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Updated: Feb 22, 2026

A New Method for Inducing a Depression-Like Behavior in Rats
Published on: February 22, 2018
Big Five aspects of personality interact to predict depression
Timothy A Allen1, Bridget E Carey2, Carolina McBride3
1Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health.
Three personality traits—withdrawal, industriousness, and enthusiasm—interact to predict depressive symptoms in both healthy and major depressive disorder populations. A "best two out of three" principle suggests protective effects, while a "worst two out of three" principle indicates equivalent severity.
Area of Science:
- Psychology
- Psychopathology
- Personality Science
Background:
- Three major personality traits (Neuroticism, Extraversion, Conscientiousness) interact to predict depressive symptoms in healthy individuals.
- This study investigates if this interaction is driven by lower-order traits: withdrawal, industriousness, and enthusiasm.
Purpose of the Study:
- To test the hypothesis that withdrawal, industriousness, and enthusiasm interact to predict depressive symptoms.
- To replicate this interaction in a clinical population with major depressive disorder for the first time.
Main Methods:
- Sample 1: 376 healthy adults assessed with Big Five Aspect Scales and Personality Inventory for DSM-5.
- Sample 2: 354 patients with major depressive disorder assessed with NEO-PI-R and Beck Depression Inventory-II.
Main Results:
- Withdrawal, industriousness, and enthusiasm interacted to predict depressive tendencies in both healthy and clinical samples.
- Findings supported a "best two out of three" principle: low scores on two traits protected against a high score on the third.
- Evidence also supported a "worst two out of three" principle: high scores on two traits predicted depressive severity comparable to high scores on all three.
Conclusions:
- The interactive effects of personality traits are crucial for understanding psychopathology.
- These lower-order traits provide a nuanced understanding of depression risk and severity.
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