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Survival Tree Analysis of Interactions Among Factors Associated With Colorectal Cancer Risk in Patients With Type 2 Diabetes: Retrospective Cohort Study

Survival Tree Analysis of Interactions Among Factors Associated With Colorectal Cancer Risk in Patients With Type 2 Diabetes: Retrospective Cohort Study

A previous meta-analysis on gene-environment interaction studies found insufficient evidence for the interaction effects between genetic and environmental factors [37]. However, a recent large-scale gene-environment interaction study [38] suggested that common genetic variants related to insulin signaling and immune function may potentially modify the association between diabetes and CRC risk. In addition, some medical conditions may share common pathophysiology with diabetes.

Sarah Tsz Yui Yau, Chi Tim Hung, Eman Yee Man Leung, Albert Lee, Eng Kiong Yeoh

JMIR Public Health Surveill 2025;11:e62756

Assessing Social Interaction and Loneliness and Their Association With Frailty Among Older Adults With Subjective Cognitive Decline or Mild Cognitive Impairment: Ecological Momentary Assessment Approach

Assessing Social Interaction and Loneliness and Their Association With Frailty Among Older Adults With Subjective Cognitive Decline or Mild Cognitive Impairment: Ecological Momentary Assessment Approach

Daily social interaction frequency and level of loneliness were the main independent variables. Daily social interaction frequency was measured to reflect quantifiable aspects of social contact, while the level of loneliness was assessed to capture one’s perceived view of the consequences of social contact [7]. While the level of loneliness is often measured with a single directional question about one’s loneliness status, a solid assessment method for social interaction has yet to be established [7].

Bada Kang, Dahye Hong, Seolah Yoon, Chaeeun Kang, Jennifer Ivy Kim

JMIR Mhealth Uhealth 2025;13:e64853

Designing a Multimodal and Culturally Relevant Alzheimer Disease and Related Dementia Generative Artificial Intelligence Tool for Black American Informal Caregivers: Cognitive Walk-Through Usability Study

Designing a Multimodal and Culturally Relevant Alzheimer Disease and Related Dementia Generative Artificial Intelligence Tool for Black American Informal Caregivers: Cognitive Walk-Through Usability Study

Lola incorporates a chatbot feature represented by a floating green bubble in the bottom right corner, accessible to users throughout their interaction with the app (Figure 1). Users can interact with the Lola chatbot by clicking the green call-to-action button, which initiates a conversation through text or voice input.

Cristina Bosco, Ege Otenen, John Osorio Torres, Vivian Nguyen, Darshil Chheda, Xinran Peng, Nenette M Jessup, Anna K Himes, Bianca Cureton, Yvonne Lu, Carl V Hill, Hugh C Hendrie, Priscilla A Barnes, Patrick C Shih

JMIR Aging 2025;8:e60566

Design and Implementation of a Dashboard for Drug Interactions Mediated by Cytochromes Using a Health Care Data Warehouse in a University Hospital Center: Development Study

Design and Implementation of a Dashboard for Drug Interactions Mediated by Cytochromes Using a Health Care Data Warehouse in a University Hospital Center: Development Study

To our knowledge, there is no drug interaction dashboard (DID) specifically linked to a health care data warehouse (HDW) for cytochrome-mediated DIs. In the literature, there are DIDs for pediatric interactions [11], primary care [12], patients infected with SARS-Co V-2 [13], tracking direct oral anticoagulants [14], and implementing DIs within a decision support tool in electronic health records [15].

Laura Gosselin, Alexandre Maes, Kevin Eyer, Badisse Dahamna, Flavien Disson, Stefan Darmoni, Julien Wils, Julien Grosjean

JMIR Med Inform 2024;12:e57705

Online Ambassador Visits for Hospitalized Children With Cancer: Qualitative Evaluation of Implementation

Online Ambassador Visits for Hospitalized Children With Cancer: Qualitative Evaluation of Implementation

Previous research from the RESPECT study has shown that social interaction by hospitalized children with cancer can promote a sense of connectedness with their classmates while, in turn, motivating the classmates to support them [17-19]. Recently, technologies, including video conferencing and telepresence robots, have become viable options for socialization and schooling [20,21].

Natasha Nybro Boensvang, Mette Weibel, Claire E Wakefield, Pernille Envold Bidstrup, Marianne Olsen, Karin Bækgaard Nissen, Vibeke Spager, Martin Kaj Fridh, Hanne Bækgaard Larsen

JMIR Pediatr Parent 2024;7:e53309

Characterizing the Adoption and Experiences of Users of Artificial Intelligence–Generated Health Information in the United States: Cross-Sectional Questionnaire Study

Characterizing the Adoption and Experiences of Users of Artificial Intelligence–Generated Health Information in the United States: Cross-Sectional Questionnaire Study

Users may appreciate certain aspects of Chat GPT, such as the conversational interaction, user interface, and quick reception of information, which may not be as easily executed on other OHI platforms. It may be the case that users who rated in this manner more heavily weighted the advantages of Chat GPT’s information delivery and accessibility over their perception of inaccuracy or information usefulness.

Oluwatobiloba Ayo-Ajibola, Ryan J Davis, Matthew E Lin, Jeffrey Riddell, Richard L Kravitz

J Med Internet Res 2024;26:e55138

The Impact of Expectation Management and Model Transparency on Radiologists’ Trust and Utilization of AI Recommendations for Lung Nodule Assessment on Computed Tomography: Simulated Use Study

The Impact of Expectation Management and Model Transparency on Radiologists’ Trust and Utilization of AI Recommendations for Lung Nodule Assessment on Computed Tomography: Simulated Use Study

Although most studies on AI for lung nodule assessment focus on the development and stand-alone performance of AI models [8,10,11], few studies have focused on user interaction with AI models in the clinical context beyond the theoretical level [12-16]. However, human-AI interaction is essential to enable radiologists to comprehend and effectively use AI recommendations in their tasks, ultimately achieving the highest levels of diagnostic quality and efficiency.

Lotte J S Ewals, Lynn J J Heesterbeek, Bin Yu, Kasper van der Wulp, Dimitrios Mavroeidis, Mathias Funk, Chris C P Snijders, Igor Jacobs, Joost Nederend, Jon R Pluyter, e/MTIC Oncology group

JMIR AI 2024;3:e52211