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Research Article

Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression

Affiliations Department of Psychology, University of Gothenburg, Gothenburg, Sweden, Network for Empowerment and Well-Being, University of Gothenburg, Gothenburg, Sweden

Affiliation Network for Empowerment and Well-Being, University of Gothenburg, Gothenburg, Sweden

Affiliations Department of Psychology, University of Gothenburg, Gothenburg, Sweden, Network for Empowerment and Well-Being, University of Gothenburg, Gothenburg, Sweden, Department of Psychology, Education and Sport Science, Linneaus University, Kalmar, Sweden

* E-mail: [email protected]

Affiliations Network for Empowerment and Well-Being, University of Gothenburg, Gothenburg, Sweden, Center for Ethics, Law, and Mental Health (CELAM), University of Gothenburg, Gothenburg, Sweden, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

Ali Al Nima,
Patricia Rosenberg,
Trevor Archer,
Danilo Garcia

Published: September 9, 2013
https://doi.org/10.1371/journal.pone.0073265
Reader Comments

23 Sep 2013: Nima AA, Rosenberg P, Archer T, Garcia D (2013) Correction: Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression. PLOS ONE 8(9): 10.1371/annotation/49e2c5c8-e8a8-4011-80fc-02c6724b2acc. https://doi.org/10.1371/annotation/49e2c5c8-e8a8-4011-80fc-02c6724b2acc View correction

Mediation analysis investigates whether a variable (i.e., mediator) changes in regard to an independent variable, in turn, affecting a dependent variable. Moderation analysis, on the other hand, investigates whether the statistical interaction between independent variables predict a dependent variable. Although this difference between these two types of analysis is explicit in current literature, there is still confusion with regard to the mediating and moderating effects of different variables on depression. The purpose of this study was to assess the mediating and moderating effects of anxiety, stress, positive affect, and negative affect on depression.

Two hundred and two university students (males = 93, females = 113) completed questionnaires assessing anxiety, stress, self-esteem, positive and negative affect, and depression. Mediation and moderation analyses were conducted using techniques based on standard multiple regression and hierarchical regression analyses.

Main Findings

The results indicated that (i) anxiety partially mediated the effects of both stress and self-esteem upon depression, (ii) that stress partially mediated the effects of anxiety and positive affect upon depression, (iii) that stress completely mediated the effects of self-esteem on depression, and (iv) that there was a significant interaction between stress and negative affect, and between positive affect and negative affect upon depression.

The study highlights different research questions that can be investigated depending on whether researchers decide to use the same variables as mediators and/or moderators.

Citation: Nima AA, Rosenberg P, Archer T, Garcia D (2013) Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression. PLoS ONE 8(9): e73265. https://doi.org/10.1371/journal.pone.0073265

Editor: Ben J. Harrison, The University of Melbourne, Australia

Received: February 21, 2013; Accepted: July 22, 2013; Published: September 9, 2013

Copyright: © 2013 Nima 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.

Funding: The authors have no support or funding to report.

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

Introduction

Mediation refers to the covariance relationships among three variables: an independent variable (1), an assumed mediating variable (2), and a dependent variable (3). Mediation analysis investigates whether the mediating variable accounts for a significant amount of the shared variance between the independent and the dependent variables–the mediator changes in regard to the independent variable, in turn, affecting the dependent one [1] , [2] . On the other hand, moderation refers to the examination of the statistical interaction between independent variables in predicting a dependent variable [1] , [3] . In contrast to the mediator, the moderator is not expected to be correlated with both the independent and the dependent variable–Baron and Kenny [1] actually recommend that it is best if the moderator is not correlated with the independent variable and if the moderator is relatively stable, like a demographic variable (e.g., gender, socio-economic status) or a personality trait (e.g., affectivity).

Although both types of analysis lead to different conclusions [3] and the distinction between statistical procedures is part of the current literature [2] , there is still confusion about the use of moderation and mediation analyses using data pertaining to the prediction of depression. There are, for example, contradictions among studies that investigate mediating and moderating effects of anxiety, stress, self-esteem, and affect on depression. Depression, anxiety and stress are suggested to influence individuals' social relations and activities, work, and studies, as well as compromising decision-making and coping strategies [4] , [5] , [6] . Successfully coping with anxiety, depressiveness, and stressful situations may contribute to high levels of self-esteem and self-confidence, in addition increasing well-being, and psychological and physical health [6] . Thus, it is important to disentangle how these variables are related to each other. However, while some researchers perform mediation analysis with some of the variables mentioned here, other researchers conduct moderation analysis with the same variables. Seldom are both moderation and mediation performed on the same dataset. Before disentangling mediation and moderation effects on depression in the current literature, we briefly present the methodology behind the analysis performed in this study.

Mediation and moderation

Baron and Kenny [1] postulated several criteria for the analysis of a mediating effect: a significant correlation between the independent and the dependent variable, the independent variable must be significantly associated with the mediator, the mediator predicts the dependent variable even when the independent variable is controlled for, and the correlation between the independent and the dependent variable must be eliminated or reduced when the mediator is controlled for. All the criteria is then tested using the Sobel test which shows whether indirect effects are significant or not [1] , [7] . A complete mediating effect occurs when the correlation between the independent and the dependent variable are eliminated when the mediator is controlled for [8] . Analyses of mediation can, for example, help researchers to move beyond answering if high levels of stress lead to high levels of depression. With mediation analysis researchers might instead answer how stress is related to depression.

In contrast to mediation, moderation investigates the unique conditions under which two variables are related [3] . The third variable here, the moderator, is not an intermediate variable in the causal sequence from the independent to the dependent variable. For the analysis of moderation effects, the relation between the independent and dependent variable must be different at different levels of the moderator [3] . Moderators are included in the statistical analysis as an interaction term [1] . When analyzing moderating effects the variables should first be centered (i.e., calculating the mean to become 0 and the standard deviation to become 1) in order to avoid problems with multi-colinearity [8] . Moderating effects can be calculated using multiple hierarchical linear regressions whereby main effects are presented in the first step and interactions in the second step [1] . Analysis of moderation, for example, helps researchers to answer when or under which conditions stress is related to depression.

Mediation and moderation effects on depression

Cognitive vulnerability models suggest that maladaptive self-schema mirroring helplessness and low self-esteem explain the development and maintenance of depression (for a review see [9] ). These cognitive vulnerability factors become activated by negative life events or negative moods [10] and are suggested to interact with environmental stressors to increase risk for depression and other emotional disorders [11] , [10] . In this line of thinking, the experience of stress, low self-esteem, and negative emotions can cause depression, but also be used to explain how (i.e., mediation) and under which conditions (i.e., moderation) specific variables influence depression.

Using mediational analyses to investigate how cognitive therapy intervations reduced depression, researchers have showed that the intervention reduced anxiety, which in turn was responsible for 91% of the reduction in depression [12] . In the same study, reductions in depression, by the intervention, accounted only for 6% of the reduction in anxiety. Thus, anxiety seems to affect depression more than depression affects anxiety and, together with stress, is both a cause of and a powerful mediator influencing depression (See also [13] ). Indeed, there are positive relationships between depression, anxiety and stress in different cultures [14] . Moreover, while some studies show that stress (independent variable) increases anxiety (mediator), which in turn increased depression (dependent variable) [14] , other studies show that stress (moderator) interacts with maladaptive self-schemata (dependent variable) to increase depression (independent variable) [15] , [16] .

The present study

In order to illustrate how mediation and moderation can be used to address different research questions we first focus our attention to anxiety and stress as mediators of different variables that earlier have been shown to be related to depression. Secondly, we use all variables to find which of these variables moderate the effects on depression.

The specific aims of the present study were:

To investigate if anxiety mediated the effect of stress, self-esteem, and affect on depression.
To investigate if stress mediated the effects of anxiety, self-esteem, and affect on depression.
To examine moderation effects between anxiety, stress, self-esteem, and affect on depression.

Ethics statement

This research protocol was approved by the Ethics Committee of the University of Gothenburg and written informed consent was obtained from all the study participants.

Participants

The present study was based upon a sample of 206 participants (males = 93, females = 113). All the participants were first year students in different disciplines at two universities in South Sweden. The mean age for the male students was 25.93 years ( SD = 6.66), and 25.30 years ( SD = 5.83) for the female students.

In total, 206 questionnaires were distributed to the students. Together 202 questionnaires were responded to leaving a total dropout of 1.94%. This dropout concerned three sections that the participants chose not to respond to at all, and one section that was completed incorrectly. None of these four questionnaires was included in the analyses.

Instruments

Hospital anxiety and depression scale [17] ..

The Swedish translation of this instrument [18] was used to measure anxiety and depression. The instrument consists of 14 statements (7 of which measure depression and 7 measure anxiety) to which participants are asked to respond grade of agreement on a Likert scale (0 to 3). The utility, reliability and validity of the instrument has been shown in multiple studies (e.g., [19] ).

Perceived Stress Scale [20] .

The Swedish version [21] of this instrument was used to measures individuals' experience of stress. The instrument consist of 14 statements to which participants rate on a Likert scale (0 = never , 4 = very often ). High values indicate that the individual expresses a high degree of stress.

Rosenberg's Self-Esteem Scale [22] .

The Rosenberg's Self-Esteem Scale (Swedish version by Lindwall [23] ) consists of 10 statements focusing on general feelings toward the self. Participants are asked to report grade of agreement in a four-point Likert scale (1 = agree not at all, 4 = agree completely ). This is the most widely used instrument for estimation of self-esteem with high levels of reliability and validity (e.g., [24] , [25] ).

Positive Affect and Negative Affect Schedule [26] .

This is a widely applied instrument for measuring individuals' self-reported mood and feelings. The Swedish version has been used among participants of different ages and occupations (e.g., [27] , [28] , [29] ). The instrument consists of 20 adjectives, 10 positive affect (e.g., proud, strong) and 10 negative affect (e.g., afraid, irritable). The adjectives are rated on a five-point Likert scale (1 = not at all , 5 = very much ). The instrument is a reliable, valid, and effective self-report instrument for estimating these two important and independent aspects of mood [26] .

Questionnaires were distributed to the participants on several different locations within the university, including the library and lecture halls. Participants were asked to complete the questionnaire after being informed about the purpose and duration (10–15 minutes) of the study. Participants were also ensured complete anonymity and informed that they could end their participation whenever they liked.

Correlational analysis

Depression showed positive, significant relationships with anxiety, stress and negative affect. Table 1 presents the correlation coefficients, mean values and standard deviations ( sd ), as well as Cronbach ' s α for all the variables in the study.

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https://doi.org/10.1371/journal.pone.0073265.t001

Mediation analysis

Regression analyses were performed in order to investigate if anxiety mediated the effect of stress, self-esteem, and affect on depression (aim 1). The first regression showed that stress ( B = .03, 95% CI [.02,.05], β = .36, t = 4.32, p <.001), self-esteem ( B = −.03, 95% CI [−.05, −.01], β = −.24, t = −3.20, p <.001), and positive affect ( B = −.02, 95% CI [−.05, −.01], β = −.19, t = −2.93, p = .004) had each an unique effect on depression. Surprisingly, negative affect did not predict depression ( p = 0.77) and was therefore removed from the mediation model, thus not included in further analysis.

The second regression tested whether stress, self-esteem and positive affect uniquely predicted the mediator (i.e., anxiety). Stress was found to be positively associated ( B = .21, 95% CI [.15,.27], β = .47, t = 7.35, p <.001), whereas self-esteem was negatively associated ( B = −.29, 95% CI [−.38, −.21], β = −.42, t = −6.48, p <.001) to anxiety. Positive affect, however, was not associated to anxiety ( p = .50) and was therefore removed from further analysis.

A hierarchical regression analysis using depression as the outcome variable was performed using stress and self-esteem as predictors in the first step, and anxiety as predictor in the second step. This analysis allows the examination of whether stress and self-esteem predict depression and if this relation is weaken in the presence of anxiety as the mediator. The result indicated that, in the first step, both stress ( B = .04, 95% CI [.03,.05], β = .45, t = 6.43, p <.001) and self-esteem ( B = .04, 95% CI [.03,.05], β = .45, t = 6.43, p <.001) predicted depression. When anxiety (i.e., the mediator) was controlled for predictability was reduced somewhat but was still significant for stress ( B = .03, 95% CI [.02,.04], β = .33, t = 4.29, p <.001) and for self-esteem ( B = −.03, 95% CI [−.05, −.01], β = −.20, t = −2.62, p = .009). Anxiety, as a mediator, predicted depression even when both stress and self-esteem were controlled for ( B = .05, 95% CI [.02,.08], β = .26, t = 3.17, p = .002). Anxiety improved the prediction of depression over-and-above the independent variables (i.e., stress and self-esteem) (Δ R 2 = .03, F (1, 198) = 10.06, p = .002). See Table 2 for the details.

https://doi.org/10.1371/journal.pone.0073265.t002

A Sobel test was conducted to test the mediating criteria and to assess whether indirect effects were significant or not. The result showed that the complete pathway from stress (independent variable) to anxiety (mediator) to depression (dependent variable) was significant ( z = 2.89, p = .003). The complete pathway from self-esteem (independent variable) to anxiety (mediator) to depression (dependent variable) was also significant ( z = 2.82, p = .004). Thus, indicating that anxiety partially mediates the effects of both stress and self-esteem on depression. This result may indicate also that both stress and self-esteem contribute directly to explain the variation in depression and indirectly via experienced level of anxiety (see Figure 1 ).

Changes in Beta weights when the mediator is present are highlighted in red.

https://doi.org/10.1371/journal.pone.0073265.g001

For the second aim, regression analyses were performed in order to test if stress mediated the effect of anxiety, self-esteem, and affect on depression. The first regression showed that anxiety ( B = .07, 95% CI [.04,.10], β = .37, t = 4.57, p <.001), self-esteem ( B = −.02, 95% CI [−.05, −.01], β = −.18, t = −2.23, p = .03), and positive affect ( B = −.03, 95% CI [−.04, −.02], β = −.27, t = −4.35, p <.001) predicted depression independently of each other. Negative affect did not predict depression ( p = 0.74) and was therefore removed from further analysis.

The second regression investigated if anxiety, self-esteem and positive affect uniquely predicted the mediator (i.e., stress). Stress was positively associated to anxiety ( B = 1.01, 95% CI [.75, 1.30], β = .46, t = 7.35, p <.001), negatively associated to self-esteem ( B = −.30, 95% CI [−.50, −.01], β = −.19, t = −2.90, p = .004), and a negatively associated to positive affect ( B = −.33, 95% CI [−.46, −.20], β = −.27, t = −5.02, p <.001).

A hierarchical regression analysis using depression as the outcome and anxiety, self-esteem, and positive affect as the predictors in the first step, and stress as the predictor in the second step, allowed the examination of whether anxiety, self-esteem and positive affect predicted depression and if this association would weaken when stress (i.e., the mediator) was present. In the first step of the regression anxiety ( B = .07, 95% CI [.05,.10], β = .38, t = 5.31, p = .02), self-esteem ( B = −.03, 95% CI [−.05, −.01], β = −.18, t = −2.41, p = .02), and positive affect ( B = −.03, 95% CI [−.04, −.02], β = −.27, t = −4.36, p <.001) significantly explained depression. When stress (i.e., the mediator) was controlled for, predictability was reduced somewhat but was still significant for anxiety ( B = .05, 95% CI [.02,.08], β = .05, t = 4.29, p <.001) and for positive affect ( B = −.02, 95% CI [−.04, −.01], β = −.20, t = −3.16, p = .002), whereas self-esteem did not reach significance ( p < = .08). In the second step, the mediator (i.e., stress) predicted depression even when anxiety, self-esteem, and positive affect were controlled for ( B = .02, 95% CI [.08,.04], β = .25, t = 3.07, p = .002). Stress improved the prediction of depression over-and-above the independent variables (i.e., anxiety, self-esteem and positive affect) (Δ R 2 = .02, F (1, 197) = 9.40, p = .002). See Table 3 for the details.

https://doi.org/10.1371/journal.pone.0073265.t003

Furthermore, the Sobel test indicated that the complete pathways from the independent variables (anxiety: z = 2.81, p = .004; self-esteem: z = 2.05, p = .04; positive affect: z = 2.58, p <.01) to the mediator (i.e., stress), to the outcome (i.e., depression) were significant. These specific results might be explained on the basis that stress partially mediated the effects of both anxiety and positive affect on depression while stress completely mediated the effects of self-esteem on depression. In other words, anxiety and positive affect contributed directly to explain the variation in depression and indirectly via the experienced level of stress. Self-esteem contributed only indirectly via the experienced level of stress to explain the variation in depression. In other words, stress effects on depression originate from “its own power” and explained more of the variation in depression than self-esteem (see Figure 2 ).

https://doi.org/10.1371/journal.pone.0073265.g002

Moderation analysis

Multiple linear regression analyses were used in order to examine moderation effects between anxiety, stress, self-esteem and affect on depression. The analysis indicated that about 52% of the variation in the dependent variable (i.e., depression) could be explained by the main effects and the interaction effects ( R 2 = .55, adjusted R 2 = .51, F (55, 186) = 14.87, p <.001). When the variables (dependent and independent) were standardized, both the standardized regression coefficients beta (β) and the unstandardized regression coefficients beta (B) became the same value with regard to the main effects. Three of the main effects were significant and contributed uniquely to high levels of depression: anxiety ( B = .26, t = 3.12, p = .002), stress ( B = .25, t = 2.86, p = .005), and self-esteem ( B = −.17, t = −2.17, p = .03). The main effect of positive affect was also significant and contributed to low levels of depression ( B = −.16, t = −2.027, p = .02) (see Figure 3 ). Furthermore, the results indicated that two moderator effects were significant. These were the interaction between stress and negative affect ( B = −.28, β = −.39, t = −2.36, p = .02) (see Figure 4 ) and the interaction between positive affect and negative affect ( B = −.21, β = −.29, t = −2.30, p = .02) ( Figure 5 ).

https://doi.org/10.1371/journal.pone.0073265.g003

Low stress and low negative affect leads to lower levels of depression compared to high stress and high negative affect.

https://doi.org/10.1371/journal.pone.0073265.g004

High positive affect and low negative affect lead to lower levels of depression compared to low positive affect and high negative affect.

https://doi.org/10.1371/journal.pone.0073265.g005

The results in the present study show that (i) anxiety partially mediated the effects of both stress and self-esteem on depression, (ii) that stress partially mediated the effects of anxiety and positive affect on depression, (iii) that stress completely mediated the effects of self-esteem on depression, and (iv) that there was a significant interaction between stress and negative affect, and positive affect and negative affect on depression.

Mediating effects

The study suggests that anxiety contributes directly to explaining the variance in depression while stress and self-esteem might contribute directly to explaining the variance in depression and indirectly by increasing feelings of anxiety. Indeed, individuals who experience stress over a long period of time are susceptible to increased anxiety and depression [30] , [31] and previous research shows that high self-esteem seems to buffer against anxiety and depression [32] , [33] . The study also showed that stress partially mediated the effects of both anxiety and positive affect on depression and that stress completely mediated the effects of self-esteem on depression. Anxiety and positive affect contributed directly to explain the variation in depression and indirectly to the experienced level of stress. Self-esteem contributed only indirectly via the experienced level of stress to explain the variation in depression, i.e. stress affects depression on the basis of ‘its own power’ and explains much more of the variation in depressive experiences than self-esteem. In general, individuals who experience low anxiety and frequently experience positive affect seem to experience low stress, which might reduce their levels of depression. Academic stress, for instance, may increase the risk for experiencing depression among students [34] . Although self-esteem did not emerged as an important variable here, under circumstances in which difficulties in life become chronic, some researchers suggest that low self-esteem facilitates the experience of stress [35] .

Moderator effects/interaction effects

The present study showed that the interaction between stress and negative affect and between positive and negative affect influenced self-reported depression symptoms. Moderation effects between stress and negative affect imply that the students experiencing low levels of stress and low negative affect reported lower levels of depression than those who experience high levels of stress and high negative affect. This result confirms earlier findings that underline the strong positive association between negative affect and both stress and depression [36] , [37] . Nevertheless, negative affect by itself did not predicted depression. In this regard, it is important to point out that the absence of positive emotions is a better predictor of morbidity than the presence of negative emotions [38] , [39] . A modification to this statement, as illustrated by the results discussed next, could be that the presence of negative emotions in conjunction with the absence of positive emotions increases morbidity.

The moderating effects between positive and negative affect on the experience of depression imply that the students experiencing high levels of positive affect and low levels of negative affect reported lower levels of depression than those who experience low levels of positive affect and high levels of negative affect. This result fits previous observations indicating that different combinations of these affect dimensions are related to different measures of physical and mental health and well-being, such as, blood pressure, depression, quality of sleep, anxiety, life satisfaction, psychological well-being, and self-regulation [40] – [51] .

Limitations

The result indicated a relatively low mean value for depression ( M = 3.69), perhaps because the studied population was university students. These might limit the generalization power of the results and might also explain why negative affect, commonly associated to depression, was not related to depression in the present study. Moreover, there is a potential influence of single source/single method variance on the findings, especially given the high correlation between all the variables under examination.

Conclusions

The present study highlights different results that could be arrived depending on whether researchers decide to use variables as mediators or moderators. For example, when using meditational analyses, anxiety and stress seem to be important factors that explain how the different variables used here influence depression–increases in anxiety and stress by any other factor seem to lead to increases in depression. In contrast, when moderation analyses were used, the interaction of stress and affect predicted depression and the interaction of both affectivity dimensions (i.e., positive and negative affect) also predicted depression–stress might increase depression under the condition that the individual is high in negative affectivity, in turn, negative affectivity might increase depression under the condition that the individual experiences low positive affectivity.

Acknowledgments

The authors would like to thank the reviewers for their openness and suggestions, which significantly improved the article.

Author Contributions

Conceived and designed the experiments: AAN TA. Performed the experiments: AAN. Analyzed the data: AAN DG. Contributed reagents/materials/analysis tools: AAN TA DG. Wrote the paper: AAN PR TA DG.

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Stress and Health: A Review of Psychobiological Processes

Affiliations.

1 School of Psychology, University of Leeds, Leeds LS2 9JT, United Kingdom; email: [email protected].
2 Department of Psychological Science, School of Social Ecology, University of California, Irvine, California 92697, USA; email: [email protected].
3 Division of Primary Care, School of Medicine, University of Nottingham, Nottingham NG7 2UH, United Kingdom; email: [email protected].
PMID: 32886587
DOI: 10.1146/annurev-psych-062520-122331

The cumulative science linking stress to negative health outcomes is vast. Stress can affect health directly, through autonomic and neuroendocrine responses, but also indirectly, through changes in health behaviors. In this review, we present a brief overview of ( a ) why we should be interested in stress in the context of health; ( b ) the stress response and allostatic load; ( c ) some of the key biological mechanisms through which stress impacts health, such as by influencing hypothalamic-pituitary-adrenal axis regulation and cortisol dynamics, the autonomic nervous system, and gene expression; and ( d ) evidence of the clinical relevance of stress, exemplified through the risk of infectious diseases. The studies reviewed in this article confirm that stress has an impact on multiple biological systems. Future work ought to consider further the importance of early-life adversity and continue to explore how different biological systems interact in the context of stress and health processes.

Keywords: HPA axis; allostatic load; autonomic nervous system; cortisol; genomics.

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Recent developments in stress and anxiety research

Published: 01 September 2021
Volume 128 , pages 1265–1267, ( 2021 )

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Stress and anxiety are virtually omnipresent in today´s society, pervading almost all aspects of our daily lives. While each and every one of us experiences “stress” and/or “anxiety” at least to some extent at times, the phenomena themselves are far from being completely understood. In stress research, scientists are particularly grappling with the conceptual issue of how to define stress, also with regard to delimiting stress from anxiety or negative affectivity in general. Interestingly, there is no unified theory of stress, despite many attempts at defining stress and its characteristics. Consequently, the available literature relies on a variety of different theoretical approaches, though the theories of Lazarus and Folkman ( 1984 ) or McEwen ( 1998 ) are relatively pervasive in the literature. One key issue in conceptualizing stress is that research has not always differentiated between the perception of a stimulus or a situation as a stressor and the subsequent biobehavioral response (often called the “stress response”). This is important, since, for example, psychological factors such as uncontrollability and social evaluation, i.e. factors that may influence how an individual perceives a potentially stressful stimulus or situation, have been identified as characteristics that elicit particularly powerful physiological stressful responses (Dickerson and Kemeny 2004 ). At the core of the physiological stress response is a complex physiological system, which is located in both the central nervous system (CNS) and the body´s periphery. The complexity of this system necessitates a multi-dimensional assessment approach involving variables that adequately reflect all relevant components. It is also important to consider that the experience of stress and its psychobiological correlates do not occur in a vacuum, but are being shaped by numerous contextual factors (e.g. societal and cultural context, work and leisure time, family and dyadic systems, environmental variables, physical fitness, nutritional status, etc.) and dispositional factors (e.g. genetics, personality, resilience, regulatory capacities, self-efficacy, etc.). Thus, a theoretical framework needs to incorporate these factors. In sum, as stress is considered a multi-faceted and inherently multi-dimensional construct, its conceptualization and operationalization needs to reflect this (Nater 2018 ).

The goal of the World Association for Stress Related and Anxiety Disorders (WASAD) is to promote and make available basic and clinical research on stress-related and anxiety disorders. Coinciding with WASAD’s 3rd International Congress held in September 2021 in Vienna, Austria, this journal publishes a Special Issue encompassing state-of-the art research in the field of stress and anxiety. This special issue collects answers to a number of important questions that need to be addressed in current and future research. Among the most relevant issues are (1) the multi-dimensional assessment that arises as a consequence of a multi-faceted consideration of stress and anxiety, with a particular focus on doing so under ecologically valid conditions. Skoluda et al. 2021 (in this issue) argue that hair as an important source of the stress hormone cortisol should not only be taken as a complementary stress biomarker by research staff, but that lay persons could be also trained to collect hair at the study participants’ homes, thus increasing the ecological validity of studies incorporating this important measure; (2) the incongruence between psychological and biological facets of stress and anxiety that has been observed both in laboratory and field research (Campbell and Ehlert 2012 ). Interestingly, there are behavioral constructs that do show relatively high congruence. As shown in the paper of Vatheuer et al. ( 2021 ), gaze behavior while exposed to an acute social stressor correlates with salivary cortisol, thus indicating common underlying mechanisms; (3) the complex dynamics of stress-related measures that may extend over shorter (seconds to minutes), medium (hours and diurnal/circadian fluctuations), and longer (months, seasonal) time periods. In particular, momentary assessment studies are highly qualified to examine short to medium term fluctuations and interactions. In their study employing such a design, Stoffel and colleagues (Stoffel et al. 2021 ) show ecologically valid evidence for direct attenuating effects of social interactions on psychobiological stress. Using an experimental approach, on the other hand, Denk et al. ( 2021 ) examined the phenomenon of physiological synchrony between study participants; they found both cortisol and alpha-amylase physiological synchrony in participants who were in the same group while being exposed to a stressor. Importantly, these processes also unfold over time in relation to other biological systems; al’Absi and colleagues showed in their study (al’Absi et al. 2021 ) the critical role of the endogenous opioid system and its relation to stress-related analgesia; (4) the influence of contextual and dispositional factors on the biological stress response in various target samples (e.g., humans, animals, minorities, children, employees, etc.) both under controlled laboratory conditions and in everyday life environments. In this issue, Sattler and colleagues show evidence that contextual information may only matter to a certain extent, as in their study (Sattler et al. 2021 ), the biological response to a gay-specific social stressor was equally pronounced as the one to a general social stressor in gay men. Genetic information is probably the most widely researched dispositional factor; Kuhn et al. show in their paper (Kuhn et al. 2021 ) that the low expression variant of the serotonin transporter gene serves as a risk factor for increased stress reactivity, thus clearly indicating the important role of dispositional factors in stress processing. An interesting factor combining both aspects of dispositional and contextual information is maternal care; Bentele et al. ( 2021 ) in their study are able to show that there was an effect of maternal care on the amylase stress response, while no such effect was observed for cortisol. In a similar vein, Keijser et al. ( 2021 ) showed in their gene-environment interaction study that the effects of FKBP5, a gene very closely related to HPA axis regulation, and early life stress on depressive symptoms among young adults was moderated by a positive parenting style; and (5) the role of stress and anxiety as transdiagnostic factors in mental disorders, be it as an etiological factor, a variable contributing to symptom maintenance, or as a consequence of the condition itself. Stress, e.g., as a common denominator for a broad variety of psychiatric diagnoses has been extensively discussed, and stress as an etiological factor holds specific significance in the context of transdiagnostic approaches to the conceptualization and treatment of mental disorders (Wilamowska et al. 2010 ). The HPA axis, specifically, is widely known to be dysregulated in various conditions. Fischer et al. ( 2021 ) discuss in their comprehensive review the role of this important stress system in the context of patients with post-traumatic disorder. Specifically focusing on the cortisol awakening response, Rausch and colleagues provide evidence for HPA axis dysregulation in patients diagnosed with borderline personality disorder (Rausch et al. 2021 ). As part of a longitudinal project on ADHD, Szep et al. ( 2021 ) investigated the possible impact of child and maternal ADHD symptoms on mothers’ perceived chronic stress and hair cortisol concentration; although there was no direct association, the findings underline the importance of taking stress-related assessments into consideration in ADHD studies. As the HPA axis is closely interacting with the immune system, Rhein et al. ( 2021 ) examined in their study the predicting role of the cytokine IL-6 on psychotherapy outcome in patients with PTSD, indicating that high reactivity of IL-6 to a stressor at the beginning of the therapy was associated with a negative therapy outcome. The review of Kyunghee Kim et al. ( 2021 ) also demonstrated the critical role of immune pathways in the molecular changes due to antidepressant treatment. As for the therapy, the important role of cognitive-behavioral therapy with its key elements to address both stress and anxiety reduction have been shown in two studies in this special issue, evidencing its successful application in obsessive–compulsive disorder (Ivarsson et al. 2021 ; Hollmann et al. 2021 ). Thus, both stress and anxiety are crucial transdiagnostic factors in various mental disorders, and future research needs elaborate further on their role in etiology, maintenance, and treatment.

In conclusion, a number of important questions are being asked in stress and anxiety research, as has become evident above. The Special Issue on “Recent developments in stress and anxiety research” attempts to answer at least some of the raised questions, and I want to invite you to inspect the individual papers briefly introduced above in more detail.

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Nater, U.M. Recent developments in stress and anxiety research. J Neural Transm 128 , 1265–1267 (2021). https://doi.org/10.1007/s00702-021-02410-3

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Accepted : 13 August 2021

Published : 01 September 2021

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DOI : https://doi.org/10.1007/s00702-021-02410-3

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ORIGINAL RESEARCH article

Academic stress and mental well-being in college students: correlations, affected groups, and covid-19.

$\nGeorgia Barbayannis&#x;$

1 Department of Neurology, Rutgers New Jersey Medical School, Newark, NJ, United States
2 Rutgers New Jersey Medical School, Newark, NJ, United States
3 Office for Diversity and Community Engagement, Rutgers New Jersey Medical School, Newark, NJ, United States
4 Department of Biology, The College of New Jersey, Ewing, NJ, United States

Academic stress may be the single most dominant stress factor that affects the mental well-being of college students. Some groups of students may experience more stress than others, and the coronavirus disease 19 (COVID-19) pandemic could further complicate the stress response. We surveyed 843 college students and evaluated whether academic stress levels affected their mental health, and if so, whether there were specific vulnerable groups by gender, race/ethnicity, year of study, and reaction to the pandemic. Using a combination of scores from the Perception of Academic Stress Scale (PAS) and the Short Warwick-Edinburgh Mental Well-Being Scale (SWEMWBS), we found a significant correlation between worse academic stress and poor mental well-being in all the students, who also reported an exacerbation of stress in response to the pandemic. In addition, SWEMWBS scores revealed the lowest mental health and highest academic stress in non-binary individuals, and the opposite trend was observed for both the measures in men. Furthermore, women and non-binary students reported higher academic stress than men, as indicated by PAS scores. The same pattern held as a reaction to COVID-19-related stress. PAS scores and responses to the pandemic varied by the year of study, but no obvious patterns emerged. These results indicate that academic stress in college is significantly correlated to psychological well-being in the students who responded to this survey. In addition, some groups of college students are more affected by stress than others, and additional resources and support should be provided to them.

Introduction

Late adolescence and emerging adulthood are transitional periods marked by major physiological and psychological changes, including elevated stress ( Hogan and Astone, 1986 ; Arnett, 2000 ; Shanahan, 2000 ; Spear, 2000 ; Scales et al., 2015 ; Romeo et al., 2016 ; Barbayannis et al., 2017 ; Chiang et al., 2019 ; Lally and Valentine-French, 2019 ; Matud et al., 2020 ). This pattern is particularly true for college students. According to a 2015 American College Health Association-National College Health Assessment survey, three in four college students self-reported feeling stressed, while one in five college students reported stress-related suicidal ideation ( Liu, C. H., et al., 2019 ; American Psychological Association, 2020 ). Studies show that a stressor experienced in college may serve as a predictor of mental health diagnoses ( Pedrelli et al., 2015 ; Liu, C. H., et al., 2019 ; Karyotaki et al., 2020 ). Indeed, many mental health disorders, including depression, anxiety, and substance abuse disorder, begin during this period ( Blanco et al., 2008 ; Pedrelli et al., 2015 ; Saleh et al., 2017 ; Reddy et al., 2018 ; Liu, C. H., et al., 2019 ).

Stress experienced by college students is multi-factorial and can be attributed to a variety of contributing factors ( Reddy et al., 2018 ; Karyotaki et al., 2020 ). A growing body of evidence suggests that academic-related stress plays a significant role in college ( Misra and McKean, 2000 ; Dusselier et al., 2005 ; Elias et al., 2011 ; Bedewy and Gabriel, 2015 ; Hj Ramli et al., 2018 ; Reddy et al., 2018 ; Pascoe et al., 2020 ). For instance, as many as 87% of college students surveyed across the United States cited education as their primary source of stress ( American Psychological Association, 2020 ). College students are exposed to novel academic stressors, such as an extensive academic course load, substantial studying, time management, classroom competition, financial concerns, familial pressures, and adapting to a new environment ( Misra and Castillo, 2004 ; Byrd and McKinney, 2012 ; Ekpenyong et al., 2013 ; Bedewy and Gabriel, 2015 ; Ketchen Lipson et al., 2015 ; Pedrelli et al., 2015 ; Reddy et al., 2018 ; Liu, C. H., et al., 2019 ; Freire et al., 2020 ; Karyotaki et al., 2020 ). Academic stress can reduce motivation, hinder academic achievement, and lead to increased college dropout rates ( Pascoe et al., 2020 ).

Academic stress has also been shown to negatively impact mental health in students ( Li and Lin, 2003 ; Eisenberg et al., 2009 ; Green et al., 2021 ). Mental, or psychological, well-being is one of the components of positive mental health, and it includes happiness, life satisfaction, stress management, and psychological functioning ( Ryan and Deci, 2001 ; Tennant et al., 2007 ; Galderisi et al., 2015 ; Trout and Alsandor, 2020 ; Defeyter et al., 2021 ; Green et al., 2021 ). Positive mental health is an understudied but important area that helps paint a more comprehensive picture of overall mental health ( Tennant et al., 2007 ; Margraf et al., 2020 ). Moreover, positive mental health has been shown to be predictive of both negative and positive mental health indicators over time ( Margraf et al., 2020 ). Further exploring the relationship between academic stress and mental well-being is important because poor mental well-being has been shown to affect academic performance in college ( Tennant et al., 2007 ; Eisenberg et al., 2009 ; Freire et al., 2016 ).

Perception of academic stress varies among different groups of college students ( Lee et al., 2021 ). For instance, female college students report experiencing increased stress than their male counterparts ( Misra et al., 2000 ; Eisenberg et al., 2007 ; Evans et al., 2018 ; Lee et al., 2021 ). Male and female students also respond differently to stressors ( Misra et al., 2000 ; Verma et al., 2011 ). Moreover, compared to their cisgender peers, non-binary students report increased stressors and mental health issues ( Budge et al., 2020 ). The academic year of study of the college students has also been shown to impact academic stress levels ( Misra and McKean, 2000 ; Elias et al., 2011 ; Wyatt et al., 2017 ; Liu, C. H., et al., 2019 ; Defeyter et al., 2021 ). While several studies indicate that racial/ethnic minority groups of students, including Black/African American, Hispanic/Latino, and Asian American students, are more likely to experience anxiety, depression, and suicidality than their white peers ( Lesure-Lester and King, 2004 ; Lipson et al., 2018 ; Liu, C. H., et al., 2019 ; Kodish et al., 2022 ), these studies are limited and often report mixed or inconclusive findings ( Liu, C. H., et al., 2019 ; Kodish et al., 2022 ). Therefore, more studies should be conducted to address this gap in research to help identify subgroups that may be disproportionately impacted by academic stress and lower well-being.

The coronavirus disease 19 (COVID-19) pandemic is a major stressor that has led to a mental health crisis ( American Psychological Association, 2020 ; Dong and Bouey, 2020 ). For college students, the COVID-19 pandemic has resulted in significant changes and disruptions to daily life, elevated stress levels, and mental and physical health deterioration ( American Psychological Association, 2020 ; Husky et al., 2020 ; Patsali et al., 2020 ; Son et al., 2020 ; Clabaugh et al., 2021 ; Lee et al., 2021 ; Lopes and Nihei, 2021 ; Yang et al., 2021 ). While any college student is vulnerable to these stressors, these concerns are amplified for members of minority groups ( Salerno et al., 2020 ; Clabaugh et al., 2021 ; McQuaid et al., 2021 ; Prowse et al., 2021 ; Kodish et al., 2022 ). Identifying students at greatest risk provides opportunities to offer support, resources, and mental health services to specific subgroups.

The overall aim of this study was to assess academic stress and mental well-being in a sample of college students. Within this umbrella, we had several goals. First, to determine whether a relationship exists between the two constructs of perceived academic stress, measured by the Perception of Academic Stress Scale (PAS), and mental well-being, measured by the Short Warwick-Edinburgh Mental Well-Being Scale (SWEMWBS), in college students. Second, to identify groups that could experience differential levels of academic stress and mental health. Third, to explore how the perception of the ongoing COVID-19 pandemic affected stress levels. We hypothesized that students who experienced more academic stress would have worse psychological well-being and that certain groups of students would be more impacted by academic- and COVID-19-related stress.

Materials and Methods

Survey instrument.

A survey was developed that included all questions from the Short Warwick-Edinburgh Mental Well-Being ( Tennant et al., 2007 ; Stewart-Brown and Janmohamed, 2008 ) and from the Perception of Academic Stress Scale ( Bedewy and Gabriel, 2015 ). The Short Warwick-Edinburgh Mental Well-Being Scale is a seven-item scale designed to measure mental well-being and positive mental health ( Tennant et al., 2007 ; Fung, 2019 ; Shah et al., 2021 ). The Perception of Academic Stress Scale is an 18-item scale designed to assess sources of academic stress perceived by individuals and measures three main academic stressors: academic expectations, workload and examinations, and academic self-perceptions of students ( Bedewy and Gabriel, 2015 ). These shorter scales were chosen to increase our response and study completion rates ( Kost and de Rosa, 2018 ). Both tools have been shown to be valid and reliable in college students with Likert scale responses ( Tennant et al., 2007 ; Bedewy and Gabriel, 2015 ; Ringdal et al., 2018 ; Fung, 2019 ; Koushede et al., 2019 ). Both the SWEMWBS and PAS scores are a summation of responses to the individual questions in the instruments. For the SWEMWBS questions, a higher score indicates better mental health, and scores range from 7 to 35. Similarly, the PAS questions are phrased such that a higher score indicates lower levels of stress, and scores range from 18 to 90. We augmented the survey with demographic questions (e.g., age, gender, and race/ethnicity) at the beginning of the survey and two yes/no questions and one Likert scale question about the impact of the COVID-19 pandemic at the end of our survey.

Participants for the study were self-reported college students between the ages of 18 and 30 years who resided in the United States, were fluent in English, and had Internet access. Participants were solicited through Prolific ( https://prolific.co ) in October 2021. A total of 1,023 individuals enrolled in the survey. Three individuals did not agree to participate after beginning the survey. Two were not fluent in English. Thirteen individuals indicated that they were not college students. Two were not in the 18–30 age range, and one was located outside of the United States. Of the remaining individuals, 906 were full-time students and 96 were part-time students. Given the skew of the data and potential differences in these populations, we removed the part-time students. Of the 906 full-time students, 58 indicated that they were in their fifth year of college or higher. We understand that not every student completes their undergraduate studies in 4 years, but we did not want to have a mixture of undergraduate and graduate students with no way to differentiate them. Finally, one individual reported their age as a non-number, and four individuals did not answer a question about their response to the COVID-19 pandemic. This yielded a final sample of 843 college students.

Data Analyses

After reviewing the dataset, some variables were removed from consideration due to a lack of consistency (e.g., some students reported annual income for themselves and others reported family income) or heterogeneity that prevented easy categorization (e.g., field of study). We settled on four variables of interest: gender, race/ethnicity, year in school, and response to the COVID-19 pandemic ( Table 1 ). Gender was coded as female, male, or non-binary. Race/ethnicity was coded as white or Caucasian; Black or African American; East Asian; Hispanic, Latino, or of Spanish origin; or other. Other was used for groups that were not well-represented in the sample and included individuals who identified themselves as Middle Eastern, Native American or Alaskan Native, and South Asian, as well as individuals who chose “other” or “prefer not to answer” on the survey. The year of study was coded as one through four, and COVID-19 stress was coded as two groups, no change/neutral response/reduced stress or increased stress.

Table 1 . Characteristics of the participants in the study.

Our first goal was to determine whether there was a relationship between self-reported academic stress and mental health, and we found a significant correlation (see Results section). Given the positive correlation, a multivariate analysis of variance (MANOVA) with a model testing the main effects of gender, race/ethnicity, and year of study was run in SPSS v 26.0. A factorial MANOVA would have been ideal, but our data were drawn from a convenience sample, which did not give equal representation to all groupings, and some combinations of gender, race/ethnicity, and year of study were poorly represented (e.g., a single individual). As such, we determined that it would be better to have a lack of interaction terms as a limitation to the study than to provide potentially spurious results. Finally, we used chi-square analyses to assess the effect of potential differences in the perception of the COVID-19 pandemic on stress levels in general among the groups in each category (gender, race/ethnicity, and year of study).

In terms of internal consistency, Cronbach's alpha was 0.82 for the SMEMWBS and 0.86 for the PAS. A variety of descriptors have been applied to Cronbach's alpha values. That said, 0.7 is often considered a threshold value in terms of acceptable internal consistency, and our values could be considered “high” or “good” ( Taber, 2018 ).

The participants in our study were primarily women (78.5% of respondents; Table 1 ). Participants were not equally distributed among races/ethnicities, with the majority of students selecting white or Caucasian (66.4% of responders; Table 1 ), or years of study, with fewer first-year students than other groups ( Table 1 ).

Students who reported higher academic stress also reported worse mental well-being in general, irrespective of age, gender, race/ethnicity, or year of study. PAS and SWEMWBS scores were significantly correlated ( r = 0.53, p < 0.001; Figure 1 ), indicating that a higher level of perceived academic stress is associated with worse mental well-being in college students within the United States.

Figure 1 . SWEMWBS and PAS scores for all participants.

Among the subgroups of students, women, non-binary students, and second-year students reported higher academic stress levels and worse mental well-being ( Table 2 ; Figures 2 – 4 ). In addition, the combined measures differed significantly between the groups in each category ( Table 2 ). However, as measured by partial eta squared, the effect sizes were relatively small, given the convention of 0.01 = small, 0.06 = medium, and 0.14 = large differences ( Lakens, 2013 ). As such, there were only two instances in which Tukey's post-hoc tests revealed more than one statistical grouping ( Figures 2 – 4 ). For SWEMWBS score by gender, women were intermediate between men (high) and non-binary individuals (low) and not significantly different from either group ( Figure 2 ). Second-year students had the lowest PAS scores for the year of study, and first-year students had the highest scores. Third- and fourth-year students were intermediate and not statistically different from the other two groups ( Figure 4 ). There were no pairwise differences in academic stress levels or mental well-being among racial/ethnic groups.

Table 2 . Results of the MANOVA.

Figure 2 . SWEMWBS and PAS scores according to gender (mean ± SEM). Different letters for SWEMWBS scores indicate different statistical groupings ( p < 0.05).

Figure 3 . SWEMWBS and PAS scores according to race/ethnicity (mean ± SEM).

Figure 4 . SWEMWBS and PAS scores according to year in college (mean ± SEM). Different letters for PAS scores indicate different statistical groupings ( p < 0.05).

The findings varied among categories in terms of stress responses due to the COVID-19 pandemic ( Table 3 ). For gender, men were less likely than women or non-binary individuals to report increased stress from COVID-19 (χ 2 = 27.98, df = 2, p < 0.001). All racial/ethnic groups responded similarly to the pandemic (χ 2 = 3.41, df = 4, p < 0.49). For the year of study, first-year students were less likely than other cohorts to report increased stress from COVID-19 (χ 2 = 9.38, df = 3, p < 0.03).

Table 3 . Impact of COVID-19 on stress level by gender, race/ethnicity, and year of study.

Our primary findings showed a positive correlation between perceived academic stress and mental well-being in United States college students, suggesting that academic stressors, including academic expectations, workload and grading, and students' academic self-perceptions, are equally important as psychological well-being. Overall, irrespective of gender, race/ethnicity, or year of study, students who reported higher academic stress levels experienced diminished mental well-being. The utilization of well-established scales and a large sample size are strengths of this study. Our results extend and contribute to the existing literature on stress by confirming findings from past studies that reported higher academic stress and lower psychological well-being in college students utilizing the same two scales ( Green et al., 2021 ; Syed, 2021 ). To our knowledge, the majority of other prior studies with similar findings examined different components of stress, studied negative mental health indicators, used different scales or methods, employed smaller sample sizes, or were conducted in different countries ( Li and Lin, 2003 ; American Psychological Association, 2020 ; Husky et al., 2020 ; Pascoe et al., 2020 ; Patsali et al., 2020 ; Clabaugh et al., 2021 ; Lee et al., 2021 ; Lopes and Nihei, 2021 ; Yang et al., 2021 ).

This study also demonstrated that college students are not uniformly impacted by academic stress or pandemic-related stress and that there are significant group-level differences in mental well-being. Specifically, non-binary individuals and second-year students were disproportionately impacted by academic stress. When considering the effects of gender, non-binary students, in comparison to gender-conforming students, reported the highest stress levels and worst psychological well-being. Although there is a paucity of research examining the impact of academic stress in non-binary college students, prior studies have indicated that non-binary adults face adverse mental health outcomes when compared to male and female-identifying individuals ( Thorne et al., 2018 ; Jones et al., 2019 ; Budge et al., 2020 ). Alarmingly, Lipson et al. (2019) found that gender non-conforming college students were two to four times more likely to experience mental health struggles than cisgender students ( Lipson et al., 2019 ). With a growing number of college students in the United States identifying as as non-binary, additional studies could offer invaluable insight into how academic stress affects this population ( Budge et al., 2020 ).

In addition, we found that second-year students reported the most academic-related distress and lowest psychological well-being relative to students in other years of study. We surmise this may be due to this group taking advanced courses, managing heavier academic workloads, and exploring different majors. Other studies support our findings and suggest higher stress levels could be attributed to increased studying and difficulties with time management, as well as having less well-established social support networks and coping mechanisms compared to upperclassmen ( Allen and Hiebert, 1991 ; Misra and McKean, 2000 ; Liu, X et al., 2019 ). Benefiting from their additional experience, upperclassmen may have developed more sophisticated studying skills, formed peer support groups, and identified approaches to better manage their academic stress ( Allen and Hiebert, 1991 ; Misra and McKean, 2000 ). Our findings suggest that colleges should consider offering tailored mental health resources, such as time management and study skill workshops, based on the year of study to improve students' stress levels and psychological well-being ( Liu, X et al., 2019 ).

Although this study reported no significant differences regarding race or ethnicity, this does not indicate that minority groups experienced less academic stress or better mental well-being ( Lee et al., 2021 ). Instead, our results may reflect the low sample size of non-white races/ethnicities, which may not have given enough statistical power to corroborate. In addition, since coping and resilience are important mediators of subjective stress experiences ( Freire et al., 2020 ), we speculate that the lower ratios of stress reported in non-white participants in our study (75 vs. 81) may be because they are more accustomed to adversity and thereby more resilient ( Brown, 2008 ; Acheampong et al., 2019 ). Furthermore, ethnic minority students may face stigma when reporting mental health struggles ( Liu, C. H., et al., 2019 ; Lee et al., 2021 ). For instance, studies showed that Black/African American, Hispanic/Latino, and Asian American students disclose fewer mental health issues than white students ( Liu, C. H., et al., 2019 ; Lee et al., 2021 ). Moreover, the ability to identify stressors and mental health problems may manifest differently culturally for some minority groups ( Huang and Zane, 2016 ; Liu, C. H., et al., 2019 ). Contrary to our findings, other studies cited racial disparities in academic stress levels and mental well-being of students. More specifically, Negga et al. (2007) concluded that African American college students were more susceptible to higher academic stress levels than their white classmates ( Negga et al., 2007 ). Another study reported that minority students experienced greater distress and worse mental health outcomes compared to non-minority students ( Smith et al., 2014 ). Since there may be racial disparities in access to mental health services at the college level, universities, professors, and counselors should offer additional resources to support these students while closely monitoring their psychological well-being ( Lipson et al., 2018 ; Liu, C. H., et al., 2019 ).

While the COVID-19 pandemic increased stress levels in all the students included in our study, women, non-binary students, and upperclassmen were disproportionately affected. An overwhelming body of evidence suggests that the majority of college students experienced increased stress levels and worsening mental health as a result of the pandemic ( Allen and Hiebert, 1991 ; American Psychological Association, 2020 ; Husky et al., 2020 ; Patsali et al., 2020 ; Son et al., 2020 ; Clabaugh et al., 2021 ; Lee et al., 2021 ; Yang et al., 2021 ). Our results also align with prior studies that found similar subgroups of students experience disproportionate pandemic-related distress ( Gao et al., 2020 ; Clabaugh et al., 2021 ; Hunt et al., 2021 ; Jarrett et al., 2021 ; Lee et al., 2021 ; Chen and Lucock, 2022 ). In particular, the differences between female students and their male peers may be the result of different psychological and physiological responses to stress reactivity, which in turn may contribute to different coping mechanisms to stress and the higher rates of stress-related disorders experienced by women ( Misra et al., 2000 ; Kajantie and Phillips, 2006 ; Verma et al., 2011 ; Gao et al., 2020 ; Graves et al., 2021 ). COVID-19 was a secondary consideration in our study and survey design, so the conclusions drawn here are necessarily limited.

The implications of this study are that college students facing increased stress and struggling with mental health issues should receive personalized and specific mental health services, resources, and support. This is particularly true for groups that have been disproportionately impacted by academic stress and stress due to the pandemic. Many students who experience mental health struggles underutilize college services due to cost, stigma, or lack of information ( Cage et al., 2020 ; Lee et al., 2021 ). To raise awareness and destigmatize mental health, colleges can consider distributing confidential validated assessments, such as the PAS and SWEMWBS, in class and teach students to self-score ( Lee et al., 2021 ). These results can be used to understand how academic stress and mental well-being change over time and allow for specific and targeted interventions for vulnerable groups. In addition, teaching students healthy stress management techniques has been shown to improve psychological well-being ( Alborzkouh et al., 2015 ). Moreover, adaptive coping strategies, including social and emotional support, have been found to improve the mental well-being of students, and stress-reduction peer support groups and workshops on campus could be beneficial in reducing stress and improving the self-efficacy of students ( Ruthig et al., 2009 ; Baqutayan, 2011 ; Bedewy and Gabriel, 2015 ; Freire et al., 2020 ; Green et al., 2021 ; Suresh et al., 2021 ). Other interventions that have been effective in improving the coping skills of college students include cognitive-behavioral therapy, mindfulness mediation, and online coping tools ( Kang et al., 2009 ; Regehr et al., 2013 ; Molla Jafar et al., 2015 ; Phang et al., 2015 ; Houston et al., 2017 ; Yusufov et al., 2019 ; Freire et al., 2020 ). Given that resilience has also been shown to help mediate stress and improve mental well-being during the COVID-19 pandemic, interventions focusing on enhancing resilience should be considered ( Surzykiewicz et al., 2021 ; Skalski et al., 2022 ). Telemental health resources across colleges can also be implemented to reduce stigma and improve at-risk students' access to care ( Toscos et al., 2018 ; Hadler et al., 2021 ). University campuses, professors, and counselors should consider focusing on fostering a more equitable and inclusive environment to encourage marginalized students to seek mental health support ( Budge et al., 2020 ).

Limitations

While our study has numerous strengths, including using standardized instruments and a large sample size, this study also has several limitations due to both the methodology and sample. First, the correlational study design precludes making any causal relationships ( Misra and McKean, 2000 ). Thereby, our findings should be taken in the context of academic stress and mental well-being, and recognize that mental health could be caused by other non-academic factors. Second, the PAS comprised only the perception of responses to academic stress, but stress is a multi-factorial response that encompasses both perceptions and coping mechanisms to different stressors, and the magnitude of stress varies with the perception of the degree of uncontrollability, unpredictability, or threat to self ( Miller, 1981 ; Hobfoll and Walfisch, 1984 ; Lazarus and Folkman, 1984 ; Wheaton, 1985 ; Perrewé and Zellars, 1999 ; Schneiderman et al., 2005 ; Bedewy and Gabriel, 2015 ; Schönfeld et al., 2016 ; Reddy et al., 2018 ; Freire et al., 2020 ; Karyotaki et al., 2020 ). Third, the SWEMSBS used in our study and the data only measured positive mental health. Mental health pathways are numerous and complex, and are composed of distinct and interdependent negative and positive indicators that should be considered together ( Margraf et al., 2020 ). Fourth, due to the small effect sizes and unequal representation for different combinations of variables, our analysis for both the PAS and SWEMSBS included only summed-up scales and did not examine group differences in response to the type of academic stressors or individual mental health questions.

An additional limitation is that the participants in our study were a convenience sample. The testing service we used, prolific.co, self-reports a sample bias toward young women of high levels of education (i.e., WEIRD bias) ( Team Prolific, 2018 ). The skew toward this population was observed in our data, as 80% of our participants were women. While we controlled for these factors, the possibility remains that the conclusions we draw for certain groups, such as nonbinary students, ethnic/racial minorities, and men, may not be as statistically powerful as they should be. Moreover, our pre-screening was designed to recruit undergraduate level, English-speaking, 18–30-year-olds who resided in the United States. This resulted in our participant demographics being skewed toward the WEIRD bias that was already inherent in the testing service we used. Future research will aim to be more inclusive of diverse races/ethnicities, sexual orientations, languages, educational backgrounds, socioeconomic backgrounds, and first-generation college students.

Another limitation of our study is the nature of satisficing. Satisficing is a response strategy in which a participant answers a question to satisfy its condition with little regard to the quality or accuracy of the answer ( Roberts et al., 2019 ). Anonymous participants are more likely to satisfice than respondents who answer the question face-to-face ( Krosnick et al., 2002 ). We sought to mitigate satisficing by offering financial incentives to increase response rates and decrease straight-lining, item skipping, total missing items, and non-completion ( Cole et al., 2015 ). Concerns of poor data quality due to surveys offering financial incentives found little evidence to support that claim and may do the opposite ( Cole et al., 2015 ). On the other hand, social desirability bias may have influenced the participant's self-reported responses, although our anonymous survey design aimed to reduce this bias ( Joinson, 1999 ; Kecojevic et al., 2020 ).

Future Studies

Future studies should replicate our study to validate our results, conduct longitudinal cohort studies to examine well-being and perceived academic stress over time, and aim for a more representative student sample that includes various groups, including diverse races/ethnicities, sexual orientations, socioeconomic backgrounds, languages, educational levels, and first-generation college students. Additionally, these studies should consider examining other non-academic stressors and students' coping mechanisms, both of which contribute to mental health and well-being ( Lazarus and Folkman, 1984 ; Freire et al., 2020 ). Further explorations of negative and other positive indicators of mental health may offer a broader perspective ( Margraf et al., 2020 ). Moreover, future research should consider extending our work by exploring group differences in relation to each factor in the PAS (i.e., academic expectations, workload and examinations, and self-perception of students) and SWEMBS to determine which aspects of academic stress and mental health were most affected and allow for the devising of targeted stress-reduction approaches. Ultimately, we hope our research spurs readers into advocating for greater academic support and access to group-specific mental health resources to reduce the stress levels of college students and improve their mental well-being.

Utilizing two well-established scales, our research found a statistically significant correlation between the perceived academic stress of university students and their mental well-being (i.e., the higher the stress, the worse the well-being). This relationship was most apparent among gender and grade levels. More specifically, non-binary and second-year students experienced greater academic burden and lower psychological well-being. Moreover, women, non-binary students, and upper-level students were disproportionately impacted by stress related to the COVID-19 pandemic.

Studies regarding broad concepts of stress and well-being using a questionnaire are limited, but our study adds value to the understanding of academic stress as a contributor to the overall well-being of college students during this specific point in time (i.e., the COVID-19 pandemic). Competition both for admission to college ( Bound et al., 2009 ) and during college ( Posselt and Lipson, 2016 ) has increased over time. Further, selective American colleges and universities draw applicants from a global pool. As such, it is important to document the dynamics of academic stress with renewed focus. We hope that our study sparks interest in both exploring and funding in-depth and well-designed psychological studies related to stress in colleges in the future.

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 Institutional Review Board at Rutgers University. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

GB and MB contributed to conceptualization, study design, IRB application, manuscript drafting, and revision. XZ participated in the conceptualization and design of the questionnaires. HB participated in subject recruitment and questionnaire collection. KP contributed to data analysis, table and figure preparation, manuscript drafting, and revision. XM contributed to conceptualization, study design, IRB application, supervision of the project, manuscript drafting, and revision. All authors contributed to the article and approved the submitted version.

This study was made possible by a generous donation from the Knights of Columbus East Hanover Chapter in New Jersey.

Conflict of Interest

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

Publisher's Note

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

Acknowledgments

The authors wish to thank Shivani Mehta and Varsha Garla for their assistance with the study. We also thank all the participants for their efforts in the completion of the study.

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Keywords: academic stress, well-being, college students, Perception of Academic Stress, Short Warwick-Edinburgh Mental Well-Being Scale, COVID-19

Citation: Barbayannis G, Bandari M, Zheng X, Baquerizo H, Pecor KW and Ming X (2022) Academic Stress and Mental Well-Being in College Students: Correlations, Affected Groups, and COVID-19. Front. Psychol. 13:886344. doi: 10.3389/fpsyg.2022.886344

Received: 28 February 2022; Accepted: 20 April 2022; Published: 23 May 2022.

Reviewed by:

Copyright © 2022 Barbayannis, Bandari, Zheng, Baquerizo, Pecor and Ming. 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: Keith W. Pecor, pecor@tcnj.edu

† These authors have contributed equally to this work and share first authorship

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.

A-Z Publications

Annual Review of Psychology

Volume 72, 2021, review article, stress and health: a review of psychobiological processes.

Daryl B. O'Connor 1 , Julian F. Thayer 2 , and Kavita Vedhara 3
View Affiliations Hide Affiliations Affiliations: 1 School of Psychology, University of Leeds, Leeds LS2 9JT, United Kingdom; email: [email protected] 2 Department of Psychological Science, School of Social Ecology, University of California, Irvine, California 92697, USA; email: [email protected] 3 Division of Primary Care, School of Medicine, University of Nottingham, Nottingham NG7 2UH, United Kingdom; email: [email protected]
Vol. 72:663-688 (Volume publication date January 2021) https://doi.org/10.1146/annurev-psych-062520-122331
First published as a Review in Advance on September 04, 2020
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Published: 20 August 2024

A rank ordering and analysis of four cognitive-behavioral stress-management competencies suggests that proactive stress management is especially valuable

Robert Epstein ORCID: orcid.org/0000-0002-7484-6282 1 ,
Jessica Aceret 1 ,
Ciara Giordani 1 ,
Vanessa R. Zankich ORCID: orcid.org/0000-0003-2375-6209 1 &
Lynette Zhang ORCID: orcid.org/0000-0001-9435-6312 1

Scientific Reports volume 14 , Article number: 19224 ( 2024 ) Cite this article

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Human behaviour

The main objective of this study was to determine the relative value of four cognitive-behavioral competencies that have been shown in empirical studies to be associated with effective stress management. Based on a review of relevant psychological literature, we named the competencies as follows: Manages or Reduces Sources of Stress, Manages Thoughts, Plans and Prevents, and Practices Relaxation Techniques. We measured their relative value by examining data obtained from a diverse convenience sample of 18,895 English-speaking participants in 125 countries (65.0% from the U.S. and Canada) who completed a new inventory of stress-management competencies. We assessed their relative value by employing a concurrent study design, which also allowed us to assess the validity of the new instrument. Regression analyses were used to rank order the four competencies according to how well they predicted desirable outcomes. Both regression and factor analyses pointed to the importance of proactive stress-management practices over reactive methods, but we note that the correlational design of our study has no implications for the possible causal effects of these methods. Questionnaire scores were strongly associated with self-reported happiness and also significantly associated with personal success, professional success, and general level of stress. Data were collected between 2007 and 2022, but we found no effect for time. The study supports the value of stress-management training, and it also suggests that moderate levels of stress may not be as beneficial as previously thought.

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Introduction.

The main objectives of the present study were to (a) introduce and evaluate a new instrument—the Epstein Stress Management Inventory for individuals (ESMI-i)—for assessing four cognitive-behavioral competencies that have been shown in empirical studies to be associated with effective stress management, (b) analyze data from a large, international group of English-speaking people who completed the new questionnaire online, (c) compare the relative value of the four competencies, and (d) analyze the data from a demographic perspective. By using a competencies approach, we are providing both the public and practitioners with a practical tool for measuring and potentially improving practices associated with effective stress management.

The ESMI-i joins a large number of test instruments and tools that have been developed since the 1950s to help people deal with various kinds of mental health challenges. It is also fairly unique in some respects. For one thing, it was designed for the general population, rather than for a particular group, and it was designed to measure broad competency areas rather than skills that might be helpful mainly in specific contexts. Similar inventories have been designed, for example, to assist individuals who regularly face stress in their work environments 1 , 2 , 3 . Other inventories have been designed to measure people’s coping skills in response to specific stressors 4 , 5 .

The ESMI-i is also available online, non-commercial, and free of charge, maintained by a nonprofit organization. Validated instruments measuring the “level” of stress people feel, such as the Holmes and Rahe Stress Scale 6 and the Perceived Stress Scale 7 , are currently available online, and so are numerous non-validated tests of this sort, accessible at websites such as OkCupid.com. Validated inventories that assess “coping styles” also exist, such as the Multidimensional Coping Inventory 8 . These instruments differ from the ESMI-i in that they are designed to classify people, while we are careful to avoid labeling those who complete the ESMI-i; we will explore this matter later in more detail.

Other validated inventories measure cognitive-behavioral skills and overlap to some extent with the ESMI-i. However, most of these instruments were developed with cognitive-behavioral therapy (CBT) in mind and thus may not be ideal measures of stress-management competencies per se. In addition, many of these inventories, such as the Cognitive-Behavioral Therapy Skills Questionnaire 9 , the Skills of Cognitive Therapy measure 10 , and the CBT Skills Checklist 11 , include items that sometimes conflate skills with reductions in symptoms of depression 12 .

Validated inventories that measure stress-management or coping skills exist, such as the Proactive Coping Inventory 13 , 14 , Chronic Pain Coping Inventory 15 , 16 , 17 , 18 , 19 , the Coping Inventory for Stressful Situations 20 , 21 , 22 , the COPE Inventory 23 , 24 , 25 , the Coping with Stress Scale 26 , the Coping Intelligence Questionnaire 27 , the Dispositional Resilience Scale 28 , 29 , the Stress Mindset Scale 30 , 31 , 32 , and the Performance of Cognitive Therapy Strategies measure 33 . However, they are either not available online or, in some cases, they can only be administered by licensed professionals or trained observers 12 . Because many people are now relying on the internet as a major resource for self-evaluation 34 , 35 , 36 , 37 , we believe that it is important to make validated tests widely available online. Self-help books that teach similar stress-management techniques are available to members of the general public, such as Mind Over Mood 38 ; however, such books are not free, and they take much longer to read than it takes to complete an online inventory.

By stress, we are referring to internal, usually unpleasant physiological and psychological states that are often induced by perceived environmental threats or environmental demands, which are sometimes called “stressors” 39 , 40 , 41 , 42 , 43 . Actual environmental threats do not necessarily produce stress reactions, and the same stressor can cause different stress reactions in different people—or even no stress reaction at all 40 , 41 .

We are not concerned in the present paper with the definitional ambiguities in the terms “stress” and “stressor.” Rather, we are focusing on stress-management practices—thoughts and behaviors that reduce stress—and we are especially interested in practices of this sort that can be both measured and trained by coaches, therapists, or counselors. The instrument we developed focuses on four classes of such behaviors; we define each class of behaviors to be a stress-management competency. The term “coping skills” is sometimes used to describe practices of this sort 44 . For purposes of the present discussion, we will avoid using that term, as well as the related term “coping strategies,” 45 , because we view these terms as referring mainly to reactive practices. In the present study, we will be measuring both reactive and proactive competencies, and we will use our data to compare the relative value of each type.

We believe that it is important to identify and measure stress-management competencies—especially those that can be trained—because of their enormous practical value. Stress-management competencies not only reduce levels of reported stress but have also been associated with increased functioning and well-being, as well as with improvements in mental, emotional, and physical health 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 . Unmanaged stress is costly, both in personal and economic terms 60 , 65 , 66 , 67 , 68 , 69 , 70 . Fortunately, stress management can be trained, and benefits of such training have been demonstrated 46 , 71 , 72 , 73 , 74 , 75 , 76 , 77 . Levels of stress can also be measured 78 , 79 , 80 , 81 , 82 , 83 , and so can stress-management proficiency 17 , 18 , 21 , 24 , 27 , 28 , 30 , 84 , 85 , 86 , 87 .

The nature and value of a competencies approach

Many, if not most, test instruments used by psychologists are based on theories, and those theories are often about hypothetical constructs such as intelligence or personality traits. The methodology for developing and evaluating such instruments is quite advanced. Factor and item analyses are often employed, for example, to remove items that do not improve the statistical validity of the construct measures.

The ESMI-i is not a theory-based questionnaire, and it does not introduce or attempt to measure constructs. The ESMI-i is a competency test, developed in the spirit of a testing approach strongly advocated by David McClelland, notably in a seminal paper published in The American Psychologist in 1973 88 ; other experts have also been strong advocates of this approach over the years 89 , 90 . A competencies approach to understanding and improving human performance is widely used in multiple fields and arenas—by the military 91 , in healthcare 92 , in business 93 , 94 , in education 95 , and in other areas in which human performance is important 96 , 97 , 98 , 99 , 100 , 101 .

As McClelland and others have pointed out, a competencies approach to understanding human functioning has some practical advantages over more traditional psychological approaches. Before he and his colleagues applied this approach to the study of leadership, for example, both businesses and armies had long been searching for “natural born leaders,” and such people exist, of course 102 . But leadership, along with many other areas of human functioning—even intelligence 88 —can be broken down into a number of skill areas that not only can be observed and measured; they can often be trained. Those skill areas, such as the set of skills one needs to drive a car, are not hypothetical, and they are also not constructs. They are sets of behaviors, many of which are observable. Tests that measure traits or constructs often leave people with labels, such as the trait measures yielded by the ubiquitous Minnesota Multiphasic Personality Inventory, and labels can be both demoralizing 103 , 104 and self-fulfilling 105 , 106 , 107 , 108 . In contrast, competency scores simply tell people where they stand at the moment; they are often used in combination with training programs that employ questionnaires to measure post-training improvements.

Development of the ESMI-i questionnaire

The ESMI-i measures “competencies,” a term that is typically defined as “the knowledge, skills, abilities, and behaviors that contribute to individual and organizational performance” 109 —specifically those competencies that are mainly cognitive or behavioral in nature and that might help people to reduce, eliminate, or avoid stress. Beginning in 2001, the first author of this paper, with the help of his students, set about searching the psychology literature to find peer-reviewed papers that identified skills, behavior, or knowledge that were associated with successful stress management, the goal being to use these papers to develop a test instrument that could measure the strength of such competencies. We were especially interested in competencies of the sort that therapists or counselors might be likely to teach—those, as opposed to stress-management techniques that might be taught by medical personnel, nutritionists, or other experts.

Over time, we developed a questionnaire that measured four relatively distinct cognitive-behavioral competencies: Manages or Reduces Sources of Stress, Manages Thoughts, Plans and Prevents, and Practices Relaxation Techniques. Table 1 shows the competencies, definitions, the scored items for each competency, and a list of relevant references. Below are examples of how studies published between 2001 and 2007 were employed to develop the four competency categories and to compose a total of 24 scored items. Table 1 also includes relevant references found after the questionnaire was posted online in May of 2007.

When possible, we tried to create items that “pinpoint” specific behaviors. Items that pinpoint behavior are good predictors of actual behavior 94 , 110 , 111 , 112 . So instead of saying, “I’m great at making people laugh,” we say, “I often try to use humor to diffuse tension.” That wording tells us about behavior and also, to some extent, about the frequency of that behavior. We were not able to do this for every item, but we used pinpointing as a standard for item composition.

Competency 1: manages or reduces sources of stress

In a year-long study with 100 adult residents of the Alameda County area of California, Folkman and Lazarus 113 interviewed participants once every four weeks to determine what strategies they employed to help them cope with the stress they experienced as a result of activities of daily living. The researchers were guided by Richard Lazarus’ cognitive-phenomenological approach to analyzing psychological stress 114 . One of two types of coping strategies analyzed in the 1980 study was labeled “problem-focused” (p. 223), and it suggested, along with other studies (see below), that one robust category of stress management was managing sources of stress. In defining this strategy, the authors spoke of “management or alteration of the person-environment relationship that is the source of stress” (p. 223), “cognitive problem-solving efforts and behavioral strategies for altering or managing the source of the problem” (p. 224), and other actions that reduced or eliminated sources of stress.

We also used language from the Folkman and Lazarus 113 study to help us construct one of our questionnaire items. In elaborating on problem-focused coping strategies, the authors stated that these strategies “include seeking information, trying to get help, inhibiting action, and taking direct action” (p. 229). Item 2 on the ESMI-i is, “I’m comfortable seeking help from other people” (Table 1 ).

Problem-focused coping strategies were also analyzed in a 2006 study with 67 families of young children with disabilities. Stoneman and Gavidia-Payne 115 found that marital harmony was higher when fathers in these families employed problem-focused strategies to overcome challenges, thus reducing sources of stress.

Competency 2: manages thoughts

Thought management—often taught by counselors and therapists as part of therapeutic treatment—can be a powerful means for reducing or eliminating stress. “Reframing,” a technique most often associated with Albert Ellis 116 and a main component of rational emotive behavior therapy 117 , is just one example of a thought-management technique. Others include cognitive restructuring 118 , 119 , 120 , 121 , cognitive reappraisal 47 , 54 , 64 , cognitive redefinition 26 , and cognitive defusion 122 , 123 , 124 . Most mindfulness techniques, such as acceptance and commitment therapy, incorporate methods for managing thoughts 125 . Cognitive-behavioral therapy, developed by Aaron Beck in the 1960s 126 , 127 , also emphasizes techniques aimed at reducing automatic thoughts and cognitive distortions 128 . Generally speaking, people have little control over the undesirable things that happen to them, but, in theory, they have—or could be trained to have—complete control over how they interpret such events; hence, the logic of using thoughts to manage stress.

Murphy 120 conducted a meta-analysis of 64 studies that examined ways in which people managed workplace stress. The most common methods used to manage stress in work settings were meditation, muscle relaxation, cognitive-behavioral skills, and biofeedback. Cognitive-behavioral techniques, which included “thought restructuring” and other methods, proved to be especially effective in reducing what the author called “psychologic” stress (as opposed to “physiologic” stress). The Murphy study proved to be especially helpful in generating possible items for inclusion in the ESMI-i. Items based in part or in full on content from the Murphy study include, “I often reinterpret events in order to lower my stress” (item 5), “Negative events can always be reinterpreted so that they seem more positive” (item 9), and “I regularly examine and try to correct any irrational beliefs I might have” (item 10).

A comprehensive literature review by Giga et al. 129 also proved helpful in developing our Manages Thoughts competency category (as well as the competency that follows—see below). Focusing again on the work environment, the authors found that thought restructuring, reframing, and similar techniques were helpful in managing stress. Language from the Giga et al. 129 study was helpful in developing items 5 and 9 (see above paragraph).

An experimental study by Keogh et al. 119 also helped us develop this competency category. 209 students in the UK were randomly assigned to either a cognitive-behaviorally oriented treatment group or a no-treatment control group. Stress reduction was significantly higher in the treatment group, with students being taught, among other things, to replace irrational beliefs (such as “I am bad at taking tests” [p. 342]) with more rational ones (such as “I can take tests, if I prepare appropriately” [p. 342]). This study helped us to develop items such as the reverse-scored item, “My thinking is as clear and as rational as it can possibly be” (item 11), as well as item 10 (noted above).

Competency 3: plans and prevents

Once again, the Giga et al. 129 literature review was helpful in developing this category. It spoke specifically about the value of “plan[ning] to prevent and manage stress,” and it helped us develop two items: “I have a clear picture of how I’d like my life to proceed” (item 15) and “I try to fight stress before it starts” (item 17).

McWilliams et al. 22 studied a group of 298 outpatients with major depressive disorder, having them complete multiple questionnaires, such as the Coping Inventory for Stressful Situations 21 . They concluded that planning and scheduling, among other strategies, were associated with lower levels of psychological stress. Content from this article helped us compose two ESMI-i items: “I keep an up-to-date list of things I’m supposed to do” (item 7), and “I spend a few moments each morning planning my day” (item 22). In addition, the Folkman et al. study 130 , mentioned earlier, helped us compose item 18: “I try to avoid destructive ways of dealing with stress.”

Competency 4: practices relaxation techniques

The value of practicing various relaxation techniques in managing stress began to be established even before the concept of “biological stress” was introduced in the early 1900s and before Hans Selye’s breakthrough research in the 1930s on the relationship between the stress response and disease 131 . Edmund Jacobson’s classic book, Progressive Relaxation 132 —based on techniques he had been developing and studying since 1915—asserted that progressive muscle relaxation exercises had multiple benefits, including improvements in memory, attention, thinking, and emotions 133 .

Later sources have repeatedly confirmed the value that various relaxation techniques have in stress management. For example, Pawlow and Jones 134 conducted a controlled experiment on progressive muscle relaxation with 55 undergraduate students, concluding that the experimental group benefitted in multiple ways from the relaxation exercises. Among other benefits, the exercises “produced significantly reduced self ratings of perceived stress and state anxiety [and] significantly increased ratings of relaxation from immediately before to immediately after the training” (p. 381). In contrast, quiet sitting (practiced by the control group) produced no such benefits. The Pawlow and Jones 134 study helped us to compose the questionnaire item, “I regularly tense and relax my muscles as a way of fighting stress” (item 13).

Smith et al. 135 compared progressive muscle relaxation to yoga with 131 adults from South Australia in a randomized study, concluding that yoga (which included breathing exercises and postures) was as effective as muscle relaxation in producing positive outcomes, including reductions in stress and anxiety. This study helped us develop three ESMI-i items: “I frequently use special breathing techniques to help me relax” (item 1), “I regularly tense and relax my muscles as a way of fighting stress” (item 13), and the reverse-scored item, “Breathing is a very hard thing to control” (item 20).

Dummy items and internal consistency score (ICS)

As is common in competency questionnaires designed by the first author 96 , 98 , 99 , 101 , the ESMI-i includes one dummy item for each of the four competencies assessed. Each dummy item rephrases a corresponding scored item. The purpose of having these dummy pairs is to be able, at the end of each user session, to quickly compute how closely the answers within each pair match each other. The match is computed using a modified version of Cohen’s kappa coefficient, a standard measure of inter-observer agreement 136 (see Supplementary Text S1 to compare the two formulas). We call this calculation our “internal consistency score” (ICS). In theory, if the ICS is low, we can ask a user to retake the questionnaire. In the present study, no users were asked to retake the questionnaire based on a low ICS. Instead, we elected to examine this issue as part of the data cleaning process (see below).

Participants

Before data cleaning, our dataset included 21,398 people who had completed the ESMI-i between May 3, 2007, and June 1, 2022. If someone completed the questionnaire more than once on the same day, we preserved only the first instance in which more than half the questionnaire items were answered. We also removed all cases in which self-reported English fluency was below 6 (on a scale from 1 to 10, where 10 indicated the highest level of fluency). After cleaning, 18,895 participants remained in the dataset.

The self-reported demographic characteristics of the participants were as follows (for details, see Table 2 ): Age ranged from 12 to 83 ( M = 30.4 [ SD = 14.1]). Because the ESMI-i has a Flesch–Kincaid reading level of 5.8, and because most 11-year-old children in the U.S. have completed the fifth grade, we received Institutional Review Board (IRB) approval for participants age 11 and over; however, our youngest participants (after cases were removed because of low self-reported fluency levels) were 12 ( n = 19).

After cleaning by English fluency and duplicate cases, we had no need to remove cases because of low ICSs. We made this determination based on the value of Cronbach’s alpha for groups of people with differing ICSs. The group of people with ICSs between 0.4 and 0.5 (or, more precisely, 0.4 < ICS ≤ 0.5) had an alpha of 0.71, and with each successive group of people with higher ICSs (0.5–0.6, 0.6–0.7, 0.7–0.8, 0.8–0.9, 0.9–1.0), alpha increased (range 0.71 to 0.88). Because alphas greater than 0.7 are normally considered acceptable in test development 137 , 138 , 139 , using this criterion, we could not justify removing cases based on low ICSs. A small number of people (40 in total, 0.21% of the total N ) had ICSs less than 0.4, but that was too few people for us to compute an alpha. Because we had no objective reason to eliminate these people from our study, we took the conservative course of action and let them remain (see Supplementary Table S1 and Supplementary Figure S1 for details).

Overall, 12,242 (64.8%) of our participants identified themselves as female, 6,565 (34.7%) as male, and 88 (0.5%) as other. Racial and ethnic background was as follows: 128 (0.7%) of our participants identified themselves as American Indian, 2,379 (12.6%) as Asian, 1,165 (6.2%) as Black, 1,107 (5.9%) as Hispanic, 13,097 (69.3%) as White, and 869 (4.6%) as Other; 150 individuals (0.8%) did not answer this question. Overall, 29.9% of the individuals in the sample identified themselves as non-White.

Regarding level of education completed: 2,115 (11.2%) reported not having a high school degree; 5,857 (31.0%) reported completing high school; 1,844 (9.8%) reported having an associates degree; 5,361 (28.4%) reported having completed college; 2,952 (15.6%) reported having a master’s degree; 644 (3.4%) reported having a doctoral degree; and 122 (0.6%) did not answer the question. Regarding sexual orientation: 16,713 (88.5%) identified themselves as straight; 558 (3.0%) as gay or lesbian; 1,211 (6.4%) as bisexual; 25 (0.1%) as other, and 388 (2.1%) did not answer this question. Regarding country of origin: 12,279 (65.0%) were from the United States and Canada; 5,712 (30.2%) were from 123 other countries; and 904 (4.8%) did not answer this question.

Study design

The present investigation utilized a “concurrent study design” that used criterion validity evidence, consistent with guidelines in the most recent edition of Standards for Educational and Psychological Testing 140 , prepared jointly by the American Educational Research Association, the American Psychological Association, and the National Council on Measurement in Education. Specifically, we sought to measure the strength of the relationships between our questionnaire scores and the scores on our self-reported criterion questions. This design is called “concurrent” because we obtained questionnaire scores and criterion measures at the same time, a strategy that avoids possible temporal confounds. Results from studies employing this design are considered especially robust when the pattern of relationships between questionnaire scores and criterion measures proves to be consistent across different demographic groups.

As noted above, the questionnaire employed in the study measured four cognitive-behavioral competencies. A total score was calculated, with higher scores indicating greater stress-management competence. Separate scores were also calculated for each of the competencies. We report all questionnaire scores as a percentage of possible maximum scores rather than as raw scores. We also calculated scores for each of the four criterion questions (see Procedure below).

Participants were first presented with brief instructions informing them, for example, that there are no right or wrong answers to the items on the questionnaire. They were then asked some basic demographic questions, following which they were asked four criterion questions regarding desirable outcomes that are sometimes associated with successful stress management, namely: How happy and fulfilled are you? How much success have you had in your personal life? How much success have you had in your professional life? How stressed do you generally feel? Answers were given on a 10-point Likert scale from Low to High (see Supplementary Figures S2-S4 for the demographic questions and the questionnaire items). After completing the 28-item questionnaire (24 items were scored), participants were given their overall questionnaire score as well as scores on the four subscales and detailed explanations about the nature of each competency (see Supplementary Fig. S5 for a screenshot of the results page). Primary access to the questionnaire was at the URL https://MyStressManagementSkills.com . Over time, links to the questionnaire appeared elsewhere on the internet, a process over which we had no control. We also had no control over the demographic characteristics of the participants (see Discussion).

Ethics statement

The federally registered Institutional Review Board (IRB) of the sponsoring institution (American Institute for Behavioral Research and Technology) approved this study with exempt status and a waiver of the requirement for informed consent under U.S. Department of Health and Human Services regulations (45 CFR 46.116(d), 45 CFR 46.117(c)(2), and 45 CFR 46.111) because (a) the anonymity of participants was preserved and (b) the risk to participants was minimal. The IRB is registered with the Office for Human Research Protections under number IRB00009303, and the Federalwide Assurance number for the IRB is FWA00021545.

Regressions and factor analysis

Linear regression was used to determine which competencies were most strongly associated with self-reported levels of happiness, personal success, professional success, and general level of stress. Notably, the Plans and Prevents competency proved to be the best predictor of all four criterion variables (Tables 3 and 4 ). Please note that by using the language of prediction, we do not mean to imply causation.

An exploratory principal components factor analysis for the 24 scored items in the questionnaire yielded a Kaiser–Meyer–Olkin sampling adequacy of 0.89, which is well above the recommended cutoff of 0.6, as well as a highly significant Bartlett’s Test of Sphericity ( p < 0.001). The factor analysis yielded four components that overlap our original four competencies and that can reasonably be described as: (1) Plans Ahead, (2) Practices Relaxation Techniques, (3) Regulates and Manages Stressors, and (4) Recognizes Weaknesses (Table 5 ). The results of the factor analysis were not used to revise the original competencies or items, because these competencies are practical skillsets, not hypothetical constructs. We did not conduct a confirmatory factor analysis for the same reason.

Reliability and validity evidence

The questionnaire had moderate but acceptable internal-consistency reliability (Cronbach’s alpha = 0.79; Guttman split-half = 0.70) 137 , 138 , 139 . Because the study was conducted over the internet and because we could not collect contact information for our participants (in order to preserve their anonymity), test–retest reliability could not be assessed. We also did not develop an alternate form of the questionnaire, so alternate-form reliability could not be estimated.

Internal consistency scores for the four competencies varied considerably: Manages or Reduces Sources of Stress: Cronbach’s alpha = 0.60; Guttman split-half = 0.64. Manages Thoughts: Cronbach’s alpha = 0.34; Guttman split-half = 0.37. Plans and Prevents: Cronbach’s alpha = 0.64; Guttman split-half = 0.68. Practices Relaxation Techniques: Cronbach’s alpha = 0.65; Guttman split-half = 0.61.

Regarding validity evidence, total scores were correlated with scores on our criterion questions, as we had predicted: Total scores were positively correlated with participants’ self-reported level of happiness (Spearman’s ρ = 0.45, p < 0.001), personal success ( ρ = 0.35, p < 0.001), and professional success ( ρ = 0.32, p < 0.001), and negatively correlated with participants’ general level of stress ( ρ = -0.33, p < 0.001). Because this was an internet-based study in which the anonymity of participants was protected, we could not assess validity by comparing scores on our questionnaire to scores on comparable questionnaires (see Discussion). (Because scores on the ESMI-i lie on an ordinal scale, nonparametric statistical tests such as Spearman’s ρ , the Mann–Whitney U , and the Kruskal–Wallis H are used throughout this study, except in our regression analyses. Nonparametric regressions are generally used only when extreme values might distort the results 141 ; outliers are unlikely with an instrument like the ESMI-i in which scores are constrained.).

Although not specifically predicted, the validity of the measuring instrument is also suggested by the fact that the mean total score for those who reported having had stress-management training was significantly higher than the mean total score for those who did not ( M Yes = 58.8 [13.2], M No = 52.6 [13.3], U = 19,888,845, p < 0.001, r = 0.18). In addition, overall questionnaire scores were positively correlated with the number of hours of stress-management training participants reported having ( ρ = 0.24, p < 0.001).

Gender, race, and other demographic effects

The overall mean total score was 53.8 [13.5] and subscale means were as follows: Manages or Reduces Sources of Stress ( M = 61.3 [18.4]), Manages Thoughts ( M = 57.2 [14.7]), Plans and Prevents ( M = 54.9 [19.7]), and Practices Relaxation Techniques ( M = 41.9 [20.5]).

We found a significant but not necessarily substantial effect for education level ( M None = 48.8 [13.1], M Highschool = 52.3 [12.9], M Associates = 54.9 [13.1], M Bachelors = 55.1 [13.6], M Masters = 57.1 [13.2], M Doctorate = 56.3 [15.1], H = 604.3, p < 0.001, E 2 R = 0.03), and scores were higher for participants who reported having been married ( M Yes = 55.0 [13.6], M No = 53.0 [13.3], U = 37,980,528.5, p < 0.001, r = 0.07) and also, surprisingly, for participants who reported having been divorced ( M Yes = 55.4 [14.0], M No = 53.6 [13.4], U = 20,128,336.5, p < 0.001, r = 0.05).

We found a significant but not necessarily substantial effect for gender ( M female = 53.7 [13.3], M male = 54.1 [13.7], M other = 44.1 [15.4] , H = 42.7, p < 0.001, E 2 R = 0.00) and no significant male/female difference ( U = 39,631,749.5, p = 0.12, r = 0.01). Participants ages 18 and older scored significantly higher than minors ( M 12-17 = 49.3 [12.9], M 18-83 = 54.8 [13.4], U = 19,539,532, p < 0.001, r = 0.15). (Note that because this is a large-n study, statistical significance is not necessarily a good indicator of the importance of mean differences. For this reason, we also have included two different measures of effect size: r , where we are comparing two means, and epsilon-squared, where we are comparing three or more means 142 . We also found a significant but not necessarily substantial effect for ethnicity, with respondents of Asian descent outscoring all other ethnicities ( M AmericanIndian = 54.5 [14.8], M Asian = 58.3 [13.4], M Black = 54.6 [14.0], M Hispanic = 53.0 [13.8], M White = 54.0 [14.1], M Other = 53.0 [13.2], H = 330.1, p < 0.001, E 2 R = 0.02 ; Asian vs. non-Asian: M Asian = 58.3 [13.4], M NonAsian = 53.2 [13.4], U = 15,133,970.5, p < 0.001, r = 0.13), a finding that is consistent with other research 143 , 144 , 145 .

We also found a significant but not necessarily substantial effect for sexual orientation, with self-labeled straights outscoring self-labeled gays, lesbians, and bisexuals ( M Bisexual = 49.0 [14.0], M Gay/Lesbian = 50.0 [14.2], M Straight = 54.3 [13.3], M Other = 52.2 [17.1], H = 203.0, p < 0.001, E 2 R = 0.01; straight vs. non-straight: M Straight = 54.3 [13.3], M NonStraight = 49.4 [14.1], U = 11,946,435, p < 0.001, r = 0.10). Participants outside the U.S. and Canada scored higher than participants from the U.S. and Canada ( M US/Canada = 53.6 [13.2], M Other = 54.5 [14.0], U = 33,681,800, p < 0.001, r = 0.03), possibly because of the higher scores of Asian participants in the study. We did not have enough participants in individual countries outside the U.S. and Canada for us to conduct, with sufficient statistical power, a country-by-country analysis; a larger sample might allow us to conduct such an analysis in future years. Age proved to be a small but significant predictor of questionnaire scores ( ρ = 0.12, p < 0.001).

Apparent value of low stress

Our results suggest that high stress is associated with low levels of happiness, personal success, and professional success; that low stress is associated with high levels of these outcomes; and that the benefits sometimes associated with a moderate level of stress might not be as beneficial as previously thought (Figs. 1 and 2 ; see Discussion). Although the spikes toward the center of the curves in Fig. 1 could be interpreted as indicating possible benefits of moderate stress, when one looks closely at the happiness, personal success, and professional success ratings reported by people who experience different levels of stress in their lives, it seems evident that low stress is more consistently associated with desirable outcomes (Fig. 2 ).

Relationship between self-reported levels of stress and self-reported levels of happiness, personal success, and professional success. Although higher stress is generally associated with poorer outcomes (note the overall downward slopes of the curves), the upward spikes in the center of the graph are sometimes mistakenly interpreted to mean that moderate stress is beneficial. Vertical bars show 95% confidence intervals.

Histograms showing distributions of self-reported levels of happiness, personal success, and professional success, separated into three categories of level of stress. Although one can find high levels of happiness, personal success, and professional success in the bottom two rows of graphs, the patterns of scores are more nearly optimal in the top row, which shows data only for people reporting their overall level of stress as very low (1 on a scale from 1 to 10).

Year-by-year analysis

Because our data were collected over a period of more than 14 years, we asked whether any trends were evident in scores, as well as in demographic characteristics of the sample. Although statistically significant changes were evident in both scores and demographic characteristics over the course of the study (Table 6 ), we did not find a linear trend in the mean total scores ( p = 0.813, r 2 = 0.005, β = 0.07, t = 0.24).

Discussion and limitations

The present study sheds light on various aspects of people’s ability to manage stress. One of its greatest limitations—that the data were collected over the internet—is also a strength. On the downside, internet sampling gives one no control over demographics, and all participants are self-selected. Our sample presumably consisted of people who were concerned about stress or how they managed it. This could mean, among other things, that our mean level of self-reported stress (6.5 out of 10) is higher than that of the general population and, perhaps, that the stress-management proficiency level we found ( M = 53.8) is lower than normal. A 2013 report by the American Psychological Association 65 states that the average stress level for Americans is 4.9 out of 10, 1.6 points below the mean we found. We might also be attracting people with abnormally low levels of happiness or success.

On the upside, the internet allows researchers to look at a large, diverse, international sample, which almost certainly yields more valid findings than the proverbial pool of second-year college students 146 , 147 , 148 . There is also accumulating evidence that people are more honest when answering personal questions through anonymous internet surveys than perhaps through any other means 149 , 150 , 151 , 152 , 153 ; a recent study by Robertson et al. 154 suggests that anonymous internet surveys yield more valid responses than sixteen other common survey techniques. Surveys yield especially valid responses when people are completing them voluntarily and they know that the results will not be used by supervisors or other authority Figures. 155 , 156 . For these reasons, we conjecture that our participants were probably honest in their responding. We also have no a priori reason to believe that the relationships we have found among variables—for example, the negative correlation between total questionnaire scores and self-reported levels of stress ( ρ = − 0.33, p < 0.001)—are invalid.

We also have no reason to doubt the validity of some of the more distinctive demographic findings in the study, particularly where such findings are consistent with those of other research. Especially notable in this study is the relatively high mean score of participants identifying as Asian. Other studies looking more directly at this issue have also found that various Asian groups are better at managing stress than non-Asians, perhaps because of the collectivist nature of many Asian cultures 157 . Tweed et al. 145 found, for example, that East Asian Canadians reported using internal strategies to manage stressful situations more often than European Canadians did. In collectivist cultures, people tend to be more mutually supportive than in individualistic cultures 158 , 159 , and Asian cultures also tend to teach explicit techniques—yoga, meditation, tai chi, and so on—which have been shown to improve well-being and lower stress 71 , 160 , 161 . In many non-Asian cultures, well-being is often sought through self-destructive means (alcoholism, drug abuse, overeating) or, at best, left to chance. Similarly, our findings that self-reported straights outscored self-reported non-straights on the ESMI-i and that self-reported straights reported experiencing less stress than self-reported non-straights are consistent with the findings of other researchers 162 , 163 , 164 , 165 .

Our study found no significant difference between scores for males and scores for females. Researchers disagree about gender differences in both stress-management proficiency and perceived stress levels. Some studies suggest that women are more likely to utilize emotion-focused coping in response to stressors while men more often use problem-focused coping 166 . The 2013 report on stress published by the American Psychological Association stated that women report higher stress levels than men 65 . However, and consistent with our results, some studies have found that gender differences in coping styles are not apparent when confounding factors such as socioeconomic status and race are controlled for 167 .

The two largest demographic effects we found should be studied in further detail in future studies. Self-labeled straights outscored non-straights by 4.9 points ( r = 0.10), and adults outscored minors (ages 12–17) by 5.5 points ( r = 0.15). Considerable research has examined the emotional problems often experienced by non-straights (brought about, most likely, by entrenched heteronormativity in most cultures 168 , 169 , 170 ), but why straights should score higher on a test of stress-management competencies is unclear. The age difference seems less mysterious. Competencies take time to learn, after all 171 , but it would be interesting to look at this learning process in more detail, especially over the teen years.

A second notable limitation of the present study is that it is correlational in design. In follow-ups to this study, one could, by employing either between-subjects or within-subjects experimental designs, assess the possible causal impact of each of the four competencies we have examined in this report.

Perhaps the clearest and, in some sense, the most surprising finding in this study is that proactive stress-management methods appear to be more helpful than reactive ones. All four of our criterion variables were best predicted by the Plans and Prevents competency, of which all questionnaire items describe proactive methods of fighting stress—in other words, ways of trying to ensure that stressful situations never arise (Tables 3 and 4 ). A planning competency also emerged in our factor analysis (Table 5 ). Unfortunately, our respondents scored relatively poorly on Plans and Prevents ( M = 54.9), which ranked third on actual competency scores. We note that our findings about proactive methods do not necessarily show that such methods are more beneficial than reactive ones; it might simply be the case that people with lower stress levels rely less on reactive coping strategies than on proactive ones. Again, questions of cause and effect can only be answered with experimental research.

Our study also yielded intriguing findings regarding the supposed value of moderate stress. Ever since the formation of the Yerkes-Dodson law in the early 1900s, researchers have suggested that moderate levels of stress (at least for stressors of certain types) are beneficial 172 , 173 , 174 , 175 , 176 . Our study suggests another possibility—namely, that the bulge that often appears in the center of performance or other curves where the stress level is moderate is a statistical anomaly. As we noted earlier, this seems evident when we examine the relationship between participants’ self-reported levels of stress and their self-reported levels of happiness, personal success, and professional success (Fig. 1 ), as well as when we look closely at the distributions of self-reported levels of happiness, personal success, and professional success when separated into low, medium, and high of levels of self-reported stress (Fig. 2 ).

The strong relationship ( ρ = 0.45, p < 0.001, ρ 2 = 0.20) we found between total questionnaire scores and self-reported happiness is also notable, suggesting the importance of stress management in having a happy life 177 (although, once again, we remind the reader that this is a correlational study). Unfortunately, our results suggest that people are generally poor at stress management; the mean percentage score on the questionnaire was 53.8%, with Practices Relaxation Skills having a mean score of only 41.9%. Our study confirms the need to educate and train people in how to manage stress, although, as noted above, our questionnaire scores might be lower than the average scores one would find in the general population. Fortunately, although the present study employed a concurrent design 140 , not an experimental one, our results are consistent with the view that stress-management training has value; as noted earlier, study participants who had had such training scored significantly higher than participants who had not, and questionnaire scores were positively correlated with the number of training hours reported.

We have already mentioned several ways in which our analysis was constrained because we collected our data online. These limitations are not trivial, because collecting data on the internet—especially when one is required to protect the anonymity of the participants—means that some of the standard tools used to validate new test instruments cannot be employed. Ideally, one would like to compare test scores to those obtained on previously validated tests. Again, ideally, one would like to be able to measure the stability of test scores by readministering the test to the same cohort after different periods of time have passed. One would also like to use multiple measures to validate the test, such as ratings by peers or clinicians. None of these methods is possible given our current design.

As noted above, future versions of the ESMI-i might include additional competency categories. People can mitigate stress using many tools, such as exercise or changes in diet; the present study focuses on cognitive-behavioral methods that might be taught by therapists and counselors. More detailed demographic analyses might also be conducted, especially with larger samples. The current online version of the ESMI-i (as of July 8, 2024) already includes additional gender and sexual orientation categories. The present study also assumes, implicitly, that stress management is the same in all cultures around the world, which is clearly not the case. Stressors themselves are culturally based 163 , 165 , 178 , 179 , and so are effective techniques of stress management 145 .

Data availability

Anonymized raw data employed in the present study will be made available at Zenodo.com upon acceptance of the manuscript. Anonymized raw data can also be requested by writing to [email protected]. Anonymization was required to comply with the requirement of the sponsoring institution’s Institutional Review Board that the identities of the participants be protected in accordance with HHS Federal Regulation 45 CFR 46.101.(b)(2).

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Acknowledgements

We are grateful to Marco Buenaventura, Philip Cheung, Matea Djokic, Shannon Fox, Allison He, Paul McKinney, Krystie Mei, and Rachel Smith for assistance in various aspects of this research. Funding was provided by the American Institute for Behavioral Research and Technology, which also provided IRB approval (IRB registered with OHRP under number IRB00009303, Federalwide Assurance number FWA00021545). This report is based in part on papers presented at the 91st (2011), 94th (2014), and 101st (2021) annual meetings of the Western Psychological Association. Each successive report analyzed larger datasets. Brief summaries of these talks were posted on the first author’s website.

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Epstein, R., Aceret, J., Giordani, C. et al. A rank ordering and analysis of four cognitive-behavioral stress-management competencies suggests that proactive stress management is especially valuable. Sci Rep 14 , 19224 (2024). https://doi.org/10.1038/s41598-024-68328-4

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v.12(6); 2020 Jun

Social Media Use and Its Connection to Mental Health: A Systematic Review

Fazida karim.

1 Psychology, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

2 Business & Management, University Sultan Zainal Abidin, Terengganu, MYS

Azeezat A Oyewande

3 Family Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

4 Family Medicine, Lagos State Health Service Commission/Alimosho General Hospital, Lagos, NGA

Lamis F Abdalla

5 Internal Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

Reem Chaudhry Ehsanullah

Safeera khan.

Social media are responsible for aggravating mental health problems. This systematic study summarizes the effects of social network usage on mental health. Fifty papers were shortlisted from google scholar databases, and after the application of various inclusion and exclusion criteria, 16 papers were chosen and all papers were evaluated for quality. Eight papers were cross-sectional studies, three were longitudinal studies, two were qualitative studies, and others were systematic reviews. Findings were classified into two outcomes of mental health: anxiety and depression. Social media activity such as time spent to have a positive effect on the mental health domain. However, due to the cross-sectional design and methodological limitations of sampling, there are considerable differences. The structure of social media influences on mental health needs to be further analyzed through qualitative research and vertical cohort studies.

Introduction and background

Human beings are social creatures that require the companionship of others to make progress in life. Thus, being socially connected with other people can relieve stress, anxiety, and sadness, but lack of social connection can pose serious risks to mental health [ 1 ].

Social media

Social media has recently become part of people's daily activities; many of them spend hours each day on Messenger, Instagram, Facebook, and other popular social media. Thus, many researchers and scholars study the impact of social media and applications on various aspects of people’s lives [ 2 ]. Moreover, the number of social media users worldwide in 2019 is 3.484 billion, up 9% year-on-year [ 3 - 5 ]. A statistic in Figure 1 shows the gender distribution of social media audiences worldwide as of January 2020, sorted by platform. It was found that only 38% of Twitter users were male but 61% were using Snapchat. In contrast, females were more likely to use LinkedIn and Facebook. There is no denying that social media has now become an important part of many people's lives. Social media has many positive and enjoyable benefits, but it can also lead to mental health problems. Previous research found that age did not have an effect but gender did; females were much more likely to experience mental health than males [ 6 , 7 ].

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Object name is cureus-0012-00000008627-i01.jpg

Impact on mental health

Mental health is defined as a state of well-being in which people understand their abilities, solve everyday life problems, work well, and make a significant contribution to the lives of their communities [ 8 ]. There is debated presently going on regarding the benefits and negative impacts of social media on mental health [ 9 , 10 ]. Social networking is a crucial element in protecting our mental health. Both the quantity and quality of social relationships affect mental health, health behavior, physical health, and mortality risk [ 9 ]. The Displaced Behavior Theory may help explain why social media shows a connection with mental health. According to the theory, people who spend more time in sedentary behaviors such as social media use have less time for face-to-face social interaction, both of which have been proven to be protective against mental disorders [ 11 , 12 ]. On the other hand, social theories found how social media use affects mental health by influencing how people view, maintain, and interact with their social network [ 13 ]. A number of studies have been conducted on the impacts of social media, and it has been indicated that the prolonged use of social media platforms such as Facebook may be related to negative signs and symptoms of depression, anxiety, and stress [ 10 - 15 ]. Furthermore, social media can create a lot of pressure to create the stereotype that others want to see and also being as popular as others.

The need for a systematic review

Systematic studies can quantitatively and qualitatively identify, aggregate, and evaluate all accessible data to generate a warm and accurate response to the research questions involved [ 4 ]. In addition, many existing systematic studies related to mental health studies have been conducted worldwide. However, only a limited number of studies are integrated with social media and conducted in the context of social science because the available literature heavily focused on medical science [ 6 ]. Because social media is a relatively new phenomenon, the potential links between their use and mental health have not been widely investigated.

This paper attempt to systematically review all the relevant literature with the aim of filling the gap by examining social media impact on mental health, which is sedentary behavior, which, if in excess, raises the risk of health problems [ 7 , 9 , 12 ]. This study is important because it provides information on the extent of the focus of peer review literature, which can assist the researchers in delivering a prospect with the aim of understanding the future attention related to climate change strategies that require scholarly attention. This study is very useful because it provides information on the extent to which peer review literature can assist researchers in presenting prospects with a view to understanding future concerns related to mental health strategies that require scientific attention. The development of the current systematic review is based on the main research question: how does social media affect mental health?

Research strategy

The research was conducted to identify studies analyzing the role of social media on mental health. Google Scholar was used as our main database to find the relevant articles. Keywords that were used for the search were: (1) “social media”, (2) “mental health”, (3) “social media” AND “mental health”, (4) “social networking” AND “mental health”, and (5) “social networking” OR “social media” AND “mental health” (Table 1 ).

Keyword/Combination of Keyword	Database	Number of Results
“social media”	Google Scholar	877,000
“mental health”	Google Scholar	633,000
“social media” AND “mental health”	Google Scholar	78,000
“social networking” AND “mental health”	Google Scholar	18,600
"social networking "OR "social media" AND "mental health"	Google Scholar	17,000

Out of the results in Table 1 , a total of 50 articles relevant to the research question were selected. After applying the inclusion and exclusion criteria, duplicate papers were removed, and, finally, a total of 28 articles were selected for review (Figure 2 ).

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Object name is cureus-0012-00000008627-i02.jpg

PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Inclusion and exclusion criteria

Peer-reviewed, full-text research papers from the past five years were included in the review. All selected articles were in English language and any non-peer-reviewed and duplicate papers were excluded from finally selected articles.

Of the 16 selected research papers, there were a research focus on adults, gender, and preadolescents [ 10 - 19 ]. In the design, there were qualitative and quantitative studies [ 15 , 16 ]. There were three systematic reviews and one thematic analysis that explored the better or worse of using social media among adolescents [ 20 - 23 ]. In addition, eight were cross-sectional studies and only three were longitudinal studies [ 24 - 29 ].The meta-analyses included studies published beyond the last five years in this population. Table 2 presents a selection of studies from the review.

IGU, internet gaming disorder; PSMU, problematic social media use

Author	Title of Study	Method	Findings
Berryman et al. [ ]	Social Media Use and Mental Health among Young Adults	Cross-sectional	Social media use was not predictive of impaired mental health functioning.
Coyne et al. [ ]	Does Time Spent using Social Media Impact Mental Health?: An Eight Year Longitudinal Study	8-year longitudinal study	Increased time spent on social media was not associated with increased mental health issues across development when examined at the individual level.
Escobar-Viera et al. [ ]	For Better or for Worse? A Systematic Review of the Evidence on Social Media Use and Depression Among Lesbian, Gay, and Bisexual Minorities	Systematic Literature Review	Social media provides a space to disclose minority experiences and share ways to cope and get support; constant surveillance of one's social media profile can become a stressor, potentially leading to depression.
O’Reilly et al. [ ]	Potential of Social Media in Promoting Mental Health in Adolescents	qualitative study	Adolescents frequently utilize social media and the internet to seek information about mental health.
O’Reilly [ ]	Social Media and Adolescent Mental Health: The Good, the Bad and the Ugly	focus groups	Much of the negative rhetoric of social media was repeated by mental health practitioners, although there was some acknowledgement of potential benefit.
Feder et al. [ ]	Is There an Association Between Social Media Use and Mental Health? The Timing of Confounding Measurement Matters	longitudinal	Frequent social media use report greater symptoms of psychopathology.
Rasmussen et al. [ ]	The Serially Mediated Relationship between Emerging Adults’ Social Media Use and Mental Well-Being	Exploratory study	Social media use may be a risk factor for mental health struggles among emerging adults and that social media use may be an activity which emerging adults resort to when dealing with difficult emotions.
Keles et al. [ ]	A Systematic Review: The Influence of Social Media on Depression, Anxiety and Psychological Distress in Adolescents	systematic review	Four domains of social media: time spent, activity, investment, and addiction. All domains correlated with depression, anxiety and psychological distress.
Nereim et al. [ ]	Social Media and Adolescent Mental Health: Who You Are and What You do Matter	Exploratory	Passive social media use (reading posts) is more strongly associated with depression than active use (making posts).
Mehmet et al. [ ]	Using Digital and Social Media for Health Promotion: A Social Marketing Approach for Addressing Co‐morbid Physical and Mental Health	Intervention	Social marketing digital media strategy as a health promotion methodology. The paper has provided a framework for implementing and evaluating the effectiveness of digital social media campaigns that can help consumers, carers, clinicians, and service planners address the challenges of rural health service delivery and the tyranny of distance,
Odgers and Jensen [ ]	Adolescent Mental Health in the Digital Age: Facts, Fears, and Future Directions	Review	The review highlights that most research to date has been correlational, has focused on adults versus adolescents, and has generated a mix of often conflicting small positive, negative, and null associations.
Twenge and Martin [ ]	Gender Differences in Associations between Digital Media Use and Psychological Well-Being: Evidence from Three Large Datasets	Cross-sectional	Females were found to be addicted to social media as compared with males.
Fardouly et al. [ ]	The Use of Social Media by Australian Preadolescents and its Links with Mental Health	Cross-sectional	Users of YouTube, Instagram, and Snapchat reported more body image concerns and eating pathology than non-users, but did not differ on depressive symptoms or social anxiety
Wartberg et al. [ ]	Internet Gaming Disorder and Problematic Social Media Use in a Representative Sample of German Adolescents: Prevalence Estimates, Comorbid Depressive Symptoms, and Related Psychosocial Aspects	Cross-sectional	Bivariate logistic regression analyses showed that more depressive symptoms, lower interpersonal trust, and family functioning were statistically significantly associated with both IGD and PSMU.
Neira and Barber [ ]	Social Networking Site Use: Linked to Adolescents’ Social Self-Concept, Self-Esteem, and Depressed Mood	Cross-sectional	Higher investment in social media (e.g. active social media use) predicted adolescents’ depressive symptoms. No relationship was found between the frequency of social media use and depressed mood.

This study has attempted to systematically analyze the existing literature on the effect of social media use on mental health. Although the results of the study were not completely consistent, this review found a general association between social media use and mental health issues. Although there is positive evidence for a link between social media and mental health, the opposite has been reported.

For example, a previous study found no relationship between the amount of time spent on social media and depression or between social media-related activities, such as the number of online friends and the number of “selfies”, and depression [ 29 ]. Similarly, Neira and Barber found that while higher investment in social media (e.g. active social media use) predicted adolescents’ depressive symptoms, no relationship was found between the frequency of social media use and depressed mood [ 28 ].

In the 16 studies, anxiety and depression were the most commonly measured outcome. The prominent risk factors for anxiety and depression emerging from this study comprised time spent, activity, and addiction to social media. In today's world, anxiety is one of the basic mental health problems. People liked and commented on their uploaded photos and videos. In today's age, everyone is immune to the social media context. Some teens experience anxiety from social media related to fear of loss, which causes teens to try to respond and check all their friends' messages and messages on a regular basis.

On the contrary, depression is one of the unintended significances of unnecessary use of social media. In detail, depression is limited not only to Facebooks but also to other social networking sites, which causes psychological problems. A new study found that individuals who are involved in social media, games, texts, mobile phones, etc. are more likely to experience depression.

The previous study found a 70% increase in self-reported depressive symptoms among the group using social media. The other social media influence that causes depression is sexual fun [ 12 ]. The intimacy fun happens when social media promotes putting on a facade that highlights the fun and excitement but does not tell us much about where we are struggling in our daily lives at a deeper level [ 28 ]. Another study revealed that depression and time spent on Facebook by adolescents are positively correlated [ 22 ]. More importantly, symptoms of major depression have been found among the individuals who spent most of their time in online activities and performing image management on social networking sites [ 14 ].

Another study assessed gender differences in associations between social media use and mental health. Females were found to be more addicted to social media as compared with males [ 26 ]. Passive activity in social media use such as reading posts is more strongly associated with depression than doing active use like making posts [ 23 ]. Other important findings of this review suggest that other factors such as interpersonal trust and family functioning may have a greater influence on the symptoms of depression than the frequency of social media use [ 28 , 29 ].

Limitation and suggestion

The limitations and suggestions were identified by the evidence involved in the study and review process. Previously, 7 of the 16 studies were cross-sectional and slightly failed to determine the causal relationship between the variables of interest. Given the evidence from cross-sectional studies, it is not possible to conclude that the use of social networks causes mental health problems. Only three longitudinal studies examined the causal relationship between social media and mental health, which is hard to examine if the mental health problem appeared more pronounced in those who use social media more compared with those who use it less or do not use at all [ 19 , 20 , 24 ]. Next, despite the fact that the proposed relationship between social media and mental health is complex, a few studies investigated mediating factors that may contribute or exacerbate this relationship. Further investigations are required to clarify the underlying factors that help examine why social media has a negative impact on some peoples’ mental health, whereas it has no or positive effect on others’ mental health.

Conclusions

Social media is a new study that is rapidly growing and gaining popularity. Thus, there are many unexplored and unexpected constructive answers associated with it. Lately, studies have found that using social media platforms can have a detrimental effect on the psychological health of its users. However, the extent to which the use of social media impacts the public is yet to be determined. This systematic review has found that social media envy can affect the level of anxiety and depression in individuals. In addition, other potential causes of anxiety and depression have been identified, which require further exploration.

The importance of such findings is to facilitate further research on social media and mental health. In addition, the information obtained from this study can be helpful not only to medical professionals but also to social science research. The findings of this study suggest that potential causal factors from social media can be considered when cooperating with patients who have been diagnosed with anxiety or depression. Also, if the results from this study were used to explore more relationships with another construct, this could potentially enhance the findings to reduce anxiety and depression rates and prevent suicide rates from occurring.

The content published in Cureus is the result of clinical experience and/or research by independent individuals or organizations. Cureus is not responsible for the scientific accuracy or reliability of data or conclusions published herein. All content published within Cureus is intended only for educational, research and reference purposes. Additionally, articles published within Cureus should not be deemed a suitable substitute for the advice of a qualified health care professional. Do not disregard or avoid professional medical advice due to content published within Cureus.

The authors have declared that no competing interests exist.

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Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression

Main Findings

Introduction

Mediation and moderation

Mediation and moderation effects on depression

The present study

Ethics statement

Participants

Instruments

Perceived Stress Scale [20] .

Rosenberg's Self-Esteem Scale [22] .

Positive Affect and Negative Affect Schedule [26] .

Correlational analysis

Mediation analysis

Moderation analysis

Mediating effects

Moderator effects/interaction effects

Limitations

Conclusions

Acknowledgments

Author Contributions

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