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Advancing the Use of Longitudinal Electronic Health Records: Tutorial for Uncovering Real-World Evidence in Chronic Disease Outcomes

Advancing the Use of Longitudinal Electronic Health Records: Tutorial for Uncovering Real-World Evidence in Chronic Disease Outcomes

To improve robustness and reduce the risk of overfitting, we recommend aggregating the predictions from multiple models using a simple cross-fitted approach and refer to this process as “ensemble learning”. The process involves the following. Data splitting: Divide the labeled data in the training set into multiple folds. Cross-fitting: For each fold, train LATTE and other machine learning models with out-of-fold data and generate predicted disease outcomes for the in-fold patient periods.

Feiqing Huang, Jue Hou, Ningxuan Zhou, Kimberly Greco, Chenyu Lin, Sara Morini Sweet, Jun Wen, Lechen Shen, Nicolas Gonzalez, Sinian Zhang, Katherine P Liao, Tianrun Cai, Zongqi Xia, Florence T Bourgeois, Tianxi Cai

J Med Internet Res 2025;27:e71873

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Addressing the Stigma of Mental Illness in Black Families and Communities in Ontario, Canada: Protocol for a Mixed Methods Study

Addressing the Stigma of Mental Illness in Black Families and Communities in Ontario, Canada: Protocol for a Mixed Methods Study

We will engage a group of Black community members, service providers, cross-sector leaders, decision makers, and community advocates (n=30) in three concept mapping sessions to (1) share and discuss the results of phases 1 and 2; (2) engage every participant in brainstorming, sorting, and ranking essential elements of a best practices model to promote mental health equity in Black families and communities, use a computer program (Group Widsom, Concept Systems Incorporated) to collate and generate concept maps

Joseph Adu, Josephine P H Wong, Priscilla Boakye, Sebastian Gyamfi, Egbe B Etowa, Mark Fordjour Owusu

JMIR Res Protoc 2025;14:e66851

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SEARCH Study: Text Messages and Automated Phone Reminders for HPV Vaccination in Uganda: Randomized Controlled Trial

SEARCH Study: Text Messages and Automated Phone Reminders for HPV Vaccination in Uganda: Randomized Controlled Trial

There was no significant difference in requested mode based on HPV vaccine dose or language (desired text messages for initiation reminders (22/39, 56%), versus for completion reminders (26/39, 67%; P=.35), desired text messages for reminders in English (21/28, 75%) versus in Luganda (27/50, 54%; P=.07). Enrollment flow diagram. Characteristics of study participants. a HPV: human papillomavirus. b KCCA: Kampala Capital City Authority.

Sabrina B Kitaka, Joseph Rujumba, Sarah K Zalwango, Betsy Pfeffer, Lubega Kizza, Juliane P Nattimba, Ashley B Stephens, Nicolette Nabukeera-Barungi, Chelsea S Wynn, Juliet N Babirye, John Mukisa, Ezekiel Mupere, Melissa S Stockwell

JMIR Mhealth Uhealth 2025;13:e63527

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Improving Diet Quality of People Living With Obesity by Building Effective Dietetic Service Delivery Using Technology in a Primary Health Care Setting: Protocol for a Randomized Controlled Trial

Improving Diet Quality of People Living With Obesity by Building Effective Dietetic Service Delivery Using Technology in a Primary Health Care Setting: Protocol for a Randomized Controlled Trial

P values A sample size of 342 participants (n=171 per group) will have 90% power to detect a difference in change between arms of at least 5% of body weight at 12 months between groups, using a conservative estimate of SD, at 90% power and 5% level of significance. Assuming 20% (n=86) of participants are not followed up, this would necessitate 430 (215 in each group) participants to be recruited.

Deborah A Kerr, Clare E Collins, Andrea Begley, Barbara Mullan, Satvinder S Dhaliwal, Claire E Pulker, Fengqing Zhu, Marie Fialkowski, Richard L Prince, Richard Norman, Anthony P James, Paul Aveyard, Helen Mitchell, Jacquie Garton-Smith, Megan E Rollo, Chloe Maxwell-Smith, Amira Hassan, Hayley Breare, Lucy M Butcher, Christina M Pollard

JMIR Res Protoc 2025;14:e64735

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Consumer-Grade Neurofeedback With Mindfulness Meditation: Meta-Analysis

Consumer-Grade Neurofeedback With Mindfulness Meditation: Meta-Analysis

We conducted 2 different approaches, trim-and-fill, which corrects for publication bias in small samples, and 3-parameter selection models which explicitly model the proportion of studies below a p-threshold. We considered applying p-curve approaches, but they require at least 3 significant findings which was not the case for multiple models. A PRISMA flow diagram is shown in Figure 2 (PRISMA checklist provided in Multimedia Appendix 2).

Isaac Treves, Zia Bajwa, Keara D Greene, Paul A Bloom, Nayoung Kim, Emma Wool, Simon B Goldberg, Susan Whitfield-Gabrieli, Randy P Auerbach

J Med Internet Res 2025;27:e68204

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