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Digital Health Intervention on Awareness of Vaccination Against Influenza Among Adults With Diabetes: Pragmatic Randomized Follow-Up Study

Digital Health Intervention on Awareness of Vaccination Against Influenza Among Adults With Diabetes: Pragmatic Randomized Follow-Up Study

To achieve effective behavior change, the theoretical model COM-B (Capability, Opportunity, Motivation, and Behavior) proposes 3 factors that interact to influence behavior [19]. The use of the COM-B model in this context is particularly effective for addressing the limited awareness of the risks associated with not getting vaccinated and for guiding strategies aimed at behavior change.

Yifat Fundoiano-Hershcovitz, Felix Lee, Catherine Stanger, Inbar Breuer Asher, David L Horwitz, Omar Manejwala, Jan Liska, David Kerr

J Med Internet Res 2025;27:e68936

Development of a Mobile Intervention for Procrastination Augmented With a Semigenerative Chatbot for University Students: Pilot Randomized Controlled Trial

Development of a Mobile Intervention for Procrastination Augmented With a Semigenerative Chatbot for University Students: Pilot Randomized Controlled Trial

Screenshots of the time management app we used for the treatment group: (A) main screen with to-do list; (B) calendar screen visualizing success rate; (C) chatting room screen for conversation with the chatbot Moa. The content that was originally in Korean has been translated into English. Moa is a semigenerative chatbot interlocked with the to-do app to facilitate conversations tailored according to the users’ delaying behavior.

Seonmi Lee, Jaehyun Jeong, Myungsung Kim, Sangil Lee, Sung-Phil Kim, Dooyoung Jung

JMIR Mhealth Uhealth 2025;13:e53133

Using Large Language Models to Automate Data Extraction From Surgical Pathology Reports: Retrospective Cohort Study

Using Large Language Models to Automate Data Extraction From Surgical Pathology Reports: Retrospective Cohort Study

(B) Enterprise large language model (LLM, such as Chat GPT): Due to regulatory constraints, only publicly available data may be shared with enterprise LLMs. Prompt entry and question curation are used to gain oncologic insights. (C) Private LLMs: EHR data can be shared with a local hospital LLM, and prompt entry with question curation can be used to gain oncologic insights. EHR: electronic health record.

Denise Lee, Akhil Vaid, Kartikeya M Menon, Robert Freeman, David S Matteson, Michael L Marin, Girish N Nadkarni

JMIR Form Res 2025;9:e64544

Evaluation of Large Language Models in Tailoring Educational Content for Cancer Survivors and Their Caregivers: Quality Analysis

Evaluation of Large Language Models in Tailoring Educational Content for Cancer Survivors and Their Caregivers: Quality Analysis

Performance of all models and prompts on the summarization task. a GPT: Generative Pretrained Transformer. b The performance (%) of GPT-3.5 Turbo was 93.3% (28/30), GPT-4 was 96.7% (29/30), and GPT-4 Turbo was 100% (30/30) for the Spanish translation. The overall performance (%) of the three GPT models in Spanish translation was 96.7% (87/90). c The performance (%) of GPT-3.5 Turbo was 76.7% (23/30), GPT-4 was 86.7% (26/30), and GPT-4 Turbo was 80% (24/30) for the Chinese translation.

Darren Liu, Xiao Hu, Canhua Xiao, Jinbing Bai, Zahra A Barandouzi, Stephanie Lee, Caitlin Webster, La-Urshalar Brock, Lindsay Lee, Delgersuren Bold, Yufen Lin

JMIR Cancer 2025;11:e67914