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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

, (3) suicide plan (“Did you ever think about how you might kill yourself, e.g., taking pills, shooting yourself, or work out a plan of how to kill yourself?”), and (4) suicide attempt history (“Did you ever make a suicide attempt, i.e., purposefully hurt yourself with at least some intention to die?”). Respondents rated each of the 4 STBs as “No,” “Yes, once,” or “Yes, more than once.”

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

Cost-Effectiveness Analysis of a Machine Learning–Based eHealth System to Predict and Reduce Emergency Department Visits and Unscheduled Hospitalizations of Older People Living at Home: Retrospective Study

Cost-Effectiveness Analysis of a Machine Learning–Based eHealth System to Predict and Reduce Emergency Department Visits and Unscheduled Hospitalizations of Older People Living at Home: Retrospective Study

This longer stay in the ED is compounded by a higher rate of transfer to other departments or hospitals [3,7]. In people aged >80 years, main causes of admission to the ED are traumatic events (generally related to fall; 25%), cardiovascular events (17%), altered general condition or infection (12%), a respiratory symptom (12%), a gastrointestinal symptom (10%), and neurological symptoms (9%) [3,7]. Emergency hospitalization represents a significant medical and economic cost.

Charlotte Havreng-Théry, Arnaud Fouchard, Fabrice Denis, Jacques-Henri Veyron, Joël Belmin

JMIR Form Res 2025;9:e63700

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

In some recent studies, chest radiographs are used to detect lung disease [[13,14]], acute respiratory distress syndrome [15], pneumonia [16,17], tuberculosis [18,19], and COVID-19 [20]. However, to facilitate other tasks with comprehensive machine understanding, chest X-ray interpretation models are being more commonly used with the help of computer vision and transformer-based natural language processing models [21,22].

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

Providers generally had positive opinions about any new intervention that could increase efficiency of history-taking, allowing a larger proportion of appointment time to be devoted to management discussions. Some providers recognized potential benefits of the tool in assisting with diagnostic clarity due to its efficiency in eliciting additional information without relying on a longer appointment.

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

The mean age for young mothers was 17.3 (SD 0.9) years; they were predominantly single (14/19, 73.7%) with a few full cohabiting (4/19, 21.1%). The age of mothers who had some high school education was 10.6 (SD 1.9) years: 8 out of 19 (42.1%) of them were still students, 2 out of 19 (10.5%) of these were first-year university undergraduates); and 11 out of 19 (57.8%) others had dropped out of school and engaged in petty trading.

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

In this text, we use the term service user to refer to the individual with a psychosis diagnosis who is receiving mental health care from an early psychosis program. We use the term support person to refer to any person that the service user has chosen to involve in their care. This is typically the individual’s parent but might be another family member, a friend, a partner, or some other close relative.

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

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 addition, some commented that they would like to self-identify the areas where they needed help rather than having professionals assume that they needed help or support in an area, which was incorporated into the assessment procedure by first asking whether there is a problem in a specific area and secondly asking whether the respondent receives enough help with respect to this problem. A yes or no response to these questions would then indicate the presence or absence of an unmet need.

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

[P 8006] There can be some people who have never used a tablet and before the training, they should be asked; “have you ever used a tablet?” If the answer is “no,” they should be taught how to use the tablet. [P 8011] ….if there would be a number of people with few tablets that will be a ‘challenge’ since you will be waiting for your friends to finish then wait for another one. [P 8023] …if the networks are malfunctioning, it will definitely affect your work.

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