Search Articles

View query in Help articles search

Search Results (1 to 10 of 2319 Results)

Download search results: CSV END BibTex RIS


Anticipated Acceptability of Blended Learning Among Lay Health Care Workers in Malawi: Qualitative Analysis Guided by the Technology Acceptance Model

Anticipated Acceptability of Blended Learning Among Lay Health Care Workers in Malawi: Qualitative Analysis Guided by the Technology Acceptance Model

. …. because I will be doing the things myself, I will be able to understand unlike having someone read to me or stand in front and say that this is this. [P 8021] You can repeat at your own time where you do not understand. [P 8007] ….the tablet cannot respond to questions that one may have as you do when you have a facilitator. [P 8003] …. with the face-to-face portion if you have other questions maybe of which you failed to ask the tablet, … then you will ask the facilitator and he will.

Tiwonge E Mbeya-Munkhondya, Caroline J Meek, Mtisunge Mphande, Tapiwa A Tembo, Mike J Chitani, Milenka Jean-Baptiste, Caroline Kumbuyo, Dhrutika Vansia, Katherine R Simon, Sarah E Rutstein, Victor Mwapasa, Vivian Go, Maria H Kim, Nora E Rosenberg

JMIR Form Res 2025;9:e62741

Development of a Predictive Dashboard With Prescriptive Decision Support for Falls Prevention in Residential Aged Care: User-Centered Design Approach

Development of a Predictive Dashboard With Prescriptive Decision Support for Falls Prevention in Residential Aged Care: User-Centered Design Approach

Power BI (PBI; Microsoft Corp) was selected on the grounds of digital data visualization, easy implementation at the user end, and stable R programming integration for advanced statistical analysis and plots. In this step, the initial prototype of the dashboard was created and shared with our partner organization and refined through collaborative efforts.

S Sandun Malpriya Silva, Nasir Wabe, Amy D Nguyen, Karla Seaman, Guogui Huang, Laura Dodds, Isabelle Meulenbroeks, Crisostomo Ibarra Mercado, Johanna I Westbrook

JMIR Aging 2025;8:e63609

Web-Based Human Papillomavirus Education and Professional Skills Intervention for Health Care Providers: Protocol for a Randomized Controlled Trial

Web-Based Human Papillomavirus Education and Professional Skills Intervention for Health Care Providers: Protocol for a Randomized Controlled Trial

Participants will be excluded from the study if they are not affiliated with the El Paso United States–Mexico border region, have not previously participated in phases I or II of the larger parent research project, do not identify as a current or emerging health care provider, decline or are unable to participate in the full intervention and follow-up time points, or are unable to complete participation and activities in the English language.

Jacob Martinez, Jacquelin I Cordero, Meagan Whitney, Katie L LaRoche, Gabriel Frietze, Eva M Moya, Kristin Gosselink

JMIR Res Protoc 2025;14:e60790

Improving Early Dementia Detection Among Diverse Older Adults With Cognitive Concerns With the 5-Cog Paradigm: Protocol for a Hybrid Effectiveness-Implementation Clinical Trial

Improving Early Dementia Detection Among Diverse Older Adults With Cognitive Concerns With the 5-Cog Paradigm: Protocol for a Hybrid Effectiveness-Implementation Clinical Trial

The PMIS (Pearson r=−0.76; P As we examined the sensitivity and specificity data to choose cut scores, we chose to favor sensitivity to minimize missing individuals with true disease in this sample of patients considered high risk because of their cognitive concerns. The cut scores for a positive result on the 5-Cog components were as follows: PMIS ≤6 (range 0-8), Symbol Match ≤25 (range 0-65), and s MCR >5 (range 0-7).

Rachel Beth Rosansky Chalmer, Emmeline Ayers, Erica F Weiss, Nicole R Fowler, Andrew Telzak, Diana Summanwar, Jessica Zwerling, Cuiling Wang, Huiping Xu, Richard J Holden, Kevin Fiori, Dustin D French, Celeste Nsubayi, Asif Ansari, Paul Dexter, Anna Higbie, Pratibha Yadav, James M Walker, Harrshavasan Congivaram, Dristi Adhikari, Mairim Melecio-Vazquez, Malaz Boustani, Joe Verghese

JMIR Res Protoc 2025;14:e60471

Perspectives of Adolescents and Young Adults With Inflammatory Bowel Disease on a Biopsychosocial Transition Intervention: Qualitative Interview Study

Perspectives of Adolescents and Young Adults With Inflammatory Bowel Disease on a Biopsychosocial Transition Intervention: Qualitative Interview Study

One participant shared: I look at [transition] as me having to know a lot about myself, especially where I am with my health. At the end of the day, my mother has to stop bringing me to the appointments, I can't bring her all the time, right? Because it’s that independent thing that comes in. So I think it’s just a learning experience about myself, learning about where I am with my health, knowing everything that I need to know for myself so I don't have to depend on anybody else to know it for me.

Brooke Allemang, Ashleigh Miatello, Mira Browne, Melanie Barwick, Pranshu Maini, Joshua Eszczuk, Chetan Pandit, Tandeep Sadhra, Laura Forhan, Natasha Bollegala, Nancy Fu, Kate Lee, Emily Dekker, Irina Nistor, Sara Ahola Kohut, Laurie Keefer, Anne Marie Griffiths, Thomas D Walters, Samantha Micsinszki, David R Mack, Sally Lawrence, Karen I Kroeker, Jacqueline de Guzman, Aalia Tausif, Claudia Tersigni, Samantha J Anthony, Eric I Benchimol

JMIR Pediatr Parent 2025;8:e64618

Digital Health Resilience and Well-Being Interventions for Military Members, Veterans, and Public Safety Personnel: Environmental Scan and Quality Review

Digital Health Resilience and Well-Being Interventions for Military Members, Veterans, and Public Safety Personnel: Environmental Scan and Quality Review

Subjective quality of each app was also assessed, and these items included “I would recommend using this app to the user” and “the number of stars that best represents your overall rating for the quality of this app is,” on a scale from 1 (strongly disagree; 1 star, worst app) to 5 (strongly agree; 5 stars, best app I have every used). After completing part A and B, the scores for each item were added up for a total score out of 30 for part A, and 60 for part B.

Rashell R Allen, Myrah A Malik, Carley Aquin, Lucijana Herceg, Suzette Brémault-Phillips, Phillip R Sevigny

JMIR Mhealth Uhealth 2025;13:e64098

Unsupervised Deep Learning of Electronic Health Records to Characterize Heterogeneity Across Alzheimer Disease and Related Dementias: Cross-Sectional Study

Unsupervised Deep Learning of Electronic Health Records to Characterize Heterogeneity Across Alzheimer Disease and Related Dementias: Cross-Sectional Study

The differential entropy for a row i is given by and the corresponding vector h ∈ Rn×1 corresponds to the entropy across every row. From the row-wise entropy, this vector is softmaxed to obtain the corresponding weights, w ∈ Rn×1, as follows: The resultant embedding for a note sequence, N ∈ R768×1, is then given by the matrix multiplication as follows: and the final patient-level representation is the simple average over all note fragments for a given patient, for their most recent encounter.

Matthew West, You Cheng, Yingnan He, Yu Leng, Colin Magdamo, Bradley T Hyman, John R Dickson, Alberto Serrano-Pozo, Deborah Blacker, Sudeshna Das

JMIR Aging 2025;8:e65178

Mobile App-Based Interactive Care Plan for Migraine: Survey Study of Usability and Improvement Opportunities

Mobile App-Based Interactive Care Plan for Migraine: Survey Study of Usability and Improvement Opportunities

A minority of respondents agreed or strongly agreed with statements that “the equipment helped in my care at home” (21/53, 40%), “helped me better understand my condition” (22/53, 41.5%), “understand how to care for myself” (19/53, 35.8%), “understand what I should be tracking throughout my care” (23/53, 43.4%), and “understand steps I can take to improve my health” (19/53, 35.8%).

Nathan P Young, Jennifer I Stern, Stephanie J Steel, Jon O Ebbert

JMIR Form Res 2025;9:e66763