intense light exposure was presented in 1984[ 148 ]. Optimal improvements were obtained with bright light exposure of 2500 Lux for two hours per day, with morning exposure shown to be superior to evening exposure[ 149 ].

A review and meta-analysis[ 150 ] showed that more intense (but shorter) exposures (10000 Lux for half an hour per day or 6000 Lux for 1.5 h per day) have the same efficacy. Importantly, this treatment method is effective both for those with seasonal and non-seasonal depression. Benefits of phototherapy related to sleep deprivation and drug treatments have also been reported[ 151 ].

Neuro-modulation treatments offer a range of treatment options for patients with depression. ECT remains the most documented and effective method in this category[ 151 ]. rTMS is an interesting technique as well, as it offers a well-tolerated profile[ 85 ], while tDCS offers encouraging but varying results that depend on the study’s design and the techniques used[ 130 ].

More investigations are needed to specify which indications are the best for each method according to the clinical and biological profiles of patients. The uses of such methods are expanding, probably, with their efficiency increasing when they are tailored to the patient. Furthermore, somatic interventions for depression need to be regularly assessed and integrated into psychiatrists’ therapeutic arsenals.

Treating depression is still a significant challenge. Finding the best option for each patient is the best way to obtaining short- and long-term effectiveness. The three principal methods available to caregivers are antidepressants, specifically structured psychotherapies, and somatic approaches. Research on depression pharmacotherapy continues to examine new molecules implicated in gamma-aminobutyric acid regulation and glutamate transmission. Also, efforts to personalize and simplify psychotherapeutic interventions are ongoing. Protocols using somatic interventions need to be studied in more depth, and their indications must be specified. ECT is the only somatic treatment with confirmed indications for certain forms of depression. Combinations of medications, psychotherapy, and somatic therapies remain the most effective ways to manage resistant forms of depression.

Conflict-of-interest statement: All authors declare that they have no conflict of interest related to this article.

Manuscript source: Invited manuscript

Peer-review started: March 31, 2021

First decision: June 5, 2021

Article in press: October 11, 2021

Specialty type: Medicine, research and experimental

Country/Territory of origin: Morocco

Peer-review report’s scientific quality classification

Grade A (Excellent): 0

Grade B (Very good): 0

Grade C (Good): 0

Grade D (Fair): D

Grade E (Poor): 0

P-Reviewer: Narumiya K S-Editor: Fan JR L-Editor: A P-Editor: Fan JR

Contributor Information

Rabie Karrouri, Department of Psychiatry, Moulay Ismaïl Military Hospital, Faculty of Medicine and Pharmacy, Sidi Mohamed Ben Abdellah University, Fez 30070, Morocco.

Zakaria Hammani, Department of Psychiatry, Moulay Ismaïl Military Hospital, Faculty of Medicine and Pharmacy, Sidi Mohamed Ben Abdellah University, Fez 30070, Morocco.

Roukaya Benjelloun, Department of Psychiatry, Faculty of Medicine, Mohammed VI University of Health Sciences, Casablanca 20000, Morocco.

Yassine Otheman, Department of Psychiatry, Moulay Ismaïl Military Hospital, Faculty of Medicine and Pharmacy, Sidi Mohamed Ben Abdellah University, Fez 30070, Morocco. [email protected] .

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Psychiatry Online

  • February 01, 2024 | VOL. 181, NO. 2 CURRENT ISSUE pp.83-170
  • January 01, 2024 | VOL. 181, NO. 1 pp.1-82

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The Critical Relationship Between Anxiety and Depression

  • Ned H. Kalin , M.D.

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Anxiety and depressive disorders are among the most common psychiatric illnesses; they are highly comorbid with each other, and together they are considered to belong to the broader category of internalizing disorders. Based on statistics from the Substance Abuse and Mental Health Services Administration, the 12-month prevalence of major depressive disorder in 2017 was estimated to be 7.1% for adults and 13.3% for adolescents ( 1 ). Data for anxiety disorders are less current, but in 2001–2003, their 12-month prevalence was estimated to be 19.1% in adults, and 2001–2004 data estimated that the lifetime prevalence in adolescents was 31.9% ( 2 , 3 ). Both anxiety and depressive disorders are more prevalent in women, with an approximate 2:1 ratio in women compared with men during women’s reproductive years ( 1 , 2 ).

Across all psychiatric disorders, comorbidity is the rule ( 4 ), which is definitely the case for anxiety and depressive disorders, as well as their symptoms. With respect to major depression, a worldwide survey reported that 45.7% of individuals with lifetime major depressive disorder had a lifetime history of one or more anxiety disorder ( 5 ). These disorders also commonly coexist during the same time frame, as 41.6% of individuals with 12-month major depression also had one or more anxiety disorder over the same 12-month period. From the perspective of anxiety disorders, the lifetime comorbidity with depression is estimated to range from 20% to 70% for patients with social anxiety disorder ( 6 ), 50% for patients with panic disorder ( 6 ), 48% for patients with posttraumatic stress disorder (PTSD) ( 7 ), and 43% for patients with generalized anxiety disorder ( 8 ). Data from the well-known Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study demonstrate comorbidity at the symptom level, as 53% of the patients with major depression had significant anxiety and were considered to have an anxious depression ( 9 ).

Anxiety and depressive disorders are moderately heritable (approximately 40%), and evidence suggests shared genetic risk across the internalizing disorders ( 10 ). Among internalizing disorders, the highest level of shared genetic risk appears to be between major depressive disorder and generalized anxiety disorder. Neuroticism is a personality trait or temperamental characteristic that is associated with the development of both anxiety and depression, and the genetic risk for developing neuroticism also appears to be shared with that of the internalizing disorders ( 11 ). Common nongenetic risk factors associated with the development of anxiety and depression include earlier life adversity, such as trauma or neglect, as well as parenting style and current stress exposure. At the level of neural circuits, alterations in prefrontal-limbic pathways that mediate emotion regulatory processes are common to anxiety and depressive disorders ( 12 , 13 ). These findings are consistent with meta-analyses that reveal shared structural and functional brain alterations across various psychiatric illnesses, including anxiety and major depression, in circuits involving emotion regulation ( 13 ), executive function ( 14 ), and cognitive control ( 15 ).

Anxiety disorders and major depression occur during development, with anxiety disorders commonly beginning during preadolescence and early adolescence and major depression tending to emerge during adolescence and early to mid-adulthood ( 16 – 18 ). In relation to the evolution of their comorbidity, studies demonstrate that anxiety disorders generally precede the presentation of major depressive disorder ( 17 ). A European community-based study revealed, beginning at age 15, the developmental relation between comorbid anxiety and major depression by specifically focusing on social phobia (based on DSM-IV criteria) and then asking the question regarding concurrent major depressive disorder ( 18 ). The findings revealed a 19% concurrent comorbidity between these disorders, and in 65% of the cases, social phobia preceded major depressive disorder by at least 2 years. In addition, initial presentation with social phobia was associated with a 5.7-fold increased risk of developing major depressive disorder. These associations between anxiety and depression can be traced back even earlier in life. For example, childhood behavioral inhibition in response to novelty or strangers, or an extreme anxious temperament, is associated with a three- to fourfold increase in the likelihood of developing social anxiety disorder, which in turn is associated with an increased risk to develop major depressive disorder and substance abuse ( 19 ).

It is important to emphasize that the presence of comor‐bid anxiety symptoms and disorders matters in relation to treatment. Across psychiatric disorders, the presence of significant anxiety symptoms generally predicts worse outcomes, and this has been well demonstrated for depression. In the STAR*D study, patients with anxious major depressive disorder were more likely to be severely depressed and to have more suicidal ideation ( 9 ). This is consistent with the study by Kessler and colleagues ( 5 ), in which patients with anxious major depressive disorder, compared with patients with nonanxious major depressive disorder, were found to have more severe role impairment and more suicidal ideation. Data from level 1 of the STAR*D study (citalopram treatment) nicely illustrate the impact of comorbid anxiety symptoms on treatment. Compared with patients with nonanxious major depressive disorder, those 53% of patients with an anxious depression were less likely to remit and also had a greater side effect burden ( 20 ). Other data examining patients with major depressive disorder and comorbid anxiety disorders support the greater difficulty and challenge in treating patients with these comorbidities ( 21 ).

This issue of the Journal presents new findings relevant to the issues discussed above in relation to understanding and treating anxiety and depressive disorders. Drs. Conor Liston and Timothy Spellman, from Weill Cornell Medicine, provide an overview for this issue ( 22 ) that is focused on understanding mechanisms at the neural circuit level that underlie the pathophysiology of depression. Their piece nicely integrates human neuroimaging studies with complementary data from animal models that allow for the manipulation of selective circuits to test hypotheses generated from the human data. Also included in this issue is a review of the data addressing the reemergence of the use of psychedelic drugs in psychiatry, particularly for the treatment of depression, anxiety, and PTSD ( 23 ). This timely piece, authored by Dr. Collin Reiff along with a subgroup from the APA Council of Research, provides the current state of evidence supporting the further exploration of these interventions. Dr. Alan Schatzberg, from Stanford University, contributes an editorial in which he comments on where the field is in relation to clinical trials with psychedelics and to some of the difficulties, such as adequate blinding, in reliably studying the efficacy of these drugs ( 24 ).

In an article by McTeague et al. ( 25 ), the authors use meta-analytic strategies to understand the neural alterations that are related to aberrant emotion processing that are shared across psychiatric disorders. Findings support alterations in the salience, reward, and lateral orbital nonreward networks as common across disorders, including anxiety and depressive disorders. These findings add to the growing body of work that supports the concept that there are common underlying factors across all types of psychopathology that include internalizing, externalizing, and thought disorder dimensions ( 26 ). Dr. Deanna Barch, from Washington University in St. Louis, writes an editorial commenting on these findings and, importantly, discusses criteria that should be met when we consider whether the findings are actually transdiagnostic ( 27 ).

Another article, from Gray and colleagues ( 28 ), addresses whether there is a convergence of findings, specifically in major depression, when examining data from different structural and functional neuroimaging modalities. The authors report that, consistent with what we know about regions involved in emotion processing, the subgenual anterior cingulate cortex, hippocampus, and amygdala were among the regions that showed convergence across multimodal imaging modalities.

In relation to treatment and building on our understanding of neural circuit alterations, Siddiqi et al. ( 29 ) present data suggesting that transcranial magnetic stimulation (TMS) targeting can be linked to symptom-specific treatments. Their findings identify different TMS targets in the left dorsolateral prefrontal cortex that modulate different downstream networks. The modulation of these different networks appears to be associated with a reduction in different types of symptoms. In an editorial, Drs. Sean Nestor and Daniel Blumberger, from the University of Toronto ( 30 ), comment on the novel approach used in this study to link the TMS-related engagement of circuits with symptom improvement. They also provide a perspective on how we can view these and other circuit-based findings in relation to conceptualizing personalized treatment approaches.

Kendler et al. ( 31 ), in this issue, contribute an article that demonstrates the important role of the rearing environment in the risk to develop major depression. Using a unique design from a Swedish sample, the analytic strategy involves comparing outcomes from high-risk full sibships and high-risk half sibships where at least one of the siblings was home reared and one was adopted out of the home. The findings support the importance of the quality of the rearing environment as well as the presence of parental depression in mitigating or enhancing the likelihood of developing major depression. In an accompanying editorial ( 32 ), Dr. Myrna Weissman, from Columbia University, reviews the methods and findings of the Kendler et al. article and also emphasizes the critical significance of the early nurturing environment in relation to general health.

This issue concludes with an intriguing article on anxiety disorders, by Gold and colleagues ( 33 ), that demonstrates neural alterations during extinction recall that differ in children relative to adults. With increasing age, and in relation to fear and safety cues, nonanxious adults demonstrated greater connectivity between the amygdala and the ventromedial prefrontal cortex compared with anxious adults, as the cues were being perceived as safer. In contrast, neural differences between anxious and nonanxious youths were more robust when rating the memory of faces that were associated with threat. Specifically, these differences were observed in the activation of the inferior temporal cortex. In their editorial ( 34 ), Dr. Dylan Gee and Sahana Kribakaran, from Yale University, emphasize the importance of developmental work in relation to understanding anxiety disorders, place these findings into the context of other work, and suggest the possibility that these and other data point to neuroscientifically informed age-specific interventions.

Taken together, the papers in this issue of the Journal present new findings that shed light onto alterations in neural function that underlie major depressive disorder and anxiety disorders. It is important to remember that these disorders are highly comorbid and that their symptoms are frequently not separable. The papers in this issue also provide a developmental perspective emphasizing the importance of early rearing in the risk to develop depression and age-related findings important for understanding threat processing in patients with anxiety disorders. From a treatment perspective, the papers introduce data supporting more selective prefrontal cortical TMS targeting in relation to different symptoms, address the potential and drawbacks for considering the future use of psychedelics in our treatments, and present new ideas supporting age-specific interventions for youths and adults with anxiety disorders.

Disclosures of Editors’ financial relationships appear in the April 2020 issue of the Journal .

1 Substance Abuse and Mental Health Services Administration (SAMHSA): Key substance use and mental health indicators in the United States: results from the 2017 National Survey on Drug Use and Health (HHS Publication No. SMA 18-5068, NSDUH Series H-53). Rockville, Md, Center for Behavioral Health Statistics and Quality, SAMHSA, 2018. https://www.samhsa.gov/data/sites/default/files/cbhsq-reports/NSDUHFFR2017/NSDUHFFR2017.htm Google Scholar

2 Kessler RC, Chiu WT, Demler O, et al. : Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication . Arch Gen Psychiatry 2005 ; 62:617–627, correction, 62:709 Crossref , Medline ,  Google Scholar

3 Merikangas KR, He JP, Burstein M, et al. : Lifetime prevalence of mental disorders in U.S. adolescents: results from the National Comorbidity Survey Replication–Adolescent Supplement (NCS-A) . J Am Acad Child Adolesc Psychiatry 2010 ; 49:980–989 Crossref , Medline ,  Google Scholar

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6 Dunner DL : Management of anxiety disorders: the added challenge of comorbidity . Depress Anxiety 2001 ; 13:57–71 Crossref , Medline ,  Google Scholar

7 Kessler RC, Sonnega A, Bromet E, et al. : Posttraumatic stress disorder in the National Comorbidity Survey . Arch Gen Psychiatry 1995 ; 52:1048–1060 Crossref , Medline ,  Google Scholar

8 Brawman-Mintzer O, Lydiard RB, Emmanuel N, et al. : Psychiatric comorbidity in patients with generalized anxiety disorder . Am J Psychiatry 1993 ; 150:1216–1218 Link ,  Google Scholar

9 Fava M, Alpert JE, Carmin CN, et al. : Clinical correlates and symptom patterns of anxious depression among patients with major depressive disorder in STAR*D . Psychol Med 2004 ; 34:1299–1308 Crossref , Medline ,  Google Scholar

10 Hettema JM : What is the genetic relationship between anxiety and depression? Am J Med Genet C Semin Med Genet 2008 ; 148C:140–146 Crossref , Medline ,  Google Scholar

11 Hettema JM, Neale MC, Myers JM, et al. : A population-based twin study of the relationship between neuroticism and internalizing disorders . Am J Psychiatry 2006 ; 163:857–864 Link ,  Google Scholar

12 Kovner R, Oler JA, Kalin NH : Cortico-limbic interactions mediate adaptive and maladaptive responses relevant to psychopathology . Am J Psychiatry 2019 ; 176:987–999 Link ,  Google Scholar

13 Etkin A, Schatzberg AF : Common abnormalities and disorder-specific compensation during implicit regulation of emotional processing in generalized anxiety and major depressive disorders . Am J Psychiatry 2011 ; 168:968–978 Link ,  Google Scholar

14 Goodkind M, Eickhoff SB, Oathes DJ, et al. : Identification of a common neurobiological substrate for mental illness . JAMA Psychiatry 2015 ; 72:305–315 Crossref , Medline ,  Google Scholar

15 McTeague LM, Huemer J, Carreon DM, et al. : Identification of common neural circuit disruptions in cognitive control across psychiatric disorders . Am J Psychiatry 2017 ; 174:676–685 Link ,  Google Scholar

16 Beesdo K, Knappe S, Pine DS : Anxiety and anxiety disorders in children and adolescents: developmental issues and implications for DSM-V . Psychiatr Clin North Am 2009 ; 32:483–524 Crossref , Medline ,  Google Scholar

17 Kessler RC, Wang PS : The descriptive epidemiology of commonly occurring mental disorders in the United States . Annu Rev Public Health 2008 ; 29:115–129 Crossref , Medline ,  Google Scholar

18 Ohayon MM, Schatzberg AF : Social phobia and depression: prevalence and comorbidity . J Psychosom Res 2010 ; 68:235–243 Crossref , Medline ,  Google Scholar

19 Clauss JA, Blackford JU : Behavioral inhibition and risk for developing social anxiety disorder: a meta-analytic study . J Am Acad Child Adolesc Psychiatry 2012 ; 51:1066–1075 Crossref , Medline ,  Google Scholar

20 Fava M, Rush AJ, Alpert JE, et al. : Difference in treatment outcome in outpatients with anxious versus nonanxious depression: a STAR*D report . Am J Psychiatry 2008 ; 165:342–351 Link ,  Google Scholar

21 Dold M, Bartova L, Souery D, et al. : Clinical characteristics and treatment outcomes of patients with major depressive disorder and comorbid anxiety disorders: results from a European multicenter study . J Psychiatr Res 2017 ; 91:1–13 Crossref , Medline ,  Google Scholar

22 Spellman T, Liston C : Toward circuit mechanisms of pathophysiology in depression . Am J Psychiatry 2020 ; 177:381–390 Link ,  Google Scholar

23 Reiff CM, Richman EE, Nemeroff CB, et al. : Psychedelics and psychedelic-assisted psychotherapy . Am J Psychiatry 2020 ; 177:391–410 Link ,  Google Scholar

24 Schatzberg AF : Some comments on psychedelic research (editorial). Am J Psychiatry 2020 ; 177:368–369 Link ,  Google Scholar

25 McTeague LM, Rosenberg BM, Lopez JW, et al. : Identification of common neural circuit disruptions in emotional processing across psychiatric disorders . Am J Psychiatry 2020 ; 177:411–421 Link ,  Google Scholar

26 Caspi A, Moffitt TE : All for one and one for all: mental disorders in one dimension . Am J Psychiatry 2018 ; 175:831–844 Link ,  Google Scholar

27 Barch DM : What does it mean to be transdiagnostic and how would we know? (editorial). Am J Psychiatry 2020 ; 177:370–372 Abstract ,  Google Scholar

28 Gray JP, Müller VI, Eickhoff SB, et al. : Multimodal abnormalities of brain structure and function in major depressive disorder: a meta-analysis of neuroimaging studies . Am J Psychiatry 2020 ; 177:422–434 Link ,  Google Scholar

29 Siddiqi SH, Taylor SF, Cooke D, et al. : Distinct symptom-specific treatment targets for circuit-based neuromodulation . Am J Psychiatry 2020 ; 177:435–446 Link ,  Google Scholar

30 Nestor SM, Blumberger DM : Mapping symptom clusters to circuits: toward personalizing TMS targets to improve treatment outcomes in depression (editorial). Am J Psychiatry 2020 ; 177:373–375 Abstract ,  Google Scholar

31 Kendler KS, Ohlsson H, Sundquist J, et al. : The rearing environment and risk for major depression: a Swedish national high-risk home-reared and adopted-away co-sibling control study . Am J Psychiatry 2020 ; 177:447–453 Abstract ,  Google Scholar

32 Weissman MM : Is depression nature or nurture? Yes (editorial). Am J Psychiatry 2020 ; 177:376–377 Abstract ,  Google Scholar

33 Gold AL, Abend R, Britton JC, et al. : Age differences in the neural correlates of anxiety disorders: an fMRI study of response to learned threat . Am J Psychiatry 2020 ; 177:454–463 Link ,  Google Scholar

34 Gee DG, Kribakaran S : Developmental differences in neural responding to threat and safety: implications for treating youths with anxiety (editorial). Am J Psychiatry 2020 ; 177:378–380 Abstract ,  Google Scholar

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The Devastating Ways Depression and Anxiety Impact the Body

Mind and body form a two-way street.

research articles in depression

By Jane E. Brody

It’s no surprise that when a person gets a diagnosis of heart disease, cancer or some other life-limiting or life-threatening physical ailment, they become anxious or depressed. But the reverse can also be true: Undue anxiety or depression can foster the development of a serious physical disease, and even impede the ability to withstand or recover from one. The potential consequences are particularly timely, as the ongoing stress and disruptions of the pandemic continue to take a toll on mental health .

The human organism does not recognize the medical profession’s artificial separation of mental and physical ills. Rather, mind and body form a two-way street. What happens inside a person’s head can have damaging effects throughout the body, as well as the other way around. An untreated mental illness can significantly increase the risk of becoming physically ill, and physical disorders may result in behaviors that make mental conditions worse.

In studies that tracked how patients with breast cancer fared, for example, Dr. David Spiegel and his colleagues at Stanford University School of Medicine showed decades ago that women whose depression was easing lived longer than those whose depression was getting worse. His research and other studies have clearly shown that “the brain is intimately connected to the body and the body to the brain,” Dr. Spiegel said in an interview. “The body tends to react to mental stress as if it was a physical stress.”

Despite such evidence, he and other experts say, chronic emotional distress is too often overlooked by doctors. Commonly, a physician will prescribe a therapy for physical ailments like heart disease or diabetes, only to wonder why some patients get worse instead of better.

Many people are reluctant to seek treatment for emotional ills. Some people with anxiety or depression may fear being stigmatized, even if they recognize they have a serious psychological problem. Many attempt to self-treat their emotional distress by adopting behaviors like drinking too much or abusing drugs, which only adds insult to their pre-existing injury.

And sometimes, family and friends inadvertently reinforce a person’s denial of mental distress by labeling it as “that’s just the way he is” and do nothing to encourage them to seek professional help.

How common are anxiety and depression?

Anxiety disorders affect nearly 20 percent of American adults . That means millions are beset by an overabundance of the fight-or-flight response that primes the body for action. When you’re stressed, the brain responds by prompting the release of cortisol, nature’s built-in alarm system. It evolved to help animals facing physical threats by increasing respiration, raising the heart rate and redirecting blood flow from abdominal organs to muscles that assist in confronting or escaping danger.

These protective actions stem from the neurotransmitters epinephrine and norepinephrine, which stimulate the sympathetic nervous system and put the body on high alert. But when they are invoked too often and indiscriminately, the chronic overstimulation can result in all manner of physical ills, including digestive symptoms like indigestion, cramps, diarrhea or constipation, and an increased risk of heart attack or stroke.

Depression, while less common than chronic anxiety, can have even more devastating effects on physical health. While it’s normal to feel depressed from time to time, more than 6 percent of adults have such persistent feelings of depression that it disrupts personal relationships, interferes with work and play, and impairs their ability to cope with the challenges of daily life. Persistent depression can also exacerbate a person’s perception of pain and increase their chances of developing chronic pain.

“Depression diminishes a person’s capacity to analyze and respond rationally to stress,” Dr. Spiegel said. “They end up on a vicious cycle with limited capacity to get out of a negative mental state.”

Potentially making matters worse, undue anxiety and depression often coexist, leaving people vulnerable to a panoply of physical ailments and an inability to adopt and stick with needed therapy.

A study of 1,204 elderly Korean men and women initially evaluated for depression and anxiety found that two years later, these emotional disorders increased their risk of physical disorders and disability. Anxiety alone was linked with heart disease, depression alone was linked with asthma, and the two together were linked with eyesight problems, persistent cough, asthma, hypertension, heart disease and gastrointestinal problems.

Treatment can counter emotional tolls

Although persistent anxiety and depression are highly treatable with medications, cognitive behavioral therapy and talk therapy, without treatment these conditions tend to get worse. According to Dr. John Frownfelter, treatment for any condition works better when doctors understand “the pressures patients face that affect their behavior and result in clinical harm.”

Dr. Frownfelter is an internist and chief medical officer of a start-up called Jvion. The organization uses artificial intelligence to identify not just medical factors but psychological, social and behavioral ones as well that can impact the effectiveness of treatment on patients’ health. Its aim is to foster more holistic approaches to treatment that address the whole patient, body and mind combined.

The analyses used by Jvion, a Hindi word meaning life-giving, could alert a doctor when underlying depression might be hindering the effectiveness of prescribed treatments for another condition. For example, patients being treated for diabetes who are feeling hopeless may fail to improve because they take their prescribed medication only sporadically and don’t follow a proper diet, Dr. Frownfelter said.

“We often talk about depression as a complication of chronic illness,” Dr. Frownfelter wrote in Medpage Today in July . “But what we don’t talk about enough is how depression can lead to chronic disease. Patients with depression may not have the motivation to exercise regularly or cook healthy meals. Many also have trouble getting adequate sleep.”

Some changes to medical care during the pandemic have greatly increased patient access to depression and anxiety treatment. The expansion of telehealth has enabled patients to access treatment by psychotherapists who may be as far as a continent away.

Patients may also be able to treat themselves without the direct help of a therapist. For example, Dr. Spiegel and his co-workers created an app called Reveri that teaches people self-hypnosis techniques designed to help reduce stress and anxiety, improve sleep, reduce pain and suppress or quit smoking.

Improving sleep is especially helpful, Dr. Spiegel said, because “it enhances a person’s ability to regulate the stress response system and not get stuck in a mental rut.” Data demonstrating the effectiveness of the Reveri app has been collected but not yet published, he said.

Jane Brody is the Personal Health columnist, a position she has held since 1976. She has written more than a dozen books including the best sellers “Jane Brody’s Nutrition Book” and “Jane Brody’s Good Food Book.” More about Jane E. Brody

Jane Brody’s Personal Health Advice

After joining the new york times in 1965, she was its personal health columnist from 1976 to 2022. revisit some of her most memorable writing:.

Brody’s first column, on jogging , ran on Nov. 10, 1976. Her last, on Feb. 21. In it, she highlighted the evolution of health advice  throughout her career.

Personal Health has often offered useful advice and a refreshing perspective. Declutter? This is why you must . Cup of coffee? Yes, please.

As a columnist, she has never been afraid to try out, and write about, new things — from intermittent fasting  to knitting groups .

How do you put into words the pain of losing a spouse of 43 years? It is “nothing like losing a parent,” she wrote of her own experience with grieving .

Need advice on aging? She has explored how to do it gracefully ,  building muscle strength  and knee replacements .

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Americans who live alone report depression at higher rates, but social support helps.

Rhitu Chatterjee

research articles in depression

The number of people living alone in the U.S. went from nearly 5 million to about 38 million in a decade. A new study shows those who live alone report depression more than those who live with others. Yana Iskayeva/Getty Images hide caption

The number of people living alone in the U.S. went from nearly 5 million to about 38 million in a decade. A new study shows those who live alone report depression more than those who live with others.

People living alone are more likely to report feeling depressed compared to those living with others, according to a new study by the CDC's National Center for Health Statistics . And that effect is particularly stark for people living alone who say they have little or no social and emotional support.

"The most interesting takeaway from this study was the importance of feeling supported," says social scientist Kasley Killam , who wasn't involved in the new study. "And this is consistent with other evidence showing that social support and emotional support really play a pivotal role in people's overall health and well-being."

The new study comes at a time when the number of single person households in the U.S. has skyrocketed. In the decade from 2012 to 2022, the number of Americans living alone jumped by nearly 5 million to 37.9 million.

The study relies on 2021 data from the annual National Health Interview Survey , which interviews people in a nationally representative sample of households across the country. It found that a little over 6% of those living alone reported feelings of depression, compared to 4% of people living with others.

The good news about the findings, says author Laryssa Mykyta , is that the vast majority of people living alone didn't report adverse mental health symptoms. "Most adults who live alone – 93% – report either no feelings of depression or low feelings of depression," she says.

The survey also asked respondents about the levels of social and emotional support in their lives. "Respondents were asked, 'How often do you get the social and emotional support you need? Would you say always, usually, sometimes, rarely or never?'" says Mykyta.

Those who live alone and receive little or no social and emotional support were far more likely to report feelings of depression compared to people who live with others who also had little or no support. On the other hand, there were no differences in reports of depression between people living alone and those living with others if they had social and emotional support.

That finding is the "most compelling and most interesting," says Mykyta, because it shows the importance of social and emotional support in people's mood and wellbeing.

Social isolation and loneliness are increasingly being recognized as a public health problem. Studies have shown them to be linked to a higher risk of mental and physical illnesses.

How to combat loneliness

How to combat loneliness

"They're associated with a whole host of negative outcomes, including diabetes, depression –like we saw in this study – dementia, heart disease and even mortality," says Killam, who's the author of the upcoming book The Art and Science of Connection . "So they truly are risk factors for people's health and well-being."

In 2023, the U.S. Surgeon General Dr. Vivek Murthy released an advisory to raise awareness about loneliness and social isolation as a public health crisis. Murthy has also penned a book on the topic, titled Together .

In 'Together,' Former Surgeon General Writes About Importance Of Human Connection

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In 'together,' former surgeon general writes about importance of human connection.

"As health care providers, we need to be asking, is there someone there for you?" says psychiatrist Dr. Tom Insel , author of Healing: Our Path from Mental Illness to Mental Health . "And that's different from saying that you're living alone, because a lot of people who live alone have plenty of social support."

Asking that question, he says, will allow healthcare professionals to help address their patients' social isolation.

"You know, we can help people to find community," he says. "We can make sure we can prescribe social interaction. We can prescribe ways for people to actually become more engaged and to get the kind of social-emotional support they need."

Correction Feb. 15, 2024

The audio version of this story and an earlier digital version overstate how quickly the number of single-person households in the U.S. is growing. The number grew by 4.8 million to reach nearly 38 million. It did not jump from 4.8 million to 37.9 million in a decade.

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An Exploratory Study of Students with Depression in Undergraduate Research Experiences

  • Katelyn M. Cooper
  • Logan E. Gin
  • M. Elizabeth Barnes
  • Sara E. Brownell

*Address correspondence to: Katelyn M. Cooper ( E-mail Address: [email protected] ).

Department of Biology, University of Central Florida, Orlando, FL, 32816

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Biology Education Research Lab, Research for Inclusive STEM Education Center, School of Life Sciences, Arizona State University, Tempe, AZ 85281

Depression is a top mental health concern among undergraduates and has been shown to disproportionately affect individuals who are underserved and underrepresented in science. As we aim to create a more inclusive scientific community, we argue that we need to examine the relationship between depression and scientific research. While studies have identified aspects of research that affect graduate student depression, we know of no studies that have explored the relationship between depression and undergraduate research. In this study, we sought to understand how undergraduates’ symptoms of depression affect their research experiences and how research affects undergraduates’ feelings of depression. We interviewed 35 undergraduate researchers majoring in the life sciences from 12 research-intensive public universities across the United States who identify with having depression. Using inductive and deductive coding, we identified that students’ depression affected their motivation and productivity, creativity and risk-taking, engagement and concentration, and self-perception and socializing in undergraduate research experiences. We found that students’ social connections, experiencing failure in research, getting help, receiving feedback, and the demands of research affected students’ depression. Based on this work, we articulate an initial set of evidence-based recommendations for research mentors to consider in promoting an inclusive research experience for students with depression.

INTRODUCTION

Depression is described as a common and serious mood disorder that results in persistent feelings of sadness and hopelessness, as well as a loss of interest in activities that one once enjoyed ( American Psychiatric Association [APA], 2013 ). Additional symptoms of depression include weight changes, difficulty sleeping, loss of energy, difficulty thinking or concentrating, feelings of worthlessness or excessive guilt, and suicidality ( APA, 2013 ). While depression results from a complex interaction of psychological, social, and biological factors ( World Health Organization, 2018 ), studies have shown that increased stress caused by college can be a significant contributor to student depression ( Dyson and Renk, 2006 ).

Depression is one of the top undergraduate mental health concerns, and the rate of depression among undergraduates continues to rise ( Center for Collegiate Mental Health, 2017 ). While we cannot discern whether these increasing rates of depression are due to increased awareness or increased incidence, it is clear that is a serious problem on college campuses. The percent of U.S. college students who self-reported a diagnosis with depression was recently estimated to be about 25% ( American College Health Association, 2019 ). However, higher rates have been reported, with one study estimating that up to 84% of undergraduates experience some level of depression ( Garlow et al. , 2008 ). Depression rates are typically higher among university students compared with the general population, despite being a more socially privileged group ( Ibrahim et al. , 2013 ). Prior studies have found that depression is negatively correlated with overall undergraduate academic performance ( Hysenbegasi et al. , 2005 ; Deroma et al. , 2009 ; American College Health Association, 2019 ). Specifically, diagnosed depression is associated with half a letter grade decrease in students’ grade point average ( Hysenbegasi et al. , 2005 ), and 21.6% of undergraduates reported that depression negatively affected their academic performance within the last year ( American College Health Association, 2019 ). Provided with a list of academic factors that may be affected by depression, students reported that depression contributed to lower exam grades, lower course grades, and not completing or dropping a course.

Students in the natural sciences may be particularly at risk for depression, given that such majors are noted to be particularly stressful due to their competitive nature and course work that is often perceived to “weed students out”( Everson et al. , 1993 ; Strenta et al. , 1994 ; American College Health Association, 2019 ; Seymour and Hunter, 2019 ). Science course instruction has also been described to be boring, repetitive, difficult, and math-intensive; these factors can create an environment that can trigger depression ( Seymour and Hewitt, 1997 ; Osborne and Collins, 2001 ; Armbruster et al ., 2009 ; Ceci and Williams, 2010 ). What also distinguishes science degree programs from other degree programs is that, increasingly, undergraduate research experiences are being proposed as an essential element of a science degree ( American Association for the Advancement of Science, 2011 ; President’s Council of Advisors on Science and Technology, 2012 ; National Academies of Sciences, Engineering, and Medicine [NASEM], 2017 ). However, there is some evidence that undergraduate research experiences can add to the stress of college for some students ( Cooper et al. , 2019c ). Students can garner multiple benefits from undergraduate research, including enhanced abilities to think critically ( Ishiyama, 2002 ; Bauer and Bennett, 2003 ; Brownell et al. , 2015 ), improved student learning ( Rauckhorst et al. , 2001 ; Brownell et al. , 2015 ), and increased student persistence in undergraduate science degree programs ( Jones et al. , 2010 ; Hernandez et al. , 2018 ). Notably, undergraduate research experiences are increasingly becoming a prerequisite for entry into medical and graduate programs in science, particularly elite programs ( Cooper et al. , 2019d ). Although some research experiences are embedded into formal lab courses as course-based undergraduate research experiences (CUREs; Auchincloss et al. , 2014 ; Brownell and Kloser, 2015 ), the majority likely entail working with faculty in their research labs. These undergraduate research experiences in faculty labs are often added on top of a student’s normal course work, so they essentially become an extracurricular activity that they have to juggle with course work, working, and/or personal obligations ( Cooper et al. , 2019c ). While the majority of the literature surrounding undergraduate research highlights undergraduate research as a positive experience ( NASEM, 2017 ), studies have demonstrated that undergraduate research experiences can be academically and emotionally challenging for students ( Mabrouk and Peters, 2000 ; Seymour et al. , 2004 ; Cooper et al. , 2019c ; Limeri et al. , 2019 ). In fact, 50% of students sampled nationally from public R1 institutions consider leaving their undergraduate research experience prematurely, and about half of those students, or 25% of all students, ultimately leave their undergraduate research experience ( Cooper et al. , 2019c ). Notably, 33.8% of these individuals cited a negative lab environment and 33.3% cited negative relationships with their mentors as factors that influenced their decision about whether to leave ( Cooper et al. , 2019c ). Therefore, students’ depression may be exacerbated in challenging undergraduate research experiences, because studies have shown that depression is positively correlated with student stress ( Hish et al. , 2019 ).

While depression has not been explored in the context of undergraduate research experiences, depression has become a prominent concern surrounding graduate students conducting scientific research. A recent study that examined the “graduate student mental health crisis” ( Flaherty, 2018 ) found that work–life balance and graduate students’ relationships with their research advisors may be contributing to their depression ( Evans et al. , 2018 ). Specifically, this survey of 2279 PhD and master’s students from diverse fields of study, including the biological/physical sciences, showed that 39% of graduate students have experienced moderate to severe depression. Fifty-five percent of the graduate students with depression who were surveyed disagreed with the statement “I have good work life balance,” compared to only 21% of students with depression who agreed. Additionally, the study highlighted that more students with depression disagreed than agreed with the following statements: their advisors provided “real” mentorship, their advisors provided ample support, their advisors positively impacted their emotional or mental well-being, their advisors were assets to their careers, and they felt valued by their mentors. Another recent study identified that depression severity in biomedical doctoral students was significantly associated with graduate program climate, a perceived lack of employment opportunities, and the quality of students’ research training environment ( Nagy et al. , 2019 ). Environmental stress, academic stress, and family and monetary stress have also been shown to be predictive of depression severity in biomedical doctoral students ( Hish et al. , 2019 ). Further, one study found that self-esteem is negatively correlated and stress is positively correlated with graduate student depression; presumably research environments that challenge students’ self-esteem and induce stress are likely contributing to depressive symptoms among graduate students ( Kreger, 1995 ). While these studies have focused on graduate students, and there are certainly notable distinctions between graduate and undergraduate research, the research-related factors that affect graduate student depression, including work–life balance, relationships with mentors, research environment, stress, and self-esteem, may also be relevant to depression among undergraduates conducting research. Importantly, undergraduates in the United States have reported identical levels of depression as graduate students but are often less likely to seek mental health care services ( Wyatt and Oswalt, 2013 ), which is concerning if undergraduate research experiences exacerbate depression.

Based on the literature on the stressors of undergraduate research experiences and the literature identifying some potential causes of graduate student depression, we identified three aspects of undergraduate research that may exacerbate undergraduates’ depression. Mentoring: Mentors can be an integral part of a students’ research experience, bolstering their connections with others in the science community, scholarly productivity, and science identity, as well as providing many other benefits ( Thiry and Laursen, 2011 ; Prunuske et al. , 2013 ; Byars-Winston et al. , 2015 ; Aikens et al. , 2016 , 2017 ; Thompson et al. , 2016 ; Estrada et al. , 2018 ). However, recent literature has highlighted that poor mentoring can negatively affect undergraduate researchers ( Cooper et al. , 2019c ; Limeri et al. , 2019 ). Specifically, one study of 33 undergraduate researchers who had conducted research at 10 institutions identified seven major ways that they experienced negative mentoring, which included absenteeism, abuse of power, interpersonal mismatch, lack of career support, lack of psychosocial support, misaligned expectations, and unequal treatment ( Limeri et al. , 2019 ). We hypothesize negative mentoring experiences may be particularly harmful for students with depression, because support, particularly social support, has been shown to be important for helping individuals with depression cope with difficult circumstances ( Aneshensel and Stone, 1982 ; Grav et al. , 2012 ). Failure: Experiencing failure has been hypothesized to be an important aspect of undergraduate research experiences that may help students develop some the most distinguishing abilities of outstanding scientists, such as coping with failure, navigating challenges, and persevering ( Laursen et al. , 2010 ; Gin et al. , 2018 ; Henry et al. , 2019 ). However, experiencing failure and the stress and fatigue that often accompany it may be particularly tough for students with depression ( Aldwin and Greenberger, 1987 ; Mongrain and Blackburn, 2005 ). Lab environment: Fairness, inclusion/exclusion, and social support within one’s organizational environment have been shown to be key factors that cause people to either want to remain in the work place and be productive or to want to leave ( Barak et al. , 2006 ; Cooper et al. , 2019c ). We hypothesize that dealing with exclusion or a lack of social support may exacerbate depression for some students; patients with clinical depression react to social exclusion with more pronounced negative emotions than do individuals without clinical depression ( Jobst et al. , 2015 ). While there are likely other aspects of undergraduate research that affect student depression, we hypothesize that these factors have the potential to exacerbate negative research experiences for students with depression.

Depression has been shown to disproportionately affect many populations that are underrepresented or underserved within the scientific community, including females ( American College Health Association, 2018 ; Evans et al. , 2018 ), first-generation college students ( Jenkins et al. , 2013 ), individuals from low socioeconomic backgrounds ( Eisenberg et al. , 2007 ), members of the LGBTQ+ community ( Eisenberg et al. , 2007 ; Evans et al. , 2018 ), and people with disabilities ( Turner and Noh, 1988 ). Therefore, as the science community strives to be more diverse and inclusive ( Intemann, 2009 ), it is important that we understand more about the relationship between depression and scientific research, because negative experiences with depression in scientific research may be contributing to the underrepresentation of these groups. Specifically, more information is needed about how the research process and environment of research experiences may affect depression.

Given the high rate of depression among undergraduates, the links between depression and graduate research, the potentially challenging environment of undergraduate research, and how depression could disproportionately impact students from underserved communities, it is imperative to begin to explore the relationship between scientific research and depression among undergraduates to create research experiences that could maximize student success. In this exploratory interview study, we aimed to 1) describe how undergraduates’ symptoms of depression affect their research experiences, 2) understand how undergraduate research affects students’ feelings of depression, and 3) identify recommendations based on the literature and undergraduates’ reported experiences to promote a positive research experience for students with depression.

This study was done with an approved Arizona State University Institutional Review Board protocol #7247.

In Fall 2018, we surveyed undergraduate researchers majoring in the life sciences across 25 research-intensive (R1) public institutions across the United States (specific details about the recruitment of the students who completed the survey can be found in Cooper et al. (2019c) ). The survey asked students for their opinions about their undergraduate research experiences and their demographic information and whether they would be interested in participating in a follow-up interview related to their research experiences. For the purpose of this study, we exclusively interviewed students about their undergraduate research experiences in faculty member labs; we did not consider students’ experiences in CUREs. Of the 768 undergraduate researchers who completed the survey, 65% ( n = 496) indicated that they would be interested in participating in a follow-up interview. In Spring 2019, we emailed the 496 students, explaining that we were interested in interviewing students with depression about their experiences in undergraduate research. Our specific prompt was: “If you identify as having depression, we would be interested in hearing about your experience in undergraduate research in a 30–60 minute online interview.” We did not define depression in our email recruitment because we conducted think-aloud interviews with four undergraduates who all correctly interpreted what we meant by depression ( APA, 2013 ). We had 35 students agree to participate in the interview study. The interview participants represented 12 of the 25 R1 public institutions that were represented in the initial survey.

Student Interviews

We developed an interview script to explore our research questions. Specifically, we were interested in how students’ symptoms of depression affect their research experiences, how undergraduate research negatively affects student depression, and how undergraduate research positively affects student depression.

We recognized that mental health, and specifically depression, can be a sensitive topic to discuss with undergraduates, and therefore we tried to minimize any discomfort that the interviewees might experience during the interview. Specifically, we conducted think-aloud interviews with three graduate students who self-identified with having depression at the time of the interview. We asked them to note whether any interview questions made them uncomfortable. We also sought their feedback on questions given their experiences as persons with depression who had once engaged in undergraduate research. We revised the interview protocol after each think-aloud interview. Next, we conducted four additional think-aloud interviews with undergraduates conducting basic science or biology education research who identified with having depression to establish cognitive validity of the questions and to elicit additional feedback about any questions that might make someone uncomfortable. The questions were revised after each think-aloud interview until no question was unclear or misinterpreted by the students and we were confident that the questions minimized students’ potential discomfort ( Trenor et al. , 2011 ). A copy of the final interview script can be found in the Supplemental Material.

All interviews were individually conducted by one of two researchers (K.M.C. and L.E.G.) who conducted the think-aloud interviews together to ensure that their interviewing practices were as similar as possible. The interviews were approximately an hour long, and students received a $15 gift card for their participation.

Personal, Research, and Depression Demographics

All student demographics and information about students’ research experiences were collected using the survey distributed to students in Fall 2018. We collected personal demographics, including the participants’ gender, race/ethnicity, college generation status, transfer status, financial stability, year in college, major, and age. We also collected information about the students’ research experiences, including the length of their first research experiences, the average number of hours they spend in research per week, how they were compensated for research, who their primary mentors were, and the focus areas of their research.

In the United States, mental healthcare is disproportionately unavailable to Black and Latinx individuals, as well as those who come from low socioeconomic backgrounds ( Kataoka et al. , 2002 ; Howell and McFeeters, 2008 ; Santiago et al. , 2013 ). Therefore, to minimize a biased sample, we invited anyone who identified with having depression to participate in our study; we did not require students to be diagnosed with depression or to be treated for depression in order to participate. However, we did collect information about whether students had been formally diagnosed with depression and whether they had been treated for depression. After the interview, all participants were sent a link to a short survey that asked them if they had ever been diagnosed with depression and how, if at all, they had ever been treated for depression. A copy of these survey questions can be found in the Supplemental Material. The combined demographic information of the participants is in Table 1 . The demographics for each individual student can be found in the Supplemental Material.

a Students reported the time they had spent in research 6 months before being interviewed and only reported on the length of time of their first research experiences.

b Students were invited to report multiple ways in which they were treated for their depression; other treatments included lifestyle changes and meditation.

c Students were invited to report multiple means of compensation for their research if they had been compensated for their time in different ways.

d Students were asked whether they felt financially stable, particularly during the undergraduate research experience.

e Students reported who they work/worked with most closely during their research experiences.

f Staff members included lab coordinators or lab managers.

g Other focus areas of research included sociology, linguistics, psychology, and public health.

Interview Analysis

The initial interview analysis aimed to explore each idea that a participant expressed ( Charmaz, 2006 ) and to identify reoccurring ideas throughout the interviews. First, three authors (K.M.C., L.E.G., and S.E.B.) individually reviewed a different set of 10 interviews and took detailed analytic notes ( Birks and Mills, 2015 ). Afterward, the authors compared their notes and identified reoccurring themes throughout the interviews using open coding methods ( Saldaña, 2015 ).

Once an initial set of themes was established, two researchers (K.M.C. and L.E.G.) individually reviewed the same set of 15 randomly selected interviews to validate the themes identified in the initial analysis and to screen for any additional themes that the initial analysis may have missed. Each researcher took detailed analytic notes throughout the review of an interview, which they discussed after reviewing each interview. The researchers compared what quotes from each interview they categorized into each theme. Using constant comparison methods, they assigned quotes to each theme and constantly compared the quotes to ensure that each quote fit within the description of the theme ( Glesne and Peshkin, 1992 ). In cases in which quotes were too different from other quotes, a new theme was created. This approach allowed for multiple revisions of the themes and allowed the authors to define a final set of codes; the researchers created a final codebook with refined definitions of emergent themes (the final coding rubric can be found in the Supplemental Material). Once the final codebook was established, the researchers (K.M.C. and L.E.G.) individually coded seven additional interviews (20% of all interviews) using the coding rubric. The researchers compared their codes, and their Cohen’s κ interrater score for these seven interviews was at an acceptable level (κ  =  0.88; Landis and Koch, 1977 ). One researcher (L.E.G.) coded the remaining 28 out of 35 interviews. The researchers determined that data saturation had been reached with the current sample and no further recruitment was needed ( Guest et al. , 2006 ). We report on themes that were mentioned by at least 20% of students in the interview study. In the Supplemental Material, we provide the final coding rubric with the number of participants whose interview reflected each theme ( Hannah and Lautsch, 2011 ). Reporting the number of individuals who reported themes within qualitative data can lead to inaccurate conclusions about the generalizability of the results to a broader population. These qualitative data are meant to characterize a landscape of experiences that students with depression have in undergraduate research rather than to make claims about the prevalence of these experiences ( Glesne and Peshkin, 1992 ). Because inferences about the importance of these themes cannot be drawn from these counts, they are not included in the results of the paper ( Maxwell, 2010 ). Further, the limited number of interviewees made it not possible to examine whether there were trends based on students’ demographics or characteristics of their research experiences (e.g., their specific area of study). Quotes were lightly edited for clarity by inserting clarification brackets and using ellipses to indicate excluded text. Pseudonyms were given to all students to protect their privacy.

The Effect of Depressive Symptoms on Undergraduate Research

We asked students to describe the symptoms associated with their depression. Students described experiencing anxiety that is associated with their depression; this could be anxiety that precedes their depression or anxiety that results from a depressive episode or a period of time when an individual has depression symptoms. Further, students described difficulty getting out of bed or leaving the house, feeling tired, a lack of motivation, being overly self-critical, feeling apathetic, and having difficulty concentrating. We were particularly interested in how students’ symptoms of depression affected their experiences in undergraduate research. During the think-aloud interviews that were conducted before the interview study, graduate and undergraduate students consistently described that their depression affected their motivation in research, their creativity in research, and their productivity in research. Therefore, we explicitly asked undergraduate researchers how, if at all, their depression affected these three factors. We also asked students to describe any additional ways in which their depression affected their research experiences. Undergraduate researchers commonly described five additional ways in which their depression affected their research; for a detailed description of each way students’ research was affected and for example quotes, see Table 2 . Students described that their depression negatively affected their productivity in the lab. Commonly, students described that their productivity was directly affected by a lack of motivation or because they felt less creative, which hindered the research process. Additionally, students highlighted that they were sometimes less productive because their depression sometimes caused them to struggle to engage intellectually with their research or caused them to have difficulty remembering or concentrating; students described that they could do mundane or routine tasks when they felt depressed, but that they had difficulty with more complex and intellectually demanding tasks. However, students sometimes described that even mundane tasks could be difficult when they were required to remember specific steps; for example, some students struggled recalling a protocol from memory when their depression was particularly severe. Additionally, students noted that their depression made them more self-conscious, which sometimes held them back from sharing research ideas with their mentors or from taking risks such as applying to competitive programs. In addition to being self-conscious, students highlighted that their depression caused them to be overly self-critical, and some described experiencing imposter phenomenon ( Clance and Imes, 1978 ) or feeling like they were not talented enough to be in research and were accepted into a lab by a fluke or through luck. Finally, students described that depression often made them feel less social, and they struggled to socially engage with other members of the lab when they were feeling down.

The Effect of Undergraduate Research Experiences on Student Depression

We also wanted to explore how research impacted students’ feelings of depression. Undergraduates described how research both positively and negatively affected their depression. In the following sections, we present aspects of undergraduate research and examine how each positively and/or negatively affected students’ depression using embedded student quotes to highlight the relationships between related ideas.

Lab Environment: Relationships with Others in the Lab.

Some aspects of the lab environment, which we define as students’ physical, social, or psychological research space, could be particularly beneficial for students with depression.

Specifically, undergraduate researchers perceived that comfortable and positive social interactions with others in the lab helped their depression. Students acknowledged how beneficial their relationships with graduate students and postdocs could be.

Marta: “I think always checking in on undergrads is important. It’s really easy [for us] to go a whole day without talking to anybody in the lab. But our grad students are like ‘Hey, what’s up? How’s school? What’s going on?’ (…) What helps me the most is having that strong support system. Sometimes just talking makes you feel better, but also having people that believe in you can really help you get out of that negative spiral. I think that can really help with depression.”

Kelley: “I know that anytime I need to talk to [my postdoc mentors] about something they’re always there for me. Over time we’ve developed a relationship where I know that outside of work and outside of the lab if I did want to talk to them about something I could talk to them. Even just talking to someone about hobbies and having that relationship alone is really helpful [for depression].”

In addition to highlighting the importance of developing relationships with graduate students or postdocs in the lab, students described that forming relationships with other undergraduates in the lab also helped their depression. Particularly, students described that other undergraduate researchers often validated their feelings about research, which in turn helped them realize that what they are thinking or feeling is normal, which tended to alleviate their negative thoughts. Interestingly, other undergraduates experiencing the same issues could sometimes help buffer them from perceiving that a mentor did not like them or that they were uniquely bad at research. In this article, we use the term “mentor” to refer to anyone who students referred to in the interviews as being their mentors or managing their research experiences; this includes graduate students, postdoctoral scholars, lab managers, and primary investigators (PIs).

Abby: “One of my best friends is in the lab with me.  A lot of that friendship just comes from complaining about our stress with the lab and our annoyance with people in the lab. Like when we both agree like, ‘Yeah, the grad students were really off today, it wasn’t us,’ that helps. ‘It wasn’t me, it wasn’t my fault that we were having a rough day in lab; it was the grad students.’ Just being able to realize, ‘Hey, this isn’t all caused by us,’ you know? (…) We understand the stresses in the lab. We understand the details of what each other are doing in the lab, so when something doesn’t work out, we understand that it took them like eight hours to do that and it didn’t work. We provide empathy on a different level.”

Meleana: “It’s great to have solidarity in being confused about something, and it’s just that is a form of validation for me too. When we leave a lab meeting and I look at [another undergrad] I’m like, ‘Did you understand anything that they were just saying?’ And they’re like, ‘Oh, no.’ (…) It’s just really validating to hear from the other undergrads that we all seem to be struggling with the same things.”

Developing positive relationships with faculty mentors or PIs also helped alleviate some students’ depressive feelings, particularly when PIs shared their own struggles with students. This also seemed to normalize students’ concerns about their own experiences.

Alexandra: “[Talking with my PI] is helpful because he would talk about his struggles, and what he faced. A lot of it was very similar to my struggles.  For example, he would say, ‘Oh, yeah, I failed this exam that I studied so hard for. I failed the GRE and I paid so much money to prepare for it.’ It just makes [my depression] better, like okay, this is normal for students to go through this. It’s not an out of this world thing where if you fail, you’re a failure and you can’t move on from it.”

Students’ relationships with others in the lab did not always positively impact their depression. Students described instances when the negative moods of the graduate students and PIs would often set the tone of the lab, which in turn worsened the mood of the undergraduate researchers.

Abby: “Sometimes [the grad students] are not in a good mood. The entire vibe of the lab is just off, and if you make a joke and it hits somebody wrong, they get all mad. It really depends on the grad students and the leadership and the mood that they’re in.”

Interviewer: “How does it affect your depression when the grad students are in a bad mood?”

Abby: “It definitely makes me feel worse. It feels like, again, that I really shouldn’t go ask them for help because they’re just not in the mood to help out. It makes me have more pressure on myself, and I have deadlines I need to meet, but I have a question for them, but they’re in a bad mood so I can’t ask. That’s another day wasted for me and it just puts more stress, which just adds to the depression.”

Additionally, some students described even more concerning behavior from research mentors, which negatively affected their depression.

Julie: “I had a primary investigator who is notorious in the department for screaming at people, being emotionally abusive, unreasonable, et cetera. (…) [He was] kind of harassing people, demeaning them, lying to them, et cetera, et cetera. (…) Being yelled at and constantly demeaned and harassed at all hours of the day and night, that was probably pretty bad for me.”

While the relationships between undergraduates and graduate, postdoc, and faculty mentors seemed to either alleviate or worsen students’ depressive symptoms, depending on the quality of the relationship, students in this study exclusively described their relationships with other undergraduates as positive for their depression. However, students did note that undergraduate research puts some of the best and brightest undergraduates in the same environment, which can result in students comparing themselves with their peers. Students described that this comparison would often lead them to feel badly about themselves, even though they would describe their personal relationship with a person to be good.

Meleana: “In just the research field in general, just feeling like I don’t really measure up to the people around me [can affect my depression]. A lot of the times it’s the beginning of a little spiral, mental spiral. There are some past undergrads that are talked about as they’re on this pedestal of being the ideal undergrads and that they were just so smart and contributed so much to the lab. I can never stop myself from wondering like, ‘Oh, I wonder if I’m having a contribution to the lab that’s similar or if I’m just another one of the undergrads that does the bare minimum and passes through and is just there.’”

Natasha: “But, on the other hand, [having another undergrad in the lab] also reminded me constantly that some people are invested in this and meant to do this and it’s not me. And that some people know a lot more than I do and will go further in this than I will.”

While students primarily expressed that their relationships with others in the lab affected their depression, some students explained that they struggled most with depression when the lab was empty; they described that they did not like being alone in the lab, because a lack of stimulation allowed their minds to be filled with negative thoughts.

Mia: “Those late nights definitely didn’t help [my depression]. I am alone, in the entire building.  I’m left alone to think about my thoughts more, so not distracted by talking to people or interacting with people. I think more about how I’m feeling and the lack of progress I’m making, and the hopelessness I’m feeling. That kind of dragged things on, and I guess deepened my depression.”

Freddy: “Often times when I go to my office in the evening, that is when I would [ sic ] be prone to be more depressed. It’s being alone. I think about myself or mistakes or trying to correct mistakes or whatever’s going on in my life at the time. I become very introspective. I think I’m way too self-evaluating, way too self-deprecating and it’s when I’m alone when those things are really, really triggered. When I’m talking with somebody else, I forget about those things.”

In sum, students with depression highlighted that a lab environment full of positive and encouraging individuals was helpful for their depression, whereas isolating or competitive environments and negative interactions with others often resulted in more depressive feelings.

Doing Science: Experiencing Failure in Research, Getting Help, Receiving Feedback, Time Demands, and Important Contributions.

In addition to the lab environment, students also described that the process of doing science could affect their depression. Specifically, students explained that a large contributor to their depression was experiencing failure in research.

Interviewer: “Considering your experience in undergraduate research, what tends to trigger your feelings of depression?”

Heather: “Probably just not getting things right. Having to do an experiment over and over again. You don’t get the results you want. (…) The work is pretty meticulous and it’s frustrating when I do all this work, I do a whole experiment, and then I don’t get any results that I can use. That can be really frustrating. It adds to the stress. (…) It’s hard because you did all this other stuff before so you can plan for the research, and then something happens and all the stuff you did was worthless basically.”

Julie: “I felt very negatively about myself [when a project failed] and pretty panicked whenever something didn’t work because I felt like it was a direct reflection on my effort and/or intelligence, and then it was a big glaring personal failure.”

Students explained that their depression related to failing in research was exacerbated if they felt as though they could not seek help from their research mentors. Perceived insufficient mentor guidance has been shown to be a factor influencing student intention to leave undergraduate research ( Cooper et al. , 2019c ). Sometimes students talked about their research mentors being unavailable or unapproachable.

Michelle: “It just feels like [the graduate students] are not approachable. I feel like I can’t approach them to ask for their understanding in a certain situation. It makes [my depression] worse because I feel like I’m stuck, and that I’m being limited, and like there’s nothing I can do. So then I kind of feel like it’s my fault that I can’t do anything.”

Other times, students described that they did not seek help in fear that they would be negatively evaluated in research, which is a fear of being judged by others ( Watson and Friend, 1969 ; Weeks et al. , 2005 ; Cooper et al. , 2018 ). That is, students fear that their mentor would think negatively about them or judge them if they were to ask questions that their mentor thought they should know the answer to.

Meleana: “I would say [my depression] tends to come out more in being more reserved in asking questions because I think that comes more like a fear-based thing where I’m like, ‘Oh, I don’t feel like I’m good enough and so I don’t want to ask these questions because then my mentors will, I don’t know, think that I’m dumb or something.’”

Conversely, students described that mentors who were willing to help them alleviated their depressive feelings.

Crystal: “Yeah [my grad student] is always like, ‘Hey, I can check in on things in the lab because you’re allowed to ask me for that, you’re not totally alone in this,’ because he knows that I tend to take on all this responsibility and I don’t always know how to ask for help. He’s like, ‘You know, this is my lab too and I am here to help you as well,’ and just reminds me that I’m not shouldering this burden by myself.”

Ashlyn: “The graduate student who I work with is very kind and has a lot of patience and he really understands a lot of things and provides simple explanations. He does remind me about things and he will keep on me about certain tasks that I need to do in an understanding way, and it’s just because he’s patient and he listens.”

In addition to experiencing failure in science, students described that making mistakes when doing science also negatively affected their depression.

Abby: “I guess not making mistakes on experiments [is important in avoiding my depression]. Not necessarily that your experiment didn’t turn out to produce the data that you wanted, but just adding the wrong enzyme or messing something up like that. It’s like, ‘Oh, man,’ you know? You can get really down on yourself about that because it can be embarrassing.”

Commonly, students described that the potential for making mistakes increased their stress and anxiety regarding research; however, they explained that how other people responded to a potential mistake was what ultimately affected their depression.

Briana: “Sometimes if I made a mistake in correctly identifying an eye color [of a fly], [my PI] would just ridicule me in front of the other students. He corrected me but his method of correcting was very discouraging because it was a ridicule. It made the others laugh and I didn’t like that.”

Julie: “[My PI] explicitly [asked] if I had the dedication for science. A lot of times he said I had terrible judgment. A lot of times he said I couldn’t be trusted. Once I went to a conference with him, and, unfortunately, in front of another professor, he called me a klutz several times and there was another comment about how I never learn from my mistakes.”

When students did do things correctly, they described how important it could be for them to receive praise from their mentors. They explained that hearing praise and validation can be particularly helpful for students with depression, because their thoughts are often very negative and/or because they have low self-esteem.

Crystal: “[Something that helps my depression is] I have text messages from [my graduate student mentor] thanking me [and another undergraduate researcher] for all of the work that we’ve put in, that he would not be able to be as on track to finish as he is if he didn’t have our help.”

Interviewer: “Why is hearing praise from your mentor helpful?”

Crystal: “Because a lot of my depression focuses on everybody secretly hates you, nobody likes you, you’re going to die alone. So having that validation [from my graduate mentor] is important, because it flies in the face of what my depression tells me.”

Brian: “It reminds you that you exist outside of this negative world that you’ve created for yourself, and people don’t see you how you see yourself sometimes.”

Students also highlighted how research could be overwhelming, which negatively affected their depression. Particularly, students described that research demanded a lot of their time and that their mentors did not always seem to be aware that they were juggling school and other commitments in addition to their research. This stress exacerbated their depression.

Rose: “I feel like sometimes [my grad mentors] are not very understanding because grad students don’t take as many classes as [undergrads] do. I think sometimes they don’t understand when I say I can’t come in at all this week because I have finals and they’re like, ‘Why though?’”

Abby: “I just think being more understanding of student life would be great. We have classes as well as the lab, and classes are the priority. They forget what it’s like to be a student. You feel like they don’t understand and they could never understand when you say like, ‘I have three exams this week,’ and they’re like, ‘I don’t care. You need to finish this.’”

Conversely, some students reported that their research labs were very understanding of students’ schedules. Interestingly, these students talked most about how helpful it was to be able to take a mental health day and not do research on days when they felt down or depressed.

Marta: “My lab tech is very open, so she’ll tell us, ‘I can’t come in today. I have to take a mental health day.’ So she’s a really big advocate for that. And I think I won’t personally tell her that I’m taking a mental health day, but I’ll say, ‘I can’t come in today, but I’ll come in Friday and do those extra hours.’ And she’s like, ‘OK great, I’ll see you then.’  And it makes me feel good, because it helps me take care of myself first and then I can take care of everything else I need to do, which is amazing.”

Meleana: “Knowing that [my mentors] would be flexible if I told them that I’m crazy busy and can’t come into work nearly as much this week [helps my depression]. There is flexibility in allowing me to then care for myself.”

Interviewer: “Why is the flexibility helpful given the depression?”

Meleana: “Because sometimes for me things just take a little bit longer when I’m feeling down. I’m just less efficient to be honest, and so it’s helpful if I feel like I can only go into work for 10 hours in a week. It declutters my brain a little bit to not have to worry about all the things I have to do in work in addition the things that I need to do for school or clubs, or family or whatever.”

Despite the demanding nature of research, a subset of students highlighted that their research and research lab provided a sense of stability or familiarity that distracted them from their depression.

Freddy: “I’ll [do research] to run away from those [depressive] feelings or whatever. (…) I find sadly, I hate to admit it, but I do kind of run to [my lab]. I throw myself into work to distract myself from the feelings of depression and sadness.”

Rose: “When you’re sad or when you’re stressed you want to go to things you’re familiar with. So because lab has always been in my life, it’s this thing where it’s going to be there for me I guess. It’s like a good book that you always go back to and it’s familiar and it makes you feel good. So that’s how lab is. It’s not like the greatest thing in the world but it’s something that I’m used to, which is what I feel like a lot of people need when they’re sad and life is not going well.”

Many students also explained that research positively affects their depression because they perceive their research contribution to be important.

Ashlyn: “I feel like I’m dedicating myself to something that’s worthy and something that I believe in. It’s really important because it contextualizes those times when I am feeling depressed. It’s like, no, I do have these better things that I’m working on. Even when I don’t like myself and I don’t like who I am, which is again, depression brain, I can at least say, ‘Well, I have all these other people relying on me in research and in this area and that’s super important.’”

Jessica: “I mean, it just felt like the work that I was doing had meaning and when I feel like what I’m doing is actually going to contribute to the world, that usually really helps with [depression] because it’s like not every day you can feel like you’re doing something impactful.”

In sum, students highlighted that experiencing failure in research and making mistakes negatively contributed to depression, especially when help was unavailable or research mentors had a negative reaction. Additionally, students acknowledged that the research could be time-consuming, but that research mentors who were flexible helped assuage depressive feelings that were associated with feeling overwhelmed. Finally, research helped some students’ depression, because it felt familiar, provided a distraction from depression, and reminded students that they were contributing to a greater cause.

We believe that creating more inclusive research environments for students with depression is an important step toward broadening participation in science, not only to ensure that we are not discouraging students with depression from persisting in science, but also because depression has been shown to disproportionately affect underserved and underrepresented groups in science ( Turner and Noh, 1988 ; Eisenberg et al. , 2007 ; Jenkins et al. , 2013 ; American College Health Association, 2018 ). We initially hypothesized that three features of undergraduate research—research mentors, the lab environment, and failure—may have the potential to exacerbate student depression. We found this to be true; students highlighted that their relationships with their mentors as well as the overall lab environment could negatively affect their depression, but could also positively affect their research experiences. Students also noted that they struggled with failure, which is likely true of most students, but is known to be particularly difficult for students with depression ( Elliott et al. , 1997 ). We expand upon our findings by integrating literature on depression with the information that students provided in the interviews about how research mentors can best support students. We provide a set of evidence-based recommendations focused on mentoring, the lab environment, and failure for research mentors wanting to create more inclusive research environments for students with depression. Notably, only the first recommendation is specific to students with depression; the others reflect recommendations that have previously been described as “best practices” for research mentors ( NASEM, 2017 , 2019 ; Sorkness et al. , 2017 ) and likely would benefit most students. However, we examine how these recommendations may be particularly important for students with depression. As we hypothesized, these recommendations directly address three aspects of research: mentors, lab environment, and failure. A caveat of these recommendations is that more research needs to be done to explore the experiences of students with depression and how these practices actually impact students with depression, but our national sample of undergraduate researchers with depression can provide an initial starting point for a discussion about how to improve research experiences for these students.

Recommendations to Make Undergraduate Research Experiences More Inclusive for Students with Depression

Recognize student depression as a valid illness..

Allow students with depression to take time off of research by simply saying that they are sick and provide appropriate time for students to recover from depressive episodes. Also, make an effort to destigmatize mental health issues.

Undergraduate researchers described both psychological and physical symptoms that manifested as a result of their depression and highlighted how such symptoms prevented them from performing to their full potential in undergraduate research. For example, students described how their depression would cause them to feel unmotivated, which would often negatively affect their research productivity. In cases in which students were motivated enough to come in and do their research, they described having difficulty concentrating or engaging in the work. Further, when doing research, students felt less creative and less willing to take risks, which may alter the quality of their work. Students also sometimes struggled to socialize in the lab. They described feeling less social and feeling overly self-critical. In sum, students described that, when they experienced a depressive episode, they were not able to perform to the best of their ability, and it sometimes took a toll on them to try to act like nothing was wrong, when they were internally struggling with depression. We recommend that research mentors treat depression like any other physical illness; allowing students the chance to recover when they are experiencing a depressive episode can be extremely important to students and can allow them to maximize their productivity upon returning to research ( Judd et al. , 2000 ). Students explained that if they are not able to take the time to focus on recovering during a depressive episode, then they typically continue to struggle with depression, which negatively affects their research. This sentiment is echoed by researchers in psychiatry who have found that patients who do not fully recover from a depressive episode are more likely to relapse and to experience chronic depression ( Judd et al. , 2000 ). Students described not doing tasks or not showing up to research because of their depression but struggling with how to share that information with their research mentors. Often, students would not say anything, which caused them anxiety because they were worried about what others in the lab would say to them when they returned. Admittedly, many students understood why this behavior would cause their research mentors to be angry or frustrated, but they weighed the consequences of their research mentors’ displeasure against the consequences of revealing their depression and decided it was not worth admitting to being depressed. This aligns with literature that suggests that when individuals have concealable stigmatized identities, or identities that can be hidden and that carry negative stereotypes, such as depression, they will often keep them concealed to avoid negative judgment or criticism ( Link and Phelan, 2001 ; Quinn and Earnshaw, 2011 ; Jones and King, 2014 ; Cooper and Brownell, 2016 ; Cooper et al. , 2019b ; Cooper et al ., unpublished data ). Therefore, it is important for research mentors to be explicit with students that 1) they recognize mental illness as a valid sickness and 2) that students with mental illness can simply explain that they are sick if they need to take time off. This may be useful to overtly state on a research website or in a research syllabus, contract, or agreement if mentors use such documents when mentoring undergraduates in their lab. Further, research mentors can purposefully work to destigmatize mental health issues by explicitly stating that struggling with mental health issues, such as depression and anxiety, is common. While we do not recommend that mentors ask students directly about depression, because this can force students to share when they are not comfortable sharing, we do recommend providing opportunities for students to reveal their depression ( Chaudoir and Fisher, 2010 ). Mentors can regularly check in with students about how they’re doing, and talk openly about the importance of mental health, which may increase the chance that students may feel comfortable revealing their depression ( Chaudoir and Quinn, 2010 ; Cooper et al ., unpublished data ).

Foster a Positive Lab Environment.

Encourage positivity in the research lab, promote working in shared spaces to enhance social support among lab members, and alleviate competition among undergraduates.

Students in this study highlighted that the “leadership” of the lab, meaning graduate students, postdocs, lab managers, and PIs, were often responsible for establishing the tone of the lab; that is, if they were in a bad mood it would trickle down and negatively affect the moods of the undergraduates. Explicitly reminding lab leadership that their moods can both positively and negatively affect undergraduates may be important in establishing a positive lab environment. Further, students highlighted how they were most likely to experience negative thoughts when they were alone in the lab. Therefore, it may be helpful to encourage all lab members to work in a shared space to enhance social interactions among students and to maximize the likelihood that undergraduates have access to help when needed. A review of 51 studies in psychiatry supported our undergraduate researchers’ perceptions that social relationships positively impacted their depression; the study found that perceived emotional support (e.g., someone available to listen or give advice), perceived instrumental support (e.g., someone available to help with tasks), and large diverse social networks (e.g., being socially connected to a large number of people) were significantly protective against depression ( Santini et al. , 2015 ). Additionally, despite forming positive relationships with other undergraduates in the lab, many undergraduate researchers admitted to constantly comparing themselves with other undergraduates, which led them to feel inferior, negatively affecting their depression. Some students talked about mentors favoring current undergraduates or talking positively about past undergraduates, which further exacerbated their feelings of inferiority. A recent study of students in undergraduate research experiences highlighted that inequitable distribution of praise to undergraduates can create negative perceptions of lab environments for students (Cooper et al. , 2019). Further, the psychology literature has demonstrated that when people feel insecure in their social environments, it can cause them to focus on a hierarchical view of themselves and others, which can foster feelings of inferiority and increase their vulnerability to depression ( Gilbert et al. , 2009 ). Thus, we recommend that mentors be conscious of their behaviors so that they do not unintentionally promote competition among undergraduates or express favoritism toward current or past undergraduates. Praise is likely best used without comparison with others and not done in a public way, although more research on the impact of praise on undergraduate researchers needs to be done. While significant research has been done on mentoring and mentoring relationships in the context of undergraduate research ( Byars-Winston et al. , 2015 ; Aikens et al. , 2017 ; Estrada et al. , 2018 ; Limeri et al. , 2019 ; NASEM, 2019 ), much less has been done on the influence of the lab environment broadly and how people in nonmentoring roles can influence one another. Yet, this study indicates the potential influence of many different members of the lab, not only their mentors, on students with depression.

Develop More Personal Relationships with Undergraduate Researchers and Provide Sufficient Guidance.

Make an effort to establish more personal relationships with undergraduates and ensure that they perceive that they have access to sufficient help and guidance with regard to their research.

When we asked students explicitly how research mentors could help create more inclusive environments for undergraduate researchers with depression, students overwhelmingly said that building mentor–student relationships would be extremely helpful. Students suggested that mentors could get to know students on a more personal level by asking about their career interests or interests outside of academia. Students also remarked that establishing a more personal relationship could help build the trust needed in order for undergraduates to confide in their research mentors about their depression, which they perceived would strengthen their relationships further because they could be honest about when they were not feeling well or their mentors might even “check in” with them in times where they were acting differently than normal. This aligns with studies showing that undergraduates are most likely to reveal a stigmatized identity, such as depression, when they form a close relationship with someone ( Chaudoir and Quinn, 2010 ). Many were intimidated to ask for research-related help from their mentors and expressed that they wished they had established a better relationship so that they would feel more comfortable. Therefore, we recommend that research mentors try to establish relationships with their undergraduates and explicitly invite them to ask questions or seek help when needed. These recommendations are supported by national recommendations for mentoring ( NASEM, 2019 ) and by literature that demonstrates that both social support (listening and talking with students) and instrumental support (providing students with help) have been shown to be protective against depression ( Santini et al. , 2015 ).

Treat Undergraduates with Respect and Remember to Praise Them.

Avoid providing harsh criticism and remember to praise undergraduates. Students with depression often have low self-esteem and are especially self-critical. Therefore, praise can help calibrate their overly negative self-perceptions.

Students in this study described that receiving criticism from others, especially harsh criticism, was particularly difficult for them given their depression. Multiple studies have demonstrated that people with depression can have an abnormal or maladaptive response to negative feedback; scientists hypothesize that perceived failure on a particular task can trigger failure-related thoughts that interfere with subsequent performance ( Eshel and Roiser, 2010 ). Thus, it is important for research mentors to remember to make sure to avoid unnecessarily harsh criticisms that make students feel like they have failed (more about failure is described in the next recommendation). Further, students with depression often have low self-esteem or low “personal judgment of the worthiness that is expressed in the attitudes the individual holds towards oneself” ( Heatherton et al. , 2003 , p. 220; Sowislo and Orth, 2013 ). Specifically, a meta-analysis of longitudinal studies found that low self-esteem is predictive of depression ( Sowislo and Orth, 2013 ), and depression has also been shown to be highly related to self-criticism ( Luyten et al. , 2007 ). Indeed, nearly all of the students in our study described thinking that they are “not good enough,” “worthless,” or “inadequate,” which is consistent with literature showing that people with depression are self-critical ( Blatt et al. , 1982 ; Gilbert et al. , 2006 ) and can be less optimistic of their performance on future tasks and rate their overall performance on tasks less favorably than their peers without depression ( Cane and Gotlib, 1985 ). When we asked students what aspects of undergraduate research helped their depression, students described that praise from their mentors was especially impactful, because they thought so poorly of themselves and they needed to hear something positive from someone else in order to believe it could be true. Praise has been highlighted as an important aspect of mentoring in research for many years ( Ashford, 1996 ; Gelso and Lent, 2000 ; Brown et al. , 2009 ) and may be particularly important for students with depression. In fact, praise has been shown to enhance individuals’ motivation and subsequent productivity ( Hancock, 2002 ; Henderlong and Lepper, 2002 ), factors highlighted by students as negatively affecting their depression. However, something to keep in mind is that a student with depression and a student without depression may process praise differently. For a student with depression, a small comment that praises the student’s work may not be sufficient for the student to process that comment as praise. People with depression are hyposensitive to reward or have reward-processing deficits ( Eshel and Roiser, 2010 ); therefore, praise may affect students without depression more positively than it would affect students with depression. Research mentors should be mindful that students with depression often have a negative view of themselves, and while students report that praise is extremely important, they may have trouble processing such positive feedback.

Normalize Failure and Be Explicit about the Importance of Research Contributions.

Explicitly remind students that experiencing failure is expected in research. Also explain to students how their individual work relates to the overall project so that they can understand how their contributions are important. It can also be helpful to explain to students why the research project as a whole is important in the context of the greater scientific community.

Experiencing failure has been thought to be a potentially important aspect of undergraduate research, because it may provide students with the potential to develop integral scientific skills such as the ability to navigate challenges and persevere ( Laursen et al. , 2010 ; Gin et al. , 2018 ; Henry et al. , 2019 ). However, in the interviews, students described that when their science experiments failed, it was particularly tough for their depression. Students’ negative reaction to experiencing failure in research is unsurprising, given recent literature that has predicted that students may be inadequately prepared to approach failure in science ( Henry et al. , 2019 ). However, the literature suggests that students with depression may find experiencing failure in research to be especially difficult ( Elliott et al. , 1997 ; Mongrain and Blackburn, 2005 ; Jones et al. , 2009 ). One potential hypothesis is that students with depression may be more likely to have fixed mindsets or more likely to believe that their intelligence and capacity for specific abilities are unchangeable traits ( Schleider and Weisz, 2018 ); students with a fixed mindset have been hypothesized to have particularly negative responses to experiencing failure in research, because they are prone to quitting easily in the face of challenges and becoming defensive when criticized ( Forsythe and Johnson, 2017 ; Dweck, 2008 ). A study of life sciences undergraduates enrolled in CUREs identified three strategies of students who adopted adaptive coping mechanisms, or mechanisms that help an individual maintain well-being and/or move beyond the stressor when faced with failure in undergraduate research: 1) problem solving or engaging in strategic planning and decision making, 2) support seeking or finding comfort and help with research, and 3) cognitive restructuring or reframing a problem from negative to positive and engaging in self encouragement ( Gin et al. , 2018 ). We recommend that, when undergraduates experience failure in science, their mentors be proactive in helping them problem solve, providing help and support, and encouraging them. Students also explained that mentors sharing their own struggles as undergraduate and graduate students was helpful, because it normalized failure. Sharing personal failures in research has been recommended as an important way to provide students with psychosocial support during research ( NASEM, 2019 ). We also suggest that research mentors take time to explain to students why their tasks in the lab, no matter how small, contribute to the greater research project ( Cooper et al. , 2019a ). Additionally, it is important to make sure that students can explain how the research project as a whole is contributing to the scientific community ( Gin et al. , 2018 ). Students highlighted that contributing to something important was really helpful for their depression, which is unsurprising, given that studies have shown that meaning in life or people’s comprehension of their life experiences along with a sense of overarching purpose one is working toward has been shown to be inversely related to depression ( Steger, 2013 ).

Limitations and Future Directions

This work was a qualitative interview study intended to document a previously unstudied phenomenon: depression in the context of undergraduate research experiences. We chose to conduct semistructured interviews rather than a survey because of the need for initial exploration of this area, given the paucity of prior research. A strength of this study is the sampling approach. We recruited a national sample of 35 undergraduates engaged in undergraduate research at 12 different public R1 institutions. Despite our representative sample from R1 institutions, these findings may not be generalizable to students at other types of institutions; lab environments, mentoring structures, and interactions between faculty and undergraduate researchers may be different at other institution types (e.g., private R1 institutions, R2 institutions, master’s-granting institutions, primarily undergraduate institutions, and community colleges), so we caution against making generalizations about this work to all undergraduate research experiences. Future work could assess whether students with depression at other types of institutions have similar experiences to students at research-intensive institutions. Additionally, we intentionally did not explore the experiences of students with specific identities owing to our sample size and the small number of students in any particular group (e.g., students of a particular race, students with a graduate mentor as the primary mentor). We intend to conduct future quantitative studies to further explore how students’ identities and aspects of their research affect their experiences with depression in undergraduate research.

The students who participated in the study volunteered to be interviewed about their depression; therefore, it is possible that depression is a more salient part of these students’ identities and/or that they are more comfortable talking about their depression than the average population of students with depression. It is also important to acknowledge the personal nature of the topic and that some students may not have fully shared their experiences ( Krumpal, 2013 ), particularly those experiences that may be emotional or traumatizing ( Kahn and Garrison, 2009 ). Additionally, our sample was skewed toward females (77%). While females do make up approximately 60% of students in biology programs on average ( Eddy et al. , 2014 ), they are also more likely to report experiencing depression ( American College Health Association, 2018 ; Evans et al. , 2018 ). However, this could be because women have higher rates of depression or because males are less likely to report having depression; clinical bias, or practitioners’ subconscious tendencies to overlook male distress, may underestimate depression rates in men ( Smith et al. , 2018 ). Further, females are also more likely to volunteer to participate in studies ( Porter and Whitcomb, 2005 ); therefore, many interview studies have disproportionately more females in the data set (e.g., Cooper et al. , 2017 ). If we had been able to interview more male students, we might have identified different findings. Additionally, we limited our sample to life sciences students engaged in undergraduate research at public R1 institutions. It is possible that students in other majors may have different challenges and opportunities for students with depression, as well as different disciplinary stigmas associated with mental health.

In this exploratory interview study, we identified a variety of ways in which depression in undergraduates negatively affected their undergraduate research experiences. Specifically, we found that depression interfered with students’ motivation and productivity, creativity and risk-taking, engagement and concentration, and self-perception and socializing. We also identified that research can negatively affect depression in undergraduates. Experiencing failure in research can exacerbate student depression, especially when students do not have access to adequate guidance. Additionally, being alone or having negative interactions with others in the lab worsened students’ depression. However, we also found that undergraduate research can positively affect students’ depression. Research can provide a familiar space where students can feel as though they are contributing to something meaningful. Additionally, students reported that having access to adequate guidance and a social support network within the research lab also positively affected their depression. We hope that this work can spark conversations about how to make undergraduate research experiences more inclusive of students with depression and that it can stimulate additional research that more broadly explores the experiences of undergraduate researchers with depression.

Important note

If you or a student experience symptoms of depression and want help, there are resources available to you. Many campuses provide counseling centers equipped to provide students, staff, and faculty with treatment for depression, as well as university-dedicated crisis hotlines. Additionally, there are free 24/7 services such as Crisis Text Line, which allows you to text a trained live crisis counselor (Text “CONNECT” to 741741; Text Depression Hotline , 2019 ), and phone hotlines such as the National Suicide Prevention Lifeline at 1-800-273-8255 (TALK). You can also learn more about depression and where to find help near you through the Anxiety and Depression Association of American website: https://adaa.org ( Anxiety and Depression Association of America, 2019 ) and the Depression and Biopolar Support Alliance: http://dbsalliance.org ( Depression and Biopolar Support Alliance, 2019 ).

ACKNOWLEDGMENTS

We are extremely grateful to the undergraduate researchers who shared their thoughts and experiences about depression with us. We acknowledge the ASU LEAP Scholars for helping us create the original survey and Rachel Scott for her helpful feedback on earlier drafts of this article. L.E.G. was supported by a National Science Foundation (NSF) Graduate Fellowship (DGE-1311230) and K.M.C. was partially supported by a Howard Hughes Medical Institute (HHMI) Inclusive Excellence grant (no. 11046) and an NSF grant (no. 1644236). Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF or HHMI.

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research articles in depression

Submitted: 4 November 2019 Revised: 24 February 2020 Accepted: 6 March 2020

© 2020 K. M. Cooper, L. E. Gin, et al. CBE—Life Sciences Education © 2020 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

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A brain pacemaker helped a woman with crippling depression. It may soon be available to more people

Researchers are testing deep brain stimulation as a treatment for people with a severe form of depression. Doctors compare it to a pacemaker for the brain. It involves implanting electrodes in the brain, which are attached to a device placed under the skin in the chest. (Feb. 21)(AP Video: Mary Conlon)

Emily Hollenbeck, a deep brain stimulation therapy patient, demonstrates an EEG device that records brain activity as she reacts to short videos at Mount Sinai’s “Q-Lab” in New York on Dec. 20, 2023. Dr. Brian Kopell, who directs Mount Sinai's Center for Neuromodulation, says in normal brains electrical activity reverberates unimpeded in all areas, in a sort of dance. In depression, the dancers get stuck within the brain’s emotional circuitry. DBS seems to “unstick the circuit,” he says, allowing the brain to do what it normally would. (AP Photo/Mary Conlon)

Emily Hollenbeck, a deep brain stimulation therapy patient, demonstrates an EEG device that records brain activity as she reacts to short videos at Mount Sinai’s “Q-Lab” in New York on Dec. 20, 2023. Dr. Brian Kopell, who directs Mount Sinai’s Center for Neuromodulation, says in normal brains electrical activity reverberates unimpeded in all areas, in a sort of dance. In depression, the dancers get stuck within the brain’s emotional circuitry. DBS seems to “unstick the circuit,” he says, allowing the brain to do what it normally would. (AP Photo/Mary Conlon)

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This brain scan image provided by Mount Sinai in 2024 shows the targeted sites for electrodes implanted in patient Emily Hollenbeck for use with deep brain stimulation therapy. Researchers say the treatment could eventually help many of the nearly 3 million Americans like her with depression that resists other treatments. (Mount Sinai via AP)

Emily Hollenbeck stands for a portrait at the American Museum of Natural History’s Rose Center in New York on Jan. 12, 2024. Hollenbeck, a deep brain stimulation patient being treated for depression, says, “The stress is pretty extreme at times, but I’m able to see and remember, even on a bodily level, that I’m going to be OK. ... If I hadn’t had DBS, I’m pretty sure I would not be alive today.” (AP Photo/Mary Conlon)

Emily Hollenbeck, a deep brain stimulation therapy patient, demonstrates how she makes circles in the air with her arms that are interpreted and projected as light on an interactive wall at Mount Sinai’s “Q-Lab” in New York on Dec. 20, 2023. Researchers use various methods to collect data as patients recover. Like many other patients, she moves her arms faster now that she’s doing better. (AP Photo/Mary Conlon)

Dr. Helen Mayberg, founding director of The Nash Family Center for Advanced Circuit Therapeutics, speaks to patient Emily Hollenbeck in her office at Mount Sinai West in New York on Dec. 20, 2023. Recent research by Mayberg and others published in the journal Nature showed it’s possible to provide a “readout” of how someone is doing at any given time. Analyzing the brain activity of deep brain stimulation patients, researchers found a unique pattern that reflects the recovery process. (AP Photo/Mary Conlon)

Emily Hollenbeck, a deep brain stimulation therapy patient being treated for depression, stands for a portrait at the American Museum of Natural History’s Rose Center in New York on Jan. 12, 2024. “When I was depressed, I couldn’t listen to music. It sounded and felt like I was listening to radio static,” she says. “Then on a sunny day in the summer, I was walking down the street listening to a song. I just felt this buoyancy, this, ‘Oh, I want to walk more, I want to go and do things!’ And I realized I’m getting better.” She only wishes the therapy had been there for her parents. (AP Photo/Mary Conlon)

Neuroimaging expert Ki Seung Choi explains how he uses brain scans to locate the exact spot in a particular patient where electrodes for deep brain stimulation therapy should be placed, at Mount Sinai West in New York on Dec. 20, 2023. Dr. Helen Mayberg, founding director of The Nash Family Center for Advanced Circuit Therapeutics, says, “Everybody’s brain is a little different, just like people’s eyes are a little further apart or a nose is a little bigger or smaller.” (AP Photo/Mary Conlon)

Emily Hollenbeck stands for a portrait at the American Museum of Natural History’s Rose Center in New York on Jan. 12, 2024. Hollenbeck lived with a deep, recurring depression she likened to a black hole, where gravity felt so strong and her limbs so heavy she could barely move. She was willing to try something extreme: Having electrodes implanted in her brain as part of an experimental therapy. (AP Photo/Mary Conlon)

A sample pacemaker-like device, used for deep brain stimulation therapy, and its electrodes which are implanted into a specific site in the brain are displayed at Mount Sinai West in New York on Dec. 20, 2023. The device controls the amount of electrical stimulation to the brain and delivers constant low-voltage pulses. Patient Emily Hollenbeck calls it “continuous Prozac.” (AP Photo/Mary Conlon)

This series of PET brain scan images provided by Mount Sinai in 2024 shows changes in patient Emily Hollenbeck with deep brain stimulation therapy. Analyzing the brain activity of DBS patients, researchers found a unique pattern that reflects the recovery process. (Mount Sinai via AP)

research articles in depression

NEW YORK (AP) — Emily Hollenbeck lived with a deep, recurring depression she likened to a black hole, where gravity felt so strong and her limbs so heavy she could barely move. She knew the illness could kill her. Both of her parents had taken their lives.

She was willing to try something extreme: Having electrodes implanted in her brain as part of an experimental therapy.

Researchers say the treatment —- called deep brain stimulation , or DBS — could eventually help many of the nearly 3 million Americans like her with depression that resists other treatments. It’s approved for conditions such as Parkinson’s disease and epilepsy, and many doctors and patients hope it will become more widely available for depression soon.

The treatment gives patients targeted electrical impulses, much like a pacemaker for the brain. A growing body of recent research is promising, with more underway — although two large studies that showed no advantage to using DBS for depression temporarily halted progress, and some scientists continue to raise concerns.

Meanwhile, the Food and Drug Administration has agreed to speed up its review of Abbott Laboratories’ request to use its DBS devices for treatment-resistant depression.

Emily Hollenbeck, a deep brain stimulation therapy patient being treated for depression, stands for a portrait at the American Museum of Natural History's Rose Center in New York on Jan. 12, 2024. “When I was depressed, I couldn’t listen to music. It sounded and felt like I was listening to radio static,” she says. “Then on a sunny day in the summer, I was walking down the street listening to a song. I just felt this buoyancy, this, ‘Oh, I want to walk more, I want to go and do things!’ And I realized I’m getting better.” She only wishes the therapy had been there for her parents. (AP Photo/Mary Conlon)

Emily Hollenbeck, a deep brain stimulation therapy patient being treated for depression, stands for a portrait at the American Museum of Natural History’s Rose Center in New York on Jan. 12, 2024. (AP Photo/Mary Conlon)

“At first I was blown away because the concept of it seems so intense. Like, it’s brain surgery. You have wires embedded in your brain,” said Hollenbeck, who is part of ongoing research at Mount Sinai West. “But I also felt like at that point I tried everything, and I was desperate for an answer.”

“NOTHING ELSE WAS WORKING”

Hollenbeck suffered from depression symptoms as a child growing up in poverty and occasional homelessness. But her first major bout happened in college, after her father’s suicide in 2009. Another hit during a Teach for America stint, leaving her almost immobilized and worried she’d lose her classroom job and sink into poverty again. She landed in the hospital.

“I ended up having sort of an on-and-off pattern,” she said. After responding to medication for a while, she’d relapse.

She managed to earn a doctorate in psychology, even after losing her mom in her last year of grad school. But the black hole always returned to pull her in. At times, she said, she thought about ending her life.

She said she’d exhausted all options, including electroconvulsive therapy, when a doctor told her about DBS three years ago.

“Nothing else was working,” she said.

She became one of only a few hundred treated with DBS for depression.

Hollenbeck had the brain surgery while sedated but awake. Dr. Brian Kopell, who directs Mount Sinai’s Center for Neuromodulation, placed thin metal electrodes in a region of her brain called the subcallosal cingulate cortex, which regulates emotional behavior and is involved in feelings of sadness.

A sample pacemaker-like device, used for deep brain stimulation therapy, and its electrodes which are implanted into a specific site in the brain are displayed at Mount Sinai West in New York on Dec. 20, 2023. The device controls the amount of electrical stimulation to the brain and delivers constant low-voltage pulses. Patient Emily Hollenbeck calls it “continuous Prozac.” (AP Photo/Mary Conlon)

A sample pacemaker-like device, used for deep brain stimulation therapy, and its electrodes which are implanted into a specific site in the brain are displayed at Mount Sinai West in New York on Dec. 20, 2023. (AP Photo/Mary Conlon)

The electrodes are connected by an internal wire to a device placed under the skin in her chest, which controls the amount of electrical stimulation and delivers constant low-voltage pulses. Hollenbeck calls it “continuous Prozac.”

Doctors say the stimulation helps because electricity speaks the brain’s language. Neurons communicate using electrical and chemical signals.

In normal brains, Kopell said, electrical activity reverberates unimpeded in all areas, in a sort of dance. In depression, the dancers get stuck within the brain’s emotional circuitry. DBS seems to “unstick the circuit,” he said, allowing the brain to do what it normally would.

Hollenbeck said the effect was almost immediate.

“The first day after surgery, she started feeling a lifting of that negative mood, of the heaviness,” said her psychiatrist, Dr. Martijn Figee. “I remember her telling me that she was able to enjoy Vietnamese takeout for the first time in years and really taste the food. She started to decorate her home, which had been completely empty since she moved to New York.”

Emily Hollenbeck, a deep brain stimulation therapy patient, demonstrates an EEG device that records brain activity as she reacts to short videos at Mount Sinai’s “Q-Lab” in New York on Dec. 20, 2023. Dr. Brian Kopell, who directs Mount Sinai's Center for Neuromodulation, says in normal brains electrical activity reverberates unimpeded in all areas, in a sort of dance. In depression, the dancers get stuck within the brain’s emotional circuitry. DBS seems to “unstick the circuit,” he says, allowing the brain to do what it normally would. (AP Photo/Mary Conlon)

For Hollenbeck, the most profound change was finding pleasure in music again.

“When I was depressed, I couldn’t listen to music. It sounded and felt like I was listening to radio static,” she said. “Then on a sunny day in the summer, I was walking down the street listening to a song. I just felt this buoyancy, this, ‘Oh, I want to walk more, I want to go and do things!’ And I realized I’m getting better.”

She only wishes the therapy had been there for her parents.

THE TREATMENT’S HISTORY

The road to this treatment stretches back two decades, when neurologist Dr. Helen Mayberg led promising early research.

Dr. Helen Mayberg, founding director of The Nash Family Center for Advanced Circuit Therapeutics, speaks to patient Emily Hollenbeck in her office at Mount Sinai West in New York on Dec. 20, 2023. Recent research by Mayberg and others published in the journal Nature showed it’s possible to provide a “readout” of how someone is doing at any given time. Analyzing the brain activity of deep brain stimulation patients, researchers found a unique pattern that reflects the recovery process. (AP Photo/Mary Conlon)

Dr. Helen Mayberg, founding director of The Nash Family Center for Advanced Circuit Therapeutics, speaks to patient Emily Hollenbeck in her office at Mount Sinai West in New York on Dec. 20, 2023. (AP Photo/Mary Conlon)

But setbacks followed. Large studies launched more than a dozen years ago showed no significant difference in response rates for treated and untreated groups. Dr. Katherine Scangos, a psychiatrist at the University of California, San Francisco, also researching DBS and depression, cited a couple of reasons: The treatment wasn’t personalized, and researchers looked at outcomes over a matter of weeks.

Some later research showed depression patients had stable, long-term relief from DBS when observed over years. Overall, across different brain targets, DBS for depression is associated with average response rates of 60%, one 2022 study said.

Treatments being tested by various teams are much more tailored to individuals today. Mount Sinai’s team is one of the most prominent researching DBS for depression in the U.S. There, a neuroimaging expert uses brain images to locate the exact spot for Kopell to place electrodes.

“We have a template, a blueprint of exactly where we’re going to go,” said Mayberg, a pioneer in DBS research and founding director of The Nash Family Center for Advanced Circuit Therapeutics at Mount Sinai. “Everybody’s brain is a little different, just like people’s eyes are a little further apart or a nose is a little bigger or smaller.”

This series of PET brain scan images provided by Mount Sinai in 2024 shows changes in patient Emily Hollenbeck with deep brain stimulation therapy. Analyzing the brain activity of DBS patients, researchers found a unique pattern that reflects the recovery process. (Mount Sinai via AP)

This series of PET brain scan images provided by Mount Sinai in 2024 shows changes in patient Emily Hollenbeck with deep brain stimulation therapy. (Mount Sinai via AP)

Other research teams also tailor treatment to patients, although their methods are slightly different. Scangos and her colleagues are studying various targets in the brain and delivering stimulation only when needed for severe symptoms. She said the best therapy may end up being a combination of approaches.

As teams keep working, Abbott is launching a big clinical trial this year, ahead of a potential FDA decision.

“The field is advancing quite quickly,” Scangos said. “I’m hoping we will have approval within a short time.”

But some doctors are skeptical, pointing to potential complications such as bleeding, stroke or infection after surgery.

Dr. Stanley Caroff, an emeritus professor of psychiatry at the University of Pennsylvania, said scientists still don’t know the exact pathways or mechanisms in the brain that produce depression, which is why it’s hard to pick a site to stimulate. It’s also tough to select the right patients for DBS, he said, and approved, successful treatments for depression are available.

“I believe from a psychiatric point of view, the science is not there,” he said of DBS for depression.

MOVING FORWARD

Hollenbeck acknowledges DBS hasn’t been a cure-all; she still takes medicines for depression and needs ongoing care.

She recently visited Mayberg in her office and discussed recovery. “It’s not about being happy all the time,” the doctor told her. “It’s about making progress.”

That’s what researchers are studying now — how to track progress.

Emily Hollenbeck, a deep brain stimulation therapy patient, demonstrates how she makes circles in the air with her arms that are interpreted and projected as light on an interactive wall at Mount Sinai’s “Q-Lab” in New York on Dec. 20, 2023. Researchers use various methods to collect data as patients recover. Like many other patients, she moves her arms faster now that she’s doing better. (AP Photo/Mary Conlon)

Emily Hollenbeck, a deep brain stimulation therapy patient, demonstrates how she makes circles in the air with her arms that are interpreted and projected as light on an interactive wall at Mount Sinai’s “Q-Lab” in New York on Dec. 20, 2023. (AP Photo/Mary Conlon)

Recent research by Mayberg and others in the journal Nature showed it’s possible to provide a “readout” of how someone is doing at any given time. Analyzing the brain activity of DBS patients, researchers found a unique pattern that reflects the recovery process. This gives them an objective way to observe how people get better and distinguish between impending depression and typical mood fluctuations.

Scientists are confirming those findings using newer DBS devices in a group of patients that includes Hollenbeck.

She and other participants do their part largely at home. She gives researchers regular brain recordings by logging onto a tablet, putting a remote above the pacemaker-like device in her chest and sending the data. She answers questions that pop up about how she feels. Then she records a video that will be analyzed for things such as facial expression and speech.

Psychiatrist Dr. Martijn Figee shows a tablet used to program the amount of deep brain electrical stimulation given to patients at Mount Sinai West in New York on Dec. 20, 2023. With Emily Hollenbeck, “The first day after surgery, she started feeling a lifting of that negative mood, of the heaviness,” said Figee, her psychiatrist. “I remember her telling me that she was able to enjoy Vietnamese takeout for the first time in years and really taste the food. She started to decorate her home, which had been completely empty since she moved to New York.” (AP Photo/Mary Conlon)

Occasionally, she goes into Mount Sinai’s “Q-Lab,” an immersive environment where scientists do quantitative research collecting all sorts of data, including how she moves in a virtual forest or makes circles in the air with her arms. Like many other patients, she moves her arms faster now that she’s doing better.

Data from recordings and visits are combined with other information, such as life events, to chart how she’s doing. This helps guide doctors’ decisions, such as whether to increase her dose of electricity – which they did once.

On a recent morning, Hollenbeck moved her collar and brushed her hair aside to reveal scars on her chest and head from her DBS surgery. To her, they’re signs of how far she’s come.

She makes her way around the city, taking walks in the park and going to libraries, which were a refuge in childhood. She no longer worries that normal life challenges will trigger a crushing depression.

Emily Hollenbeck stands for a portrait at the American Museum of Natural History's Rose Center in New York on Jan. 12, 2024. Hollenbeck, a deep brain stimulation patient being treated for depression, says, “The stress is pretty extreme at times, but I’m able to see and remember, even on a bodily level, that I’m going to be OK. ... If I hadn’t had DBS, I’m pretty sure I would not be alive today.” (AP Photo/Mary Conlon)

Emily Hollenbeck stands for a portrait at the American Museum of Natural History’s Rose Center in New York on Jan. 12, 2024. (AP Photo/Mary Conlon)

“The stress is pretty extreme at times, but I’m able to see and remember, even on a bodily level, that I’m going to be OK,” she said.

“If I hadn’t had DBS, I’m pretty sure I would not be alive today.”

The Associated Press Health and Science Department receives support from the Howard Hughes Medical Institute’s Science and Educational Media Group. The AP is solely responsible for all content.

LAURA UNGAR

ORIGINAL RESEARCH article

Perceived academic stress and depression: the mediation role of mobile phone addiction and sleep quality.

\nXin Zhang&#x;

  • 1 Department of Social Medicine, School of Public Health, Health Management College, Harbin Medical University, Harbin, China
  • 2 Institute of Food Safety and School Health, Heilongjiang Center for Disease Control and Prevention, Harbin, China
  • 3 Department of Educational Administration, Ningbo College of Health Sciences, Ningbo, China
  • 4 Department of Elderly Healthcare and Management, School of Health Services and Management, Ningbo College of Health Sciences, Ningbo, China

Background: Although academic stress is a well-known risk factor for students' depression, little is known about the possible psychological mechanisms underlying this association. In this study, we investigated the prevalence of depression and sleep disturbance among Chinese students, examined the relationship between perceived academic stress and depression, considered if mobile phone addiction and sleep quality is a mediator of this relationship, and tested if mobile phone addiction and sleep quality together play a serial mediating role in the influence of perceived academic stress on depression.

Method: A cross-sectional survey was conducted among students from September to December 2018 in Heilongjiang Province, China. The final analysis included 5,109 students. Mobile phone addiction, sleep quality, and depressive symptoms were assessed using the Mobile Phone Addiction Index, Pittsburgh Sleep Quality Index, and Center for Epidemiologic Studies-Depression scales, respectively. The serial mediation model was used to analyse the relationship between perceived academic stress, mobile phone addiction, sleep quality, and depression.

Results: Among all participants, the prevalence of depressive symptoms and sleep disturbance was 28.69 and 27.95%, respectively. High school students showed the highest scores of perceived academic stress (2.68 ± 1.06), and the highest prevalence of depressive symptoms (33.14%) and sleep disturbance (36.47%). The serial mediation model indicated that perceived academic stress was a significant predictor of depression (B = 0.10, SE = 0.02, 95% CI = 0.06 – 0.13). Additionally, mobile phone addiction (B = 0.08, 95% boot CI = 0.06–0.11) and sleep quality (B = 0.27, 95% boot CI = 0.22–0.33) played a mediating role between perceived academic stress and depression. Mobile phone addiction and sleep quality together played a serial mediating role in the influence of perceived academic stress on depression (B = 0.11, 95% boot CI = 0.08–0.14). Furthermore, the indirect effect (i.e., the mediating effect of mobile phone addiction and sleep quality) was significant and accounted for 64.01% of the total effect.

Conclusions: Our research results underscore the need for stakeholders—including family members, educators, and policy makers—to take preventative intervention measures to address depression among Chinese students, especially high school students.

- Perceived academic stress significantly predicts depression.

- Sleep quality mediates perceived academic stress and depression.

- Mobile phone addiction mediates perceived academic stress and depression.

- Mobile phone addiction and sleep quality together play a serially mediating role in the influence of PAS on depression.

Introduction

Depression (major depressive disorder) is a widespread chronic medical illness that can influence mood, thoughts, and physical health ( 1 ), and is a severe problem faced by students worldwide. A meta-analysis that included 183 studies from 43 countries shows that the overall pooled crude prevalence of depression was 27.2% among medical students ( 2 ). Previous studies demonstrated that the prevalence of depression was 51.3, 38.3, 28.4, and 30.6% among Indian students ( 3 ), Japanese adolescents ( 4 ), Chinese university students ( 5 ), and Cameroon medical students ( 6 ), respectively. It is important to evaluate the prevalence of depressive symptoms and explore the effect mechanism of depressive symptoms to protect students from the harmful effects of depression. Studies related to students' depressive symptoms often focus on a particular group of students, such as medical ( 2 ), college ( 7 ), and university students ( 8 ), and scant research exists about depressive symptoms among students at different levels of education. Many risk factors have been associated with depression, including being female ( 9 , 10 ), life stressors ( 9 , 10 ), physical and mental factors, social media addiction ( 11 ), and parental factors, including parental psychopathology and parenting attachment ( 12 ). Stress has been shown to be one of the most important risk factors of depression, and numerous studies have demonstrated that stress plays an important role in the emergence of depression ( 13 – 15 ). For example, Torres-Berrío et al. supposed that depression is caused by a combination of genetic predisposition and life events ( 16 ). Stress often leads to adverse consequences—such as depression and anxiety ( 17 – 19 ), mobile phone addiction (MPA) ( 20 , 21 ), poor sleep quality (PSQ) ( 22 , 23 ), changes in legal drug consumption ( 24 ), cardiovascular disease ( 25 ), and worsens the outcomes of many medical illnesses ( 26 ), potentially even leading to suicide ( 27 , 28 ). Additionally, various physical and mental factors influence the prevalence of depressive symptoms, such as PSQ ( 29 ), bodily pain ( 30 ), and poor cognitive and physical functioning ( 31 ). Scholars have noted that there is a remarkable association between alterations in sleep patterns and depression ( 32 ). Furthermore, in the internet age, studies show that individuals who experience depressive symptoms often suffer from social media addictions, such as Facebook ( 33 , 34 ), mobile phone ( 35 ), and internet addictions ( 8 ). For instance, Ivanova found that MPA was positively related to both depression and loneliness in Ukrainian students ( 36 ).

In China, the school environment and parental practices contribute to the extraordinarily high expectations of students' academic performance ( 37 ). Chinese students experience high levels of academic stress throughout their academic careers, including numerous, intense examinations—such as end-of-term tests and the standardized senior high school and university entrance examinations—and a heavy homework burden ( 37 ). Scholars have demonstrated that Chinese students experience sleep deprivation owing to this culture of academic achievement. A study of 9,392 Chinese students in primary education through university levels showed that 35.6% of participants slept <7 h a day ( 38 ). In addition to the threat of academic stress and sleep deprivation, MPA is a risk factor affecting Chinese students' physical and mental health. Mobile phones have become an integral part of students' quotidian lives—Meng's survey from December 2016 to January 2017 found that 100% of the college students had mobile phones ( 39 )—and the prevalence of problematic mobile phone use has been found to be 28.2% among Chinese college students ( 40 ). Our study explored the correlations between perceived academic stress (PAS), MPA, sleep quality, and depression among Chinese students in middle school through college levels. Based on previous literature, our study proposed research hypotheses, and tested hypothesis by using survey data on Chinese students. To our knowledge, this was the first study to investigate relations between these variables among Chinese students by using the serial mediation model.

Literature Review and Research Hypotheses

Academic stress.

Academic concerns are the most important sources of chronic and sporadic stress for young people in both Western and Asian countries ( 41 ). Academic stress is defined as a student's psychological state resulting from continuous social and self-imposed pressure in a school environment that depletes the student's psychological reserves ( 42 , 43 ). Students experience academic stress throughout their secondary school ( 41 ), high school ( 44 ), and university ( 45 , 46 ), educational careers. Studies have shown that academic stress has been positively associated with depression ( 41 ), PSQ ( 24 , 47 ), and MPA ( 48 ) among students. Jayanthi observed that, compared to adolescents who do not experience academic stress, adolescents who experienced academic stress were 2.4 times more likely to have depressive symptoms ( 41 ). Other studies have found that there is a relationship between high academic stress and PSQ ( 47 , 49 ). However, scholars have not adequately addressed the adverse consequences (e.g., depression, PSQ, and MPA) of Chinese students' academic stress. Hence, we propose the following hypotheses:

H1 : PAS is positively associated with depression.

H2 : PAS is positively associated with MPA.

H3 : PAS is positively associated with PSQ.

MPA is one of the most common behavioral (i.e., non-drug) addictions ( 48 ), and is accompanied by negative effects, such as PSQ ( 50 ), depression ( 35 ), and impaired academic performance ( 51 ). The positive relationship between MPA and PSQ has been proved in previous studies, including a longitudinal study conducted among Korean adolescents ( 52 ) and a one-year prospective study among Chinese college students ( 50 ). Zhang found that among Chinese university students, there is a significant positive relationship between smartphone addiction and bedtime procrastination, which is one of the indicators of PSQ ( 53 ). Hence, we propose the following hypothesis:

H4 : MPA is positively associated with PSQ.

Similarly, the positive relationship between MPA and depression has been proved in previous studies, including a cross-sectional study conducted among Saudi university students ( 35 ), a cross-sectional study among Ukrainian college students ( 36 ), and a systematic review of relations between problematic smartphone use, anxiety and depression psychopathology ( 54 ). Furthermore, another study based on three cohorts of Korean children and adolescents confirmed the bidirectional relationship between MPA and depression ( 55 ). Hence, we propose the following hypothesis:

H5 : MPA is positively associated with depression.

Researchers have documented that stress is associated with MPA, and that MPA is associated with depression. For example, according to Wan et al., smartphone addictions are significantly positively associated with both depression and stress among Malaysian public university students ( 56 ). However, it is unclear if MPA mediates the relationship between PAS and depression. Hence, we propose the following hypothesis:

H6 : MPA mediates the relationship between PAS and depression.

Sleep Quality

Sleep disturbance has complex associations with depression (major depressive disorder) ( 31 ), and is a common physical symptom of depression. Numerous studies have confirmed the remarkable association between PSQ and depression ( 29 , 57 , 58 ). For example, Okun et al. found that PSQ is positively related to depression symptoms in postpartum women ( 29 ). Hence, we propose the following hypothesis:

H7 : PSQ is positively associated with depression.

Scholars have also demonstrated that there are relationships between stress, PSQ, and depression. A prospective birth cohort study showed that PSQ is associated with stress and depression symptoms among Chinese pregnant women ( 58 ). Zhang et al. found that perceived stress is associated with sleep quality and depressive symptoms among Chinese nursing students ( 59 ). However, it has not been documented if sleep quality mediates the relationship between PAS and depression among Chinese students. Hence, we propose the following hypothesis:

H8: Sleep quality mediates the relationship between PAS and depression.

Mobile Phone Addiction and Sleep Quality and the Relationship Between Perceived Academic Stress and Depression

Scholars have posited that there are significant associations between MPA, depression levels, and sleep quality. Demirci found that there were positive correlations between MPA, depression levels, and sleep quality ( 60 ). The results of Kaya's multivariate regression analysis showed a relationship between smartphone usage, PSQ, and depression in university students ( 57 ). A recent meta-analysis also found that there are positive correlations between MPA, depression, and sleep quality ( 61 ). Another literature review and case study found that depressive symptoms are associated with screen time-induced poor sleep, digital device night use, and mobile phone dependency ( 62 ). Although these studies explored the correlations between MPA, sleep quality, and depression among students, several scholars have added academic stress into the relationship—for example, a review found that sleep disturbance, anxiety, stress, and depression have been associated with problematic mobile phone use ( 63 ). There still exist gaps in the literature on how PAS influences depression. First, few scholars have focused on PAS, MPA, sleep quality, and depression among Chinese students. Second, the underlying mediating mechanisms that account for this association have been disregarded partly. Based on H6 and H8, it remains unclear if MPA and sleep quality serially mediate the relationship between PAS and depression. Therefore, we propose the following hypothesis:

H9: MPA and sleep quality serially mediate the relationship between PAS and depression.

Study Objectives

In this study, our primary aim was to investigate the prevalence of depression and sleep disturbance among Chinese students. Our secondary aim was to test if there were relationships between PAS, MPA, sleep quality, and depression. First, we tested if there was a relationship between PAS and depression among Chinese students (H1: PAS is positively associated with depression). Second, we tested if MPA was a mediator of the relationship between PAS and depression (H2: PAS is positively associated with MPA, H5: MPA is positively associated with depression, and H6: MPA mediates the relationship between PAS and depression). Third, we tested if sleep quality was a mediator of the relationship between PAS and MPA (H3: PAS is positively associated with PSQ, H7: PSQ is positively associated with depression, and H8: Sleep quality mediates the relationship between PAS and depression). Finally, we also tested if MPA and sleep quality together played a serial mediating role in the influence of PAS on depression (H4: MPA is positively associated with PSQ and H9: MPA and sleep quality serially mediate the relationship between PAS and depression).

Data were collected from a cross-sectional questionnaire survey that was conducted from September to December 2018 in Heilongjiang Province, China, by the Heilongjiang Center for Disease Control and Prevention. A multistage cluster sampling method was used. In the first stage, three cities of Heilongjiang province were randomly selected by economic characteristics. In the second stage, one urban district and one rural township were chosen at random. In the third stage, two middle schools were randomly selected in each urban district and rural township; Since nine-year compulsory education was implemented in China, high school education is not included in the nine-year compulsory education, high schools are more in urban districts than in rural townships, two high schools and one high school were randomly selected in urban district and rural township, respectively; Since vocational high schools and universities are scarce in rural townships, one vocational high school and one college were randomly selected from the urban district. In the fourth stage, two classes were randomly selected from each grade of middle school, high school, vocational high school, and from grades 1, 2, and 3 in college. Since senior students may have been looking for a job or working as an intern, some of them were not on campus, they were not been investigated. Finally, four middle schools, three high schools, one vocational high school, and one college were randomly selected within each city (Harbin, Jiamusi, and Jixi) of Heilongjiang Province. Data were collected through a self-administered questionnaire distributed in class. Students completed the survey within 1 h, while a well-trained member of the research group supervised. All the students were informed of the purpose of the study and assured that their identities would remain confidential. Students and their parents provided written informed assent to participate in the study.

Participants

Finally, we recruited 6,480 students in our investigation; 6,430 (99.23%) valid questionnaires were analyzed after excluding those with incomplete information. Participants were included in the sample if they had one constant internet-accessible mobile phone, which is similar with previous studies ( 64 – 68 ). A total of 5,109 (79.46%) participants reported having one constant internet-accessible mobile phone at the time of the survey. The final sample comprised 1,904 middle school students from grades 1, 2, and 3, respectively; 1,859 high school students from grades 1, 2, and 3, respectively; 660 vocational high school students from grades 1, 2, and 3, respectively; and 686 college students from grades 1, 2 and 3, respectively. Of these participants, there were 2,422 (47.41%) boys and 2,687 (52.59%) girls; on average, the mean age of participants was 15.53 years, with a standard deviation of 2.22, ranging from 11 to 25 years. Approval was obtained from the Medical Research Ethics Committee of Harbin Medical University and the principals of the participating schools.

Perceived Academic Stress

Consistent with previous studies ( 69 – 71 ), PAS was measured using one self-report item “How much academic stress did you feel in the study during the past month?” using a 5-point Likert scale where 1 = “No,” 2 = “relatively low,” 3 = “average/general,” 4 =“relatively high” and 5 = “extremely heavy,” with a higher score indicating more PAS.

Center for Epidemiologic Studies-Depression Scale. The 20-item CES-D developed by Radloff ( 72 ) is a self-report measure that has been widely used to assess depressive symptoms in different populations ( 73 ). The reliability and validity of the CES-D have been tested among Chinese populations ( 74 ). The CES-D, when used in Chinese adolescents and university students, has shown good reliability ( 75 – 78 ), as well as good validity ( 77 , 78 ). There are four components of CES-D, namely somatic and retarded activity, depressed affect, positive affect, and interpersonal relationships. Among the 20 items, four (items 4, 8, 12, and 16) are reversed scores. All items are evaluated on a 4-point Likert scale in relation to their incidence during the previous week, and are scored from 0 to 3 (0 = not at all, 1 = a little, 2 = some, 3 = a lot); total possible scores thus range from 0 to 60, with higher scores indicating greater number of symptoms ( 79 ).

For the original CES-D scale, a total score of 16 or greater is considered as indicative of subthreshold depression ( 72 ). Many studies have evaluated the diagnostic accuracy of the CES-D to detect depression among the general population and proposed a variety of cut-off scores, such as a cut-off score of 21 for Chinese patients with type 2 diabetes ( 80 ), and a cut-off score of 22 for the older Chinese population ( 81 ). However, the cut-off score of 16 has been widely used for Chinese adolescents and university students ( 7 , 76 , 82 – 84 ). Therefore, the same cut-off score has been used in our study too. Students with CES-D scores between 16 and 21 were defined as “mildly depressed,” between 21 and 24 as “moderately depressed,” and ≥ 25 as “severely depressed” ( 83 ). The CFA on the four-factor model showed a good model fit, with χ 2 = 16.54, df = 1, P < 0.000, RMSEA = 0.06, SRMR = 0.01, CFI = 0.99, TLI = 0.98. Additionally, the Cronbach's alpha coefficient was 0.84 for the total scale, all four dimensions had acceptable reliability with Cronbach's alpha coefficient of 0.70, 0.83, 0.78, and 0.62.

Mobile Phone Use Situation and Mobile Phone Addiction

Mobile phone use situation was assessed by three items. First, “How many hours do you use your mobile phone every day?” to which participants answered with one of four options: “less than a half hour,” “a half hour to one hour,” “one to two hours,” or “more than two hours.” Second, “How long have you had a mobile phone?” to which participants answered “ <1 year,” “1–2 years,” “2–3 years,” or “more than 3 years.” Third, “How much do you spend on mobile phone charges every month?” to which participants answered “less 30 yuan,” “30–50 yuan,” “50–100 yuan,” or “more than 100 yuan.”

The Mobile Phone Addiction Index (MPAI) was used in our study ( 85 ). Participants rated the 17 items on a 5-point Likert scale ranging from 1 (not at all) to 5 (always). Higher scores indicated greater addiction to mobile phones ( 86 ). There are four components of MPAI, namely inability to control craving, feeling of anxiety and being lost, withdrawal or escape, and productivity loss. The Confirmatory Factor Analysis (CFA) on the four-factor model showed a good model fit, with χ 2 = 6.44, df = 1, p < 0.05, RMSEA = 0.03, SRMR = 0.004, CFI = 0.99, TLI = 0.99. Additionally, the Cronbach's alpha coefficient was 0.90 for the total scale. All four dimensions had satisfactory reliability with Cronbach's alpha coefficient of 0.76, 0.81, 0.85, and 0.75.

The Pittsburgh Sleep Quality Index (PSQI) was used in our study ( 87 ). PSQI scale contains 19 items covering seven components: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction. Each component was scored from 0 (no difficulty) to 3 (severe difficulty). The total score was calculated from the seven component scores, ranging from 0 to 21. A score of more than 5 implied poor sleep ( 87 ). The CFA on the seven-factor model showed a good model fit, with χ 2 = 79.49, df = 11, P < 0.000, RMSEA = 0.04, SRMR = 0.02, CFI = 0.99, TLI = 0.98. Additionally, Cronbach's alpha coefficient was 0.624 for the PSQI scale in our study.

Data Analyses

SPSS version 19.0. and Mplus 7.0 were used to analyse data in our study. Descriptive analyses were first conducted of participants' characteristics, participants' mobile phone use and the prevalence of sleep disturbance, MPA, and depression. We tested the reliability and validity of the MPAI scale, PSQI scale and CES-D scale by examining their Cronbach's alpha coefficient and performing a CFA. Spearman's correlation analysis was performed to examine the general relationships among the four variables—PAS, MPA, sleep quality, and depression. A structural equation model (SEM) was built to examine hypotheses. We tested the mediating role of MPA and sleep quality; the constructed serial mediation model included three latent variables (MPA, sleep quality and depression) and one manifest variable (PAS), PAS was the independent variable, depression was the dependent variable, and MPA and sleep quality were the mediating variables ( 88 ). The bootstrapping analyses used 5,000 samples at the 95% confidence interval (CI) to indicate significance.

To determine whether the model fits the data well, multiple indices were tested, including (1) the model χ 2 and its p value, in which non-significance is desirable for good fit. With increasing sample size and a fixed degree of freedom, the χ 2 value increases. It is difficult to get a nonsignificant chi-square (indicative of good fit) when sample sizes are over 200 ( 89 ). This can lead to a problem where plausible models might be rejected. Because this statistic is sensitive to the sample size, inspection of the other fit indices is recommended ( 90 ). (2) The root mean square error of approximation (RMSEA) in which values ranging from 0.05 to 0.08 represent adequate fit, and values <0.05 indicate good fit. (3) The standardized root mean square residual (SRMR) in which values are ≤0.08 indicate good fit. (4) The comparative fit index (CFI), in which values range from 0.90 to 0.95 indicate an adequate fit and values ≥0.95 indicate a good fit, and (5) the Tacker-Lewis index (TLI) in which values >0.90 indicate a good fit.

Descriptive Statistics

The mean scores of PAS were 2.61 ± 1.03, 2.68 ± 1.06, 2.13 ± 0.98, and 2.29 ±0.96 for middle school students, high school students, vocational high school students, and college school students, respectively.

Among the participants, 45.55% used their mobile phone more than 2 h daily; 39.5% of the participants had a mobile phone for more than 3 years; 53.24% of the participants spent more than or equal to 30 yuan on mobile phone charges every month ( Table 1 ). The mean MPAI score of all the participants was 30.62 ± 11.92.

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Table 1 . Participants' mobile phone use.

The prevalence of depressive symptoms was 28.69% ( n = 1,466) with a mean CES-D score of 12.52 ± 8.86. Prevalence of depression at a mild level (CES-D ≥ 16 and CES-D < 21), moderate level (CES-D ≥ 21 and CES-D < 25), and severe level (CES-D ≥ 25) was 12.62, 6.95, and 9.12%, respectively. The prevalence of depressive symptoms among high school students (33.14%) was the highest, while the prevalence of depressive symptoms among college students (21.43%) was the lowest ( Table 2 ).

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Table 2 . Depression classifications of participants.

The prevalence of sleep disturbance was 27.95% ( n = 1,428) with a mean global PSQI score of 4.29 ± 2.59. The prevalence of sleep disturbance among high school students (36.47%) was the highest, while the prevalence of sleep disturbance among middle school students (20.75%) was the lowest. The average sleep time and sleep latency were 7.40 ± 1.28 h and 15.81 ± 12.48 min, respectively. Among the participants, 14.50% reported that they had bad or very bad sleep quality; 36.29% reported that their sleep latency was more than 15 min; 50.89% reported that they slept ≤7 h a day; 12.62% reported that their sleep efficiency was ≤85%; 67.59% reported that they experienced sleep disturbances; 2.90% of them reported that they used sleep medication; and 78.80% reported that they had daytime dysfunction ( Table 3 ).

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Table 3 . Prevalence of sleep disturbance for participants at different education levels.

Means, Standard Deviation (SD) and correlations of the main variables in the mediation model are shown in Table 4 . The results, indicating that the variables were significantly and positively correlated, provide initial support for the hypotheses of this study, and act as a foundation of the serial mediation model.

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Table 4 . Means, SD, Pearson's correlation coefficient of variables.

Test for Serial Mediation Model

SEM was used to provide the fit indexes of the serial mediation model. A model was constructed with MPA (M1) as a mediator and sleep quality (M2) as another mediator. In this model, PAS was set as the predictor (X) and depression as the outcome (Y). Results of the serial mediation model indicated that the constructed model exhibited a satisfactory fit with the data: χ 2 = 1,196.50, df = 95, P < 0.000, SRMR = 0.04, RMSEA = 0.05, CFI = 0.95, and TLI = 0.94.

First, PAS was positively associated with depression (B = 0.10, SE = 0.02, 95% CI = 0.06–0.13). Higher levels of PAS were related to higher levels of depression, and thus H1 was supported. Second, PAS positively predicted MPA (B = 0.18, SE = 0.02, 95% CI = 0.15–0.21). Higher levels of PAS were related to higher levels of MPA, and thus H2 was supported. Third, PAS was positively associated with PSQ (B = 0.23, SE = 0.02, 95% CI = 0.19–0.26). Higher levels of PAS were related to poorer sleep quality, and thus H3 was supported. Fourth, MPA was positively associated with PSQ (B = 0.51, SE = 0.02, 95% CI = 0.47–0.54). Higher levels of MPA were related to poorer sleep quality, and thus H4 was supported. Fifth, MPA was positively associated with depression (B = 0.17, SE = 0.02, 95% CI = 0.13–0.22). Higher levels of MPA were related to higher levels of depression, and thus H5 was supported. Last, PSQ was positively associated with depression (B = 0.44, SE = 0.03, 95% CI = 0.39–0.49). PSQ was related to higher levels of depression, and thus H7 was supported.

Total, Direct, and Indirect Effects

Table 5 shows all possible indirect effects of the mediation model. First, the indirect effect of PAS on depression through MPA was significant (B = 0.08, 95% boot CI = 0.06–0.11), and thus H6 was supported. Second, the indirect effect of PAS on depression through sleep quality was significant (B = 0.27, 95% boot CI = 0.22–0.33), and thus H8 was supported. Third, the indirect effect of PAS on depression through MPA and sleep quality was also significant (B = 0.11, 95% boot CI = 0.08–0.14), and thus H9 was also supported. The total indirect effect was B = 0.46, 95% boot CI = 0.40–0.53, and the mediating effect of MPA and sleep quality were significant ( P < 0.001), accounting for 64.01% (total indirect effect/total effect) of the total effect. The indirect effect related to sleep quality accounted for 82.61% of the total indirect effect, that is, (indirect effect 2 + indirect effect 3)/total indirect effect ( Table 5 ).

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Table 5 . Total, direct, and indirect effects.

Although academic stress is a well-known risk factor for depression in students, little is known about the possible psychological mechanisms underlying this association, or how MPA and PSQ—which also are risk factors of depression—operate to have an impact on it. The main aim of our study was to test if there is a relationship between PAS and depression and if MPA and sleep quality together play a serial mediating role in the influence of PAS on depression among Chinese students. To the best of our knowledge, this was the first study to investigate the relationship between the variables using SEM. As expected, the serial mediation model showed that PAS was a significant predictor of depression. MPA and sleep quality played a mediating role between PAS and depression. Furthermore, MPA and sleep quality together played a serial mediating role in the influence of PAS on depression. In our study, the indirect effect (i.e., the mediating effect of MPA and sleep quality) was significant and accounted for 64.01% of the total effect. Thus, apart from the direct effect of PAS on depression, the indirect effect of PAS on depression should be emphasized. Our findings provide significant insights into the risk factors for depressive symptoms in students.

Depression Among Students

According to studies that have focused on depression among Chinese students, the prevalence of depression varies from 22.0 to 68.5% ( 5 , 91 – 95 ). In our study, the prevalence of depressive symptoms was 28.69%. The differences across these studies may have resulted from temporal or regional disparities or variations in depression definitions and assessment methods. Depressive symptoms are related to many negative consequences, such as increased suicide risk among students ( 96 ) and increased college withdrawal rates ( 97 ). Controlling depressive symptoms among students can both protect human capital value from the societal perspective and maintain students' physical and mental health from the individual perspective. In our study, the most stressed, depressed, and sleep-deprived students were high school students. Thus, Chinese high school students' physical and mental health requires attention. In China, high school students are admitted to colleges and universities based on gaokao , the standardized National College Entrance Examination ( 98 ). These admission decisions are extremely important, as they impact high school students' future educational opportunities, career paths, and life experiences. Our research results prove that Chinese students experience the most stressful and competitive academic environment of their academic careers when they are in high school.

Mediating Role of Mobile Phone Addiction

Chinese students spend considerable time on mobile phones−45.55% of the participants spent more than 2 h daily on their mobile devices. 39.5% of participants had had a mobile phone for more than 3 years, while the mean age of participants was 15.53 years. Using the mediation model, we illustrated the mediating role of MPA in line with our hypothesis. As H6 predicted, MPA played a role in the path from PAS to depression. MPA could partially explain the association between PAS and depression among Chinese students—hence, MPA was not only an outcome of PAS, but also a catalyst of depression. First, we found that high levels of PAS were associated with high levels of MPA. This finding is consistent with previous research results ( 48 ) and suggests that PAS may be a significant trigger for students' negative behaviors—such as MPA. Scholars have posited that young people's digital distraction activities—including playing computer games and online surfing—may be interpreted as a way to avoid problems, reality, and stress ( 99 , 100 ). High levels of PAS were associated with high levels of MPA, which may be due to students' use of mobile phones to escape from academic stress. Second, we found that high levels of MPA were associated with high levels of depression, which is in line with existing research results ( 35 , 36 , 101 ). Students who experience MPA may neglect real-world social engagement ( 102 ) resulting in academic underperformance ( 103 ), clinical health symptoms ( 68 ), which are related to negative emotions—such as depression. Our findings add to the existing research that suggests that when students are facing academic stress, they may be addicted to their mobile phones to escape from academic stress, and thus the negative consequences of MPA may lead to depression in students.

Mediating Role of Sleep Quality

As H8 predicted, sleep quality is not only an outcome of academic pressure—it is also a catalyst of depression. Moreover, the indirect effect related to sleep quality accounted for 82.61% of the total indirect effect. Thus, compared to MPA, sleep quality played a more important role in the path from PAS to depression. We found that higher levels of PAS were associated with poorer sleep quality. This finding is consistent with previous research findings ( 24 , 47 ). For example, Waqas et al. demonstrated that perceived stress is a significant predictor of PSQ ( 47 ). In China, students exist in a prolonged competitive learning environment and experience unrelenting academic stress. To achieve better academic performance and meet the extraordinarily high expectations of parents and educators, Chinese students have heavy homework burdens and learning burdens, resulting in sleep deprivation. Furthermore, academic stress decreases sleep quality. According to Almojali et al., students who are not suffering from academic stress are less likely to experience PSQ ( 104 ). Previous studies have proved that sleep deficiency and sleep health problems are common among Chinese students ( 105 ). Our research results may explain why higher levels of PAS were related to poorer sleep quality.

We also found that high levels of PSQ were associated with high levels of depression, which is consistent with prior research findings ( 31 , 50 , 57 ). Scholars have proved that PSQ is related to multiple negative consequences that may lead to depression—including daytime dysfunction, poor academic performance, and fatigue ( 106 , 107 ). Our findings add to the existing research that suggests that sleep quality is a mediator between PAS and depression among students, which means that higher levels of PAS were related to poorer sleep quality—such as sleep deficiency and daytime dysfunction—which was related to higher levels of depression.

Serial Mediating Effect of Mobile Phone Addiction and Sleep Quality

As per H9, MPA and sleep quality together play a serial mediating role in the influence of PAS on depression. The results of our study showed that higher levels of PAS were related to higher levels of MPA, which was associated with poorer sleep quality, which was associated with higher levels of depression. Numerous studies have documented that there is a positive relationship between MPA and PSQ ( 50 , 52 ). For example, Kang et al. found that there were bidirectional longitudinal relationships between MPA and PSQ ( 50 ). Scholars have posited that the more screen time young people use, the less sleep time they have ( 108 ). Moreover, young people often use their mobile phone in the bedroom—bedtime mobile phone use is related to higher insomnia scores and increased fatigue ( 109 ), and both insomnia and fatigue are related to depression ( 110 , 111 ). This may explain why MPA and PSQ together play a serial mediating role in the influence of PAS on depression. Our findings suggests that Chinese students are likely to distract themselves from PAS by using their mobile phones, and thus shortening their sleep duration, decreasing their sleep quality, leading to PSQ, and resulting in depressive symptoms.

Measures to Reduce Depressive Symptoms Among Chinese Students

To reduce depressive symptoms among students, their PAS should be managed. Given the multiple, negative consequences (MPA, PSQ, and depression) of PAS, stakeholders—family members, educators (including teachers, school administrators, and school health professionals), and policy makers—should take preventative measures to help students manage and relieve academic stress, such as provide counseling services ( 112 ), foster their psychological resilience ( 113 ), and increase social support ( 19 ) to improve their overall well-being. Second, students' sleep quality should be ensured to reduce depressive symptoms. Stakeholders should actively promote counseling and intervention for students experiencing sleep disturbances. Third, given that higher levels of MPA are associated with poorer sleep quality and higher levels of depression, stakeholders should develop mitigating strategies to manage mobile phone use to ensure students' sleep quality and to relieve their depressive symptoms. Rational and normative mobile phone use should be advocated and classroom management strategies enforced to ensure that students use their mobile phones at restricted times and places for positive purposes, such as online learning. Fourth, regular psychological assessment of depression, MPA, and PSQ will help stakeholders detect and manage students' health problems. Last, parents and family members, educators, and policy makers should encourage students to exercise more to alleviate MPA ( 114 ), improve sleep quality ( 115 ), and reduce depression ( 116 ).

Limitations

This study has several limitations. First, although we conducted our research based on previous studies, due to the cross-sectional design of our study, we could not confirm causal relationships among the study variables. Second, the study period was September to December 2018, which was more than 2 years ago. However, we believe that the results of our study are valuable for understanding the mechanisms of how PAS influences students' depression through MPA and sleep quality, and our study can provide a basis for future research. Third, the study measured the participants' perceived academic stress using a single item, which may not have captured various other relevant stressors, such as parental learning expectations. Future studies should use a multiple-item scale to assess the participants' perceived academic stress. Forth, this study was limited to middle school, high school, vocational high school, and college students. Future research on Chinese students at all education levels from primary school to postgraduate levels is necessary. Fifth, perceived academic stress can increase during stressful conditions ( 117 ), such as during exams or major change in life (e.g., from high-school student to freshman). While our study was conducted in 27 schools in three cities, it is impossible that we conducted the survey when the participants had no examinations or changes. Future studies can control for stressful academic conditions in the analyses to enhance their accuracy. Last, gender, age, and other factors are important influencing factors of PAS, MPA, sleep quality, and depression. Since the main aim of this study was to test if there was a relationship between PAS and depression and if MPA and sleep quality together play a serial mediating role in the influence of PAS on depression, the aforementioned factors were not considered in this study. Future studies should consider these factors and test the relationships between PAS, MPA, sleep quality, depression, and other health indicators.

Conclusions

Our study's results showed that Chinese students face the risk of depression and sleep disturbance, and the most stressed, depressed, and sleep-disturbed students are those in high school. Second, the results of the serial mediation model indicated that PAS predicted depression, and MPA and sleep quality played a mediating role between PAS and depression. Furthermore, MPA and sleep quality together play a serial mediating role in the influence of PAS on depression. Our study extends the understanding of how PAS is associated with depression among Chinese students. Considering the harmful effects of depression, stakeholders—including parents and family members, educators, and policy makers—should take preventative measures to alleviate Chinese students' depression and depressive symptoms.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. Requests to access these datasets should be directed to wuqunhong@163.com .

Author Contributions

XZ, FG, ZK, and QW: conceptualization. XZ, HZ, JW, and HL: formal analysis. FG, JZ, JL, JY, HZ, and BL: investigation. XZ, FG, ZK, and BL: data curation. XZ, FG, and ZK: writing—original draft preparation. QW and BL: writing—review and editing. All authors have read and agreed to the published version of the manuscript.

This research was funded by QW of The National Key Social Science Fund of China (Grant No.19AZD013).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

The authors would like to express our appreciation to all of the individuals for their involvement in the study, including each of students and teachers for their support during the data collection.

Abbreviations

PAS, Perceived Academic Stress; MPA, Mobile Phone Addiction; MPAI, Mobile Phone Addiction Index; CES-D, Center for Epidemiologic Studies-Depression; PSQ, Poor Sleep Quality; PSQI, Pittsburgh Sleep Quality Index; SEM, Structural Equation Model.

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Keywords: perceived academic stress, mobile phone addiction (MPA), sleep quality, depression, depressive symptoms, Chinese students

Citation: Zhang X, Gao F, Kang Z, Zhou H, Zhang J, Li J, Yan J, Wang J, Liu H, Wu Q and Liu B (2022) Perceived Academic Stress and Depression: The Mediation Role of Mobile Phone Addiction and Sleep Quality. Front. Public Health 10:760387. doi: 10.3389/fpubh.2022.760387

Received: 18 August 2021; Accepted: 07 January 2022; Published: 25 January 2022.

Reviewed by:

Copyright © 2022 Zhang, Gao, Kang, Zhou, Zhang, Li, Yan, Wang, Liu, Wu and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Qunhong Wu, wuqunhong@163.com ; Baohua Liu, liubaohuawoshi@163.com

† These authors have contributed equally to this work

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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  • Systematic Review
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  • Published: 20 July 2022

The serotonin theory of depression: a systematic umbrella review of the evidence

  • Joanna Moncrieff 1 , 2 ,
  • Ruth E. Cooper 3 ,
  • Tom Stockmann 4 ,
  • Simone Amendola 5 ,
  • Michael P. Hengartner 6 &
  • Mark A. Horowitz 1 , 2  

Molecular Psychiatry volume  28 ,  pages 3243–3256 ( 2023 ) Cite this article

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The serotonin hypothesis of depression is still influential. We aimed to synthesise and evaluate evidence on whether depression is associated with lowered serotonin concentration or activity in a systematic umbrella review of the principal relevant areas of research. PubMed, EMBASE and PsycINFO were searched using terms appropriate to each area of research, from their inception until December 2020. Systematic reviews, meta-analyses and large data-set analyses in the following areas were identified: serotonin and serotonin metabolite, 5-HIAA, concentrations in body fluids; serotonin 5-HT 1A receptor binding; serotonin transporter (SERT) levels measured by imaging or at post-mortem; tryptophan depletion studies; SERT gene associations and SERT gene-environment interactions. Studies of depression associated with physical conditions and specific subtypes of depression (e.g. bipolar depression) were excluded. Two independent reviewers extracted the data and assessed the quality of included studies using the AMSTAR-2, an adapted AMSTAR-2, or the STREGA for a large genetic study. The certainty of study results was assessed using a modified version of the GRADE. We did not synthesise results of individual meta-analyses because they included overlapping studies. The review was registered with PROSPERO (CRD42020207203). 17 studies were included: 12 systematic reviews and meta-analyses, 1 collaborative meta-analysis, 1 meta-analysis of large cohort studies, 1 systematic review and narrative synthesis, 1 genetic association study and 1 umbrella review. Quality of reviews was variable with some genetic studies of high quality. Two meta-analyses of overlapping studies examining the serotonin metabolite, 5-HIAA, showed no association with depression (largest n  = 1002). One meta-analysis of cohort studies of plasma serotonin showed no relationship with depression, and evidence that lowered serotonin concentration was associated with antidepressant use ( n  = 1869). Two meta-analyses of overlapping studies examining the 5-HT 1A receptor (largest n  = 561), and three meta-analyses of overlapping studies examining SERT binding (largest n  = 1845) showed weak and inconsistent evidence of reduced binding in some areas, which would be consistent with increased synaptic availability of serotonin in people with depression, if this was the original, causal abnormaly. However, effects of prior antidepressant use were not reliably excluded. One meta-analysis of tryptophan depletion studies found no effect in most healthy volunteers ( n  = 566), but weak evidence of an effect in those with a family history of depression ( n  = 75). Another systematic review ( n  = 342) and a sample of ten subsequent studies ( n  = 407) found no effect in volunteers. No systematic review of tryptophan depletion studies has been performed since 2007. The two largest and highest quality studies of the SERT gene, one genetic association study ( n  = 115,257) and one collaborative meta-analysis ( n  = 43,165), revealed no evidence of an association with depression, or of an interaction between genotype, stress and depression. The main areas of serotonin research provide no consistent evidence of there being an association between serotonin and depression, and no support for the hypothesis that depression is caused by lowered serotonin activity or concentrations. Some evidence was consistent with the possibility that long-term antidepressant use reduces serotonin concentration.

Introduction

The idea that depression is the result of abnormalities in brain chemicals, particularly serotonin (5-hydroxytryptamine or 5-HT), has been influential for decades, and provides an important justification for the use of antidepressants. A link between lowered serotonin and depression was first suggested in the 1960s [ 1 ], and widely publicised from the 1990s with the advent of the Selective Serotonin Reuptake Inhibitor (SSRI) antidepressants [ 2 , 3 , 4 ]. Although it has been questioned more recently [ 5 , 6 ], the serotonin theory of depression remains influential, with principal English language textbooks still giving it qualified support [ 7 , 8 ], leading researchers endorsing it [ 9 , 10 , 11 ], and much empirical research based on it [ 11 , 12 , 13 , 14 ]. Surveys suggest that 80% or more of the general public now believe it is established that depression is caused by a ‘chemical imbalance’ [ 15 , 16 ]. Many general practitioners also subscribe to this view [ 17 ] and popular websites commonly cite the theory [ 18 ].

It is often assumed that the effects of antidepressants demonstrate that depression must be at least partially caused by a brain-based chemical abnormality, and that the apparent efficacy of SSRIs shows that serotonin is implicated. Other explanations for the effects of antidepressants have been put forward, however, including the idea that they work via an amplified placebo effect or through their ability to restrict or blunt emotions in general [ 19 , 20 ].

Despite the fact that the serotonin theory of depression has been so influential, no comprehensive review has yet synthesised the relevant evidence. We conducted an ‘umbrella’ review of the principal areas of relevant research, following the model of a similar review examining prospective biomarkers of major depressive disorder [ 21 ]. We sought to establish whether the current evidence supports a role for serotonin in the aetiology of depression, and specifically whether depression is associated with indications of lowered serotonin concentrations or activity.

Search strategy and selection criteria

The present umbrella review was reported in accordance with the 2009 PRISMA statement [ 22 ]. The protocol was registered with PROSPERO in December 2020 (registration number CRD42020207203) ( https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=207203 ). This was subsequently updated to reflect our decision to modify the quality rating system for some studies to more appropriately appraise their quality, and to include a modified GRADE to assess the overall certainty of the findings in each category of the umbrella review.

In order to cover the different areas and to manage the large volume of research that has been conducted on the serotonin system, we conducted an ‘umbrella’ review. Umbrella reviews survey existing systematic reviews and meta-analyses relevant to a research question and represent one of the highest levels of evidence synthesis available [ 23 ]. Although they are traditionally restricted to systematic reviews and meta-analyses, we aimed to identify the best evidence available. Therefore, we also included some large studies that combined data from individual studies but did not employ conventional systematic review methods, and one large genetic study. The latter used nationwide databases to capture more individuals than entire meta-analyses, so is likely to provide even more reliable evidence than syntheses of individual studies.

We first conducted a scoping review to identify areas of research consistently held to provide support for the serotonin hypothesis of depression. Six areas were identified, addressing the following questions: (1) Serotonin and the serotonin metabolite 5-HIAA–whether there are lower levels of serotonin and 5-HIAA in body fluids in depression; (2) Receptors - whether serotonin receptor levels are altered in people with depression; (3) The serotonin transporter (SERT) - whether there are higher levels of the serotonin transporter in people with depression (which would lower synaptic levels of serotonin); (4) Depletion studies - whether tryptophan depletion (which lowers available serotonin) can induce depression; (5) SERT gene – whether there are higher levels of the serotonin transporter gene in people with depression; (6) Whether there is an interaction between the SERT gene and stress in depression.

We searched for systematic reviews, meta-analyses, and large database studies in these six areas in PubMed, EMBASE and PsycINFO using the Healthcare Databases Advanced Search tool provided by Health Education England and NICE (National Institute for Health and Care Excellence). Searches were conducted until December 2020.

We used the following terms in all searches: (depress* OR affective OR mood) AND (systematic OR meta-analysis), and limited searches to title and abstract, since not doing so produced numerous irrelevant hits. In addition, we used terms specific to each area of research (full details are provided in Table  S1 , Supplement). We also searched citations and consulted with experts.

Inclusion criteria were designed to identify the best available evidence in each research area and consisted of:

Research synthesis including systematic reviews, meta-analysis, umbrella reviews, individual patient meta-analysis and large dataset analysis.

Studies that involve people with depressive disorders or, for experimental studies (tryptophan depletion), those in which mood symptoms are measured as an outcome.

Studies of experimental procedures (tryptophan depletion) involving a sham or control condition.

Studies published in full in peer reviewed literature.

Where more than five systematic reviews or large analyses exist, the most recent five are included.

Exclusion criteria consisted of:

Animal studies.

Studies exclusively concerned with depression in physical conditions (e.g. post stroke or Parkinson’s disease) or exclusively focusing on specific subtypes of depression such as postpartum depression, depression in children, or depression in bipolar disorder.

No language or date restrictions were applied. In areas in which no systematic review or meta-analysis had been done within the last 10 years, we also selected the ten most recent studies at the time of searching (December 2020) for illustration of more recent findings. We performed this search using the same search string for this domain, without restricting it to systematic reviews and meta-analyses.

Data analysis

Each member of the team was allocated one to three domains of serotonin research to search and screen for eligible studies using abstract and full text review. In case of uncertainty, the entire team discussed eligibility to reach consensus.

For included studies, data were extracted by two reviewers working independently, and disagreement was resolved by consensus. Authors of papers were contacted for clarification when data was missing or unclear.

We extracted summary effects, confidence intervals and measures of statistical significance where these were reported, and, where relevant, we extracted data on heterogeneity. For summary effects in the non-genetic studies, preference was given to the extraction and reporting of effect sizes. Mean differences were converted to effect sizes where appropriate data were available.

We did not perform a meta-analysis of the individual meta-analyses in each area because they included overlapping studies [ 24 ]. All extracted data is presented in Table  1 . Sensitivity analyses were reported where they had substantial bearing on interpretation of findings.

The quality rating of systematic reviews and meta-analyses was assessed using AMSTAR-2 (A MeaSurement Tool to Assess systematic Reviews) [ 25 ]. For two studies that did not employ conventional systematic review methods [ 26 , 27 ] we used a modified version of the AMSTAR-2 (see Table  S3 ). For the genetic association study based on a large database analysis we used the STREGA assessment (STrengthening the REporting of Genetic Association Studies) (Table  S4 ) [ 28 ]. Each study was rated independently by at least two authors. We report ratings of individual items on the relevant measure, and the percentage of items that were adequately addressed by each study (Table  1 , with further detail in Tables  S3 and S4 ).

Alongside quality ratings, two team members (JM, MAH) rated the certainty of the results of each study using a modified version of the GRADE guidelines [ 29 ]. Following the approach of Kennis et al. [ 21 ], we devised six criteria relevant to the included studies: whether a unified analysis was conducted on original data; whether confounding by antidepressant use was adequately addressed; whether outcomes were pre-specified; whether results were consistent or heterogeneity was adequately addressed if present; whether there was a likelihood of publication bias; and sample size. The importance of confounding by effects of current or past antidepressant use has been highlighted in several studies [ 30 , 31 ]. The results of each study were scored 1 or 0 according to whether they fulfilled each criteria, and based on these ratings an overall judgement was made about the certainty of evidence across studies in each of the six areas of research examined. The certainty of each study was based on an algorithm that prioritised sample size and uniform analysis using original data (explained more fully in the supplementary material), following suggestions that these are the key aspects of reliability [ 27 , 32 ]. An assessment of the overall certainty of each domain of research examining the role of serotonin was determined by consensus of at least two authors and a direction of effect indicated.

Search results and quality rating

Searching identified 361 publications across the 6 different areas of research, among which seventeen studies fulfilled inclusion criteria (see Fig.  1 and Table  S1 for details of the selection process). Included studies, their characteristics and results are shown in Table  1 . As no systematic review or meta-analysis had been performed within the last 10 years on serotonin depletion, we also identified the 10 latest studies for illustration of more recent research findings (Table  2 ).

figure 1

Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) flow diagramme.

Quality ratings are summarised in Table  1 and reported in detail in Tables  S2 – S3 . The majority (11/17) of systematic reviews and meta-analyses satisfied less than 50% of criteria. Only 31% adequately assessed risk of bias in individual studies (a further 44% partially assessed this), and only 50% adequately accounted for risk of bias when interpreting the results of the review. One collaborative meta-analysis of genetic studies was considered to be of high quality due to the inclusion of several measures to ensure consistency and reliability [ 27 ]. The large genetic analysis of the effect of SERT polymorphisms on depression, satisfied 88% of the STREGA quality criteria [ 32 ].

Serotonin and 5-HIAA

Serotonin can be measured in blood, plasma, urine and CSF, but it is rapidly metabolised to 5-hydroxyindoleacetic acid (5-HIAA). CSF is thought to be the ideal resource for the study of biomarkers of putative brain diseases, since it is in contact with brain interstitial fluid [ 33 ]. However, collecting CSF samples is invasive and carries some risk, hence large-scale studies are scarce.

Three studies fulfilled inclusion criteria (Table  1 ). One meta-analysis of three large observational cohort studies of post-menopausal women, revealed lower levels of plasma 5-HT in women with depression, which did not, however, reach statistical significance of p  < 0.05 after adjusting for multiple comparisons. Sensitivity analyses revealed that antidepressants were strongly associated with lower serotonin levels independently of depression.

Two meta-analyses of a total of 19 studies of 5-HIAA in CSF (seven studies were included in both) found no evidence of an association between 5-HIAA concentrations and depression.

Fourteen different serotonin receptors have been identified, with most research on depression focusing on the 5-HT 1A receptor [ 11 , 34 ]. Since the functions of other 5-HT receptors and their relationship to depression have not been well characterised, we restricted our analysis to data on 5-HT 1A receptors [ 11 , 34 ]. 5-HT 1A receptors, known as auto-receptors, inhibit the release of serotonin pre-synaptically [ 35 ], therefore, if depression is the result of reduced serotonin activity caused by abnormalities in the 5-HT 1A receptor, people with depression would be expected to show increased activity of 5-HT 1A receptors compared to those without [ 36 ].

Two meta-analyses satisfied inclusion criteria, involving five of the same studies [ 37 , 38 ] (see Table  1 ). The majority of results across the two analyses suggested either no difference in 5-HT 1A receptors between people with depression and controls, or a lower level of these inhibitory receptors, which would imply higher concentrations or activity of serotonin in people with depression. Both meta-analyses were based on studies that predominantly involved patients who were taking or had recently taken (within 1–3 weeks of scanning) antidepressants or other types of psychiatric medication, and both sets of authors commented on the possible influence of prior or current medication on findings. In addition, one analysis was of very low quality [ 37 ], including not reporting on the numbers involved in each analysis and using one-sided p-values, and one was strongly influenced by three studies and publication bias was present [ 38 ].

The serotonin transporter (SERT)

The serotonin transporter protein (SERT) transports serotonin out of the synapse, thereby lowering the availability of serotonin in the synapse [ 39 , 40 ]. Animals with an inactivated gene for SERT have higher levels of extra-cellular serotonin in the brain than normal [ 41 , 42 , 43 ] and SSRIs are thought to work by inhibiting the action of SERT, and thus increasing levels of serotonin in the synaptic cleft [ 44 ]. Although changes in SERT may be a marker for other abnormalities, if depression is caused by low serotonin availability or activity, and if SERT is the origin of that deficit, then the amount or activity of SERT would be expected to be higher in people with depression compared to those without [ 40 ]. SERT binding potential is an index of the concentration of the serotonin transporter protein and SERT concentrations can also be measured post-mortem.

Three overlapping meta-analyses based on a total of 40 individual studies fulfilled inclusion criteria (See Table  1 ) [ 37 , 39 , 45 ]. Overall, the data indicated possible reductions in SERT binding in some brain areas, although areas in which effects were detected were not consistent across the reviews. In addition, effects of antidepressants and other medication cannot be ruled out, since most included studies mainly or exclusively involved people who had a history of taking antidepressants or other psychiatric medications. Only one meta-analysis tested effects of antidepressants, and although results were not influenced by the percentage of drug-naïve patients in each study, numbers were small so it is unlikely that medication-related effects would have been reliably detected [ 45 ]. All three reviews cited evidence from animal studies that antidepressant treatment reduces SERT [ 46 , 47 , 48 ]. None of the analyses corrected for multiple testing, and one review was of very low quality [ 37 ]. If the results do represent a positive finding that is independent of medication, they would suggest that depression is associated with higher concentrations or activity of serotonin.

Depletion studies

Tryptophan depletion using dietary means or chemicals, such as parachlorophenylalanine (PCPA), is thought to reduce serotonin levels. Since PCPA is potentially toxic, reversible tryptophan depletion using an amino acid drink that lacks tryptophan is the most commonly used method and is thought to affect serotonin within 5–7 h of ingestion. Questions remain, however, about whether either method reliably reduces brain serotonin, and about other effects including changes in brain nitrous oxide, cerebrovascular changes, reduced BDNF and amino acid imbalances that may be produced by the manipulations and might explain observed effects independent of possible changes in serotonin activity [ 49 ].

One meta-analysis and one systematic review fulfilled inclusion criteria (see Table  1 ). Data from studies involving volunteers mostly showed no effect, including a meta-analysis of parallel group studies [ 50 ]. In a small meta-analysis of within-subject studies involving 75 people with a positive family history, a minor effect was found, with people given the active depletion showing a larger decrease in mood than those who had a sham procedure [ 50 ]. Across both reviews, studies involving people diagnosed with depression showed slightly greater mood reduction following tryptophan depletion than sham treatment overall, but most participants had taken or were taking antidepressants and participant numbers were small [ 50 , 51 ].

Since these research syntheses were conducted more than 10 years ago, we searched for a systematic sample of ten recently published studies (Table  2 ). Eight studies conducted with healthy volunteers showed no effects of tryptophan depletion on mood, including the only two parallel group studies. One study presented effects in people with and without a family history of depression, and no differences were apparent in either group [ 52 ]. Two cross-over studies involving people with depression and current or recent use of antidepressants showed no convincing effects of a depletion drink [ 53 , 54 ], although one study is reported as positive mainly due to finding an improvement in mood in the group given the sham drink [ 54 ].

SERT gene and gene-stress interactions

A possible link between depression and the repeat length polymorphism in the promoter region of the SERT gene (5-HTTLPR), specifically the presence of the short repeats version, which causes lower SERT mRNA expression, has been proposed [ 55 ]. Interestingly, lower levels of SERT would produce higher levels of synaptic serotonin. However, more recently, this hypothesis has been superseded by a focus on the interaction effect between this polymorphism, depression and stress, with the idea that the short version of the polymorphism may only give rise to depression in the presence of stressful life events [ 55 , 56 ]. Unlike other areas of serotonin research, numerous systematic reviews and meta-analyses of genetic studies have been conducted, and most recently a very large analysis based on a sample from two genetic databanks. Details of the five most recent studies that have addressed the association between the SERT gene and depression, and the interaction effect are detailed in Table  1 .

Although some earlier meta-analyses of case-control studies showed a statistically significant association between the 5-HTTLPR and depression in some ethnic groups [ 57 , 58 ], two recent large, high quality studies did not find an association between the SERT gene polymorphism and depression [ 27 , 32 ]. These two studies consist of  by far the largest and most comprehensive study to date [ 32 ] and a high-quality meta-analysis that involved a consistent re-analysis of primary data across all conducted studies, including previously unpublished data, and other comprehensive quality checks [ 27 , 59 ] (see Table  1 ).

Similarly, early studies based on tens of thousands of participants suggested a statistically significant interaction between the SERT gene, forms of stress or maltreatment and depression [ 60 , 61 , 62 ], with a small odds ratio in the only study that reported this (1.18, 95% CI 1.09 to 1.28) [ 62 ]. However, the two recent large, high-quality studies did not find an interaction between the SERT gene and stress in depression (Border et al [ 32 ] and Culverhouse et al.) [ 27 ] (see Table  1 ).

Overall results

Table  3 presents the modified GRADE ratings for each study and the overall rating of the strength of evidence in each area. Areas of research that provided moderate or high certainty of evidence such as the studies of plasma serotonin and metabolites and the genetic and gene-stress interaction studies all showed no association between markers of serotonin activity and depression. Some other areas suggested findings consistent with increased serotonin activity, but evidence was of very low certainty, mainly due to small sample sizes and possible residual confounding by current or past antidepressant use. One area - the tryptophan depletion studies - showed very low certainty evidence of lowered serotonin activity or availability in a subgroup of volunteers with a family history of depression. This evidence was considered very low certainty as it derived from a subgroup of within-subject studies, numbers were small, and there was no information on medication use, which may have influenced results. Subsequent research has not confirmed an effect with numerous negative studies in volunteers.

Our comprehensive review of the major strands of research on serotonin shows there is no convincing evidence that depression is associated with, or caused by, lower serotonin concentrations or activity. Most studies found no evidence of reduced serotonin activity in people with depression compared to people without, and methods to reduce serotonin availability using tryptophan depletion do not consistently lower mood in volunteers. High quality, well-powered genetic studies effectively exclude an association between genotypes related to the serotonin system and depression, including a proposed interaction with stress. Weak evidence from some studies of serotonin 5-HT 1A receptors and levels of SERT points towards a possible association between increased serotonin activity and depression. However, these results are likely to be influenced by prior use of antidepressants and its effects on the serotonin system [ 30 , 31 ]. The effects of tryptophan depletion in some cross-over studies involving people with depression may also be mediated by antidepressants, although these are not consistently found [ 63 ].

The chemical imbalance theory of depression is still put forward by professionals [ 17 ], and the serotonin theory, in particular, has formed the basis of a considerable research effort over the last few decades [ 14 ]. The general public widely believes that depression has been convincingly demonstrated to be the result of serotonin or other chemical abnormalities [ 15 , 16 ], and this belief shapes how people understand their moods, leading to a pessimistic outlook on the outcome of depression and negative expectancies about the possibility of self-regulation of mood [ 64 , 65 , 66 ]. The idea that depression is the result of a chemical imbalance also influences decisions about whether to take or continue antidepressant medication and may discourage people from discontinuing treatment, potentially leading to lifelong dependence on these drugs [ 67 , 68 ].

As with all research synthesis, the findings of this umbrella review are dependent on the quality of the included studies, and susceptible to their limitations. Most of the included studies were rated as low quality on the AMSTAR-2, but the GRADE approach suggested some findings were reasonably robust. Most of the non-genetic studies did not reliably exclude the potential effects of previous antidepressant use and were based on relatively small numbers of participants. The genetic studies, in particular, illustrate the importance of methodological rigour and sample size. Whereas some earlier, lower quality, mostly smaller studies produced marginally positive findings, these were not confirmed in better-conducted, larger and more recent studies [ 27 , 32 ]. The identification of depression and assessment of confounders and interaction effects were limited by the data available in the original studies on which the included reviews and meta-analyses were based. Common methods such as the categorisation of continuous measures and application of linear models to non-linear data may have led to over-estimation or under-estimation of effects [ 69 , 70 ], including the interaction between stress and the SERT gene. The latest systematic review of tryptophan depletion studies was conducted in 2007, and there has been considerable research produced since then. Hence, we provided a snapshot of the most recent evidence at the time of writing, but this area requires an up to date, comprehensive data synthesis. However, the recent studies were consistent with the earlier meta-analysis with little evidence for an effect of tryptophan depletion on mood.

Although umbrella reviews typically restrict themselves to systematic reviews and meta-analyses, we aimed to provide the most comprehensive possible overview. Therefore, we chose to include meta-analyses that did not involve a systematic review and a large genetic association study on the premise that these studies contribute important data on the question of whether the serotonin hypothesis of depression is supported. As a result, the AMSTAR-2 quality rating scale, designed to evaluate the quality of conventional systematic reviews, was not easily applicable to all studies and had to be modified or replaced in some cases.

One study in this review found that antidepressant use was associated with a reduction of plasma serotonin [ 26 ], and it is possible that the evidence for reductions in SERT density and 5-HT 1A receptors in some of the included imaging study reviews may reflect compensatory adaptations to serotonin-lowering effects of prior antidepressant use. Authors of one meta-analysis also highlighted evidence of 5-HIAA levels being reduced after long-term antidepressant treatment [ 71 ]. These findings suggest that in the long-term antidepressants might produce compensatory changes [ 72 ] that are opposite to their acute effects [ 73 , 74 ]. Lowered serotonin availability has also been demonstrated in animal studies following prolonged antidepressant administration [ 75 ]. Further research is required to clarify the effects of different drugs on neurochemical systems, including the serotonin system, especially during and after long-term use, as well as the physical and psychological consequences of such effects.

This review suggests that the huge research effort based on the serotonin hypothesis has not produced convincing evidence of a biochemical basis to depression. This is consistent with research on many other biological markers [ 21 ]. We suggest it is time to acknowledge that the serotonin theory of depression is not empirically substantiated.

Data availability

All extracted data is available in the paper and supplementary materials. Further information about the decision-making for each rating for categories of the AMSTAR-2 and STREGA are available on request.

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There was no specific funding for this review. MAH is supported by a Clinical Research Fellowship from North East London NHS Foundation Trust (NELFT). This funder had no role in study design, data collection, data analysis, data interpretation, or writing of the report.

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JM conceived the idea for the study. JM, MAH, MPH, TS and SA designed the study. JM, MAH, MPH, TS, and SA screened articles and abstracted data. JM drafted the first version of the manuscript. JM, MAH, MPH, TS, SA, and REC contributed to the manuscript’s revision and interpretation of findings. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.

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All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author). SA declares no conflicts of interest. MAH reports being co-founder of a company in April 2022, aiming to help people safely stop antidepressants in Canada. MPH reports royalties from Palgrave Macmillan, London, UK for his book published in December, 2021, called “Evidence-biased Antidepressant Prescription.” JM receives royalties for books about psychiatric drugs, reports grants from the National Institute of Health Research outside the submitted work, that she is co-chairperson of the Critical Psychiatry Network (an informal group of psychiatrists) and a board member of the unfunded organisation, the Council for Evidence-based Psychiatry. Both are unpaid positions. TS is co-chairperson of the Critical Psychiatry Network. RC is an unpaid board member of the International Institute for Psychiatric Drug Withdrawal.

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Moncrieff, J., Cooper, R.E., Stockmann, T. et al. The serotonin theory of depression: a systematic umbrella review of the evidence. Mol Psychiatry 28 , 3243–3256 (2023). https://doi.org/10.1038/s41380-022-01661-0

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Running or yoga can help beat depression, research shows – even if exercise is the last thing you feel like

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At least one in ten people have depression at some point in their lives, with some estimates closer to one in four . It’s one of the worst things for someone’s wellbeing – worse than debt, divorce or diabetes .

One in seven Australians take antidepressants. Psychologists are in high demand . Still, only half of people with depression in high-income countries get treatment.

Our new research shows that exercise should be considered alongside therapy and antidepressants. It can be just as impactful in treating depression as therapy, but it matters what type of exercise you do and how you do it.

Read more: Why are so many Australians taking antidepressants?

Walk, run, lift, or dance away depression

We found 218 randomised trials on exercise for depression, with 14,170 participants. We analysed them using a method called a network meta-analysis. This allowed us to see how different types of exercise compared, instead of lumping all types together.

We found walking, running, strength training, yoga and mixed aerobic exercise were about as effective as cognitive behaviour therapy – one of the gold-standard treatments for depression. The effects of dancing were also powerful. However, this came from analysing just five studies, mostly involving young women. Other exercise types had more evidence to back them.

Walking, running, strength training, yoga and mixed aerobic exercise seemed more effective than antidepressant medication alone, and were about as effective as exercise alongside antidepressants.

But of these exercises, people were most likely to stick with strength training and yoga.

Antidepressants certainly help some people . And of course, anyone getting treatment for depression should talk to their doctor before changing what they are doing.

Still, our evidence shows that if you have depression, you should get a psychologist and an exercise plan, whether or not you’re taking antidepressants.

Join a program and go hard (with support)

Before we analysed the data, we thought people with depression might need to “ease into it” with generic advice, such as “some physical activity is better than doing none.”

But we found it was far better to have a clear program that aimed to push you, at least a little. Programs with clear structure worked better, compared with those that gave people lots of freedom. Exercising by yourself might also make it hard to set the bar at the right level, given low self-esteem is a symptom of depression.

We also found it didn’t matter how much people exercised, in terms of sessions or minutes a week. It also didn’t really matter how long the exercise program lasted. What mattered was the intensity of the exercise: the higher the intensity, the better the results.

Yes, it’s hard to keep motivated

We should exercise caution in interpreting the findings. Unlike drug trials, participants in exercise trials know which “treatment” they’ve been randomised to receive, so this may skew the results.

Many people with depression have physical, psychological or social barriers to participating in formal exercise programs. And getting support to exercise isn’t free.

We also still don’t know the best way to stay motivated to exercise, which can be even harder if you have depression.

Our study tried to find out whether things like setting exercise goals helped, but we couldn’t get a clear result.

Other reviews found it’s important to have a clear action plan (for example, putting exercise in your calendar) and to track your progress (for example, using an app or smartwatch). But predicting which of these interventions work is notoriously difficult.

A 2021 mega-study of more than 60,000 gym-goers found experts struggled to predict which strategies might get people into the gym more often. Even making workouts fun didn’t seem to motivate people. However, listening to audiobooks while exercising helped a lot, which no experts predicted.

Still, we can be confident that people benefit from personalised support and accountability. The support helps overcome the hurdles they’re sure to hit. The accountability keeps people going even when their brains are telling them to avoid it.

So, when starting out, it seems wise to avoid going it alone. Instead:

join a fitness group or yoga studio

get a trainer or an exercise physiologist

ask a friend or family member to go for a walk with you.

Taking a few steps towards getting that support makes it more likely you’ll keep exercising.

Read more: Exercise is even more effective than counselling or medication for depression. But how much do you need?

Let’s make this official

Some countries see exercise as a backup plan for treating depression. For example, the American Psychological Association only conditionally recommends exercise as a “complementary and alternative treatment” when “psychotherapy or pharmacotherapy is either ineffective or unacceptable”.

Based on our research, this recommendation is withholding a potent treatment from many people who need it.

In contrast, The Royal Australian and New Zealand College of Psychiatrists recommends vigorous aerobic activity at least two to three times a week for all people with depression.

Given how common depression is, and the number failing to receive care, other countries should follow suit and recommend exercise alongside front-line treatments for depression.

I would like to acknowledge my colleagues Taren Sanders, Chris Lonsdale and the rest of the coauthors of the paper on which this article is based.

If this article has raised issues for you, or if you’re concerned about someone you know, call Lifeline on 13 11 14.

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Patients With Depression Face Highest Risk for Suicide in Days After Hospital Discharge

By Dennis Thompson HealthDay Reporter

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TUESDAY, Feb. 20, 2024 (HealthDay News) -- People treated at psychiatric hospitals are at highest risk of committing suicide immediately after their discharge if they suffer from depression, a new study reports.

Patients hospitalized for depression are hundreds of times more likely to commit suicide within the first three days of discharge, compared to the suicide rate of the general population, results show.

“Although we found a decreasing trend over time, the high-risk post-discharge period still requires intensified attention,” wrote the authors, who were led by Dr. Kari Aaltonen of the University of Helsinki in Finland. “Continuity of care and access to enhanced psychiatric outpatient care within days of discharge should be imperative.”

More than half of all people who die by suicide are depressed, and about 40% had been recently hospitalized for psychiatric reasons, researchers said in an American Psychiatric Association news release.

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For the study, researchers analyzed health data on more than 91,000 Finnish people hospitalized for depression between 1996 and 2017. Each person was tracked for up to two years following their discharge.

A total of 1,219 men and 757 women died by suicide during the study period, results show.

Researchers found that within the first three days of discharge, the suicide rate was 6,063 per 100,000 person-years. Person-years take into account both the number of people in a study and the amount of time each person spends in the study.

That rate is 330 times higher than the suicide rate for Finland overall, researchers noted.

The suicide rate remained high through the first week after discharge, running at 3,884 per 100,000 person-years on days four through seven, results show.

But the rate then fell steadily, dropping to 478 per 100,000 person-years after one year.

People admitted to the hospital due to a suicide attempt by firearm or hanging had the highest risk of death by suicide in the first three days after discharge, researchers said.

Other factors associated with immediate suicide risk included psychotic depression, severe mental illness with impaired function, and a history of suicide attempts. Men were at higher risk, as well as those age 40 and above, results show. 

Some risk factors changed over time, researchers found.

For example, people with higher household incomes had a higher suicide risk right after discharge, but it fell over time compared to those with less money.

On the other hand, alcoholics had a lower immediate suicide risk following discharge, but their risk increased over time.

The new study was published recently in the journal JAMA Psychiatry .

If you or a loved one is having suicidal thoughts, the 988 Suicide and Crisis Lifeline offers free, anonymous 24/7 help.

More information

The U.S. Centers for Disease Control and Prevention has more about risk factors for suicide .

SOURCE: American Psychiatric Association, news release, Feb. 14, 2024

Copyright © 2024 HealthDay . All rights reserved.

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A pacemaker for the brain helped a woman with crippling depression. It may soon be available widely.

Emily Hollenbeck.

NEW YORK (AP) — Emily Hollenbeck lived with a deep, recurring depression she likened to a black hole, where gravity felt so strong and her limbs so heavy she could barely move. She knew the illness could kill her. Both of her parents had taken their lives.

She was willing to try something extreme: Having electrodes implanted in her brain as part of an experimental therapy.

Researchers say the treatment —- called deep brain stimulation, or DBS — could eventually help many of the nearly 3 million Americans like her with depression that resists other treatments. It’s approved for conditions such as Parkinson’s disease and epilepsy, and many doctors and patients hope it will become more widely available for depression soon.

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The treatment gives patients targeted electrical impulses, much like a pacemaker for the brain. A growing body of recent research is promising, with more underway — although two large studies that showed no advantage to using DBS for depression temporarily halted progress, and some scientists continue to raise concerns.

Meanwhile, the Food and Drug Administration has agreed to speed up its review of Abbott Laboratories' request to use its DBS devices for treatment-resistant depression.

“At first I was blown away because the concept of it seems so intense. Like, it’s brain surgery. You have wires embedded in your brain,” said Hollenbeck, who is part of ongoing research at Mount Sinai West. “But I also felt like at that point I tried everything, and I was desperate for an answer.”

‘Nothing else was working’

Hollenbeck suffered from depression symptoms as a child growing up in poverty and occasional homelessness. But her first major bout happened in college, after her father’s suicide in 2009. Another hit during a Teach for America stint, leaving her almost immobilized and worried she’d lose her classroom job and sink into poverty again. She landed in the hospital.

“I ended up having sort of an on-and-off pattern,” she said. After responding to medication for a while, she'd relapse.

She managed to earn a doctorate in psychology, even after losing her mom in her last year of grad school. But the black hole always returned to pull her in. At times, she said, she thought about ending her life.

She said she'd exhausted all options, including electroconvulsive therapy, when a doctor told her about DBS three years ago.

“Nothing else was working,” she said.

She became one of only a few hundred treated with DBS for depression.

Hollenbeck had the brain surgery while sedated but awake. Dr. Brian Kopell, who directs Mount Sinai's Center for Neuromodulation, placed thin metal electrodes in a region of her brain called the subcallosal cingulate cortex, which regulates emotional behavior and is involved in feelings of sadness.

The electrodes are connected by an internal wire to a device placed under the skin in her chest, which controls the amount of electrical stimulation and delivers constant low-voltage pulses. Hollenbeck calls it “continous Prozac.”

Doctors say the stimulation helps because electricity speaks the brain’s language. Neurons communicate using electrical and chemical signals.

In normal brains, Kopell said, electrical activity reverberates unimpeded in all areas, in a sort of dance. In depression, the dancers get stuck within the brain’s emotional circuitry. DBS seems to “unstick the circuit,” he said, allowing the brain to do what it normally would.

Hollenbeck said the effect was almost immediate.

“The first day after surgery, she started feeling a lifting of that negative mood, of the heaviness,” said her psychiatrist, Dr. Martijn Figee. “I remember her telling me that she was able to enjoy Vietnamese takeout for the first time in years and really taste the food. She started to decorate her home, which had been completely empty since she moved to New York.”

For Hollenbeck, the most profound change was finding pleasure in music again.

“When I was depressed, I couldn’t listen to music. It sounded and felt like I was listening to radio static,” she said. “Then on a sunny day in the summer, I was walking down the street listening to a song. I just felt this buoyancy, this, ‘Oh, I want to walk more, I want to go and do things!’ And I realized I’m getting better.”

She only wishes the therapy had been there for her parents.

The treatment’s history

The road to this treatment stretches back two decades, when neurologist Dr. Helen Mayberg led promising early research.

But setbacks followed. Large studies launched more than a dozen years ago showed no significant difference in response rates for treated and untreated groups. Dr. Katherine Scangos, a psychiatrist at the University of California, San Francisco, also researching DBS and depression, cited a couple of reasons: The treatment wasn’t personalized, and researchers looked at outcomes over a matter of weeks.

Some later research showed depression patients had stable, long-term relief from DBS when observed over years. Overall, across different brain targets, DBS for depression is associated with average response rates of 60%, one 2022 study said.

Treatments being tested by various teams are much more tailored to individuals today. Mount Sinai's team is one of the most prominent researching DBS for depression in the U.S. There, a neuroimaging expert uses brain images to locate the exact spot for Kopell to place electrodes.

“We have a template, a blueprint of exactly where we’re going to go,” said Mayberg, a pioneer in DBS research and founding director of The Nash Family Center for Advanced Circuit Therapeutics at Mount Sinai. “Everybody’s brain is a little different, just like people’s eyes are a little further apart or a nose is a little bigger or smaller.”

Other research teams also tailor treatment to patients, although their methods are slightly different. Scangos and her colleagues are studying various targets in the brain and delivering stimulation only when needed for severe symptoms. She said the best therapy may end up being a combination of approaches.

As teams keep working, Abbott is launching a big clinical trial this year, ahead of a potential FDA decision.

“The field is advancing quite quickly,” Scangos said. “I’m hoping we will have approval within a short time.”

But some doctors are skeptical, pointing to potential complications such as bleeding, stroke or infection after surgery.

Dr. Stanley Caroff, an emeritus professor of psychiatry at the University of Pennsylvania, said scientists still don't know the exact pathways or mechanisms in the brain that produce depression, which is why it's hard to pick a site to stimulate. It's also tough to select the right patients for DBS, he said, and approved, successful treatments for depression are available.

“I believe from a psychiatric point of view, the science is not there,” he said of DBS for depression.

Moving forward

Hollenbeck acknowledges DBS hasn't been a cure-all; she still takes medicines for depression and needs ongoing care.

She recently visited Mayberg in her office and discussed recovery. “It’s not about being happy all the time,” the doctor told her. “It’s about making progress.”

That’s what researchers are studying now — how to track progress.

Recent research by Mayberg and others in the journal Nature showed it’s possible to provide a “readout” of how someone is doing at any given time. Analyzing the brain activity of DBS patients, researchers found a unique pattern that reflects the recovery process. This gives them an objective way to observe how people get better and distinguish between impending depression and typical mood fluctuations.

Scientists are confirming those findings using newer DBS devices in a group of patients that includes Hollenbeck.

She and other participants do their part largely at home. She gives researchers regular brain recordings by logging onto a tablet, putting a remote above the pacemaker-like device in her chest and sending the data. She answers questions that pop up about how she feels. Then she records a video that will be analyzed for things such as facial expression and speech.

Occasionally, she goes into Mount Sinai’s “Q-Lab,” an immersive environment where scientists do quantitative research collecting all sorts of data, including how she moves in a virtual forest or makes circles in the air with her arms. Like many other patients, she moves her arms faster now that she’s doing better.

Data from recordings and visits are combined with other information, such as life events, to chart how she's doing. This helps guide doctors’ decisions, such as whether to increase her dose of electricity – which they did once.

On a recent morning, Hollenbeck moved her collar and brushed her hair aside to reveal scars on her chest and head from her DBS surgery. To her, they're signs of how far she’s come.

She makes her way around the city, taking walks in the park and going to libraries, which were a refuge in childhood. She no longer worries that normal life challenges will trigger a crushing depression.

“The stress is pretty extreme at times, but I’m able to see and remember, even on a bodily level, that I’m going to be OK,” she said.

“If I hadn’t had DBS, I’m pretty sure I would not be alive today.”

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Major Depressive Disorder: Advances in Neuroscience Research and Translational Applications

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A Correction to this article was published on 17 May 2021

This article has been updated

Major depressive disorder (MDD), also referred to as depression, is one of the most common psychiatric disorders with a high economic burden. The etiology of depression is still not clear, but it is generally believed that MDD is a multifactorial disease caused by the interaction of social, psychological, and biological aspects. Therefore, there is no exact pathological theory that can independently explain its pathogenesis, involving genetics, neurobiology, and neuroimaging. At present, there are many treatment measures for patients with depression, including drug therapy, psychotherapy, and neuromodulation technology. In recent years, great progress has been made in the development of new antidepressants, some of which have been applied in the clinic. This article mainly reviews the research progress, pathogenesis, and treatment of MDD.

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Introduction

Neuroimaging advance in depressive disorder.

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The cellular and molecular basis of major depressive disorder: towards a unified model for understanding clinical depression

Eleni Pitsillou, Sarah M. Bresnehan, … Tom C. Karagiannis

Avoid common mistakes on your manuscript.

Major depressive disorder (MDD) also referred to as depression, is one of the most severe and common psychiatric disorders across the world. It is characterized by persistent sadness, loss of interest or pleasure, low energy, worse appetite and sleep, and even suicide, disrupting daily activities and psychosocial functions. Depression has an extreme global economic burden and has been listed as the third largest cause of disease burden by the World Health Organization since 2008, and is expected to rank the first by 2030 [ 1 , 2 ]. In 2016, the Global Burden of Diseases, Injuries, and Risk Factors Study demonstrated that depression caused 34.1 million of the total years lived with disability (YLDs), ranking as the fifth largest cause of YLD [ 3 ]. Therefore, the research progress and the clinical application of new discoveries or new technologies are imminent. In this review, we mainly discuss the current situation of research, developments in pathogenesis, and the management of depression.

Current Situation of Research on Depression

Analysis of published papers.

In the past decade, the total number of papers on depression published worldwide has increased year by year as shown in Fig. 1 A. Searching the Web of Science database, we found a total of 43,863 papers published in the field of depression from 2009 to 2019 (search strategy: TI = (depression$) or ts = ("major depressive disorder$")) and py = (2009 – 2019), Articles). The top 10 countries that published papers on the topic of depression are shown in Fig. 1 B. Among them, researchers in the USA published the most papers, followed by China. Compared with the USA, the gap in the total number of papers published in China is gradually narrowing (Fig. 1 C), but the quality gap reflected by the index (the total number of citations and the number of citations per paper) is still large, and is lower than the global average (Fig. 1 D). As shown in Fig. 1 E, the hot research topics in depression are as follows: depression management in primary care, interventions to prevent depression, the pathogenesis of depression, comorbidity of depression and other diseases, the risks of depression, neuroimaging studies of depression, and antidepressant treatment.

figure 1

Analysis of published papers around the world from 2009 to 2019 in depressive disorder. A The total number of papers [from a search of the Web of Science database (search strategy: TI = (depression$) or ts = ("major depressive disorder$")) and py = (2009 – 2019), Articles)]. B The top 10 countries publishing on the topic. C Comparison of papers in China and the USA. D Citations for the top 10 countries and comparison with the global average. E Hot topics.

Analysis of Patented Technology Application

There were 16,228 patent applications in the field of depression between 2009 and 2019, according to the Derwent Innovation Patent database. The annual number and trend of these patents are shown in Fig. 2 A. The top 10 countries applying for patents related to depression are shown in Fig. 2 B. The USA ranks first in the number of depression-related patent applications, followed by China. The largest number of patents related to depression is the development of antidepressants, and drugs for neurodegenerative diseases such as dementia comorbid with depression. The top 10 technological areas of patents related to depression are shown in Fig. 2 C, and the trend in these areas have been stable over the past decade (Fig. 2 D).

figure 2

Analysis of patented technology applications from 2009 to 2019 in the field of depressive disorder. A Annual numbers and trends of patents (the Derwent Innovation patent database). B The top 10 countries/regions applying for patents. C The top 10 technological areas of patents. D The trend of patent assignees. E Global hot topic areas of patents.

Analysis of technical hotspots based on keyword clustering was conducted from the Derwent Innovation database using the "ThemeScape" tool. This demonstrated that the hot topic areas are as follows (Fig. 2 E): (1) improvement for formulation and the efficiency of hydrobromide, as well as optimization of the dosage; intervention for depression comorbid with AD, diabetes, and others; (3) development of alkyl drugs; (4) development of pharmaceutical acceptable salts as antidepressants; (5) innovation of the preparation of antidepressants; (6) development of novel antidepressants based on neurotransmitters; (7) development of compositions based on nicotinic acetylcholine receptors; and (8) intervention for depression with traditional Chinese medicine.

Analysis of Clinical Trial

There are 6,516 clinical trials in the field of depression in the ClinicalTrials.gov database, and among them, 1,737 valid trials include the ongoing recruitment of subjects, upcoming recruitment of subjects, and ongoing clinical trials. These clinical trials are mainly distributed in the USA (802 trials), Canada (155), China (114), France (93), Germany (66), UK (62), Spain (58), Denmark (41), Sweden (39), and Switzerland (23). The indications for clinical trials include various types of depression, such as minor depression, depression, severe depression, perinatal depression, postpartum depression, and depression comorbid with other psychiatric disorders or physical diseases, such as schizophrenia, epilepsy, stroke, cancer, diabetes, cardiovascular disease, and Parkinson's disease.

Based on the database of the Chinese Clinical Trial Registry website, a total of 143 clinical trials for depression have been carried out in China. According to the type of research, they are mainly interventional and observational studies, as well as a small number of related factor studies, epidemiological studies, and diagnostic trials. The research content involves postpartum, perinatal, senile, and other age groups with clinical diagnosis (imaging diagnosis) and intervention studies (drugs, acupuncture, electrical stimulation, transcranial magnetic stimulation). It also includes intervention studies on depression comorbid with coronary heart disease, diabetes, and heart failure.

New Medicine Development

According to the Cortellis database, 828 antidepressants were under development by the end of 2019, but only 292 of these are effective and active (Fig. 3 A). Large number of them have been discontinued or made no progress, indicating that the development of new drugs in the field of depression is extremely urgent.

figure 3

New medicine development from 2009 to 2019 in depressive disorder. A Development status of new candidate drugs. B Top target-based actions.

From the perspective of target-based actions, the most common new drugs are NMDA receptor antagonists, followed by 5-HT targets, as well as dopamine receptor agonists, opioid receptor antagonists and agonists, AMPA receptor modulators, glucocorticoid receptor antagonists, NK1 receptor antagonists, and serotonin transporter inhibitors (Fig. 3 B).

Epidemiology of Depression

The prevalence of depression varies greatly across cultures and countries. Previous surveys have demonstrated that the 12-month prevalence of depression was 0.3% in the Czech Republic, 10% in the USA, 4.5% in Mexico, and 5.2% in West Germany, and the lifetime prevalence of depression was 1.0% in the Czech Republic, 16.9% in the USA, 8.3% in Canada, and 9.0% in Chile [ 4 , 5 ]. A recent meta-analysis including 30 Countries showed that lifetime and 12-month prevalence depression were 10.8% and 7.2%, respectively [ 6 ]. In China, the lifetime prevalence of depression ranged from 1.6% to 5.5% [ 7 , 8 , 9 ]. An epidemiological study demonstrated that depression was the most common mood disorder with a life prevalence of 3.4% and a 12-month prevalence of 2.1% in China [ 10 ].

Some studies have also reported the prevalence in specific populations. The National Comorbidity Survey-Adolescent Supplement (NCS-A) survey in the USA showed that the lifetime and 12-month prevalence of depression in adolescents aged 13 to 18 were 11.0% and 7.5%, respectively [ 11 ]. A recent meta-analysis demonstrated that lifetime prevalence and 12-month prevalence were 2.8% and 2.3%, respectively, among the elderly population in China [ 12 ].

Neurobiological Pathogenesis of Depressive Disorder

The early hypothesis of monoamines in the pathophysiology of depression has been accepted by the scientific community. The evidence that monoamine oxidase inhibitors and tricyclic antidepressants promote monoamine neurotransmission supports this theory of depression [ 13 ]. So far, selective serotonin reuptake inhibitors and norepinephrine reuptake inhibitors are still the first-line antidepressants. However, there remain 1/3 to 2/3 of depressed patients who do not respond satisfactorily to initial antidepressant treatment, and even as many as 15%–40% do not respond to several pharmacological medicines [ 14 , 15 ]. Therefore, the underlying pathogenesis of depression is far beyond the simple monoamine mechanism.

Other hypotheses of depression have gradually received increasing attention because of biomarkers for depression and the effects pharmacological treatments, such as the stress-responsive hypothalamic pituitary adrenal (HPA) axis, neuroendocrine systems, the neurotrophic family of growth factors, and neuroinflammation.

Stress-Responsive HPA Axis

Stress is causative or a contributing factor to depression. Particularly, long-term or chronic stress can lead to dysfunction of the HPA axis and promote the secretion of hormones, including cortisol, adrenocorticotropic hormone, corticotropin-releasing hormone, arginine vasopressin, and vasopressin. About 40%–60% of patients with depression display a disturbed HPA axis, including hypercortisolemia, decreased rhythmicity, and elevated cortisol levels [ 16 , 17 ]. Mounting evidence has shown that stress-induced abnormality of the HPA axis is associated with depression and cognitive impairment, which is due to the increased secretion of cortisol and the insufficient inhibition of glucocorticoid receptor regulatory feedback [ 18 , 19 ]. In addition, it has been reported that the increase in cortisol levels is related to the severity of depression, especially in melancholic depression [ 20 , 21 ]. Further, patients with depression whose HPA axis was not normalized after treatment had a worse clinical response and prognosis [ 22 , 23 ]. Despite the above promising insights, unfortunately previous studies have shown that treatments regulating the HPA axis, such as glucocorticoid receptor antagonists, do not attenuate the symptoms of depressed patients [ 24 , 25 ].

Glutamate Signaling Pathway

Glutamate is the main excitatory neurotransmitter released by synapses in the brain; it is involved in synaptic plasticity, cognitive processes, and reward and emotional processes. Stress can induce presynaptic glutamate secretion by neurons and glutamate strongly binds to ionotropic glutamate receptors (iGluRs) including N-methyl-D-aspartate receptors (NMDARs) and α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptors (AMPARs) [ 26 ] on the postsynaptic membrane to activate downstream signal pathways [ 27 ]. Accumulating evidence has suggested that the glutamate system is associated with the incidence of depression. Early studies have shown increased levels of glutamate in the peripheral blood, cerebrospinal fluid, and brain of depressed patients [ 28 , 29 ], as well as NMDAR subunit disturbance in the brain [ 30 , 31 ]. Blocking the function of NMDARs has an antidepressant effect and protects hippocampal neurons from morphological abnormalities induced by stress, while antidepressants reduce glutamate secretion and NMDARs [ 32 ]. Most importantly, NMDAR antagonists such as ketamine have been reported to have profound and rapid antidepressant effects on both animal models and the core symptoms of depressive patients [ 33 ]. On the other hand, ketamine can also increase the AMPAR pathway in hippocampal neurons by up-regulating the AMPA glutamate receptor 1 subunit [ 34 ]. Further, the AMPAR pathway may be involved in the mechanism of antidepressant effects. For example, preclinical studies have indicated that AMPAR antagonists might attenuate lithium-induced depressive behavior by increasing the levels of glutamate receptors 1 and 2 in the mouse hippocampus [ 35 ].

Gamma-Aminobutyric Acid (GABA)

Contrary to glutamate, GABA is the main inhibitory neurotransmitter. Although GABA neurons account for only a small proportion compared to glutamate, inhibitory neurotransmission is essential for brain function by balancing excitatory transmission [ 36 ]. Number of studies have shown that patients with depression have neurotransmission or functional defects of GABA [ 37 , 38 ]. Schür et al ., conducted a meta-analysis of magnetic resonance spectroscopy studies, which showed that the brain GABA level in depressive patients was lower than that in healthy controls, but no difference was found in depressive patients in remission [ 39 ]. Several postmortem studies have shown decreased levels of the GABA synthase glutamic acid decarboxylase in the prefrontal cortex of patients with depression [ 40 , 41 ]. It has been suggested that a functional imbalance of the GABA and glutamate systems contributes to the pathophysiology of depression, and activation of the GABA system might induce antidepressant activity, by which GABA A  receptor mediators α2/α3 are considered potential antidepressant candidates [ 42 , 43 ]. Genetic mouse models, such as the GABA A receptor mutant mouse and conditional the Gad1-knockout mouse (GABA in hippocampus and cerebral cortex decreased by 50%) and optogenetic methods have verified that depression-like behavior is induced by changing the level of GABA [ 44 , 45 ].

Neurotrophin Family

The neurotrophin family plays a key role in neuroplasticity and neurogenesis. The neurotrophic hypothesis of depression postulates that a deficit of neurotrophic support leads to neuronal atrophy, the reduction of neurogenesis, and the destruction of glia support, while antidepressants attenuate or reverse these pathophysiological processes [ 46 ]. Among them, the most widely accepted hypothesis involves brain-derived neurotrophic factor (BDNF). This was initially triggered by evidence that stress reduces the BDNF levels in the animal brain, while antidepressants rescue or attenuate this reduction [ 47 , 48 ], and agents involved in the BDNF system have been reported to exert antidepressant-like effects [ 49 , 50 ]. In addition, mounting studies have reported that the BDNF level is decreased in the peripheral blood and at post-mortem in depressive patients, and some have reported that antidepressant treatment normalizes it [ 51 , 52 ]. Furthermore, some evidence also showed that the interaction of BDNF and its receptor gene is associated with treatment-resistant depression [ 15 ].

Recent studies reported that depressed patients have a lower level of the pro-domain of BDNF (BDNF pro-peptide) than controls. This is located presynaptically and promotes long-term depression in the hippocampus, suggesting that it is a promising synaptic regulator [ 53 ].

Neuroinflammation

The immune-inflammation hypothesis has attracted much attention, suggesting that the interactions between inflammatory pathways and neural circuits and neurotransmitters are involved in the pathogenesis and pathophysiological processes of depression. Early evidence found that patients with autoimmune or infectious diseases are more likely to develop depression than the general population [ 54 ]. In addition, individuals without depression may display depressive symptoms after treatment with cytokines or cytokine inducers, while antidepressants relieve these symptoms [ 55 , 56 ]. There is a complex interaction between the peripheral and central immune systems. Previous evidence suggested that peripheral inflammation/infection may spread to the central nervous system in some way and cause a neuroimmune response [ 55 , 57 ]: (1) Some cytokines produced in the peripheral immune response, such as IL-6 and IL-1 β, can leak into the brain through the blood-brain barrier (BBB). (2) Cytokines entering the central nervous system act directly on astrocytes, small stromal cells, and neurons. (3) Some peripheral immune cells can cross the BBB through specific transporters, such as monocytes. (4) Cytokines and chemokines in the circulation activate the central nervous system by regulating the surface receptors of astrocytes and endothelial cells at the BBB. (5) As an intermediary pathway, the immune inflammatory response transmits peripheral danger signals to the center, amplifies the signals, and shows the external phenotype of depressive behavior associated with stress/trauma/infection. (6) Cytokines and chemokines may act directly on neurons, change their plasticity and promote depression-like behavior.

Patients with depression show the core feature of the immune-inflammatory response, that is, increased concentrations of pro-inflammatory cytokines and their receptors, chemokines, and soluble adhesion molecules in peripheral blood and cerebrospinal fluid [ 58 , 59 , 60 ]. Peripheral immune-inflammatory response markers not only change the immune activation state in the brain that affects explicit behavior, but also can be used as an evaluation index or biological index of antidepressant therapy [ 61 , 62 ]. Li et al . showed that the level of TNF-α in patients with depression prior to treatment was higher than that in healthy controls. After treatment with venlafaxine, the level of TNF-α in patients with depression decreased significantly, and the level of TNF-α in the effective group decreased more [ 63 ]. A recent meta-analysis of 1,517 patients found that antidepressants significantly reduced peripheral IL-6, TNF-α, IL-10, and CCL-2, suggesting that antidepressants reduce markers of peripheral inflammatory factors [ 64 ]. Recently, Syed et al . also confirmed that untreated patients with depression had higher levels of inflammatory markers and increased levels of anti-inflammatory cytokines after antidepressant treatment, while increased levels of pro-inflammatory cytokines were found in non-responders [ 62 ]. Clinical studies have also found that anti-inflammatory cytokines, such as monoclonal antibodies and other cytokine inhibitors, may play an antidepressant role by blocking cytokines. The imbalance of pro-inflammatory and anti-inflammatory cytokines may be involved in the pathophysiological process of depression.

In addition, a recent study showed that microglia contribute to neuronal plasticity and neuroimmune interaction that are involved in the pathophysiology of depression [ 65 ]. When activated microglia promote inflammation, especially the excessive production of pro-inflammatory factors and cytotoxins in the central nervous system, depression-like behavior can gradually develop [ 65 , 66 ]. However, microglia change polarization as two types under different inflammatory states, regulating the balance of pro- and anti-inflammatory factors. These two types are M1 and M2 microglia; the former produces large number of pro-inflammatory cytokines after activation, and the latter produces anti-inflammatory cytokines. An imbalance of M1/M2 polarization of microglia may contribute to the pathophysiology of depression [ 67 ].

Microbiome-Gut-Brain Axis

The microbiota-gut-brain axis has recently gained more attention because of its ability to regulate brain activity. Many studies have shown that the microbiota-gut-brain axis plays an important role in regulating mood, behavior, and neuronal transmission in the brain [ 68 , 69 ]. It is well established that comorbidity of depression and gastrointestinal diseases is common [ 70 , 71 ]. Some antidepressants can attenuate the symptoms of patients with irritable bowel syndrome and eating disorders [ 72 ]. It has been reported that gut microbiome alterations are associated with depressive-like behaviors [ 73 , 74 ], and brain function [ 75 ]. Early animal studies have shown that stress can lead to long-term changes in the diversity and composition of intestinal microflora, and is accompanied by depressive behavior [ 76 , 77 ]. Interestingly, some evidence indicates that rodents exhibit depressive behavior after fecal transplants from patients with depression [ 74 ]. On the other hand, some probiotics attenuated depressive-like behavior in animal studies, [ 78 ] and had antidepressant effects on patients with depression in several double-blind, placebo-controlled clinical trials [ 79 , 80 ].

The potential mechanism may be that gut microbiota can interact with the brain through a variety of pathways or systems, including the HPA axis, and the neuroendocrine, autonomic, and neuroimmune systems [ 81 ]. For example, recent evidence demonstrated that gut microbiota can affect the levels of neurotransmitters in the gut and brain, including serotonin, dopamine, noradrenalin, glutamate, and GABA [ 82 ]. In addition, recent studies showed that changes in gut microbiota can also impair the gut barrier and promote higher levels of peripheral inflammatory cytokines [ 83 , 84 ]. Although recent research in this area has made significant progress, more clinical trials are needed to determine whether probiotics have any effect on the treatment of depression and what the potential underlying mechanisms are.

Other Systems and Pathways

There is no doubt that several other systems or pathways are also involved in the pathophysiology of depression, such as oxidant-antioxidant imbalance [ 85 ], mitochondrial dysfunction [ 86 , 87 ], and circadian rhythm-related genes [ 88 ], especially their critical interactions ( e.g. interaction between the HPA and mitochondrial metabolism [ 89 , 90 ], and the reciprocal interaction between oxidative stress and inflammation [ 2 , 85 ]). The pathogenesis of depression is complex and all the hypotheses should be integrated to consider the many interactions between various systems and pathways.

Advances in Various Kinds of Research on Depressive Disorder

Genetic, molecular, and neuroimaging studies continue to increase our understanding of the neurobiological basis of depression. However, it is still not clear to what extent the results of neurobiological studies can help improve the clinical and functional prognosis of patients. Therefore, over the past 10 years, the neurobiological study of depression has become an important measure to understand the pathophysiological mechanism and guide the treatment of depression.

Genetic Studies

Previous twin and adoption studies have indicated that depression has relatively low rate of heritability at 37% [ 91 ]. In addition, environmental factors such as stressful events are also involved in the pathogenesis of depression. Furthermore, complex psychiatric disorders, especially depression, are considered to be polygenic effects that interact with environmental factors [ 13 ]. Therefore, reliable identification of single causative genes for depression has proved to be challenging. The first genome-wide association studies (GWAS) for depression was published in 2009, and included 1,738 patients and 1,802 controls [ 92 , 93 ]. Although many subsequent GWASs have determined susceptible genes in the past decade, the impact of individual genes is so small that few results can be replicated [ 94 , 95 ]. So far, it is widely accepted that specific single genetic mutations may play minor and marginal roles in complex polygenic depression. Another major recognition in GWASs over the past decade is that prevalent candidate genes are usually not associated with depression. Further, the inconsistent results may also be due to the heterogeneity and polygenic nature of genetic and non-genetic risk factors for depression as well as the heterogeneity of depression subtypes [ 95 , 96 ]. Therefore, to date, the quality of research has been improved in two aspects: (1) the sample size has been maximized by combining the data of different evaluation models; and (2) more homogenous subtypes of depression have been selected to reduce phenotypic heterogeneity [ 97 ]. Levinson et al . pointed out that more than 75,000 to 100,000 cases should be considered to detect multiple depression associations [ 95 ]. Subsequently, several recent GWASs with larger sample sizes have been conducted. For example, Okbay et al . identified two loci associated with depression and replicated them in separate depression samples [ 98 ]. Wray et al . also found 44 risk loci associated with depression based on 135,458 cases and 344,901 controls [ 99 ]. A recent GWAS of 807,553 individuals with depression reported that 102 independent variants were associated with depression; these were involved in synaptic structure and neural transmission, and were verified in a further 1,507,153 individuals [ 100 ]. However, even with enough samples, GWASs still face severe challenges. A GWAS only marks the region of the genome and is not directly related to the potential biological function. In addition, a genetic association with the indicative phenotype of depression may only be part of many pathogenic pathways, or due to the indirect influence of intermediate traits in the causal pathway on the final result [ 101 ].

Given the diversity of findings, epigenetic factors are now being investigated. Recent studies indicated that epigenetic mechanisms may be the potential causes of "loss of heritability" in GWASs of depression. Over the past decade, a promising discovery has been that the effects of genetic information can be directly influenced by environment factors, and several specific genes are activated by environmental aspects. This process is described as interactions between genes and the environment, which is identified by the epigenetic mechanism. Environmental stressors cause alterations in gene expression in the brain, which may cause abnormal neuronal plasticity in areas related to the pathogenesis of the disease. Epigenetic events alter the structure of chromatin, thereby regulating gene expression involved in neuronal plasticity, stress behavior, depressive behavior, and antidepressant responses, including DNA methylation, histone acetylation, and the role of non-coding RNA. These new mechanisms of trans-generational transmission of epigenetic markers are considered a supplement to orthodox genetic heredity, providing the possibility for the discovery of new treatments for depression [ 102 , 103 ]. Recent studies imply that life experiences, including stress and enrichment, may affect cellular and molecular signaling pathways in sperm and influence the behavioral and physiological phenotypes of offspring in gender-specific patterns, which may also play an important role in the development of depression [ 103 ].

Brain Imaging and Neuroimaging Studies

Neuroimaging, including magnetic resonance imaging (MRI) and molecular imaging, provides a non-invasive technique for determining the underlying etiology and individualized treatment for depression. MRI can provide important data on brain structure, function, networks, and metabolism in patients with depression; it includes structural MRI (sMRI), functional MRI (fMRI), diffusion tensor imaging, and magnetic resonance spectroscopy.

Previous sMRI studies have found damaged gray matter in depression-associated brain areas, including the frontal lobe, anterior cingulate gyrus, hippocampus, putamen, thalamus, and amygdala. sMRI focuses on the thickness of gray matter and brain morphology [ 104 , 105 ]. A recent meta-analysis of 2,702 elderly patients with depression and 11,165 controls demonstrated that the volumes of the whole brain and hippocampus of patients with depression were lower than those of the control group [ 106 ]. Some evidence also showed that the hippocampal volume in depressive patients was lower than that of controls, and increased after treatment with antidepressants [ 107 ] and electroconvulsive therapy (ECT) [ 108 ], suggesting that the hippocampal volume plays a critical role in the development, treatment response, and clinical prognosis of depression. A recent study also reported that ECT increased the volume of the right hippocampus, amygdala, and putamen in patients with treatment-resistant depression [ 109 ]. In addition, postmortem research supported the MRI study showing that dentate gyrus volume was decreased in drug-naive patients with depression compared to healthy controls, and was potentially reversed by treatment with antidepressants [ 110 ].

Diffusion tensor imaging detects the microstructure of the white matter, which has been reported impaired in patients with depression [ 111 ]. A recent meta-analysis that included first-episode and drug-naïve depressive patients showed that the decrease in fractional anisotropy was negatively associated with illness duration and clinical severity [ 112 ].

fMRI, including resting-state and task-based fMRI, can divide the brain into self-related regions, such as the anterior cingulate cortex, posterior cingulate cortex, medial prefrontal cortex, precuneus, and dorsomedial thalamus. Many previous studies have shown the disturbance of several brain areas and intrinsic neural networks in patients with depression which could be rescued by antidepressants [ 113 , 114 , 115 , 116 ]. Further, some evidence also showed an association between brain network dysfunction and the clinical correlates of patients with depression, including clinical symptoms [ 117 ] and the response to antidepressants [ 118 , 119 ], ECT [ 120 , 121 ], and repetitive transcranial magnetic stimulation [ 122 ].

It is worth noting that brain imaging provides new insights into the large-scale brain circuits that underlie the pathophysiology of depressive disorder. In such studies, large-scale circuits are often referred to as “networks”. There is evidence that a variety of circuits are involved in the mechanisms of depressive disorder, including disruption of the default mode, salience, affective, reward, attention, and cognitive control circuits [ 123 ]. Over the past decade, the study of intra-circuit and inter-circuit connectivity dysfunctions in depression has escalated, in part due to advances in precision imaging and analysis techniques [ 124 ]. Circuit dysfunction is a potential biomarker to guide psychopharmacological treatment. For example, Williams et al . found that hyper-activation of the amygdala is associated with a negative phenotype that can predict the response to antidepressants [ 125 ]. Hou et al . showed that the baseline characteristics of the reward circuit predict early antidepressant responses [ 126 ].

Molecular imaging studies, including single photon emission computed tomography and positron emission tomography, focus on metabolic aspects such as amino-acids, neurotransmitters, glucose, and lipids at the cellular level in patients with depression. A recent meta-analysis examined glucose metabolism and found that glucose uptake dysfunction in different brain regions predicts the treatment response [ 127 ].

The most important and promising studies were conducted by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, which investigated the human brain across 43 countries. The ENIGMA-MDD Working Group was launched in 2012 to detect the structural and functional changes associated with MDD reliably and replicate them in various samples around the world [ 128 ]. So far, the ENIGMA-MDD Working Group has collected data from 4,372 MDD patients and 9,788 healthy controls across 14 countries, including 45 cohorts [ 128 ]. Their findings to date are shown in Table 1 [ 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 ].

Objective Index for Diagnosis of MDD

To date, the clinical diagnosis of depression is subjectively based on interviews according to diagnostic criteria ( e.g. International Classification of Diseases and Diagnostic and Statistical Manual diagnostic systems) and the severity of clinical symptoms are assessed by questionnaires, although patients may experience considerable differences in symptoms and subtypes [ 138 ]. Meanwhile, biomarkers including genetics, epigenetics, peripheral gene and protein expression, and neuroimaging markers may provide a promising supplement for the development of the objective diagnosis of MDD, [ 139 , 140 , 141 ]. However, the development of reliable diagnosis for MDD using biomarkers is still difficult and elusive, and all methods based on a single marker are insufficiently specific and sensitive for clinical use [ 142 ]. Papakostas et al . showed that a multi-assay, serum-based test including nine peripheral biomarkers (soluble tumor necrosis factor alpha receptor type II, resistin, prolactin, myeloperoxidase, epidermal growth factor, BDNF, alpha1 antitrypsin, apolipoprotein CIII, brain-derived neurotrophic factor, and cortisol) yielded a specificity of 81.3% and a sensitivity of 91.7% [ 142 ]. However, the sample size was relatively small and no other studies have yet validated their results. Therefore, further studies are needed to identify biomarker models that integrate all biological variables and clinical features to improve the specificity and sensitivity of diagnosis for MDD.

Management of Depression

The treatment strategies for depression consist of pharmacological treatment and non-pharmacological treatments including psychotherapy, ECT [ 98 ], and transcranial magnetic stimulation. As psychotherapy has been shown to have effects on depression including attenuating depressive symptoms and improving the quality of life [ 143 , 144 ]; several practice guidelines are increasingly recommending psychotherapy as a monotherapy or in combination with antidepressants [ 145 , 146 ].

Current Antidepressant Treatment

Antidepressants approved by the US Food and Drug Administration (FDA) are shown in Table 2 . Due to the relatively limited understanding of the etiology and pathophysiology of depression, almost all the previous antidepressants were discovered by accident a few decades ago. Although most antidepressants are usually safe and effective, there are still some limitations, including delayed efficacy (usually 2 weeks) and side-effects that affect the treatment compliance [ 147 ]. In addition, <50% of all patients with depression show complete remission through optimized treatment, including trials of multiple drugs with and without simultaneous psychotherapy. In the past few decades, most antidepressant discoveries focused on finding faster, safer, and more selective serotonin or norepinephrine receptor targets. In addition, there is an urgent need to develop new approaches to obtain more effective, safer, and faster antidepressants. In 2019, the FDA approved two new antidepressants: Esketamine for refractory depression and Bresanolone for postpartum depression. Esmolamine, a derivative of the anesthetic drug ketamine, was approved by the FDA for the treatment of refractory depression, based on a large number of preliminary clinical studies [ 148 ]. For example, several randomized controlled trials and meta-analysis studies showed the efficacy and safety of Esketamine in depression or treatment-resistant depression [ 26 , 149 , 150 ]. Although both are groundbreaking new interventions for these debilitating diseases and both are approved for use only under medical supervision, there are still concerns about potential misuse and problems in the evaluation of mental disorders [ 151 ].

To date, although several potential drugs have not yet been approved by the FDA, they are key milestones in the development of antidepressants that may be modified and used clinically in the future, such as compounds containing dextromethorphan (a non-selective NMDAR antago–nist), sarcosine (N-methylglycine, a glycine reuptake inhibitor), AMPAR modulators, and mGluR modulators [ 152 ].

Neuromodulation Therapy

Neuromodulation therapy acts through magnetic pulse, micro-current, or neural feedback technology within the treatment dose, acting on the central or peripheral nervous system to regulate the excitatory/inhibitory activity to reduce or attenuate the symptoms of the disease.

ECT is one of most effective treatments for depression, with the implementation of safer equipment and advancement of techniques such as modified ECT [ 153 ]. Mounting evidence from randomized controlled trial (RCT) and meta-analysis studies has shown that rTMS can treat depressive patients with safety [ 154 ]. Other promising treatments for depression have emerged, such as transcranial direct current stimulation (tDCS) [ 155 ], transcranial alternating current stimulation (tACS)[ 156 ], vagal nerve stimulation [ 157 ], deep brain stimulation [ 158 ] , and light therapy [ 159 ], but some of them are still experimental to some extent and have not been widely used. For example, compared to tDCS, tACS displays less sensory experience and adverse reactions with weak electrical current in a sine-wave pattern, but the evidence for the efficacy of tACS in the treatment of depression is still limited [ 160 ]. Alexander et al . recently demonstrated that there was no difference in efficacy among different treatments (sham, 10-Hz and 40-Hz tACS). However, only the 10-Hz tACS group had more responders than the sham and 40-Hz tACS groups at week 2 [ 156 ]. Further RCT studies are needed to verify the efficacy of tACS. In addition, the mechanism of the effect of neuromodulation therapy on depression needs to be further investigated.

Precision Medicine for Depression

Optimizing the treatment strategy is an effective way to improve the therapeutic effect on depression. However, each individual with depression may react very differently to different treatments. Therefore, this raises the question of personalized treatment, that is, which patients are suitable for which treatment. Over the past decade, psychiatrists and psychologists have focused on individual biomarkers and clinical characteristics to predict the efficiency of antidepressants and psychotherapies, including genetics, peripheral protein expression, electrophysiology, neuroimaging, neurocognitive performance, developmental trauma, and personality [ 161 ]. For example, Bradley et al . recently conducted a 12-week RCT, which demonstrated that the response rate and remission rates of the pharmacogenetic guidance group were significantly higher than those of the non-pharmacogenetic guidance group [ 162 ].

Subsequently, Greden et al . conducted an 8-week RCT of Genomics Used to Improve Depression Decisions (GUIDED) on 1,167 MDD patients and demonstrated that although there was no difference in symptom improvement between the pharmacogenomics-guided and non- pharmacogenomics-guided groups, the response rate and remission rate of the pharmacogenomics-guided group increased significantly [ 163 ].

A recent meta-analysis has shown that the baseline default mode network connectivity in patients with depression can predict the clinical responses to treatments including cognitive behavioral therapy, pharmacotherapy, ECT, rTMS, and transcutaneous vagus nerve stimulation [ 164 ]. However, so far, the biomarkers that predict treatment response at the individual level have not been well applied in the clinic, and there is still a lot of work to be conducted in the future.

Future Perspectives

Although considerable progress has been made in the study of depression during a past decade, the heterogeneity of the disease, the effectiveness of treatment, and the gap in translational medicine are critical challenges. The main dilemma is that our understanding of the etiology and pathophysiology of depression is inadequate, so our understanding of depression is not deep enough to develop more effective treatment. Animal models still cannot fully simulate this heterogeneous and complex mental disorder. Therefore, how to effectively match the indicators measured in animals with those measured in genetic research or the development of new antidepressants is another important challenge.

Change history

17 may 2021.

A Correction to this paper has been published: https://doi.org/10.1007/s12264-021-00694-9

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Acknowledgments

This review was supported by the National Basic Research Development Program of China (2016YFC1307100), the National Natural Science Foundation of China (81930033 and 81771465; 81401127), Shanghai Key Project of Science & Technology (2018SHZDZX05), Shanghai Jiao Tong University Medical Engineering Foundation (YG2016MS48), Shanghai Jiao Tong University School of Medicine (19XJ11006), the Sanming Project of Medicine in Shenzhen Municipality (SZSM201612006), the National Key Technologies R&D Program of China (2012BAI01B04), and the Innovative Research Team of High-level Local Universities in Shanghai.

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Clinical Research Center and Division of Mood Disorders of Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China

Zezhi Li, Jun Chen & Yiru Fang

Department of Neurology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China

Shanghai Institute of Nutrition and Health, Shanghai Information Center for Life Sciences, Chinese Academy of Science, Shanghai, 200031, China

Meihua Ruan

Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Science, Shanghai, 200031, China

Shanghai Key Laboratory of Psychotic Disorders, Shanghai, 201108, China

Jun Chen & Yiru Fang

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Li, Z., Ruan, M., Chen, J. et al. Major Depressive Disorder: Advances in Neuroscience Research and Translational Applications. Neurosci. Bull. 37 , 863–880 (2021). https://doi.org/10.1007/s12264-021-00638-3

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DOI : https://doi.org/10.1007/s12264-021-00638-3

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Why Depression Rates Are Higher Among Liberals

Columbia researchers look at the politics of despair.

Photo of woman looking sadly at phone with blue light emanating

American adults who identify as politically liberal have long reported lower levels of happiness and psychological well-being than conservatives, a trend that mental-health experts suspect is at least partly explained by liberals’ tendency to spend more time worrying about stress-inducing topics like racial injustice, income inequality, gun violence, and climate change.

Now a team of Columbia epidemiologists has found evidence that the same pattern holds for American teenagers. The researchers analyzed surveys collected from more than eighty-six thousand twelfth graders over a thirteen-year period and discovered that while rates of depression have been rising among students of all political persuasions and demographics, they have been increasing most sharply among progressive students — and especially among liberal girls from low-income families.

The authors, who include Columbia professors Katherine M. Keyes ’10PH, Seth J. Prins ’16PH, and Lisa M. Bates , along with graduate student and lead author Catherine Gimbrone, speculate that left-leaning teens may have been deeply affected by Donald Trump’s election as president, the US Supreme Court’s subsequent lurch to the right, rising socioeconomic inequality, and worsening political polarization. “Liberal adolescents may have therefore experienced alienation within a growing conservative political climate such that their mental health suffered in comparison to that of their conservative peers whose hegemonic views were flourishing,” they write.

This article appears in the Spring/Summer 2023 print edition of Columbia Magazine with the title "The politics of depression."

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