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Methodological Challenges in Randomized Controlled Trials of mHealth Interventions: Cross-Sectional Survey Study and Consensus-Based Recommendations

Methodological Challenges in Randomized Controlled Trials of mHealth Interventions: Cross-Sectional Survey Study and Consensus-Based Recommendations

Consensus methods allow for the integration of expert perspectives to produce recommendations. This approach is essential given the lack of consistent solutions to these challenges. The goal of the consensus exercise was to develop recommendations for researchers working in m Health. The intended audience is global, with participation from experts across regions, making the recommendations relevant for both high- and low-resource settings.

Jesus Lopez-Alcalde, L Susan Wieland, Yuqian Yan, Jürgen Barth, Mohammad Reza Khami, Siddharudha Shivalli, Cynthia Lokker, Harleen Kaur Rai, Paul Macharia, Sergi Yun, Elvira Lang, Agnes Bwanika Naggirinya, Concepción Campos-Asensio, Leila Ahmadian, Claudia M Witt

J Med Internet Res 2024;26:e53187

Artificial Intelligence–Augmented Clinical Decision Support Systems for Pregnancy Care: Systematic Review

Artificial Intelligence–Augmented Clinical Decision Support Systems for Pregnancy Care: Systematic Review

Specifically, in support of diagnostics and therapeutics recommendations for ectopic pregnancy, ontology has been used for supporting the annotation of medical images (eg, ultrasound images for obstetrics) [26,27]. Arden syntax was used to formalize obstetric clinical guidelines into a knowledge base that supports CDSS functions for obstetrics [29]. XML was used for encoding a knowledge base that underpins mobile app–based CDSS for prenatal care [34].

Xinnian Lin, Chen Liang, Jihong Liu, Tianchu Lyu, Nadia Ghumman, Berry Campbell

J Med Internet Res 2024;26:e54737

Digital Competencies and Training Approaches to Enhance the Capacity of Practitioners to Support the Digital Transformation of Public Health: Rapid Review of Current Recommendations

Digital Competencies and Training Approaches to Enhance the Capacity of Practitioners to Support the Digital Transformation of Public Health: Rapid Review of Current Recommendations

(2) What training approaches may best facilitate the learning and teaching of identified practice competency recommendations? and (3) What disciplines/disciplinary perspectives should be considered to facilitate identified practice competencies and training recommendations?

Swathi Ramachandran, Hsiu-Ju Chang, Catherine Worthington, Andre Kushniruk, Francisco Ibáñez-Carrasco, Hugh Davies, Geoffrey McKee, Adalsteinn Brown, Mark Gilbert, Ihoghosa Iyamu

JMIR Public Health Surveill 2024;10:e52798

Evaluating Large Language Models for Automated Reporting and Data Systems Categorization: Cross-Sectional Study

Evaluating Large Language Models for Automated Reporting and Data Systems Categorization: Cross-Sectional Study

Examples were attributing a 12-mm pulmonary nodule to the ≥6-mm but Explanatory errors (E4) including incorrect RADS category definitions (E4a) and inappropriate management recommendations (E4b) also substantially declined with prompt-1 and prompt-2. For instance, in the first Lung-RADS question response, the statement “The 4 X designation indicates infectious/inflammatory etiology is suspected.” is incorrect.

Qingxia Wu, Qingxia Wu, Huali Li, Yan Wang, Yan Bai, Yaping Wu, Xuan Yu, Xiaodong Li, Pei Dong, Jon Xue, Dinggang Shen, Meiyun Wang

JMIR Med Inform 2024;12:e55799

Development of Recommendations for the Digital Sharing of Notes With Adolescents in Mental Health Care: Delphi Study

Development of Recommendations for the Digital Sharing of Notes With Adolescents in Mental Health Care: Delphi Study

The Delphi method [21] was used to reach a consensus on recommendations for the digital sharing of notes with adolescents in mental health care. The Delphi study involved creating suggestions for recommendations, receiving feedback on the recommendations from Delphi participants, and creating final recommendations based on consensus. A literature search was performed to develop suggestions for recommendations and to identify participants for the Delphi study.

Martine Stecher Nielsen, Aslak Steinsbekk, Torunn Hatlen Nøst

JMIR Ment Health 2024;11:e57965

Identifying Existing Guidelines, Frameworks, Checklists, and Recommendations for Implementing Patient-Reported Outcome Measures: Protocol for a Scoping Review

Identifying Existing Guidelines, Frameworks, Checklists, and Recommendations for Implementing Patient-Reported Outcome Measures: Protocol for a Scoping Review

Along with the increase in the use of PROMs, it is important to ensure that guidelines, frameworks, checklists, and recommendations for implementing PROMs, addressing various aspects of PROMs’ implementation, exist to aid successful PROs collection. The findings of this scoping review will help us identify which guidelines, frameworks, checklists, and recommendations exist and if and how they have been applied in PROMs’ implementation in clinical trials, clinical practice, and CQRs.

Randi Thisakya Jayasinghe, Susannah Ahern, Ashika D Maharaj, Lorena Romero, Rasa Ruseckaite

JMIR Res Protoc 2024;13:e52572

Search Engines and Generative Artificial Intelligence Integration: Public Health Risks and Recommendations to Safeguard Consumers Online

Search Engines and Generative Artificial Intelligence Integration: Public Health Risks and Recommendations to Safeguard Consumers Online

The remaining 61.02% (83/136) of Google’s and 43.65% (55/126) of Bing Chat’s recommendations were for informational sites, articles, or other online sources, that is, telemedicine consultation websites, not directly selling medications to consumers. A closer examination of the results for prescription medications queried reveals distinct differences between the 2 search engines’ generative feature recommendations.

Amir Reza Ashraf, Tim Ken Mackey, András Fittler

JMIR Public Health Surveill 2024;10:e53086