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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

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

Furthermore, this simplifies the prediction task to a single time point, making it more feasible to compare multiple models and augmentation strategies. Patients with a chest radiograph within 48 hours before the first elevated e CART score were included in the study. Available anterior-posterior or posterior-anterior views were included in the study cohort.

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

Many of the young mothers noted it could help them to reduce the times they might have to go to the clinics because of the long waiting times they often experience: Many times at the clinic, I get tired and just want to go home because the crowd can be many…so this kind of app, will help someone like me since it could reduce clinic visits. A few saw it as a way to overcome access stigma related to being pregnant at a young age and cost-related barriers to health care.

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

Co-Designing a Web-Based and Tablet App to Evaluate Clinical Outcomes of Early Psychosis Service Users in a Learning Health Care Network: User-Centered Design Workshop and Pilot Study

Co-Designing a Web-Based and Tablet App to Evaluate Clinical Outcomes of Early Psychosis Service Users in a Learning Health Care Network: User-Centered Design Workshop and Pilot Study

For example, a narrative review of an MBC approach in behavioral health clinics found such benefits as significantly improving clinical outcomes, improving symptoms more quickly, and decreasing treatment costs [6]. To this end, the EPI-CAL team chose to design and implement a web-based and tablet app called Beehive.

Kathleen E Burch, Valerie L Tryon, Katherine M Pierce, Laura M Tully, Sabrina Ereshefsky, Mark Savill, Leigh Smith, Adam B Wilcox, Christopher Komei Hakusui, Viviana E Padilla, Amanda P McNamara, Merissa Kado-Walton, Andrew J Padovani, Chelyah Miller, Madison J Miles, Nitasha Sharma, Khanh Linh H Nguyen, Yi Zhang, Tara A Niendam

JMIR Hum Factors 2025;12:e65889

A Risk Prediction Model (CMC-AKIX) for Postoperative Acute Kidney Injury Using Machine Learning: Algorithm Development and Validation

A Risk Prediction Model (CMC-AKIX) for Postoperative Acute Kidney Injury Using Machine Learning: Algorithm Development and Validation

Acute kidney injury (AKI) represents a critical challenge in postoperative care, significantly affecting patient outcomes and health care systems. It is a common complication that affects up to 5% to 7.5% of all hospitalized patients, with a markedly higher prevalence of 20% in intensive care units [1]. Among all AKI in hospitalized patients, 40% occur in postoperative patients [1].

Ji Won Min, Jae-Hong Min, Se-Hyun Chang, Byung Ha Chung, Eun Sil Koh, Young Soo Kim, Hyung Wook Kim, Tae Hyun Ban, Seok Joon Shin, In Young Choi, Hye Eun Yoon

J Med Internet Res 2025;27:e62853

Identifying Unmet Needs of Informal Dementia Caregivers in Clinical Practice: User-Centered Development of a Digital Assessment Tool

Identifying Unmet Needs of Informal Dementia Caregivers in Clinical Practice: User-Centered Development of a Digital Assessment Tool

In phase 2, the chosen assessment version covering most unmet needs was tested in a memory clinic. A tablet computer was deemed most appropriate to serve as digital device due to its size, weight, flexibility, and ease of handling. Based on a previous study on the use of a tablet-based digital expert system [26,28,30], we had taken several decisions on the hardware basis of our system before the participatory part of our study started.

Olga A Biernetzky, Jochen René Thyrian, Melanie Boekholt, Matthias Berndt, Wolfgang Hoffmann, Stefan J Teipel, Ingo Kilimann

JMIR Aging 2025;8:e59942

Anticipated Acceptability of Blended Learning Among Lay Health Care Workers in Malawi: Qualitative Analysis Guided by the Technology Acceptance Model

Anticipated Acceptability of Blended Learning Among Lay Health Care Workers in Malawi: Qualitative Analysis Guided by the Technology Acceptance Model

Perceived usefulness refers to the belief that a certain technology would increase an individual’s job performance. Perceived ease of use is a belief that the use of the new technology would be effortless [27]. TAM proposes that a populations’ perceptions of usefulness and ease of use of a technology impact the population’s intention to use the technology, which in turn influences the population’s actual usage of the technology.

Tiwonge E Mbeya-Munkhondya, Caroline J Meek, Mtisunge Mphande, Tapiwa A Tembo, Mike J Chitani, Milenka Jean-Baptiste, Caroline Kumbuyo, Dhrutika Vansia, Katherine R Simon, Sarah E Rutstein, Victor Mwapasa, Vivian Go, Maria H Kim, Nora E Rosenberg

JMIR Form Res 2025;9:e62741