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.
Authors
- Caroline Figueroa (ORCID: https://orcid.org/0000-0003-0692-2244)
- Tiffany Luo (ORCID: https://orcid.org/0000-0003-4461-8585)
- Vivian Yip (ORCID: https://orcid.org/0000-0002-3069-9882)
- Suchitra Sudarshan (ORCID: https://orcid.org/0009-0002-3926-417X)
- Marvyn R. Arévalo Avalos (ORCID: https://orcid.org/0000-0002-6667-4396)
- Chris Karr (ORCID: https://orcid.org/0000-0003-1828-4497)
- Karina Rosales
- Adrián Aguilera (ORCID: https://orcid.org/0000-0003-1773-8768)
Institutions
- University of California, San Francisco (US)
- University of California, Berkeley (US)
- Delft University of Technology (NL)
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
Funders
- Health Resources and Services Administration