Beyond Star Ratings: Supporting Informed Choices in Digital Mental Health
Beyond Star Ratings: Supporting Informed Choices in Digital Mental Health
MD Romael Haque
Topic: Beyond Star Ratings: Supporting Informed Choices in Digital Mental Health
Mobile mental health applications offer increasingly accessible support for mental health and well-being, but choosing an appropriate app remains challenging. App-store descriptions and star ratings provide limited insight into whether an application will meet a person’s needs, protect their privacy, or offer a useful everyday experience. How can we make the evidence behind these choices more accessible, understandable, and actionable?
This talk explores that question through human-centered research on mental health app evaluation and selection. It introduces MindMatch, a web-based recommender that brings together large-scale user experiences and professionally informed app evaluations. MindMatch summarizes recurring experiences from user reviews into concise pros and cons, preserves access to the original reviews, and presents professional assessments as a distinct source of evidence. Search and filtering tools help people explore applications according to their own needs and priorities, while keeping the final decision in their hands.
Drawing on a mixed-methods evaluation involving experienced mental health app users and mental health experts, the talk examines how people interpret different sources of evidence, where their priorities converge or diverge, and what they need from app-selection tools. The presentation concludes with broader implications for designing transparent, interpretable, and user-controlled recommender systems in digital mental health.
Biography:
MD Romael Haque, Ph.D., is an Assistant Professor in the Department of Computer Science at Purdue University Fort Wayne. His research spans human-computer interaction, digital mental health, artificial intelligence, privacy, and social computing. He investigates how people experience and evaluate emerging technologies and develops human-centered systems that support informed decisions and address societal needs.
His work includes mental health app evaluation and recommendation, technology-mediated peer support for U.S. military veterans, and privacy in shared-device environments. He combines computational methods, including machine learning and natural-language processing, with interviews, participatory design, and mixed-methods evaluation. His research has appeared in prestigious human-computer interaction venues, including ACM CHI and ACM CSCW, as well as IEEE Big Data and JMIR mHealth and uHealth. He received a Best Paper Honorable Mention Award at ACM CHI. He earned his Ph.D. in Computer Science from Marquette University and his bachelor’s degree in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology.
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- 2101 East Coliseum Boulevard
- Fort Wayne, Indiana
- United States IN 46805
- Building: Engineering Building (ETCS)
- Room Number: ET 235
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Technical Seminor: Beyond Star Ratings: Supporting Informed Choices in Digital Mental Health
- Starts 15 October 2026 01:47 PM UTC
- Ends 22 October 2026 01:49 PM UTC
- No Admission Charge
Speakers
Beyond Star Ratings: Supporting Informed Choices in Digital Mental Health
Mobile mental health applications offer increasingly accessible support for mental health and well-being, but choosing an appropriate app remains challenging. App-store descriptions and star ratings provide limited insight into whether an application will meet a person’s needs, protect their privacy, or offer a useful everyday experience. How can we make the evidence behind these choices more accessible, understandable, and actionable?
This talk explores that question through human-centered research on mental health app evaluation and selection. It introduces MindMatch, a web-based recommender that brings together large-scale user experiences and professionally informed app evaluations. MindMatch summarizes recurring experiences from user reviews into concise pros and cons, preserves access to the original reviews, and presents professional assessments as a distinct source of evidence. Search and filtering tools help people explore applications according to their own needs and priorities, while keeping the final decision in their hands.
Drawing on a mixed-methods evaluation involving experienced mental health app users and mental health experts, the talk examines how people interpret different sources of evidence, where their priorities converge or diverge, and what they need from app-selection tools. The presentation concludes with broader implications for designing transparent, interpretable, and user-controlled recommender systems in digital mental health.
MD Romael Haque
Assistant Professor of Computer Science
Biography:
MD Romael Haque, Ph.D., is an Assistant Professor in the Department of Computer Science at Purdue University Fort Wayne. His research spans human-computer interaction, digital mental health, artificial intelligence, privacy, and social computing. He investigates how people experience and evaluate emerging technologies and develops human-centered systems that support informed decisions and address societal needs.
His work includes mental health app evaluation and recommendation, technology-mediated peer support for U.S. military veterans, and privacy in shared-device environments. He combines computational methods, including machine learning and natural-language processing, with interviews, participatory design, and mixed-methods evaluation. His research has appeared in prestigious human-computer interaction venues, including ACM CHI and ACM CSCW, as well as IEEE Big Data and JMIR mHealth and uHealth. He received a Best Paper Honorable Mention Award at ACM CHI. He earned his Ph.D. in Computer Science from Marquette University and his bachelor’s degree in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology.
Agenda
Thursday, Oct. 22 2026
Social Hour & Pizza: 6:00PM-6:30PM
Technical Talk: 6:30PM-7:30PM