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Examining the Efficacy of the Telehealth Assessment and Skill-Building Kit (TASK III) Intervention for Stroke Caregivers: Protocol for a Randomized Controlled Clinical Trial

Examining the Efficacy of the Telehealth Assessment and Skill-Building Kit (TASK III) Intervention for Stroke Caregivers: Protocol for a Randomized Controlled Clinical Trial

We will also explore racial differences (ie, Black or African American vs White individuals) by careful description of subgroup effects. We will make every effort to avoid missing data. If missing data are identified, the PI or the project manager will access the corresponding audio recording to determine whether missing data were due to an error in data entry.

Tamilyn Bakas, Elaine Miller, Heidi Sucharew, Natalie Kreitzer, Jahmeel Israel, Matthew Rota, Brett Harnett, Kari Dunning, Holly Jones, Michael McCarthy, Bonnie Brehm, Joan K Austin, Pamela H Mitchell

JMIR Res Protoc 2025;14:e67219

Analyzing Geospatial and Socioeconomic Disparities in Breast Cancer Screening Among Populations in the United States: Machine Learning Approach

Analyzing Geospatial and Socioeconomic Disparities in Breast Cancer Screening Among Populations in the United States: Machine Learning Approach

However, despite the relatively higher mammography screening rates in areas with a larger Black population, it is crucial to underscore that Black women are 40% more likely to die from breast cancer compared to White women [26].

Soheil Hashtarkhani, Yiwang Zhou, Fekede Asefa Kumsa, Shelley White-Means, David L Schwartz, Arash Shaban-Nejad

JMIR Cancer 2025;11:e59882

Gamified Web-Delivered Attentional Bias Modification Training for Adults With Chronic Pain: Randomized, Double-Blind, Placebo-Controlled Trial

Gamified Web-Delivered Attentional Bias Modification Training for Adults With Chronic Pain: Randomized, Double-Blind, Placebo-Controlled Trial

Word stimuli in each set were not replicated in any other set, and each word stimulus was presented in a black 28-point uppercase Courier New font on a white background. Word pairs used in the practice, training, and assessment trials. a S: sensory pain-related word. b A: affective pain-related word. Tasks were programmed and presented using Inquisit 6.4 (Millisecond Software) on participants’ internet-connected computers.

Julie F Vermeir, Melanie J White, Daniel Johnson, Geert Crombez, Dimitri M L Van Ryckeghem

JMIR Serious Games 2025;13:e50635

Concerns Over Vuse e-Cigarette Digital Marketing and Implications for Public Health Regulation: Content Analysis

Concerns Over Vuse e-Cigarette Digital Marketing and Implications for Public Health Regulation: Content Analysis

Most of the codes were binary (0 as not present and 1 as present), with a few exceptions for nonbinary options (for example, for perceived race or ethnicity of humans in the advertisement, 1=White, 2=non-White, 3=both White and non-White), or when free text entry was appropriate. We had two coders (EH and FV) for this study, with agreement on the codes by both coders.

Eileen Han, Lauren K Lempert, Francesca Vescia, Bonnie Halpern-Felsher

JMIR Form Res 2024;8:e54661

The CareVirtue Digital Journal for Family and Friend Caregivers of People Living With Alzheimer Disease and Related Dementias: Exploratory Topic Modeling and User Engagement Study

The CareVirtue Digital Journal for Family and Friend Caregivers of People Living With Alzheimer Disease and Related Dementias: Exploratory Topic Modeling and User Engagement Study

Further, this study was completed with a relatively small sample of predominantly White, female caregivers and may not be generalizable to all caregiving situations. Readers should exercise caution in drawing broad conclusions from this work. Future research may seek to examine Journal use among larger and more diverse samples. This study examined the use of a novel tool, the digital Care Virtue Journal, by caregivers of people living with AD/ADRD.

Andrew C Pickett, Danny Valdez, Lillian A White, Priya Loganathar, Anna Linden, Justin J Boutilier, Clover Caldwell, Christian Elliott, Matthew Zuraw, Nicole E Werner

JMIR Aging 2024;7:e67992

Current State of Community-Driven Radiological AI Deployment in Medical Imaging

Current State of Community-Driven Radiological AI Deployment in Medical Imaging

The IHE AI in imaging white paper [22], which references AI workflow for imaging [23] and AI results [24], describes the steps and boundaries that should be considered. Some examples of using AI in clinical workflows can be seen in Figure 1 [16], and their relation to AI workflow for imaging and AI results can be found in Table 1. The table also shows how these capabilities were achieved using MONAI Deploy tools.

Vikash Gupta, Barbaros Erdal, Carolina Ramirez, Ralf Floca, Bradley Genereaux, Sidney Bryson, Christopher Bridge, Jens Kleesiek, Felix Nensa, Rickmer Braren, Khaled Younis, Tobias Penzkofer, Andreas Michael Bucher, Ming Melvin Qin, Gigon Bae, Hyeonhoon Lee, M Jorge Cardoso, Sebastien Ourselin, Eric Kerfoot, Rahul Choudhury, Richard D White, Tessa Cook, David Bericat, Matthew Lungren, Risto Haukioja, Haris Shuaib

JMIR AI 2024;3:e55833