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Scaling a Brief Digital Well-Being Intervention (the Big Joy Project) and Sociodemographic Moderators: Single-Group Pre-Post Study

Darwin A Guevarra, Yoobin Park, Xuhai Xu, Jin Liou, Jolene Smith, Peggy Callahan, Emiliana Simon-Thomas, Elissa S Epel

J Med Internet Res 2025;27:e72053

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The Potential to Leverage Real-World Data for Pediatric Clinical Trials: A Proof-of-Concept Study

Jens Declerck, Joanne Lee, Anando Sen, Avril Palmeri, Rianne Oostenbrink, Viviana Giannuzzi, Simon Woodworth, Salma Malik, Fenna Mahler, Beate Aurich, Rebecca Leary, Dipak Kalra, Volker Straub

J Med Internet Res 2025;27:e72573

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Attitudes Toward AI Usage in Patient Health Care: Evidence From a Population Survey Vignette Experiment

In this regard, many studies refer to 2 key frameworks of technology acceptance and usage underlying attitudes toward technology (including, in principle, AI): the Technology Acceptance Model (TAM, Davis [32]), highlighting perceived usefulness and perceived ease of use, and the Unified Theory of Acceptance and Use of Technology (UTAUT, Venkatesh et al [33]), including four key factors: performance expectancy, effort expectancy, social influence, and facilitating conditions.

Simon Kühne, Jannes Jacobsen, Nicolas Legewie, Jörg Dollmann

J Med Internet Res 2025;27:e70179

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Ambivalent User Needs as a Challenge and Chance for the Design of a Web-Based Intervention for Gaming Disorder: Qualitative Interview Study With Adolescents and Young Adults

This has not been thoroughly reflected in previous research on WBI development as the WBI being too attractive is a specific problem for people with GD or other IUDs, and there is still a lack of research literature reflecting on the development of a self-guided WBI for GD, especially with regard to design.

Birte Linny Geisler, Kay Uwe Petersen, Sara Hanke, Simon Schurer, Anne Schreiber, Christine Lämmle, Anil Batra, Tobias Renner, Isabel Brandhorst

JMIR Form Res 2025;9:e63258

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Preferences and Willingness to Pay for Health App Assessments Among Health Care Stakeholders: Discrete Choice Experiment

With regard to digital health–related decisions, 18% (7/40) of the health app developers reported being the sole or final decision maker, 45% (18/40) indicated being part of a group of decision makers, and 35% (14/40) stated that they provided advice to inform decisions, while 2% (1/40) indicated having no influence on decision-making. The majority of health app developers (32/41, 78%) had prior experience with health app assessment, which was indicated to include regulatory certification.

Anna-Lena Frey, Simon Leigh, Carla Toro, Carme Pratdepàdua Bufill, Charles McCay, Tatjana Prenđa Trupec, Giuseppe D'Avenio, Menno Kok, Antanas Montvila, Philipp Goedecker, Petra Hoogendoorn