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Assessing the Clinical Feasibility of the DiaFocus System for Integrated Personalized Management of Type 2 Diabetes: 6-Month Pilot Cohort Study

Assessing the Clinical Feasibility of the DiaFocus System for Integrated Personalized Management of Type 2 Diabetes: 6-Month Pilot Cohort Study

The system is designed to collect diabetes-related data, including participant-reported outcomes, sensor-based measures on physical activity, and participant-selected focus areas, aiming to support communication and shared decision-making between the HCP and the person with diabetes. The technical feasibility of using the Dia Focus app for T2 D management was assessed in a 6-week pilot study with 12 participants [13].

Nanna Lind, Per Bækgaard, Jakob E Bardram, Claus Cramer-Petersen, Kirsten Nørgaard, Merete B Christensen

JMIR Diabetes 2025;10:e63894

Comparing the Costs of Surveillance of Early-Stage Breast Cancer by Digital or Traditional Follow-Up Methods: Randomized Crossover Study

Comparing the Costs of Surveillance of Early-Stage Breast Cancer by Digital or Traditional Follow-Up Methods: Randomized Crossover Study

Due to the increasing number of breast cancer survivors and limited health care resources, there was a need to develop web-based systems for communication between patients and professionals. In 2015, a web-based patient report app Noona (Helsinki University Hospital; Noona Healthcare) was developed at the HUS CCC in collaboration with a Finnish start-up company. Noona app enabled patients to contact specialist breast cancer nurses between visits.

Maria Peltola, Carl Blomqvist, Niilo Färkkilä, Paula Poikonen-Saksela, Johanna Mattson

JMIR Cancer 2025;11:e58113

Communicating Antimicrobial Resistance on Instagram: Content Analysis of #AntibioticResistance

Communicating Antimicrobial Resistance on Instagram: Content Analysis of #AntibioticResistance

The sender-message-channel-receiver (SMCR) communication model, developed by Berlo in 1960 [37,38], outlines 4 essential components in the communication process: the sender, the message, the channel, and the receiver. This model has been extensively used in communication research, including as a framework for understanding how SNS users disseminate and receive information [39-41].

Elin Nilsson, Emma Oljans, Anna-Carin Nordvall, Mirko Ancillotti

JMIR Infodemiology 2025;5:e67825

Outcomes of an App-Based Intervention to Target Naming Among Individuals With Poststroke Aphasia: Virtual Randomized Controlled Trial

Outcomes of an App-Based Intervention to Target Naming Among Individuals With Poststroke Aphasia: Virtual Randomized Controlled Trial

Specifically, we examined the impact of training with the Voice Adapt app on language and communication outcomes in individuals with chronic aphasia. Primary outcomes were naming ability, and secondary outcomes included measures of overall language, communication effectiveness, and quality of life.

Esther S Kim, Laura Laird, Carlee Wilson, Steven Stewart, Philip Mildner, Sebastian Möller, Raimund Schatz, Robert P Spang, Jan-Niklas Voigt-Antons, Elizabeth Rochon

JMIR Mhealth Uhealth 2025;13:e67711

Examining Potential Implicit Bias in Oncologist-Patient Communication (CONNECT): Protocol for an Observational 2-Site Study

Examining Potential Implicit Bias in Oncologist-Patient Communication (CONNECT): Protocol for an Observational 2-Site Study

Minority patients have reported poor patient-centered communication (eg, respecting and responding to patients’ wants, needs, and preferences), which can influence assessments, recommendations, and outcomes [15].

Veronica C K Duck, Marsha L Augustin, Jose A Morillo, Aviel N Alkon, Robert M Thomas, Brianna N Richardson, Lihua Li, Kathryn I Pollak, Cardinale B Smith

JMIR Res Protoc 2025;14:e66086

Use of a Medical Communication Framework to Assess the Quality of Generative Artificial Intelligence Replies to Primary Care Patient Portal Messages: Content Analysis

Use of a Medical Communication Framework to Assess the Quality of Generative Artificial Intelligence Replies to Primary Care Patient Portal Messages: Content Analysis

Frameworks for medical communication are widely accepted and taught, with a consensus on “best practice” for high-quality communication [18]. Ideal automation would ensure that standards for communication were consistently met, and such a tool would invariably be helpful to PCPs while maintaining or enhancing patient care. However, no prior studies have applied a medical communication framework to systematically evaluate Gen AI draft quality or the consistency of its quality.

Natalie S Lee, Nathan Richards, Jodi Grandominico, Robert M Cronin, Amanda K Hendricks, Ravi S Tripathi, Daniel E Jonas

JMIR Form Res 2025;9:e71966

Evaluating the Feasibility of Web-Monitoring Methodology for Measuring Exposure to Online Cancer Misinformation

Evaluating the Feasibility of Web-Monitoring Methodology for Measuring Exposure to Online Cancer Misinformation

The purpose of this viewpoint paper is to share lessons learned from this novel application of web-monitoring software for health communication research. We aim to provide practical information to other researchers who are exploring technology-based methods to objectively measure the quality of cancer information individuals are exposed to online.

Cindy A Turner, Andy J King, Ida Tovar, Morgan M Millar, Rachel R Codden, Jia-Wen Guo, Skyler Johnson, Anne C Kirchhoff, Margaret Raber, Xiaoming Sheng, Deanna Kepka, Echo L Warner

JMIR Cancer 2025;11:e65887

Patient Perspectives on Artificial Intelligence in Health Care: Focus Group Study for Diagnostic Communication and Tool Implementation

Patient Perspectives on Artificial Intelligence in Health Care: Focus Group Study for Diagnostic Communication and Tool Implementation

Our study aims to address this gap by investigating patient and family perspectives on AI’s role in diagnosis and diagnostic communication across various theoretical and practical applications through a co-design approach. By engaging patients and families as partners in this research, we seek to uncover their expectations, concerns, and preferences for how AI should be used to enhance diagnostic safety, support clinician-patient communication, and promote equitable health care delivery.

Garrett Foresman, Joshua Biro, Alberta Tran, Kate MacRae, Sadaf Kazi, Laura Schubel, Adam Visconti, William Gallagher, Kelly M Smith, Traber Giardina, Helen Haskell, Kristen Miller

J Particip Med 2025;17:e69564

Networked Behaviors Associated With a Large-Scale Secure Messaging Network: Cross-Sectional Secondary Data Analysis

Networked Behaviors Associated With a Large-Scale Secure Messaging Network: Cross-Sectional Secondary Data Analysis

Communication among health care professionals is key to effective clinical care, with reports suggesting that health care professionals spend >80% of their time on clinical communication [1,2]. Although face-to-face communication is often preferred, it is often not possible due to a lack of geographical proximity or other constraints [3]. As such, health care professionals rely on a number of synchronous (eg, phone) or asynchronous (eg, secure messaging, email, and pager) modes of communication.

Laura Rosa Baratta, Linlin Xia, Daphne Lew, Elise Eiden, Y Jasmine Wu, Noshir Contractor, Bruce L Lambert, Sunny S Lou, Thomas Kannampallil

JMIR Med Inform 2025;13:e66544

Nurses’ Experience Regarding Barriers to Providing Internet Plus Continuous Nursing: Mixed Methods Study

Nurses’ Experience Regarding Barriers to Providing Internet Plus Continuous Nursing: Mixed Methods Study

This approach aims to build a connection between health care providers and patients by leveraging the power of the internet to facilitate real-time monitoring, communication, and data sharing. Health care professionals can thus remotely monitor patients’ vital signs, provide guidance, offer medication reminders, and deliver personalized care plans [9,10]. In addition, the novel model could also streamline clinical workflows [11], enhance patient engagement [12], and facilitate knowledge sharing [13].

Huanhuan Huang, Zhiyu Chen, Lijuan Chen, Xingyao Du, Qi Huang, Wenbi Jia, Qinghua Zhao

JMIR Med Inform 2025;13:e65445