Abstract

Cognitive vulnerabilities (CVs) are important constructs for developmental psychopathology, intervention research, and clinical nosology. However, the validity and utility of these constructs is called into question when evidence of psychometric properties is inadequate. To date, evidence of dependability, or correlations of scores on a trait measure across timepoints when true change is highly unlikely, is underdeveloped in the field of cognitive vulnerabilities. With a large sample of undergraduates, the present study evaluated the dependability of five commonly used CV measures, relative to personality, affect, and symptom measures, and then compared dependability estimates across one-week and one-month intervals. Inadequate dependability of all four trait CV measures (i.e., BFNE, ASI, RRS, DAS-A) was demonstrated, whereas the symptom-like CV measure (i.e., ATQ) had acceptable dependability. Further, equivalent dependability across the two intervals for the BFNE and RRS supports the conceptualization of fear of negative evaluations and rumination as trait constructs. The ASI and DAS-A failed to demonstrate equivalent levels of dependability across the two different time intervals, which challenges the assumption that anxiety sensitivity and dysfunctional attitudes are successfully assessed as traits. Meanwhile, the ATQ demonstrated a substantial decrease in test-retest correlations over time, consistent with its conceptualization as a symptom-state. Current findings indicate CV measures do not reliably capture respondents’ general levels of the target construct. Future investigations into sources of transient error will inform advancements to trait assessment of CVs and, in turn, improve the interpretability, validity, and replicability of research on CVs.

Degree Date

Spring 5-16-2025

Document Type

Thesis

Degree Name

M.A.

Department

Psychology

Advisor

Michael Chmielewski

Number of Pages

70

Format

.pdf

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

Available for download on Friday, May 10, 2030

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