AI-driven analyzes of open-ended responses to assess outcomes of internet-based cognitive behavioral therapy (ICBT) in adolescents with anxiety and depression comorbidity.

Journal: Journal of affective disorders
Published Date: Apr 3, 2025

Abstract

OBJECTIVE: Although patients prefer describing their problems using words, mental health interventions are commonly evaluated using rating scales. Fortunately, recent advances in natural language processing (i.e., AI-methods) yield new opportunities to quantify people's own mental health descriptions. Our aim was to explore whether responses to open-ended questions, quantified using AI, provide additional value in measuring intervention outcomes compared to traditional rating scales.

Authors

  • Danilo Garcia
    Department of Behavioural Sciences and Learning, Linköping University, Sweden.
  • Alexandre Granjard
    Promotion of Health and Innovation for Well-Being (PHI-WELL), Department of Social Studies, University of Stavanger, Stavanger, Norway; Lab for Biopsychosocial Personality Research (BPS-PR), International Network for Well-Being; Promotion of Health and Innovation (PHI) Lab, International Network for Well-Being; Department of Psychology, University of Gothenburg, Gothenburg, Sweden.
  • Loïs Vanhée
    Department of Computing Sciences, Umeå University, Sweden.
  • Matilda Berg
    Department of Behavioral Sciences and Learning, Linköping University, Linköping, Sweden.
  • Gerhard Andersson
    Department of Behavioural Sciences and Learning, Linköping University, Sweden.
  • Marta Lasota
    SWPS University, Poland.
  • Sverker Sikström
    Department of Psychology, Lund University, Lund, Sweden. Sverker.sikstrom@psy.lu.se.

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