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Factor Analysis of Patients Who Find Tablets or Capsules Difficult to Swallow Due to Their Large Size: Using the Personal Health Record Infrastructure of Electronic Medication Notebooks J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-24 Masaki Asano, Shungo Imai, Yuri Shimizu, Hayato Kizaki, Yukiko Ito, Makoto Tsuchiya, Ryoko Kuriyama, Nao Yoshida, Masanori Shimada, Takanori Sando, Tomo Ishijima, Satoko Hori
Background: Understanding patient preference regarding taking tablet or capsule formulations plays a pivotal role in treatment efficacy and adherence. Therefore, these preferences should be taken into account when designing formulations and prescriptions. Objective: This study investigates the factors affecting patient preference in patients who have difficulties swallowing large tablets or capsules
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The Costs of Anonymization: Case Study Using Clinical Data J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-24 Lisa Pilgram, Thierry Meurers, Bradley Malin, Elke Schaeffner, Kai-Uwe Eckardt, Fabian Prasser, GCKD Investigators
Background: Sharing data from clinical studies can accelerate scientific progress, improve transparency, and increase the potential for innovation and collaboration. However, privacy concerns remain a barrier to data sharing. Certain concerns, such as reidentification risk, can be addressed through the application of anonymization algorithms, whereby data are altered so that it is no longer reasonably
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Large Language Models and User Trust: Consequence of Self-Referential Learning Loop and the Deskilling of Health Care Professionals J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-25 Avishek Choudhury, Zaira Chaudhry
As the health care industry increasingly embraces large language models (LLMs), understanding the consequence of this integration becomes crucial for maximizing benefits while mitigating potential pitfalls. This paper explores the evolving relationship among clinician trust in LLMs, the transition of data sources from predominantly human-generated to artificial intelligence (AI)–generated content,
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Electronic Media Use and Sleep Quality: Updated Systematic Review and Meta-Analysis J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-23 Xiaoning Han, Enze Zhou, Dong Liu
Background: This paper explores the widely discussed relationship between electronic media use and sleep quality, indicating negative effects due to various factors. However, existing meta-analyses on the topic have some limitations. Objective: The study aims to analyze and compare the impacts of different digital media types, such as smartphones, online games, and social media, on sleep quality. Methods:
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The Impact of Video-Based Microinterventions on Attitudes Toward Mental Health and Help Seeking in Youth: Web-Based Randomized Controlled Trial J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-24 Diana Lemmer, Markus Moessner, Nicolas Arnaud, Harald Baumeister, Agnes Mutter, Sarah-Lena Klemm, Elisa König, Paul Plener, Christine Rummel-Kluge, Rainer Thomasius, Michael Kaess, Stephanie Bauer
Background: Mental health (MH) problems in youth are prevalent, burdening, and frequently persistent. Despite the existence of effective treatment, the uptake of professional help is low, particularly due to attitudinal barriers. Objective: This study evaluated the effectiveness and acceptability of 2 video-based microinterventions aimed at reducing barriers to MH treatment and increasing the likelihood
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Behavior Change Approaches in Digital Technology–Based Physical Rehabilitation Interventions Following Stroke: Scoping Review J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-24 Helen J Gooch, Kathryn A Jarvis, Rachel C Stockley
Background: Digital health technologies (DHTs) are increasingly used in physical stroke rehabilitation to support individuals in successfully engaging with the frequent, intensive, and lengthy activities required to optimize recovery. Despite this, little is known about behavior change within these interventions. Objective: This scoping review aimed to identify if and how behavior change approaches
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Evaluation of Prompts to Simplify Cardiovascular Disease Information Generated Using a Large Language Model: Cross-Sectional Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-22 Vishala Mishra, Ashish Sarraju, Neil M Kalwani, Joseph P Dexter
In this cross-sectional study, we evaluated the completeness, readability, and syntactic complexity of cardiovascular disease prevention information produced by GPT-4 in response to 4 kinds of prompts.
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ChatGPT’s Performance in Cardiac Arrest and Bradycardia Simulations Using the American Heart Association's Advanced Cardiovascular Life Support Guidelines: Exploratory Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-22 Cecilia Pham, Romi Govender, Salik Tehami, Summer Chavez, Omolola E Adepoju, Winston Liaw
Background: ChatGPT is the most advanced large language model to date, with prior iterations having passed medical licensing examinations, providing clinical decision support, and improved diagnostics. Although limited, past studies of ChatGPT’s performance found that artificial intelligence could pass the American Heart Association’s advanced cardiovascular life support (ACLS) examinations with modifications
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Patient and Staff Experience of Remote Patient Monitoring—What to Measure and How: Systematic Review J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-22 Valeria Pannunzio, Hosana Cristina Morales Ornelas, Pema Gurung, Robert van Kooten, Dirk Snelders, Hendrikus van Os, Michel Wouters, Rob Tollenaar, Douwe Atsma, Maaike Kleinsmann
Background: Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience–measuring methods and tools exists. Objective: This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary
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Using ChatGPT-4 to Create Structured Medical Notes From Audio Recordings of Physician-Patient Encounters: Comparative Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-22 Annessa Kernberg, Jeffrey A Gold, Vishnu Mohan
Background: Medical documentation plays a crucial role in clinical practice, facilitating accurate patient management and communication among health care professionals. However, inaccuracies in medical notes can lead to miscommunication and diagnostic errors. Additionally, the demands of documentation contribute to physician burnout. Although intermediaries like medical scribes and speech recognition
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Problems and Barriers Related to the Use of mHealth Apps From the Perspective of Patients: Focus Group and Interview Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-23 Godwin Denk Giebel, Carina Abels, Felix Plescher, Christian Speckemeier, Nils Frederik Schrader, Kirstin Börchers, Jürgen Wasem, Silke Neusser, Nikola Blase
Background: Since fall 2020, mobile health (mHealth) apps have become an integral part of the German health care system. The belief that mHealth apps have the potential to make the health care system more efficient, close gaps in care, and improve the economic outcomes related to health is unwavering and already partially confirmed. Nevertheless, problems and barriers in the context of mHealth apps
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Empowering School Staff to Support Pupil Mental Health Through a Brief, Interactive Web-Based Training Program: Mixed Methods Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-23 Emma Soneson, Emma Howarth, Alison Weir, Peter B Jones, Mina Fazel
Background: Schools in the United Kingdom and elsewhere are expected to protect and promote pupil mental health. However, many school staff members do not feel confident in identifying and responding to pupil mental health difficulties and report wanting additional training in this area. Objective: We aimed to explore the feasibility of Kognito’s At-Risk for Elementary School Educators, a brief, interactive
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Investigating the Cost-Effectiveness of Telemonitoring Patients With Cardiac Implantable Electronic Devices: Systematic Review J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-19 Sarah Raes, Andrea Prezzi, Rik Willems, Hein Heidbuchel, Lieven Annemans
Background: Telemonitoring patients with cardiac implantable electronic devices (CIEDs) can improve their care management. However, the results of cost-effectiveness studies are heterogeneous. Therefore, it is still a matter of debate whether telemonitoring is worth the investment. Objective: This systematic review aims to investigate the cost-effectiveness of telemonitoring patients with CIEDs, focusing
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The Alzheimer’s Knowledge Base: A Knowledge Graph for Alzheimer Disease Research J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-18 Joseph D Romano, Van Truong, Rachit Kumar, Mythreye Venkatesan, Britney E Graham, Yun Hao, Nick Matsumoto, Xi Li, Zhiping Wang, Marylyn D Ritchie, Li Shen, Jason H Moore
Background: As global populations age and become susceptible to neurodegenerative illnesses, new therapies for Alzheimer disease (AD) are urgently needed. Existing data resources for drug discovery and repurposing fail to capture relationships central to the disease’s etiology and response to drugs. Objective: We designed the Alzheimer’s Knowledge Base (AlzKB) to alleviate this need by providing a
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Psychometric Evaluation of a Tablet-Based Tool to Detect Mild Cognitive Impairment in Older Adults: Mixed Methods Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-19 Josephine McMurray, AnneMarie Levy, Wei Pang, Paul Holyoke
Background: With the rapid aging of the global population, the prevalence of mild cognitive impairment (MCI) and dementia is anticipated to surge worldwide. MCI serves as an intermediary stage between normal aging and dementia, necessitating more sensitive and effective screening tools for early identification and intervention. The BrainFx SCREEN is a novel digital tool designed to assess cognitive
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Twitter Analysis of Health Care Workers’ Sentiment and Discourse Regarding Post–COVID-19 Condition in Children and Young People: Mixed Methods Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-17 Macarena Chepo, Sam Martin, Noémie Déom, Ahmad Firas Khalid, Cecilia Vindrola-Padros
Background: The COVID-19 pandemic has had a significant global impact, with millions of cases and deaths. Research highlights the persistence of symptoms over time (post–COVID-19 condition), a situation of particular concern in children and young people with symptoms. Social media such as Twitter (subsequently rebranded as X) could provide valuable information on the impact of the post–COVID-19 condition
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Digital Interventions for Recreational Cannabis Use Among Young Adults: Systematic Review, Meta-Analysis, and Behavior Change Technique Analysis of Randomized Controlled Studies J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-17 José Côté, Gabrielle Chicoine, Billy Vinette, Patricia Auger, Geneviève Rouleau, Guillaume Fontaine, Didier Jutras-Aswad
Background: The high prevalence of cannabis use among young adults poses substantial global health concerns due to the associated acute and long-term health and psychosocial risks. Digital modalities, including websites, digital platforms, and mobile apps, have emerged as promising tools to enhance the accessibility and availability of evidence-based interventions for young adults for cannabis use
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Comparing Open-Access Database and Traditional Intensive Care Studies Using Machine Learning: Bibliometric Analysis Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-17 Yuhe Ke, Rui Yang, Nan Liu
Background: Intensive care research has predominantly relied on conventional methods like randomized controlled trials. However, the increasing popularity of open-access, free databases in the past decade has opened new avenues for research, offering fresh insights. Leveraging machine learning (ML) techniques enables the analysis of trends in a vast number of studies. Objective: This study aims to
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Comparing Contact Tracing Through Bluetooth and GPS Surveillance Data: Simulation-Driven Approach J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-17 Weicheng Qian, Aranock Cooke, Kevin Gordon Stanley, Nathaniel David Osgood
Background: Accurate and responsive epidemiological simulations of epidemic outbreaks inform decision-making to mitigate the impact of pandemics. These simulations must be grounded in quantities derived from measurements, among which the parameters associated with contacts between individuals are notoriously difficult to estimate. Digital contact tracing data, such as those provided by Bluetooth beaconing
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Mobile Apps to Support Mental Health Response in Natural Disasters: Scoping Review J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-17 Nwamaka Alexandra Ezeonu, Attila J Hertelendy, Medard Kofi Adu, Janice Y Kung, Ijeoma Uchenna Itanyi, Raquel da Luz Dias, Belinda Agyapong, Petra Hertelendy, Francis Ohanyido, Vincent Israel Opoku Agyapong, Ejemai Eboreime
Background: Disasters are becoming more frequent due to the impact of extreme weather events attributed to climate change, causing loss of lives, property, and psychological trauma. Mental health response to disasters emphasizes prevention and mitigation, and mobile health (mHealth) apps have been used for mental health promotion and treatment. However, little is known about their use in the mental
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Integrating Biomarkers From Virtual Reality and Magnetic Resonance Imaging for the Early Detection of Mild Cognitive Impairment Using a Multimodal Learning Approach: Validation Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-17 Bogyeom Park, Yuwon Kim, Jinseok Park, Hojin Choi, Seong-Eun Kim, Hokyoung Ryu, Kyoungwon Seo
Background: Early detection of mild cognitive impairment (MCI), a transitional stage between normal aging and Alzheimer disease, is crucial for preventing the progression of dementia. Virtual reality (VR) biomarkers have proven to be effective in capturing behaviors associated with subtle deficits in instrumental activities of daily living, such as challenges in using a food-ordering kiosk, for early
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Evaluating Algorithmic Bias in 30-Day Hospital Readmission Models: Retrospective Analysis J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-18 H Echo Wang, Jonathan P Weiner, Suchi Saria, Hadi Kharrazi
Background: The adoption of predictive algorithms in health care comes with the potential for algorithmic bias, which could exacerbate existing disparities. Fairness metrics have been proposed to measure algorithmic bias, but their application to real-world tasks is limited. Objective: This study aims to evaluate the algorithmic bias associated with the application of common 30-day hospital readmission
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Quality of Answers of Generative Large Language Models Versus Peer Users for Interpreting Laboratory Test Results for Lay Patients: Evaluation Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-17 Zhe He, Balu Bhasuran, Qiao Jin, Shubo Tian, Karim Hanna, Cindy Shavor, Lisbeth Garcia Arguello, Patrick Murray, Zhiyong Lu
Background: Although patients have easy access to their electronic health records and laboratory test result data through patient portals, laboratory test results are often confusing and hard to understand. Many patients turn to web-based forums or question-and-answer (Q&A) sites to seek advice from their peers. The quality of answers from social Q&A sites on health-related questions varies significantly
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Service Quality and Residents’ Preferences for Facilitated Self-Service Fundus Disease Screening: Cross-Sectional Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-17 Senlin Lin, Yingyan Ma, Yanwei Jiang, Wenwen Li, Yajun Peng, Tao Yu, Yi Xu, Jianfeng Zhu, Lina Lu, Haidong Zou
Background: Fundus photography is the most important examination in eye disease screening. A facilitated self-service eye screening pattern based on the fully automatic fundus camera was developed in 2022 in Shanghai, China; it may help solve the problem of insufficient human resources in primary health care institutions. However, the service quality and residents’ preference for this new pattern are
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User-Centered Development of a Patient Decision Aid for Choice of Early Abortion Method: Multi-Cycle Mixed Methods Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-16 Kate J Wahl, Melissa Brooks, Logan Trenaman, Kirsten Desjardins-Lorimer, Carolyn M Bell, Nazgul Chokmorova, Romy Segall, Janelle Syring, Aleyah Williams, Linda C Li, Wendy V Norman, Sarah Munro
Background: People seeking abortion in early pregnancy have the choice between medication and procedural options for care. The choice is preference-sensitive—there is no clinically superior option and the choice depends on what matters most to the individual patient. Patient decision aids (PtDAs) are shared decision-making tools that support people in making informed, values-aligned health care choices
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Adverse Event Signal Detection Using Patients’ Concerns in Pharmaceutical Care Records: Evaluation of Deep Learning Models J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-16 Satoshi Nishioka, Satoshi Watabe, Yuki Yanagisawa, Kyoko Sayama, Hayato Kizaki, Shungo Imai, Mitsuhiro Someya, Ryoo Taniguchi, Shuntaro Yada, Eiji Aramaki, Satoko Hori
Background: Early detection of adverse events and their management are crucial to improving anticancer treatment outcomes, and listening to patients’ subjective opinions (patients’ voices) can make a major contribution to improving safety management. Recent progress in deep learning technologies has enabled various new approaches for the evaluation of safety-related events based on patient-generated
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Factors Influencing Recovery From Pediatric Stroke Based on Discussions From a UK-Based Online Stroke Community: Qualitative Thematic Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-16 Charlotte Howdle, William James Alexander Wright, Jonathan Mant, Anna De Simoni
Background: The incidence of stroke in children is low, and pediatric stroke rehabilitation services are less developed than adult ones. Survivors of pediatric stroke have a long poststroke life expectancy and therefore have the potential to experience impairments from their stroke for many years. However, there are relatively few studies characterizing these impairments and what factors facilitate
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The Effectiveness of a Digital App for Reduction of Clinical Symptoms in Individuals With Panic Disorder: Randomized Controlled Trial J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-12 KunJung Kim, Hyunchan Hwang, Sujin Bae, Sun Mi Kim, Doug Hyun Han
Background: Panic disorder is a common and important disease in clinical practice that decreases individual productivity and increases health care use. Treatments comprise medication and cognitive behavioral therapy. However, adverse medication effects and poor treatment compliance mean new therapeutic models are needed. Objective: We hypothesized that digital therapy for panic disorder may improve
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Application of AI in in Multilevel Pain Assessment Using Facial Images: Systematic Review and Meta-Analysis J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-12 Jian Huo, Yan Yu, Wei Lin, Anmin Hu, Chaoran Wu
Background: The continuous monitoring and recording of patients’ pain status is a major problem in current research on postoperative pain management. In the large number of original or review articles focusing on different approaches for pain assessment, many researchers have investigated how computer vision (CV) can help by capturing facial expressions. However, there is a lack of proper comparison
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Patients’ Experiences With Digitalization in the Health Care System: Qualitative Interview Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-11 Christian Gybel Jensen, Frederik Gybel Jensen, Mia Ingerslev Loft
Background: The digitalization of public and health sectors worldwide is fundamentally changing health systems. With the implementation of digital health services in health institutions, a focus on digital health literacy and the use of digital health services have become more evident. In Denmark, public institutions use digital tools for different purposes, aiming to create a universal public digital
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Evaluating the Digital Health Experience for Patients in Primary Care: Mixed Methods Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-11 Melinda Ada Choy, Kathleen O'Brien, Katelyn Barnes, Elizabeth Ann Sturgiss, Elizabeth Rieger, Kirsty Douglas
Background: The digital health divide for socioeconomic disadvantage describes a pattern in which patients considered socioeconomically disadvantaged, who are already marginalized through reduced access to face-to-face health care, are additionally hindered through less access to patient-initiated digital health. A comprehensive understanding of how patients with socioeconomic disadvantage access and
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Regulatory Standards and Guidance for the Use of Health Apps for Self-Management in Sub-Saharan Africa: Scoping Review J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-11 Benard Ayaka Bene, Sunny Ibeneme, Kayode Philip Fadahunsi, Bala Isa Harri, Nkiruka Ukor, Nikolaos Mastellos, Azeem Majeed, Josip Car
Background: Health apps are increasingly recognized as crucial tools for enhancing health care delivery. Many countries, particularly those in sub-Saharan Africa, can substantially benefit from using health apps to support self-management and thus help to achieve universal health coverage and the third sustainable development goal. However, most health apps published in app stores are of unknown or
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A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-11 Peter Washington
Modern machine learning approaches have led to performant diagnostic models for a variety of health conditions. Several machine learning approaches, such as decision trees and deep neural networks, can, in principle, approximate any function. However, this power can be considered to be both a gift and a curse, as the propensity toward overfitting is magnified when the input data are heterogeneous and
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Moderating Effect of Coping Strategies on the Association Between the Infodemic-Driven Overuse of Health Care Services and Cyberchondria and Anxiety: Partial Least Squares Structural Equation Modeling Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-09 Richard Huan Xu, Caiyun Chen
Background: The COVID-19 pandemic has led to a substantial increase in health information, which has, in turn, caused a significant rise in cyberchondria and anxiety among individuals who search for web-based medical information. To cope with this information overload and safeguard their mental well-being, individuals may adopt various strategies. However, the effectiveness of these strategies in mitigating
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Converge or Collide? Making Sense of a Plethora of Open Data Standards in Health Care J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-09 Guy Tsafnat, Rachel Dunscombe, Davera Gabriel, Grahame Grieve, Christian Reich
Practitioners of digital health are familiar with disjointed data environments that often inhibit effective communication among different elements of the ecosystem. This fragmentation leads in turn to issues such as inconsistencies in services versus payments, wastage, and notably, care delivered being less than best-practice. Despite the long-standing recognition of interoperable data as a potential
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Effectiveness of a Web-Based Individual Coping and Alcohol Intervention Program for Children of Parents With Alcohol Use Problems: Randomized Controlled Trial J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-10 Håkan Wall, Helena Hansson, Ulla Zetterlind, Pia Kvillemo, Tobias H Elgán
Background: Children whose parents have alcohol use problems are at an increased risk of several negative consequences, such as poor school performance, an earlier onset of substance use, and poor mental health. Many would benefit from support programs, but the figures reveal that only a small proportion is reached by existing support. Digital interventions can provide readily accessible support and
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Methodological Frameworks and Dimensions to Be Considered in Digital Health Technology Assessment: Scoping Review and Thematic Analysis J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-10 Joan Segur-Ferrer, Carolina Moltó-Puigmartí, Roland Pastells-Peiró, Rosa Maria Vivanco-Hidalgo
Background: Digital health technologies (dHTs) offer a unique opportunity to address some of the major challenges facing health care systems worldwide. However, the implementation of dHTs raises some concerns, such as the limited understanding of their real impact on health systems and people’s well-being or the potential risks derived from their use. In this context, health technology assessment (HTA)
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Longitudinal Monitoring of Clinician-Patient Video Visits During the Peak of the COVID-19 Pandemic: Adoption and Sustained Challenges in an Integrated Health Care Delivery System J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-08 Jessica A Palakshappa, Erica R Hale, Joshua D Brown, Carol A Kittel, Emily Dressler, Gary E Rosenthal, Sarah L Cutrona, Kristie L Foley, Emily R Haines, Thomas K Houston II
Background: Numerous prior opinion papers, administrative electronic health record data studies, and cross-sectional surveys of telehealth during the pandemic have been published, but none have combined assessments of video visit success monitoring with longitudinal assessments of perceived challenges to the rapid adoption of video visits during the pandemic. Objective: This study aims to quantify
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Evaluation of Large Language Model Performance and Reliability for Citations and References in Scholarly Writing: Cross-Disciplinary Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-05 Joseph Mugaanyi, Liuying Cai, Sumei Cheng, Caide Lu, Jing Huang
Background: Large language models (LLMs) have gained prominence since the release of ChatGPT in late 2022. Objective: The aim of this study was to assess the accuracy of citations and references generated by ChatGPT (GPT-3.5) in two distinct academic domains: the natural sciences and humanities. Methods: Two researchers independently prompted ChatGPT to write an introduction section for a manuscript
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Assessing the Clinical Efficacy of a Virtual Reality Tool for the Treatment of Obesity: Randomized Controlled Trial J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-05 Dimitra Anastasiadou, Pol Herrero, Paula Garcia-Royo, Julia Vázquez-De Sebastián, Mel Slater, Bernhard Spanlang, Elena Álvarez de la Campa, Andreea Ciudin, Marta Comas, Josep Antoni Ramos-Quiroga, Pilar Lusilla-Palacios
Background: Virtual reality (VR) interventions, based on cognitive behavioral therapy principles, have been proven effective as complementary tools in managing obesity and have been associated with promoting healthy behaviors and addressing body image concerns. However, they have not fully addressed certain underlying causes of obesity, such as a lack of motivation to change, low self-efficacy, and
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Moving Biosurveillance Beyond Coded Data Using AI for Symptom Detection From Physician Notes: Retrospective Cohort Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-04 Andrew J McMurry, Amy R Zipursky, Alon Geva, Karen L Olson, James R Jones, Vladimir Ignatov, Timothy A Miller, Kenneth D Mandl
Background: Real-time surveillance of emerging infectious diseases necessitates a dynamically evolving, computable case definition, which frequently incorporates symptom-related criteria. For symptom detection, both population health monitoring platforms and research initiatives primarily depend on structured data extracted from electronic health records. Objective: This study sought to validate and
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Impacts of an Acute Care Telenursing Program on Discharge, Patient Experience, and Nursing Experience: Retrospective Cohort Comparison Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-04 Courtenay R Bruce, Steve Klahn, Lindsay Randle, Xin Li, Kelkar Sayali, Barbara Johnson, Melissa Gomez, Meagan Howard, Roberta Schwartz, Farzan Sasangohar
Background: Despite widespread growth of televisits and telemedicine, it is unclear how telenursing could be applied to augment nurse labor and support nursing. Objective: This study evaluated a large-scale acute care telenurse (ACTN) program to support web-based admission and discharge processes for hospitalized patients. Methods: A retrospective, observational cohort comparison was performed in a
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Public Discourse, User Reactions, and Conspiracy Theories on the X Platform About HIV Vaccines: Data Mining and Content Analysis J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-03 Jueman M Zhang, Yi Wang, Magali Mouton, Jixuan Zhang, Molu Shi
Background: The initiation of clinical trials for messenger RNA (mRNA) HIV vaccines in early 2022 revived public discussion on HIV vaccines after 3 decades of unsuccessful research. These trials followed the success of mRNA technology in COVID-19 vaccines but unfolded amid intense vaccine debates during the COVID-19 pandemic. It is crucial to gain insights into public discourse and reactions about
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The Impact of Digital Self-Monitoring of Weight on Improving Diabetes Clinical Outcomes: Quasi-Randomized Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-02 Yifat Fundoiano-Hershcovitz, Marilyn D Ritholz, David L Horwitz, Ephraim Behar, Omar Manejwala, Pavel Goldstein
Background: The management of type 2 diabetes (T2D) and obesity, particularly in the context of self-monitoring, remains a critical challenge in health care. As nearly 80% to 90% of patients with T2D have overweight or obesity, there is a compelling need for interventions that can effectively manage both conditions simultaneously. One of the goals in managing chronic conditions is to increase awareness
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The Challenges in Using eHealth Decision Resources for Surrogate Decision-Making in the Intensive Care Unit J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-01 Wan-Na Sun, Chi-Yin Kao
The mortality rate in intensive care units (ICUs) is notably high, with patients often relying on surrogates for critical medical decisions due to their compromised state. This paper provides a comprehensive overview of eHealth. The challenges of applying eHealth tools, including economic disparities and information inaccuracies are addressed. This study then introduces eHealth literacy and the assessment
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Response of Unvaccinated US Adults to Official Information About the Pause in Use of the Johnson & Johnson–Janssen COVID-19 Vaccine: Cross-Sectional Survey Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-04-01 Vishala Mishra, Joseph P Dexter
Using a rapid response web-based survey, we identified gaps in public understanding of the Centers for Disease Control and Prevention’s messaging about the pause in use of the Johnson & Johnson–Janssen COVID-19 vaccine and estimated changes in vaccine hesitancy using counterfactual questions.
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Medical Misinformation in Polish on the World Wide Web During the COVID-19 Pandemic Period: Infodemiology Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-03-29 Małgorzata Chlabicz, Aleksandra Nabożny, Jolanta Koszelew, Wojciech Łaguna, Anna Szpakowicz, Paweł Sowa, Wojciech Budny, Katarzyna Guziejko, Magdalena Róg-Makal, Sławomir Pancewicz, Maciej Kondrusik, Piotr Czupryna, Beata Cudowska, Dariusz Lebensztejn, Anna Moniuszko-Malinowska, Adam Wierzbicki, Karol A Kamiński
Background: Although researchers extensively study the rapid generation and spread of misinformation about the novel coronavirus during the pandemic, numerous other health-related topics are contaminating the internet with misinformation that have not received as much attention. Objective: This study aims to gauge the reach of the most popular medical content on the World Wide Web, extending beyond
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An Entity Extraction Pipeline for Medical Text Records Using Large Language Models: Analytical Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-03-29 Lei Wang, Yinyao Ma, Wenshuai Bi, Hanlin Lv, Yuxiang Li
Background: The study of disease progression relies on clinical data, including text data, and extracting valuable features from text data has been a research hot spot. With the rise of large language models (LLMs), semantic-based extraction pipelines are gaining acceptance in clinical research. However, the security and feature hallucination issues of LLMs require further attention. Objective: This
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Usability of Health Care Price Transparency Data in the United States: Mixed Methods Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-03-29 Negar Maleki, Balaji Padmanabhan, Kaushik Dutta
Background: Increasing health care expenditure in the United States has put policy makers under enormous pressure to find ways to curtail costs. Starting January 1, 2021, hospitals operating in the United States were mandated to publish transparent, accessible pricing information online about the items and services in a consumer-friendly format within comprehensive machine-readable files on their websites
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#ProtectOurElders: Analysis of Tweets About Older Asian Americans and Anti-Asian Sentiments During the COVID-19 Pandemic J. Med. Internet Res. (IF 7.4) Pub Date : 2024-03-29 Reuben Ng, Nicole Indran
Background: A silver lining to the COVID-19 pandemic is that it cast a spotlight on a long-underserved group. The barrage of attacks against older Asian Americans during the crisis galvanized society into assisting them in various ways. On Twitter, now known as X, support for them coalesced around the hashtag #ProtectOurElders. To date, discourse surrounding older Asian Americans has escaped the attention
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The Influence of Joe Wicks on Physical Activity During the COVID-19 Pandemic: Thematic, Location, and Social Network Analysis of X Data J. Med. Internet Res. (IF 7.4) Pub Date : 2024-03-29 Wasim Ahmed, Opeoluwa Aiyenitaju, Simon Chadwick, Mariann Hardey, Alex Fenton
Background: Social media (SM) was essential in promoting physical activity during the COVID-19 pandemic, especially among people confined to their homes. Joe Wicks, a fitness coach, became particularly popular on SM during this time, posting daily workouts that millions of people worldwide followed. Objective: This study aims to investigate the influence of Joe Wicks on SM and the impact of his content
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Developing and Testing the Usability of a Novel Child Abuse Clinical Decision Support System: Mixed Methods Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-03-29 Amy Thomas, Andrea Asnes, Kyle Libby, Allen Hsiao, Gunjan Tiyyagura
Background: Despite the impact of physical abuse on children, it is often underdiagnosed, especially among children evaluated in general emergency departments (EDs) and those belonging to racial or ethnic minority groups. Electronic clinical decision support (CDS) can improve the recognition of child physical abuse. Objective: We aimed to develop and test the usability of a natural language processing–based
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Identification of Predictors for Clinical Deterioration in Patients With COVID-19 via Electronic Nursing Records: Retrospective Observational Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-03-29 Sumi Sung, Youlim Kim, Su Hwan Kim, Hyesil Jung
Background: Few studies have used standardized nursing records with Systematized Nomenclature of Medicine–Clinical Terms (SNOMED CT) to identify predictors of clinical deterioration. Objective: This study aims to standardize the nursing documentation records of patients with COVID-19 using SNOMED CT and identify predictive factors of clinical deterioration in patients with COVID-19 via standardized
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Telehealth Care Through Internet Hospitals in China: Qualitative Interview Study of Physicians’ Views on Access, Expectations, and Communication J. Med. Internet Res. (IF 7.4) Pub Date : 2024-03-29 Yuqiong Zhong, Jessica Hahne, Xiaomin Wang, Xuxi Wang, Ying Wu, Xin Zhang, Xing Liu
Background: Internet hospitals in China are an emerging medical service model similar to other telehealth models used worldwide. Internet hospitals are currently in a stage of rapid development, giving rise to a series of new opportunities and challenges for patient care. Little research has examined the views of chronic disease physicians regarding internet hospitals in China. Objective: We aimed
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Effects of a Digital Mental Health Intervention on Perceived Stress and Rumination in Adolescents Aged 13 to 17 Years: Randomized Controlled Trial J. Med. Internet Res. (IF 7.4) Pub Date : 2024-03-29 Eliane M Boucher, Haley Ward, Cynthia J Miles, Robert D Henry, Sarah Elizabeth Stoeckl
Background: Although adolescents report high levels of stress, they report engaging in few stress management techniques. Consequently, developing effective and targeted programs to help address this transdiagnostic risk factor in adolescence is particularly important. Most stress management programs for adolescents are delivered within schools, and the evidence for these programs is mixed, suggesting
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Evaluation of Telehealth Services that are Clinically Appropriate for Reimbursement in the US Medicaid Population: Mixed Methods Study J. Med. Internet Res. (IF 7.4) Pub Date : 2024-03-28 Sanjeev Saravanakumar, Andrey Ostrovsky
Background: When the US Department of Health and Human Services instituted a State of Public Health Emergency (PHE) during the COVID-19 pandemic, many telehealth flexibilities were fast-tracked to allow state Medicaid agencies to reimburse new specialty services, sites of care, and mediums such as FaceTime to communicate with patients.. This resulted in expanded access to care for financially vulnerable
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Development and External Validation of Machine Learning Models for Diabetic Microvascular Complications: Cross-Sectional Study With Metabolites J. Med. Internet Res. (IF 7.4) Pub Date : 2024-03-28 Feng He, Clarissa Ng Yin Ling, Simon Nusinovici, Ching-Yu Cheng, Tien Yin Wong, Jialiang Li, Charumathi Sabanayagam
Background: Diabetic kidney disease (DKD) and diabetic retinopathy (DR) are major diabetic microvascular complications, contributing significantly to morbidity, disability, and mortality worldwide. The kidney and the eye, having similar microvascular structures and physiological and pathogenic features, may experience similar metabolic changes in diabetes. Objective: This study aimed to use machine
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Augmenting K-Means Clustering With Qualitative Data to Discover the Engagement Patterns of Older Adults With Multimorbidity When Using Digital Health Technologies: Proof-of-Concept Trial J. Med. Internet Res. (IF 7.4) Pub Date : 2024-03-28 Yiyang Sheng, Raymond Bond, Rajesh Jaiswal, John Dinsmore, Julie Doyle
Background: Multiple chronic conditions (multimorbidity) are becoming more prevalent among aging populations. Digital health technologies have the potential to assist in the self-management of multimorbidity, improving the awareness and monitoring of health and well-being, supporting a better understanding of the disease, and encouraging behavior change. Objective: The aim of this study was to analyze
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Weight Gain Prevention Outcomes From a Pragmatic Digital Health Intervention With Community Health Center Patients: Randomized Controlled Trial J. Med. Internet Res. (IF 7.4) Pub Date : 2024-03-28 Hailey N Miller, John A Gallis, Miriam B Berger, Sandy Askew, Joseph R Egger, Melissa C Kay, Eric Andrew Finkelstein, Mia de Leon, Abigail DeVries, Ashley Brewer, Marni Gwyther Holder, Gary G Bennett
Background: The prevalence of obesity and its associated comorbidities continue to rise in the United States. Populations who are uninsured and from racial and ethnic minority groups continue to be disproportionately affected. These populations also experience fewer clinically meaningful outcomes in most weight loss trials. Weight gain prevention presents a useful strategy for individuals who experience
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Digital Alcohol Interventions Could Be Part of the Societal Response to Harmful Consumption, but We Know Little About Their Long-Term Costs and Health Outcomes J. Med. Internet Res. (IF 7.4) Pub Date : 2024-03-27 Katarina Ulfsdotter Gunnarsson, Martin Henriksson, Marcus Bendtsen
Alcohol consumption causes both physical and psychological harm and is a leading risk factor for noncommunicable diseases. Digital alcohol interventions have been found to support those looking for help by giving them tools for change. However, whether digital interventions can help tackle the long-term societal consequences of harmful alcohol consumption in a cost-effective manner has not been adequately