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Unlocking the Potential of Wear Time of a Wearable Device to Enhance Postpartum Depression Screening and Detection: Cross-Sectional Study

Unlocking the Potential of Wear Time of a Wearable Device to Enhance Postpartum Depression Screening and Detection: Cross-Sectional Study

One significant issue with PPD is that most women do not receive sufficient screening, as only about 31% of women with PPD receive a diagnosis [4]. As noted by Cox et al [4], there are reliable screening instruments for PPD (eg, the Edinburgh-Postnatal Depression Scale [EPDS]) [9] and specific treatments for PPD (eg, brexanalone and zuranolone) [10,11]; yet screening and diagnosis of PPD lag behind and novel approaches for PPD detection are direly needed.

Eric Hurwitz, Samantha Meltzer-Brody, Zachary Butzin-Dozier, Rena C Patel, Noémie Elhadad, Melissa A Haendel

JMIR Form Res 2025;9:e67585

Challenges in Implementing Artificial Intelligence in Breast Cancer Screening Programs: Systematic Review and Framework for Safe Adoption

Challenges in Implementing Artificial Intelligence in Breast Cancer Screening Programs: Systematic Review and Framework for Safe Adoption

Second, high false-positive recall rates on initial screening often lead to additional procedures and cause undue anxiety for the patient [4]. Third, approximately 25% of cancers—known as interval breast cancers—are diagnosed between routine screening mammograms that initially appear normal and the next scheduled screening, despite adherence to regular screening intervals [5].

Serene Goh, Rachel Sze Jen Goh, Bryan Chong, Qin Xiang Ng, Gerald Choon Huat Koh, Kee Yuan Ngiam, Mikael Hartman

J Med Internet Res 2025;27:e62941

Potential Harms of Feedback After Web-Based Depression Screening: Secondary Analysis of Negative Effects in the Randomized Controlled DISCOVER Trial

Potential Harms of Feedback After Web-Based Depression Screening: Secondary Analysis of Negative Effects in the Randomized Controlled DISCOVER Trial

In the last decades, depression screening has been increasingly discussed as promising to reach those affected but undetected at an early stage. In addition to population-level screening in routine clinical care, as, for example, recommended in the United States [3], advocates also speak out in favor of screening for depression on the web [4]. For many affected individuals, the web is already the favored source for information on mental health [5,6].

Franziska Sikorski, Bernd Löwe, Anne Daubmann, Sebastian Kohlmann

J Med Internet Res 2025;27:e59476

Mobile Health Interventions for Modifying Indigenous Maternal and Child–Health Related Behaviors: Systematic Review

Mobile Health Interventions for Modifying Indigenous Maternal and Child–Health Related Behaviors: Systematic Review

The literature screening was performed using the Covidence systematic review software. After removing duplicate articles, the title and the abstract screen were performed by 1 reviewer per article (SI, OE, and AD). The studies selected for full-text review were screened by 2 independent assessors (SI, OE, and AD) against the eligibility criteria, with conflicts managed with discussion and with the assistance of an expert reviewer (BB).

Sana Ishaque, Ola Ela, Anna Dowling, Chris Rissel, Karla Canuto, Kerry Hall, Niranjan Bidargaddi, Annette Briley, Claire T Roberts, Billie Bonevski

J Med Internet Res 2025;27:e57019

Vital Sign and Biochemical Data Collection Using Non-contact Photoplethysmography and the Comestai Mobile Health App: Protocol for an Observational Study

Vital Sign and Biochemical Data Collection Using Non-contact Photoplethysmography and the Comestai Mobile Health App: Protocol for an Observational Study

Data collected using the reference devices will be stored without any identifiable participant information and will only be identifiable using the participant identification number provided during screening. The raw data of participants’ vital signs will be locked, encrypted, and accessible only to the study center team. Raw data can be processed only after unlocking the files to calculate the final measured results.

Gianvincenzo Zuccotti, Paolo Osvaldo Agnelli, Lucia Labati, Erika Cordaro, Davide Braghieri, Simone Balconi, Marco Xodo, Fabrizio Losurdo, Cesare Celeste Federico Berra, Roberto Franco Enrico Pedretti, Paolo Fiorina, Sergio Maria De Pasquale, Valeria Calcaterra

JMIR Res Protoc 2025;14:e65229

Telemedicine Booths for Screening Cardiovascular Risk Factors: Prospective Multicenter Study

Telemedicine Booths for Screening Cardiovascular Risk Factors: Prospective Multicenter Study

Various screening programs have been set up over the years to target people who rarely consult a GP. These programs have often focused on detecting hypertension, also known as the “silent killer,” and they have been run in a variety of different settings [15-17]. Some screening programs have involved health checks carried out by nurses, pharmacists, or medical students in settings such as pharmacies, dental surgeries, and community centers [18].

Mélanie Decambron, Christine Tchikladze Merand

JMIR Hum Factors 2025;12:e57032

Daily Automated Prediction of Delirium Risk in Hospitalized Patients: Model Development and Validation

Daily Automated Prediction of Delirium Risk in Hospitalized Patients: Model Development and Validation

As a result, a basic assessment for delirium is recommended for all hospitalized patients aged 65 years or older [5], and formal screening for delirium is recommended for critically ill patients [6]. Despite these recommendations, delirium frequently remains undiagnosed [7]. An automated delirium prediction tool could help address this, by alerting clinicians to at-risk patients so that they could be more carefully assessed for delirium.

Kendrick Matthew Shaw, Yu-Ping Shao, Manohar Ghanta, Valdery Moura Junior, Eyal Y Kimchi, Timothy T Houle, Oluwaseun Akeju, Michael Brandon Westover

JMIR Med Inform 2025;13:e60442

Barriers and Determinants of Referral Adherence in AI-Enabled Diabetic Retinopathy Screening for Older Adults in Northern India During the COVID-19 Pandemic: Mixed Methods Pilot Study

Barriers and Determinants of Referral Adherence in AI-Enabled Diabetic Retinopathy Screening for Older Adults in Northern India During the COVID-19 Pandemic: Mixed Methods Pilot Study

Significant scientific evidence shows that early screening and timely treatment referral can prevent most visual loss caused by DR [11]. Conventionally, DR screening (DRS) includes fundus (retina) examination by ophthalmologists or color fundus photography using conventional cameras (mydriatic or nonmydriatic) conducted by trained eye technicians or optometrists [12].

Anshul Chauhan, Anju Goyal, Ritika Masih, Gagandeep Kaur, Lakshay Kumar, ­ Neha, Harsh Rastogi, Sonam Kumar, Bidhi Lord Singh, Preeti Syal, Vishali Gupta, Luke Vale, Mona Duggal

JMIR Form Res 2025;9:e67047

The AI Reviewer: Evaluating AI’s Role in Citation Screening for Streamlined Systematic Reviews

The AI Reviewer: Evaluating AI’s Role in Citation Screening for Streamlined Systematic Reviews

However, the conventional systematic review methodology is time-consuming, particularly the manual screening of articles for pertinence [2]. The exponential increase in biomedical literature presents a challenge for researchers to remain updated. Artificial intelligence (AI) has shown promise in various fields [3], with large language models (LLMs) specifically offering capabilities to interpret complex text, which can be leveraged in the systematic review process [4].

Jamie Ghossein, Brett N Hryciw, Tim Ramsay, Kwadwo Kyeremanteng

JMIR Form Res 2025;9:e58366