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Journal of Psychopathology and Behavioral Assessment

01-10-2024

Risk Profiles Among College Students: Associations with Pathological Personality Traits and Mental Health Issues

Auteurs: Nicole L. Hayes, Monica A. Marsee, Daniel W. Russell

Gepubliceerd in: Journal of Psychopathology and Behavioral Assessment

Abstract

Research has shown that although aggression and victimization often co-occur, individuals may differ in terms of their involvement with aggression, experiences of victimization as well as their social-psychological adjustment. Two studies investigated whether there are distinct groups of college students who experience different subtypes of aggression (e.g., reactive & proactive) and victimization. We also examined whether these groups differ from one another in their psychological profiles (e.g., maladaptive personality traits and emotion dysregulation), mental health, and substance use. Study 1 included 715 undergraduate students (53.6% female; 78.7% White; average age = 19.37 years, SD = 1.42) and Study 2 included 780 undergraduates (63.7% female; 75.3% White; average age = 19.42, years SD = 1.44). Hypotheses for Study 2 were pre-registered, and a multiverse approach was taken in both studies to demonstrate the robustness of the results. Across both studies, latent profile analysis identified three groups: low involvement, victim-only, and combined aggressor/victim. Characteristics of group members also differed across the three groups. Individuals in the combined aggressor/victim group exhibited the poorest psychosocial profile across both studies. In Study 1, the combined group reported significantly higher levels of Machiavellianism, narcissism, psychopathy, and callous-unemotional traits. In Study 2, the combined group reported significantly higher levels of psychopathy, callous-unemotional traits, and sadism. Mental health symptoms and substance use were similar for individuals who reported being victimized and for those who engaged in aggression in addition to being victimized. These findings enhance our understanding of the heterogeneity in aggression and victimization among college students and highlight the importance of developing interventions to reduce aggressive behaviors and target their specific mental health needs.

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Mixture models such as latent class analysis (LCA) and latent profile analysis (LPA) are superior methods of classification because they provide multiple model fit indices and greater precision when classifying individuals into groups.

These results were consistent across multiverse data sets; with the exception of the multivariate outlier and multivariate and univariate outlier data sets. In these two multiverse data sets a four group model was a significant better fit than a three-group model; although the entropy was lower. Moreover, retaining all cases, including outliers is recommended in mixture modeling, as these cases might represent the most at-risk groups. It is important to note that the class enumeration results were similar with the winsorized and outlier included data sets; demonstrating the robustness of the results.

Results were consistent across multiverse data sets.

This pattern of results for the post-hoc comparisons was consistent across the multiverse analysis for psychopathy, CU-traits, and Machiavellism which highlights the robustness of the results. The pattern of results was consistent across 60% of the multiverse models for narcissism and 80% for emotion dysregulation.

This pattern was consistent for 100% for psychopathy, CU traits, and emotion dysregulation, and 40% of Machiavellianism.

Based on the LMRT, multiverse models indicated that a three-group model fit for the winsorzied and multivariate excluded data sets, that both a three and four group fit for both the univariate and univariate and multivariate outliers excluded data sets. The LMRT was not significant for any groups in the outlier included data set. We noted that in the four group solutions, that there was two combined aggression/victim groups, and two victim-only groups; there was no low involvement group.

This overall pattern was consistent across the multiverse data sets except that the pairwise comparison between the victim-only and combined groups for social victimization was non-significant in the winsorized and outlier included data sets.

This pattern of results (p’s < .05) was consistent across the multiverse analysis for all outcome variables, with the exception of narcissism (significant in 40% of the multiverse models) which highlights the robustness of the results.

This pattern of results was consistent across 100% of the multiverse models for Machiavellianism and emotion regulation, 80% for psychopathy and sadism, and 40% for CU traits and narcissism.

This pattern was consistent across 100% of multiverse models for Machiavellianism, psychopathy, sadism, and 60% for emotion regulation.

This pattern of results (p’s < .05) was consistent across the multiverse analysis for depression, anxiety, and stress which highlights the robustness of the results. Alcohol use was significant in 80% and cannabis use non-significant in 100% of the multiverse models, respectively.

This pattern of results was consistent across 100% of the multiverse models for depression, stress, alcohol and cannabis use, and 80% for anxiety.

These results were consistent across multiverse models 100% for depression, anxiety, stress, and cannabis use. Alcohol was only consistent for 40% of the multiverse models.

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Titel: Risk Profiles Among College Students: Associations with Pathological Personality Traits and Mental Health Issues
Auteurs: Nicole L. Hayes
Monica A. Marsee
Daniel W. Russell
Publicatiedatum: 01-10-2024
Uitgeverij: Springer US
Gepubliceerd in: Journal of Psychopathology and Behavioral Assessment
Print ISSN: 0882-2689
Elektronisch ISSN: 1573-3505
DOI: https://doi.org/10.1007/s10862-024-10172-x

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