Personalizing a mental health texting intervention using reinforcement learning

StayWell is a 60-day CBT/DBT-based text messaging intervention which leverages reinforcement learning algorithms to support mental health. Participants were randomly assigned to receiving personalized messaging (adaptive arm), static messaging (random arm) or mood-monitoring only messages (control arm). A diverse sample of 1121 adults participated in a fully remote trial between December 2021 and July 2022. Across study arms, participants showed a 25% reduction in depression symptoms (PHQ-8) and 24% reduction in anxiety symptoms (GAD-7) following the intervention. We did not find statistically significant differences in PHQ-8 and GAD-7 reductions between intervention arms. Participants in the control arm had higher mood-monitoring messages response rates than those in other conditions. Finally, post-hoc exploratory analysis assessing outcomes by condition indicated that patients with minimal to mild depression symptoms (PHQ-8 < 10) benefitted from the reinforcement learning algorithm. The results of this trial suggest that StayWell is a promising text-messaging intervention to achieve reductions in depression and anxiety among diverse populations.

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Publication Details

Journal
npj Mental Health Research
Published
2025-12-02
DOI
https://doi.org/10.1038/s44184-025-00173-3
Primary Topic
Digital Mental Health Interventions
Type
article
Field-Weighted Citation Impact
0.00

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article

Personalizing a mental health texting intervention using reinforcement learning

Caroline Figueroa, Tiffany Luo, Vivian Yip, Suchitra Sudarshan et al.
npj Mental Health Research
Digital Mental Health Interventions
article

Personalizing a mental health texting intervention using reinforcement learning

Caroline Figueroa, Tiffany Luo, Vivian Yip, Suchitra Sudarshan, Marvyn R. Arévalo Avalos, Chris Karr, Karina Rosales, Adrián Aguilera
article en

Abstract

StayWell is a 60-day CBT/DBT-based text messaging intervention which leverages reinforcement learning algorithms to support mental health. Participants were randomly assigned to receiving personalized messaging (adaptive arm), static messaging (random arm) or mood-monitoring only messages (control arm). A diverse sample of 1121 adults participated in a fully remote trial between December 2021 and July 2022. Across study arms, participants showed a 25% reduction in depression symptoms (PHQ-8) and 24% reduction in anxiety symptoms (GAD-7) following the intervention. We did not find statistically significant differences in PHQ-8 and GAD-7 reductions between intervention arms. Participants in the control arm had higher mood-monitoring messages response rates than those in other conditions. Finally, post-hoc exploratory analysis assessing outcomes by condition indicated that patients with minimal to mild depression symptoms (PHQ-8 < 10) benefitted from the reinforcement learning algorithm. The results of this trial suggest that StayWell is a promising text-messaging intervention to achieve reductions in depression and anxiety among diverse populations.

npj Mental Health ResearchVol. 4(1)
University of California, San Francisco (US), University of California, Berkeley (US), Delft University of Technology (NL)
Health Resources and Services Administration
Openalex Percentile: Top 58%
Digital Mental Health Interventions
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