Developing personalized algorithms for sensing mental health symptoms in daily life.

Journal: Npj mental health research
Published Date: Aug 6, 2025

Abstract

The integration of artificial intelligence (AI) and pervasive computing offers new opportunities to sense mental health symptoms and deliver just-in-time adaptive interventions via mobile devices. This pilot study tested personalized versus generalized machine learning models for detecting individual and family mental health symptoms as a foundational step toward JITAI development, using data collected through the Colliga app on smart devices. Over a 60-day period, data from 35 families resulted in approximately 14 million data points across 52 data streams. Findings showed that personalized models consistently outperformed generalized models. Model performance varied significantly based on individual factors and symptom profiles, underscoring the need for tailored approaches. These preliminary findings suggest that successful implementation of passive sensing technologies for mental health will require accounting for users' unique characteristics. Further research with larger samples is needed to refine the models, address data heterogeneity, and develop scalable systems for personalized mental health interventions.

Authors

  • Adela C Timmons
    Department of Psychology, University of Texas at Austin Institute for Mental Health Research.
  • Abdullah Aman Tutul
    Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka 1205, Bangladesh.
  • Kleanthis Avramidis
    Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.
  • Jacqueline B Duong
    Department of Psychology, University of Texas at Austin Institute for Mental Health Research.
  • Kayla E Carta
    University of Texas at Austin, Austin, TX, USA.
  • Sierra N Walters
    University of Texas at Austin, Austin, TX, USA.
  • Grace A Jumonville
    University of Texas at Austin, Austin, TX, USA.
  • Alyssa S Carrasco
    University of Texas at Austin, Austin, TX, USA.
  • Gabrielle F Freitag
    Florida International University, Miami, FL, USA.
  • Daniela N Romero
    University of Texas at Austin, Austin, TX, USA.
  • Matthew W Ahle
    Colliga Apps Corporation, Austin, Texas.
  • Jonathan S Comer
    Department of Psychology, Florida International University.
  • Shrikanth S Narayanan
  • Ishita P Khurd
    University of Texas at Austin, Austin, TX, USA.
  • Theodora Chaspari
    University of Southern California, Ming Hsieh Department of Electrical Engineering , Los Angeles, CA , USA.

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