Personally meaningful life events from adolescence to young adulthood: a longitudinal natural language processing analysis

BACKGROUND: Large-scale population-based studies of risk and protective factors for youth mental health rarely assess youths' first-hand experiences in their own words. This longitudinal study analyzed young people's self-reported most important life events and examined how the key topics changed from midadolescence to young adulthood and are associated with internalizing symptoms. METHODS: N = 1,442 participants from an urban, multiethnic cohort reported their most important life events at ages 15, 17, 20, and 24 in open-text segments. Themes in N = 5,670 descriptions were analyzed using topic modeling with the Python library BERTopic. RESULTS: Most reported events were positive in valence (83.1%), and were often 'normative', commonly occurring experiences spanning diverse life domains (education and career development, social relationships, leisure activities and successes, mental health and well-being, and other life transitions and independence). Event topics displayed systematic developmental shifts from midadolescence to adulthood. Higher internalizing symptoms were associated with a greater likelihood of reporting interpersonal and stressful events rather than positive or achievement-related ones. CONCLUSIONS: Longitudinal population-based research can draw on open-text data and employ NLP techniques to assess young people's lived experiences. The predominance of positive events and their associations with internalizing symptoms suggest that an increased focus on promoting beneficial experiences, next to reducing stressful events, may promote youth mental health.