Objectives Major depressive disorder (MDD) is a leading cause of disability worldwide, with peak incidence in young adulthood. Personality traits, coping styles, and cognitive functioning are established vulnerabilities, yet few studies have examined these dimensions together in young Asian adults. This study investigates whether personality, coping, and cognition function as layered vulnerabilities for MDD and whether their integration enhances diagnostic accuracy and identifies intervention targets, specifically in young Singaporean adults. Methods In an exploratory case–control study, 36 patients with MDD and 36 matched healthy controls aged 21–29 years completed validated measures of personality traits, coping strategies, and cognition. Analyses included group comparisons, correlational analyses, and hierarchical regression models with false discovery rate correction. Results Compared with controls, patients scored lower in emotional stability, conscientiousness, extraversion, and agreeableness; relied more on maladaptive coping; and reported more perceived cognitive deficits (all q 0.05). Emotional stability and subjective cognition were the strongest predictors of MDD status: adding emotional stability to the baseline demographic model markedly improved diagnostic accuracy ( AUC = 0.920, ΔAUC = 0.170, p 0.001), while subjective cognition (but not objective performance) provided a modest additional increase ( AUC = 0.954, p 0.001). In the patient subsample (N = 36), maladaptive coping also significantly predicted depression severity. Conclusions Personality, coping, and subjective cognition reflect layered vulnerabilities for MDD in young adults. Emotional stability emerged as the most impactful distal predictor, while perceived cognitive deficits provided a proximal, state-dependent marker, modestly enhancing diagnostic accuracy. Maladaptive coping related to symptom severity, highlighting its role as a potential intervention target. These findings illustrate how distal, semi-malleable, and proximal factors can inform early detection and targeted interventions.
Tay et al. (Tue,) studied this question.