Objective: The high degree of heterogeneity in the development of depression under stress is unaccounted for in traditional statistical modeling. We employ growth mixture modeling to identify classes of individuals at highest risk of depression under stress.
Method: Medical internship was used as a prospective stress model. Interns from US residency programs completed demographic, psychological, and depressive symptom assessments 2 months prior to internship and at 3-month intervals throughout internship year.
Results: A total of 2278 (59%) of interns chose to take part in the study. Three classes of depressive symptoms were identified: i) Stress-resilient class: 62% of participants report low depressive symptoms before and throughout internship year; ii) Stress-neutral class: 22% of participants report mild depressive symptoms before and throughout internship year; and iii) Stress-sensitive class: 16% of participants report low depressive symptoms before internship stress, and high levels of depressive symptoms throughout internship year. Individuals in the Stress-sensitive class were more likely to be female, in a surgical specialty, and have a history of depression, difficulty early family environment and high-neuroticism scores compared with individuals in the Stress-resilient class.
Conclusion: Trajectory-based analysis allows for the identification of a high-risk group, within a heterogeneous population, that accounts for the link between stress and depression.
Keywords: affective disorders; biostatistics; stress.
© 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.