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

Lookup NU author(s): Professor James WasonORCiD

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).

Abstract

© The Author(s) 2025.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.

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Author(s): Furukawa TA, Noma H, Tajika A, Toyomoto R, Sakata M, Luo Y, Horikoshi M, Akechi T, Kawakami N, Nakayama T, Kondo N, Fukuma S, Wason JMS, Kessler RC, Lutz W, Cuijpers P

Publication type: Article

Publication status: Published

Journal: npj Digital Medicine

Year: 2025

Volume: 8

Issue: 1

Online publication date: 20/08/2025

Acceptance date: 23/07/2025

Date deposited: 02/09/2025

ISSN (electronic): 2398-6352

Publisher: Nature Research

URL: https://doi.org/10.1038/s41746-025-01906-6

DOI: 10.1038/s41746-025-01906-6

Data Access Statement: De-identified individual participant data and data dictionary will be made available 24 months after publication on UMIN-ICDR, an individual case data repository managed by the Japanese University hospital Medical Information Network (UMIN) Centre (https://www.umin.ac.jp/icdr/index. html). Proposals with specific aims and an analysis plan should be directed to the corresponding author. R code files used in the statistical analyses are available on GitHub at https:// github.com/nomahi/RESiLIENT_POT.

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