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Should Digital Interventions for HIV Self-Testing Be Regulated with World Health Organization Prequalification?

Should Digital Interventions for HIV Self-Testing Be Regulated with World Health Organization Prequalification?

By prequalifying digital interventions for HIVST, the WHOPQ could consolidate data collection and de-silo interoperability issues. Although digital health interventions, including those for HIVST, have shown the ability to improve health outcomes and patient experiences, they are not yet incorporated into traditional budgeting practices that often only consider medications, medical devices, and services [37].

Alex Emilio Fischer, Samanta Tresha Lalla-Edward, Vinodh Edward, Musaed Abrahams, Luke Shankland, John de Wit

JMIR Mhealth Uhealth 2025;13:e60276

Mobile Health Adoption in High-Risk Pregnancies Using Cluster Analysis of Biopsychosocial Outcomes: Observational Longitudinal Cohort Study

Mobile Health Adoption in High-Risk Pregnancies Using Cluster Analysis of Biopsychosocial Outcomes: Observational Longitudinal Cohort Study

This is an observational longitudinal cohort study approved by the Institutional Ethics Committee of the Hospital de Clínicas Complex (47084021.5.0000.0096). All participants provided written informed consent before enrollment in the study. Participants’ personal data were anonymized to preserve confidentiality and privacy. No financial or other compensation was offered for participation. MAUQ was chosen because it is a widely recognized tool in the literature for evaluating the usability of m Health apps.

Fernanda Schier de Fraga, Mayara Marenda Narita, Monique Schreiner, Flavio Belli, Jaqueline Leonel Celestino, Karolayne Braz Pereira, Gabriella Soecki, Vitória Bevervanso, Rogério de Fraga

JMIR Hum Factors 2025;12:e67680

Use of Wearable Sensors to Assess Fall Risk in Neurological Disorders: Systematic Review

Use of Wearable Sensors to Assess Fall Risk in Neurological Disorders: Systematic Review

Notably, Silva de Lima et al [42] detected fall events automatically using a wearable sensor, without monitoring ADLs or gait. We analyzed features extracted from wearable sensors related to the quantification of supervised or unsupervised motor tasks in patients with MS, PD, or stroke. Several of the studies (10/19, 53%) [35,36,39-41,45,47-49,52] extracted specific gait parameters from wearable sensors.

Mirjam Bonanno, Augusto Ielo, Paolo De Pasquale, Antonio Celesti, Alessandro Marco De Nunzio, Angelo Quartarone, Rocco Salvatore Calabrò

JMIR Mhealth Uhealth 2025;13:e67265

Promoting Comprehensive Care for People With Rare Diseases in a Tertiary Care Setting in Brazil: Protocol for a Mixed Methods Implementation Study

Promoting Comprehensive Care for People With Rare Diseases in a Tertiary Care Setting in Brazil: Protocol for a Mixed Methods Implementation Study

CIA: Information and Informatics Center; DAS: department of health care; HCRP: Clinics Hospital of Ribeirão Preto (Hospital das Clínicas de Ribeirão Preto); GGA: general outpatient management; PCC: primary care center; RD: rare disease; RG: research group; WG: working group.

Domingos Alves, Filipe Andrade Bernardi, Vinicius Costa Lima, Diego Bettiol Yamada, Tatiana Takahasi Komoto, Michele de Souza Seixas, Victor Cassão, Leticia Fontanelli Straube de Souza, Amaury Lelis Dal Fabbro, Têmis Maria Félix, Ricardo Cavalli, Victor Evangelista de Faria Ferraz

JMIR Res Protoc 2025;14:e68949

Optimizing and Testing an Individualized and Adaptive Physical Activity Digital Health Intervention: Protocol for a Control Optimization Trial Embedded Within a Randomized Controlled Trial

Optimizing and Testing an Individualized and Adaptive Physical Activity Digital Health Intervention: Protocol for a Control Optimization Trial Embedded Within a Randomized Controlled Trial

De-identified data were downloaded for analysis and stored on password-protected servers at the EPARC, with no personally identifiable information was linked to the device-captured data. EPARC servers were accessible only to study staff involved in the measurement of study participants and analysis of study data.

Meelim Kim, Shadia Mansour-Assi, Mohamed El Mistiri, Junghwan Park, Sarasij Banerjee, Owais Khan, Steven De La Torre, Michael Higgins, Job Godino, Kevin Patrick, Camille Nebeker, Sonia Jain, Predrag Klasnja, Daniel E Rivera, Eric Hekler

JMIR Res Protoc 2025;14:e70599