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Impact of an Alert-Based Inpatient Clinical Decision Support Tool to Prevent Drug-Induced Long QT Syndrome: Large-Scale, System-Wide Observational Study

Impact of an Alert-Based Inpatient Clinical Decision Support Tool to Prevent Drug-Induced Long QT Syndrome: Large-Scale, System-Wide Observational Study

An example of one such CDS system is that designed to prevent drug-induced QT prolongation (di LQTS) [5]. di LQTS, and the subsequent risk of torsade de pointes, is widely recognized as a clinical concern across health care systems due to the number of medications that can cause di LQTS, including many used for noncardiac indications [6].

Katy E Trinkley, Steven T Simon, Michael A Rosenberg

J Med Internet Res 2025;27:e68256

Designing eHealth Interventions for Pediatric Emergency Departments: Protocol for a Usability Testing Study With Youth, Parent, and Clinician Participants

Designing eHealth Interventions for Pediatric Emergency Departments: Protocol for a Usability Testing Study With Youth, Parent, and Clinician Participants

The International Organization for Standardization describes usability as “the extent to which a system, product or service can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specified context of use” [1]. Usability testing is a method in which a product is evaluated by users as they perform tasks, and may include formative or summative testing [2].

Mari Somerville, Lori Wozney, Allyson Gallant, Janet A Curran

JMIR Res Protoc 2025;14:e64350

Early Detection of Type 1 Diabetes in First-Degree Relatives in Saudi Arabia (VISION-T1D): Protocol for a Pilot Implementation Study

Early Detection of Type 1 Diabetes in First-Degree Relatives in Saudi Arabia (VISION-T1D): Protocol for a Pilot Implementation Study

To enhance recruitment, a home testing option is provided, allowing families to conveniently perform finger-prick testing and data collection at home. After screening results are available, a research physician reviews the findings. Participants who test positive for islet autoantibodies are invited to a follow-up visit that includes personalized counseling, targeted educational interventions, and additional metabolic staging to determine their T1 D stage.

Iman S Algadi, Yazed AlRuthia, Muhammad H Mujammami, Khaled Hani Aburisheh, Metib Alotaibi, Sharifah Al Issa, Amal A Al-Saif, David Seftel, Cheng-Ting Tsai, Reem A Al Khalifah

JMIR Res Protoc 2025;14:e70575

Identifying Intersecting Factors Associated With Suicidal Thoughts and Behaviors Among Transgender and Gender Diverse Adults: Preliminary Conditional Inference Tree Analysis

Identifying Intersecting Factors Associated With Suicidal Thoughts and Behaviors Among Transgender and Gender Diverse Adults: Preliminary Conditional Inference Tree Analysis

Conditional inference trees model the nonlinear relationships between a wide range of predictors and an outcome. As a data mining approach, the conditional inference tree is a data-driven analytic strategy that identifies interacting social determinants from many candidate predictors to determine which predictors are most relevant to specific outcomes.

Amelia M Stanton, Lauren A Trichtinger, Norik Kirakosian, Simon M Li, Katherine E Kabel, Kiyan Irani, Alexandra H Bettis, Conall O’Cleirigh, Richard T Liu, Qimin Liu

J Med Internet Res 2025;27:e65452

Motivation Theories and Constructs in Experimental Studies of Online Instruction: Systematic Review and Directed Content Analysis

Motivation Theories and Constructs in Experimental Studies of Online Instruction: Systematic Review and Directed Content Analysis

For example, medical students completing an online module on a basic science topic may be confident in their ability to learn but struggle to see the value in the material beyond their next examination. Conversely, students completing a virtual examination with a standardized patient may see the value in what they are learning but not feel confident in their ability to succeed.

Adam Gavarkovs, Erin Miller, Jaimie Coleman, Tharsiga Gunasegaran, Rashmi A Kusurkar, Kulamakan Kulasegaram, Melanie Anderson, Ryan Brydges

JMIR Med Educ 2025;11:e64179

Development of an eHealth Mindfulness-Based Music Therapy Intervention for Adults Undergoing Allogeneic Hematopoietic Stem Cell Transplantation: Qualitative Study

Development of an eHealth Mindfulness-Based Music Therapy Intervention for Adults Undergoing Allogeneic Hematopoietic Stem Cell Transplantation: Qualitative Study

Participants (N=11; mean age 43.6, SD 17.8; range 19‐76 years) were female (55%, n=6), White (91%, n=10), Hispanic (73%, n=8), with a history of acute myeloid leukemia (100%, n=11), and a mean time of 1.64 (SD 0.81) years post-SCT at the time of the focus groups.

Sara E Fleszar-Pavlovic, Blanca Noriega Esquives, Padideh Lovan, Arianna E Brito, Ann Marie Sia, Mary Adelyn Kauffman, Maria Lopes, Patricia I Moreno, Tulay Koru-Sengul, Rui Gong, Trent Wang, Eric D Wieder, Maria Rueda-Lara, Michael Antoni, Krishna Komanduri, Teresa Lesiuk, Frank J Penedo

JMIR Form Res 2025;9:e65188

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

The aim of this study is to develop risk calculators that best predict (1) a mother’s risk of having a neonate with abnormal fetal growth (large for gestational age [LGA] or small for gestational age [SGA]); (2) a mother’s risk of having a serious adverse neonatal outcome; and (3) a mother’s risk of developing new metabolic disease after pregnancy (Figure 1).

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

JMIR Res Protoc 2025;14:e72542

Comparison of Deep Learning Approaches Using Chest Radiographs for Predicting Clinical Deterioration: Retrospective Observational Study

Comparison of Deep Learning Approaches Using Chest Radiographs for Predicting Clinical Deterioration: Retrospective Observational Study

This study was a secondary analysis of limited HIPAA data from hospital electronic health records. The study was approved with a waiver of informed consent. All direct identifiers of patients whose data were used in this study were de-identified prior to analysis to ensure participants privacy and confidentiality. Minimal necessary identifiable information was accessed or stored during the study beyond possible HIPAA data in clinical notes, radiological images, and real dates.

Mahmudur Rahman, Jifan Gao, Kyle A Carey, Dana P Edelson, Askar Afshar, John W Garrett, Guanhua Chen, Majid Afshar, Matthew M Churpek

JMIR AI 2025;4:e67144

Provider Perspectives on Implementing an Enhanced Digital Screening for Adolescent Depression and Suicidality: Qualitative Study

Provider Perspectives on Implementing an Enhanced Digital Screening for Adolescent Depression and Suicidality: Qualitative Study

Transcripts were coded by the first author following a template analysis approach [18] with NVivo software (version 14; Lumivero), using a prespecified codebook. The codebook was created according to a hybrid approach, using a deductive approach to generate high-level codes based on the CFIR Codebook Template [15], and an inductive approach to incorporate themes that arose from the data [19].

Morgan A Coren, Oliver Lindhiem, Abby R Angus, Emma K Toevs, Ana Radovic

JMIR Form Res 2025;9:e67624

Factors Impacting Mobile Health Adoption for Depression Care and Support by Adolescent Mothers in Nigeria: Preliminary Focus Group Study

Factors Impacting Mobile Health Adoption for Depression Care and Support by Adolescent Mothers in Nigeria: Preliminary Focus Group Study

Perinatal depression, a condition common in pregnant women, is higher among adolescent mothers than older mothers [10,11] occurring during pregnancy and up to one year after childbirth. Untreated perinatal depression is a risk for negative health outcomes for mothers and their infants [12].

Lola Kola, Tobi Fatodu, Manasseh Kola, Bisola A Olayemi, Adeyinka O Adefolarin, Simpa Dania, Manasi Kumar, Dror Ben-Zeev

JMIR Form Res 2025;9:e42406