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Greater Improvements in Vaccination Outcomes Among Black Young Adults With Vaccine-Resistant Attitudes in the United States South Following a Digital Health Intervention: Latent Profile Analysis of a Randomized Control Trial

Greater Improvements in Vaccination Outcomes Among Black Young Adults With Vaccine-Resistant Attitudes in the United States South Following a Digital Health Intervention: Latent Profile Analysis of a Randomized Control Trial

A total of 360 Black young adults were included in this study, of whom 76% (n=272) identified as cisgender or transgender women. The median age was 24 (IQR 21‐27) years, and approximately one-third of participants (n=122) had a bachelor’s degree or higher. Overall vaccine uptake at month 3 was low (n=21) and did not significantly differ between the intervention and control arms (odds ratio [OR] 1.88, 95% CI 0.76 to 4.69).

Noah Mancuso, Jenna Michaels, Erica N Browne, Allysha C Maragh-Bass, Jacob B Stocks, Zachary R Soberano, C Lily Bond, Ibrahim Yigit, Maria Leonora G Comello, Margo Adams Larsen, Kathryn E Muessig, Audrey Pettifor, Lisa B Hightow-Weidman, Henna Budhwani, Marie C D Stoner

JMIR Public Health Surveill 2025;11:e67370

Mental Health Apps Available in App Stores for Indian Users: Protocol for a Systematic Review

Mental Health Apps Available in App Stores for Indian Users: Protocol for a Systematic Review

Features of interactive self-care apps (N=33) were reviewed further, and this exercise showed that less than 10% of the apps incorporated explicit delineation of their scope or initial screening for suitability. Slightly more than one-third of these apps included content aimed at encouraging professional help-seeking when needed or an explicit mention of their theoretical or empirical basis. Challenges for potential users were highlighted [20].

Seema Mehrotra, Ravikesh Tripathi, Pramita Sengupta, Abhishek Karishiddimath, Angelina Francis, Pratiksha Sharma, Paulomi Sudhir, Srikanth TK, Girish N Rao, Rajesh Sagar

JMIR Res Protoc 2025;14:e71071

Testing a Machine Learning–Based Adaptive Motivational System for Socioeconomically Disadvantaged Smokers (Adapt2Quit): Protocol for a Randomized Controlled Trial

Testing a Machine Learning–Based Adaptive Motivational System for Socioeconomically Disadvantaged Smokers (Adapt2Quit): Protocol for a Randomized Controlled Trial

In a subanalysis among those who reported lower education (n=49), the average rating of the messages was higher on more days than the average ratings of true comparison messages (77% vs 23%; P The Adapt2 Quit intervention is based on the self-determination theory (SDT). SDT-based interventions support autonomous decisions and are designed to increase intrinsic motivation and self-regulation and they have been shown to improve motivation and cessation outcomes among those who smoke [19-24].

Ariana Kamberi, Benjamin Weitz, Julie Flahive, Julianna Eve, Reem Najjar, Tara Liaghat, Daniel Ford, Peter Lindenauer, Sharina Person, Thomas K Houston, Megan E Gauvey-Kern, Jackie Lobien, Rajani S Sadasivam

JMIR Res Protoc 2025;14:e63693

Evaluating the Acceptability of a Brief Web-Based Alcohol Misuse Prevention Program Among US Military Cadets: Mixed Methods Formative Evaluation

Evaluating the Acceptability of a Brief Web-Based Alcohol Misuse Prevention Program Among US Military Cadets: Mixed Methods Formative Evaluation

A slight majority (n=12, 54%) were male. The mean age was 19.64 (SD 1.86; range 18‐26) years, with 6 (27%) participants aged 21 years or older. Approximately, 40% (n=9) of participants identified as non-Hispanic White, approximately one-fifth (n=4, 18%) of participants identified as Hispanic or Latinx or multiracial, 14% (n=3) of participants identified as Black or African American, and 4% (n=1) of participants identified as Asian Pacific Islander or Asian.

Emily Schmied, Lauren Hurtado, W Ken Robinson, Cynthia M Simon-Arndt, Richard Moyer III, Leslie Wilson, Mark Reed, Shannon M Blakey, Marni Kan

JMIR Form Res 2025;9:e67637

Methadone Patient Access to Collaborative Treatment: Protocol for a Pilot and a Randomized Controlled Trial to Establish Feasibility of Adoption and Impact on Methadone Treatment Delivery and Patient Outcomes

Methadone Patient Access to Collaborative Treatment: Protocol for a Pilot and a Randomized Controlled Trial to Establish Feasibility of Adoption and Impact on Methadone Treatment Delivery and Patient Outcomes

We evaluate the number of clinics and number of patients, assuming that MPACT intervention reduces this frequency to 45% (n=240), 50% (n=300), and 55% (n=330). The power curves based on independent observations (no cluster effect) are shown in Figure 3. The graph shows that the recruitment of 30 clinics, with 20 patients per clinic, provides greater than 80% power to detect a difference in treatment interruption rates of 66% (control) and 55% (MPACT) with α=.05.

Beth E Meyerson, Alissa Davis, Richard A Crosby, Linnea B Linde-Krieger, Benjamin R Brady, Gregory A Carter, Arlene N Mahoney, David Frank, Janet Rothers, Zhanette Coffee, Elana Deuble, Jonathon Ebert, Mary F Jablonsky, Marlena Juarez, Barbara Lee, Heather M Lorenz, Michael D Pava, Kristen Tinsely, Sana Yousaf

JMIR Res Protoc 2025;14:e69829

Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study

Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study

Consequently, the final 2 patients initially reserved for this purpose were included in the final cohort evaluation (n=92 patients, 626 medications). Aside from the consistency-based method described later, all LLM calls were performed with a fixed temperature (temperature=0; low randomness in generated responses) and seed to ensure reproducibility and deterministic outputs.

Vimig Socrates, Donald S Wright, Thomas Huang, Soraya Fereydooni, Christine Dien, Ling Chi, Jesse Albano, Brian Patterson, Naga Sasidhar Kanaparthy, Catherine X Wright, Andrew Loza, David Chartash, Mark Iscoe, Richard Andrew Taylor

JMIR Aging 2025;8:e69504

Maternal Metabolic Health and Mother and Baby Health Outcomes (MAMBO): Protocol of a Prospective Observational Study

Maternal Metabolic Health and Mother and Baby Health Outcomes (MAMBO): Protocol of a Prospective Observational Study

Given the anticipated overlap of these conditions, ≈20% (n=90) of women will have at least one maternal metabolic disease of interest (secondary outcome). Study data are collected using paper case report forms. These paper documents will be kept in a locked cupboard accessible only to local research staff. Patient information is collected and stored by the investigators in a confidential REDCap (Research Electronic Data Capture system; Vanderbilt University), with password protection and restricted access.

Sarah A L Price, Digsu N Koye, Alice Lewin, Alison Nankervis, Stefan C Kane

JMIR Res Protoc 2025;14:e72542

Identification of Patients With Congestive Heart Failure From the Electronic Health Records of Two Hospitals: Retrospective Study

Identification of Patients With Congestive Heart Failure From the Electronic Health Records of Two Hospitals: Retrospective Study

Then, using the associated, CHF-related ICD codes as a rough approximation of ground-truth CHF status, for each n-gram, we conducted a Mann-Whitney U test to compare the median number of occurrences in the groups with and without CHF. Words that occurred with significantly different frequencies between groups were included in the keyword list. We further expanded the set of potentially classifying features by augmenting keywords and phrases with their negations.

Daniel Sumsion, Elijah Davis, Marta Fernandes, Ruoqi Wei, Rebecca Milde, Jet Malou Veltink, Wan-Yee Kong, Yiwen Xiong, Samvrit Rao, Tara Westover, Lydia Petersen, Niels Turley, Arjun Singh, Stephanie Buss, Shibani Mukerji, Sahar Zafar, Sudeshna Das, Valdery Moura Junior, Manohar Ghanta, Aditya Gupta, Jennifer Kim, Katie Stone, Emmanuel Mignot, Dennis Hwang, Lynn Marie Trotti, Gari D Clifford, Umakanth Katwa, Robert Thomas, M Brandon Westover, Haoqi Sun

JMIR Med Inform 2025;13:e64113

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

We reviewed 102 surgical pathology reports from 102 patients and excluded reports if they were from other organ sites (n=10), benign (n=2), cytopathology (n=5), or outside review (n=1). We included 84 reports for analysis. The study flowchart is shown in Figure 2. Flowchart of the study design and analysis. *The concordance rate was calculated as the total number of concordant answers/total number of answers for each of the 12 medical question answering (MQA).

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

JMIR Form Res 2025;9:e64544