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Effects of a Theory- and Evidence-Based, Motivational Interviewing–Oriented Artificial Intelligence Digital Assistant on Vaccine Attitudes: A Randomized Controlled Trial

Effects of a Theory- and Evidence-Based, Motivational Interviewing–Oriented Artificial Intelligence Digital Assistant on Vaccine Attitudes: A Randomized Controlled Trial

Attitude-targeted interventions by modifying attitudinal factors have been prioritized in vaccine promotion programs, with particular efforts on reducing hesitancy and facilitating individuals’ readiness for vaccination [8]. Vaccine hesitancy is significantly associated with reduced readiness for vaccination and is influenced by multifaceted factors [9].

Yan Li, Mengqi Li, Janelle Yorke, Daniel Bressington, Joyce Chung, Yao-Jie Xie, Lin Yang, Mengting He, Tsz-Ching Sun, Angela Y M Leung

J Med Internet Res 2025;27:e72637


Health Care Professionals’ Experiences and Opinions About Generative AI and Ambient Scribes in Clinical Documentation: Protocol for a Scoping Review

Health Care Professionals’ Experiences and Opinions About Generative AI and Ambient Scribes in Clinical Documentation: Protocol for a Scoping Review

records systems, computerized”[Mesh] OR “Electronic Health Records”[Mesh] OR “Health Records, Personal”[Mesh] OR “Patient Discharge”[Mesh] OR “Patient Discharge Summaries”[Mesh] OR documentation*[Title/Abstract] OR “medical record*”[Title/Abstract] OR “clinical note*”[Title/Abstract] OR “medical note*”[Title/Abstract] OR “clinical record*”[Title/Abstract] OR “patient discharge*”[Title/Abstract] OR “health record*”[Title/Abstract] OR “patient record*”[Title/Abstract] Experiences and opinions search string “Attitude

Carolina Garcia Sanchez, Anna Kharko, Maria Hägglund, Sara Riggare, Charlotte Blease

JMIR Res Protoc 2025;14:e73602


Electronic Clinical Decision Support System for Stroke Risk Screening in Patients With Atrial Fibrillation in Mental Health Care: Mixed Methods Study

Electronic Clinical Decision Support System for Stroke Risk Screening in Patients With Atrial Fibrillation in Mental Health Care: Mixed Methods Study

The main barriers were resistance or reluctance, alert fatigue, information overload, disruption of workflow, negative attitude, lack of motivation to use, lack of computer skills, and validity concerns [25]. This study has several strengths. First, it used both quantitative and qualitative data collection and analysis methods, which provided a comprehensive and holistic understanding of the topic of interest.

Dina Farran, Hou Wang Cheang, Juliana Onwumere, Mark Ashworth, Fiona Gaughran

JMIR Cardio 2025;9:e66428


Evolving Perceptions and Attitudes to Adopting Generative AI in Professional Settings: Multicenter Longitudinal Qualitative Study of Senior Chinese Hospital Leaders

Evolving Perceptions and Attitudes to Adopting Generative AI in Professional Settings: Multicenter Longitudinal Qualitative Study of Senior Chinese Hospital Leaders

All participants, regardless of their leadership roles, expressed a baseline supportive attitude toward Gen AI. Many described Gen AI as an innovative tool with transformative potential for streamlining processes and enhancing efficiency. They recognized the benefits of personal experimentation and adoption of the technology and believed that its integration could eventually lead to broader institutional improvements: Technologies such as this (Gen AI) are inevitable.

Zheng Zhi, Jing Zhao, Qiang Li, Qingxia Li, Meifang Xu, Yan Zuo, Ming Wang, Jiankang Liu, Jingyi Guan, Jia Wang

J Med Internet Res 2025;27:e75531


Understanding Dermatologists’ Acceptance of Digital Health Interventions: Cross-Sectional Survey and Cluster Analysis

Understanding Dermatologists’ Acceptance of Digital Health Interventions: Cross-Sectional Survey and Cluster Analysis

The Adopters (mean age 46.9, SD 11.7 y) were significantly younger compared to both the Indecisives (mean age 51.4, SD 7.9 y; P=.03) and Rejectors (mean age 58.8, SD 6.7 y; P The analysis of individual items revealed distinct profiles of the three clusters on their attitude toward DHIs. The following paragraphs describe selected items for each factor and cluster. A comprehensive overview of all item ratings is presented in Figure 1.

Patrick Reinders, Matthias Augustin, Marina Otten

JMIR Hum Factors 2025;12:e59757