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

Title: Personalised & optimised therapy (POT) algorithm using five cognitive and behavioural skills for subthreshold depression
Authors: 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
Source: npj Digital Medicine, December 2025
Publisher Information: Nature Research
Publication Year: 2025
Collection: Newcastle University Library ePrints Service
Description: © 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.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: unknown
Relation: https://eprints.ncl.ac.uk/307470; https://eprints.ncl.ac.uk/fulltext.aspx?url=307470/E306E42C-A37C-482C-BBDE-D25714F85700.pdf&pub_id=307470
Availability: https://eprints.ncl.ac.uk/307470
Rights: https://creativecommons.org/licenses/by-nc-nd/4.0/
Accession Number: edsbas.47B93B62
Database: BASE