Trade-offs in mental health support: Preferred patient-centered communication attributes across AI chatbots, telemedicine, online health communities, and in-person clinicians
Abstract
Mental health support now extends beyond in-person clinicians, search engines, and medical websites to interactive healthcare providers (IHPs), including AI chatbots, telemedicine (i.e., digital clinicians), and online health communities. Two preregistered U.S. studies examined how patient-centered communication (PCC) attributes shape preferences for mental health support. Study 1 (N = 414, U.S. quota sample, fielded August - September 2025) used Best-Worst Scaling (BWS) to rank eight attributes in each of three domains (informational, interpersonal, and community-based), selecting the top two per domain for Study 2. Study 2 (N = 1,011, U.S. representative sample, fielded September 2025) used a Discrete Choice Experiment (DCE) testing these six attributes in trade-off decisions. Study 2 revealed provider-specific preferences. Extendedsupportbeyond the consultation and multi-symptom assessment capabilities were most salient for in-person clinicians. Multi-symptom assessment capabilities and reflective attentiveness and listening skills stood out for IHPs. We also tested for the moderating effects of faith-based thriving as it gains relevance in patient-centered mental health communication. Moderation analyses indicated a provider-specific pattern: higher faith-based thriving was associated with a stronger preference for scope and help provided when using AI chatbots and a stronger preference for community-based assistance when talking to a digital clinician. Taken together, these findings suggest a complementary care model: those designing and delivering mental health support through IHPs should prioritize robust multi-symptom assessment and reflective listening, while in-person clinicians should prioritize support beyond the consultation. Faith-based thriving findings further highlight the need for group-sensitive mental health communication.
Fields of Study & Subjects
Digital Mental Health Interventions
Artificial Intelligence in Healthcare and Education
AI in Service Interactions
Publication details
- Journal / source
- Social Science & Medicine
- Publisher
- Elsevier BV
- Volume
- 403
- Pages
- 119431–119431
- Publication date
- 22 May 2026
- Language
- EN