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Analyzing Trends in Suicidal Thoughts Among Patients With Psychosis in India: Exploratory Secondary Analysis of Smartphone Ecological Momentary Assessment Data

Analyzing Trends in Suicidal Thoughts Among Patients With Psychosis in India: Exploratory Secondary Analysis of Smartphone Ecological Momentary Assessment Data

Smartphone-based EMAs can assess dynamic symptoms such as SI, and help measure its duration, while enabling a safe disclosure of SI without face-to-face contact with the researcher or clinician [19,20]. However, most EMA studies on suicidality, as also EMA studies on day-to-day functioning of people with schizophrenia have been conducted in higher-income countries [21].

Ameya P Bondre, Aashish Ranjan, Ritu Shrivastava, Deepak Tugnawat, Nirmal Kumar Chaturvedi, Anant Bhan, Snehil Gupta, Abhijit R Rozatkar, Srilakshmi Nagendra, Siddharth Dutt, Soumya Choudhary, Preethi V Reddy, Urvakhsh Meherwan Mehta, John A Naslund, John Torous

JMIR Form Res 2025;9:e67745

Supporting Medication Adherence in Pediatric Patients Undergoing Hematopoietic Stem Cell Transplant Using the BMT4me mHealth App: Mixed Methods Usability Study

Supporting Medication Adherence in Pediatric Patients Undergoing Hematopoietic Stem Cell Transplant Using the BMT4me mHealth App: Mixed Methods Usability Study

Eligible caregivers were identified from the HCT clinic schedule and inpatient HCT unit based on the following eligibility criteria: (1) English-speaking, (2) 18 years of age or older, (3) having a child between 2 and 18 years of age undergoing allogeneic HCT, and (4) having a smartphone (either Android or i Phone) at recruitment and during the study period. All 20 caregivers of children who received HCT during the study period and met the eligibility criteria were approached for participation.

Mariam Kochashvili, Parishma Guttoo, Emre Sezgin, Ahna Pai, Rajinder Bajwa, Wendy Landier, Cynthia Gerhardt, Micah Skeens

JMIR Cancer 2025;11:e66847

A 12-Month Digital Peer-Supported App Intervention to Promote Physical Activity Among Community-Dwelling Older Adults: Follow-Up Study of a Nonrandomized Controlled Trial

A 12-Month Digital Peer-Supported App Intervention to Promote Physical Activity Among Community-Dwelling Older Adults: Follow-Up Study of a Nonrandomized Controlled Trial

The number of steps reported to the group chat in the DPSA was measured by the smartphone but was not used as an outcome. Physical function was assessed using grip strength and the 30-second chair stand test (CS-30). The grip strength was measured using a digital dynamometer (Grip D; TKK 5401; Takei Scientific Instruments).

Kento Tabira, Yuko Oguma, Shota Yoshihara, Megumi Shibuya, Manabu Nakamura, Natsue Doihara, Akihiro Hirata, Tomoki Manabe, Takashi Yamashita

JMIR Aging 2025;8:e66610

Using Personalized Intervention Criteria in a Mobile Just-in-Time Adaptive Intervention for Increasing Physical Activity in University Students: Pilot Study

Using Personalized Intervention Criteria in a Mobile Just-in-Time Adaptive Intervention for Increasing Physical Activity in University Students: Pilot Study

Mair et al [18] showed the feasibility of using personalized smartphone-delivered JITAI in elderly people. JITAI was tailored to the individual based on real time physical activity, daily physical activity goal, time of day, and weather conditions [18]. In most JITAI studies to date, however, the criteria for the intervention have been uniform (eg, 15 steps fewer per hour and sitting continuously for 30 or 60 minutes), and have not reflected the different activity patterns of the individual [12,18].

Mai Ikegaya, Jerome Clifford Foo, Taiga Murata, Kenta Oshima, Jinhyuk Kim

JMIR Hum Factors 2025;12:e66750

Using Digital Phenotyping to Discriminate Unipolar Depression and Bipolar Disorder: Systematic Review

Using Digital Phenotyping to Discriminate Unipolar Depression and Bipolar Disorder: Systematic Review

Eligible studies involved participants diagnosed with UD, BD, or HC and used portable or wearable digital devices such as smartphone apps, wearable sensors, or audio or visual recordings. The studies were required to either compare digital phenotyping results with diagnostic outcomes from professional medical evaluations, compare UD with BD, or perform a classification task involving UD, BD, and HC.

Rongrong Zhong, XiaoHui Wu, Jun Chen, Yiru Fang

J Med Internet Res 2025;27:e72229

Effects of Mobile Health Care App "Asmile" on Physical Activity of 80,689 Users in Osaka Prefecture, Japan: Longitudinal Observational Study

Effects of Mobile Health Care App "Asmile" on Physical Activity of 80,689 Users in Osaka Prefecture, Japan: Longitudinal Observational Study

In the first method, data are automatically transferred from a standard smartphone health care app into Asmile. This method transfers the daily step count for the last 42 days each time the user opens the app. The second method involves manual input of steps recorded by a pedometer. We used only automatically linked data in this study, excluding manual input data.

Asuka Oyama, Kenshiro Taguchi, Hiroe Seto, Reiko Kanaya, Jun'ichi Kotoku, Miyae Yamakawa, Hiroshi Toki, Ryohei Yamamoto

J Med Internet Res 2025;27:e65943

Efficacy, Safety, and Cost-Effectiveness of “Internet + Pharmacy Care” Via the Alfalfa App in Warfarin Therapy Management After Cardiac Valve Replacement: Randomized Controlled Trial

Efficacy, Safety, and Cost-Effectiveness of “Internet + Pharmacy Care” Via the Alfalfa App in Warfarin Therapy Management After Cardiac Valve Replacement: Randomized Controlled Trial

The main goal of this study was to evaluate the efficacy, safety, and economic impact of using the Alfalfa app, a smartphone app designed for dose consultation and adjustment in patients undergoing long-term anticoagulation therapy with warfarin. TTR was selected as the primary outcome, with a TTR of 60% or higher generally considered indicative of high-quality anticoagulant therapy [25].

Yiyi Qian, Weizhao Chen, Bin Zhou, Jiangya Li, Yuanyuan Guo, Zhiying Weng, Jinhua Zhang

JMIR Mhealth Uhealth 2025;13:e53586

Combining Artificial Intelligence and Human Support in Mental Health: Digital Intervention With Comparable Effectiveness to Human-Delivered Care

Combining Artificial Intelligence and Human Support in Mental Health: Digital Intervention With Comparable Effectiveness to Human-Delivered Care

Rapid advances in technology, computing, and artificial intelligence (AI) in recent years have led to a rise in the development of digital interventions aiming to solve this scalability problem, and there are an estimated 10,000-20,000 smartphone apps available for mental health support [6,7].

Clare E Palmer, Emily Marshall, Edward Millgate, Graham Warren, Michael Ewbank, Elisa Cooper, Samantha Lawes, Alastair Smith, Chris Hutchins-Joss, Jessica Young, Malika Bouazzaoui, Morad Margoum, Sandra Healey, Louise Marshall, Shaun Mehew, Ronan Cummins, Valentin Tablan, Ana Catarino, Andrew E Welchman, Andrew D Blackwell

J Med Internet Res 2025;27:e69351

Augmenting Engagement in Decentralized Clinical Trials for Atrial Fibrillation: Development and Implementation of a Programmatic Architecture

Augmenting Engagement in Decentralized Clinical Trials for Atrial Fibrillation: Development and Implementation of a Programmatic Architecture

Consented participants received study smartphones accompanied by training on their use and summary guides on smartphone and app operation developed for this study specific to the intervention and control arms. Materials provided to participants in the rural study and randomized to the intervention are provided as an Appendix in Multimedia Appendix 1.

Toluwa Daniel Omole, Andrew Mrkva, Danielle Ferry, Erin Shepherd, Jessica Caratelli, Noah Davis, Richmond Akatue, Timothy Bickmore, Michael K Paasche-Orlow, Jared W Magnani

JMIR Cardio 2025;9:e66436