• Open access
  • Published: 06 July 2020

Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: a systematic review and meta-analysis

  • Nader Salari 1 , 2 ,
  • Amin Hosseinian-Far 3 ,
  • Rostam Jalali 4 ,
  • Aliakbar Vaisi-Raygani 4 ,
  • Shna Rasoulpoor 5 ,
  • Masoud Mohammadi   ORCID: orcid.org/0000-0002-5722-8300 4 ,
  • Shabnam Rasoulpoor 4 &
  • Behnam Khaledi-Paveh 2  

Globalization and Health volume  16 , Article number:  57 ( 2020 ) Cite this article

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The COVID-19 pandemic has had a significant impact on public mental health. Therefore, monitoring and oversight of the population mental health during crises such as a panedmic is an immediate priority. The aim of this study is to analyze the existing research works and findings in relation to the prevalence of stress, anxiety and depression in the general population during the COVID-19 pandemic.

In this systematic review and meta-analysis, articles that have focused on stress and anxiety prevalence among the general population during the COVID-19 pandemic were searched in the Science Direct, Embase, Scopus, PubMed, Web of Science (ISI) and Google Scholar databases, without a lower time limit and until May 2020. In order to perform a meta-analysis of the collected studies, the random effects model was used, and the heterogeneity of studies was investigated using the I 2 index. Moreover. data analysis was conducted using the Comprehensive Meta-Analysis (CMA) software.

The prevalence of stress in 5 studies with a total sample size of 9074 is obtained as 29.6% (95% confidence limit: 24.3–35.4), the prevalence of anxiety in 17 studies with a sample size of 63,439 as 31.9% (95% confidence interval: 27.5–36.7), and the prevalence of depression in 14 studies with a sample size of 44,531 people as 33.7% (95% confidence interval: 27.5–40.6).

COVID-19 not only causes physical health concerns but also results in a number of psychological disorders. The spread of the new coronavirus can impact the mental health of people in different communities. Thus, it is essential to preserve the mental health of individuals and to develop psychological interventions that can improve the mental health of vulnerable groups during the COVID-19 pandemic.

In December 2019, in the city of Wuhan, China, unusual cases of patients with pneumonia caused by the new Coronavirus (COVID-19) were reported [ 1 ], and the spread of the virus swiftly became a global health threat [ 2 ]. There have been several viral diseases in the past 20 years including Severe Acute Respiratory Syndrome (SARS) in 2003, influenza virus with the H1N1 subtype in 2009, Middle East Respiratory Syndrome (MERS) in 2012, and Ebola virus in 2014 [ 3 , 4 , 5 ].

Although COVID-19 is a new strain of coronaviruses, it is known to cause diseases ranging from cold to more severe illnesses such as SARS and MERS [ 5 ]. Symptoms of the Coronavirus infection include fever, chills, cough, sore throat, myalgia, nausea and vomiting, and diarrhea. Men with a history of underlying diseases are more likely to be infected with the virus and would experience worse outcomes [ 6 ]. Severe cases of the disease can lead to heart, and respiratory failure, acute respiratory syndrome, or even death [ 7 ]. In addition to the physical impacts, COVID-19 can have serious effects on people’s mental health [ 8 ]. A wide range of psychological outcomes have been observed during the Virus outbreak, at individual, community, national, and international levels. At the individual level, people are more likely to experience fear of getting sick or dying, feeling helpless, and being stereotyped by others [ 9 ]. The pandemic has had a harmful effect on the public mental health which can even lead to psychological crises [ 10 ]. Early identification of individuals in the early stages of a psychological disorder makes the intervention strategies more effective. Health crises such the COVID-19 pandemic lead to psychological changes, not only in the medical workers, but also in the citizens, and such psychological changes are instigated by fear, anxiety, depression, or insecurity [ 11 ].

Nervousness and anxiety in a society affect everyone to a large extent. Recent evidence suggests that people who are kept in isolation and quarantine experience significant levels of anxiety, anger, confusion, and stress [ 12 ]. At large, all of the studies that have examined the psychological disorders during the COVID-19 pandemic have reported that the affected individuals show several symptoms of mental trauma, such as emotional distress, depression, stress, mood swings, irritability, insomnia, attention deficit hyperactivity disorder, post-traumatic stress, and anger [ 12 , 13 , 14 ]. Research has also shown that frequent media exposure may cause distress [ 15 ]. Nevertheless, in the current situation, it is challenging to accurately predict the psychological and emotional consequences of COVID-19. Studies conducted in China, the first country that was affected by this recent Virus spread, show that people’s fear of the unknown nature of the Virus can lead to mental disorders [ 16 ].

Due to the pathogenicity of the virus, the rate of spread, the resulting high mortality rate, COVID-19 may affect the mental health of individuals at several layers of society, ranging from the infected patients, and health care workers, to families, children, students, patients with mental illness, and even workers in other sectors [ 17 , 18 , 19 ].

Considering several reported psychological consequences of COVID-19 and its spread (Fig.  1 ), and the lack of general statistics on the topic globally, we decided to conduct a systematic review of the existing studies in this field, with a view to providing a holistic, yet comprehensive statistics on the impact of the Virus on general population mental health. The aim of this study is to examine and systematically review and analyze the literature and their reported results related to the impacts of COVID-19 on the prevalence of stress, anxiety, and depression.

figure 1

Impacts of the COVID-19 pandemic on mental health

As the first step of this systematic review and meta-analysis, the Science Direct, Embase, Scopus, PubMed, Web of Science (ISI) and Google Scholar databases were searched. To identify the articles, the search terms of Coronavirus, COVID-19, 2019-ncov, SARS-cov-2, Mental illness, Mental health problem, Distress, Anxiety, Depression, and all the possible combinations of these keywords were used.

(((((((((((((Coronavirus [Title/Abstract]) OR (COVID-19[Title/Abstract])) OR (2019-ncov [Title/Abstract])) AND (SARS-cov-2[Title/Abstract])) AND (Mental illness [Title/Abstract])) OR (Mental health problem [Title/Abstract])) AND (Anxiety [Title/Abstract])) AND (Social Anxiety [Title/Abstract])) OR (Anxiety Disorders [Title/Abstract])) AND (Depression [Title/Abstract])) OR (Emotional Depression [Title/Abstract])) OR (Depressive Symptoms [Title/Abstract]))))))))))))

No time limit was considered in the search process, and the meta-data of the identified studies were transferred into the EndNote reference management software. In order to maximize the comprehensiveness of the search, the lists of references used within all the collected articles were manually reviewed.

Inclusion and exclusion criteria

The criteria for entering the systematic review included: 1- Studies that examined the prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic. 2- Studies that were observational (i.e. non-interventional studies) 3- Studies that their full text was available. The criteria for excluding a study were: 1- Unrelated research works, 2- Studies without sufficient data, 3- Duplicate sources, 4-Pieces of research with unclear methods 5- Interventional studies 6- Case reports, and 7- Articles that their full text was not available.

Study selection

Initially, duplicate articles that were repeatedly found in various databases were removed. Then, a title list of all the remaining articles was prepared, so that the articles could be filtered out during the evaluation phase in a structured way. As part of the first stage of the systematic review process, i.e. screening, the title and abstract of the remaining articles were carefully examined, and a number of articles were removed considering the inclusion and exclusion criteria. In the second stage, i.e. eligibility evaluation, the full text of the studies, remaining from the screening stage, were thoroughly examined according to the criteria, and similarly, a number of other unrelated studies were excluded. To prevent subjectivity, article review and data extraction activities were performed by two reviewers, independently. If an article was not included, the reason for excluding it was mentioned. In cases where there was a disagreement between the two reviewers, a third person reviewed the article. Seventeen studies entered the third stage, i.e. quality evaluation.

Quality evaluation

In order to examine the quality of the remaining articles (i.e. methodological validity and results), a checklist appropriate to the type of study was adopted. STROBE checklists are commonly used to critique and evaluate the quality of observational studies. The checklist consists of six scales/general sections that are: title, abstract, introduction, methods, results, and discussion. Some of these scales have subscales, resulting in a total of 32 fields (subscales). In fact, these 32 fields represent different methodological aspects of a piece of research. Examples of subscales include title, problem statement, study objectives, study type, statistical population, sampling method, sample size, the definition of variables and procedures, data collection method(s), statistical analysis techniques, and findings. Accordingly, the maximum score that can be obtained during the quality evaluation phase and using the STROBE checklist is 32. By considering the score of 16 as the cut-off point, any article with a score of 16 or above is considered as a medium or a high-quality article [ 20 ]. Sixteen papers obtained a score below 16, denoting a low methodological quality, and were therefore excluded from the study. In the present study, following the quality evaluation by means of the STROBE checklist, 17 papers, with a medium or high quality, entered the systematic review and meta-analysis phases.

Data extraction

Data of from all the final studies were extracted using a different pre-prepared checklist. The items on the checklist included: article title, first author’s name, year of publication, place of study, sample size, assessment method, gender, type of study, the prevalence of depression, anxiety, and stress.

Statistical analysis

The I 2 (%) test was used to assess the heterogeneity of the selected research works. In order to assess publication bias, due to the high volume of samples that entered the study, the Egger’s test was conducted with the significance level of 0.05, and the corresponding Forest plots were drawn. Data analysis was performed using the Comprehensive Meta-Analysis (CMA version 2.0) software.

In this work, the prevalence of stress and anxiety among general population during the COVID-19 pandemic was assessed. Articles with this focus were collected with no lower time limit and until May 2020 and were systematically reviewed according to the PRISMA guidelines. Following the initial search, 350 possible related articles were identified and transferred to the reference management software, EndNote. Of the 350 studies identified, 100 were duplicates, and therefore excluded. At the screening stage, out of the remaining 250 studies, 170 articles were removed after assessing their title and abstract and considering the inclusion and exclusion criteria. At the eligibility evaluation phase, out of the remaining 80 studies, 60 articles were removed after the examination of their full text, and similarly by considering the inclusion and exclusion criteria. At the quality evaluation stage, through the evaluation of the full text of the articles, and based on the score obtained from the STROBE checklist for each paper, out of the remaining 20 studies, 3 studies, that were assessed as low methodological quality works, were eliminated, and finally 17 cross-sectional studies reached the final analysis stage (please see Fig.  2 ). Details and characteristics of these articles are also provided in Table  1 .

figure 2

PRISMA (2009) flow diagram demonstrating the stages for sieving articles in this systematic review and meta-analysis

Investigating heterogeneity and publication Bias

To investigate the heterogeneity of the studies, the I 2 (%) indices for the prevalence of stress (I 2 : 96.8%), anxiety (I 2 : 99.3%) and depression (I 2 : 99.4%) were obtained. Due to the high heterogeneity in the studies, the random effects model was used in the analysis of findings. To examine publication bias in the collected articles, the Egger’s test indices were obtained for the prevalence of stress (p: 0.304) (Fig.  3 ), anxiety (p: 0.064) (Fig.  4 ), and depression (p: 0.073) (Fig.  5 ), indicating that publication bias was not significant for any of the three clinical symptoms.

figure 3

Funnel plot of results of prevalence of stress among the general population during the COVID-19 pandemic

figure 4

Funnel plot of results of prevalence of anxiety among the general population during the COVID-19 pandemic

figure 5

Funnel plot of results of prevalence of depression among the general population during the COVID-19 pandemic

  • Meta-analysis

The prevalence of stress in 5 of the studies with a sample size of 9074 was 29.6% (95% CI: 24.3–35.4). Results of the 5 studies are evaluated by the Depression, Anxiety and Stress Scale (DASS-21) instrument (Fig.  6 ). The prevalence of anxiety in 17 studies with a sample size of 63,439 was obtained as 31.9% (95% CI: 27.5–36.7) (Fig.  7 ). Moreover, the prevalence of depression in 14 studies with a sample size of 44,531 was 33.7% (95% CI: 27.5–40.6) (Fig.  8 ).

figure 6

The prevalence of stress in the studies based on the random effects model

figure 7

The prevalence of anxiety in the studies based on the random effects model

figure 8

The prevalence of depression in the studies based on the random effects model

Figures 3 , 4 and 5 present the Forest plots for the prevalence of stress, anxiety, and depression based on the random effects model, in which each black square is the prevalence rate, and the length of the line on which the square is located denotes 95% confidence interval. The black diamond shape represents the overall prevalence rate for the symptoms.

Subgroup analysis

Table  2 , reports the prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic in different continents. The highest prevalence of anxiety in Asia is 32.9 (95% CI: 28.2–37.9), the highest prevalence of stress in Europe is 31.9 (95% CI: 23.1–42.2), and the highest prevalence of depression in Asia is 35.3 (95% CI: 27.3–44.1) (Table 2 ).

This work is the first systematic review and meta-analysis on the prevalence of stress, anxiety and depression in the general population following the COVID-19 pandemic. This study has followed the appropriate methods of secondary data analysis for examining 17 related research works. The articles used in this study were all cross-sectional. According to our analysis, the prevalences of stress, anxiety, and depression, as a result of the pandemic in the general population, are 29.6, 31.9 and 33.7% respectively.

The emergence of COVID-19, with its rapid spread, has exacerbated anxiety in populations globally, leading to mental health disorders in individuals. This has even caused cases of stereotyping and discrimination [ 37 , 38 ]. Therefore, it is necessary to examine and recognize people’s mental states in this challenging, destructive and unprecedented time. Evidence suggests that individuals may experience symptoms of psychosis, anxiety, trauma, suicidal thoughts, and panic attacks [ 39 , 40 ]. Recent studies have similarly shown that COVID-19 affects mental health outcomes such as anxiety, depression, and post-traumatic stress symptoms [ 22 , 24 , 31 ]. COVID-19 is novel and unexplored, and its rapid transmission, its high mortality rate, and concerns about the future can be the causes of anxiety [ 41 ]. Anxiety, when above normal, weakens body’s immune system and consequently increases the risk of contracting the virus [ 39 ].

Research shows that people who follow COVID-19 news the most, experience more anxiety [ 39 ]. Most of the news published on COVID-19 are distressing, and sometimes news are associated with rumors, which is why anxiety levels rise when a person is constantly exposed to COVID-19 news [ 21 ]. Misinformation and fabricated reports about COVID-19 can exacerbate depressive symptoms in the general population [ 23 ]. The latest and most accurate information, such as the number of people who have improved and the progress of medications and vaccines, can reduce anxiety levels [ 42 ]. In this regard, mental health professionals recommend promoting healthy behaviors, avoiding exposure to negative news, and using alternative communication methods such as social networks and digital communication platforms to prevent social isolation [ 41 ].

Such conditions are even more significant for populations with poorer health conditions. In the under-developed and developing countriesthe epidemic conditions of COVID-19 impose greater psychological effects on the population, given that these countries are also affected by many other infectious diseases. Uncertainty about health status, follow-up of patients, treatment care, and inefficiency in these communities can also increase the vulnerability of such communities to the psychological effects of COVID-19 [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ].

The results of epidemiological studies show that women are at a higher risk of depression [ 43 ]. Women are more vulnerable to stress and post-traumatic stress disorder than men [ 44 ]. In recent studies, the prevalence of anxiety and depression and stress during COVID-19 pandemic is shown to be higher in women than in men [ 21 , 23 , 27 , 31 ].

Aging increases the risk of COVID-19 infection and mortality, however, the results of existing studies show that during the pandemic, the levels of anxiety, depression and stress are significantly higher in the age group of 21–40 years. The main reason for this seems to be that this age group are concerned over the future consequences and economic challenges caused by the pandemic, as they are key active working forces in a society and are, therefore, mostly affected by redundancies and business closures [ 21 , 22 , 25 ]. Some researchers have argued that a greater anxiety among young people may be due to their greater access to information through social media, which can also cause stress [ 45 ].

During the COVID-19 pandemic, people with higher levels of education had greater levels of anxiety, depression, and stress. According to recent studies, during the COVID-19 pandemic, there is an association between education levels, and anxiety and depression levels [ 21 , 31 ]. According to a study which was conducted in China, the higher prevalence of mental symptoms among people with higher levels of education is probably due to this group’s high self-awareness in relation to their own health [ 46 ]. In addition, anxiety levels are significantly higher in people with at least one family member, relative, or a friend with the COVID-19 disease [ 21 , 24 , 42 ].

Recent studies have revealed an association between medical history and increased anxiety and depression caused by the COVID-19 spread [ 36 ]. Previous research works had shown that medical history and chronic illnesses are associated with increased psychiatric distress levels [ 42 , 47 ]. People who have a history of medical problems and are also suffering from poor health may feel more vulnerable to a new disease [ 48 ].

Governments and health officials must provide accurate information on the state of the pandemic, refute rumors in a timely manner, and reduce the impact of misinformation on the general public’s emotional state. These high level activities result in a sense of public security and potential psychological benefits. Governments and health authorities need to ensure that infrastructure is provided to produce and supply adequate amounts of personal protective equipment (PPE), e.g. masks, hand sanitizers and other personal hygiene products during the COVID-19 pandemic. Optimistic and positive thoughts and attitude toward the COVID-19 spread are also protective factors against depression and anxiety [ 23 ]. The use of electronic devices and applications to provide counseling can reduce the psychological damages caused by COVID-19, and can consequently promote social stability [ 31 ]. The rise in the number of infections and mortalities are likely to affect the symptoms of depression and anxiety. During the H1N1 epidemic, anxiety reached the highest point at the peak of the epidemic and decreased with its decline [ 49 ].

Our research has a few limitations; All of the studies in our analysis were periodic, which could reflect the psychological state of the population over a period of time. However, psychological states change with the passage of time and with the alterations in one’s surrounding environment. Therefore, it is necessary to portray the psychological impacts of the COVID-19 catastrophe over a longer and more forward-looking period. Follow-up studies can be helpful in clarifying the mental state of the population in future. Although several research works in this meta-analysis have used the same tests for population screening, yet there were a few studies that followed different scales to assess stress, anxiety and depression.

In less than a few months, the COVID-19 pandemic has created an emergency state globally. This contagious virus has not only raised concerns over general public health, but has also caused a number of psychological and mental disorders. According to our analysis, it can be concluded that the COVID-19 pandemic can affect mental health in individuals and different communities. Therefore, in the current crisis, it is vital to identify individuals prone to psychological disorders from different groups and at different layers of populations, so that with appropriate psychological strategies, techniques and interventions, the general population mental health is preserved and improved.

Availability of data and materials

Datasets are available through the corresponding author upon reasonable request.

Abbreviations

Severe Acute Respiratory Syndrome

Middle East Respiratory Syndrome

Strengthening the Reporting of Observational studies in Epidemiology

Preferred Reporting Items for Systematic Reviews and Meta-Analysis

Bai Y, Yao L, Wei T, Tian F, Jin D-Y, Chen L, et al. Presumed asymptomatic carrier transmission of COVID-19. JAMA. 2020;323(14):1406–7.

CAS   PubMed Central   PubMed   Google Scholar  

Wang C, Horby PW, Hayden FG, Gao GF. A novel coronavirus outbreak of global health concern. Lancet. 2020;395(10223):470–3.

CAS   PubMed   PubMed Central   Google Scholar  

Feldmann H, Jones S, Klenk H-D, Schnittler H-J. Ebola virus: from discovery to vaccine. Nat Rev Immunol. 2003;3(8):677–85.

CAS   PubMed   Google Scholar  

Team N-O, Dawood F, Jain S, Finelli L, Shaw M, Lindstrom S, et al. Emergence of a novel swine-origin influenza a (H1N1) virus in humans. N Engl J Med. 2009;360(25):2605–15.

Google Scholar  

Ashour HM, Elkhatib WF, Rahman M, Elshabrawy HA. Insights into the recent 2019 novel coronavirus (SARS-CoV-2) in light of past human coronavirus outbreaks. Pathogens. 2020;9(3):186.

PubMed Central   Google Scholar  

Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395(10223):507–13.

Holshue ML, DeBolt C, Lindquist S, Lofy KH, Wiesman J, Bruce H, et al. First case of 2019 novel coronavirus in the United States. N Engl J Med. 2020;382:929–36.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Huang Y, Zhao N. Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 epidemic in China: a web-based cross-sectional survey. MedRxiv. 2020;288:112954.

CAS   Google Scholar  

Hall RC, Hall RC, Chapman MJ. The 1995 Kikwit Ebola outbreak: lessons hospitals and physicians can apply to future viral epidemics. Gen Hosp Psychiatry. 2008;30(5):446–52.

PubMed   PubMed Central   Google Scholar  

Xiang Y-T, Yang Y, Li W, Zhang L, Zhang Q, Cheung T, et al. Timely mental health care for the 2019 novel coronavirus outbreak is urgently needed. Lancet Psychiatry. 2020;7(3):228–9.

Zhang J, Lu H, Zeng H, Zhang S, Du Q, Jiang T, et al. The differential psychological distress of populations affected by the COVID-19 pandemic. Brain Behav Immun. 2020;87:49–50.

Brooks SK, Webster RK, Smith LE, Woodland L, Wessely S, Greenberg N, et al. The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet. 2020. 14;395(10227):912–20.

Wang Y, Xu B, Zhao G, Cao R, He X, Fu S. Is quarantine related to immediate negative psychological consequences during the 2009 H1N1 epidemic? Gen Hosp Psychiatry. 2011;33(1):75–7.

PubMed   Google Scholar  

Rubin GJ, Wessely S. The psychological effects of quarantining a city. BMJ. 2020;368:m313.

Neria Y, Sullivan GM. Understanding the mental health effects of indirect exposure to mass trauma through the media. JAMA. 2011;306(12):1374–5.

Shigemura J, Ursano RJ, Morganstein JC, Kurosawa M, Benedek DM. Public responses to the novel 2019 coronavirus (2019-nCoV) in Japan: mental health consequences and target populations. Psychiatry Clin Neurosci. 2020;74(4):281.

Bao Y, Sun Y, Meng S, Shi J, Lu L. 2019-nCoV epidemic: address mental health care to empower society. Lancet. 2020;395(10224):e37–e8.

Ryu S, Chun BC, Epidemiology of KS. An interim review of the epidemiological characteristics of 2019 novel coronavirus. Epidemiol Health. 2020;42:e2020006.

Chen Q, Liang M, Li Y, Guo J, Fei D, Wang L, et al. Mental health care for medical staff in China during the COVID-19 outbreak. Lancet Psychiatry. 2020;7(4):e15–e6.

Salari N, Mohammadi M, Vaisi-Raygani A, Abdi A, Shohaimi S, Khaledipaveh B, et al. The prevalence of severe depression in Iranian older adult: a meta-analysis and meta-regression. BMC Geriatr. 2020;20(1):39.

Moghanibashi-Mansourieh A. Assessing the anxiety level of Iranian general population during COVID-19 outbreak. Asian J Psychiatr. 2020;51:102076.

Ahmed MZ, Ahmed O, Aibao Z, Hanbin S, Siyu L, Ahmad A. Epidemic of COVID-19 in China and associated psychological problems. Asian J Psychiatr. 2020;51:102092.

Zhou S-J, Zhang L-G, Wang L-L, Guo Z-C, Wang J-Q, Chen J-C, et al. Prevalence and socio-demographic correlates of psychological health problems in Chinese adolescents during the outbreak of COVID-19. Eur Child Adolesc Psychiatry. 2020;29:1–10.

Cao W, Fang Z, Hou G, Han M, Xu X, Dong J, et al. The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Res. 2020;287:112934.

Huang Y, Zhao N. Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 outbreak in China: a web-based cross-sectional survey. Psychiatry Res. 2020;288:112954.

Ueda M, Stickley A, Sueki H, Matsubayashi T. Mental health status of the general population during the Covid-19 pandemic: a cross-sectional national survey in Japan. medRxiv. 2020;1:1–10.

Liu D, Ren Y, Yan F, Li Y, Xu X, Yu X, et al. Psychological impact and predisposing factors of the coronavirus disease 2019 (COVID-19) pandemic on general public in China. 2020.

Sigdel A, Bista A, Bhattarai N, Poon BC, Giri G, Marqusee H. Depression, Anxiety and Depression-anxiety comorbidity amid COVID-19 Pandemic: An online survey conducted during lockdown in Nepal. medRxiv. 2020;2:1–11.

Kazmi SSH, Hasan K, Talib S, Saxena S. COVID-19 and Lockdwon: A Study on the Impact on Mental Health. Available at SSRN 3577515. 2020.

Othman N. Depression, anxiety, and stress in the time of COVID-19 pandemic in Kurdistan region, Iraq. Kurdistan J Appl Res. 2020;5:37–44.

Wang Y, Di Y, Ye J, Wei W. Study on the public psychological states and its related factors during the outbreak of coronavirus disease 2019 (COVID-19) in some regions of China. Psychol Health Med. 2020;30:1–10.

Qian M, Wu Q, Wu P, Hou Z, Liang Y, Cowling BJ, et al. Psychological responses, behavioral changes and public perceptions during the early phase of the COVID-19 outbreak in China: a population based cross-sectional survey. medRxiv. 2020;22:30–7.

Shevlin M, Nolan E, Owczarek M, McBride O, Murphy J, Miller JG, et al. Covid-19-related anxiety predicts somatic symptoms in the U.K. Population. Br J Health Psychol. 2020:27. https://doi.org/10.1111/bjhp.12430 .

Odriozola-González P, Planchuelo-Gómez Á, Irurtia-Muñiz MJ, de Luis-García R. Psychological symptoms of the outbreak of the COVID-19 crisis and confinement in the population of Spain; 2020.

Agberotimi SF, Akinsola OS, Oguntayo R, Olaseni AO. Interactions between socioeconomic status and mental health outcomes in the nigerian context amid covid-19 pandemic: a comparative study; 2020.

Mazza C, Ricci E, Biondi S, Colasanti M, Ferracuti S, Napoli C, et al. A Nationwide survey of psychological distress among Italian people during the COVID-19 pandemic: immediate psychological responses and associated factors. Int J Environ Res Public Health. 2020;17(9):3165.

Lima CKT, de Medeiros Carvalho PM, Lima ID, de Oliveira Nunes JV, Saraiva JS, de Souza RI, et al. The emotional impact of coronavirus 2019-nCoV (new coronavirus disease). Psychiatry Res. 2020;287:112915.

Hahad O, Gilan D, Daiber A, Münzel T. Public Mental Health as One of the Key Factors in Dealing with COVID-19. Germany: Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes); 2020.

World Health O. Mental health and psychosocial considerations during the COVID-19 outbreak, 18 March 2020. Geneva: World Health Organization; 2020. Contract No.: WHO/2019-nCoV/MentalHealth/2020.1.

Taylor MR, Agho KE, Stevens GJ, Raphael B. Factors influencing psychological distress during a disease epidemic: data from Australia's first outbreak of equine influenza. BMC Public Health. 2008;8(1):347.

Banerjee D. The COVID-19 outbreak: crucial role the psychiatrists can play. Asian J Psychiatr. 2020;50:102014.

Wang C, Pan R, Wan X, Tan Y, Xu L, Ho CS, et al. Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. Int J Environ Res Public Health. 2020;17(5):1729.

Lim GY, Tam WW, Lu Y, Ho CS, Zhang MW, Ho RC. Prevalence of depression in the community from 30 countries between 1994 and 2014. Sci Rep. 2018;8(1):1–10.

Sareen J, Erickson J, Medved MI, Asmundson GJ, Enns MW, Stein M, et al. Risk factors for post-injury mental health problems. Depress Anxiety. 2013;30(4):321–7.

Cheng C, Jun H, Liang B. Psychological health diathesis assessment system: a nationwide survey of resilient trait scale for Chinese adults. Stud Psychol Behav. 2014;12:735–42.

Zhang Y, Ma ZF. Impact of the COVID-19 pandemic on mental health and quality of life among local residents in Liaoning Province, China: a cross-sectional study. Int J Environ Res Public Health. 2020;17(7):2381.

Holmes EA, O'Connor RC, Perry VH, Tracey I, Wessely S, Arseneault L, et al. Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science. Lancet Psychiatry. 2020;7:547–60.

Hatch R, Young D, Barber V, Griffiths J, Harrison DA, Watkinson P. Anxiety, depression and post traumatic stress disorder after critical illness: a UK-wide prospective cohort study. Crit Care. 2018;22(1):310.

Liao Q, Cowling BJ, Lam WW, Ng DM, Fielding R. Anxiety, worry and cognitive risk estimate in relation to protective behaviors during the 2009 influenza a/H1N1 pandemic in Hong Kong: ten cross-sectional surveys. BMC Infect Dis. 2014;14(1):169.

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Nader Salari

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Rostam Jalali, Aliakbar Vaisi-Raygani, Masoud Mohammadi & Shabnam Rasoulpoor

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NS and SHR contributed to the design, MM and RJ statistical analysis, participated in most of the study steps. SHR and AHF and AVR and BKH prepared the manuscript. All authors have read and approved the content of the manuscript.

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Salari, N., Hosseinian-Far, A., Jalali, R. et al. Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: a systematic review and meta-analysis. Global Health 16 , 57 (2020). https://doi.org/10.1186/s12992-020-00589-w

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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  

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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.

Coppen A. The biochemistry of affective disorders. Br J Psychiatry. 1967;113:1237–64.

Article   CAS   PubMed   Google Scholar  

American Psychiatric Association. What Is Psychiatry? 2021. https://www.psychiatry.org/patients-families/what-is-psychiatry-menu .

GlaxoSmithKline. Paxil XR. 2009. www.Paxilcr.com (site no longer available). Last accessed 27th Jan 2009.

Eli Lilly. Prozac - How it works. 2006. www.prozac.com/how_prozac/how_it_works.jsp?reqNavId=2.2 . (site no longer available). Last accessed 10th Feb 2006.

Healy D. Serotonin and depression. BMJ: Br Med J. 2015;350:h1771.

Article   Google Scholar  

Pies R. Psychiatry’s New Brain-Mind and the Legend of the “Chemical Imbalance.” 2011. https://www.psychiatrictimes.com/view/psychiatrys-new-brain-mind-and-legend-chemical-imbalance . Accessed March 2, 2021.

Geddes JR, Andreasen NC, Goodwin GM. New Oxford Textbook of Psychiatry. Oxford, UK: Oxford University Press; 2020.

Book   Google Scholar  

Sadock BJ, Sadock VA, Ruiz P. Kaplan & Sadock’s Comprehensive Textbook of Psychiatry. 10th Editi. Lippincott Williams & Wilkins (LWW); 2017.

Cowen PJ, Browning M. What has serotonin to do with depression? World Psychiatry. 2015;14:158–60.

Article   PubMed   PubMed Central   Google Scholar  

Harmer CJ, Duman RS, Cowen PJ. How do antidepressants work? New perspectives for refining future treatment approaches. Lancet Psychiatry. 2017;4:409–18.

Yohn CN, Gergues MM, Samuels BA. The role of 5-HT receptors in depression. Mol Brain. 2017;10:28.

Hahn A, Haeusler D, Kraus C, Höflich AS, Kranz GS, Baldinger P, et al. Attenuated serotonin transporter association between dorsal raphe and ventral striatum in major depression. Hum Brain Mapp. 2014;35:3857–66.

Amidfar M, Colic L, Kim MWAY-K. Biomarkers of major depression related to serotonin receptors. Curr Psychiatry Rev. 2018;14:239–44.

Article   CAS   Google Scholar  

Albert PR, Benkelfat C, Descarries L. The neurobiology of depression—revisiting the serotonin hypothesis. I. Cellular and molecular mechanisms. Philos Trans R Soc Lond B Biol Sci. 2012;367:2378–81.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Pilkington PD, Reavley NJ, Jorm AF. The Australian public’s beliefs about the causes of depression: associated factors and changes over 16 years. J Affect Disord. 2013;150:356–62.

Article   PubMed   Google Scholar  

Pescosolido BA, Martin JK, Long JS, Medina TR, Phelan JC, Link BG. A disease like any other? A decade of change in public reactions to schizophrenia, depression, and alcohol dependence. Am J Psychiatry. 2010;167:1321–30.

Read J, Renton J, Harrop C, Geekie J, Dowrick C. A survey of UK general practitioners about depression, antidepressants and withdrawal: implementing the 2019 Public Health England report. Therapeutic Advances in. Psychopharmacology. 2020;10:204512532095012.

Google Scholar  

Demasi M, Gøtzsche PC. Presentation of benefits and harms of antidepressants on websites: A cross-sectional study. Int J Risk Saf Med. 2020;31:53–65.

Jakobsen JC, Gluud C, Kirsch I. Should antidepressants be used for major depressive disorder? BMJ Evidence-Based. Medicine. 2020;25:130–130.

Moncrieff J, Cohen D. Do antidepressants cure or create abnormal brain states? PLoS Med. 2006;3:e240.

Kennis M, Gerritsen L, van Dalen M, Williams A, Cuijpers P, Bockting C. Prospective biomarkers of major depressive disorder: a systematic review and meta-analysis. Mol Psychiatry. 2020;25:321–38.

Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097.

Fusar-Poli P, Radua J. Ten simple rules for conducting umbrella reviews. Evid Based Ment Health. 2018;21:95–100.

Pollock M, Fernandes RM, Becker LA, Pieper D, Hartling L. Chapter V: Overviews of Reviews. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al., editors. Cochrane Handbook for Systematic Reviews of Interventions version 6.2,. version 6.Cochrane; 2021.

Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ. 2017;358:j4008.

Huang T, Balasubramanian R, Yao Y, Clish CB, Shadyab AH, Liu B, et al. Associations of depression status with plasma levels of candidate lipid and amino acid metabolites: a meta-analysis of individual data from three independent samples of US postmenopausal women. Mol Psychiatry. 2020;2020. https://doi.org/10.1038/s41380-020-00870-9 .

Culverhouse RC, Saccone NL, Horton AC, Ma Y, Anstey KJ, Banaschewski T, et al. Collaborative meta-analysis finds no evidence of a strong interaction between stress and 5-HTTLPR genotype contributing to the development of depression. Mol Psychiatry. 2018;23:133–42.

Little J, Higgins JPT, Ioannidis JPA, Moher D, Gagnon F, von Elm E, et al. STrengthening the REporting of Genetic Association Studies (STREGA)— An Extension of the STROBE Statement. PLoS Med. 2009;6:e1000022.

Guyatt GH, Oxman AD, Kunz R, Vist GE, Falck-Ytter Y, Schünemann HJ. What is quality of evidence and why is it important to clinicians? BMJ. 2008;336:995–8.

Yoon HS, Hattori K, Ogawa S, Sasayama D, Ota M, Teraishi T, et al. Relationships of cerebrospinal fluid monoamine metabolite levels with clinical variables in major depressive disorder. J Clin Psychiatry. 2017;78:e947–56.

Kugaya A, Seneca NM, Snyder PJ, Williams SA, Malison RT, Baldwin RM, et al. Changes in human in vivo serotonin and dopamine transporter availabilities during chronic antidepressant administration. Neuropsychopharmacology. 2003;28:413–20.

Border R, Johnson EC, Evans LM, Smolen A, Berley N, Sullivan PF, et al. No support for historical candidate gene or candidate gene-by-interaction hypotheses for major depression across multiple large samples. Am J Psychiatry. 2019;176:376–87.

Ogawa S, Tsuchimine S, Kunugi H. Cerebrospinal fluid monoamine metabolite concentrations in depressive disorder: A meta-analysis of historic evidence. J Psychiatr Res. 2018;105:137–46.

Nautiyal KM, Hen R. Serotonin receptors in depression: from A to B. F1000Res. 2017;6:123.

Rojas PS, Neira D, Muñoz M, Lavandero S, Fiedler JL. Serotonin (5‐HT) regulates neurite outgrowth through 5‐HT1A and 5‐HT7 receptors in cultured hippocampal neurons. J Neurosci Res. 2014;92:1000–9.

Kaufman J, DeLorenzo C, Choudhury S, Parsey RV. The 5-HT1A receptor in Major Depressive Disorder. Eur Neuropsychopharmacol. 2016;26:397–410.

Nikolaus S, Müller H-W, Hautzel H. Different patterns of 5-HT receptor and transporter dysfunction in neuropsychiatric disorders – a comparative analysis of in vivo imaging findings. Rev Neurosci. 2016;27:27–59.

Wang L, Zhou C, Zhu D, Wang X, Fang L, Zhong J, et al. Serotonin-1A receptor alterations in depression: A meta-analysis of molecular imaging studies. BMC Psychiatry. 2016;16:1–9.

Kambeitz JP, Howes OD. The serotonin transporter in depression: Meta-analysis of in vivo and post mortem findings and implications for understanding and treating depression. J Affect Disord. 2015;186:358–66.

Meyer JH. Imaging the serotonin transporter during major depressive disorder and antidepressant treatment. J Psychiatry Neurosci. 2007;32:86–102.

PubMed   PubMed Central   Google Scholar  

Mathews TA, Fedele DE, Coppelli FM, Avila AM, Murphy DL, Andrews AM. Gene dose-dependent alterations in extraneuronal serotonin but not dopamine in mice with reduced serotonin transporter expression. J Neurosci Methods. 2004;140:169–81.

Shen H-W, Hagino Y, Kobayashi H, Shinohara-Tanaka K, Ikeda K, Yamamoto H, et al. Regional differences in extracellular dopamine and serotonin assessed by in vivo microdialysis in mice lacking dopamine and/or serotonin transporters. Neuropsychopharmacology. 2004;29:1790–9.

Hagino Y, Takamatsu Y, Yamamoto H, Iwamura T, Murphy DL, Uhl GR, et al. Effects of MDMA on extracellular dopamine and serotonin levels in mice lacking dopamine and/or serotonin transporters. Curr Neuropharmacol. 2011;9:91–5.

Zhou Z, Zhen J, Karpowich NK, Law CJ, Reith MEA, Wang D-N. Antidepressant specificity of serotonin transporter suggested by three LeuT-SSRI structures. Nat Struct Mol Biol. 2009;16:652–7.

Gryglewski G, Lanzenberger R, Kranz GS, Cumming P. Meta-analysis of molecular imaging of serotonin transporters in major depression. J Cereb Blood Flow Metab. 2014;34:1096–103.

Benmansour S, Owens WA, Cecchi M, Morilak DA, Frazer A. Serotonin clearance in vivo is altered to a greater extent by antidepressant-induced downregulation of the serotonin transporter than by acute blockade of this transporter. J Neurosci. 2002;22:6766–72.

Benmansour S, Cecchi M, Morilak DA, Gerhardt GA, Javors MA, Gould GG, et al. Effects of chronic antidepressant treatments on serotonin transporter function, density, and mRNA level. J Neurosci. 1999;19:10494–501.

Horschitz S, Hummerich R, Schloss P. Down-regulation of the rat serotonin transporter upon exposure to a selective serotonin reuptake inhibitor. Neuroreport. 2001;12:2181–4.

Young SN. Acute tryptophan depletion in humans: a review of theoretical, practical and ethical aspects. J Psychiatry Neurosci. 2013;38:294–305.

Ruhe HG, Mason NS, Schene AH. Mood is indirectly related to serotonin, norepinephrine and dopamine levels in humans: a meta-analysis of monoamine depletion studies. Mol Psychiatry. 2007;12:331–59.

Fusar-Poli P, Allen P, McGuire P, Placentino A, Cortesi M, Perez J. Neuroimaging and electrophysiological studies of the effects of acute tryptophan depletion: A systematic review of the literature. Psychopharmacology. 2006;188:131–43.

Hogenelst K, Schoevers RA, Kema IP, Sweep FCGJ, aan het Rot M. Empathic accuracy and oxytocin after tryptophan depletion in adults at risk for depression. Psychopharmacology. 2016;233:111–20.

Weinstein JJ, Rogers BP, Taylor WD, Boyd BD, Cowan RL, Shelton KM, et al. Effects of acute tryptophan depletion on raphé functional connectivity in depression. Psychiatry Res. 2015;234:164–71.

Moreno FA, Erickson RP, Garriock HA, Gelernter J, Mintz J, Oas-Terpstra J, et al. Association study of genotype by depressive response during tryptophan depletion in subjects recovered from major depression. Mol. Neuropsychiatry. 2015;1:165–74.

Munafò MR. The serotonin transporter gene and depression. Depress Anxiety. 2012;29:915–7.

Caspi A, Sugden K, Moffitt TE, Taylor A, Craig IW, Harrington H, et al. Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science 2003;301:386–9.

Kiyohara C, Yoshimasu K. Association between major depressive disorder and a functional polymorphism of the 5-hydroxytryptamine (serotonin) transporter gene: A meta-analysis. Psychiatr Genet. 2010;20:49–58.

Oo KZ, Aung YK, Jenkins MA, Win AK. Associations of 5HTTLPR polymorphism with major depressive disorder and alcohol dependence: A systematic review and meta-analysis. Aust N. Z J Psychiatry. 2016;50:842–57.

Culverhouse RC, Bowes L, Breslau N, Nurnberger JI, Burmeister M, Fergusson DM, et al. Protocol for a collaborative meta-analysis of 5-HTTLPR, stress, and depression. BMC Psychiatry. 2013;13:1–12.

Karg K, Burmeister M, Shedden K, Sen S. The serotonin transporter promoter variant (5-HTTLPR), stress, and depression meta-analysis revisited. Arch Gen Psychiatry. 2011;68:444.

Sharpley CF, Palanisamy SKA, Glyde NS, Dillingham PW, Agnew LL. An update on the interaction between the serotonin transporter promoter variant (5-HTTLPR), stress and depression, plus an exploration of non-confirming findings. Behav Brain Res. 2014;273:89–105.

Bleys D, Luyten P, Soenens B, Claes S. Gene-environment interactions between stress and 5-HTTLPR in depression: A meta-analytic update. J Affect Disord. 2018;226:339–45.

Delgado PL. Monoamine depletion studies: implications for antidepressant discontinuation syndrome. J Clin Psychiatry. 2006;67:22–26.

CAS   PubMed   Google Scholar  

Kemp JJ, Lickel JJ, Deacon BJ. Effects of a chemical imbalance causal explanation on individuals’ perceptions of their depressive symptoms. Behav Res Ther. 2014;56:47–52.

Lebowitz MS, Ahn W-K, Nolen-Hoeksema S. Fixable or fate? Perceptions of the biology of depression. J Consult Clin Psychol. 2013;81:518.

Zimmermann M, Papa A. Causal explanations of depression and treatment credibility in adults with untreated depression: Examining attribution theory. Psychol Psychother. 2020;93:537–54.

Maund E, Dewar-Haggart R, Williams S, Bowers H, Geraghty AWA, Leydon G, et al. Barriers and facilitators to discontinuing antidepressant use: A systematic review and thematic synthesis. J Affect Disord. 2019;245:38–62.

Eveleigh R, Speckens A, van Weel C, Oude Voshaar R, Lucassen P. Patients’ attitudes to discontinuing not-indicated long-term antidepressant use: barriers and facilitators. Therapeutic Advances in. Psychopharmacology. 2019;9:204512531987234.

Harrell FE Jr. Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis. Springer, Cham; 2015.

Schafer JL, Kang J. Average causal effects from nonrandomized studies: a practical guide and simulated example. Psychol Methods. 2008;13:279–313.

Pech J, Forman J, Kessing LV, Knorr U. Poor evidence for putative abnormalities in cerebrospinal fluid neurotransmitters in patients with depression versus healthy non-psychiatric individuals: A systematic review and meta-analyses of 23 studies. J Affect Disord. 2018;240:6–16.

Fava GA. May antidepressant drugs worsen the conditions they are supposed to treat? The clinical foundations of the oppositional model of tolerance. Therapeutic Adv Psychopharmacol. 2020;10:2045125320970325.

Kitaichi Y, Inoue T, Nakagawa S, Boku S, Kakuta A, Izumi T, et al. Sertraline increases extracellular levels not only of serotonin, but also of dopamine in the nucleus accumbens and striatum of rats. Eur J Pharm. 2010;647:90–6.

Gartside SE, Umbers V, Hajós M, Sharp T. Interaction between a selective 5‐HT1Areceptor antagonist and an SSRI in vivo: effects on 5‐HT cell firing and extracellular 5‐HT. Br J Pharmacol. 1995;115:1064–70.

Bosker FJ, Tanke MAC, Jongsma ME, Cremers TIFH, Jagtman E, Pietersen CY, et al. Biochemical and behavioral effects of long-term citalopram administration and discontinuation in rats: role of serotonin synthesis. Neurochem Int. 2010;57:948–57.

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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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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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Research Article

Depression, anxiety and stress among high school students: A cross-sectional study in an urban municipality of Kathmandu, Nepal

Contributed equally to this work with: Anita Karki, Bipin Thapa

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Writing – original draft, Writing – review & editing

* E-mail: [email protected] (PB); [email protected] (AK)

Affiliation Central Department of Public Health, Institute of Medicine, Tribhuvan University, Kathmandu, Nepal

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Roles Data curation, Formal analysis, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing

Affiliation Department of Child, Adolescent Health and Maternal Care, School of Public Health, Capital Medical University, Beijing, China

Roles Writing – review & editing

Affiliation Department of Community Medicine, Maharajgunj Medical Campus, Institute of Medicine, Tribhuvan University, Kathmandu, Nepal

Roles Conceptualization, Methodology, Supervision, Writing – review & editing

  • Anita Karki, 
  • Bipin Thapa, 
  • Pranil Man Singh Pradhan, 

PLOS

  • Published: May 31, 2022
  • https://doi.org/10.1371/journal.pgph.0000516
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Table 1

Depression and anxiety are the most widely recognized mental issues affecting youths. It is extremely important to investigate the burden and associated risk factors of these common mental disorders to combat them. Therefore, this study was undertaken with the aim to estimate the prevalence and identify factors associated with depression, anxiety, and stress among high school students in an urban municipality of Kathmandu, Nepal. A cross-sectional study was conducted among 453 students of five randomly selected high schools in Tokha Municipality of Kathmandu. Previously validated Nepali version of depression, anxiety, and stress scale (DASS-21) was used to assess the level of symptoms of depression, anxiety and stress (DAS). Multivariable logistic regression was carried out to decide statistically significant variables of symptoms of DAS at p-value<0.05. The overall prevalence of DAS was found to be 56.5% (95% CI: 51.8%, 61.1%), 55.6% (95%CI: 50.9%, 60.2%) and 32.9% (95%CI: 28.6%, 37.4%) respectively. In the multivariable model, nuclear family type, students from science or humanities faculty, presence of perceived academic stress, and being electronically bullied were found to be significantly associated with depression. Female sex, having mother with no formal education, students from science or humanities faculty and presence of perceived academic stress were significantly associated with anxiety. Likewise, female sex, currently living without parents, and presence of perceived academic stress were significantly associated with stress. Prevention and control activities such as school-based counseling services focusing to reduce and manage academic stress and electronic bullying are recommended in considering the findings of this research.

Citation: Karki A, Thapa B, Pradhan PMS, Basel P (2022) Depression, anxiety and stress among high school students: A cross-sectional study in an urban municipality of Kathmandu, Nepal. PLOS Glob Public Health 2(5): e0000516. https://doi.org/10.1371/journal.pgph.0000516

Editor: Khameer Kidia, Brigham and Women’s Hospital, UNITED STATES

Received: February 22, 2022; Accepted: May 2, 2022; Published: May 31, 2022

Copyright: © 2022 Karki et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data that support the findings of descriptive analysis of this study are available in Figshare with the identifier given below: https://doi.org/10.6084/m9.figshare.19203512 The data that support the findings of inferential analysis of this study are available in Figshare with the identifier given below: https://doi.org/10.6084/m9.figshare.19203491 .

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Mental disorders contribute to a huge proportion of disease burden across all societies [ 1 ]. Among them, depression, anxiety and stress are the leading causes of illness and disability among adolescents [ 2 ]. The physical, psychological, and behavioral changes that occur throughout adolescence predispose them to a variety of mental health issues [ 3 ]. Despite this, mental health and mental disorders are largely ignored and not given the same importance as physical health [ 4 ].

The existing community-based studies conducted among high school students of various parts of Nepal have reported a wide range of prevalence of symptoms of depression and anxiety. The prevalence of depressive symptoms has been reported to range from 27% to 76% [ 5 – 7 ]. Likewise, the limited studies conducted in Nepal have estimated the proportion of symptoms of anxiety to range from 10% to 57% [ 7 – 9 ]. A nationwide survey conducted in Nepal revealed the prevalence of mental distress among adolescents (13-17years) to be 5.2% [ 10 ]. The Global School Health Survey which was a nationwide survey conducted in 2015 reported anxiety among 4.6% of the students [ 11 ].

Previous studies have revealed that sex [ 12 – 16 ], staying away from home [ 17 ], grade [ 12 , 14 , 16 ], stream of study [ 18 ], academic performance and examination related issues [ 7 , 19 ], cyber bullying [ 20 ] were linked with depression. Likewise, sex [ 8 , 21 ], grade of students and type of school i.e., public or private [ 8 ], family type [ 17 ], not living with parents, educational level of parents [ 21 ] and high educational stress [ 22 ] had been the determinants of anxiety as per previous studies.

High school education is an important turning point in the life of academic students in Nepal [ 23 ]. As the educational system becomes more specialized and tough in high school, the students become more likely to experience stress at this level. This might put them at risk of developing common mental disorders such as depression, anxiety and stress (DAS). However, there is a paucity of research studies that have assessed DAS among high school students in Nepal.

Exploring the magnitude and risk factors of symptoms of DAS are very crucial to combat the burden of adolescent mental health issues [ 24 ]. However, due to limited access to psychological and psychiatric services as well as the significant social stigma associated with mental health issues, anxiety and depression in early adolescence frequently go undiagnosed and untreated, particularly in developing countries such as Nepal. Therefore, this study aimed to estimate the prevalence and identify factors associated with the symptoms of DAS among high school students in an urban municipality of Kathmandu, Nepal.

Materials and methods

Study setting, design, and population.

This was a cross-sectional survey conducted in randomly selected high schools of Tokha Municipality, Kathmandu District in province no. 3 of Nepal. The data collection period was from 27 th August to 11 th September 2019. This municipality was formed on 7 December 2014 by merging five previous villages. It has an area of 16.2 sq.km. and comprises 11 wards [ 25 , 26 ]. The municipality is rich in cultural and ethnic diversity [ 25 ]. According to Nepal government records as of 2017, there were total 218,554 students in Tokha municipality in 82 schools. High school students were the study population for this study [ 26 ]. In Nepal, high school students comprise of grade 11 and grade 12 students. The high school differs from lower schooling level since the students have the opportunity to enroll in specialized areas such as science, management, humanities and education. High school are also popularly known as 10+2 [ 27 ].

Sample size calculation and sampling technique

Sample size was estimated using the formula for cross-sectional survey [ 28 ], n = Z 2 p(1-p)/ e 2 considering the following assumptions; proportion (p) = 0.24 [ 12 ], 95% confidence level, the margin of error of 5%. The estimated proportion used for sample size calculation was based on proportion of symptoms of anxiety i.e., 24%, as reported by a similar study conducted in Manipur, India [ 12 ].

After calculation, the minimum sample size required was 280. After adjusting for design effect of 1.5 to adjust variance from cluster design and assuming non-response rate of 10%, final sample of 467 was calculated. Two-stage cluster sampling was used. A list of all high schools of Tokha municipality was obtained from the education division of the municipality. Out of twelve high schools (8 private schools and 4 public schools), five schools were randomly selected. Within each selected high school further two sections each of grades 11 and 12 were randomly selected. A total of 20 sections were selected, 4 from each selected school, and all the students from the selected sections were included in the study.

Data collection tools

A structured questionnaire was prepared based on our study objectives which was divided into three sections. The first section included information about socio-demographic, familial and academic characteristics of the students. The second section included two item question to assess socializing among the students which was based on a previous study by Vankim and Nelson [ 29 ], two questions to assess bullying among the students based on 2019 Youth Risk Behavior Survey [ 30 ] and one item question to assess perceived academic stress. The third section consisted of Depression, Anxiety and Stress Scale (DASS-21) used to assess level of symptoms of depression, anxiety and stress among the students.

DASS-21 is a psychological screening instrument capable of differentiating symptoms of DAS. Depression, anxiety, and stress are three subscales and there are 7 items in each subscale. Each item is scored on a 4-point Likert scale which ranges from 0 i.e., did not apply to me at all to 3 i.e., applied to me very much. Scores for DAS were calculated by summing the scores for the relevant items. and multiplying by two [ 31 ]. A previously validated Nepali version of DASS-21 was obtained and used for data collection. Nepali version of the DASS-21 has demonstrated adequate internal consistency and validity. However, in the validation paper, the construct validity of the tool was evaluated against life satisfaction scale and not a systematic diagnostic tool [ 32 ]. Reliability for the symptoms of DAS was tested by Cronbach alpha. Cronbach alpha values for DAS were 0.74, 0.77, and 0.74 respectively.

Data collection procedure and technique

Data was collected after obtaining permission from the municipality’s education division as well as individual high schools. The questionnaire was in both English and Nepali language and had been pre-tested among 45 high school students of neighboring municipality. Self-administered anonymous questionnaires were distributed to students in their respective classrooms and requested for participation. An orientation session was conducted for the filling the questionnaire before distribution. Written informed consent was taken from all students prior to data collection whereas additional written parental consent was obtained from students below 18 years of age. One of the investigators herself collected the data from students. After data collection, a session on depression, anxiety, and stress along with the importance of discussing it with the guardians/ teachers and asking for help was conducted.

Study variables

The study variables are described in Table 1 .

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https://doi.org/10.1371/journal.pgph.0000516.t001

Data analysis

Compilation of data was done in EpiData 3.1 and then exported to IBM SPSS Statistics version 20 (IBM Corp., Armonk, NY) for cleaning and analysis. Descriptive analysis was performed. Frequency tables with percentages were generated for categorical variables, while mean and standard deviation (SD) were calculated for continuous variables.

Binary logistic regression was performed to identify associated factors of symptoms of DAS. Firstly, we performed univariate analysis in which each co-variate was modeled separately to determine the odds of DAS. Those variables with p-value <0.15 in univariate analysis were identified as candidate variables for multivariable logistic regression. In multivariable logistic regression, a p-value of < .05 was considered to be statistically significant and strength of association was measured using adjusted odds ratio (AOR) at 95% confidence interval.

Multicollinearity of variables was tested before entering them in the regression analysis. No problem of multicollinearity was seen among the variables (the highest observed VIF was 1.25,1.10 and 1.13 for symptoms of DAS respectively. The goodness of fit of the regression model was tested by the application of the Hosmer and Lemeshow test; the model was found to be a good fit (P >.05).

The regression model was explained by the equation:

Log [Y/ (1-Y)] = b 0 + b 1 X 1 + b 2 X 2 + b 3 X 3 … ..b n X n + e

Where Y is the expected probability for the outcome variable to occur, b 0 is the constant/intercept, b 1 through b n are the regression coefficients and the X 1 through X n are distinct independent variables and e is the error term.

Ethical approval and consent

The study protocol was approved by the Institutional Review Committee (IRC) of the Institute of Medicine, Tribhuvan University (Reference no. 23/ (6–11) 76/077). Approval to conduct this study was also obtained from the education division of Tokha Municipality (Ref: 076/077-23) and respective school authorities. A written informed consent (in the Nepali language) was obtained from the students before the data collection to assure their willingness to participate and no identifiers were listed in the questionnaire to make it anonymous and confidential. Parental consent was obtained for students who were under the age of 18. No incentives were provided.

Sociodemographic, academic and contextual characteristics of the students

The research questionnaire was distributed to a sample of 468 high school students, one of whom refused to participate in this study, with a response rate of 99.78%. Responses from 14 students were excluded due to incompleteness. This study presents the analysis on a total of 453 students.

The mean age of the students was 16.99 years (SD = ±1.12), ranging from 14 to 22 years. The proportion of female students (54.1%) was higher than male students (45.9%). Majority of the students were found to be currently living with their parents i.e., 65.8%. Around 70% of the students were from nuclear family. Regarding parent’s educational level, majority of the students responded that their father as well as mother had attained secondary level of education i.e., 31.6% and 33.3% respectively.

With regards to academic characteristics, more than two- third of students i.e., 69.5% were from private high schools while the remaining 30.5% were studying in a government or public high school. More than half i.e. (53.4%) of the students studied in grade eleven. About half of the students i.e., 50.6% were from management faculty. Only 3.8% students reported to have failed in the previous examination.

It was noted that about 60% of students perceived themselves to be stressed due to their studies. Most students were low socializing i.e., 60.9%. Around one-tenth students reported being bullied electronically in the past 12 months (10.2%). Similar proportion of students i.e., 10.4% also reported being bullied on school property in the past 12 months ( Table 2 ).

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https://doi.org/10.1371/journal.pgph.0000516.t002

Level of symptoms of DAS among the students

The prevalence of symptoms of DAS was found to be 56.5% (51.8%, 61.1%), 55.6% (50.9%, 60.2%) and 32.9% (28.6%, 37.4%) respectively. About a quarter of students showed moderate level of symptoms of depression and anxiety i.e., 25.8% and 24.5% respectively. On the other hand, symptoms of mild stress were most prevalent among the students. i.e., 14.8% ( Table 3 ).

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https://doi.org/10.1371/journal.pgph.0000516.t003

Factors associated with symptoms of depression

The results from multivariable logistic regression analyses for correlates of symptoms of depression are shown in Table 4 . The variables that remain in the final model were age, type of family, father’s education, mother’s education, type of school, grade, faculty, perceived academic stress, and bullied electronically as these variables had p-value less than 0.15 in the univariate model. In the final model, nuclear family type (AOR: 1.64, 95% CI: 1.06–2.52), students from science/humanities faculty (AOR: 1.58, 95% CI: 1.05–2.40), presence of perceived academic stress (AOR: 1.62, 95% CI: 1.08–2.44) and bullied electronically in past 12 months (AOR: 2.84, 95% CI: 1.34–5.99) were significantly associated with symptoms of depression.

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https://doi.org/10.1371/journal.pgph.0000516.t004

Factors associated with symptoms of anxiety

The results from multivariable logistic regression analyses for correlates of symptoms of anxiety are shown in Table 5 . The variables that remained in the final model were age, sex, mother’s education, stream/ faculty, perceived academic stress, bullied electronically, and bullied on school property (p<0.15). Female sex (AOR: 1.82, 95% CI: 1.23–2.71), no formal education attained by the mother (AOR: 1.63, 95% CI: 1.08–2.47), students from science or humanities faculties (AOR: 1.50, 95% CI: 1.01–2.21), and presence of perceived academic stress (AOR: 1.93, 95% CI: 1.30–2.87), and were significantly associated with symptoms of anxiety.

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https://doi.org/10.1371/journal.pgph.0000516.t005

Factors associated with symptoms of stress

The results from multivariable logistic regression analyses for main correlates of symptoms of stress are shown in Table 6 . The variables that remained in the final model were sex, current living status, grade, stream / faculty, perceived academic stress, bullied electronically and bullied on school property. In the final model, female sex (AOR: 1.54, 95% CI: 1.01–2.34), currently living without parents, (AOR: 1.70, 95% CI: 1.11–2.61), and presence of perceived academic stress (AOR: 2.11, 95% CI: 1.36–3.26) were significantly associated with stress symptoms.

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https://doi.org/10.1371/journal.pgph.0000516.t006

In our study, the prevalence of depressive symptoms among high school students was found to be 56.5%. The existing community-based studies conducted among high school students of various parts of Nepal have reported a wide range of prevalence of depressive symptoms. A study by Gautam et al. reported that more than one quarter i.e., 27% of high school students in a rural setting of Nepal showed depressive symptoms [ 6 ]. Similarly, in a study conducted by Bhattarai et. al. in four schools of a metropolitan city in Nepal, it was found that more than 2/5 th i.e., 44.2% students exhibited depressive symptoms [ 5 ]. Similar proportion of depressive symptoms i.e., 41.6% was also reported by Sharma et. al in a study conducted among adolescent students of public schools of Kathmandu [ 9 ]. The prevalence estimated by these studies are lower than the findings of our study [ 5 , 6 , 9 ]. On contrary, a single high school study by Bhandari et al reported depressive symptoms among 76% students [ 7 ]. In our study, the proportion of students showing symptoms of anxiety were 55.6%. A study by Sharma et al. revealed that more than half i.e. 56.9% of public high school students showed symptoms of anxiety [ 9 ]. Another study by Bhandari et. al, also found out that nearly one out of two students i.e., 46.5% suffered from anxiety [ 8 ].These findings are in line with the findings of our study. On contrary, a study by Bhandari reported that only 10% students had mild anxiety [ 7 ]. In our study, the prevalence of stress symptoms among students was 32.9%. A study by Sharma et. al reported that more than 1/4 th students i.e., 27.5% showed symptoms of stress which corroborates with the findings of our study.

While the prevalence of symptoms of DAS reported by our study corroborates with the existing literatures in Nepal, it is exceptionally high. One possible explanation for this could be that the data was collected at the beginning of academic session. The students in the eleventh grade were undergoing sudden transition from secondary school life to high school life with regards to new friends, teachers, school environment, and change in daily schedules whereas the students in 12 th grade were awaiting results of previous board exam. This anticipation and the tremendous pressure faced by 12 th grade students for tertiary education might have contributed to the high prevalence of symptoms of DAS among 12 th grade students whereas the higher prevalence of symptoms of DAS among 11 th grade students could be possibly explained by the inability to cope with the adjustment of sudden transition from secondary to high school life. Moreover, the wide range in prevalence of DAS symptoms among these community-based studies could be attributed to the difference in the setting (rural or urban) and difference in methodology used.

Among South Asian countries, the prevalence of depression reported by our study is in line with the studies conducted in India, and Bangladesh, but slightly higher than one conducted in China and [ 13 , 17 , 33 , 34 ]. On contrary, our study has shown higher prevalence of anxiety among students as compared to study conducted in India, Sri Lanka, Vietnam and China [ 12 , 19 , 22 , 34 ].The prevalence of symptoms of stress in this study is comparable to the study from Chandigarh but higher than similar study from Manipur, India [ 12 , 17 ]. Hence, it can be suggested that there is a huge burden of DAS among high school students in South Asia. In context of Nepal, there is no standalone mental health policy. Further, there is inadequate funding allocated for mental health services along with shortage of qualified mental health professionals. In addition, there is much stigma that surrounds mental illness which acts as a barrier to seek and utilize mental health care services [ 35 ]. Due to these reasons, mental health illnesses are likely to remain untreated and continue to persist in the society. This may explain the high prevalence of DAS in our setting.

Socio-demographic characteristics and association with symptoms of DAS (depression, anxiety and stress)

In current study, it was found that females were more likely to suffer from symptoms of anxiety and stress than their male counterparts. This finding corroborates with the findings from previous studies [ 19 , 21 , 36 – 39 ]. On the contrary, a study conducted in Dang, Nepal reported that males were 1.5 times more likely to become anxious [ 8 ].One possible explanation for this is adolescent stage in girls is marked by hormonal changes as a result of various reproductive events which may have a role in the etiology of anxiety disorders [ 40 ]. Furthermore, when compared to boys, girls are more likely to be subjected to stressful situations such as sexual and domestic violence, which may make them more prone to anxiety and stress problems [ 41 ].

This study revealed that the students who live in nuclear families were more likely to exhibit depressive symptoms compared to students from joint or extended families. There are more members in a joint family system, which may provide better opportunities for adolescents to share their emotions and issues, hence providing a strong support system that may serve as a protective factor against depression which may be lacking in nuclear families [ 42 ]. Moreover, this study also found out that risks of stress symptoms was higher among students who were staying far from their parents. A similar finding was reported by Arif et al., 2019 in Uttar Pradesh, India [ 43 ]. One of the possible explanations might be that students who live without their parents may spend a substantial amount of time alone after school, which does not encourage familial intimacy [ 44 ]. As a result, they may feel alone and disconnected from their parents [ 45 ]. These adolescents may miss out on the opportunity to internalize the support they would otherwise get, leading to increased stress.

In our study, the students who reported no formal mother’s education were at greater risk of showing symptoms of anxiety. This was in accordance with other similar studies [ 38 , 46 ]. The attachment theory provides a robust foundation for understanding how parental behavior affects a child’s ability to recognize and manage stressful events throughout their lives [ 47 ]. The theory supports that the educated mother plays a stronger parenting role in the development of emotional skills and mental health outcomes in teenagers which might be protective for anxiety.

Academic characteristics and association with symptoms of DAS

In our study, the students from science or humanities faculties were more likely to have depression and anxiety as compared to management students. This was in line with other studies which showed higher proportion of depressive symptoms among science students. [ 48 ]. Generally, science students have to compete more, study longer hours and have a higher level of curriculum difficulty than management students which explains the finding. Likewise, it is believed that the humanities students have a poorer past academic performance in the secondary school, and may have chosen this stream / faculty as a secondary choice [ 49 ]. This combined with the uncertainty regarding future work prospects among humanities students may likely explain the higher prevalence of depression among humanities students.

In our study, the students who reported to be stressed due to their studies were more likely to suffer from symptoms of DAS. Several studies have documented similar findings [ 7 , 22 ]. A possible explanation might be that high school is an important stage in an individual’s academic life. However, the inability to meet the expectation of parents, teachers, and oneself in terms of academic performance can lead to overburden of stress [ 50 ]. This persistent academic related stress might accelerate the development of mood disorders such as depression, anxiety and stress among the adolescents [ 51 ].

Contextual factors and association with symptoms of DAS

In our study, the risk of depressive symptoms was higher among those students who were bullied via electronic means. Literature suggests that higher the level of cyberbullying/electronic bullying leads to higher the level of depressive symptoms among adolescents [ 52 ]. A similar study by Perren et. al demonstrated that depression was significantly associated with cyberbullying even after controlling for traditional forms of bullying [ 20 ]. The victims of cyberbullying may experience anonymous verbal or visual threats via electronic means. These repeated incidents can cause the victims to feel powerless which exacerbates the feeling of fear. This can cause significant emotional distress among victims and contribute to development of depressive symptoms [ 53 ].

Even though widely utilized in both clinical as well as research setting, DASS scales are screening tools for symptoms of depression, anxiety, and stress. Hence, they cannot be used as a modality for diagnosis. This limitation should be considered when interpreting the findings of this study. Due to its cross-sectional design, this study was unable to establish causal relationship of depression, anxiety, and stress with associated factors. Since the study tools used in this study investigate the habits and activities of the high school students in the past, recall and reporting bias are likely; however, the effect due to potential confounders have been controlled. As Nepal is a culturally diverse country, the findings of only one municipality may not be generalized to the whole country. Therefore, future studies covering a larger population of high school students employing more robust study designs such as interventional studies are recommended to get the real scenario of common mental disorders.

In conclusion, more than half of the students had depression and anxiety symptoms and nearly one third of the students had stress symptoms. Nuclear family type, students from humanities/science faculty, presence of perceived academic stress, and being bullied electronically were found to be significantly associated with symptoms of depression. Female sex, no formal mother education, students from humanities/science faculty, and presence of perceived academic stress were significantly associated with symptoms of anxiety. Likewise, symptoms of stress were significantly associated with female sex, currently living without parents, and presence of perceived academic stress.

Therefore, prevention and control activities such as school-based counseling services focusing to reduce and manage academic stress and electronic bullying faced by the students are recommended considering findings of this research.

Supporting information

S1 file. questionnaire form used in data collection..

https://doi.org/10.1371/journal.pgph.0000516.s001

Acknowledgments

We are grateful to Tokha municipality for granting permission to conduct the study. Special thank goes to the school management and teachers for their co-ordination during data collection. Lastly, we would like to thank all the study participants for their co-operation and support during the study.

  • View Article
  • PubMed/NCBI
  • Google Scholar
  • 2. Adolescent mental health. [cited 27 Jul 2021]. Available: https://www.who.int/news-room/fact-sheets/detail/adolescent-mental-health
  • 3. World Health Organization. Regional Office for South-East Asia. Mental health status of adolescents in South-East Asia: evidence for action. New Delhi: World Health Organization. Regional Office for South-East Asia; 2017. Available: https://apps.who.int/iris/handle/10665/254982%0A
  • 9. Sharma P, Choulagai B. Stress, anxiety, and depression among adolescent students of public schools in Kathmandu. [cited 19 Mar 2022]. Available: www.jiom.com.np
  • 10. Nepal Health Research Council. National Mental Health Survey, Nepal-2020. In: Nepal Health Research Council [Internet]. 2020 pp. 1–4. Available: http://nhrc.gov.np/projects/nepal-mental-health-survey-2017-2018/
  • 25. Brief Introduction | Tokha Municipality, Office Of the Municipal Executive. [cited 25 Jul 2021]. Available: https://www.tokhamun.gov.np/en/node/4
  • 26. Tokha Municipality Profile | Facts & Statistics–Nepal Archives. [cited 25 Jul 2021]. Available: https://www.nepalarchives.com/content/tokha-municipality-kathmandu-profile/
  • 27. Nepal—Secondary Education—Level, Schools, Technical, and Training—StateUniversity.com. [cited 22 Mar 2022]. Available: https://education.stateuniversity.com/pages/1058/Nepal-SECONDARY-EDUCATION.html
  • 30. 2019 State and Local Youth Risk Behavior Survey. 2019; 7. Available: https://www.cdc.gov/healthyyouth/data/yrbs/pdf/2019/2019_YRBS-Standard-HS-Questionnaire.pdf
  • 35. World Health Organization (WHO). Nepal WHO Special Initiative for Mental Health Situational Assessment CONTEXT.

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  • PMC9377379.1 ; 2021 Dec 1
  • ➤ PMC9377379.2; 2022 May 3

Research in child and adolescent anxiety and depression: treatment uncertainties prioritised by youth and professionals

Brynhildur axelsdóttir.

1 Regional Centre for Child and Adolescent Mental Health, Eastern and Southern Norway, Oslo, 0484, Norway

Lise Mette Eidet

Ragnhild thoner, sølvi biedilæ, ingrid borren, mari elvsåshagen, kristine horseng ludvigsen, astrid dahlgren, associated data, underlying data.

Harvard Dataverse: Priorities for research in child and adolescent anxiety and depression: a priority setting partnership with youth and professionals https://doi.org/10.7910/DVN/UQPYVT . 28

This project contains the following underlying data:

  • • Coding_priorities from participants_Clinicians_final_25.09.2019.tab
  • • Coding_Priorities_Adolescents_Final_07.11.2019.tab

Extended data

This project contains the following extended data:

  • • Tables 3-6 (in Norwegian, pdf.)
  • • Appendix I (Copy of survey no.1, no.2. and no.3.)
  • • IN SUM Search strategies_2021.pdf

Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver ( CC0 1.0 Public domain dedication ).

Version Changes

Revised. amendments from version 1.

We wish to thank the reviewers for valuable comments on the manuscript. The main differences compared with the previous version are: We have changed the title of the paper due to discrepancies in our approaches and of the James Lind Alliances. We have also tried to highlight the differences between the two approaches in methods and discussion and have revised the manuscript to make this clearer. We have rephrased the objectives to make it clearer. We have given a definition on key concepts such as treatment, outcomes, research uncertainties and research priorities, in the introduction, for clarification.

Peer Review Summary

Background: A starting point for evaluating the effectiveness of treatments should be to identify evidence gaps. Furthermore, such evaluations should consider the perspectives of patients, clinicians and carers to ensure relevance and potentially influence future research initiatives.

Methods: Our approach, inspired by the James Lind Alliance methods, involved three steps. First, we performed a document analysis by identifying interventions and outcomes in two recently published overviews of systematic reviews, which summarised the effects of interventions for anxiety and depression in children and adolescents. Second, we surveyed children and adolescents with personal experiences of depression or anxiety as well as clinicians, and asked them to suggest treatments and outcomes associated with uncertainty. Finally, we facilitated a consensus process where clinicians and youth mental health patient representatives were invited to prioritise research uncertainties in separate consensus processes.

Results: The survey included 674 respondents who reported a total of 1267 uncertainties. Independent coding by four investigators revealed 134 suggestions for treatments of anxiety, 90 suggestions for treatments of depression, 84 for outcomes of interventions for anxiety and 71 suggestions for outcomes of interventions for depression. Two separate priority setting workshops with eight clinicians and ten youth resulted in four independent top ten priority lists.

Conclusion: Top ten lists of treatments and outcome domains of anxiety and depression in children and adolescents was identified by youth and clinicians. The results may influence the research agenda, and ultimately benefit patients.

Introduction

Anxiety and depression are common mental disorders in adolescence. Anxiety is characterised by restlessness or nervousness, poor concentration, and irritability. Depression is characterised by persistent low mood, loss of interest and enjoyment. 1

The prevalence of anxiety and depression increases during adolescence, and the comorbidity between these diagnoses is high among young people. 2 Almost 10% of adolescents will meet the criteria of an anxiety disorder. 3 The one-year prevalence rate of adolescent depression is estimated to be 5.6%. 4 In Norway, the prevalence of diagnosed depression in girls 15-17 years has increased from 1.5% to 2.3% from 2010-2013. 5

Both anxiety and depression in adolescence are associated with functional impairment and can affect academic achievement, which may have a lifelong effect on employment. 6 , 7 According to the WHO’s Global Burden of Disease, the leading cause of years lost due to disability (YLDs) for both genders 10-24 years is unipolar depressive disorders. 8 The serious consequences of anxiety and depression in adolescence highlights the need for efficient interventions, and the importance of including perspectives of their own experiences.

Currently, recommended treatments for anxiety and depression are psychological therapy, pharmacotherapy, or a combination of both. 9 – 11 By “treatment” we refer to any action or intervention used to change an aspect of a young person’s mental health, that being medicines or school-based interventions. Such treatments may also have an impact on other aspects of the young person’s life that may be important to consider in research. There are also many other treatments used for both anxiety and depression. Some based on well-founded scientific research while others can be regarded as treatment uncertainties, as there is uncertainty about the effectiveness of the treatment. Such uncertainties are either consequences of a lack of research, or that the research is not adequately performed and therefore the evidence is weak. 12 A starting point for new research on treatments should be to identify treatment uncertainties (evidence gaps), in order to shape future research priorities. 13 , 14

Evidence gaps can be prioritised through user involvement. 20 The purpose of user involvement in research is to ensure that research becomes as relevant to the population in question as possible. When initiating research on treatment effects, it has not always been common practice to obtain the perspectives of patients, clinicians or carers. 15 , 16 Thus, important research questions remain unanswered, and research funding may not be used where most needed. 17 A recent systematic review, based on 83 studies involving 15,722 participants, demonstrated how uncommon it is to involve children and their caregivers in setting research priorities in the field of childhood chronic disease. 16

A recent publication by Chevance et al ., 18 published in 2020, described a similar process with adult participants in an international survey, identifying outcomes for depression that matter to patients, informal caregivers, and health-care professionals. Another process of developing an Overall Paediatric Health Standard Set [OPH-SS] of outcome measures which matters to young people and their families, internationally, was also published in 2020. 19 The current study complements both papers, as this paper looks at both children and adolescents, as well as desired research priorities in terms of treatments, as well as outcomes.

We recently produced two overviews of systematic reviews on the effects of interventions for anxiety and depression in children and young people, respectively. 10 , 11 This left us with a momentum for inviting young representatives from these populations (youth) and those providing mental health services to identify and prioritise research uncertainties associated with these conditions.

The objective of this study was to a) to obtain suggestions from youth and clinicians of treatments and treatment outcomes not identified in our overviews of systematic reviews on depression and anxiety. b) to have the two groups prioritise the ten most favoured suggestions and subsequently vote on their ranking in preferred order of importance.

REK, Regional Committees for Medical and Health Research Ethics, Norway was contacted for approval of the project. They concluded that the project did not require their approval as there was no registered personal data. All information was collected through Nettskjema (a web-based survey system), ascertaining a high level of data security and safety.

All respondents were given information about the purpose of the study and how the results would be managed and presented and were informed that by responding to the survey, they consented to participation in the study. The questionnaire was anonymous and once submitted, the information could not be traced back to the respondent.

In the current study, we included both qualitative and quantitative methods in three stages:

  • 1. Document analysis : identification of interventions and outcome measures used for treating children and adolescents with anxiety and depression in two previously published overviews of systematic reviews. 10 , 11
  • 2. Mapping study (surveys) : we encouraged identification by clinicians and patient representatives (children and adolescents who have, or have had, anxiety or depression) of additional priorities outside of those previously identified.
  • 3. Consensus process : prioritisation of research uncertainties by clinicians and patient representatives.

Our approach was partly inspired by a method developed by the JLA. 20 The method involves patients and clinicians in suggesting research priorities. The method is designed to raise awareness of important evidence gaps, with the potential of influencing new research initiatives. 15

The stages of the prioritisation process are outlined in Figure 1 .

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Document analysis: identification of interventions and outcomes in existing research

In two recently published overviews of systematic reviews, we have summarised the effects of interventions for anxiety and depression in children and adolescents. 10 , 11 Although these publications are in Norwegian, the methodology of the review process have been published in registered protocols and is available in English through the PROSPERO database; CRD42020159883 (depression) and CRD42020159884 (anxiety). To provide context to this paper, we briefly describe the inclusion criteria and search strategy of the reviews here. Both overviews adhered to the PRISMA guidelines 21 and to the following inclusion criteria:

Publications: Systematic reviews published 2012 and later, fulfilling the DARE-criteria .

Language: English, Norwegian, Danish, or Swedish.

Participants: Children and adolescents under the age of 18, with or without an identified risk of developing mental health problems or those who have already developed these problems.

Intervention: Any intervention aimed at preventing or reducing mental health problems or welfare interventions, including psychological therapy, pharmaceutical interventions, psychosocial interventions etc.

Comparison: Other relevant interventions, treatment as usual (TAU), no treatment or wait list.

Outcomes: All outcomes of mental health problems and child welfare evaluated in children and adolescents, including other health outcomes, quality of life, function, use of health care, attitudes and adverse effects of interventions.

The search for reviews that were included in these two overviews was largely based on the IN SUM database and was performed in April 2018, with an updated search in December 2018. IN SUM is a recently developed database of systematic reviews of the effects of interventions relevant to children and young people’s mental health and welfare. The database indexes systematic reviews from the following databases: Cochrane Database of Systematic Reviews, Campbell Library, PsycINFO, Medline, Embase, Web of Science, Database of Abstracts of Reviews of Effects (DARE) and Evidence-Based Mental Health. IN SUM is continuously updated monthly with the latest systematic reviews. In addition to IN SUM, we hand searched the websites of the Norwegian Institute of Public Health, the Swedish Agency for Health Technology Assessment and Assessment of Social Services, the Danish Health Authority for Systematic Reviews and the National Institute for Health and Care Excellence for evidence-based guidelines, UK. For complete search strategies see Extended data. 28

The first author (BA) extracted all interventions and outcomes reported in these two overviews in a simple document analysis and second author (AD) double-checked the extraction.

Mapping study (survey): identification of uncertainties in research

We created three surveys, each including four questions asking the respondents to report what treatments and outcomes ought to be topics for research, in their opinion. For each question, the recipients were presented with a list of the treatments and the outcomes already addressed in existing research (see Table 1 , Table 2 ), based on the two overviews of reviews. 10 , 11 The three surveys were distributed to clinicians and users as an electronic questionnaire via Nettskjema.

The survey questions had an open answer option (see Extended data 28 ). Respondents can be unfamiliar with research, and we therefore considered it more appropriate to let respondents formulate their need for research in their own words. 20 The purpose of the surveys was to collect suggestions for research uncertainties, consequently, the sample did not need to be representative. 20 Instead, we used convenience sampling to recruit the participants. Anyone living in Norway with experience and understanding of living with anxiety or depression was eligible to participate in the identification of uncertainties. This included children and adolescents with anxiety and/or depression, carers, family members and friends. Also, healthcare, and social care professionals who had worked with children and adolescents living with the conditions were eligible. We strived to ensure that professionals working in different levels in health and welfare services were represented, as well as users. No demographic data were collected as it is not a part of later analysis in priority setting partnerships. In contrast to the principles of JLA the priority lists in the current paper were not rewritten or rephrased as questions. Instead, the lists consist of keywords of outcomes and treatments. The background for this decision was related to the scope of the project; to have the participants choose among suggestions of treatments and treatment outcomes identified as evidence gaps. Our narrow scope did not require full phrased questions.

The first survey was sent on 22 nd February 2019, to our institution's contacts working with children and young people's mental health in the municipalities (Eastern and Southern Norway), including employees in child welfare institutions/orphanages, special education teachers working in schools, child welfare services, child welfare guards, family protection offices, refugee and immigration departments.

The second survey was distributed on 19 th March 2019, to professionals working in the specialist mental health service for children and adolescents. These were also contacted through our networks. In addition, we recruited respondents in collaboration with the Norwegian Association for Children and Young People’s Mental Health (NBUP) and from our institution’s newsletter.

The third survey was distributed on 25 th April 2019, to children and adolescents having personal experiences with depression and/or anxiety, as well as to their carers, in collaboration with the Norwegian organisation for youth mental health, Mental Helse Ungdom (MHU). We also sought to recruit respondents through social media platforms of our institution, e.g., Facebook and Instagram. We posted a link of the survey on the platforms 2 nd August 2019, with an invite to eligible participants to complete the survey.

Content analysis

The interventions and outcomes suggested by the respondents were coded independently by at least two investigators (IB, SB, LME and BA). This part of the process is both interpretative and subjective. Duplicates and similar submissions were combined to a common suggestion. Combining submissions can greatly reduce the volume of data in the process of finalising a top ten list. 20 Based on this analysis we created four “master-lists” including all suggestions for:

  • 1) interventions for anxiety
  • 2) interventions for depression
  • 3) outcomes of interventions for anxiety
  • 4) outcomes of interventions for depression

Consensus process: prioritisation of research uncertainties

Preparations for the consensus process

The next step was to prepare for the consensus process, where selected professionals and users were asked to prioritise the suggested research uncertainties. There is no gold standard for conducting a consensus process. However, group composition can have an impact and may lead to different judgements. 22

A multi-disciplinary team of professionals were recruited through our networks through convenience sampling. We received help recruiting clinicians from a local child and adolescent psychiatric outpatient clinic. Our contact person there, reached out via e-mail on 21 st August 2019, to clinicians with a request to participate in the consensus process. The criteria were clinicians who work, or have worked, with children and adolescents with anxiety or depression. A variety of professionals from different backgrounds and working at different levels of health and welfare services (such as psychologists, psychiatrists, physiotherapists, nurses, educators, and health nurses) came forward. Seven clinicians from the specialist mental health services and four from the municipal health services accepted the invitation to participate. For recruitment of user representatives, we contacted the Assistant General Secretary of MHU. She reached out via e-mail on 15 th September 2019, to their members of staff and youth with experience of the conditions, and twelve participants accepted the invitation.

Once recruited, we received contact information of 10 participants proposed by the assistant general secretary of the organisation on October 10 th ,2019. We emailed the four lists with the suggested interventions and outcomes for anxiety and depression, respectively to the participants. They were individually asked to put the suggestions in ranked order, by selecting only 10 options that were assigned 1 point each. For the three most important options we asked them to assign these 2 points. This resulted in the first drafts of prioritised lists of interventions, and outcomes of interventions, for anxiety and depression.

The results from this pre-prioritisation were summarised by two members of the research team (AD and BA), and four lists were created with the highest-ranking suggestions. The two overviews of systematic reviews documented which treatments and outcomes that lacked or had weak scientific evidence. 10 , 11 The participants of the workshops were made aware of this before conducting the interim prioritisation, also enabling them to prioritise among those.

The workshops

For practical reasons, it was not possible to host a shared workshop for professionals and users. Instead, separate workshops were held.

When conducting consensus processes, the criteria for establishing priorities should be applied using a systematic and transparent process. 22 Furthermore, group discussions should follow some basic rules that the participants have chosen jointly. Participants should listen to each other and show respect for each other’s ideas. 20

We applied the Nominal Group Technique for both workshops. This approach is characterised as a structured method for group brainstorming, encouraging discussion and facilitating agreement on the relative importance of issues in question. The process should be led by someone who is not part of the project group, who has no research background. The person will, therefore, have a more neutral role in the process. It is essential that the entire process has openness and justice as guiding principles. 20 For this study, we invited an experienced expert in consensus processes to facilitate and host the workshops (RT), the rest of the team played the part of silent observers and handled all practical needs (LME, SB, AD, and BA).

The first workshop was held at our organisation’s location in Oslo, Norway on 26 th September 2019, from 9:00 am to 3:00 pm. Three members of the project group attended the workshop in addition to the consensus host (LME, RT, AD, and BA). Eight out of 11 clinicians were able to participate in the workshop: psychologists, special educators, clinical social workers, and a physician. Three clinicians were unable to attend for various reasons such as sickness etc.

For the second workshop, we recruited youth from MHU. The workshop took place in their location on 11 th November 2019, from 9:00 am to 3:00 pm and was administrated in the same way as the workshop with the clinicians. Ten out of 12 invited youth were able to participate in the priority setting, and three members of the project group facilitated the workshop (RT, SB and LME). Two participants were unable to attend.

After formal introductions and light refreshments, the participants received an introduction for one hour, to the principles of research, systematic reviews, and evidence-based practice. They were also informed about the purpose and agenda of the day. Thereafter, the participants were divided into small groups based on their professional background, age and in the workshop with the youth, earlier experience with anxiety and/or depression. For each topic, the participants were then mixed in different groups with at least three participants in each group. This part of the workshops lasted for four hours with a half an hour lunch break.

The groups were assigned the task of selecting 10 options and prioritising these for each topic. The groups worked independently but were facilitated by the host when necessary. Other members of the project group were silent observers, taking notes. At the workshop with the professionals, the host used images of children and adolescents with depression and anxiety during this process, as a reminder of the perspectives of the target group involved.

The final hour of the workshops included individual prioritising. All four lists were entered into a voting app by one of the members of the project group and each participant was asked to anonymously rank the final top ten priorities per list. This resulted in four top ten lists of priorities ranked in order by their perceived importance [see Underlying data 28 ].

Summary of existing research

The results of the document analysis were collated and made into 4 lists. In the surveys, the respondents were presented with these lists (see Table 1 and Table 2 ). Note that for several of these treatments and outcomes, the quality of the evidence is graded as low or very low (marked with * in the tables). Therefore, these could still be suggested as research uncertainties.

Results of the surveys: identified research uncertainties by clinicians and patient representatives

Overall, 674 respondents submitted a total of 1267 research suggestions in the three surveys. After content analysis, 379 unique suggestions (134 treatments for anxiety, 90 treatments for depression, 84 outcomes for anxiety and 71 outcomes for depression), were sent for ranking via e-mail to the clinicians and youth participating in the workshops.

In response, the clinicians ranked and shortened the list to 70 suggestions. The youth ranked and shortened it to 51 suggestions. For full detail of the results of the process see Figure 2 .

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Object name is f1000research-10-133634-g0001.jpg

Prioritisation of research uncertainties

Eight clinicians participated in the first workshop: psychologists, special educators, clinical social workers, and a physician. Two of the clinicians worked in the mental health services in the municipalities, and the six others worked in the specialist mental health service for children and adolescents.

The 10 youth participants from MHU participated in the second workshop. See detailed results of the process in Figure 2 and the final results of the workshops priority setting in Tables 3 , ​ ,4 4 , ​ ,5 5 and ​ and6 6 .

This study has demonstrated essential research priorities in terms of treatments that should be evaluated and outcomes that should be measured according to youth and clinicians. The top ten lists reflect both similarities and differences in what is considered important by the clinicians and the youth.

Clinicians ranked family and parent-based interventions as their top priority for both lists of treatments (anxiety and depression). Youth also ranked family and parent-based interventions as their top priority for treatments of anxiety. Functioning in daily life, and in the family are amongst the top ten treatment priorities by both groups. Other common priorities important to both clinicians and youth are increased cooperation between mental health services and schools, and multi-disciplinary cooperation.

Top priority for depression treatment among the adolescents, were easy access to treatment. The clinicians also emphasize increased cooperation between mental health services and schools, as well as group treatment and school-based interventions. Thus, the clinicians seem to focus on strengthening the environment around the youth to a greater extent than the adolescents do. School-based therapies, school functioning and access to a school psychologist are also similar priorities. The youth seem, however, to display a greater need for interventions for forming relationships, resilience groups, and life coping strategies, which is not mentioned at all in the clinicians’ list.

A unique priority suggested by the youth is therapy for transgender people, specifically regarding anxiety. This may demonstrate a difference between generations regarding the focus on gender identity and the need to cope with such issues.

On the lists of outcomes of interventions for both conditions, functioning in daily life, in the family, and at work were ranked very high by both the clinicians and the youth, as well as friends and social activities. Other important common suggestions are long-term follow-up of interventions, treatment satisfaction and user involvement. However, it is worth noting that the outcomes most important for the adolescents, for both anxiety and depression, were highly subjective/internal outcomes like resilience, faith in oneself, life skills, identity, daily life functioning and trust in other people. In contrast, the clinicians ranked friends and social activities on top of both lists, while this suggestion was not found on the adolescent’s lists. Thus, the clinicians seem to view the context the youth is in as more important than the youths do themselves, who to a greater extent emphasize personal coping skills, like faith in oneself and resilience. This difference may possibly tell us that contextual factors (friends, school or dropping out of school) are regarded less important for individuals struggling with mental health challenges, and that inner personal growth and mastery are key factors for these young people. The clinicians may, on the other hand, have been thinking more in terms of outcomes known to be preventive factors (like friendship and social structures). 23

Clinicians rated adverse events as important for both conditions. The lack of research of unwanted effects of treatments for depression in children and adolescents has recently been demonstrated in a mapping of systematic reviews. 24 Both the clinician’s views and Eidet’s article 24 point to the need for more research, and thus address adverse events in these treatment groups as an important evidence gap.

Strength and limitations

This study builds on rigorous qualitative and quantitative methods, including two extensive systematic reviews on the effects of treatments for anxiety and depression. To our knowledge this is also the first mapping study in Norway exploring research uncertainties related to treatments and associated outcomes for anxiety and depression.

The current study is in line with evidence-based practice as it is defined as ‘The conscientious, explicit and judicious use of current best evidence in making decisions about the care of the individual patient’. 25 Evidence-based practice highlights the consideration of the patient’s opinions in choice of treatment (alongside clinical opinions and research-based methods), and the current project contributes along these lines also, by letting patients voice their concerns regarding research gaps. We have integrated the best research evidence and involved clinical expertise both in the surveys and the workshop with clinicians. Furthermore, we have included the personal and unique values of the patients. All of these should be a part in any decision-making process concerning research and treatments for children and adolescents.

There has been increasing attention to patient-reported outcomes during recent years. Outcomes should be relevant and important to both patients, caregivers, health care professionals and other stakeholders making decisions about health care. 26 , 27 For discovering what outcomes are important to patients and health care professionals, consensus processes, as demonstrated in this study, are vital. This study is especially important because we succeeded in including the views of young people, considering how rare patient and family engagement are in research priority setting. 16

The importance of user involvement is demonstrated in feedback from participants in both workshops:

“ It feels very meaningful to be able to contribute to this project on behalf of all the patients I have been in contact with ”. “ Children and adolescents should always be involved in decision-making, not just clinicians ”.

Although the current study was partly inspired by the JLA framework there are some major discrepancies that need to be addressed. Firstly, we were unable to arrange a joint priority setting partnership between the two groups. Secondly, our study resulted in four different lists of priorities as it covers both treatments and treatment outcomes for anxiety and depression. Third, the lists in the current study consist of keywords and not fully phrased questions, due to the narrower scope aiming at extracting specific treatments and outcomes.

The limitation of consensus processes should be acknowledged. The current priorities are based on individual’s or groups’ point of views and their subjective opinions. We might, in our consensus process with a different pool of people in a different situation, reach a different result. 20 However, involving people together in a quality discussion to reach genuine consensus is of great value, as it represents an important contribution to the debate on research priorities. Bringing people together in a workshop enables them to exchange knowledge and information and make decisions in their meetings with the health services, based on a wider set of experiences.

Initially we intended to host only one priority setting workshop with both clinicians and the youth, however we were unable to find an appropriate date suitable for both groups. Although hosting a shared workshop would have had several benefits, we also found it useful to keep the groups separated. We were able to avoid challenges, such as ensuring the choice of participants being balanced, avoiding domination by one person, and reaching consensus when there may have been disagreement. The two separate processes allowed us to compare the results of professionals and the youth. It also provided a safe zone for professionals and the youth, where especially the latter could speak more freely and perhaps avoid feeling ‘led’ to conclusions by clinicians whom they perhaps could see as authority figures with more experience than themselves. However, keeping the groups separate meant that we also missed the opportunity of cross-fertilization of ideas and nuancing of perspectives, that mixing professionals and users may have contributed to.

We have demonstrated the possibility to develop an agreed four top ten lists of research priorities for anxiety and depression in children and adolescents, with contribution from youth experiencing anxiety or depression as well as clinicians. The perspectives from their individual lists, have the possibility to influence the research agenda according to the needs and opinions of both clinicians and the patients themselves.

Data availability

Acknowledgements.

We would like to thank the following for helping recruiting participants to the workshop with clinicians: Signe Revold, Akershus University Hospital, Morten Grøvli, Akershus University Hospital and a member of the RBUPs board and Kaja Kierulf, centre manager of RBUP. We would like to thank Thisbe Verner-Carlsson and Aida Tesfai at the Norwegian Mental Health Youth (Mental Helse Ungdom) for distributing the survey no. 3 and recruiting participants to the second workshop with the youth. We are grateful to NBUP, the Norwegian Associations of Mental Health Services for Children and Adolescents for help of distributing the survey no. 2. We also would like to thank our colleagues at RBUP, Siri Saugestad Helland, Kristian Rognstad and John Kjøbli for assistance with the first survey, distributed to persons working with children and young people's mental health in the municipalities. Finally, and most importantly, we would like to thank all the participants of both workshops.

[version 2; peer review: 2 approved]

Funding Statement

The author(s) declared that no grants were involved in supporting this work.

Reviewer response for version 2

Judith borghouts.

1 Department of Medicine, University of California Irvine, Irvine, CA, USA

I have looked at the authors’ responses and am satisfied with changes made.

Is the work clearly and accurately presented and does it cite the current literature?

If applicable, is the statistical analysis and its interpretation appropriate?

Not applicable

Are all the source data underlying the results available to ensure full reproducibility?

Is the study design appropriate and is the work technically sound?

Are the conclusions drawn adequately supported by the results?

Are sufficient details of methods and analysis provided to allow replication by others?

Reviewer Expertise:

Academic researcher in Digital Mental Health and Human-Computer Interaction with 10 years of experience in quantitative and qualitative research.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Kristina Staley

1 TwoCan Associates, Ross-on-Wye, UK

I have looked at the authors’ responses and changes and am satisfied that the issues I raised have been addressed. I am happy to recommend the revised version for indexing.

I cannot comment. A qualified statistician is required.

Reviewer response for version 1

This paper describes an approach, inspired by James Lind Alliance (JLA) methods, to identify research priorities in child and adolescent anxiety and depression treatments. Strengths of the paper are the detailed descriptions of the methods used. I also appreciate the authors making the data available.

It was however quite unclear what the paper is trying to contribute, as the problem, objective and results do not seem aligned. The paper starts by highlighting the problem of treatment uncertainties, and that some treatments lack scientific evidence. The introduction then states that the objective of the study was to identify research priorities, which seems different from treatment uncertainties. Finally, it presents results of what types of treatments clinicians and youth would like to see. If this all relates to the same thing, the paper should do a better job explaining how these are all connected.

Related to my point above, the key terms are not well-defined. The abstract mentions treatment uncertainties but it is unclear what this is. It becomes a little bit clearer through examples given in the introduction (“uncertainties are either consequences of a lack of research, or the research is not adequately performed”), but it is then not clear how you ‘prioritize’ uncertainties? Do the authors mean which type of treatments should be given priority in future research? Furthermore, Table 4 and 6 mention the term ‘outcomes’, which in the context of treatment usually means treatment outcomes, such as measurable health symptoms. A number of the outcomes in these tables do not seem to be outcomes in the traditional sense; for example, how is ‘friends and social activities’ an outcome? Is this somehow related to social connectedness? The paper is currently lacking a clear explanation of all of these terms, concepts and how they relate to one another.

Lastly, if the objective was to identify research priorities, it was not clear to me why non-researchers were asked to identify uncertainties. As the paper states, respondents can be unfamiliar with research and may not be equipped to prioritize research. It seems that the paper instead collected a stakeholder perspective of important considerations in adolescent treatment for anxiety and depression, which is still important, but is not reflected in the paper’s objective at all.

I recommend the authors to clearly define the key concepts, clarify the problem, aim of the study, how the results address this problem and aim, and make this consistent throughout the paper.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

Brynhildur Axelsdottir

Regional Centre for Child and Adolescent Mental Health, Eastern and Southern Norway (RBUP), Norway

1.This paper describes an approach, inspired by James Lind Alliance (JLA) methods, to identify research priorities in child and adolescent anxiety and depression treatments. Strengths of the paper are the detailed descriptions of the methods used. I also appreciate the authors making the data available.

Response: We see the reviewers point; however, we see this as the one influencing the other. What we hope with our process is that identified treatment uncertainties (treatments that lack scientific evidence) should become priorities in future research. Research priorities should be based on research uncertainties established by systematic reviews of the existing evidence. We have added a sentence to make this more explicit.

By “treatment” we refer  to any action or intervention used to change an aspect of a young person’s mental health, that being medicines or school-based interventions. Such treatments may also have an impact on other aspects of the young person’s life that may be important to consider in research. As we state in the paper, the outcomes found to be important to evaluate in research by researchers often differs from those of providers and patients. Thus, in many cases effects on outcomes important to patients and providers are unknown. This study tries to address this issue. Such outcomes may include a person’s ability to participate in social activities and so on.

Our aim was to enable the participants to suggest and prioritise preferred treatments and outcomes and thus highlight the needs of users and clinicians in hope that these needs could be met in future studies. The lists of priorities are the outcome of this whole process, presenting the interventions and outcomes that the involved groups would like to see in future studies. We acknowledge that this link may have not been sufficiently elaborated on and have therefore inserted some sentences that may help clarify the link between these stages of the process in the introduction and the discussion. The objectives have also been rephrased and hopefully appear clearer.

2. Lastly, if the objective was to identify research priorities, it was not clear to me why non-researchers were asked to identify uncertainties. As the paper states, respondents can be unfamiliar with research and may not be equipped to prioritize research. It seems that the paper instead collected a stakeholder perspective of important considerations in adolescent treatment for anxiety and depression, which is still important, but is not reflected in the paper’s objective at all.

Response: The idea here is to involve the perspectives of the patients involved and the professionals that treat them. They have unique insights in their needs, which may deviate from the priorities of a researcher. Further, user involvement is one of the main principles of the JLA guidebook, which have partly inspired us in conducting this study. The JLA initiative was established to bring both patients, carers and clinicians together in priority setting partnerships. This ensures shared decision-making processes, which is a cornerstone of evidence-based practice.

3.I recommend the authors to clearly define the key concepts, clarify the problem, aim of the study, how the results address this problem and aim, and make this consistent throughout the paper.

Response: We have, based on the reviewers’ responses, rephrased the aim, and sought to make the objective clearer. We believe that our responses to other remarks from the reviewers may also make the paper more accessible. In the introduction, we have described some of the key concepts for clarification.

We would like to thank the reviewers for their valuable comments.

This paper reports on a priority setting exercise which has drawn on the JLA approach but has changed so far from it that I question whether to make the links is appropriate. For example I'd challenge the use of the term priority setting partnership in the title.

The approach in this paper differs from the JLA process in two main ways:

Furthermore, I'd like the authors to comment on how the prioritised lists of interventions and outcomes might be used to shape future research.

  • The final workshop - it is essential that all parties come together and reach a shared agreement of the Top Ten. It would seem important to find a date for such a meeting that all could attend rather than have separate meetings. And for the group discussion to inform the prioritised list rather than individuals voting on an app. 

So in general there seems to have been limited shared decision-making at each of the stages of this process which makes me question whether this was genuinely a partnership or actually different groups prioritising topics separately. This is what makes it very different to the JLA process.

The outputs are quite distinct from those of a JLA process - so I suggest the authors refer to the JLA perhaps once, and instead describe their own process and the rationale for how they have approached it, what they expect the impact to be, and their perceived value of their outputs. 

Different does not mean better or worse - this is a different process to the JLA and may have strengths or weaknesses as a result. Perhaps these could be explored in the article. The JLA is not a set of methods, but the principles and values that underpin partnership working are absolutely key to it and these are not described in the approach in this paper and I therefore recommend that the suggestions that this process is linked to the JLA approach are reduced.

I have worked on over a dozen JLA PSPs as an Information Specialist and have worked in the field of patient and carer involvement in research for over 20 years

1.This paper reports on a priority setting exercise which has drawn on the JLA approach but has changed so far from it that I question whether to make the links is appropriate. For example I'd challenge the use of the term priority setting partnership in the title.

Categorising the uncertainties collected via survey of young people and professionals. In a JLA process the Steering Group, a mix of professionals and affected patients/carers, are heavily involved in interpreting the responses to generate a list of uncertainties using phrasing and language that summarise the responses. The aim is always to stay faithful to the original responses. In this paper the researchers have drawn out interventions and outcomes as separate lists - not whole questions. I do not understand the rationale for this and would like a clearer explanation in the article. As they have identified, the language used and the priority given to different ways of understanding the issues makes it difficult to combine the youth and professionals' priority lists of interventions/outcomes. In the JLA process, this is done in the partnership of the Steering Group to reach a shared agreement of the list of topics to be prioritised, a shared understanding of what these mean so that people from all perspectives can understand and prioritise the shared list.

Response: We thank the reviewer for pointing this out and we acknowledge the differences of our study and the James Lind Alliance framework. We have therefore changed the title of the article. In addition, we have elaborated on these differences in methods and discussion.

As to the comment on how the prioritised lists of interventions and outcomes might be used to shape future research, we strongly believe that researchers can be inspired to see what interventions lack evidence (based on evidence gaps identified by the overviews of systematic reviews) as well as what outcomes should be measured when designing new studies on these subjects, based on the participants’ priorities. To highlight the desired interventions and outcomes of users and clinicians may hopefully bring awareness to researchers regarding the needs of these groups – potentially enhancing shared decision-making in future studies.

2. The final workshop - it is essential that all parties come together and reach a shared agreement of the Top Ten. It would seem important to find a date for such a meeting that all could attend rather than have separate meetings. And for the group discussion to inform the prioritised list rather than individuals voting on an app.

Response: There is no gold standard to priority setting of research uncertainties. JLA has however developed an extensive experience and evidence base in this area which has inspired our efforts.

We acknowledge that our approach differs from that of the JLA. We have revised our manuscript to make this clearer and have made it explicit which of the methodological choices recommended by JLA we have applied. We have also added a paragraph to the discussion about the potential limitations and strengths of the choices we made.

As the reviewer points out, the JLA is not a set of methods but suggests some principles and values that should be considered. The experts and patients taking part in our study were not able to meet in the same day for the consensus workshop, and thus our process resulted in two separate sets of priority lists. Although the resulting lists were not created in a partnership of patients and providers, the results of these two consensus processes provides the opportunity to compare the differences in priorities by patients and providers. This may have brought additional – and potentially valuable – information and possibly cover more evidence gaps.

Even though our process differs from that of JLA, we have used methods of high quality, including basing our process on high-quality systematic reviews, including both qualitative and quantitative feedback from experts and patients, and applying a recognized consensus-process methodology. We believe that the priorities-lists resulting from our study is an important contribution to this research and should be used to shape future research efforts.

3. The outputs are quite distinct from those of a JLA process - so I suggest the authors refer to the JLA perhaps once, and instead describe their own process and the rationale for how they have approached it, what they expect the impact to be, and their perceived value of their outputs.

Response: We accept and agree that our process varies from the one of JLA and we have erased the sentence of JLA in the abstract and reframed sentences where we mention JLA  in the method section, as well as reduced the numbers of references to the JLA guidance. We have elaborated on strengths and weaknesses of the current study in the discussion and added some clarifications in the introduction about the differences between our approach and the JLA method.

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Anxiety and Depression Overlap: Link Between Comorbid Disorders

  • How They Feel
  • When Treatment-Resistant

Having depression and anxiety at the same time is somewhat common. Research shows that 60% of people with anxiety will also have symptoms of depression. The rate is the same for those who have depression with symptoms of anxiety.

Anxiety and depression are two distinct conditions that can occur at the same time. This can make symptoms more complex. However, the same treatments can address both problems. They can often improve with psychotherapy (talk therapy), drugs, or both.

This article describes the link between anxiety and depression. It also explains their symptoms, diagnosis, and treatment when they occur at the same time.

MementoJpeg / Getty Images

Anxiety and Depression: An Indirect or Direct Link?

The relationship between anxiety and depression is complex. While depression is typically regarded as a low-energy condition and anxiety a high-energy condition, these disorders and their symptoms commonly occur together. The reason they are often linked is well understood, though several potential factors exist.

Many of the same factors that predispose you to anxiety also make you vulnerable to depression. Both are considered internalizing disorders, problems that are developed and maintained to a great extent within the affected person.

Like other internalizing disorders, anxiety and depression are linked to similar factors that include genetic risk and neuroticism (the tendency toward negative thoughts). They are also associated with several shared nongenetic risk factors such as early trauma and current stress.

Anxiety and depression have many overlapping symptoms because they both involve changes in the function of neurotransmitters like serotonin in your brain. Your symptoms may meet the criteria of both disorders.

The relationship between anxiety and depression may not be a situation in which one causes the other, but the fact that they may be two sides of the same coin. Being depressed can often make you feel worried or anxious. Similarly, having an anxiety attack can make you feel hopeless with depression.

Related Causes/Risk Factors

While the exact causes of comorbid depression and anxiety are not known, the following risk factors increase your chances of having these disorders together:

  • Lifetime history of anxiety or depression
  • Adversity during childhood
  • Poor parenting
  • Recent major life events
  • Current exposure to stress
  • High neuroticism
  • Substance use disorders
  • Family history

How Anxiety and Depression Symptoms Feel

Symptoms of anxiety and depression can vary by individual. However, both disorders can cause symptoms that can interfere with daily life and interpersonal relationships.

Similarities

Symptoms common in both anxiety and depression include:

  • Problems with digestion
  • Unintended changes in appetite or weight
  • Inability to concentrate or make decisions
  • Problems sleeping, either too much or too little
  • Feeling constantly restless or irritable

Differences

Worrying is normal in some situations. Anxiety differs from normal worrying because it involves excessive fear that can be debilitating. Symptoms that may be characteristic of anxiety include:

  • Constantly feeling wound up or restless
  • Ongoing excessive worry about the immediate or long-term future
  • Focusing on negative outcomes when decision-making
  • Uncontrollable, racing thoughts about something going wrong
  • Avoiding situations that could cause worry and anxiety
  • Feeling a lack of certainty

The key characteristics of depression involve a persistent feeling of extremely low mood and/or loss of interest in activities you once enjoyed. Symptoms that may be characteristic of depression include:

  • Feelings of sadness and persistent low mood
  • Lack of interest or enjoyment in life experiences
  • Loss of energy or extreme fatigue
  • Increase in purposeless physical activities such as hand-wringing that is noticeable to others
  • Increase in slowed movements or speech that occur often enough to be noticed by others
  • Feelings of worthlessness or guilt
  • Emphasis on loss or deprivation
  • Thoughts of death or suicide

Help Is Available

If you or someone you know is having suicidal thoughts, call or text 988  to contact the  988 Suicide & Crisis Lifeline  and connect with a trained counselor. If you or they are in immediate danger, dial 911 .

For more mental health resources, see our  National Helpline Database .

Anxiety, Depression, or Both: How to Diagnose Symptoms

Many symptoms of anxiety and depression overlap, making it harder to determine which disorder is causing the problem. When anxiety and depression occur together, symptoms tend to be more intense and persistent because they work together. This can make your condition harder to diagnose and more complex to treat.

Diagnosing symptoms of a mental health disorder requires a comprehensive evaluation by a mental health provider. This can help ensure you get an accurate diagnosis and treatment.

Symptoms that might indicate that both anxiety and depression exist include:

  • Persistent irrational fears or worries
  • Physical symptoms like fatigue, headaches , labored breathing , abdominal pain , or rapid heartbeat
  • Persistent feelings of worthlessness or sadness
  • Problems going to sleep or staying asleep
  • Difficulty remembering or concentrating
  • Inability to make decisions
  • Loss of interest in hobbies or activities
  • Constantly feeling tired and cranky
  • Panic attacks or a sense of losing inner control
  • Inability to live in the moment and relax

Role of Gut Microbiome

Gut microbiome includes all the microorganisms living in your digestive system. It affects your digestive health as well as your overall health.

Research indicates that there is evidence of a link between gut microbes and depression. It is attributed to the gut and brain connection, called the gut-brain axis. Evidence shows that inflammation caused by gut microbes can influence mood in depression.

How to Cope With Comorbid Anxiety and Depression

There is no single treatment appropriate for every case of comorbid (co-occurring) anxiety and depression. Therapies typically include antidepressant drugs and/or a form of psychotherapy. Self-care can help you maintain your progress.

While research indicates that a combination of medication and therapy can provide the best results, your treatment plan may differ. Depending on your symptoms, you may be advised to start your treatment with either one of these therapies.

Self-care includes behaviors that support your physical and mental well-being. It involves actions that can help manage symptoms of anxiety and/or depression and complement therapy and/or medications.

The following strategies are ways to prioritize self-care:

  • Establish and maintain a regular exercise routine with a target of 30 minutes daily. Exercising for smaller amounts of time can also make a difference.
  • Follow a diet of nutritious meals and adequate hydration. Limit caffeinated beverages, alcohol, and added sugar.
  • Maintain proper sleep hygiene , which involves following a daily sleep schedule and other behaviors supporting a good night's sleep.
  • Try activities that involve relaxation, meditation, and breathing exercises to relieve stress and reduce feelings linked with anxiety and depression.
  • Remain connected with friends or family members you can count on to provide practical help and emotional support if needed.
  • Practice gratitude by journaling to remind yourself of the positive things in your life.
  • Establish goals and priorities to avoid taking on new tasks and responsibilities that can overwhelm you.

Therapy is regarded as a key part of treatment for symptoms that involve anxiety and/or depression. Your results and the time it takes to achieve them depend on your symptoms and your unique situation.

The following types of therapy are used to treat anxiety and depression:

  • Cognitive behavioral therapy (CBT) : This type of psychotherapy is considered the gold standard for treating anxiety and depression, among other mental health conditions.
  • CBT is a time-limited and goal-oriented therapy. It focuses on changing negative thought patterns by altering negative behaviors and emotions.
  • Interpersonal therapy (IPT) : This type of time-limited psychotherapy helps you see emotions as social signals so you can use them to improve interpersonal challenges. Rather than focusing on your past, IPT focuses on communication and current interpersonal relationships and issues you're having related to them.
  • Dialectical  behavioral therapy (DBT) : DBT is a modified version of CBT that focuses on healthy ways to live in the moment, regulate emotions, and improve interpersonal relationships. It integrates mindfulness skills, interpersonal effectiveness, distress tolerance, and emotion regulation into treatment.
  • Acceptance and commitment therapy (ACT) : ACT is a type of psychotherapy that focuses on mindfulness, remaining in the present, and strategies for behavioral changes. It focuses on helping you become psychologically flexible so you can accept difficult thoughts and emotions while committing to meaningful life activities consistent with your goals and values.

With Medication

Medication for anxiety and/or depression works by increasing the activity of neurotransmitters, like serotonin , dopamine , norepinephrine , and gamma-aminobutyric acid ( GABA ). These are the chemical messengers in your brain that affect mood regulation.

The type of medication you receive depends on your symptoms and other factors regarding your overall condition. The following classes of medications are commonly used:

Selective serotonin reuptake inhibitors (SSRIs) : SSRIs are the first-line treatments preferred for treating depression and many comorbid anxiety disorders. They work by increasing serotonin levels.

SSRIs include:

  • Celexa ( citalopram )
  • Lexapro ( escitalopram )
  • Paxil ( paroxetine )
  • Prozac ( fluoxetine )
  • Zoloft ( sertraline )

Serotonin-norepinephrine reuptake inhibitors (SNRIs) : SNRIs increase levels of serotonin and norepinephrine. These drugs are also acceptable first-line treatments for comorbid anxiety and depression.

SNRIs include:

  • Effexor ( venlafaxine )
  • Pristiq ( desvenlafaxine )
  • Cymbalta ( duloxetine )
  • Savella ( milnacipran ):
  • Fetzima ( levomilnacipran ):

Tricyclic antidepressants (TCAs) : TCAs boost levels of serotonin and norepinephrine. TCAs include:

  • Elavil ( amitriptyline )
  • Pamelor ( nortriptyline )
  • Tofranil ( imipramine )
  • Norpramin ( desipramine )
  • Anafranil ( clomipramine )

Monoamine oxidase inhibitors (MAOIs) : MAOIs were the first class of antidepressants. They are generally regarded as outdated because of their side effects, though they may be appropriate for treatment-resistant depression in its later stages.

MAOIs include:

  • Marplan ( isocarboxazid )
  • Nardil ( phenelzine )
  • Emsam ( selegiline patch)

Treatment-Resistant Depression (With Anxiety)

Treatment-resistant depression (with anxiety) describes depression that hasn't responded to an adequate trial of at least two different antidepressants. Research indicates that the situation is not uncommon. Between 29% and 46% of people with depression show partial or no response to treatments.

Therapies for treatment-resistant depression (with anxiety) involve the following:

  • Transcranial magnetic stimulation (TMS) : TMS is a noninvasive treatment that involves placing electromagnets on your head. The magnets send hundreds of thousands of targeted magnetic pulses to stimulate and reset the neurological processes regulating mood.
  • Electroconvulsive therapy (ECT) : ECT, previously known as electroshock therapy, is a procedure in which controlled electric currents are passed through your brain while you are under anesthesia. Treatment is usually given two or three times a week for six to 12 weeks, depending on your symptoms and response.
  • Ketamine : Ketamine has been used as an anesthetic in surgeries for many years. It is also used off-label for treatment-resistant depression. It works by targeting subsets of neurotransmitters that are different from those affected by traditional antidepressants. Ketamine is delivered by intravenous infusion (directly into your vein) in a procedure that takes up to an hour.
  • Spravato (esketamine): Esketamine is a ketamine formulation approved by the Food and Drug Administration (FDA) for depression. Esketamine is more potent than ketamine, so it may produce results with lower doses than ketamine. It is administered as an intranasal spray in monitored treatment sessions over a few weeks.

Feelings of sadness and worry are normal. However, when these types of feelings intrude on your daily life, they may be signs of mental health problems.

Anxiety and depression are two of the most commonly diagnosed mental health problems. While they are two distinct conditions, they often occur at the same time.

When these disorders occur together, treatments are more complex. Symptoms can overlap and often worsen when more than one mental health problem exists. The good news is that treating these comorbid disorders is most effective when they are handled at the same time.

National Association on Mental Illness NAMI. The comorbidity of anxiety and depression .

Hartgrove Behavioral Health System. The relationship between anxiety and depression .

Kalin NH. The critical relationship between anxiety and depression .  AJP . 2020;177(5):365-367. doi:10.1176/appi.ajp.2020.20030305

Hopwood M. Anxiety symptoms in patients with major depressive disorder: commentary on prevalence and clinical implications .  Neurol Ther . 2023;12(1):5-12. doi:10.1007/s40120-023-00469-6

Möller HJ, Bandelow B, Volz HP, Barnikol UB, Seifritz E, Kasper S. The relevance of ‘mixed anxiety and depression’ as a diagnostic category in clinical practice .  Eur Arch Psychiatry Clin Neurosci . 2016;266(8):725-736. doi:10.1007/s00406-016-0684-7

Cleveland Clinic Health Essentials. Anxiety vs. depression: which do I have (or is it both)?

Mental Health Foundation. Generalized anxiety disorder .

American Psychiatric Association. What is depression?

Pennisi E.  Gut microbe linked to depression in large health study .  Science . Published online February 4, 2022. doi:10.1126/science.ada0998

Harvard Health Publishing Harvard Medical School. Medication or therapy for depression? Or both?

National Institute of Mental Health. Caring for your mental health .

David D, Cristea I, Hofmann SG.  Why cognitive behavioral therapy is the current gold standard of psychotherapy .  Front Psychiatry . 2018;9. doi:10.3389/fpsyt.2018.00004

Coffey SF, Banducci AN, Vinci C.  Common questions about cognitive behavior therapy for psychiatric disorders .  Am Fam Physician . 2015;92(9):807-812. PMID: 26554473.

International Society of Interpersonal Psychotherapy. Overview of IPT .

The Linehan Institute Behavioral Tech.  What is dialectical behavior therapy (DBT)? .

Dindo L, Van Liew JR, Arch JJ. Acceptance and commitment therapy: a transdiagnostic behavioral intervention for mental health and medical conditions .  Neurotherapeutics . 2017;14(3):546-553. doi:10.1007/s13311-017-0521-3

Centre for Addiction and Mental Health (CAMH). Antidepressant medications .

Coplan JD, Aaronson CJ, Panthangi V, Kim Y. Treating comorbid anxiety and depression: Psychosocial and pharmacological approaches .  World Journal of Psychiatry . 2015;5(4):366. doi:10.5498/wjp.v5.i4.366

UpToDate. Patient education: medicines for depression (the basics) .

Columbia University Department of Psychiatry. Finding solutions when depression resists treatment .

UCSanDiego Health. Transcranial magnetic stimulation .

American Psychiatric Association. What is electroconvulsive therapy?

Nebraska Medicine. What is esketamine, and is it effective in treating depression?

Yale Medicine. How ketamine drug helps with depression .

By Anna Giorgi Anna Zernone Giorgi is a writer who specializes in health and lifestyle topics. Her experience includes over 25 years of writing on health and wellness-related subjects for consumers and medical professionals, in addition to holding positions in healthcare communications.

ORIGINAL RESEARCH article

The relationship between anxiety and depression under the pandemic: the role of life meaning.

Daniel T. L. Shek

  • Department of Applied Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China

Introduction: COVID-19 is a stressor creating much anxiety for the general public, such as anxiety related to possible infection, social distancing, financial strain and uncertainty. As the scientific literature shows that there is an intimate relationship between anxiety and depression, it is important to ask whether anxiety is related to depression under the pandemic and whether spirituality indexed by life meaning can moderate the relationship between anxiety and depression. According to theories highlighting the importance of life meaning, relative to people with a higher level of life meaning, the relationship between anxiety and depression would be stronger in people with a lower level of life meaning.

Methods: Empirically, we collected data in two waves (i.e., before and after the first wave of COVID-19, respectively) from 4,981 adolescents recruited in Sichuan, China. Then, the 41-item “Screen for Child Anxiety Related Emotional Disorders” was employed to measure anxiety symptoms, 20-item “Center for Epidemiological Studies-Depression Scale” was utilized to examine depression symptoms, and the “Spirituality Subscale of the Chinese Positive Youth Development Scale” for assessing life meaning.

Results: We found that anxiety significantly predicted depression at each wave and across time. Second, controlling for Wave 1 depression scores, results showed that a drop in Wave 1 anxiety predicted a drop in depressive symptoms over time. Regarding the relationship between meaning in life and depression, spirituality indexed by meaning in life negatively predicted depression at each wave and over time, and predicted change in depression across time. Finally, multiple regression analyses showed that life meaning moderated the predictive effect of anxiety on depression.

Discussion: The findings support the thesis that spirituality serves as a protective factor for psychological morbidity in Chinese adolescents. The study also suggests the importance of helping adolescents to develop life meaning under COVID-19.

Introduction

Anxiety is a negative emotional state that is prevalent in different stages of the life cycle, especially in childhood and adolescence ( Blumberg and Izard, 1986 ; Cohen et al., 2018 ). There is also an intimate link between anxiety and other negative emotional states, particularly depression. While anxiety and depression have similar emotional profiles ( Clark and Watson, 1991 ; Brady and Kendall, 1992 ), they are different in terms of several areas. Blumberg and Izard (1986) pointed out that while fear and apprehension are dominant in anxiety, sadness and lack of energy are central features of depression. Higgin et al.’s ( Higgins et al., 1985 ) self-concept discrepancy theory also highlights that depression is primarily related to dejection whereas anxiety is characterized by agitation. According to Beck and Clark (1988) , the perceived physical or psychological threat is central to anxiety whereas the depressive state emphasizes loss or deprivation. Watson et al. (1995) further proposed that “anhedonia” is a central feature of depression whereas “hyperarousal” is the prime attribute of anxiety disorders.

Empirically, consistent results across comorbidity studies suggest the co-existence of anxiety and depression at the same time (e.g., Almeida et al., 2012 ). Under COVID-19, the reported combined rate of anxiety and depression was 12.4%, with incidence rates of 14% and 19% for anxiety and depression, respectively, among 500 participants in Hong Kong society ( Choi et al., 2020 ). Axelson and Birmaher (2001) concluded that approximately 10%–15% of adolescents reporting anxiety symptoms also report depressive disorders and around 25%–50% of youth experiencing depression have a comorbid anxiety disorder. As early as 1988, the World Health Organization initiated an international study involving 14 countries with concerns about mental health in primary care, discovering that “nearly half of the cases of depression and anxiety appeared in the same patients and at the same time” ( Sartorius et al., 1996 , p. 40). In New Zealand, according to a birth cohort ( N  = 1,037), Moffitt et al. (2007) found that while for 32% with anxiety disorders, depression preceded or coincided with anxiety disorder, anxiety occurred before or simultaneously with the onset of depression among up to 37% of depression cases.

In this study, we explored several issues using a longitudinal dataset collected from young people in mainland China before and after school lockdown in the first wave of the pandemic in 2019–2020. These include the predictive effect of anxiety on depression; the predictive effect of life meaning on depression; and the moderating effect of life meaning on the relationship between anxiety and depression.

Relationship between anxiety and depression

There are continuous debates on the causal relationships (i.e., anxiety contributes to depression; depression results in anxiety) and comorbidity involved in anxiety and depression ( Cohen et al., 2018 ). On the one hand, there are several conceptual models proposing that anxiety is an antecedent of depression. Barlow (2000) proposed the triple vulnerabilities model of anxiety disorders. In this model, it was hypothesized that “generalized biological vulnerability” combined with “generalized psychological vulnerability” (e.g., weaker sense of predictability and control) and “specific psychological vulnerabilities” rooted in special early risk learning experiences would lead to stress (p. 1257), which would further lead to generalized anxiety and depression. With reference to genetic factors, stressful life events, anxiety traits and depression, Sandi and Richter-Levin (2009) proposed that genetic risk factors and early experiences serve crucial roles during the evolution of high anxiety trait neuroticism, which is the primary etiology for the anxiety disorder incidence leading to the development of depression. To elucidate the developmental trajectories and relational patterns of internalizing problems over childhood and adolescence, Cohen et al. (2018) hypothesized a “heterotypic discontinuity” model proposing that childhood anxiety shapes adolescent depressive symptomology. While “heterotypic continuity” arises when a symptom expression sets the stage for one new form of psychopathology, “discontinuity” refers to the same symptom functioning differently at various stages of progression. In their study, they found that while child anxiety predicted adolescent anxiety, child anxiety (and child depression) predicted adolescent depression. In another theoretical framework, Cyranowski et al. (2000) explained “depressogenic vulnerabilities” in women. It maintains that a combination of “insecure parental attachments,” “anxious/inhibited temperament,” and “low instrumental coping skills” for independence (and interaction) put individuals at risk for “difficult adolescent transition,” then resulting in “anxiety.” Concurrently, female-specific “hormonal changes at puberty,” “pubertal intensification in affiliative need,” along with “female gender socialization” lead females to greater vulnerability throughout this process, creating a stronger “depressogenic diathesis” with anxiety at its core. Subsequently, high-risk females who possess high anxiety accompanied by “elevated affiliative focus, low attachment security, and low instrumentality” are predisposed to depression when coping with “negative life events” (p. 24).

On the other hand, there are models proposing that depression is an antecedent of anxiety, although the number of such theories is few. In an early study, Neale and Kendler (1995) suggested that major depression might cause generalized anxiety disorder (i.e., increased anxiety because of higher depression liability). Weeks et al. (2009) also formulated a cognitive model on social anxiety highlighting that “fear of evaluation and depressive cognitions lead to social anxiety and submissive withdrawal” (p. 375).

Finally, there are views suggesting the comorbidity of anxiety with depression. Brady and Kendall (1992) proposed that anxiety symptoms are at a greater likelihood of occurring in conjunction with depression rather than in isolation, and that they highly overlap. Similarly, Clark and Watson (1991) argued that syndromes of anxiety and depression possess common nonspecific components (i.e., “negative affectivity”), such as upset, distress and general maladjustment, while the two are distinguished by “physiological hyperarousal” particular to anxiety and “absence of positive affect” (e.g., anhedonia) typical of depression (p. 316). Likewise, Neale and Kendler (1995) proposed the co-morbidity of generalized anxiety and major depression could be contributed by a cluster of shared genetic and environmental risk factors (i.e., correlated liabilities model). Consistent with the shared etiology hypothesis, Alloy et al. (1990) proposed a helplessness-hopelessness perspective for anxiety and depression disorders to explain the high comorbidity of the two domains. When confronted with negative life events, individuals with pessimistic inferential styles are much more inclined to generate a feeling of helplessness that would increase their likelihood of developing hopelessness, which is a substantial cause of anxiety and depression. For the comorbidity of anxiety with depression in young people, Seligman and Ollendick (1998) proposed four possible explanations. First, it is due to conceptual overlap such as the symptoms involved. Second, they are different indicators underlying a single construct. Third, overlaps in risk factors lead to the observation of comorbidity. Finally, anxiety increases depression risk in young people.

Empirical evidence on the predictive relationships between anxiety and depression

There is research evidence supporting the claim that anxiety is a precursor of depression. Pine et al. (1998) showed adolescent anxiety or depression significantly predicted an enhanced peril of depression in adulthood by approximately 2 to 3 fold. Based on a birth cohort of 1,265 New Zealand children, Woodward and Fergusson (2001) revealed a positive significant association between reported anxiety during teenage years and the later onset of anxiety disorders, major depressive disorder, and drug abuse. Chaplin et al.’s ( 2009 ) longitudinal survey in five middle schools also showed a predictive contribution of anxiety and worry to depressive symptoms one year later, which was more intense in girls than boys. Assessing Norwegian children ( N  = 1,439), Aune and Stiles (2009) showed that while preliminary depressive signs were not observed to predict future social anxiety, initial social anxiety did predict the evolution of depression. Similarly, tracking Swedish middle-aged and older twins ( N  = 1,391), Wetherell et al. (2001) revealed that despite the fact that depression and anxiety were strongly associated and anxiety symptoms led significantly to the progression of depression over time, the opposite causal direction failed to hold.

Studies also showed the predictive relationship of anxiety with depression in clinical studies. Beesdo et al. (2007) discovered that the cumulative incidence of social anxiety disorder was 11.0% and subsequent major depressive episode or dysthymia was 27.0% among 3,021 young adults in Germany. According to Parker et al. (1999) , anxiety manifested as social avoidance or inhibition preceded “early-onset non-melancholic major depression” (p. 11) particularly readily, with the character of anxiety established as a risk role. Bittner et al. (2007) showed that childhood overanxious disorder significantly predicted both overanxious disorder and depression in adolescence. Coelho et al. (2011) suggested that high-level antenatal generalized anxiety disorder was detected as an independent predictive factor for postnatal depression. Among the 250 patients in primary care struggling with both affective disorders and physical pain who live in the United States, Bair et al. (2013) revealed that baseline generalized anxiety disorder significantly predicted depression severity after 12 months. Similarly, Starr and Davila (2012) revealed that, at various time lags, daily anxiety anticipated the subsequent emergence of the depressed mood, whereas they simultaneously found that depressed mood consistently failed to forecast later anxiety.

Under COVID-19, Vowels et al. (2022) found that personal attachment anxiety significantly predicted individual depression, while their partner’s attachment style did not predict the worsening of one’s mental health. In contrast, Beesdo et al. (2007) argued that not only the severity of social anxiety disorder predicted individual subsequent depression, but the predictive effect of parental anxiety was also significant. Ranney’s et al. ( 2021 ) research additionally suggested that parental anxiety was significantly categorized as one of the critical risk contributors to their children’s depression progression. There are also studies examining mediating factors in the significant linkage between anxiety and depression, including non-acceptance in intimate relationships ( Jacobson and Newman, 2016 ), anhedonia ( Winer et al., 2017 ), and avoidance ( Jacobson and Newman, 2014 ).

On the other hand, there are few studies suggesting that depression predicts anxiety. Kim-Cohen et al. (2003) also showed that individuals suffering from adult anxiety were considered probable with a depression history during adolescence. Rallis et al. (2014) found among 214 pregnant women in Australia that an increase in depression in early pregnancy was predictive of elevated stress and anxiety in late pregnancy. As opposed, Schiffer et al. (2008) argued that negative affectivity and social inhibition, rather than depressive symptoms, predicted clinical anxiety based on the sample of Dutch patients with systolic chronic heart failure.

Besides the above two categories of evidence, there are studies suggesting the bidirectional influences between anxiety and depression, although the intermediate latent trajectories and mechanisms of such influences are as yet less clear ( Olino et al., 2010 ). Based on a 3-year longitudinal study of elementary school children ( N  = 330) and their parents ( N  = 228), Cole et al. (1998) found that both child-and parent-reported anxiety positively predicted a slight but significantly increased childhood depression over time, yet unexpectedly discovered that parent-reported child depression negatively predicted anxiety, implying that children whose parents reported depression had lower anxiety levels subsequently. Echoing this observation, Snyder et al. (2009) identified that teacher-rated child anxiety symptoms from children aged 5.3 to 6.8 years promoted later depressive symptoms, whereas depressive symptoms suppressed later anxiety from children aged 6.8 to 9.3 years. After performing a meta-analysis encompassing 66 studies, Jacobson and Newman (2017) reached the conclusion that anxiety and depression acted as bidirectional risk factors toward each other longitudinally.

Life meaning and psychological well-being

Life meaning plays an important role in existential psychology. In contrast to the behaviorists’ view that human beings are passive organisms responding to environmental stimuli and the psychoanalysts’ belief that human beings are susceptible to the influence of inner instincts, existential psychologists assert that individuals are capable of making authentic choices within their freedom and constraints of the reality. With particular reference to Frankl (1959) , he posited that human beings are not passively responding to the environment and are not motivated by the “will to pleasure” (i.e., psychoanalytic focus on hedonic drives). Instead, life meaning (i.e., “will” to meaning) plays an important role in human behavior. The basic thesis is that when there is no meaning in an individual (i.e., existential vacuum), psychopathologies come in to fill the psychological vacuum. According to Crumbaugh and Maholick (1964) , life purpose or life meaning was conceived as “ontological significance of life from the point of view of the experiencing individual” (p. 201). The general hypothesis derived from Frankl’s theory is that life meaning would be a positive predictor of psychological well-being.

There are other conceptualizations of meaning of life in the scientific literature. Heintzelman (2018) proposed that meaning of life has three aspects: “purpose, significance, and coherence,” with purpose meaning pursuing significant goals which makes one feel “life is worth living”; significance refers to making significant contributions transcending the self; coherence means that the “stimuli, events, and one’s life make sense” (p. 7). George and Park (2016) proposed a similar “tripartite view” of meaning of life that has three components. The first component is “comprehension” which has similar meaning with “coherence”; the second component is “purpose” referring to having a valuable goal and clear direction in one’s life; the third component is “mattering” which refers to a feeling that one’s existence in the world is “of significance, importance, and value” ( George and Park, 2016 , p. 206). Steger et al. (2009) proposed that life meaning contains two dimensions, including “presence of life meaning” (i.e., “having” meaning) and “search for life meaning” (i.e., “seeking” of meaning). Regarding “presence of life meaning,” it refers to whether one sees one’s life as important, valuable, with clear direction, purposeful, and meaningful. On the other hand, “seeking” life meaning is a process through which one identifies or works out how one can have a meaningful life. Generally speaking, while a positive relationship was identified between “presence of life meaning” and psychological well-being, the relationship between “search for life meaning” and mental health is more complex. For example, the study of Steger et al. (2008) suggested that the relationships among these dimensions of life meaning may differ across cultures. Furthermore, Ryff (2013 , p. 235) argued that in contrast to “hedonic” wellbeing, meaning of life belongs to the “eudaimonic” approach of wellbeing which involves a “reconstruction process” to “make things interpretable.” While there are differences in these theories of meaning of life, they all highlighted and indicated that meaning of life would contribute to an individual’s positive development and mental health.

With specific reference to young people, the importance of meaning in life is strongly emphasized in youth development models. For example, the Search Institute proposed 20 internal and 20 external developmental assets for the optimal development of adolescents 1 . Under “positive identity,” there is an asset of “sense of purpose” which refers to whether young people perceive their lives as purposeful. In another framework on positive youth development (PYD) attributes, based on reviewing a large amount of PYD programs, Catalano et al. (2004) found 15 PYD attributes underlying successful PYD programs. Among the 15 PYD constructs, spirituality is listed as an attribute shaping effective PYD programs. Spirituality was defined as “relating to, consisting of, or having the nature of spirit; concerned with or affecting the soul; of, from, or relating to God; of or belonging to a church or religion” ( Catalano et al., 2004 , p.105). Furthermore, with reference to the models focusing on the importance of spirituality strengths (e.g., Lerner, 2004 ; Starnino et al., 2012 ), life meaning is defined as “inner strength” which could promote positive well-being and reduce psychosocial adjustment problems in adolescents ( Lin and Shek, 2019 ). As remarked by Krok (2018) , “purpose embedded in the concept of meaning in life appears central to the formation of adolescent well-being as young people come to establish overarching aims” (p. 96).

Meaning in life, anxiety and depression

Regarding the negative relationship between anxiety and meaning in life, there are at least two possible explanations. First, a high level of anxiety may make a person difficult to appreciate meaning in life because anxiety would make a person exhausted and confused. Second, the lack of life meaning is anxiety-provoking, as proposed in logotherapy that existential vacuum leads to “noogenic neurosis.” Empirically, there are studies supporting the negative relationship between anxiety and life meaning. In a study based on 1,538 German participants, Schnell and Krampe (2020) revealed that life meaning was negatively associated with mental distress indexed by anxiety and depression. They also found that life meaning moderated the impact of COVID-19 stress and mental distress. In another study involving 202 Dutch old people, Korte et al. (2012) reported a negative association among life meaning, anxiety and depression, and life meaning served as a mediator between reminiscence and depression. However, although the relationship between life meaning and anxiety is negative when using a unidimensional measure of life meaning, the relationship is complex if we look at different dimensions of meaning in life. For instance, Steger et al. (2009) found that while there was a negative linkage between “presence of life meaning” and anxiety, the relationship between “search for life meaning” and anxiety was positive.

Regarding the relationship between life meaning and depression, studies showed a negative linkage between purpose in life and depression, or life meaning is a predictor of depression (i.e., the direct effect of life meaning on depression). Based on 401 young men, Kleftaras and Psarra (2012) found that higher life meaning was related to lower depression and different dimensions of life meaning were related to different levels of depression. They concluded that “those with higher meaning of life present a better psychological health” (p. 337). Utilizing a large sample based on adult participants, Schaefer et al. (2013) investigated the association between purpose in life and emotional recovery. They identified that higher purpose in life predicted better emotional recovery after demographic variables and initial emotional reactivity were controlled. They reasoned that purpose in life is a factor protecting a person from negative life events through more resilient emotional regulation and emotional provocation.

Clinical studies also showed a negative linkage between life meaning and depression. Based on adult patients, Doolittle and Farrell (2004) found that spiritual involvement, spiritual beliefs and physical health were predictors of depression. Dursun et al. (2022) compared people with general anxiety disorders ( N  = 38) and control participants ( N  = 31) and found that participants with general anxiety disorders showed higher death anxiety and lower presence of life meaning and hardiness; life meaning was also a predictor of death anxiety. Furthermore, the negative linkage between life meaning and depression is also exhibited in adolescents. In a study of 215 university students, Hedayati and Khazaei (2014) showed negative relationships between depression and life meaning (including “presence” and “search for” meaning). Parra (2020) also reported a moderate negative linkage of the meaning of life with depression under the pandemic.

Besides the negative effect of life meaning on depression, other studies showed the protective and moderating effect of meaning in life on depression. In a longitudinal study over 2.5 years involving 909 African Americans, Park et al. (2020) showed that life meaning predicted a reduction in depression and an increase in positive emotions over time, and then they concluded that “meaning in life appears to robustly protect against future depressive symptoms and promote positive affect over time” (p. 3037) and such protective effect was not affected by demographic factors and the related stress experience. Based on two large national samples ( N  = 3,664), Hartanto et al. (2020) examined the relationships among purpose in life, child abuse and depression. Results revealed that purpose in life moderated the impact of emotional abuse in childhood on depression in adulthood. They highlighted the important role of life purpose in “building resilience, coping against adverse life events, and psychological well-being” (p. 473).

Researchers have also identified the moderating effect of life meaning in young people. Based on 204 university students in Slovakia, Halama and Bakosova (2009) showed that the overall sense of life meaning was a moderator of perceived stress with avoidance coping but not with emotional coping. Basu et al. (2022) also reported that meaning-making moderated the impact of traumatic life events experienced and suicidal ideation in 568 undergraduate students. Finally, for a sample of 177 adolescents, Dulaney et al. (2018) found a negative association between life meaning and depression symptoms, and life meaning moderated the impact of stress exposure on depression.

The moderating function of life meaning on depression is also found in the clinical field. With 151 helping professionals, Chan et al. (2021) examined the relationships among self-competence in death work, life meaning, and depressive symptoms. They showed significant correlations among these three measures, and life meaning moderated the association between depressive symptoms and self-competence in death work. In another study involving 49 psychiatric patients, Heisel and Flett (2004) showed that purpose in life had a positive association with satisfaction with life, and a negative association with neuroticism, hopelessness and depression. Besides, purpose in life and life satisfaction explained additional variance in suicidal ideation, and purpose in life moderated the impact of depression on suicidal ideation.

Meaning in life also plays an important role under adverse environmental conditions. Based on data collected from 12,243 subjects from 30 countries, Eisenbeck et al. (2021) showed that meaning-centered coping was negatively related to stress and psychological morbidity indexed by anxiety and depression symptoms during the pandemic; meaning-making coping also moderated the impact of risk factors on psychological morbidity, including depression. They concluded that life meaning plays a “critical role of meaning-centered coping in attenuating the detrimental effects of the COVID-19 pandemic on psychological distress, especially on depressive symptoms” (p. 9).

Nevertheless, some studies did not support the protective effects of life meaning. Hedberg et al. (2010) collected data from 189 old persons. While the depressive elderly scored lower on purpose in life, purpose did not predict depression 5 years later. Based on 90 patients, Kim et al. (2019) revealed that while life purpose mediated the impact of depression on quality of life, no moderating effect was found. Also, there are studies founding that the association between life meaning and mental well-being depends on the aspects of meaning in life. With 753 participants, Yek et al. (2017) found that presence of meaning was negatively linked with health anxiety while meaning search functioned oppositely, and further, higher meaning search and higher meaning presence reduced health anxiety than higher search and lower presence of meaning.

There are several gaps in the scientific literature on the relationship between meaning in life and depression in adolescents. First, although life meaning is an important developmental domain in adolescents, there is insufficient research ( Zhu et al., 2022 ). Second, in their review of constructs of PYD used in effective programs on PYD, Catalano et al. (2004) found that only very few effective programs incorporated spirituality in the interventions. Third, most of the studies in this field are Western studies. There are two arguments for why we need more Chinese studies. The first reason is that because of the huge number of Chinese adolescents, we need more studies to ascertain the generalizability of Western theories. The second reason is that as Confucian thoughts place a strong emphasis on life meaning, it is theoretically interesting to understand the linkage between life meaning and well-being in Chinese adolescents. Fourth, in the related studies in the field, the sample size was generally small, hence limiting the generalizability of the related results. Fifth, longitudinal studies are few in the field, hence limiting our ability to understand the causal linkage between life meaning and psychological well-being. Sixth, there are few studies examining life meaning and psychological well-being within the context of COVID-19 ( Zhu et al., 2022 ). This area is important because COVID-19 is anxiety-provoking, particularly because of changing teaching and learning modes ( Shek et al., 2022a , b ). As such, positive psychological attributes such as life meaning would have important functions in adjustment during the pandemic. Finally, we need more studies to clarify the moderating effects of life meaning in the context of the anxiety-depression relationship in Chinese young people ( Shek, 2021 ).

The present study

As there are more theories and research findings supporting the hypothesis that anxiety is an antecedent of depression, we adopted this perspective in this study. Specifically, we asked several research questions:

Research Question 1: What is the concurrent and longitudinal relationships between anxiety and depression? We predicted that anxiety would positively predict depression (Hypothesis 1).

Research Question 2: What is the relationship between anxiety and change in depression over time? Based on the literature, we expected that Wave 1 anxiety would positively predict change in depression over time (Hypothesis 2).

Research Question 3: Is life meaning concurrently and longitudinally related to depression? We expected that a negative relationship would exist between life meaning and depression (Hypothesis 3).

Research Question 4: Is life meaning related to change in depression over time? Based on the previous studies, we expected that Wave 1 life meaning would be a negative predictor of change in depression over time (Hypothesis 4).

Research Question 5: Does meaning in life moderate the influence of anxiety on depression? We expected that there would be a moderating function of life meaning on the association between anxiety and depression (Hypothesis 5).

Materials and methods

Participants and procedure.

The participants of the present study were 4,981 students coming from five schools (two primary schools, one secondary school, and two schools enrolling both primary and secondary students) in Chengdu, mainland China. The schools agreed to join the study and formal consent was collected from the schools, students, and parents. The study adopted a longitudinal design in which the participants responded to a questionnaire at two time points. For data collection at the first time point (i.e., Wave 1: from December 2019 to January 2020 before school lockdown because of the outbreak of COVID-19), the students from the five schools responded to a questionnaire in the paper-and-pencil format in school classrooms. The study purpose and confidentiality of data and personal information were made clear to the students before they responded to the questionnaire. In total, 5,690 students responded to the questionnaire at the first wave. For the second wave (from June to July 2020 after the resumption of school), the students were invited to do the questionnaire again ( N  = 4,981). In total, 4,981 participants were matched for both waves. The mean age of the participants at Wave 1 was 13.15 ± 1.32 years old, with 48.5% were female.

Anxiety was examined through the “Screen for Child Anxiety Related Emotional Disorders (SCARED).” The SCARED assesses children’s anxiety disorders ( Birmaher et al., 1999 ; Muris, 2002 ). It includes 41 items under five dimensions: “Panic/Somatic,” “Generalized Anxiety,” “Separation Anxiety,” “Social Phobia,” and “School Phobia.” Being validated in adolescent populations across cultures, the scale demonstrated good reliability and stable factor structure ( Hale et al., 2005 ; Su et al., 2008 ; Crocetti et al., 2009 ). Through a three-point scale, the participants evaluated each item to indicate the level of their experiencing the specified anxiety symptom (“0” = “Never,” “1” = “Sometimes,” and “2” = “Often”). A higher score (i.e., the sum of all item scores) refers to a higher level of anxiety.

We used “Center for Epidemiologic Studies Depression Scale (CES-D)” to measure depression ( Radloff, 1977 ). The CES-D includes 20 items representing 20 depressive symptoms. Each item describes a feeling or behavior related to different depressive symptoms. The participants needed to select the frequency of their having the feeling or engaging in the behavior in the past week through a scale with four points (“0” = “rarely or none of the time (<1 day),” “1” = “some or little of the time (1–2 days),” “2” = “moderately or much of the time (3–4 days),” and “3” = “most or almost all the time (5–7 days)”). The CES-D was widely used and validated across different age groups ( Roberts et al., 1990 ; Radloff, 1991 ). Previous studies support the factorial validity of the Chinese CES-D ( Dou et al., 2021 ; Zhu et al., 2021 ). The scale score was the sum of all items scores, with scores of four items measuring “positive affect” that were reversely coded. Higher depression was indicated by higher composite score.

Life Meaning

Life meaning was measured through “Spirituality” (SP) dimension of the “Chinese Positive Youth Development Scale (CPYDS).” Referring to positive youth development (PYD) indicators identified by Catalano et al. (2004) , the CPYDS was developed by assessing 15 PYD attributes in Chinese youth ( Shek et al., 2007 ). The measure showed desirable internal consistency and validity in different validation studies ( Shek and Ma, 2010 ; Shek and Chai, 2020 ). The SP subscale contains seven items measuring adolescents’ meaning of life, with each item being evaluated through a seven-point scale. The composite score is generated by averaging all item scores; the higher the score is, the higher the life meaning is.

Data analyses

Descriptive analyses were performed which include mean scores and standard deviation (SD). Besides, mean inter-item correlation and Cronbach’s α for all major variables were also computed. We also computed correlations between different variables. To answer Research Question 1 and Research Question 3, several hierarchical multiple regression analyses were performed to test the predicting effects of anxiety (i.e., SCARED) and life meaning (i.e., SP) on depression (i.e., CES-D) both at each wave and from the first wave to the second wave, with effects of demographic variables (i.e., age and gender) being controlled. To answer Research Question 2 and Question 4, hierarchical multiple regressions were also computed to test the predicting effect of SCARED and SP at Wave 1 on CES-D at Wave 2 with the effects of CES-D at Wave 1 being controlled. Finally, to examine whether SP moderated the predicting effect of SCARED on CES-D (i.e., Research Question 5), hierarchical multiple regression was conducted. In Step 1, we controlled age and gender effects. In Step 2, SCARED at the first wave and SP at the second wave were put in the analyses. In Step 3, we included the interaction between SCARED at the first wave and SP at the second wave. Adopting 2,000 re-samplings, we conducted bootstrapping to examine bias-corrected (BC) 95% confidence intervals (CIs) for the regression coefficients for all the hierarchical multiple regression analyses.

The descriptive statistics of major variables are shown in Table 1 . The Cronbach’s alpha values for SCARED, SP, and CES-D in both waves ranged from 0.89 to 0.96, indicating excellent internal consistency. Table 2 shows correlations between different variables involved in the study in the expected directions. As both age at the first wave and gender had positive correlation with CES-D at both waves ( r  = 0.04–0.12, ps  < 0.01). their effects were controlled in hierarchical multiple regression on the effects of SCARED and SP on CES-D.

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Table 1 . Mean, standard deviation (SD), Cronbach’s alpha, and mean inter-item correlation of different variables.

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Table 2 . Correlations between different variables.

Results of the hierarchical multiple regression in Table 3 showed that SCARED significantly and positively predicted CES-D at each wave (for Wave 1 and 2, B  = 0.43 and 0.45, 95% bootstrap confidence intervals (CIs) = [0.41, 0.45] and [0.43, 0.47], β  = 0.61 and 0.62, ps  < 0.001. Cohen’s f 2  = 0.570 and 0.594, respectively). Longitudinally, there was significant positive predicting effect of SCARED at the first wave on CES-D at the second wave ( B  = 0.32, 95% bootstrap confidence intervals (CIs) = [0.29, 0.34], β  = 0.42, p  < 0.001, Cohen’s f 2  = 0.213; Table 4 ). The findings give support to Hypothesis 1. In addition, SCARED at the first wave also significantly and positively predicted change in CES-D over time ( B  = 0.11, 95% bootstrap confidence intervals (CIs) = [0.08, 0.14], β  = 0.15, p  < 0.001, Cohen’s f 2  = 0.019). Table 4 shows the details of the results. Therefore, Hypothesis 2 was also supported.

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Table 3 . Cross sectional predicting effects of anxiety (SCARED) on depression (CES-D).

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Table 4 . Longitudinal predicting effects of anxiety (SCARED) on depression (CES-D) and its change.

In Table 5 , results showed that SP significantly and negatively predicted CES-D (for Wave 1 and Wave 2, B  = −5.12 and −5.04, 95% bootstrap confidence intervals (CIs) = [−5.37, −4.86] and [−5.26, −4.82], β  = −0.62 and −0.64, ps  < 0.001. Cohen’s f 2  = 0.593 and 0.680, respectively). SP at the first wave also negatively predicted CES-D at the second wave ( B  = −4.07, 95% bootstrap confidence intervals (CIs) = [−4.34, −3.79], β  = −0.46, p  < 0.001, Cohen’s f 2  = 0.266; Table 6 ). This provides support for Hypothesis 3. Besides, after controlling the effect of first-wave CES-D, first-wave SP negatively predicted second-wave CES-D ( B  = −1.77, 95% bootstrap confidence intervals (CIs) = [−2.07, −1.47], β  = −0.20, p  < 0.001, Cohen’s f 2  = 0.037). This provided support for Hypothesis 4.

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Table 5 . Cross sectional predicting effects of life meaning (SP) on depression (CES-D).

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Table 6 . Longitudinal predicting effects of life meaning (SP) on depression (CES-D) and its change.

Another hierarchical regression was conducted to test the moderating effect of SP on the predicting effect of SCARED on CES-D ( Table 7 ). In the first step, the effects of demographic variables were controlled. In the second step, predictors of SCARED at Wave 1 and SP at Wave 2 were put in the regression model. Results showed significant main effects of the first-wave SCARED ( B  = 0.16, 95% bootstrap confidence intervals (CIs) = [0.14, 0.18], β  = 0.21, p  < 0.001, Cohen’s f 2  = 0.067) and the second-wave SP ( B  = −4.42, BC 95% CI = [−4.66, −4.19], β  = −0.56, p  < 0.001, Cohen’s f 2  = 0.478) on the second-wave CES-D. In Step 3, the interaction between the first-wave SCARED and the second-wave SP was put in the analyses. The interaction between the first-wave SCARED and the second-wave SP had a significant predicting effect on the second-wave CES-D ( B  = −0.71, 95% bootstrap confidence intervals (CIs) = [−0.96, −0.46], β  = −0.08, p  < 0.001, Cohen’s f 2  = 0.010). This suggests the predicting effect of SCARED on CES-D was moderated by SP, hence supporting Hypothesis 5. The analyses of the simple slopes ( Figure 1 ) showed that the predicting effect of the first-wave SCARED on the second-wave CES-D was more positive for participants with lower SP (−1 SD; β  = 0.36, p  < 0.001) than the participants with higher SP (+1 SD; β  = 0.22, p  < 0.001) at the first wave. The findings also provided support for Hypothesis 5.

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Table 7 . Hierarchical multiple regression analyses for the predicting effects of anxiety (SCARED) at Wave 1 and life meaning (SP) at Wave 2 on depression (CES-D) at Wave 2.

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Figure 1 . Moderating effect of SP at Wave 2 on the relationship between SCARED at Wave 1 and CES-D at Wave 2.

The study has several advances concerning the existing research gaps. First, as research on meaning in life has predominantly been done in adult samples, we recruited adolescent samples for the present study. Second, in view of the scarcity of Chinese studies on meaning in life, we recruited Chinese students for the present study. The findings can give some insight into the applicability of Western theories and research findings in the Chinese context. Third, in contrast to the common practice of recruiting small samples, we employed a large sample in this study. Fourth, utilizing two waves of data, we can look at the concurrent as well as longitudinal relationships between anxiety (and life meaning) and depression. Fifth, we examined the relationship among anxiety, life meaning and depression within the context of COVID-19 pandemic which is pioneered in the field. Sixth, we tested the moderating function of life meaning in the predictive relation between anxiety and depression.

Hypothesis 1 was supported with results showing that anxiety concurrently and longitudinally predicted depression in Chinese adolescents in the context of the pandemic. Also, supporting Hypothesis 2, anxiety predicted the change in depression from the first to the second wave. The findings are in line with the existing empirical results suggesting that anxiety could be an antecedent of depression (e.g., Cole et al., 1998 ; Chaplin et al., 2009 ; Price et al., 2016 ). For instance, a study based on two-wave data showed that anxiety symptoms predicted depressive symptoms in middle school students 1 year later ( Chaplin et al., 2009 ). Another six-wave longitudinal study based on both student-and parent-report data identified that early-time anxiety predicted later-time change in depression in primary school students ( Cole et al., 1998 ). The results provide further empirical support to the theoretical view that anxiety is a precursor or risk factor for depression ( Mathew et al., 2011 ). Cummings et al. (2014) also explained that adolescents with a constitutional predisposition to anxiety tended to develop “anxiety-related impairment” if their anxiety remains untreated, and the “anxiety-related impairment” would be a risk factor for depressive symptoms.

Supporting Hypothesis 3, this study showed that meaning in life both concurrently and longitudinally negatively predicted depression. The results are in line with the existing empirical studies suggesting the negative linkage of life meaning with depression based on the general population and clinical samples ( Doolittle and Farrell, 2004 ; Kleftaras and Psarra, 2012 ; Schaefer et al., 2013 ). Also, supporting Hypothesis 4, the study showed that life meaning negatively predicted change in depression. The findings extend the existing literature showing that life meaning is a unique negative predictor of depressive symptoms in Chinese youth during the pandemic. This highlights the important role of life meaning in decreasing the risk for depressive symptoms. In addition, the results provide support to Frankl’s theory of life meaning that individuals are not motivated by “will to pleasure” but are driven by a meaning in life ( Frankl, 1959 ; Shek, 1992 ).

Findings of the study also support Hypothesis 5, showing that meaning in life moderated the predictive effect of anxiety on depression. This is in line with the existing literature that persons having higher meaning in life would develop lower depression compared with persons with lower meaning in life when confronting the same level of negative or stressful life events ( Hartanto et al., 2020 ; Park et al., 2020 ). However, many of the existing studies were based on adult or general population samples, there were few studies on youth or adolescents. Also, there were few studies on Chinese adolescents. Whether life meaning functioned as a protector in Chinese youth against mental health problems under stressful environments was not very clear ( Zhang et al., 2018 ). This study provides evidence of the important protective function of life meaning in Chinese culture. Besides, the results shed light on the unique role of life meaning in maintaining mental health under the COVID-19 pandemic, which posed significant stress to individuals, particularly adolescents who are more vulnerable to stress. There are consistent reports of an increased level of mental health problems such as depression in adolescents during COVID-19 ( Miranda et al., 2020 ; Hawes et al., 2021 ). The present research echoes the claim that life meaning could be an important buffer against mental health problems.

The present study has several theoretical implications. First, it offers further empirical support for the role of anxiety being a precursor or antecedent of depressive symptoms ( Cohen et al., 2018 ). Particularly, it provides support to the theoretical proposition that anxiety could be a causal factor for depression because its impairment would lead to comorbid or more severe mental health problems ( Cummings et al., 2014 ). Second, the study provides support to the protective function of life meaning in the mental health of adolescents under stressful situations. This further confirms and highlights the important role of life meaning in positive youth development models in literature (e.g., Catalano et al., 2004 ; Benson, 2007 ).

The study also has several practical implications. First, as anxiety could be a precursor of depression, it is highly important to assess and treat anxiety in young people to prevent the later onset of depressive symptoms. Second, as life meaning plays important role in reducing depression and moderating the predicting effect of anxiety on depression, it is also key to promote the life meaning of adolescents through different educational or intervention programs. Third, the present study also indicates the importance of implementing PYD programs in adolescents during the pandemic period to promote their mental health. Unfortunately, there are few related studies under the pandemic ( Shek, 2021 ; Shek et al., in press ).

Several limitations of the study should be noted. First, as the study was only based on data collected from two waves, the longitudinal predicting role of anxiety in depression should be further tested with data collected from more waves. Second, the participants of the study were recruited from five schools. While the schools were randomly selected, further studies should be performed based on participants from more schools to verify the results and increase the generalizability of the results. Third, we used a unidimensional measure to assess life meaning. As life meaning may contain multiple dimensions, future studies should test the moderating role of life meaning based on the multidimensional measure. Despite of these limitations, the study provides support to the risk role of anxiety and the protective role of life meaning in depression in Chinese adolescents, which shed light on the theoretical understanding of the relationship between these mental health factors and on the prevention in mental health among adolescents in China during the pandemic.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving human participants were reviewed and approved by the Ethics Committee of Sichuan University. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.

Author contributions

DS designed the research project and contributed to all the steps of the work. WC conducted data analyses and contributed to the first draft, and revised the manuscript based on the comments and editing provided by DS. LT contributed to the drafts at different stages and proof-read the paper. All authors contributed to the article and approved the submitted version.

This work is financially supported by Wofoo Foundation and the Research Matching Fund of the Research Grants Council (R.54.CC.83Y7).

Acknowledgments

We would like to acknowledge the financial support of Wofoo Foundation and the Research Grants Council for implementing this study and the writing of this article.

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.

1. ^ https://searchinstitute.org/

Alloy, L. B., Kelly, K. A., Mineka, S., and Clements, C. M. (1990). “Comorbidity of anxiety and depressive disorders: a helplessness-hopelessness perspective,” in Comorbidity of Mood and Anxiety Disorders . eds. J. D. Maser and C. R. Cloninger (Washington, DC: American Psychiatric Association), 499–543.

Google Scholar

Almeida, O. P., Draper, B., Pirkis, J., Snowdon, J., Lautenschlager, N. T., Byrne, G., et al. (2012). Anxiety, depression, and comorbid anxiety and depression: risk factors and outcome over two years. Int. Psychogeriatr. 24, 1622–1632. doi: 10.1017/S104161021200107X

PubMed Abstract | CrossRef Full Text | Google Scholar

Aune, T., and Stiles, T. C. (2009). The effects of depression and stressful life events on the development and maintenance of syndromal social anxiety: sex and age differences. J. Clin. Child Adolesc. Psychol. 38, 501–512. doi: 10.1080/15374410902976304

Axelson, D. A., and Birmaher, B. (2001). Relation between anxiety and depressive disorders in childhood and adolescence. Depress. Anxiety 14, 67–78. doi: 10.1002/da.1048

CrossRef Full Text | Google Scholar

Bair, M. J., Poleshuck, E. L., Wu, J., Krebs, E. K., Damush, T. M., Tu, W., et al. (2013). Anxiety but not social stressors predict 12-month depression and pain severity. Clin. J. Pain 29, 95–101. doi: 10.1097/AJP.0b013e3182652ee9

Barlow, D. H. (2000). Unraveling the mysteries of anxiety and its disorders from the perspective of emotion theory. Am. Psychol. 55, 1247–1263. doi: 10.1037/0003-066X.55.11.1247

Basu, N., Schuler, K. R., Marie, L., Taylor, S. E., Fadoir, N. A., and Smith, P. N. (2022). Moderating effect of meanings-made on the relationship between exposure to potentially traumatic life events and suicidal ideation. Illn. Crisis Loss 30, 192–208. doi: 10.1177/1054137319898333

Beck, A. T., and Clark, D. A. (1988). Anxiety and depression: an information processing perspective. Anxiety Res. 1, 23–36. doi: 10.1080/10615808808248218

Beesdo, K., Bittner, A., Pine, D. S., Stein, M. B., Höfler, M., Lieb, R., et al. (2007). Incidence of social anxiety disorder and the consistent risk for secondary depression in the first three decades of life. Arch. Gen. Psychiatry 64, 903–912. doi: 10.1001/archpsyc.64.8.903

Benson, P. L. (2007). “Developmental assets: an overview of theory, research, and practice,” in Approaches to Positive Youth Development . eds. R. K. Silbereisen and R. M. Lerner (London, United Kingdom: SAGE Publications Ltd)

Birmaher, B., Brent, D. A., Chiappetta, L., Bridge, J., Monga, S., and Baugher, M. (1999). Psychometric properties of the screen for child anxiety related emotional disorders (SCARED): a replication study. J. Am. Acad. Child Adolesc. Psychiatry 38, 1230–1236. doi: 10.1097/00004583-199910000-00011

Bittner, A., Egger, H. L., Erkanli, A., Jane Costello, E., Foley, D. L., and Angold, A. (2007). What do childhood anxiety disorders predict? J. Child Psychol. Psychiatry 48, 1174–1183. doi: 10.1111/j.1469-7610.2007.01812.x

Blumberg, S. H., and Izard, C. E. (1986). Discriminating patterns of emotions in 10-and 11-yr-old children's anxiety and depression. J. Pers. Soc. Psychol. 51, 852–857. doi: 10.1037/0022-3514.51.4.852

Brady, E. U., and Kendall, P. C. (1992). Comorbidity of anxiety and depression in children and adolescents. Psychol. Bull. 111, 244–255. doi: 10.1037/0033-2909.111.2.244

Catalano, R. F., Berglund, M. L., Ryan, J. A. M., Lonczak, H. S., and Hawkins, J. D. (2004). Positive youth development in the United States: research findings on evaluations of positive youth development programs. Ann. Am. Acad. Pol. Soc. Sci. 591, 98–124. doi: 10.1177/0002716203260102

Chan, W. C. H., Tin, A. F., and Wong, A. L. Y. (2021). Moderating effects of meaning in life on the relationship between depression and self-competence in death work among helping professionals. Death Stud. 45, 594–602. doi: 10.1080/07481187.2019.1671541

Chaplin, T. M., Gillham, J. E., and Seligman, M. E. P. (2009). Gender, anxiety, and depressive symptoms: a longitudinal study of early adolescents. J. Early Adolesc. 29, 307–327. doi: 10.1177/0272431608320125

Choi, E. P. H., Hui, B. P. H., and Wan, E. Y. F. (2020). Depression and anxiety in Hong Kong during COVID-19. Int. J. Environ. Res. Public Health 17:3740. doi: 10.3390/ijerph17103740

Clark, L. A., and Watson, D. (1991). Tripartite model of anxiety and depression: psychometric evidence and taxonomic implications. J. Abnorm. Psychol. 100, 316–336. doi: 10.1037/0021-843X.100.3.316

Coelho, H. F., Murray, L., Royal-Lawson, M., and Cooper, P. J. (2011). Antenatal anxiety disorder as a predictor of postnatal depression: a longitudinal study. J. Affect. Disord. 129, 348–353. doi: 10.1016/j.jad.2010.08.002

Cohen, J. R., Andrews, A. R., Davis, M. M., and Rudolph, K. D. (2018). Anxiety and depression during childhood and adolescence: testing theoretical models of continuity and discontinuity. J. Abnorm. Child Psychol. 46, 1295–1308. doi: 10.1007/s10802-017-0370-x

Cole, D. A., Peeke, L. G., Martin, J. M., Truglio, R., and Seroczynski, A. D. (1998). A longitudinal look at the relation between depression and anxiety in children and adolescents. J. Consult. Clin. Psychol. 66, 451–460. doi: 10.1037/0022-006X.66.3.451

Crocetti, E., Hale, W. W., Fermani, A., Raaijmakers, Q., and Meeus, W. (2009). Psychometric properties of the screen for child anxiety related emotional disorders (SCARED) in the general Italian adolescent population: a validation and a comparison between Italy and the Netherlands. J. Anxiety Disord. 23, 824–829. doi: 10.1016/j.janxdis.2009.04.003

Crumbaugh, J. C., and Maholick, L. T. (1964). An experimental study in existentialism: the psychometric approach to Frankl's concept of noogenic neurosis. J. Clin. Psychol. 20, 200–207. doi: 10.1002/1097-4679(196404)20:2<200::AID-JCLP2270200203>3.0.CO;2-U

Cummings, C. M., Caporino, N. E., and Kendall, P. C. (2014). Comorbidity of anxiety and depression in children and adolescents: 20 years after. Psychol. Bull. 140, 816–845. doi: 10.1037/a0034733

Cyranowski, J. M., Frank, E., Young, E., and Shear, M. K. (2000). Adolescent onset of the gender difference in lifetime rates of major depression: a theoretical model. Arch. Gen. Psychiatry 57, 21–27. doi: 10.1001/archpsyc.57.1.21

Doolittle, B. R., and Farrell, M. (2004). The association between spirituality and depression in an urban clinic. Prim Care Companion J Clin Psychlatry 06, 114–118. doi: 10.4088/PCC.v06n0302

Dou, D., Shek, D. T. L., Zhu, X., and Zhao, L. (2021). Dimensionality of the Chinese CES-D: is it stable across gender, time, and samples? Int. J. Environ. Res. Public Health 18:11818. doi: 10.3390/ijerph182211818

Dulaney, E. S., Graupmann, V., Grant, K. E., Adam, E. K., and Chen, E. (2018). Taking on the stress-depression link: meaning as a resource in adolescence. J. Adolesc. 65, 39–49. doi: 10.1016/j.adolescence.2018.02.011

Dursun, P., Alyagut, P., and Yılmaz, I. (2022). Meaning in life, psychological hardiness and death anxiety: individuals with or without generalized anxiety disorder (GAD). Curr. Psychol. 41, 3299–3317. doi: 10.1007/s12144-021-02695-3

Eisenbeck, N., Carreno, D. F., and Pérez-Escobar, J. A. (2021). Meaning-centered coping in the era of COVID-19: direct and moderating effects on depression, anxiety, and stress. Front. Psychol. 12:648383. doi: 10.3389/fpsyg.2021.648383

Frankl, V.E. (1959). Man's Search for Meaning: An Introduction to Logotherapy . Boston, MA: Beacon Press.

George, L. S., and Park, C. L. (2016). Meaning in life as comprehension, purpose, and mattering: toward integration and new research questions. Rev. Gen. Psychol. 20, 205–220. doi: 10.1037/gpr0000077

Halama, P., and Bakosova, K. (2009). Meaning in life as a moderator of the relationship between perceived stress and coping. Stud. Psychol. 51, 143–148.

Hale, W. W., Raaijmakers, Q., Muris, P., and Meeus, W. (2005). Psychometric properties of the screen for child anxiety related emotional disorders (SCARED) in the general adolescent population. J. Am. Acad. Child Adolesc. Psychiatry 44, 283–290. doi: 10.1097/00004583-200503000-00013

Hartanto, A., Yong, J. C., Lee, S. T. H., Ng, W. Q., and Tong, E. M. W. (2020). Putting adversity in perspective: purpose in life moderates the link between childhood emotional abuse and neglect and adulthood depressive symptoms. J. Ment. Health 29, 473–482. doi: 10.1080/09638237.2020.1714005

Hawes, M. T., Szenczy, A. K., Klein, D. N., Hajcak, G., and Nelson, B. D. (2021). Increases in depression and anxiety symptoms in adolescents and young adults during the COVID-19 pandemic. Psychol. Med. 1-9, 1–9. doi: 10.1017/S0033291720005358

Hedayati, M., and Khazaei, M. (2014). An investigation of the relationship between depression, meaning in life and adult hope. Procedia. Soc. Behav. Sci. 114, 598–601. doi: 10.1016/j.sbspro.2013.12.753

Hedberg, P., Gustafson, Y., Alèx, L., and Brulin, C. (2010). Depression in relation to purpose in life among a very old population: a five-year follow-up study. Aging Ment. Health 14, 757–763. doi: 10.1080/13607861003713216

Heintzelman, S. J. (2018). “Eudaimonia in the contemporary science of subjective well-being: psychological well-being, self-determination, and meaning in life,” in Handbook of Well-Being . eds. E. Diener, S. Oishi, and L. Tay (Salt Lake City, UT: DEF Publishers), 1–14.

Heisel, M. J., and Flett, G. L. (2004). Purpose in life, satisfaction with life, and suicide ideation in a clinical sample. J. Psychopathol. Behav. Assess. 26, 127–135. doi: 10.1023/B:JOBA.0000013660.22413.e0

Higgins, E. T., Klein, R., and Strauman, T. (1985). Self-concept discrepancy theory: a psychological model for distinguishing among different aspects of depression and anxiety. Soc. Cogn. 3, 51–76. doi: 10.1521/soco.1985.3.1.51

Jacobson, N. C., and Newman, M. G. (2014). Avoidance mediates the relationship between anxiety and depression over a decade later. J. Anxiety Disord. 28, 437–445. doi: 10.1016/j.janxdis.2014.03.007

Jacobson, N. C., and Newman, M. G. (2016). Perceptions of close and group relatioships mediate the relationship between anxiety and depression over a decade later. Depress. Anxiety 33, 66–74. doi: 10.1002/da.22402

Jacobson, N. C., and Newman, M. G. (2017). Anxiety and depression as bidirectional risk factors for one another: a meta-analysis of longitudinal studies. Psychol. Bull. 143, 1155–1200. doi: 10.1037/bul0000111

Kim, J.-Y., Lee, Y. W., Kim, H.-S., and Lee, E.-H. (2019). The mediating and moderating effects of meaning in life on the relationship between depression and quality of life in patients with dysphagia. J. Clin. Nurs. 28, 2782–2789. doi: 10.1111/jocn.14907

Kim-Cohen, J., Caspi, A., Moffitt, T. E., Harrington, H., Milne, B. J., and Poulton, R. (2003). Prior juvenile diagnoses in adults with mental disorder: developmental follow-back of a prospective-longitudinal cohort. Arch. Gen. Psychiatry 60, 709–717. doi: 10.1001/archpsyc.60.7.709

Kleftaras, G., and Psarra, E. (2012). Meaning in life, psychological well-being and depressive symptomatology: a comparative study. Psychology 03, 337–345. doi: 10.4236/psych.2012.34048

Korte, J., Cappeliez, P., Bohlmeijer, E. T., and Westerhof, G. J. (2012). Meaning in life and mastery mediate the relationship of negative reminiscence with psychological distress among older adults with mild to moderate depressive symptoms. Eur. J. Ageing 9, 343–351. doi: 10.1007/s10433-012-0239-3

Krok, D. (2018). When is meaning in life most beneficial to young people? Styles of meaning in life and well-being among late adolescents. J. Adult Dev. 25, 96–106. doi: 10.1007/s10804-017-9280-y

Lerner, R.M. (2004). Liberty: Thriving and Civic Engagement Among America's Youth . Thousand Oaks, CA: SAGE Publications.

Lin, L., and Shek, D. T. L. (2019). The influence of meaning in life on adolescents’ hedonic well-being and risk behaviour: implications for social work. Br. J. Soc. Work 49, 5–24. doi: 10.1093/bjsw/bcy029

Mathew, A. R., Pettit, J. W., Lewinsohn, P. M., Seeley, J. R., and Roberts, R. E. (2011). Co-morbidity between major depressive disorder and anxiety disorders: shared etiology or direct causation? Psychol. Med. 41, 2023–2034. doi: 10.1017/S0033291711000407

Miranda, D. M. D., Athanasio, B. D. S., Oliveira, A. C. S., and Simoes-e-Silva, A. C. (2020). How is COVID-19 pandemic impacting mental health of children and adolescents? Int. J. Disaster Risk Reduct. 51:101845. doi: 10.1016/j.ijdrr.2020.101845

Moffitt, T. E., Harrington, H., Caspi, A., Kim-Cohen, J., Goldberg, D., Gregory, A. M., et al. (2007). Depression and generalized anxiety disorder: cumulative and sequential comorbidity in a birth cohort followed prospectively to age 32 years. Arch. Gen. Psychiatry 64, 651–660. doi: 10.1001/archpsyc.64.6.651

Muris, P. (2002). Relationships between self-efficacy and symptoms of anxiety disorders and depression in a normal adolescent sample. Personal. Individ. Differ. 32, 337–348. doi: 10.1016/S0191-8869(01)00027-7

Neale, M. C., and Kendler, K. S. (1995). Models of comorbidity for multifactorial disorders. Am. J. Hum. Genet. 57, 935–953.

PubMed Abstract | Google Scholar

Olino, T. M., Klein, D. N., Lewinsohn, P. M., Rohde, P., and Seeley, J. R. (2010). Latent trajectory classes of depressive and anxiety disorders from adolescence to adulthood: descriptions of classes and associations with risk factors. Compr. Psychiatry 51, 224–235. doi: 10.1016/j.comppsych.2009.07.002

Park, C. L., Knott, C. L., Williams, R. M., Clark, E. M., Williams, B. R., and Schulz, E. (2020). Meaning in life predicts decreased depressive symptoms and increased positive affect over time but does not buffer stress effects in a national sample of African-Americans. J. Happiness Stud. 21, 3037–3049. doi: 10.1007/s10902-019-00212-9

Parker, G., Wilhelm, K., Mitchell, P., Austin, M.-P., Roussos, J., and Gladstone, G. (1999). The influence of anxiety as a risk to early onset major depression. J. Affect. Disord. 52, 11–17. doi: 10.1016/S0165-0327(98)00084-6

Parra, M. R. (2020). Depression and the meaning of life in university students in times of pandemic. Int. J. Educ. Psychol. 9, 223–242. doi: 10.17583/ijep.2020.6784

Pine, D. S., Cohen, P., Gurley, D., Brook, J., and Ma, Y. (1998). The risk for early-adulthood anxiety and depressive disorders in adolescents with anxiety and depressive disorders. Arch. Gen. Psychiatry 55, 56–64. doi: 10.1001/archpsyc.55.1.56

Price, R. B., Rosen, D., Siegle, G. J., Ladouceur, C. D., Tang, K., Allen, K. B., et al. (2016). From anxious youth to depressed adolescents: prospective prediction of 2-year depression symptoms via attentional bias measures. J. Abnorm. Psychol. 125, 267–278. doi: 10.1037/abn0000127

Radloff, L. S. (1977). The CES-D scale: a self-report depression scale for research in the general population. Appl. Psychol. Meas. 1, 385–401. doi: 10.1177/014662167700100306

Radloff, L. S. (1991). The use of the center for epidemiologic studies depression scale in adolescents and young adults. J. Youth Adolesc. 20, 149–166. doi: 10.1007/BF01537606

Rallis, S., Skouteris, H., McCabe, M., and Milgrom, J. (2014). A prospective examination of depression, anxiety and stress throughout pregnancy. Women Birth 27, e36–e42. doi: 10.1016/j.wombi.2014.08.002

Ranney, R. M., Behar, E., and Zinsser, K. M. (2021). Gender as a moderator of the relationship between parental anxiety and adolescent anxiety and depression. J. Child Fam. Stud. 30, 1247–1260. doi: 10.1007/s10826-021-01931-5

Roberts, R. E., Andrews, J. A., Lewinsohn, P. M., and Hops, H. (1990). Assessment of depression in adolescents using the center for epidemiologic studies depression scale. Psychol. Assess. J. Consult. Clin. Psychol. 2, 122–128. doi: 10.1037/1040-3590.2.2.122

Ryff, C. D. (2013). “Existential well-being and health,” in The Human Quest for Meaning . ed. P. T. P. Wong (New York, NY: Routledge), 279–294.

Sandi, C., and Richter-Levin, G. (2009). From high anxiety trait to depression: a neurocognitive hypothesis. Trends Neurosci. 32, 312–320. doi: 10.1016/j.tins.2009.02.004

Sartorius, N., Üstün, T. B., Lecrubier, Y., and Wittchen, H.-U. (1996). Depression comorbid with anxiety: results from the WHO study on psychological disorders in primary health care. Br. J. Psychiatry 168, 38–43. doi: 10.1192/S0007125000298395

Schaefer, S. M., Morozink Boylan, J., van Reekum, C. M., Lapate, R. C., Norris, C. J., Ryff, C. D., et al. (2013). Purpose in life predicts better emotional recovery from negative stimuli. PLoS One 8:e80329. doi: 10.1371/journal.pone.0080329

Schiffer, A. A., Pedersen, S. S., Broers, H., Widdershoven, J. W., and Denollet, J. (2008). Type-D personality but not depression predicts severity of anxiety in heart failure patients at 1-year follow-up. J. Affect. Disord. 106, 73–81. doi: 10.1016/j.jad.2007.05.021

Schnell, T., and Krampe, H. (2020). Meaning in life and self-control buffer stress in times of COVID-19: moderating and mediating effects with regard to mental distress. Front. Psyciatry 11:582352. doi: 10.3389/fpsyt.2020.582352

Seligman, L. D., and Ollendick, T. H. (1998). Comorbidity of anxiety and depression in children and adolescents: an integrative review. Clin. Child. Fam. Psychol. Rev. 1, 125–144. doi: 10.1023/A:1021887712873

Shek, D. T. L. (1992). Meaning in life and psychological wellbeing: an empirical study using the Chinese version of the purpose in life questionnaire. J. Genet. Psychol. 153, 185–200. doi: 10.1080/00221325.1992.10753712

Shek, D. T. L. (2021). COVID-19 and quality of life: twelve reflections. Appl. Res. Qual. Life 16, 1–11. doi: 10.1007/s11482-020-09898-z

Shek, D. T. L., and Chai, W. (2020). The impact of positive youth development attributes and life satisfaction on academic well-being: a longitudinal mediation study. Front. Psychol. 11:2126. doi: 10.3389/fpsyg.2020.02126

Shek, D. T. L., Leung, J. T. Y., and Tan, L. (in press). Social policies and theories on quality of life under COVID-19: in search of the missing links. Appl. Res. Qual. Life.

Shek, D. T. L., Li, X., Yu, L., Lin, L., and Chen, Y. (2022a). Evaluation of electronic service-learning (e-service-learning) projects in mainland China under COVID-19. Appl. Res. Qual. Life 17, 3175–3198. doi: 10.1007/s11482-022-10058-8

Shek, D. T. L., and Ma, C. M. S. (2010). Dimensionality of the Chinese positive youth development scale: confirmatory factor analyses. Soc. Indic. Res. 98, 41–59. doi: 10.1007/s11205-009-9515-9

Shek, D. T. L., Siu, A. M. H., and Lee, T. Y. (2007). The Chinese positive youth development scale: a validation study. Res. Soc. Work. Pract. 17, 380–391. doi: 10.1177/1049731506296196

Shek, D. T. L., Zhu, X., Li, X., and Dou, D. (2022b). Satisfaction with HyFlex teaching and law-abiding leadership education in Hong Kong university students under COVID-19. Appl. Res. Qual. Life 17, 2833–2858. doi: 10.1007/s11482-022-10040-4

Snyder, J., Bullard, L., Wagener, A., Leong, P. K., Snyder, J., and Jenkins, M. (2009). Childhood anxiety and depressive symptoms: trajectories, relationship, and association with subsequent depression. J. Clin. Child Adolesc. Psychol. 38, 837–849. doi: 10.1080/15374410903258959

Starnino, V. R., Gomi, S., and Canda, E. R. (2012). Spiritual strengths assessment in mental health practice. Br. J. Soc. Work 44, 849–867. doi: 10.1093/bjsw/bcs179

Starr, L. R., and Davila, J. (2012). Temporal patterns of anxious and depressed mood in generalized anxiety disorder: a daily diary study. Behav. Res. Ther. 50, 131–141. doi: 10.1016/j.brat.2011.11.005

Steger, M. F., Kawabata, Y., Shimai, S., and Otake, K. (2008). The meaningful life in Japan and the United States: levels and correlates of meaning in life. J. Res. Pers. 42, 660–678. doi: 10.1016/j.jrp.2007.09.003

Steger, M. F., Mann, J. R., Michels, P., and Cooper, T. C. (2009). Meaning in life, anxiety, depression, and general health among smoking cessation patients. J. Psychosom. Res. 67, 353–358. doi: 10.1016/j.jpsychores.2009.02.006

Su, L., Wang, K., Fan, F., Su, Y., and Gao, X. (2008). Reliability and validity of the screen for child anxiety related emotional disorders (SCARED) in Chinese children. J. Anxiety Disord. 22, 612–621. doi: 10.1016/j.janxdis.2007.05.011

Vowels, L. M., Carnelley, K. B., and Stanton, S. C. E. (2022). Attachment anxiety predicts worse mental health outcomes during COVID-19: evidence from two studies. Personal. Individ. Differ. 185:111256. doi: 10.1016/j.paid.2021.111256

Watson, D., Weber, K., Assenheimer, J. S., Clark, L. A., Strauss, M. E., and McCormick, R. A. (1995). Testing a tripartite model: I. evaluating the convergent and discriminant validity of anxiety and depression symptom scales. J. Abnorm. Psychol. 104, 3–14. doi: 10.1037/0021-843X.104.1.3

Weeks, J. W., Rodebaugh, T. L., Heimberg, R. G., Norton, P. J., and Jakatdar, T. A. (2009). “To avoid evaluation, withdraw,”: fears of evaluation and depressive cognitions lead to social anxiety and submissive withdrawal. Cogn. Ther. Res. 33, 375–389. doi: 10.1007/s10608-008-9203-0

Wetherell, J. L., Gatz, M., and Pedersen, N. L. (2001). A longitudinal analysis of anxiety and depressive symptoms. Psychol. Aging 16, 187–195. doi: 10.1037/0882-7974.16.2.187

Winer, E. S., Bryant, J., Bartoszek, G., Rojas, E., Nadorff, M. R., and Kilgore, J. (2017). Mapping the relationship between anxiety, anhedonia, and depression. J. Affect. Disord. 221, 289–296. doi: 10.1016/j.jad.2017.06.006

Woodward, L. J., and Fergusson, D. M. (2001). Life course outcomes of young people with anxiety disorders in adolescence. J. Am. Acad. Child Adolesc. Psychiatry 40, 1086–1093. doi: 10.1097/00004583-200109000-00018

Yek, M. H., Olendzki, N., Kekecs, Z., Patterson, V., and Elkins, G. (2017). Presence of meaning in life and search for meaning in life and relationship to health anxiety. Psychol. Rep. 120, 383–390. doi: 10.1177/0033294117697084

Zhang, M. X., Mou, N. L., Tong, K. K., and Wu, A. M. S. (2018). Investigation of the effects of purpose in life, grit, gratitude, and school belonging on mental distress among Chinese emerging adults. Int. J. Environ. Res. Public Health 15:2147. doi: 10.3390/ijerph15102147

Zhu, X., Chai, W., Shek, D. T. L., and Lin, L. (2022). Promotion of meaning in life and wellbeing among university students during the COVID-19 pandemic via a service-learning subject. Front. Public Health 10. doi: 10.3389/fpubh.2022.924711

Zhu, X., Shek, D. T. L., and Dou, D. (2021). Factor structure of the Chinese CES-D and invariance analyses across gender and over time among Chinese adolescents. J. Affect. Disord. 295, 639–646. doi: 10.1016/j.jad.2021.08.122

Keywords: anxiety, life meaning, spirituality, depression, comorbidity, positive youth development

Citation: Shek DTL, Chai W and Tan L (2022) The relationship between anxiety and depression under the pandemic: The role of life meaning. Front. Psychol . 13:1059330. doi: 10.3389/fpsyg.2022.1059330

Received: 01 October 2022; Accepted: 09 November 2022; Published: 28 November 2022.

Reviewed by:

Copyright © 2022 Shek, Chai and Tan. 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: Daniel T. L. Shek, [email protected]

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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