Longitudinal Associations Between Reward Responsiveness and Depression Across Adolescence

Abstract

Objective: Lower neural response to reward predicts subsequent depression during adolescence. Both pubertal development and biological sex have important effects on reward system development and depression during this period. However, relations among these variables across the transition from childhood to adolescence are not well characterized. Method: Depressive symptoms, pubertal status, and the reward positivity (RewP) event-related potential component, a neural indicator of reward responsivity, were assessed in 609 community-recruited youth at 9, 12, and 15 years of age. Structural equation modeling was used to examine concurrent and prospective relations within and between depression and reward responsiveness as well as the influence of pubertal status and biological sex on these variables across assessments. Results: Stability paths for depression, the RewP, and pubertal status were significant across assessments. Compared with male participants, female participants reported more advanced pubertal status at all assessments, a smaller RewP at age 9, and higher levels of depression at age 15. More advanced pubertal status was associatedwith a larger RewP at age 15. Most importantly, therewere bidirectional prospective effects between the RewPand depression fromages 12 to 15; a lower RewP at age 12 predicted increases in depression at age 15, whereas increased depression at age 12 predicted a lower RewP at age 15. Conclusion: These findings indicate that there are bidirectional prospective effects between reward responsiveness and depression that emerge between ages 12 and 15. This may be a crucial time for studying bidirectional reward responsiveness–depression associations across time.

Publication
In Journal of the American Academy of Child and Adolescent Psychiatry
Daniel M. Mackin, Ph.D.
Daniel M. Mackin, Ph.D.
Postdoctoral Fellow in Biomedical Data Science

Psychologist and data scientist interested in the intersection of technology and mental health. I apply traditional and advanced quantitative methods to understand the development and course of psychopathology.