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Contribution title Major life events from adolescence to young adulthood: A longitudinal natural language processing analysis of a large urban cohort
Contribution code D1.136
Authors
  1. David Bürgin Jacobs Center for Productive Youth Development, Universität Zürich, Zürich, Schweiz Presenter
  2. Christina Haag Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
  3. Lynn Alison Büeler Jacobs Center for Productive Youth Development, University of Zurich, Zurich, Switzerland
  4. Laura Bechtiger University of Zurich (UZH)
  5. Clarissa Janousch Jacobs Center for Productive Youth Development, University of Zurich, Zurich, Switzerland
  6. Denis Ribeaud Jacobs Center for Productive Youth Development, University of Zurich, Zurich, Switzerland
  7. Manuel Eisner Jacobs Center for Productive Youth Development, University of Zurich, Zurich, Switzerland
  8. Viktor von Wyl Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
  9. Lilly Shanahan University of Zurich
Form of presentation Poster
Topic
  • T43 - Trauma
Abstract Background: Recent research shows an increase in mental health problems among young people oftentimes labelled 'youth mental health crisis'. Even though youth mental health is a growing area of concern, much of the research is based on predefined survey instruments. This limits the understanding of the subjective experiences and evolving priorities of youth.
Aims: Our study addresses this gap by integrating youths‘ first-hand accounts using innovative Natural Language Processing (NLP) techniques to uncover risk and protective factors. Specifically, we aim to investigate openly assessed major life-events in youths and describe how key life-event topics change from mid adolescence to early adulthood.
Methods: In the Zurich Project on Social Development from Childhood to Adulthood (z-proso), 1,442 participants answered a single-item open-ended question on their most significant life-event in the previous years at four measurement occasions between the ages 15 to 24. We analyzed themes in N=5,708 text narratives using topic modelling with the Python library 'BERTopic', combining conventional techniques with large language models (LLMs) and analyzed shifts in life-event topics over time.
Results and Conclusion: Results display a diverse range of youths’ life-events across multiple life domains (education & career development; social relationships, leisure activities & successes; mental health & well-being; and life-events related to other transitions & independence). Most life-events were of positive valence (83.2%). Major life-event topics showed distinct developmental shifts over time. Our work, thus, highlights salient life-event topics across different ages and illustrates how longitudinal population-based research can draw on text data through NLP techniques to assess lived experiences of youth.