Personalised & optimised therapy (POT) algorithm using five cognitive and behavioural skills for subthreshold depression.

Journal: NPJ digital medicine
Published Date: Aug 20, 2025

Abstract

Personalising psychotherapies for depression may enhance their efficacy. We conducted a randomised controlled trial of smartphone cognitive-behavioural therapy (CBT) among 4,469 adults in Japan (RESiLIENT trial, UMIN-CTR UMIN000047124). Participants received one of nine CBT skills or combinations, or a health information control (HI), over six weeks. All interventions were found efficacious. We developed prescriptive models using machine learning to forecast changes on the Patient Health Questionnaire-9 (PHQ-9) at week 26 and created a personalised and optimised therapy (POT) algorithm that recommended the most suitable CBT for each participant. In a simulated randomised comparison, the effect of POTs over HI was a difference by -1.41 (95%CI: -1.91 to -0.90) points on the PHQ-9 corresponding with a standardised mean difference of -0.37 (-0.49 to -0.23), which was 35% greater than that of the group-average best intervention. A new randomized trial to confirm the external validity and applicability of the algorithm is warranted.

Authors

  • Toshi A Furukawa
    Department of Health Promotion and Human Behavior, Kyoto University Graduate School of Medicine/School of Public Health, Kyoto University, Kyoto, Japan.
  • Hisashi Noma
    Department of Data Science, The Institute of Statistical Mathematics, Tokyo, Japan.
  • Aran Tajika
    Department of Health Promotion and Human Behavior, Kyoto University Graduate School of Medicine/School of Public Health, Kyoto, Japan.
  • Rie Toyomoto
    Department of Health Promotion and Human Behavior, Kyoto University Graduate School of Medicine/School of Public Health, Kyoto, Japan.
  • Masatsugu Sakata
    Department of Neurodevelopmental Disorders, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.
  • Yan Luo
    School of Public Health and Management, Research Center for Medicine and Social Development, Innovation Center for Social risk Governance in Health, Chongqing Medical University, Chongqing 400016, China.
  • Masaru Horikoshi
    Musashino University, Tokyo, Japan.
  • Tatsuo Akechi
    Department of Psychiatry and Cognitive-Behavioral Medicine, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.
  • Norito Kawakami
    Department of Digital Mental Health, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Takeo Nakayama
    Department of Health Informatics, Graduate School of Medicine/School of Public Health, Kyoto University.
  • Naoki Kondo
    Department of Social Epidemiology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Shingo Fukuma
    Human Health Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan.
  • James M S Wason
    Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK.
  • Ronald C Kessler
    Department of Health Care Policy, Harvard Medical School.
  • Wolfgang Lutz
    Department of Psychology, University of Trier, Trier, Germany.
  • Pim Cuijpers
    Department of Clinical, Neuro, and Developmental Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; WHO Collaborating Center for Research and Dissemination of Psychological Interventions, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Babeș-Bolyai University, International Institute for Psychotherapy, Cluj-Napoca, Romania.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals