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Abstract

Research shows that person-centered statistics are useful for identifying coping profiles in adolescents and adults, including college students, where such studies are limited. This study aimed to discern coping profiles among American college students and examine associations with mental health outcomes. Participants completed the Brief COPE inventory, Depression, Anxiety, and Stress scale – 21 items (DASS-21), and a demographics form. Using latent profile analysis, we identified three latent profiles including: disengaged/low, approach, and avoidant copers. Participants assigned to the approach and disengaged/low coper profiles reported lower levels of stress, anxiety, and depression than members of the avoidant coper profile. Interestingly, approach and low copers reported similar levels of stress, anxiety, and depression. The results provide insight into the contribution of coping categories (e.g., problem-focused, avoidant, etc.) to mental health concerns and have the potential to support institutional efforts to improve university students’ ability to cope with academic stressors.

Keywords

Coping latent profile analysis university students

Introduction

Considerable research has been conducted to explore the determinants of student success within higher education settings. The results of this area of study have provided evidence that success within university settings is closely associated with students’ ability to navigate ongoing academic, social, and professional stressors (Alhasani & Orji, 2024; Pascoe et al., 2020). Available evidence suggests that a significant number of university students struggle to effectively cope with everyday stressors within and beyond academic settings, which contributes to the experience of elevated levels of stress, anxiety, and other related mental health concerns. For instance, investigations with diverse populations have estimated that approximately 15–30% of university students report potentially debilitating levels of anxiety, depression, and perceived stress (ACHA, 2019; Bayram & Bilgel, 2008; Eisenberg et al., 2007; Hunt & Eisenberg, 2010). Unfortunately, the experience of elevated stress, anxiety, and other related mental health concerns have been shown to undermine student psychological well-being, physical health, academic motivation, and academic performance and are powerful predictors of student attrition (Nieuwoudt & Pedler, 2023; Pascoe et al., 2020; Ribeiro et al., 2018).

Research focused on behavioral and cognitive reactions to stress suggests the experience of emotional distress and other mental health-related concerns can be partially attributed to the use of maladaptive coping responses (Cooper et al., 2006). Although the identification of effective coping responses is a source of considerable debate (Somerfield & McCrae, 2000), there is a general consensus that “maladaptive” coping involves the selection of strategies that cannot adequately alter or eliminate the source of stress or fail to help the individual achieve a desired outcome (Cassady & Boseck, 2008; Crick & Dodge, 1994; Folkman & Moskowitz, 2004). Given the importance of coping to adaptive social and emotional functioning, recent work has focused on better understanding how “adaptive” and “maladaptive” coping processes interact to influence important outcomes using person-centered statistical methods – techniques used to identify unique subpopulations or groupings within a sample. These investigations have identified unique coping profiles within adolescent, emerging adult, and adult populations exposed to a variety of stressors that differ along important affective, cognitive, and behavioral outcomes (Aldridge & Roesch, 2008; Doron et al., 2014; Gaudreau & Blondin, 2004; Kavcic et al., 2022). However, investigations of coping processes using person-centered analytic methods within academic settings are scarce (Freire et al., 2020), with relatively few focused on identifying coping profiles among university students within the United States context. Therefore, the purpose of the current study was to investigate the coping responses of American university students using person-centered analytic procedures.

Coping

Transactional process models view coping as a dynamic process involving the implementation of behavioral and cognitive processes directed at regulating internal and environmental factors within situations with a high level of personal significance (Folkman & Moskowitz, 2004; Lazarus & Folkman, 1984; Skinner & Zimmer-Gembeck, 2007). Although people report considerable diversity in their responses to stressful and challenging situations, past work has suggested that individual coping responses can be classified as belonging to one of three higher-order categories: problem-focused, emotion-focused, and avoidant. Problem-focused coping strategies include responses that are directed at altering the perception of or eliminating sources of stress (MacCann et al., 2011). Emotion-focused coping involves efforts to down-regulate the experience of negative emotions following the determination that an event has the potential to impede goal progress (Folkman, 1984). Finally, avoidant coping involves efforts with the explicit goal of disengaging from sources of stress or negative emotional states (Parker & Endler, 1996).

Evaluating the effectiveness of individual and categories of coping responses continues to be a source of considerable debate in the literature, as coping outcomes often vary as a function of the characteristics of the stressor (Somerfield & McCrae, 2000). However, there is general agreement that efforts to eliminate sources of stress (i.e., problem-focused coping) when situational control is possible are associated with adaptive outcomes (Dyson & Renk, 2006; Lapierre & Allen, 2006; Riley & Park, 2014). Further, a considerable body of empirical work has demonstrated that individuals who rely on strategies involving regulating emotional responses and avoiding sources of stress tend to be at increased risk for negative academic, social, mental, and physical outcomes (Austin et al., 2010; Turner-Sack et al., 2012). It is important to note, however, that emotion-focused and avoidant strategies can support adaptive outcomes when it is difficult to eliminate or modify stressor(s) and in situations where disengagement provides individuals some reprieve from negative emotions and general distress caused by a long-term stressor (Beasley et al., 2003; Carson & Polman, 2010; Zeidner, 1995).

Person-Centered Coping Investigations

A review of prior coping investigations shows that researchers have historically relied on variable-centered statistical procedures to describe the antecedents and outcomes of various coping strategies. Variable-centered analytic approaches are commonly used within psychological and education research and are designed to analyze sources of variation to determine if relationships exist between a collection of variables (Laursen & Hoff, 2006). Commonly used variable-centered techniques include correlation, regression, analysis of variance (ANOVA), and factor analysis (Howard & Hoffman, 2018). Although the use of these procedures has expanded our understanding, researchers have long advocated the field’s reliance on variable-oriented investigative methods has made it difficult to develop a fully realized understanding of the coping process (Eisenbarth, 2012). Specifically, it has been suggested that variable-centric methods make it difficult for investigators to determine how coping responses interact to influence outcomes of interest (Doron et al., 2014; Eisenbarth, 2012).

In response to these criticisms, coping researchers have begun using person-centered analytic approaches within their investigations. Person-centered statistical techniques – such as latent profile analysis and cluster analysis – allow researchers to identify subpopulations within a sample that demonstrate homogeneity on a collection of observed indicators (Nylund-Gibson & Choi, 2018; Williams & Kibowski, 2016). Stated another way, person-centered statistical methods are designed to identify subgroups that share certain characteristics (Howard & Hoffman, 2018). Critically, the focus on the characteristics of individual participants can provide a more holistic view of the interaction between the variables in comparison to variable-centered procedures (Daljeet et al., 2017; Han et al., 2017; Pastor & Barron, 2012).

Prior work has demonstrated that person-centered methods can be used to identify subgroups that differ in their preferred methods of coping with stressful events and has shown considerable promise in expanding our understanding of the antecedents and outcomes of particular coping patterns. For instance, Pété, Leprince, Lienhart, and Doron (2022) subjected French athletes’ responses to the Brief COPE inventory to latent profile analysis and identified four unique profiles, including self-reliant copers (i.e., moderate cognitive restructuring and distraction), engaged copers (i.e., high problem solving), avoidant copers (i.e., high avoidant coping), and active and social copers (e.g., moderate use of support seeking and problem-solving and cognitive structuring). In another representative example, Aldridge and Roesch (2008) subjected responses to the COPE inventory provided by minority adolescents to latent profile analysis and identified three unique profiles. Specifically, participants were classified into groups characterized by (1) low levels of overall coping (i.e., low copers), (2) reliance on approach-oriented coping methods including active coping and planning (i.e., active copers), and (3) use of avoidance-oriented strategies such as denial, substance use, and behavioral disengagement (e.g., avoidant copers). More recently, Cheng and colleagues (2019) found evidence of two distinct coping profiles when assessing the mental adjustment of cancer survivors. Specifically, researchers showed individuals working to manage stress related to a cancer diagnosis demonstrated a preference for adaptive (i.e., low hopelessness, high fighting spirit scores, and low cognitive avoidance scores) or maladaptive (i.e., high hopelessness, high anxious avoidance, low fighting spirit scores, and high cognitive avoidance) coping strategies.

Perhaps more germane to the current study are those investigations that have used person-centered methods to explore the coping responses of university students. Although relatively rare (Freire et al., 2020), these investigations have provided insight into the prototypical coping patterns of students in a variety of cultural contexts. For instance, using latent cluster analysis, Doron and colleagues (2014) found evidence of high (i.e., high support seeking & distraction, moderate problem-solving & cognitive restructuring), adaptive (i.e., high problem-solving and moderate cognitive restructuring), avoidant (i.e., high avoidance), and low copers (i.e., low use of multiple strategies) within a sample of French university students. In another investigation, Yang and colleagues (2022) found evidence for four distinct coping profiles when assessing coping strategies for stress among Chinese college students using latent class analysis. Specifically, researchers identified emotional coping (i.e., high use of venting, humor disengagement, etc.), inactive coping (i.e., low use of humor, religion, social support, active coping, planning, etc.), support seeking (i.e., high use of instrumental and emotional support), independent and positive coping groups (i.e., high in positive coping and low use of social support; Yang et al., 2022). In a final example, Freire and colleagues (2020) found evidence of four distinct coping subgroups within a sample of Spanish university students. Specifically, the researchers identified subgroups characterized by low use of approach-oriented coping strategies, high use of social-focused coping approaches, reliance on cognitive approach approaches, and high use of general approach-oriented strategies using latent profile analysis.

The results of prior investigations have demonstrated the potential utility of using person-centered statistical methods to investigate coping processes among participants of different ages, living in different cultural contexts, and working to navigate distinct stressors. One notable characteristic of prior person-centered coping investigations is the variability observed in the number of coping profiles identified and the characteristics of the subgroups. Thus, additional work is needed to identify common coping responses within academic settings, as this information could provide insight into how best to support the psychological, physical, and academic well-being of learners.

The Current Study

The current study had two primary aims. First, we sought to better understand the coping responses used by university students confronted with situational demands that exceed their perceived personal resources. Specifically, we attempted to identify unique student subgroups based on their use of various coping strategies using latent profile analysis. Second, we sought to determine if members of the identified profiles reported differing levels of anxiety, stress, and depression.

Method

Participants

Participants (N = 401, males n = 48 (12.31%), females n = 340 (87.18%), and non-binary n = 2 (0.51%)) were undergraduate & graduate students attending a public university in the Southern United States. Our sample included participants from a variety of ethnic backgrounds including Asian or Pacific Islander (n = 11, 2.83%), Hispanic/Latino (n = 71, 18.25%), Black or African American (n = 26, 6.68%), Caucasian or White (n = 266, 68.38%), Native American or American Indian (n = 1, 0.26%), two or more races (n = 6, 1.53%), South Asian (n = 1, 0.26%). A small percentage of respondents elected not to report their ethnicity (n = 4, 1.03%). Additionally, we were missing gender information for eleven participants. The mean age of participants was 26.15(SD = 8.25).

Measures

DASS-21

We assessed the severity of participants’ negative emotional states using the Depression Anxiety Stress Scales (DASS-21; Lovibond & Lovibond, 1995). The DASS-21 is a 21-item instrument designed to measure depression (i.e., “I couldn’t seem to experience any positive feelings at all”), anxiety (i.e., I was aware of dryness in my mouth”), and psychological stress (i.e., I found it hard to wind down). Participants reported how well each statement described their affective experiences over the past week using a 4-point Likert-type scale (0 = did not apply to me, 3 = I have been doing this a lot). Responses to items in each domain were summed and multiplied by 2 to create indices of stress, anxiety, and depression. The scores are interpreted such that higher values indicate greater levels of the construct (Lovibond & Lovibond, 1995). Psychometric investigations have provided evidence of the structural (Henry & Crawford, 2005) and predictive utility (Ronk et al., 2013) of the instrument when applied to clinical and non-clinical samples. The depression (Cronbach’s α = .91, Mc Donald’s ω = .91), anxiety (Cronbach’s α = .88, McDonald’s ω = .88), and psychological stress (Cronbach’s α = .87, McDonald’s ω = .88) subscales demonstrated excellent levels of internal consistency in the present study.

The Brief COPE

We assessed how participants have been coping with stress using the Brief COPE (Carver, 1997). The Brief Cope is a 28-item, self-report instrument designed to assess the extent to which individuals use 14 conceptually distinct coping reactions when confronted with situational stressors. Specifically, the inventory assesses the use of active coping, positive reframing, planning, acceptance, humor, religion, using emotional support, using instrumental support, self-distraction, denial, venting, substance use, behavioral disengagement, and self-blame using a 4-point Likert-type scale (1 = I haven’t been doing this at all, 4 = I’ve been doing this a lot). The average of the responses associated with each coping strategy is calculated to create an index of its usage, with higher values indicating a greater utilization of that particular coping response. Previous studies have demonstrated the structural validity of the Brief Cope inventory using exploratory factor analysis techniques (Carver, 1997). The results of a reliability analysis indicated that the coping subscales demonstrated acceptable to excellent internal consistency (Cronbach’s α’s .60–.94) in the current investigation.

Procedure

Participants were recruited as part of their involvement in an undergraduate/graduate research pool. Specifically, students in select education courses received course credit for acting as a participant in approved research studies or by completing alternative assignments requiring similar time and effort commitment. All data were collected using the Qualtrics online survey platform (Qualtrics, Provo, UT, https://www.qualtrics.com) and participants provided informed consent before completing study materials. This study was approved by the University of Texas at Tyler Institutional Review Board.

Analytic Plan

First, descriptive statistics were calculated for the variables of interest to gain insight into the broad characteristics of the dataset. Next, Pearson’s product-moment correlation coefficients were used to gain greater insights into the general relationship among broad coping constructs and estimates of student anxiety, stress, and depression.

We attempted to identify coping profiles by subjecting participants’ responses to the Brief COPE to latent profile analysis. As highlighted in the opening section of the manuscript, past work adopting a person-centered orientation has provided evidence that individuals demonstrate unique coping preferences when confronted with sources of stress. Therefore, we investigated the viability of 2-, 3-, and 4-profile solutions identified in prior work (Cheng et al., 2019; Doron, Thomas-Ollivier, Vachon, & Fortes-Bourbousson, 2013; Yang et al., 2022). The COPE inventory subscale scores were converted to z-scores to support the interpretation of the identified profile grouping. The appropriateness of each solution was evaluated using Akaike Information Criterion (AIC; Akaikie, 1974), Bayesian Information Criterion (BIC; Schwarz, 1978), sample-size adjusted Bayesian Information Criterion (SBIC; Sclove, 1987), entropy values, the results of the bootstrapped likelihood ratio test (BLRT; McCutcheon, 1987), average posterior probability values, and the alignment of profile content with existing research. AIC, BIC, and ABIC are relative fit indices that provide insight into how well different solutions fit predicted patterns in the observed data and are interpreted such that lower values indicate better model fit. Entropy is an index of classification accuracy with higher values suggesting a particular solution has a clear delineation among identified groupings (Celeux & Soromenho, 1996; Nylund et al., 2007). An appropriate level of classification accuracy was indicated by entropy values exceeding .80 (Jung & Wickrama, 2008). The BLRT is a statistical procedure that compares the fit of a target model to another solution that specifies the existence of 1 less profile. A significant BLRT value indicates the target model provides a superior fit to the observed data compared to the k – 1 alternative. Average posterior probably values provide insight into the likelihood that participants have been sorted into the correct latent profile. In this investigation, mean posterior probability values of .80 or greater were taken as evidence of adequate classification accuracy (Spurk et al., 2020). Finally, we considered the results of past investigations that have generated coping profiles using person-centered analytic methods, the conditional-response patterns of the other coping profiles, and the alignment of profile characteristics with dominant coping frameworks when evaluating the appropriateness of each latent profile solution.

After identifying the optimal solution, we reviewed mean z-score values to better understand the characteristics of members of the extracted profiles. The magnitude of z-score means were evaluated considering their absolute values (ABS) and the following criteria: average scores, ABS z-score between .00 and .20; slightly high/low scores, ABS z-score between .20 and .50; high/low scores, ABS z-score between .50 and .80; very high/low scores, ABS z-score above .80 (Walsh et al., 2023).

Finally, a series of one-way ANOVA tests with Scheffe post hoc comparisons were used to determine if individuals assigned to the identified coping profiles reported differing levels of anxiety, depression, and psychological stress. The p-values for the omnibus tests were adjusted using the Bonferroni correction to prevent Type I error inflation resulting from the use of multiple hypothesis tests to investigate the possibility of group differences.

Results

Descriptive Statistics and Correlational Analysis

A series of correlational analyses were conducted to explore the relationships among coping strategy use, anxiety, depression, and stress. The results of the analyses showed that coping strategies involving efforts to avoid or disengage from sources of stress (i.e., self-distraction, denial, substance abuse, behavioral disengagement, and self-blame) were positively correlated with self-reported depression, anxiety, and psychological stress. Further, our results suggest that coping responses directed at eliminating environmental stressors (i.e., planning, active coping, and positive reframing were negatively associated with anxiety, stress, and depression. However, it is important to note that the association between planning and stress did not reach statistical significance. Interestingly, coping strategies involving the support of social others (i.e., using emotional support & using instrumental support) were not associated with stress, anxiety, or depression in the current investigation. Descriptive information for and correlations among the variables of interest is presented in Tables 1 and 2.

Table 1.

Descriptive Information for the Primary Constructs of Interest.

Variable	Mean score	SD	α	ω
Psychological stress	31.31	10.95	.87	.88
Anxiety	26.18	10.92	.88	.88
Depression	25.52	11.01	.91	.91
Self-distraction	3.08	0.74	.62	.62
Active coping	3.09	0.71	.81	.81
Denial	1.57	0.77	.83	.83
Substance use	1.52	0.84	.93	.94
Use of emotional support	2.81	0.92	.89	.89
Instrumental support	2.84	0.88	.90	.90
Behavioral disengagement	1.59	0.74	.87	.87
Venting	2.15	0.76	.60	.60
Positive reframing	3.05	0.81	.85	.85
Planning	3.24	0.74	.82	.82
Humor	2.59	1.03	.90	.90
Acceptance	3.14	0.64	.63	.63
Religion	2.88	1.08	.93	.93
Self-blame	2.44	0.98	.86	.86

Table 2.

Pearson Product-Moment Correlation Coefficients Between Coping Indicators, Anxiety, Stress, and Depression.

Variable	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17
1. Stress	-
2. Anxiety	.77*	-
3. Depression	.75*	.72*	-
4. Active coping	−.16*	−.21*	−.27*	-
5. Planning	−.04	−.11*	−.13*	.68*	-
6. Positive reframing	−.25*	−.23*	−.29*	.51*	.43*	-
7. Acceptance	.02	−.04	−.07	.34*	.29*	.36*	-
8. Humor	.14*	.13	.13*	.05	.06	.08	.33*	-
9. Religion	−.11*	−.06	−.18*	.26*	.15*	.30*	.09	−.06	-
10. Using emotional support	.03	.04	−.02	.30*	.23*	.18*	.08	.03	.25*	-
11. Using instrumental support	.00	−.07	−.07	.33*	.15*	.15*	.04	.01	.25*	.80*	-
12. Self-distraction	.20*	.11*	.12*	.23*	.24*	.24*	.24*	.17*	.09	.25*	.22*	-
13. Denial	.20*	.34*	.31*	−.14*	−.15*	−.11*	−.14*	.12*	.04	.08	.02	.00	-
14. Venting	.27*	.29*	.24*	−.07	−.05	.03	.03	.21*	−.02	.26*	.24*	.13*	.39*	-
15. Substance use	.13*	.16*	.23*	−.21*	−.20*	−.06	−.06	.21*	.22*	.00	−.09	−.02	.31*	.24*	-
16. Behavioral disengagement	.31*	.41*	.51*	−.19*	−.19*	−.10*	−.10*	.21*	−.09	−.03	−.12*	−.02	.61*	.36*	.40*	-
17. Self-blame	.48*	.42*	.48*	−.08	−.08	−.00	−.00	.25*	−.14	.03	−.00	.20*	.34*	.41*	.21*	.52*	-

Note. *p < .05.

Latent profile analysis

The AIC, BIC, and SBIC values were lowest for the 4-profile model suggesting the latent profile solution provides the best fit to the observed data. The superiority of the 4-profile solution is further reinforced by BLRT results, indicating the model provides a superior fit compared to the 3-profile solution, which was also shown to outperform the 2-profile solution. Finally, entropy and average posterior probability values fell within accepted limits, suggesting the latent profile solution demonstrated an acceptable level of classification accuracy in the current investigation. Although the statistical indices supported the viability of the 4-profile solution, a review of conditional response mean z-scores showed this model was difficult to interpret and had little connection to the existing coping literature. The z-score means of participants assigned to each of the identified profiles is presented in the supplemental materials for this article (Table S1). Thus, the 3-profile solution was retained as it demonstrated an acceptable model fit according to the statistical indices and was interpretable. (Tables 3 and 4).

Table 3.

Model Fit Indices for the 2, 3, 4 Profile Solutions.

Model	Log-likelihood values	AIC	BIC	SBIC	Entropy	Prob_min	Prob max	n-min	BLRT
2 profile	−7407.09	14,894.18	15,064.62	14,928.18	.87	.94	.94	.33	632.87*
3 profile	−7228.58	14,573.16	14,803.05	14,619.02	.85	.90	.95	.27	351.01*
4 profile	−7128.58	14,403.17	14,692.51	14,460.88	.87	.88	.95	.17	199.99*

Note. p < .05

Table 4.

Z Scores for 3 Profile Solution.

Coping strategy	Profile 1: Disengaged/Low copers (n = 116; 29.82%)	Profile 2: Approach copers (n = 167; 42.93%)	Profile 3: Avoidant copers (n = 106; 27.24%)
Active coping	−.43	.58	−.45
Planning	−.29	.38	−.29
Positive reframing	−.31	.47	−.40
Acceptance	−.14	.22	−.19
Humor	−.18	−.09	.35
Religion	−.42	.40	−.17
Using emotional support	−.98	.64	.06
Using instrumental support	−.95	.70	.07
Self-distraction	−.29	.23	−.04
Denial	−.43	−.36	1.04
Venting	−.48	−.10	.69
Substance use	−.13	−.36	.71
Behavioral disengagement	−.36	−.58	1.32
Self-blame	−.18	−.35	.75

According to mean z-score values, participants assigned to profile 1, labeled “disengaged/low copers”, reported average levels of acceptance (z = −0.14), humor (z = −0.18), substance use (z = -0.13), and self-blame (z = −0.18). Further, members of this profile reported slightly low levels of active coping (z = −0.43), planning (z = −0.29), positive reframing (z = −0.31), religion (z = −0.42), self-distraction (z = −0.29), denial (z = −0.43), venting (z = −0.48), and behavioral disengagement (z = −0.36). Finally, participants assigned to this profile reported very low use of using emotional support (z = −0.98) and using instrumental support (z = −0.95).

Participants assigned to profile 2, labeled “approach copers”, reported low levels of behavioral disengagement (z = −0.58) and slightly low levels of self-blame (z = −0.35), substance use (z = −0.36), and denial (z = −0.36). Additionally, profile members reported average levels of venting (z = −0.10) and humor (z = −0.09). Members of profile 2 also reported slightly high levels of planning (z = 0.38), positive reframing (z = 0.47), acceptance (z = .22), religion (z = 0.40), and self-distraction (z = 0.20). Finally, profile members reported high levels of active coping (z = 0.58), use of emotional support (z = 0.64), and using instrumental support (z = 0.70).

The participants assigned to profile 3, labeled “avoidant copers”, reported slightly low levels of active coping (z = −0.45), planning (z = −0.29), and positive reframing (z = −0.40). The participants assigned to this profile also reported average levels of acceptance (z = −0.19), religion (z = −0.17), using emotional support (z = 0.06), using instrumental support (z = 0.07), and self-distraction (z = −0.04). Finally, profile members reported high levels of venting (z = 0.69), substance use (z = 0.71), self-blame (z = 0.75) and very high levels of denial (z = 1.04) and behavioral disengagement (z = 1.32).

Differences in Anxiety, Depression, and Psychological Stress Across Latent Profiles

The ANOVA analyses explored differences in stress, anxiety, and depression among the profiles identified in the latent profile analysis. The results of the analyses indicated there was a statistically significant effect of profile membership on self-reported stress, anxiety, and depression levels. Post hoc comparisons indicated that disengaged/low copers and approach copers reported significantly lower stress, anxiety, and depression than avoidant copers. Interestingly, there was not a statistically significant difference in stress, anxiety, or depression levels between disengaged/low copers and approach copers in the current investigation. Summary information for the ANOVA analyses can be found in Table 5.

Table 5.

Summary Table for a Series of One-Way ANOVAs Exploring Coping Profile Differences on Measures of Stress, Anxiety and Depression.

	Profile 1: Disengaged/Low copers	Profile 2: Approach copers	Profile 3:Avoidant copers	F	p	ω²
	M (SD)	M (SD)	M (SD)	F	p	ω²
Stress	30.08 (10.00)^a	28.98 (10.85)^a	36.49 (10.43)^b	17.80	<. 001	.07
Anxiety	23.60 (8.60)^a	23.42 (10.94)^a	33.32 (9.86)^b	37.18	<.001	.15
Depression	22.34 (9.54)^a	22.01 (8.95)^a	33.50 (11.53)^b	47.91	<.001	.19

Note. Scheffe post hoc analyses comparing group differences are summarized with superscripts (a, b). The difference between values sharing a subscript was not statistically significant.

Discussion

The purpose of the current investigation was to better understand the coping preferences of university students. Using latent profile analysis, we were able to identify three unique coping profiles, including disengaged/low, approach, and avoidant copers. Our data indicated that members of the approach copers profile demonstrated a preference for strategies directed at eliminating or altering the perception of sources of stress (e.g., active coping, positive reframing, planning), while members of the avoidant copers profile reported a preference for strategies supporting disengagement from stressors (e.g., substance abuse, self-distraction). Additionally, we identified a latent profile characterized by below-average use of coping strategies assessed by the COPE inventory (e.g., disengaged/low copers). These results are consistent with prior work suggesting there are important individual differences in the propensity to actively approach (i.e., approach coping orientation) or avoid (avoidance coping orientation) environmental stressors (Moos & Schaefer, 1993; Roth & Cohen, 1986). Perhaps more notably, the characteristics of these latent profiles are consistent with coping profiles identified using person-centered analytic methods within samples of American minority adolescents (e.g., active, avoidant & low copers; Aldridge & Roesch, 2008), French university students (e.g., adaptive, avoidant copers & low copers; Doron et al., 2014), French-Canadian athletes (high utilization of task-oriented coping, high utilization of disengagement oriented coping, & low utilization of all coping strategies; Gaudreau & Blondin, 2004), and Slovenian adults (e.g., engaged, avoidant & disengaged coping; Kavcic et al., 2022). The similarity of profiles identified within this study and prior investigations provide preliminary evidence of the existence of several fundamental coping profiles that manifest across developmental levels, cultural contexts, and stressful encounters.

Beyond providing information about broad individual differences in coping preferences, the current investigation was also designed to determine if members of the identified coping profiles reported meaningful differences in anxiety, stress, and depression. The approach copers in our investigation displayed lower levels of assessed mental health outcomes than avoidant copers. Although the effectiveness of coping responses is believed to be dependent on the nature of the stressor, these findings are consistent with empirical evidence noting that coping efforts focused on resolving underlying sources of stress are generally better able to support physical and mental well-being than strategies focused on disengaging from environmental stressors (Sheffler et al., 2019).

Our results also indicated that disengaged/low copers reported significantly lower levels of depression, anxiety, and stress than avoidant copers and levels comparable to approach copers. The apparent benefits associated with the sparing utilization of coping strategies in response to environmental stressors have been documented within other person-centered investigations of coping profiles (Aldridge & Roesch, 2008; Gaudreau & Blondin, 2004). Further, these prior investigations offer potential explanations for the adaptive outcomes observed among those assigned to the disengaged coper profile. According to transactional frameworks, coping is a dynamic process involving appraisals of stressful encounters, personal resources that support effective coping (e.g., energy, problem-solving skills, social support etc.), and constraints that limit coping options (Lazarus & Folkman, 1984). Specifically, individuals initiate coping strategies within situations identified as a threat to the ego or goal attainment (Folkman & Moskowitz, 2004). Further, the strategy selected is dependent on the characteristics of the threatening situation and determinations of what strategies can realistically be implemented given the individuals’ current resources and constraints (Lazarus & Folkman, 1984). Thus, as suggested by Gaudreau and Blondin (2004), it is possible that our disengaged copers have a general tendency to appraise situations as non-threatening to the self, which translates into reduced coping efforts and acts as a buffer to stress, anxiety, and depression.

Beyond expanding our understanding of the nature and outcomes of prototypical coping responses, we believe the results of the current investigation have important implications for interventions designed to support university students as they work to navigate stressors within and beyond traditional learning environments. To begin, our data indicate that a concerning number of participants (roughly 27% of respondents) belonged to a profile associated with elevated levels of anxiety, stress, and depression. If these findings can be generalized to the larger university population, they suggest that a concerning number of students are ill-equipped to cope with everyday stressors and are at an increased risk for negative mental health outcomes with the potential to undermine psychological well-being and academic success. Based on past work noting that emotion management can be enhanced through explicit instruction (Boyle et al., 2017), we believe it is critical to identify individuals who are similar to our avoidant profile and direct them to structured support programs focused on expanding coping potential. Emotional information processing frameworks highlight that effective coping requires individuals to have an understanding not only of how to implement approach-oriented/active coping responses but also a firm understanding of situations when various strategies should be implemented (Cassady & Boseck, 2008; Crick & Dodge, 1994; Thomas & Cassady, 2020). Therefore, we believe these support programs should utilize a combination of explicit instruction and structured practice to ensure students possess a robust social and emotional knowledge store to support their efforts to cope with stressors (both related and unrelated to education).

Limitations

We believe the current study possessed several limitations worthy of additional discussion. First, the primary constructs of interest were measured solely in an online environment using self-report instruments. Given that self-report measures rely on individuals’ subjective evaluation and are subject to bias, it is possible we did not collect accurate estimates of psychological stress, depression, anxiety, and coping preferences. Future research could overcome this limitation through the use of experiential sampling methods that allow researchers to gain a more nuanced view of individuals' responses to stressors (Prescott & Csikszentmihalyi, 1981). It is also important to acknowledge a potential limitation associated with the characteristics of our sample. Although the demographic characteristics of the sample were representative of the population from which it was drawn, it is not clear how well the results of the current investigation will generalize to other contexts with increased diversity in terms of student gender and ethnic heritage Lastly, the timing of data collection during the COVID-19 pandemic could also be a limitation. It is possible the unique intrapersonal, social, financial, and health-related concerns associated with the COVID-19 pandemic influenced the responses to the self-report measures. Thus, we encourage researchers to replicate our findings using data collected following the end of the COVID-19 pandemic.

Conclusion

Using latent profile analysis – a person-centered statistical method - we identified three prototypical coping subpopulations in a sample of American university students. Specifically, we identified subgroups characterized by the use of coping strategies directed at altering or eliminating sources of stress (i.e., approach copers), the use of strategies focused on avoiding or minimizing stressors (i.e., avoidant copers), and low overall utilization of coping strategies (i.e., disengaged/low copers). Further group comparisons revealed that avoidant copers reported higher levels of anxiety, stress, and depression. Thus, it is important for higher education institutions to identify students with characteristics similar to our “avoidant copers” profile and direct them to structured supports to enhance their coping potential.

Supplemental Material

Supplemental Material - Coping Profiles and Mental Health Outcomes in American University Students: A Latent Profile Analysis

Supplemental Material for Coping Profiles and Mental Health Outcomes in American University Students: A Latent Profile Analysis by Christopher L. Thomas, Meera Nair, and Jamey K. Ganske in Psychological Reports

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Funding

The author(s) received no financial support for the research,authorship,and/or publication of this article.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

ORCID iDs

Christopher L. Thomas

Meera Nair

Data Availability Statement

The data that support the findings of this study are available from the corresponding author,upon reasonable request.

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Christopher Thomas,Ph.D.,is an Associate Professor of Educational Psychology in the School of Education at the University of Texas at Tyler. With expertise in quantitative methodologies,academic anxieties,emotional intelligence,and cognitive dissonance theory,Dr. Thomas conducts research aimed at supporting student success and fostering optimal learning environments.

Meera R Nair,earned M.S. in Clinical Psychology from the University of Texas at Tyler. She is currently working as a clinician under the supervision of a licensed Clinical Psychologist at Elvive Psychological Services. Her primary area of interest includes anxiety and mood disorders. Through mentorship from experienced faculties,she has contributed to research on psychological distress,coping profiles,and psychological flexibility. She has also been involved in research associated to meta-analysis,further enhancing her expertise in synthesizing and evaluating scientific literature.

Jamey K. Ganske is a dedicated student in the Clinical Mental Health Counseling program at the University of Texas at Tyler. With a passion for supporting the emotional and mental well-being of young people,she aspires to work in a school-based setting,providing guidance and support to both students and teachers. Her commitment to fostering a positive and inclusive learning environment drives her studies and future career goals in counseling.

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