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. Author manuscript; available in PMC: 2025 Nov 15.
Published in final edited form as: J Affect Disord. 2024 Aug 17;365:437–442. doi: 10.1016/j.jad.2024.08.090

Chronic stress and lack of social support: Role in adolescent depression and suicide-related behaviors in the context of the COVID-19 pandemic

Carol Vidal a,b,*, Maddy Reinert c, Theresa Nguyen c, Hyun-Jin Jun d
PMCID: PMC12032621  NIHMSID: NIHMS2070107  PMID: 39159787

Abstract

Objective:

This study aimed to examine acute and chronic stressors, and perceived lack social support, and their associations with depression and suicidal ideation in adolescents during the COVID-19 pandemic.

Methods:

Deidentified data from (N = 270,153) U.S. adolescents aged 11 to 17 who completed the Patient Health Questionnaire 9-item tool (PHQ-9) in the years 2020 and 2021 were sourced from a collection of online screening tools that are free, confidential, anonymous, and scientifically validated. In addition to depression, the survey included questions about suicidality, past/chronic stressful events, and contributors to mental health problems and sociodemographic variables. SPSS software version 28 for descriptive analyses, and Mplus version 7.31 for confirmatory factor analysis (CFA) and structural equation modeling (SEM), were respectively used.

Results:

Participants were predominantly female, White, and heterosexual, and exhibited a high prevalence of severe depression and a significant frequency of suicidal thoughts. Significant associations were found between past/chronic stressful events, and lack of social support, with suicidality and depression. Mental health stress due to the COVID-19 pandemic itself presented no significant associations with depression and suicidality and was weakly and negatively associated with lack of social support and past/chronic stressors.

Discussion:

These findings reinforce the notion that prior traumatic events can create vulnerabilities in the face of acute stressors, while social support can enhance resilience in adolescents. Factors that increase resilience, such as preventing traumatic events, reducing social stressors, and increasing social support, can serve as valuable guidelines for clinical and public health interventions.

Keywords: Stress, COVID-19 pandemic, Social support, Depression, Suicidality

1. Introduction

The COVID-19 pandemic has contributed to an ongoing, decades-long, crisis in mental health among youth (Keyes and Platt, 2023). Multiple epidemiological national and international studies have examined the impact of the COVID-19 pandemic on youth (Bussières et al., 2021; Gabriel et al., 2022; Kauhanen et al., 2023) and several have demonstrated worsening depression and an increase in suicidal thoughts and behaviors, including deaths by suicide among youth in the U.S. during the pandemic (Center for Disease Control and Prevention., 2023; Charpignon et al., 2022; Yard et al., 2021). While the causes for this worsening mental health crisis are still under debate, the discreet and acute stressor of a pandemic highlighted differences in individual and communal responses, and levels of resiliency (Chan et al., 2021; Samuelson et al., 2022), with youth and minorities being the most negatively affected (Czeisler et al., 2020).

One explanation for the heterogeneity in responses to the pandemic is based on the diathesis-stress model, which postulates that the etiological factors underlying psychiatric illness include those that are more chronic and present from an early age (diathesis) and those that are temporally discrete and occur closer in time to the disorder onset (stress). Animal models and human research suggest an over-imposing effect of acute stress on chronic stress that impacts the surfacing of disorders such as post-traumatic stress disorder, depression, and suicidal thoughts and behaviors (Braet et al., 2013; Eberhart and Hammen, 2010; Hammen et al., 2009; Roth et al., 2012). This diathesis-stress model comes from a well-supported theory of predisposition-excitation framework, used to explain both depression and suicide (Kendler, 2020). Factors like a history of experiencing racism, financial stressors, or previous traumatic events (Heim et al., 2008) may constitute chronic stressors that predispose individuals to mental health problems, particularly depression and suicidality, and make them more vulnerable to the acute stress of the pandemic than those who have experienced less chronic stress. (Fortuna et al., 2020).

The impact of the COVID-19 pandemic and its response on depression and suicide among children and adolescents has been widely discussed (Vidal et al., 2023). However, research gaps still remain. Among others, questions remain about the effects of social distancing given the wide and unprecedented extended implementation of social distancing measures during the COVID-19 pandemic, as well as the role of risk and resilience factors, including previous traumatization, and other environmental and individual factors affecting stress regulation and coping, as well as the untangling of the associations among various risk factors (Fegert et al., 2020).

Loneliness and lack of social support are known risk factors for depression and suicide (Saltzman et al., 2020). Factors involving social relationships during the COVID-19 pandemic such as relationship problems with family members or others residing in the home during lockdowns, and/or grieving the death of a family member or friend may also have had an impact on youth mental health. While loneliness related to lockdown measures has also been associated to worsening mental health (Fancourt et al., 2021), more research is needed to examine the associations between perceived acute and chronic stressors and lack of social support during the pandemic, with depression and suicidal ideation outcomes in adolescents.

This study aims to examine acute and chronic stressors, and perceived lack social support, and their associations with depression and suicidal ideation in adolescents during the COVID-19 pandemic. We propose a model to explain the strength of the associations of past/chronic stressful events (trauma, racism, poverty), lack of social support, and the acute stressor of experiencing a pandemic, and depression and suicidal thoughts in a national sample of adolescents residing in the United States (U.S.).

2. Methods

2.1. Data source and sample

Deidentified data from adolescents aged 11 to 17 who completed the Patient Health Questionnaire 9-item tool (PHQ-9) in the years 2020 and 2021 were acquired by Mental Health America (MHA). These data were sourced from a collection of online screening tools that are free, confidential, anonymous, and scientifically validated. The screening tools cover various mental health areas, including depression, anxiety, bipolar disorder, post-traumatic stress disorder, alcohol and substance use, and early psychosis for both adolescents and adults. MHA screening data is organic, with participants discovering the survey through search engines (e.g., Google, Bing, and Yahoo), as well as from the main MHA National website or various national social media platforms, including Instagram, Twitter, Reddit, and YouTube. About 1 % of the sample consists of referred users from MHA affiliate organizations or other websites. Our analyses focused exclusively on data from individuals who indicated residing in the U.S. in response to the state demographic question. Those who selected “I live outside the U.S.,” “I live in a U.S. territory,” or did not respond to the question were excluded from the dataset. This study specifically examined a subset of data collected from adolescents aged 11 to 17 who identified as “students” during the years 2020 and 2021, resulting in a final sample of 270,153 cases. This sample included youth residing in all 50 states and the District of Columbia (D.C.).

2.2. Measures

2.2.1. Depression

The Patient Health Questionnaire 9-item tool (PHQ-9) (Kroenke et al., 2001) served as the assessment tool to evaluate the risk of depression over the preceding two weeks. It applied the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM–IV) diagnostic criteria to assess the presence and intensity of depressive symptomatology. Each question in the PHQ-9 corresponds to a set of response options, scored from 0 (not at all) to 3 (nearly every day), reflecting the severity of the symptom. The scores for each question are then aggregated to generate a total score, ranging from 0 to 27. Higher scores generally indicate a more severe level of depressive symptoms. The PHQ-9 is often used by healthcare professionals to help diagnose depression, assess its severity, and monitor treatment progress over time. The reliability and validity of PHQ-9 among adolescents has been established in studies (Richardson et al., 2010). The sum score of the PHQ-9 was dichotomized, with scores 9 or less indicating the presence of no or mild depressive symptoms, and scores 10 or above indicating moderate or severe depression.

2.2.2. Suicidality

The PHQ-9 includes a specific item dedicated to assessing suicidal ideation, which involves the presence of thoughts related to wanting to die or hurt oneself over the past two weeks. This item particular is designed to gauge the severity of individual’s distress and help healthcare professionals in identifying those who might be at risk of self-harm or suicide. Respondents were provided with the same set of response options as the other items on the PHQ-9, ranging from “not at all” (0) to “nearly every day” (3). Higher scores indicate more severe thoughts of self-harm or suicide. For the analytical purposes, this item was dummy-coded, with 0 indicating the absence of suicidal ideation and 1 indicating the presence of suicidal ideation.

2.2.3. Past/chronic stressful events

Participants were asked with the question, “What are the main things contributing to your mental health problems right now?.” Response options for the question about main contributors to mental health included: coronavirus, relationship problems, past trauma, loneliness or isolation, grief or loss, financial problems, racism, and current events (news, politics, etc.). All variables were recoded into dichotomous variables (0 = No; 1 = Yes). Past trauma, financial problems, and racism were considered as an indicator of past/chronic stressful events.

2.2.4. Mental health stressor due to coronavirus

A single item assessed Coronavirus as one of the main contributors to acute mental health problems (0 = No, 1 = Yes).

2.2.5. Lack of social support

Among the contributors presented above, loneliness/isolation, relationship problems, and grief/loss were included as a proxy of lack of social support.

2.2.6. Sociodemographic variables

Sex (female, male, others), race (White, Black) and ethnicity (Hispanic), LGBTQ, and income were included as sociodemographic variables.

2.3. Data analysis

Using SPSS software version 28, descriptive analyses were conducted to examine the characteristics of the sample, the variables of interest, and the distribution of the study variables. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were performed using Mplus version 7.31.(Muthén, 2014). SEM allows for the assessment of whether a pre-established theoretical model aligns with observed data by simultaneously evaluating the relationships among variables and their underlying constructs. The SEM process followed the recommended two-step methodology. Initially, a measurement model was evaluated through CFA, with all relevant pathways allowed to vary, aiming to identify the factor structure of independent variables. Subsequently, only individual items with significant factor loadings were retained in the final CFA model to achieve a well-fitting parsimonious model. Following this, the hypothesized structural model (Fig. 1) that integrated constructs validated by the measurement model was tested. In this stage, all anticipated paths were freely estimated, meaning that all parameters were allowed to vary in the model without any equality constraints on the parameters.

Fig. 1.

Fig. 1.

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Conceptual model hypothesizing the impact of past/chronic stressful events, mental health stressor due to Coronavirus, lack of social support on depression and suicidality. Positive (+) and negative (−) signs are employed to denote pathways reflecting favorable and adverse associations, respectively.

The final model was re-specified from the proposed hypothesized model according to preceding literature and modification indices (Kline, 2016). In all SEM analyses, the weighted least squares mean and variance adjusted (WLSMV) estimator was employed, given that the observed variables were categorical. The goodness of fit was evaluated using multiple fit indices. (Hu and Bentler, 1999; Kline, 2016). Specifically, the following criteria were applied: a chi-square (χ2) goodness-of-fit index, the Comparative Fit Index (CFI) and the Tucker–Lewis index (TLI) with values ≥ 0.95; the Root Mean Square Error of Approximation (RMSEA) ≤ 0.06, and a Standardized Root Mean Square Residual (SRMR) < 0.08.

3. Results

3.1. Descriptive statistics

A majority of participants identified as female (66.6 %), White (46.0 %), non-Hispanic/Latino (81.5 %), and heterosexual (65.8 %). Over one-third of the respondents indicated a household income below $60,000. >70 % of participants disclosed experiencing suicidal ideation and severe depression. Among participants, 22.7 % identified the Coronavirus pandemic as a primary factor influencing their mental health challenges. Additionally, around 42 % of respondents cited past trauma as a concern, 5 % mentioned racism, and 2 % indicated financial problems as contributing factors. Notably, 60 % of respondents reported feelings of loneliness or isolation, while 38.2 % noted relationship problems, and 13.4 % mentioned grief or loss (see Table 1 for more details).

Table 1.

Sample characteristics (N = 270,153).

Number %
Sex
 Female 180,013 66.6
 Male 74,637 27.6
 Non-binary 15,503 5.7
Race/Ethnicity
 White 124,236 46.0
 Black/African American 28,985 10.7
 Asian/Pacific Islander/Native Hawaiian 25,951 9.6
 Hispanic/Latino 6104 2.3
 Multiple races 49,893 18.5
 Other 20,212 7.5
 Sexual orientation
 Heterosexual 177,671 65.8
 LGBTQ 92,482 34.2
Household income
 Less than $20,000 38,282 14.2
 $20,000–$39,999 32,846 12.2
 $40,000–$59,999 28,381 10.5
 $60,000–$79,999 24,366 9.0
 $80,000–$99,999 17,717 6.6
 $100,000–$149,999 22,004 8.1
 More than $150,000 20,424 7.6
Past/chronic stressful events
 Past trauma 113,181 41.9
 Racism 17,118 6.3
 Financial stressors 6598 2.4
Mental health stressor due to Coronavirus 61,363 22.7
Lack of social support
 Loneliness/isolation 163,023 60.3
 Relationship problems 103,286 38.2
 Grief/loss 36,148 13.4
Depression
 None 3812 1.4
 Mild 10,576 3.9
 Moderate 24,632 9.1
 Moderately severe 38,968 14.4
 Severe 192,165 71.1
Suicidal thoughts
 Not at all 73,372 27.2
 Several days 65,758 24.3
 More than half the days 81,025 30.0
 Nearly every day 49,998 18.5
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3.2. Measurement model

A three-factor CFA model for past/chronic stressful events, encompassing variables of past trauma (+), racism (−), financial stressors (−), exhibited excellent fit (χ2(0) = 0.000, p = .000, CFI = 1.00, TLI = 1.00, SRMR = 0.00). Similarly, a three-factor CFA model for lack of social support, comprising variables of loneliness (+), relationship problems (+), and grief/loss (+), also demonstrated excellent fit (χ2(0) = 0.000, p = .000, CFI = 1.00, TLI = 1.00, SRMR = 0.04). Every standardized factor loading was statistically significant and aligned with the expected directions. Consequently, the measurement model was deemed reasonable and was adapted for this study.

3.3. Structural model

SEM was performed to assess acute and chronic stressors and their associations with depression and suicidal ideation in adolescents during the COVID-19 pandemic. The full structural model demonstrated a good fit to the data (χ2(27) = 135.73, p = .000, CFI = 1.00, TLI = 0.99, RMSEA = 0.00 [0.00–0.01], SRMR = 0.04). As shown in Fig. 2, both past/chronic stressful events and lack of social support were positively associated with both depression (β = 0.09, p < .001; β = 0.25, p < .001) and suicidality (β = 0.08, p < .001; β = 0.30, p < .001), indicating that higher levels of past/chronic stressful events and lack of social support were associated with an increased risk of depression and suicidal ideation. Past/chronic stressful events had a significant positive association with lack of social support (β = 0.37, p < .001), whereas it had a significant negative relationship with mental health stressor due to Coronavirus (β = −2.04, p < .001). Lack of social support was negatively correlated with mental health stressor due to Coronavirus (r = −0.07, p < .001). Mental health stress due to coronavirus was not significantly related to depression and suicidality.

Fig. 2.

Fig. 2.

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Structural equation model exploring the impact of past/chronic stressful events, mental health stressor due to Coronavirus, lack of social support on depression and suicidality. Ovals present the latent variables, whereas rectangles symbolize the observed variables. For the sake of clarity, only significant coefficients are displayed. The provided coefficients are standardized. *p < .05, **p < .01, ***p < .001.

4. Discussion

This study aimed to elucidate the associations between acute and chronic stressors, perceived lack social support, and depression and suicidal ideation in a large sample of adolescents during the COVID-19 pandemic. Participants were predominantly female, White, and heterosexual, and exhibited a high prevalence of severe depression and a significant frequency of suicidal thoughts. A majority of survey completers reported a household income below the median household income in the U.S., which was approximately $70,000 in 2021 (Semega and Kollar, 2022). Females (66.6 %) and LGBTQ adolescents (34.2 %) in this sample were over-represented compared to the general population in 2021 (24.5 %), as indicated by the Youth Risk Behavior Surveillance System (YRBSS) (Conron, 2020).

The prevalence of nearly 70 % of participants endorsing some frequency of suicidal thoughts (with 48.5 % reporting suicidal thoughts more than half of the days or nearly every day of the week), and over 70 % endorsing symptoms of severe depression, is considerably higher than the prevalence of these symptoms in general population samples (Ivey-Stephenson et al., 2020; Mojtabai et al., 2016). This difference is most likely explained by the self-selection of the sample. Our sample reflects individuals who voluntarily completed a mental health screening online. They were likely searching for information about mental health or seeking resources when they encountered the survey and chose to participate.

The findings of this study align with prior research highlighting a role of previous traumatic experiences (Heim et al., 2008; Panagioti et al., 2015), and emphasizing loneliness and isolation as risk factors for depression and suicidal ideation (Loades et al., 2020). Furthermore, these results are consistent with other studies conducted during the pandemic (Fancourt et al., 2021; Lewis et al., 2023). Social support has been recognized as a moderator of stress for decades (Cobb, 1976). Interestingly, even though the survey data was collected in 2020 and 2021 during the COVID-19 pandemic, only one in five participants identified COVID-19 as one of the primary factors contributing to mental health challenges. A majority pointed to loneliness and isolation, followed by past trauma, and relationship problems as significant contributors for their mental health challenges. A minority identified grief and loss, racism, and financial stressors as causal factors for mental health challenges. It is important to note that participants were limited to selecting three contributors to mental stress. Therefore, while there may have been other contributors, this study explored the most frequently mentioned contributors to mental health perceived by the adolescents in this sample.

As expected, the results of SEM revealed a strong correlation between depression and suicidality. Significant associations were also found between past/chronic stressful events and suicidality and depression, as well as between lack of social support, and suicidality and depression. Mental health stress due to COVID-19 itself presented no significant associations with depression and suicidality and was weakly and negatively associated with lack of social support and past/chronic stressors. These findings reinforce the notion that prior traumatic events can create vulnerabilities in the face of acute stressors, while social support can enhance resilience in adolescents. Past and chronic stressors, primarily driven by past trauma, demonstrated a strong association with lack of social support and a negative association with mental health stress due to coronavirus. This negative association should be interpreted with caution since responders were limited in their selection of contributors to mental health. Therefore, while COVID-19 may not have been selected as one of the main contributors, it might still have been experienced as stressful. However, the finding may also suggest that adolescents with prior experiences of trauma, chronic stress, or low social support were less likely to identify COVID-19 as a main contributor and identified their experiences of past/chronic stressful events as more significant contributors to their mental health distress. Reported stress from COVID-19 was not significantly associated with depression or suicidality. Therefore COVID-19 stress alone likely did not contribute as much to the increase in depression and suicidality among adolescents, but rather experiences with past/chronic stress in the context of the COVID-19 pandemic. This indicates the need to target chronic stressors during and following acute stressors like the pandemic to increase resiliency and decrease mental health challenges.

Criticism of epidemiological studies relying solely on surveys for assessing depression and suicidal thoughts, without considering context, are valid and raise the need of comprehensive clinical assessments to gain a deeper understanding of the complex factors contributing to these disorders (Horwitz and Wakefield, 2006). The primary objective of this study was to enhance our understanding of the circumstances and social context in which these symptoms are endorsed. Furthermore, it aimed to provide insights into the significance of chronic and acute stressors associated with depression and suicidal ideation. The use of a validated screening tool for depression can, to some extent, offer an indication of the severity of the symptoms presented. Contrary to assumptions about the direct role of the pandemic itself on mental health, this study showed that, among youth, factors related to measures implemented to contain the pandemic (i.e.: isolation due to lockdowns) may have played a crucial role on mental health.

A limitation of this study was the lack of a validated suicide assessment, relying on only one question for this purpose. The large sample allowed us to detect small differences. For example, while participants did not identify household income as a contributing factor, exploratory analyses with small effect sizes demonstrated that higher household incomes were protective. This finding suggests that future studies should delve into assessing the impact of the pandemic and isolation on mental health by household income. Additionally, this was a cross-sectional study, and therefore, no causal relationships can be established. Longitudinal research involving subjects assessed before, during, and after the pandemic could help explain causality. While the survey asked about the participants’ causal attributions to their mental health problems, it is important to acknowledge that depression and suicide are complex and multicausal, and the individual’s subjective perception of the contributors to their mental health may not be capture the complete picture. A major limitation of this study is the lack of inclusion of validated measures to assess lack of social support, and other measures of stress. Furthermore, the question about contributors to mental health had a predetermined set of response choices that may have provided biased responses. However, the list of stressors provided are common stressors in children, and there was an additional free text option. Finally, the sample was not representative of the general population as those completing the screener represented individuals who voluntarily sought information or services about mental health, introducing potential selection bias.

In conclusion, within the context of the COVID-19 pandemic, chronic stressors such as a history of trauma and current social isolation emerged as primary perceived drivers of depression and anxiety among adolescents in need of mental health support. Recommendations to focus on factors that may increase resilience, such as preventing traumatic events, reducing social stressors, and increasing social support, can serve as valuable guidelines for public health interventions. This guidance is pertinent not only for preventing the implementation of measures that worsen social supports during crises such as pandemics, but also for promoting social support as a public health measure to improve overall mental health, as attempted by new federal initiatives (Office of the Surgeon General (OSG), 2023).

Acknowledgements

Dr. Vidal receives funding from the NIDA/AACAP Physician Scientist Training Program in Substance Abuse Research, supported by NIDA Career Development Award (K12). A previous related poster was presented at the IASR/AFSP International Summit on Suicide Research in Barcelona in October 2023.

Role of the funding source

Dr. Vidal receives funding from the NIDA/AACAP Physician Scientist Training Program in Substance Abuse Research, supported by NIDA Career Development Award (K12).

Footnotes

Declaration of competing interest

Dr. Vidal receives funding from the NIDA/AACAP Physician Scientist Training Program in Substance Abuse Research, supported by NIDA Career Development Award (K12).

CRediT authorship contribution statement

Carol Vidal: Writing – review & editing, Writing – original draft, Data curation, Conceptualization. Maddy Reinert: Writing – review & editing, Validation, Data curation. Theresa Nguyen: Writing – review & editing, Validation, Project administration. Hyun-Jin Jun: Writing – review & editing, Formal analysis, Data curation, Conceptualization.

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