JMIR Publications

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  JMIR Publications jmirpub.bsky.social · 1h
  Artificial Intelligence for Clinical Competency Assessment: A Scoping Review of Methods and Applications (preprint) #openscience #PeerReviewMe #PlanP
  

  Artificial Intelligence for Clinical Competency Assessment: A Scoping Review of Methods and Applications

  Date Submitted: Feb 3, 2026. Open Peer Review Period: Feb 6, 2026 - Apr 3, 2026.

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  JMIR Publications jmirpub.bsky.social · 3h
  "Review of Mobile Applications for Women’s Physiology Tracking" (preprint) #openscience #PeerReviewMe #PlanP
  

  "Review of Mobile Applications for Women’s Physiology Tracking"

  Date Submitted: Feb 5, 2026. Open Peer Review Period: Feb 6, 2026 - Apr 3, 2026.

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  JMIR Publications jmirpub.bsky.social · 4h
  Reminder>> The Effect of Hydrotherapy on Work Related Stress Among Academics at a University of Technology in eThekwini, South Africa: A quantitative longitudinal #Protocol (preprint) #openscience #PeerReviewMe #PlanP

  The Effect of Hydrotherapy on Work Related Stress Among Academics at a University of Technology in eThekwini, South Africa: A quantitative longitudinal #Protocol

  Date Submitted: Jan 31, 2026. Open Peer Review Period: Feb 2, 2026 - Mar 30, 2026.

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  JMIR Publications jmirpub.bsky.social · 4h
  Reminder>> Nursing Students' Awareness, Perceptions, and Readiness for Artificial Intelligence Integration: An Extended UTAUT Analysis (preprint) #openscience #PeerReviewMe #PlanP

  Nursing Students' Awareness, Perceptions, and Readiness for Artificial Intelligence Integration: An Extended UTAUT Analysis

  Date Submitted: Jan 26, 2026. Open Peer Review Period: Feb 3, 2026 - Mar 31, 2026.

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  JMIR Publications jmirpub.bsky.social · 5h
  New JMIR Diabetes: Content Validation of an Electronic Health Record–Based #diabetes Self-Management Support Tool for Older Adults With Type 2 #diabetes: Qualitative Study
  

  Content Validation of an Electronic Health Record–Based #diabetes Self-Management Support Tool for Older Adults With Type 2 #diabetes: Qualitative Study

  Background: Older adults with #diabetes frequently access their electronic health record (EHR) notes but often report difficulty understanding medical jargon and nonspecific self-care instructions. To address this communication gap, we developed SEE-#diabetes (Support-Engage-Empower-#diabetes), a patient-centered, EHR-integrated #diabetes self-management support tool designed to embed tailored educational statements within the Assessment and Plan section of clinical notes. Objective: This study aimed to validate the clarity, relevance, and alignment of SEE-#diabetes content with the Association of #diabetes Care & Education Specialists 7 Self-Care Behaviors™ (ADCES7) framework from the perspectives of older adults and clinicians. Methods: An interdisciplinary team conducted expert reviews and qualitative interviews with 11 older adults with #diabetes and 8 clinicians practicing in primary care (family medicine) and specialty #diabetes care settings at a Midwestern academic health center. Patients evaluated the readability and relevance of the content, while clinicians assessed clarity, sufficiency, and potential clinical utility. Interview data were analyzed using inductive thematic analysis, and descriptive statistics summarized participant characteristics. Results: Patients (mean age 72 years; mean #diabetes duration 26 years) reported that the SEE-#diabetes statements were clear, relevant, and written in plain language that supported understanding of self-care recommendations. Clinicians (mean 13 years of #diabetes care experience) viewed the content as concise, clinically appropriate, and well aligned with patient self-management goals and the ADCES7 framework. Both groups identified the tool’s potential to enhance patient engagement and patient–clinician communication, while noting opportunities to improve the specificity of language, particularly within medication-related content. Conclusions: SEE-#diabetes demonstrated content validity as a practical, patient-centered digital health tool for supporting #diabetes self-management communication within EHR clinical notes. The findings support its use as a complementary approach to reinforce self-care communication in routine clinical practice and highlight areas for refinement to enhance personalization.

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  JMIR Publications jmirpub.bsky.social · 5h
  New in JMIR MedEdu: Digital Choice Architecture in medical education #mededu: Applying Behavioral Economics to Online Learning Environments
  

  Digital Choice Architecture in medical education #mededu: Applying Behavioral Economics to Online Learning Environments

  Healthcare has widely adopted behavioral economics to influence clinical practice, with documented success using defaults and social comparison feedback in electronic health records. Yet online medical education #mededu, now the dominant modality for continuing professional development, remains designed on assumptions of rational learning that behavioral science has disproven in clinical contexts. This viewpoint examines the paradox of applying sophisticated behavioral insights to clinical work while designing digital learning environments as if learners are immune to cognitive limitations. We propose digital choice architecture for medical education #mededu: intentional integration of behavioral design principles into learning management systems and online platforms. Drawing from clinical nudge units and implementation science, we demonstrate how defaults, social norms, and commitment devices can be systematically applied to digital continuing education. As medical education #mededu becomes increasingly technology-mediated, behavioral science provides theoretical foundation and practical tools for designing online learning environments that align with how clinicians actually make decisions.

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  JMIR Publications jmirpub.bsky.social · 5h
  Reminder>> Impact of the Virtual Character (Avatar) in a task-focused #Medical MR #Telecollaboration: post-hoc #Study of four randomized cross-over trials (preprint) #openscience #PeerReviewMe #PlanP
  

  Impact of the Virtual Character (Avatar) in a task-focused #Medical MR #Telecollaboration: post-hoc #Study of four randomized cross-over trials

  Date Submitted: Jan 28, 2026. Open Peer Review Period: Feb 3, 2026 - Mar 31, 2026.

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  JMIR Publications jmirpub.bsky.social · 6h
  Frequency, Clinical Outcomes, Anatomical Distribution, and Management Implications of Thromboembolic Complications Associated with Cardiac Myxomas: #Protocol for a Systematic Review (preprint) #openscience #PeerReviewMe #PlanP
  

  Frequency, Clinical Outcomes, Anatomical Distribution, and Management Implications of Thromboembolic Complications Associated with Cardiac Myxomas: #Protocol for a Systematic Review

  Date Submitted: Feb 5, 2026. Open Peer Review Period: Feb 6, 2026 - Apr 3, 2026.

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  JMIR Publications jmirpub.bsky.social · 6h
  New JMIR Diabetes: Predictors of Glycemic Response to Sulfonylurea Therapy in Type 2 #diabetes Over 12 Months: Comparative Analysis of Linear Regression and Machine Learning Models
  

  Predictors of Glycemic Response to Sulfonylurea Therapy in Type 2 #diabetes Over 12 Months: Comparative Analysis of Linear Regression and Machine Learning Models

  Background: Sulphonylureas are commonly prescribed for managing type 2 #diabetes, yet treatment responses vary significantly among individuals. Although advances in machine learning (ML) may enhance predictive capabilities compared to traditional statistical methods, their practical utility in real-world clinical environments remains uncertain. Objective: This study aimed to evaluate and compare the predictive performance of linear regression models with several ML approaches for predicting glycaemic response to sulphonylurea therapy using routine clinical data, and to assess model interpretability using SHapley Additive exPlanations (SHAP) analysis as a secondary analysis. Methods: A cohort of 7,557 individuals with type 2 #diabetes who initiated sulphonylurea therapy was analysed, with all patients followed for one year. Linear and logistic regression models were used as baseline comparisons. A range of ML models was trained to predict the continuous change in HbA1c levels and the achievement of HbA1c

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  JMIR Publications jmirpub.bsky.social · 6h
  Mixed Methods Studies Examining the Physical Activity Practices of African American Women: A Methodological Scoping Review #Protocol (preprint) #openscience #PeerReviewMe #PlanP

  Mixed Methods Studies Examining the Physical Activity Practices of African American Women: A Methodological Scoping Review #Protocol

  Date Submitted: Feb 6, 2026. Open Peer Review Period: Feb 6, 2026 - Apr 3, 2026.

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