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Rapid Development and Testing of Behavioral Text Message Reminders for Antidepressant Adherence via Online Panels:
Tia R Tropea1, Steven C Marcus2, Amy Bucher3
1Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, 3535 Market Street, 3rd Fl, Philadelphia, PA, 19104, United States, 1 (215) 898-0457.
Journal of Medical Internet Research
|July 23, 2026
Summary
Artificial intelligence (AI) can efficiently generate helpful SMS text message reminders for antidepressant adherence. Online panels rapidly evaluated these AI-generated messages, showing promise for digital health intervention development.
Area of Science:
- Digital Health
- Behavioral Science
- Artificial Intelligence
Background:
- SMS text message reminders are effective for promoting health behaviors, including medication adherence.
- Developing tailored messages for specific populations is resource-intensive.
- AI and online research panels can streamline message development and testing.
Purpose of the Study:
- Develop helpful SMS text message reminders for antidepressant adherence.
- Evaluate the efficacy of online panels for message testing.
- Identify key message characteristics preferred by patients.
Main Methods:
- Developed 83 SMS messages, half AI-generated and half human-authored.
- Recruited 181 adults with depression via an online panel.
- Participants rated message helpfulness; generalized linear models analyzed associations.
Main Results:
- Online panels enabled rapid recruitment and data collection.
- AI-generated messages were rated significantly more helpful than human-authored messages.
- Messages addressing delayed symptom benefit and using self-monitoring, habit formation, or natural consequences techniques were preferred.
Conclusions:
- Online panels provide a scalable method for evaluating SMS reminders for antidepressant adherence.
- AI can efficiently generate effective adherence-promoting message content.
- Combining online panels and AI accelerates digital health intervention design.