Understanding stability and change in depressive symptom trajectories across young adulthood through the lens of career development: A mixed-methods study

INTERNATIONAL JOURNAL OF BEHAVIORAL DEVELOPMENT(2023)

引用 0|浏览0
暂无评分
摘要
Research has documented both stable and nonstable trajectories of depressive symptoms across young adulthood, but has not explored the mechanisms that might explain change in level of depressive affect over time. To explore this question, the current study draws on data from an Israeli longitudinal study of 205 young adults who reported their depressed symptoms four times from ages 23 to 35 years. Employing a latent profile analysis (LPA), three distinct trajectories of depressive symptoms were identified: stable low, moderate and decreasing, and stable high. To understand how stability and change in the course of depressive symptoms across time aligns with career development, 60 participants (20 from each profile), who had completed in-depth career development history interviews at age 29, were randomly selected. Subjecting the interviews to qualitative analysis showed that participants belonging to the stable low depressive symptoms trajectory were more likely to be intrinsically motivated, having the capacity to learn from their experiences, which resulted in a more successful career pursuit. In contrast, participants who consistently exhibited a high level of depressive affect were more likely to lack motivation, tended to feel at a loss, and were less likely to know what they want to do with their lives. Participants who were identified as belonging to the moderate and decreasing trajectory were more likely to describe the lack of a clear view of their future career plans. However, due to encouragement from significant others, they eventually found their niche. Conceptually, findings underscore the importance of understanding career factors that could covary with stability or change in the level of depressive symptoms during young adulthood.
更多
查看译文
关键词
Depressive symptoms,trajectories,young adulthood,mixed-methods
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要