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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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Home > Student Research, Creative Works, and Publications > Masters Theses and Doctoral Dissertations > 512

Masters Theses and Doctoral Dissertations

The role of resilience, emotion regulation, and perceived stress on college academic performance.

Katherine A. Pendergast , University of Tennessee at Chattanooga Follow

Committee Chair

Ozbek, Irene Nichols, 1947-

Committee Member

Clark, Amanda J.; Rogers, Katherine H.

Dept. of Psychology

College of Arts and Sciences

University of Tennessee at Chattanooga

Place of Publication

Chattanooga (Tenn.)

Stress is a common problem for college students. The goal of this thesis was to examine the relationships between protective and risk factors to experiencing stress and how these factors may predict academic performance in college students. 125 college students were surveyed twice over the course of a semester on emotion regulation strategies, trait resilience, and perceived stress. The relationships between these variables and semester GPA were analyzed using correlational, multiple regression, and hierarchical regression analyses. It was determined that trait resilience scores do predict use of emotion regulation strategies but change in stress and trait resilience do not significantly predict variation in academic performance during the semester. Limitations and future directions are further discussed.

Acknowledgments

Thanks to my advisor, Dr. Ozbek, and committee members, Dr. Clark and Dr. Rogers, for invaluable feedback and support. Additional thanks to Dr. Jonathan Davidson, M.D., for his permission to use the CD-RISC to better understand resilience in the college population. Also, I would like to extend thanks to Linda Orth, Sandy Zitkus, and the entire records office staff of the University of Tennessee at Chattanooga for their willingness to collaborate and assist with this project. Lastly, I would like to thank the faculty and students of the Psychology Department for their overall support.

M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science.

Stress (Psychology); Academic achievement -- Education (Higher)

Stress; Resilience; Emotion regulation; Academic performance

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Masters theses

xi, 72 leaves

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Recommended Citation

Pendergast, Katherine A., "The role of resilience, emotion regulation, and perceived stress on college academic performance" (2017). Masters Theses and Doctoral Dissertations. https://scholar.utc.edu/theses/512

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Stress and Coping Mechanisms Among College Students

• Masters Thesis
• Cornejo, Joaquin
• Park, Hyun Sun
• Brown, Jodi
• Acuña, Maria
• Social Work
• California State University, Northridge
• self-acceptance.
• college students
• self-compassion
• Dissertations, Academic -- CSUN -- Social Work.
• coping mechanism
• 2020-06-01T19:29:25Z
• http://hdl.handle.net/10211.3/216140
• by Joaquin Cornejo
• California State University, Northridge. Department of Social Work.

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Doctoral Dissertations and Projects

Exploring prelicensure bsn students' knowledge of mindfulness meditation using a smartphone app to manage stress and promote resilience: a qualitative single case study.

Beth A. Kelley , Liberty University Follow

School of Nursing

Doctor of Philosophy

Kara Schacke

mindfulness meditation, mindfulness meditation smartphone app, BSN student stress, BSN student resilience, meditation, stress, resilience, knowledge of mindfulness meditation, christian university

Disciplines

Education | Nursing

Recommended Citation

Kelley, Beth A., "Exploring Prelicensure BSN Students' Knowledge of Mindfulness Meditation Using A Smartphone App To Manage Stress And Promote Resilience: A Qualitative Single Case Study" (2024). Doctoral Dissertations and Projects . 5909. https://digitalcommons.liberty.edu/doctoral/5909

The purpose of this qualitative single case study was to explore pre-licensure Bachelor of Science in Nursing (BSN) students' knowledge of mindfulness meditation (MM) using a smartphone app (SMA) to manage stress and promote resilience. Guiding this study was the transactional model of stress, adaptation, and coping by Lazarus and Folkman (1984) and the zone of proximal development (ZPD) educational theory by Vygotsky. The study asked the following questions: What was pre-licensure Bachelor of Science of Nursing (BSN) students’ knowledge of mindfulness meditation (MM) using a smartphone app (SMA) to manage stress and promote resilience? What had the prelicensure BSN student experienced regarding MM with an SMA? What did prelicensure BSN students know about MM using an SMA to manage stress? What did prelicensure BSN students know about MM using an SMA to promote resilience? A sample of 91 students was obtained to answer the demographic questionnaire and three surveys. From those students, 25 volunteered for interviews and focus groups with 14 BSN students for interviews and 11 students split into two focus groups. The data were collected from surveys, interviews, and focus groups, and themes were developed. Data obtained contributes to current knowledge, and recommendations for further research are given.

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ORIGINAL RESEARCH article

Stress and hope distinguish individuals with suicidal plan from suicide ideators among chinese college students.

• 1 Ideological and Political Education Center, Northeast Normal University, Changchun, Jilin, China
• 2 Mental Health Education Center, Wenzhou Medical University, Wenzhou, Zhejiang, China
• 3 Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China

Background: Suicide among college students is a significant public health concern in China. While suicidal ideation serves as a crucial predictor of subsequent suicidal plans and behaviors, it is important to recognize that most instances of suicidal ideation may only be fleeting thoughts that do not progress to an actual plan. Therefore, it is imperative to identify the factors associated with the transition from suicidal ideation to a concrete plan. Consequently, this study aims to investigate whether certain frequently cited factors can differentiate individuals who have formulated a specific suicidal plan from those who have experienced suicidal thoughts without planning, based on data obtained through a cross-sectional survey.

Materials and methods: This survey was conducted as part of routine mental health assessments among second-year college students in October 2023. Data from a total of 4,858 second-year college students were utilized for the final analyses. Two survey questions were employed to identify past-year suicidal ideation and past-year suicidal plan. All participants were required to complete various assessments, including the Chinese version of Depression Anxiety Stress Scale 21 items (DASS-21), the Chinese version of Gratitude Questionnaire-six items (GQ-6), the Chinese version of Meaning in Life Questionnaire (MLQ), and the Chinese version of State Hope Scale (SHS).

Results: Among 4,858 participants, a total of 134 individuals (2.8%) were confirmed to have experienced past-year suicidal ideation. Out of these, 53 (1.1% overall) reported having a past-year suicidal plan, accounting for approximately 39.6% of those with suicidal ideation. Logistic regression analyses revealed that while most potential variables differentiated between students with and without suicidal ideation, only two factors stood out in distinguishing individuals with a suicidal plan from those who had not made such plans despite experiencing suicidal thoughts—presence of stress ( OR =2.49, 95% CI : 1.04–5.96) and lower scores of hope agency ( OR =0.84, 95% CI : 0.72–0.98).

Conclusion: These findings suggest that the stress may contribute to susceptibility for transitioning from mere thoughts to actual planning regarding suicide; conversely, hope agency appears to offer protection against this transition process. Therefore, we advocate for targeted interventions aimed at fostering hope among individuals who have encountered adverse and stressful life events.

Introduction

Suicide ranks as one of the primary causes contributing to morbidity and mortality among young adults globally. In China, specifically, it is estimated that approximately 10.7% of college students have experienced suicidal ideation ( 1 ) and 4.4% have formulated plans toward such ends ( 2 ). While there exists no precise national data regarding suicide rates among this population at the present time, suicide among college students presents a significant public health issue throughout China. Although contemplating suicide serves as an important indicator for predicting future attempts or completed acts thereof, many instances where individuals experience these thoughts are transient phenomena which do not necessarily culminate into concrete plans or actions; thus, identifying variables which contribute toward transitioning from mere contemplations toward actualized planning remains crucially important ( 3 – 6 ).

To date, numerous studies have been conducted to investigate the factors associated with suicidal ideation among Chinese college students. The presence of psychiatric symptoms has consistently emerged as the most reliable risk factor for suicidal ideation. For example, meta-analytic data revealed that depressive symptoms were associated with a 3.2-fold increase in the likelihood of suicidal ideation among Chinese college students ( 7 ). Similarly, a meta-analysis involving 66,752 participants reported a strong association between anxiety symptom and students’ suicidal ideation ( 8 ). Additionally, stress symptoms have been identified as predictors of suicidal ideation ( 9 ). It is estimated that approximately 20% of patients with schizophrenia attempt suicide at least once during their life ( 10 ). In addition, exposure to adverse childhood experiences strongly increases the probability of suicide behaviors in patients with schizophrenia ( 11 ). However, it remains unknown whether these psychiatric symptoms can predict the occurrence of suicidal plans among individuals experiencing suicidal thoughts.

On the contrary, in line with a positive psychology framework, numerous psychological variables have been proposed as potential protective factors against suicide. For instance, accumulating evidence suggests that gratitude is linked to reduced psychological distress ( 12 ) and decreased overall symptoms of psychopathology ( 13 ), thereby conferring resilience against suicide ( 14 ). Furthermore, a correlation has been found between the meaning of life and lower levels of suicidal ideation and attempts ( 15 ). Additionally, hope has consistently been reported to be associated with greater life satisfaction, reduced psychological distress, and enhanced psychological well-beings, thus acting as a buffer against suicide ( 16 ). Again, it remains unclear whether these positive psychological variables can effectively prevent the transition from ideation to an actual plan.

According to the ideation-to-action framework ( 3 – 6 ), it is crucial to identify variables that can effectively predict and elucidate the transition from suicidal ideation to a concrete suicidal plan. Given that virtually all students with a suicidal plan also experience suicidal ideation, it becomes imperative to control for this factor when attempting to identify predictors of a suicide plan. However, as far as our knowledge extends, no studies have thus far examined the factors that predict a suicide plan among Chinese college students who have experienced suicidal thoughts. This research gap is significant because gaining a better understanding of the progression from suicidal ideation to planning can greatly facilitate the development of targeted intervention programs for individuals at risk. Consequently, this study aims to investigate whether certain frequently cited factors can differentiate between those who have formulated a specific suicide plan and those who have only experienced suicidal thoughts without any planning, based on data obtained through a cross-sectional survey.

Sampling and participants

This survey was conducted as part of routine mental health assessments among second-year college students in October 2023. The current study was approved by the Ethics Committee of Wenzhou Medical University (Ethics Approval Code: 2023–021). Informed consent was obtained from all subjects. In total, 5,652 second-year college students should have participated in the survey, and actually 5,174 students completed the assessments (i.e., survey response rate was 91.5%). A total of 316 participants gave exactly the same option on each questionnaire/scale, so these data were defined as unqualified data and excluded from the analysis. Finally, data from 4,858 participants (1,893 men and 2,965 women, mean age was 19.32 years) were utilized for the final analyses.

Past-year suicidal ideation and past-year suicidal plan

Two survey questions were employed to identify past-year suicidal ideation and past-year suicidal plan. All participants were first asked, “In the past 12 months, did you seriously think about trying to kill yourself?” Then, those who responded “YES” were further asked, “During the past 12 months, did you make any plans to kill yourself?”

As Figure 1 shows, 134 participants were categorized as group with suicidal ideation. Among these with suicidal ideation, 53 participants had suicidal plan (i.e., group with suicidal plan).

Figure 1 . Sampling profile.

Depression, anxiety, and stress

The presence of symptoms of depression, anxiety, and stress were measured with the Chinese version of Depression Anxiety Stress Scale 21 items (DASS-21) ( 17 , 18 ). DASS-21 is a self-report measure of mental health status, including depression, anxiety, and stress severity. The total scores for each subscale range from 0 to 42, with higher scores indicating higher levels of depression, anxiety, and stress. In the present study, cutoff scores of ≥10, ≥8, and ≥15 were adopted to define the presence symptoms of depression, anxiety, and stress, respectively ( 19 ). The Cronbach’s alpha for the DASS-21 in the present study is 0.886 (depression), 0.838 (anxiety), 0.883 (stress), and 0.949 (total scores), separately.

Gratitude was measured with the Chinese version of Gratitude Questionnaire-six items (GQ-6) ( 14 , 20 ). The GQ-6 contains six items, with each item scored from 1 (strongly disagree) to 7 (strongly agree). The total scores of the GQ-6 range from 7 to 42, with higher scores indicating greater gratitude. The Cronbach’s alpha for the GQ-6 in the present study is 0.724.

Meaning in life

Meaning in life was measured with the Chinese version of Meaning in Life Questionnaire (MLQ) ( 21 , 22 ), which measures presence of meaning and search for meaning of life. The Chinese version of MLQ contains nine items, with each item scored from 1 (strongly disagree) to 7 (strongly agree). The total scores of the subscale for presence of meaning in life (MLQ-P) range from 7 to 35, with higher scores indicating higher level of presence of meaning of life. The total scores of the subscale for search of meaning in life (MLQ-L) range from 7 to 28, with higher scores indicating higher level of active search for meaning in life. The Cronbach’s alpha for the MLQ in the present study is 0.907 (MLQ-P) and 0.891 (MLQ-S), separately.

The hope level was measured by the Chinese version of State Hope Scale (SHS; 23 , 24 ), which measures beliefs about how successful in pursuing goals (Agency) and how confident in finding ways to attain goals (Pathways). The Chinese version of SHS contains six items, with each item scored from 1 (definitely false) to 8 (definitely true). The total scores of the subscale for Agency (SHS-A) and the subscale for Pathways (SHS-P) both range from 8 to 24, with higher scores representing a heightened sense of perceived hope. The Cronbach’s alpha for the SHS in the present study are 0.912 (SHS-A) and 0.947 (SHS-P), separately.

Analysis procedure

Statistical analyses were performed using the SPSS statistical package version 17.0. Chi-square test and one-way ANOVA were used to compare between groups (i.e., Group with suicidal ideation vs. Group without suicidal ideation; Group with suicidal plan vs. Group without suicidal plan but with suicidal ideation) for categorical variables and continuous variables, separately. Logistic regression was conducted to assess factors associated with suicidal ideation and suicidal plan, adjusting for gender and age. Specifically, logistic regression was first conducted to examine factors associated with suicidal ideation among all respondents. Then, we conducted the logistic regression to analyze what distinguished individuals with suicidal plan and from those without suicidal plan among students with suicidal ideation. For DASS-21, only the presence of depression, anxiety, and stress were entered into the logistic regression model.

Group comparisons

Comparisons between groups with or without suicidal ideation.

As Figure 1 shows, out of 4,858, 134 (2.8%) were confirmed as individuals with past-year suicidal ideation. Table 1 summarizes the details of group comparisons between group with suicidal ideation and group without ideation. As Table 1 shows, the group with suicidal ideation had significantly higher prevalence of depression, anxiety, and stress than the group without suicidal ideation (all p <0.01). One-way ANOVA indicated that the group with suicidal ideation had a significantly higher score on depression, anxiety, stress, GQ-6, MLQ-O, MLQ-S, SHS-A, and SHS-P (all p ≤ 0.01).

Table 1 . Comparisons between groups with or without suicidal ideation.

Comparisons between group with suicidal plan and group without suicidal plan but with suicidal ideation

As shown in Figure 1 , 53 (1.1%) of the 4,858 students reported having past-year suicidal plan, representing 39.6% of the students with suicidal ideation. Table 2 summarizes the details of comparisons between group with suicidal plan and group without suicidal plan but with suicidal ideation. As Table 2 shows, the group with suicidal plan had significantly higher prevalence of stress than the group without suicidal plan but with suicidal ideation ( p <0.01). One-way ANOVA indicated that the group with suicidal plan had a significantly higher score on SHS-A (all p =0.03). The difference between groups on total scores of depression and total scores of stress approached significance (both p =0.05). No significant difference was found for the prevalence of depression, anxiety, scores on GQ-6, MLQ-O, MLQ-S, and SHS-P between subgroups (all p ≥0.28).

Table 2 . Comparisons between subgroups with or without suicidal plan among students with suicidal ideation.

Logistic regression equations

The results of logistic regression equations for suicidal ideation and suicide plan are shown in Table 3 . Logistic regression analyses indicate that the presence of depression, anxiety, stress, and total scores of SHS-A significantly differentiated suicidal ideation from all other participants. For suicide plan, logistic regression analysis yielded a very different model, with only presence of stress and total scores of SHS-A significantly distinguishing between individuals with suicidal plan and those without suicidal plan who had suicidal ideation.

Table 3 . Logistic regression analysis for suicidal ideation and suicide plan.

Suicide among college students remain a significant public health concern in China. In order to advance the prevention efforts, it is crucial to gain a deeper understanding of the factors that contribute to or deter the transition from suicidal ideation to actual plans. This study, aligned with an ideation-to-action framework ( 3 – 6 ), aimed to investigate whether certain frequently mentioned factors could differentiate individuals who had made specific plans for suicide from those who had experienced suicidal ideation without planning. Our primary findings indicate that, while most of these potential variables distinguished between students with and without suicidal ideation, only two factors (namely, presence of stress and lower scores of SHS-A) were able to distinguish individuals with concrete suicidal plans from those who had contemplated suicide but did not have a plan in place. These findings hold significant implications for the development of effective strategies for suicide prevention and intervention.

Regarding psychiatric symptoms, our findings suggest that depression and anxiety are significant predictors of suicidal ideation but do not differentiate between individuals with a suicidal plan and those without one. This pattern aligns with previous literature. Our previous study in college students demonstrated that screening positive for psychiatric disorders offered limited discriminatory value in distinguishing suicide attempters from suicidal ideators ( 25 ). Similarly, a meta-analysis of 27 studies revealed that while depression strongly predicted suicidal ideation, its effect was minimal to small when comparing attempters to ideators ( 4 ). Importantly, our results indicate a significant positive association between the presence of stress and the development of a suicidal plan among ideators. We cautiously speculate that stress symptoms may facilitate the transition from mere ideation to planning, as prior research has shown a correlation between perceived stress and increased likelihood of developing a specific suicidal plan one year later ( 26 ).

Our findings, in line with a positive psychology framework, revealed that individuals with suicidal ideation displayed significantly lower scores on GQ-6, MLQ-P, MLQ-S, SHS-P, and SHS-A compared with those without such thoughts. However, except for the scores of SHS-A, these positive psychological variables failed to distinguish between individuals with suicidal plans and those with ideation alone. These results suggest that hope agency may be the sole factor that provides protection against the transition from ideation to planning suicide. These findings are particularly intriguing and significant because hope agency could serve as a valuable target for interventions aimed at reducing suicide risk. Indeed, hope agency fosters a sense of connectedness to successful determination. According to the three-step theory ( 27 ), this connectedness can surpass their psychological pain or hopelessness, thereby impeding the progression from occasional suicidal desires to an actual plan.

Several limitations of the current study should be acknowledged. Firstly, a cross-sectional research design was employed instead of a longitudinal approach, thus warranting the need for future longitudinal and prospective studies to establish causal relationships among the variables. Secondly, the sample size of participants with suicidal plan was small, which limited statistical power in detecting differences. Thirdly, various confounding factors such as social support ( 28 ), perceived discrimination ( 29 ), gender identity, and sexual orientation may have influenced the results of this study. Therefore, future research design should incorporate additional relevant variables to enhance our understanding of the transition process from suicidal ideation to suicide planning. Lastly, potential issues like intentional non-reporting of suicidality and recall bias cannot be ruled out.

In conclusion, these findings suggest that the stress may contribute to vulnerability in transitioning from mere thoughts to actual planning regarding suicide; conversely, hope agency appears to offer protection against this transition process. Henceforth, special attention should be given by suicide prevention programs toward recognizing stress symptoms and implementing training programs for management of stress symptoms among students reporting suicidal ideation ( 30 ). Additionally, targeted interventions aimed at fostering hope among individuals who have experienced adverse and stressful life events are strongly advocated ( 31 ).

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 humans were approved by the Ethics Committee of Wenzhou Medical University (Ethics Approval Code: 2023-021). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

NC: Formal Analysis, Methodology, Writing – original draft. ZD: Data curation, Writing – original draft. YW: Conceptualization, Supervision, Writing – review & editing.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LTGY23H090004).

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.

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Keywords: suicidal ideation, suicide plan, stress, hope, college students, ideation-to-action framework

Citation: Chen N, Dai Z and Wang Y (2024) Stress and hope distinguish individuals with suicidal plan from suicide ideators among Chinese college students. Front. Psychiatry 15:1387868. doi: 10.3389/fpsyt.2024.1387868

Received: 21 February 2024; Accepted: 22 July 2024; Published: 09 August 2024.

Reviewed by:

Copyright © 2024 Chen, Dai and Wang. 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: Yongguang Wang, [email protected]

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

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Sirenicide: The Impact of Stress on Vehicle Crashes

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Estimated 17 min reading time.

Welcome to the USFA Podcast, the official podcast of the U.S. Fire Administration. I'm your host, Teresa Neal. Today we will discuss vehicle safety. It seems a few times a month, Billy Goldfeder's Secret List provides details about an emergency vehicle crash. USFA has completed numerous studies from Alive on Arrival to Emergency Vehicle Visibility and Conspicuity Study, but despite the research, there are still too many crashes involving emergency vehicles.

Our guest, Captain Dustin Lambert, has studied this issue. He wrote “Sirenicide: The Impact of Acute Stress on Emergency Vehicle Crashes,” his dissertation for Jacksonville State University. Dustin has over 23 years of fire and emergency services experience, and is currently a career captain for the Fairmont, West Virginia, Fire Department, managing the department's training, inspection and safety bureau.

He holds a doctorate in emergency management from Jacksonville State University, a master's degree in safety management from West Virginia University, and a bachelor's degree in occupational safety from Fairmont State University. Lambert's research expertise is in responder safety and health, focusing on human factors in emergency vehicle crashes.

He's a West Virginia State fire and EMS instructor, contract instructor for the National Fire Academy's Responder Health and Safety Curriculum, and is an FAA-licensed private pilot. Thank you for joining us, Dustin. How are you?

I'm doing great today. Thank you for having me. How are you doing?

I'm doing well.

So, what led to your interest in emergency vehicle crashes?

Well, as you mentioned in my bio, my background was in safety — occupational safety — and as I moved on, I wanted to do research that tied my professional career in with my educational career — educational background in safety. So, I started just doing a quick examination, which anybody who has had Firefighter 1 knows that leading causes of firefighter deaths are going to be cardiac stress related.

I started looking at the traumatic and safety side and acute traumatic deaths in the fire service, and continually for decades now, vehicle crashes — emergency vehicle crashes — have been one of the leading causes, if not the leading cause of traumatic death. And in fact, firefighters are more likely to die on their way to a fire than they are inside of an actual fire, and that hasn't really changed over the years.

So, that piqued my interest. It was a well-known problem. But what really, I think, scared me the most is the fact that we're most likely to kill civilians than we are firefighters inside of the vehicle. So, a fact that really piqued my interest was that we kill, on average, about 10 civilians for every 1 firefighter that we lose in a vehicle crash, which is terrible.

Yeah, terrible.

And of course, the liability side — the legal side — that the cost to departments. So, it's a big issue and really has not gotten much better in recent years. So, that made me want to really focus on that and see what I could do to help solve that problem.

Yeah, and especially they're actually driving to help somebody and then there to be that type of an outcome, it would be hard for them to handle — to deal with in the first place.

Exactly. You've got that ripple effect of now they can't provide the service that they were originally set out to, to provide. So, yeah, it's not just the crash that has the impact, it's the ripple effect that goes on.

So, what leads to most emergency vehicle crashes?

You mentioned at the start about some of the recent research on the conspicuousness of vehicles. So, you know, we look at reflectivity; we look at lighting. That's a big one, and really interesting studies on that. And the U.S. Fire Administration even has focused on tanker or tenders depending on what part of the country you're from.

Trucks, because they're so dangerous. In fact, the leading cause — root cause of most crashes is the human factor. It's the person setting behind the driver's seat, and that ultimately is who has control over that vehicle, so that it kind of makes sense that that would be a root cause. So, I just sort of kept asking why, so we know that it's human factors, and well, why is that?

And the common denominator is a sense of urgency for the driver, that "get there-itis" is a term I've heard used before. So, we have a sense of urgency to get to the scene at all costs, no matter what. Which leads to aggressive and risky driving behaviors. And changing your risk perception a little bit whenever you have that sense of urgency pushing you in the back of your mind.

So, that's where I really, really focused. And an anecdotal example was in, I think, 1979 in Catlett, Virginia, just south of D.C., there was an engine that was responding to a car fire that missed the driveway, went about a mile too far, had to turn around and come back. In the meantime, the chief had beat him on scene.

There was a whole series of events that really led them to a sense of urgency to get there. And, as they were turning up the driveway, the 5 firefighters on board pulled in front of an Amtrak train going 75 miles per hour, which, as you can imagine, didn't end well, led to a couple fatalities as the 2 front firefighters derailed a dozen or so train cars.

And what was just a simple, you know, single company response snowballed into multiple agencies from multiple counties responding and after a pretty in-depth investigation into that, they determined that it was that sense of urgency. The witnesses said that the engine driver didn't even look both ways before he crossed the tracks.

He was focused on fire. So, you know, great example of what led to my research questions.

Yeah, so you said this led to your research question. So, why do drivers experience this sense of urgency? I mean, we know that they had just got called onto a fire and possible people at risk, but what are some of the factors that are associated with that emergency response?

Right. So, there's a lot of things. The way that you are dispatched is what really piqued my interest. I was able to attend — in 2011, I think — to hear a presentation at the IAFF's Redmond Symposium on research that was done in Detroit, where they studied firefighters’ physiological response, mainly to fires, but what they found during that was that at the time of dispatch, a firefighter's heart rate will jump up.

And of course, you have a startle response, but what was interesting was it was dependent on the type of dispatch that they were responding to. So, fires in 1 study, I don't believe it was that one, but fires whenever they heard the word “fire” led to a more physiological arousal state.

So, more excited state of mind than did maybe a medical call. And what was noticed was that anytime the word entrapment was involved, that their heart rate went to red line. I mean, it was almost as high as the actual doing the work itself once they got on scene. So, that was a pretty good indicator that, you know, maybe we don't perceive all calls the same way.

And if it was affecting us — certain calls, certain dispatches led to more urgency — then maybe that leads to more risk. So, I wanted to correlate those 2 things. So, what I decided to ask was that right there. Does the type of response, the type of incident that we are responding to correlate with an increased risk of crash?

And how I was able to test that was using the U.S. Fire Administration's databases that already exist. I was just able to code those a little bit differently than what had been done in the past. So, the first thing that I did was looked at the firefighter fatality database, and I had to read through the narratives.

Each one of those has a narrative, which I would encourage anybody in the fire service to take the time to read some of those because it's really sobering. Because of so many of those actions are things that many of us do every day. So, I read through probably 2,000 fatalities, pulled out all the ones that were involved in a crash, and then of those, I pulled out the ones that were involved in a response or returning from a call.

So, my first question was, is there increased risk during responses compared to returning? Because those should be about the same trip. The distance from the station to a fire is about the same distance, or they're the exact same distance, than the return trip. So, that was my first question. So, I was able to determine that from that database. And then the next question was, what were they responding to whenever the crash occurred? So, of course, I excluded just driving to a training session or driving between stations, anything like that.

It was — just had to be during a response. So, that was the first set of data that I was able to code all that from, and I coded it very similar to the NFIRS coding system, because that was where I had to pull some other data from. So, what I found was 144 fatalities occurred while responding to an emergency of some sort.

Actually, that was 144 cases, not necessarily fatalities. So, some of those crashes occurred or led to multiple fatalities, but we considered that 1 case, 1 crash case. So, 144 occurred while responding. Only 12 cases occurred while returning, so 12 times more crashes happened while responding than returning from crashes.

So, that confirmed what we presume to be true, is that there's a lot more risk involved in emergency response than there is just normal driving, and that reinforced a lot of previous research that happened leading up to this.

So, as I looked at the types of incidents they were responding to, I noticed a trend very quickly that fires in general made up the majority of those.

And in fact, just fires in general, all types of fires, made up about 56% of the fatal cases that led to a firefighter — 1 or more fatalities of a firefighter. Now, 56% might not seem like that big of a deal. And that led to my next question, which I had to pull from the database to control for how many fires do we respond to?

You know, if it's 56% of the fatal crashes, and we have about 50% of our calls be fires, then that's not really significant at all. So, then I pulled from the NFIRS database to see what our average nationwide fire department responses is. And as many of your listeners I'm sure are aware, most of the responses aren't fires in the U.S. fire service today.

Most are medical in nature and actually a small percentage are fires. That also wasn't the whole thing. I also had to account for how many vehicles — how many apparatuses or vehicles responded on average to each type of fire. And of course, a house fire would have more engines and ladders and vehicles responding to it than would a routine medical call, or maybe even a minor vehicle crash.

So, I had to account for those 2 things to really give a solid statistic. Combining those, what we call it is an exposure. So, fires made up a little bit less than 12% of the exposures. That's accounting for number of fires and response vehicles going to each one but accounted for almost 56% of the crashes.

So, that was strongly disproportionate. Among those, the worst offender was structure fires. So, structure fires only make up for a little less than 7% of the exposure responses but made up 35% of the total fatal crash cases. So, very disproportionate there when it comes to structure fire.

So, that was the highest risk response that was assessed here. Moving down to the EMS type of calls, EMS calls as a whole make up a little over half — 53% of the response’s nationwide vehicle responses, but only made up about 37% of the crashes. But, within those, when you start looking at rescues where you have potentially somebody entrapped, which makes up a little less than 12% of the total exposure responses, that accounted for almost 27% of the total fate of crashes.

So, again, very disproportionate numbers there. So, whenever you crunch those numbers and look at the actual risk, what's called a risk ratio relative to everything else when firefighters are responding to a fire compared to all other types of incidents, they encounter about a 9.5 times higher risk of a fatal crash occurring than they do any other type of response.

And the worst of those is a structure fire. When looking at structure fires compared to EMS calls — so EMS are the most common type of call and structure fires are what we would imagine the pinnacle of our training to be. It's almost 20 times higher risk between those 2 types of responses. So, it was a very significant finding.

It was sobering for sure to see the numbers as they played out, and I knew it was going to be bad as I started counting, but I didn't realize it was going to be that bad. So, yeah.

So, did you come up with any solutions to the problem?

Well, that was sort of where I stopped, and then officially for my schooling project.

But, of course, I had that question in my mind and wanted to look at, okay, how do we calm down? So, an interesting thing that I noticed back in that Detroit study was that more senior firefighters — more experienced veteran firefighters — didn't have nearly as much of an excited response to the call.

That's not much surprise. You know, they've been there done that, and they know what to expect is really what it is. So, the good news is that you can train for that, and we've got technology now that is great for this, but you can, you know, simulate the responses before they even happen. So, if we can desensitize ourselves to fires — structure fires — and make it more routine in our minds, that’s going to lead to a decreased sense of excitement.

I think that probably maybe the biggest thing is a bit of a culture change. I like to say that the response time between your station and that emergency incident is out of your control. And we have to accept that. The distance between the fire and your fire station is set.

So, if it’s 2 miles today, it’s going to be 2 miles forever. If it’s snowing, then it’s going to be a slower response. Even though the emergency hasn't occurred yet, the amount of time it takes you to get there is out of your control. And we have to accept that there are some things that are out of our control.

The things that are in control — in our control, of course, that's what we need to really focus on, you know, being very efficient in the station and being very efficient once we get on scene. But, if we accept that, then we're going to have a little bit less sense of urgency.

The other thing is, the military, especially Special Forces, has some breathing techniques, such as box breathing. You can Google that if you're interested. And also what's called a physiological sigh. Both of those are really good tools that can help you calm down and not only become a better driver, be more aware, but also a better decision-maker once you get on scene.

So, it's a great tool for officers, too, that might have to make those spur of the moment high-stress, high-urgency decisions once they get on scene. So, that's going to help increase your situational awareness for everyone. If we can just learn to reel it in a little bit and stay within our — stay in our minds.

Yeah, I think I read a study not too long ago that was saying that, and this was talking about ambulances going and speeding to a rescue, and that medically, there was not a correlation. It's like if they got there faster, 2 minutes faster did not make a medical difference to the patient that they were working on.

So, they should have taken that 2 extra minutes to get there safely because it's not going to make that much of a difference to the person that you are going to. Now, I'm sure there's outside cases and there's outliers and those types of things, and we know that if somebody's bleeding and they're not breathing, you want to get there quick.

But as you said, with this story from Virginia, you want to get there and you can't if you have an accident, and then they're even waiting longer for them to redispatch for somebody else to come behind you.

You see a lot of progressive agencies now are using that research, and there's been a lot of research recently on exactly the topic you are talking about to reinforce the fact that not everything is a true emergency, and based on that dispatch information, you have to determine whether that increased risk of running lights and sirens to a call is worth it. And many progressive departments are reeling that in a lot and determining, okay, here's a set list of types of calls that we will consider a true emergency, but everything else that couple minutes isn't going to make a big difference for the amount of risk that we're putting our members and also the general public in to — to get there.

And you're right, it spans across fire and EMS and law enforcement too. Of course, each one of those has their own dispatches that are going to increase their level of excitement.

One of the things I thought was interesting was that law enforcement officers have an increased arousal response whenever they have to back up another partner. Also, anything that involves weapons was the 2 higher level of stressful types of dispatches, which wasn't much surprise. I mean, there's a lot of camaraderie in law enforcement and anytime that you hear somebody is in need, you want to hurry up and get there.

And in EMS, it was children, any calls that involved children. Again, no surprise, but those dispatches lead to higher heart rates, higher respirations, higher stress hormones. So, there's another research project if anybody wants to duplicate this in the EMS realm, for sure.

And also — I was reading the article that you wrote — it's also people, especially because we have a large part of the United States that is covered by volunteer fire departments, and so there's people responding in their vehicles to fires.

I know that last memorial weekend, a family had lost both of their sons in a car crash going to a fire. And it's just like you said, how do we get people to understand that slowing down is not going to change too much. If we know by other fires, if we know that a house can be within flashover in 4 minutes, you're not going to get there.

So, I mean, come on, let's think this through because we already know that we're against time, and I understand to know that there's people trapped that you want to get there, but you have to consider if it's in flashover in 4 minutes, we know smoke kills before flame in the majority of cases, then what are you rushing to?

You don't want to take 30 minutes, but you can take that extra minute or 2 minutes to not go 65 miles an hour through a town.

And who's going to make the most difference in those calls is going to be the first-arriving apparatus. And many of these crashes were for mutual aid responses. So, even going a county away or the second-, third- or fourth-due apparatus.

Which, maybe there's a causal link there that when you already feel like you're behind the ball or behind the game a little bit, you have even more sense of urgency since you're not the first one there.

Yeah, and I know this sounds awful and maybe this is something we have to edit out later.

You know, also, am I going to miss it? You know what I mean? Almost like, am I going to miss it? Because like we said, a lot of our calls are not for fires, and so when there is one, everybody wants to get on it, because they don't know when the next one is going to be, and I don't mean that they're a bunch of yahoos or whatever, but it is, I mean — when I was in the military, when things were happening, I wanted to be there.

You know, that's where I wanted to be. I didn't want to be back in the States. I wanted to be where the action was happening. Even if I wasn't right there on the front lines, I still wanted to be in it. And so, I can 100% understand that's how they would feel as well.

That's the analogy that I like to make is, you have soldiers, anyone in the military, they finish up their basic training and they're perfectly okay going to war.

I mean, many occupations, because that's what they are trained for. They've received all this training, you know, top-notch training, and they want to use it.

And when you feel that confident in your skills, you want to use your skills. So, I understand that. Everybody wants a key to the city, you know, everybody wants to save the day.

But we have to realize that we're saving the day just by showing up and doing the job.

And we want you to be around. We want you to be around in the fire service for quite some time and training people up behind you. So, it's for us as well. It's for your brothers and sisters that are on the line with you that you take that time, and you take care of yourself as well.

Yeah, and I've got to clarify too that I'm not advocating for a completely risk-averse fire service. This is a risky occupation at times, but there are very, very few instances in my 20-some years that I have felt that an urgent need to take extreme risk was actually justified, and that assumption of risk isn't until we get on scene and make sure that that risk needs to be taken. So, we really have to sort of stand back and determine what we're weighing. But yeah, there certainly is times for it, but it's, it's very few, very far between.

Yeah, especially for the amount that you're saying that it is actually happening. So, are there any other nuggets that you got from your research that you just think, maybe it wasn't one of those 5 bullets or whatever that you put at the front, but you were like, hmmm?

Most — and you sort of alluded to it a little bit ago — most of the crashes were about — actually two-thirds of them were amongst volunteer firefighters, which — be a solid warning to the listeners who are in volunteer fire service that you are at increased risk for a fatal crash to occur.

Now that might seem proportionate, but if you look at most of the U.S. population is protected by career departments, then that's going to be who's running most of the calls. So, that was a little bit disproportionate. I didn't go any further than that. That was just a sort of side finding that I was like, that's sort of interesting.

And that was an apparatus or was that in POVs?

That was everything, every type of vehicle. So that was all vehicles combined, which also led to what type of vehicle they were in. And a good proportion — let me get you an actual number here — was in personal vehicles, as opposed to other types of vehicles, as opposed to tankers or tenders or engines or ladders.

So, many of those were personal vehicles.

So, is there anything else you'd like to add? We have a retired colleague, Bill Troup, and his whole thing was about vehicle safety. And he was just completely devoted to health and safety in general for firefighters, but that vehicles — and I remember when the conspicuity research came out, it was just, he was so proud, and he worked really hard to get good research for those types of manuals to go out to the fire service.

Because we're concerned about so many things about safety, and sometimes we forget the low-hanging fruit of maybe we just go a little bit slower and maybe that's the low-hanging fruit of saving some.

Yeah, you’re absolutely right, we have to just reel it in and stay in our mind and realize where that risk is.

And yeah, all those things with vehicles, they all matter, but ultimately, it is the driver which is the hardest thing to control. You know, it's easy to paint vehicles different colors, add more stickers, add more lights here and there. The hardest thing to control is the behaviors of the person behind the wheel.

So, when you're climbing into that front left seat, assuming you're in the U.S., then you have a lot of responsibility on your shoulders. And just the end of the day, I was responding to a call, and I was thinking to myself, what’s something that would hit home to me, that would make me maybe want to change my behaviors, and I imagine my wife and a baby boy standing along the road somewhere between here and that call.

How would I drive? If I imagine I know they're somewhere along the road, and that hit home to me. So, I would take no risks at that point, which is how we should see everybody's families who are out along our highway.

And also, to kind of think about the family that you have at home, you know, that wants to make sure that you come home. They already are dealing with those other risks that they know of. They know you could get in a fire, you could — something, you know, the floor could go out, any of these things, you could fall.

So, they already kind of know those but then to be driving to it or returning or something and to lose you in that type of way, that would be really hard.

Yeah, it's easy to get complacent with that, and what's even scarier is that whenever you are excited to a certain level, you don't realize you are inhibited by that.

It's just like being drunk. You know, after a few beers, many people think they're perfectly fine to drive. They don't realize that they're inhibited. They don't know that their responses are delayed. And acute stress is the same way. When you are under acute stress, you get tunnel vision. That's where you'll notice that you get in the truck to respond to a call and you can't hear what the dispatcher or anybody else is saying, so you crank the radio up and then you get back in the vehicle to go back home. And it's like, ah, why is that so loud? But nobody touched the volume.

So, yeah, that's — that's what's happening is your stress level is different. Whenever you get back in to just calmly drive back, then whenever you respond. So, if you're having that happen, that should be a red flag to you that yeah, work on some ways to reel it in and calm down a little bit.

Well, thank you, Captain Lambert, for joining us today.

If listeners would like to get in touch with you about this topic, what would be the best way for them to reach out?

They could just shoot me an email. Dusty, D-U-S-T-Y, Lambert, L-A-M-B-E-R-T, at gmail.com.

Well, thank you for listening to the USFA Podcast, and if you have a topic or a speaker you would like us to interview, please email the show at [email protected] . That's what Dusty did. That's how he's on the show. And don't forget to subscribe to our show. We share new episodes every third Thursday of each month, and you can visit us at usfa.fema.gov or on social media by searching @usfire. But until next month, stay safe.

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We share our new episodes every third Thursday of the month. You can visit us at usfa.fema.gov or on social media by searching “usfire.” Until next month, stay safe.