MoodText
Cognitive Behavioral Therapy (CBT) for depression is efficacious, but effectiveness is limited when implemented in low-income settings due to engagement difficulties including nonadherence with skill-building homework and early discontinuation of treatment. Automated messaging can be used in clinical settings to increase dosage of depression treatment and encourage sustained engagement with psychotherapy.
The aim of this study was to test whether a text messaging adjunct (mood monitoring text messages, treatment-related text messages, and a clinician dashboard to display patient data) increases engagement and improves clinical outcomes in a group CBT treatment for depression. Specifically, the investigators aim to assess whether the text messaging adjunct led to an increase in group therapy sessions attended, an increase in duration of therapy attended, and reductions in Patient Health Questionnaire-9 item (PHQ-9) symptoms compared with the control condition of standard group CBT in a sample of low-income Spanish speaking Latino patients.
Team
Principal Investigators
- Adrian Aguilera, Ph.D.
- Associate Professor
- University of California, Berkeley
- University of California, San Francisco, Psychiatry
- Associate Professor
Staff
- Patricia Avila Garcia, MPH
- Rosa Hernandez-Ramos, B.A.
- Karina Rosales, B.A.
Research Assistants
- Lizbeth Ortiz Pivaral, B.A.
