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Estimating the Population Size of People Who Inject Drugs in 3 Cities in Zambia: Capture-Recapture, Successive Sampling, and Bayesian Consensus Estimation Methods

Estimating the Population Size of People Who Inject Drugs in 3 Cities in Zambia: Capture-Recapture, Successive Sampling, and Bayesian Consensus Estimation Methods

Data analysis for counts, proportions, and PSEs was conducted using R (version 4.0.5; R Foundation for Statistical Computing). PSEs and credible intervals (CRIs) for 2-source capture-recapture (2 S-CRC) and 3 S-CRC were derived using a Bayesian nonparametric latent-class model in the shinyrecap package [18]. Size estimation was based on the number of participants overlapping (or recaptured) across capture events.

Lauren Parmley, Giles Reid, Joyce J Neal, Brave Hanunka, Leigh Tally, Lophina Chilukutu, Tepa Nkumbula, Chipili Mulemfwe, Lazarous Chelu, Ray Handema, John Mwale, Kennedy Mutale, Lloyd Mulenga, Anne F McIntyre, Neena M Philip, Hannah Chung, Maria Lahuerta

JMIR Public Health Surveill 2025;11:e66551

“Digital Clinicians” Performing Obesity Medication Self-Injection Education: Feasibility Randomized Controlled Trial

“Digital Clinicians” Performing Obesity Medication Self-Injection Education: Feasibility Randomized Controlled Trial

Data were analyzed using Jamovi version 2.4.14 developed by Love, Droppman, and Selker [36,37] and R Studio, developed by Posit PBC [37]. All Likert scale data were appropriately aggregated in treatment and control arms and recalibrated to scales from 1 to 10 for self-efficacy, and 1-7 for trust, satisfaction, and usability. The Mann-Whitney U test was used to assess differences in primary and secondary outcome variables. This nonparametric test is robust to the distribution of the outcome data.

Sean Coleman, Caitríona Lynch, Hemendra Worlikar, Emily Kelly, Kate Loveys, Andrew J Simpkin, Jane C Walsh, Elizabeth Broadbent, Francis M Finucane, Derek O' Keeffe

JMIR Diabetes 2025;10:e63503

Mobile Health Technology for Personalized Tobacco Cessation Support Among Cancer Survivors and Caregivers in Laos (Project SurvLaos): Protocol for a Pilot Randomized Controlled Trial

Mobile Health Technology for Personalized Tobacco Cessation Support Among Cancer Survivors and Caregivers in Laos (Project SurvLaos): Protocol for a Pilot Randomized Controlled Trial

Two research team members will perform qualitative data coding with the aid of the R-QDA [38]. Discrepancies will be discussed to achieve intercoder agreement. Codes and quotations will be arranged into focused themes (ie, thematic content analysis) to develop the mixed methods data inventory [39]. Codes and themes will be based on the purpose of this component (ie, explaining the RCT preliminary efficacy outcome) and on theoretical constructs of the PBM.

Phayvanh Keopaseuth, Phonepadith Xangsayarath, Shweta Kulkarni, Khatthanaphone Phandouangsy, Chanthavy Soulaphy, Phetsamone Alounlungsy, Vangnakhone Dittaphong, Dalouny Xayavong, Champadeng Vongdala, Latsamy Siengsounthone, Michael Businelle, Summer G Frank-Pearce, Damon J Vidrine, Jennifer I Vidrine, Thanh Cong Bui

JMIR Res Protoc 2025;14:e66517

Top 10 Research Lessons Learned From a Digital Child-Rearing Program in Low- and Middle-Income Countries: Multicase Study

Top 10 Research Lessons Learned From a Digital Child-Rearing Program in Low- and Middle-Income Countries: Multicase Study

At each phase in this cycle, learnings inform what are referred to as “core elements” that underpin all aspects of the research and development (R&D) process, including the overarching program theory, contextual factors, stakeholder engagement, and intervention refinements.

Haley M LaMonica, Victoria Loblay, Adam Poulsen, Gabrielle Hindmarsh, Mafruha Alam, Mahalakshmi Ekambareshwar, Qaisar Khan, Yun J C Song, Jacob J Crouse, Chloe Wilson, Madelaine Sweeney-Nash, Olivia Iannelli, Aila Naderbagi, Iqthyer U Zahed, Adam Yoon, Mujahid Torwali, Jakelin Troy, Ian B Hickie

J Med Internet Res 2025;27:e65705