Aurélien Lambert, Benoit Hombourger, Julia Salleron, Fadila Chergui, Catherine Vallance, Nadège Nicolas, Marie Moussouni, Lounisse Cherif, Emile Chenot, Céline Gavoille, Vincent Massard
Background: The transition from traditional handwritten prescriptions to electronic prescribing systems represents a significant advancement, with the potential to enhance treatment efficacy, patient safety, and professional communication.
Objective: This study aimed to examine the impact of this transition within a medical oncology service, assessing the compliance of electronic prescriptions with established good practice standards and exploring the associated risks.
Methods: In this retrospective analysis, we compared handwritten prescriptions from the pre-electronic era (January to May 2018) with electronic prescriptions (January to May 2021) following the implementation of the electronic prescribing system PandaLab Pro (PandaLab SAS). The inclusion criteria focused on outpatient oncology treatments, with a clear set of exclusion parameters to ensure a focused study scope. We defined good compliance as the written mention of the evaluated terms. The compliance rates were then compared using a chi-square test.
Results: Our findings, based on a sample size of 260 prescriptions (randomized among 30,526 archived prescriptions), indicate a substantial improvement in electronic prescriptions' compliance with prescribers and patient details, treatment accuracy, and overall adherence to regulatory standards. Notably, electronic formats achieved a remarkable 80.8% accuracy rate in compliance with safety criteria compared with 8.5% for handwritten prescriptions (P<.001). The use of prefilled prescriptions significantly increased compliance from a safety perspective (56% vs 96.2%; P<.001) compared with electronic prescriptions from scratch.
Conclusions: The analysis further underscores the advantages of prefilled electronic prescription templates, which significantly improved compliance rates compared with manually filled electronic and handwritten prescriptions. Furthermore, the study revealed a marked shift in prescribing behaviors, with electronic prescriptions tending to be more concise yet more numerous, suggesting an impact on medication management and patient adherence, which warrants further investigation. The study supports the transition to electronic prescribing systems in oncology, highlighting enhanced traceability, compliance with health authority standards, and patient safety. The implementation of prefilled templates supported by pharmacists has emerged as a pivotal factor in this improved process. While acknowledging certain limitations, such as the nonquantitative assessment of time savings and acceptability, this research advocates for the widespread adoption of electronic prescriptions and serves as a benchmark for future e-prescription initiatives in France.
{"title":"Impact of Electronic Transition and Prefilled Templates on Drug Prescription Compliance: Retrospective Study.","authors":"Aurélien Lambert, Benoit Hombourger, Julia Salleron, Fadila Chergui, Catherine Vallance, Nadège Nicolas, Marie Moussouni, Lounisse Cherif, Emile Chenot, Céline Gavoille, Vincent Massard","doi":"10.2196/57782","DOIUrl":"https://doi.org/10.2196/57782","url":null,"abstract":"<p><strong>Background: </strong>The transition from traditional handwritten prescriptions to electronic prescribing systems represents a significant advancement, with the potential to enhance treatment efficacy, patient safety, and professional communication.</p><p><strong>Objective: </strong>This study aimed to examine the impact of this transition within a medical oncology service, assessing the compliance of electronic prescriptions with established good practice standards and exploring the associated risks.</p><p><strong>Methods: </strong>In this retrospective analysis, we compared handwritten prescriptions from the pre-electronic era (January to May 2018) with electronic prescriptions (January to May 2021) following the implementation of the electronic prescribing system PandaLab Pro (PandaLab SAS). The inclusion criteria focused on outpatient oncology treatments, with a clear set of exclusion parameters to ensure a focused study scope. We defined good compliance as the written mention of the evaluated terms. The compliance rates were then compared using a chi-square test.</p><p><strong>Results: </strong>Our findings, based on a sample size of 260 prescriptions (randomized among 30,526 archived prescriptions), indicate a substantial improvement in electronic prescriptions' compliance with prescribers and patient details, treatment accuracy, and overall adherence to regulatory standards. Notably, electronic formats achieved a remarkable 80.8% accuracy rate in compliance with safety criteria compared with 8.5% for handwritten prescriptions (P<.001). The use of prefilled prescriptions significantly increased compliance from a safety perspective (56% vs 96.2%; P<.001) compared with electronic prescriptions from scratch.</p><p><strong>Conclusions: </strong>The analysis further underscores the advantages of prefilled electronic prescription templates, which significantly improved compliance rates compared with manually filled electronic and handwritten prescriptions. Furthermore, the study revealed a marked shift in prescribing behaviors, with electronic prescriptions tending to be more concise yet more numerous, suggesting an impact on medication management and patient adherence, which warrants further investigation. The study supports the transition to electronic prescribing systems in oncology, highlighting enhanced traceability, compliance with health authority standards, and patient safety. The implementation of prefilled templates supported by pharmacists has emerged as a pivotal factor in this improved process. While acknowledging certain limitations, such as the nonquantitative assessment of time savings and acceptability, this research advocates for the widespread adoption of electronic prescriptions and serves as a benchmark for future e-prescription initiatives in France.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e57782"},"PeriodicalIF":5.8,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143811658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jianan Wang, Yihong Xu, Zhichao Yang, Jie Zhang, Xiaoxiao Zhang, Wen Li, Yushu Sun, Hongying Pan
Background: Information distortion in nursing records poses significant risks to patient safety and impedes the enhancement of care quality. The introduction of information technologies, such as decision support systems and predictive models, expands the possibilities for using health data but also complicates the landscape of information distortion. Only by identifying influencing factors about information distortion can care quality and patient safety be ensured.
Objective: This study aims to explore the factors influencing information distortion in electronic nursing records (ENRs) within the context of China's health care system and provide appropriate recommendations to address these distortions.
Methods: This qualitative study used semistructured interviews conducted with 14 nurses from a Class-A tertiary hospital. Participants were primarily asked about their experiences with and observations of information distortion in clinical practice, as well as potential influencing factors and corresponding countermeasures. Data were analyzed using inductive content analysis, which involved initial preparation, line-by-line coding, the creation of categories, and abstraction.
Results: The analysis identified 4 categories and 10 subcategories: (1) nurse-related factors-skills, awareness, and work habits; (2) patient-related factors-willingness and ability; (3) operational factors-work characteristics and system deficiencies; and (4) organizational factors-management system, organizational climate, and team collaboration.
Conclusions: Although some factors influencing information distortion in ENRs are similar to those observed in paper-based records, others are unique to the digital age. As health care continues to embrace digitalization, it is crucial to develop and implement strategies to mitigate information distortion. Regular training and education programs, robust systems and mechanisms, and optimized human resources and organizational practices are strongly recommended.
{"title":"Factors Influencing Information Distortion in Electronic Nursing Records: Qualitative Study.","authors":"Jianan Wang, Yihong Xu, Zhichao Yang, Jie Zhang, Xiaoxiao Zhang, Wen Li, Yushu Sun, Hongying Pan","doi":"10.2196/66959","DOIUrl":"https://doi.org/10.2196/66959","url":null,"abstract":"<p><strong>Background: </strong>Information distortion in nursing records poses significant risks to patient safety and impedes the enhancement of care quality. The introduction of information technologies, such as decision support systems and predictive models, expands the possibilities for using health data but also complicates the landscape of information distortion. Only by identifying influencing factors about information distortion can care quality and patient safety be ensured.</p><p><strong>Objective: </strong>This study aims to explore the factors influencing information distortion in electronic nursing records (ENRs) within the context of China's health care system and provide appropriate recommendations to address these distortions.</p><p><strong>Methods: </strong>This qualitative study used semistructured interviews conducted with 14 nurses from a Class-A tertiary hospital. Participants were primarily asked about their experiences with and observations of information distortion in clinical practice, as well as potential influencing factors and corresponding countermeasures. Data were analyzed using inductive content analysis, which involved initial preparation, line-by-line coding, the creation of categories, and abstraction.</p><p><strong>Results: </strong>The analysis identified 4 categories and 10 subcategories: (1) nurse-related factors-skills, awareness, and work habits; (2) patient-related factors-willingness and ability; (3) operational factors-work characteristics and system deficiencies; and (4) organizational factors-management system, organizational climate, and team collaboration.</p><p><strong>Conclusions: </strong>Although some factors influencing information distortion in ENRs are similar to those observed in paper-based records, others are unique to the digital age. As health care continues to embrace digitalization, it is crucial to develop and implement strategies to mitigate information distortion. Regular training and education programs, robust systems and mechanisms, and optimized human resources and organizational practices are strongly recommended.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e66959"},"PeriodicalIF":5.8,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143811650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Minseo Cho, Doeun Park, Myounglee Choo, Doug Hyun Han, Jinwoo Kim
<p><strong>Background: </strong>Self-recording is an effective behavior change technology that has long been used in diverse health contexts. Recent technological advancements have broadened its applications. While previous studies have explored its role and benefits in enhancing self-awareness and informed decision-making, relatively little attention has been given to its potential to address the multidimensional nature of health with various health metrics.</p><p><strong>Objective: </strong>This study investigates the process of self-recording in adolescent health, recognizing the connections between lifestyle behaviors and mental health. Specifically, we aim to incorporate both behavioral and emotional health metrics into the self-recording process. Grounded in self-regulation theory, we explore how adolescents record lifestyle behaviors and emotions, and how they inform and implement health management strategies.</p><p><strong>Methods: </strong>We conducted a qualitative study using the grounded theory methodology. Data were collected through individual semistructured interviews with 17 adolescents, who recorded their emotions and behaviors over 4 weeks using a prototype application. Analysis followed iterative phases of coding, constant comparison, and theme saturation. This process revealed how adolescents engage in self-recording for behaviors and emotions, as well as their failures and potential system support strategies. We further examined the relevance of the identified themes to theoretical constructs in self-regulation theory.</p><p><strong>Results: </strong>Under self-regulation theory, we gained insights into how adolescents manage their health through self-recording. The findings suggested variability in the self-recording process, in relation to specific health metrics of lifestyle behaviors and emotions. Adolescents focused on evaluating behaviors for management purposes while exploring the causes underlying emotional experiences. Throughout the health management, which involved modifying behavior or distancing from triggering factors, they monitored progress and outcomes, demonstrating a self-experimental approach. Uncertainty emerged as a barrier throughout the self-regulation process, suggesting that self-recording systems for adolescents should prioritize strategies to address these uncertainties. In addition, the self-recording system demonstrated interventional effects in aiding future planning and fostering a sense of relatedness among users.</p><p><strong>Conclusions: </strong>This study offers a theoretical framework for adolescents' self-recording process on diverse health metrics. By integrating self-regulation theory, we suggest a stepwise process from recording lifestyle behaviors and emotions to health management behaviors. Through exploring potential features and health-supportive effects, our findings contribute to the development of digital self-recording systems that address various health metrics in adolescent
{"title":"Adolescent Self-Reflection Process Through Self-Recording on Multiple Health Metrics: Qualitative Study.","authors":"Minseo Cho, Doeun Park, Myounglee Choo, Doug Hyun Han, Jinwoo Kim","doi":"10.2196/62962","DOIUrl":"https://doi.org/10.2196/62962","url":null,"abstract":"<p><strong>Background: </strong>Self-recording is an effective behavior change technology that has long been used in diverse health contexts. Recent technological advancements have broadened its applications. While previous studies have explored its role and benefits in enhancing self-awareness and informed decision-making, relatively little attention has been given to its potential to address the multidimensional nature of health with various health metrics.</p><p><strong>Objective: </strong>This study investigates the process of self-recording in adolescent health, recognizing the connections between lifestyle behaviors and mental health. Specifically, we aim to incorporate both behavioral and emotional health metrics into the self-recording process. Grounded in self-regulation theory, we explore how adolescents record lifestyle behaviors and emotions, and how they inform and implement health management strategies.</p><p><strong>Methods: </strong>We conducted a qualitative study using the grounded theory methodology. Data were collected through individual semistructured interviews with 17 adolescents, who recorded their emotions and behaviors over 4 weeks using a prototype application. Analysis followed iterative phases of coding, constant comparison, and theme saturation. This process revealed how adolescents engage in self-recording for behaviors and emotions, as well as their failures and potential system support strategies. We further examined the relevance of the identified themes to theoretical constructs in self-regulation theory.</p><p><strong>Results: </strong>Under self-regulation theory, we gained insights into how adolescents manage their health through self-recording. The findings suggested variability in the self-recording process, in relation to specific health metrics of lifestyle behaviors and emotions. Adolescents focused on evaluating behaviors for management purposes while exploring the causes underlying emotional experiences. Throughout the health management, which involved modifying behavior or distancing from triggering factors, they monitored progress and outcomes, demonstrating a self-experimental approach. Uncertainty emerged as a barrier throughout the self-regulation process, suggesting that self-recording systems for adolescents should prioritize strategies to address these uncertainties. In addition, the self-recording system demonstrated interventional effects in aiding future planning and fostering a sense of relatedness among users.</p><p><strong>Conclusions: </strong>This study offers a theoretical framework for adolescents' self-recording process on diverse health metrics. By integrating self-regulation theory, we suggest a stepwise process from recording lifestyle behaviors and emotions to health management behaviors. Through exploring potential features and health-supportive effects, our findings contribute to the development of digital self-recording systems that address various health metrics in adolescent","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e62962"},"PeriodicalIF":5.8,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143811570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jun Jie Benjamin Seng, Hosea Nyanavoli, Glenn Moses Decruz, Yu Heng Kwan, Lian Leng Low
<p><strong>Background: </strong>Health coaching refers to the practice of health education and promotion to drive goal-directed behavioral changes and improve an individual's well-being. Remote patient monitoring systems, which employ health coaching interventions, have been gaining interest and may aid in the management of patients with type 2 diabetes mellitus (T2DM).</p><p><strong>Objective: </strong>This scoping review aims to summarize the impact of health coaching in the remote monitoring of patients with T2DM.</p><p><strong>Methods: </strong>A scoping review was performed in MEDLINE, Embase, CINAHL, PsychInfo, and Web of Science up to September 2024 and was reported using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. The initial abstract screening, full-text review, and data extraction were performed by 2 independent reviewers. Studies that evaluated the impact of health coaching on the remote management of patients with T2DM were included. Outcomes evaluated were grouped into clinical, humanistic, psychiatric, behavioral, knowledge, and economic domains. A narrative review was performed for the impact of health coaching on the remote management of patients with T2DM.</p><p><strong>Results: </strong>Among 168,888 citations identified, 104 studies were included. Majority of the studies were conducted in North America (56/104, 53.8%) and Asia (30/104, 28.8%). Approximately half of the studies (48/104, 46.2%) were conducted in primary health care settings, and one-third of the studies (37/104, 35.6%) employed nurses as health coaches. Phone consultations were the most common modality of remote monitoring (45/104, 43.3%). The follow-up duration of most studies (64/104, 61.5%) was less than 1 year. Regarding clinical outcomes, majority of the studies (68/92, 73%) showed improvements in diabetes-related parameters, but there was no improvement in blood pressure (21/32, 66%) or hyperlipidemia control (19/32, 59%). For humanistic outcomes, health coaching was associated with higher satisfaction with diabetes-related care (10/11, 91%), but there was no improvement in quality of life (12/20, 60%). Regarding psychiatric outcomes, there was no association with improvement in depressive (8/14, 57%) or anxiety symptoms (4/5, 80%). For behavioral outcomes, most studies (12/19, 63%) showed improvement in diabetes-related self-efficacy. For knowledge outcomes, evidence was mixed, with half of the studies (5/9, 56%) showing improvement in diabetes-related knowledge. For economic outcomes, majority of the studies (8/11, 73%) did not show a reduction in health care use.</p><p><strong>Conclusions: </strong>Health coaching was associated with improved diabetes control and self-management among patients with T2DM on remote monitoring. Its role appears limited in improving health care use, lipid parameters, and quality of life; however, this may have been confounded by the short durati
{"title":"Health Coaching and Its Impact in the Remote Management of Patients With Type 2 Diabetes Mellitus: Scoping Review of the Literature.","authors":"Jun Jie Benjamin Seng, Hosea Nyanavoli, Glenn Moses Decruz, Yu Heng Kwan, Lian Leng Low","doi":"10.2196/60703","DOIUrl":"https://doi.org/10.2196/60703","url":null,"abstract":"<p><strong>Background: </strong>Health coaching refers to the practice of health education and promotion to drive goal-directed behavioral changes and improve an individual's well-being. Remote patient monitoring systems, which employ health coaching interventions, have been gaining interest and may aid in the management of patients with type 2 diabetes mellitus (T2DM).</p><p><strong>Objective: </strong>This scoping review aims to summarize the impact of health coaching in the remote monitoring of patients with T2DM.</p><p><strong>Methods: </strong>A scoping review was performed in MEDLINE, Embase, CINAHL, PsychInfo, and Web of Science up to September 2024 and was reported using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. The initial abstract screening, full-text review, and data extraction were performed by 2 independent reviewers. Studies that evaluated the impact of health coaching on the remote management of patients with T2DM were included. Outcomes evaluated were grouped into clinical, humanistic, psychiatric, behavioral, knowledge, and economic domains. A narrative review was performed for the impact of health coaching on the remote management of patients with T2DM.</p><p><strong>Results: </strong>Among 168,888 citations identified, 104 studies were included. Majority of the studies were conducted in North America (56/104, 53.8%) and Asia (30/104, 28.8%). Approximately half of the studies (48/104, 46.2%) were conducted in primary health care settings, and one-third of the studies (37/104, 35.6%) employed nurses as health coaches. Phone consultations were the most common modality of remote monitoring (45/104, 43.3%). The follow-up duration of most studies (64/104, 61.5%) was less than 1 year. Regarding clinical outcomes, majority of the studies (68/92, 73%) showed improvements in diabetes-related parameters, but there was no improvement in blood pressure (21/32, 66%) or hyperlipidemia control (19/32, 59%). For humanistic outcomes, health coaching was associated with higher satisfaction with diabetes-related care (10/11, 91%), but there was no improvement in quality of life (12/20, 60%). Regarding psychiatric outcomes, there was no association with improvement in depressive (8/14, 57%) or anxiety symptoms (4/5, 80%). For behavioral outcomes, most studies (12/19, 63%) showed improvement in diabetes-related self-efficacy. For knowledge outcomes, evidence was mixed, with half of the studies (5/9, 56%) showing improvement in diabetes-related knowledge. For economic outcomes, majority of the studies (8/11, 73%) did not show a reduction in health care use.</p><p><strong>Conclusions: </strong>Health coaching was associated with improved diabetes control and self-management among patients with T2DM on remote monitoring. Its role appears limited in improving health care use, lipid parameters, and quality of life; however, this may have been confounded by the short durati","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e60703"},"PeriodicalIF":5.8,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143811657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Atiya Avery, Elizabeth White Baker, Brittany Wright, Ishmael Avery, Dream Gomez
<p><strong>Background: </strong>Ransomware attacks on health care provider information systems have the potential to impact patient mortality and morbidity, and event details are relayed publicly through news stories. Despite this, little research exists on how these events are depicted in the media and the subsequent impacts of these events.</p><p><strong>Objective: </strong>This study used collaborative qualitative analysis to understand how news media frames and portrays the impacts of ransomware attacks on health informatic systems, employees, and patients.</p><p><strong>Methods: </strong>We developed and implemented a systematic search protocol across academic news databases, which included (1) the Associated Press Newswires, (2) Newspaper Source, and (3) Access World News (Newsbank), using the search string "(hospital OR healthcare OR clinic OR medical) AND (ransomware OR denial of service OR cybersecurity)." In total, 4 inclusion and 4 exclusion criteria were applied as part of the search protocol. For articles included in the study, we performed an inductive and deductive analysis of the news articles, which included their article characteristics, impact portrayals, media framings, and discussions of the core functions outlined in the National Institute of Standards and Technologies (NIST) Cybersecurity Framework 2.0.</p><p><strong>Results: </strong>The search returned 2195 articles, among which 48 news articles published from 2009 to 2023 were included in the study. First, an analysis of the geographic prevalence showed that the United States (34/48, 71%), followed to a lesser extent by India (4/48, 8%) and Canada (3/48, 6%), featured more prominently in our sample. Second, there were no apparent year-to-year patterns in the occurrence of reported events of ransomware attacks on health care provider information systems. Third, ransomware attacks on health care provider information systems appeared to cascade from a single point of failure. Fourth, media frames regarding "human interest" and "responsibility" were equally representative in the sample. The "response" function of the NIST Cybersecurity Framework 2.0 was noted in 36 of the 48 (75%) articles. Finally, we noted that 17 (14%) of the articles assessed for eligibility were excluded from this study as they promoted a product or service or spoke hypothetically about ransomware events among health care providers.</p><p><strong>Conclusions: </strong>Organizational response represented a substantial aspect of the news articles in our corpus. To address the perception of health care providers' management of ransomware attacks, they should take measures to influence perceptions of (1) health care service continuity, despite a lack of availability of health informatics; (2) responsibility for the patient experience; and (3) acknowledgment of the strain on health care practitioners and patients through a public declaration of support and gratitude. Furthermore, the media portrayals reveale
{"title":"Media Framing and Portrayals of Ransomware Impacts on Informatics, Employees, and Patients: Systematic Media Literature Review.","authors":"Atiya Avery, Elizabeth White Baker, Brittany Wright, Ishmael Avery, Dream Gomez","doi":"10.2196/59231","DOIUrl":"https://doi.org/10.2196/59231","url":null,"abstract":"<p><strong>Background: </strong>Ransomware attacks on health care provider information systems have the potential to impact patient mortality and morbidity, and event details are relayed publicly through news stories. Despite this, little research exists on how these events are depicted in the media and the subsequent impacts of these events.</p><p><strong>Objective: </strong>This study used collaborative qualitative analysis to understand how news media frames and portrays the impacts of ransomware attacks on health informatic systems, employees, and patients.</p><p><strong>Methods: </strong>We developed and implemented a systematic search protocol across academic news databases, which included (1) the Associated Press Newswires, (2) Newspaper Source, and (3) Access World News (Newsbank), using the search string \"(hospital OR healthcare OR clinic OR medical) AND (ransomware OR denial of service OR cybersecurity).\" In total, 4 inclusion and 4 exclusion criteria were applied as part of the search protocol. For articles included in the study, we performed an inductive and deductive analysis of the news articles, which included their article characteristics, impact portrayals, media framings, and discussions of the core functions outlined in the National Institute of Standards and Technologies (NIST) Cybersecurity Framework 2.0.</p><p><strong>Results: </strong>The search returned 2195 articles, among which 48 news articles published from 2009 to 2023 were included in the study. First, an analysis of the geographic prevalence showed that the United States (34/48, 71%), followed to a lesser extent by India (4/48, 8%) and Canada (3/48, 6%), featured more prominently in our sample. Second, there were no apparent year-to-year patterns in the occurrence of reported events of ransomware attacks on health care provider information systems. Third, ransomware attacks on health care provider information systems appeared to cascade from a single point of failure. Fourth, media frames regarding \"human interest\" and \"responsibility\" were equally representative in the sample. The \"response\" function of the NIST Cybersecurity Framework 2.0 was noted in 36 of the 48 (75%) articles. Finally, we noted that 17 (14%) of the articles assessed for eligibility were excluded from this study as they promoted a product or service or spoke hypothetically about ransomware events among health care providers.</p><p><strong>Conclusions: </strong>Organizational response represented a substantial aspect of the news articles in our corpus. To address the perception of health care providers' management of ransomware attacks, they should take measures to influence perceptions of (1) health care service continuity, despite a lack of availability of health informatics; (2) responsibility for the patient experience; and (3) acknowledgment of the strain on health care practitioners and patients through a public declaration of support and gratitude. Furthermore, the media portrayals reveale","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e59231"},"PeriodicalIF":5.8,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143811663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Artificial intelligence (AI) has potential in promoting and supporting self-management in patients with chronic conditions. However, the development and application of current AI technologies to meet patients' needs and improve their performance in chronic condition self-management tasks remain poorly understood. It is crucial to gather comprehensive information to guide the development and selection of effective AI solutions tailored for self-management in patients with chronic conditions.
Objective: This scoping review aimed to provide a comprehensive overview of AI applications for chronic condition self-management based on 3 essential self-management tasks, medical, behavioral, and emotional self-management, and to identify the current developmental stages and knowledge gaps of AI applications for chronic condition self-management.
Methods: A literature review was conducted for studies published in English between January 2011 and October 2024. In total, 4 databases, including PubMed, Web of Science, CINAHL, and PsycINFO, were searched using combined terms related to self-management and AI. The inclusion criteria included studies focused on the adult population with any type of chronic condition and AI technologies supporting self-management. This review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines.
Results: Of the 1873 articles retrieved from the search, 66 (3.5%) were eligible and included in this review. The most studied chronic condition was diabetes (20/66, 30%). Regarding self-management tasks, most studies aimed to support medical (45/66, 68%) or behavioral self-management (27/66, 41%), and fewer studies focused on emotional self-management (14/66, 21%). Conversational AI (21/66, 32%) and multiple machine learning algorithms (16/66, 24%) were the most used AI technologies. However, most AI technologies remained in the algorithm development (25/66, 38%) or early feasibility testing stages (25/66, 38%).
Conclusions: A variety of AI technologies have been developed and applied in chronic condition self-management, primarily for medication, symptoms, and lifestyle self-management. Fewer AI technologies were developed for emotional self-management tasks, and most AIs remained in the early developmental stages. More research is needed to generate evidence for integrating AI into chronic condition self-management to obtain optimal health outcomes.
{"title":"AI Applications for Chronic Condition Self-Management: Scoping Review.","authors":"Misun Hwang, Yaguang Zheng, Youmin Cho, Yun Jiang","doi":"10.2196/59632","DOIUrl":"10.2196/59632","url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI) has potential in promoting and supporting self-management in patients with chronic conditions. However, the development and application of current AI technologies to meet patients' needs and improve their performance in chronic condition self-management tasks remain poorly understood. It is crucial to gather comprehensive information to guide the development and selection of effective AI solutions tailored for self-management in patients with chronic conditions.</p><p><strong>Objective: </strong>This scoping review aimed to provide a comprehensive overview of AI applications for chronic condition self-management based on 3 essential self-management tasks, medical, behavioral, and emotional self-management, and to identify the current developmental stages and knowledge gaps of AI applications for chronic condition self-management.</p><p><strong>Methods: </strong>A literature review was conducted for studies published in English between January 2011 and October 2024. In total, 4 databases, including PubMed, Web of Science, CINAHL, and PsycINFO, were searched using combined terms related to self-management and AI. The inclusion criteria included studies focused on the adult population with any type of chronic condition and AI technologies supporting self-management. This review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines.</p><p><strong>Results: </strong>Of the 1873 articles retrieved from the search, 66 (3.5%) were eligible and included in this review. The most studied chronic condition was diabetes (20/66, 30%). Regarding self-management tasks, most studies aimed to support medical (45/66, 68%) or behavioral self-management (27/66, 41%), and fewer studies focused on emotional self-management (14/66, 21%). Conversational AI (21/66, 32%) and multiple machine learning algorithms (16/66, 24%) were the most used AI technologies. However, most AI technologies remained in the algorithm development (25/66, 38%) or early feasibility testing stages (25/66, 38%).</p><p><strong>Conclusions: </strong>A variety of AI technologies have been developed and applied in chronic condition self-management, primarily for medication, symptoms, and lifestyle self-management. Fewer AI technologies were developed for emotional self-management tasks, and most AIs remained in the early developmental stages. More research is needed to generate evidence for integrating AI into chronic condition self-management to obtain optimal health outcomes.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e59632"},"PeriodicalIF":5.8,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143803417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yudi Jin, Min Zhao, Tong Su, Yanjia Fan, Zubin Ouyang, Fajin Lv
<p><strong>Background: </strong>Breast cancer is one of the most common malignancies among women worldwide. Patients who do not achieve a pathological complete response (pCR) or a clinical complete response (cCR) post-neoadjuvant chemotherapy (NAC) typically have a worse prognosis compared to those who do achieve these responses.</p><p><strong>Objective: </strong>This study aimed to develop and validate a random survival forest (RSF) model to predict survival risk in patients with breast cancer who do not achieve a pCR or cCR post-NAC.</p><p><strong>Methods: </strong>We analyzed patients with no pCR/cCR post-NAC treated at the First Affiliated Hospital of Chongqing Medical University from January 2019 to 2023, with external validation in Duke University and Surveillance, Epidemiology, and End Results (SEER) cohorts. RSF and Cox regression models were compared using the time-dependent area under the curve (AUC), the concordance index (C-index), and risk stratification.</p><p><strong>Results: </strong>The study cohort included 306 patients with breast cancer, with most aged 40-60 years (204/306, 66.7%). The majority had invasive ductal carcinoma (290/306, 94.8%), with estrogen receptor (ER)+ (182/306, 59.5%), progesterone receptor (PR)- (179/306, 58.5%), and human epidermal growth factor receptor 2 (HER2)+ (94/306, 30.7%) profiles. Most patients presented with T2 (185/306, 60.5%), N1 (142/306, 46.4%), and M0 (295/306, 96.4%) staging (TNM meaning "tumor, node, metastasis"), with 17.6% (54/306) experiencing disease progression during a median follow-up of 25.9 months (IQR 17.2-36.3). External validation using Duke (N=94) and SEER (N=2760) cohorts confirmed consistent patterns in age (40-60 years: 59/94, 63%, vs 1480/2760, 53.6%), HER2+ rates (26/94, 28%, vs 935/2760, 33.9%), and invasive ductal carcinoma prevalence (89/94, 95%, vs 2506/2760, 90.8%). In the internal cohort, the RSF achieved significantly higher time-dependent AUCs compared to Cox regression at 1-year (0.811 vs 0.763), 3-year (0.834 vs 0.783), and 5-year (0.810 vs 0.771) intervals (overall C-index: 0.803, 95% CI 0.747-0.859, vs 0.736, 95% CI 0.673-0.799). External validation confirmed robust generalizability: the Duke cohort showed 1-, 3-, and 5-year AUCs of 0.912, 0.803, and 0.776, respectively, while the SEER cohort maintained consistent performance with AUCs of 0.771, 0.729, and 0.702, respectively. Risk stratification using the RSF identified 25.8% (79/306) high-risk patients and a significantly reduced survival time (P<.001). Notably, the RSF maintained improved net benefits across decision thresholds in decision curve analysis (DCA); similar results were observed in external studies. The RSF model also showed promising performance across different molecular subtypes in all datasets. Based on the RSF predicted scores, patients were stratified into high- and low-risk groups, with notably poorer survival outcomes observed in the high-risk group compared to the low-risk group.</p><p>
{"title":"Comparing Random Survival Forests and Cox Regression for Nonresponders to Neoadjuvant Chemotherapy Among Patients With Breast Cancer: Multicenter Retrospective Cohort Study.","authors":"Yudi Jin, Min Zhao, Tong Su, Yanjia Fan, Zubin Ouyang, Fajin Lv","doi":"10.2196/69864","DOIUrl":"https://doi.org/10.2196/69864","url":null,"abstract":"<p><strong>Background: </strong>Breast cancer is one of the most common malignancies among women worldwide. Patients who do not achieve a pathological complete response (pCR) or a clinical complete response (cCR) post-neoadjuvant chemotherapy (NAC) typically have a worse prognosis compared to those who do achieve these responses.</p><p><strong>Objective: </strong>This study aimed to develop and validate a random survival forest (RSF) model to predict survival risk in patients with breast cancer who do not achieve a pCR or cCR post-NAC.</p><p><strong>Methods: </strong>We analyzed patients with no pCR/cCR post-NAC treated at the First Affiliated Hospital of Chongqing Medical University from January 2019 to 2023, with external validation in Duke University and Surveillance, Epidemiology, and End Results (SEER) cohorts. RSF and Cox regression models were compared using the time-dependent area under the curve (AUC), the concordance index (C-index), and risk stratification.</p><p><strong>Results: </strong>The study cohort included 306 patients with breast cancer, with most aged 40-60 years (204/306, 66.7%). The majority had invasive ductal carcinoma (290/306, 94.8%), with estrogen receptor (ER)+ (182/306, 59.5%), progesterone receptor (PR)- (179/306, 58.5%), and human epidermal growth factor receptor 2 (HER2)+ (94/306, 30.7%) profiles. Most patients presented with T2 (185/306, 60.5%), N1 (142/306, 46.4%), and M0 (295/306, 96.4%) staging (TNM meaning \"tumor, node, metastasis\"), with 17.6% (54/306) experiencing disease progression during a median follow-up of 25.9 months (IQR 17.2-36.3). External validation using Duke (N=94) and SEER (N=2760) cohorts confirmed consistent patterns in age (40-60 years: 59/94, 63%, vs 1480/2760, 53.6%), HER2+ rates (26/94, 28%, vs 935/2760, 33.9%), and invasive ductal carcinoma prevalence (89/94, 95%, vs 2506/2760, 90.8%). In the internal cohort, the RSF achieved significantly higher time-dependent AUCs compared to Cox regression at 1-year (0.811 vs 0.763), 3-year (0.834 vs 0.783), and 5-year (0.810 vs 0.771) intervals (overall C-index: 0.803, 95% CI 0.747-0.859, vs 0.736, 95% CI 0.673-0.799). External validation confirmed robust generalizability: the Duke cohort showed 1-, 3-, and 5-year AUCs of 0.912, 0.803, and 0.776, respectively, while the SEER cohort maintained consistent performance with AUCs of 0.771, 0.729, and 0.702, respectively. Risk stratification using the RSF identified 25.8% (79/306) high-risk patients and a significantly reduced survival time (P<.001). Notably, the RSF maintained improved net benefits across decision thresholds in decision curve analysis (DCA); similar results were observed in external studies. The RSF model also showed promising performance across different molecular subtypes in all datasets. Based on the RSF predicted scores, patients were stratified into high- and low-risk groups, with notably poorer survival outcomes observed in the high-risk group compared to the low-risk group.</p><p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e69864"},"PeriodicalIF":5.8,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143811636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Charlotte Brun Thorup, Mika Uitto, Kerryn Butler-Henderson, Sarah Wamala-Andersson, Merja Hoffrén-Mikkola, Diana Schack Thoft, Lisa Korsbakke Emtekær Hæsum, Gabriela Irrazabal, Laura Pruneda González, Katja Valkama
<p><strong>Background: </strong>The global demographic shift towards longer life expectancy and complex health needs is increasing the number of people with chronic diseases, placing pressure on health and care systems. With the digitalization of healthcare, digital Health Literacy (dHL), or the use of digital skills in health, is gaining importance. It involves navigating digital health information, using digital tools effectively, and making informed health decisions. Measuring dHL can help identify gaps and develop strategies to improve dHL and health, ensuring citizens equal opportunity to participate in a digital healthcare system. The European project "The Improving Digital Empowerment for Active and Healthy Living (IDEAHL)" with the objective to empower European Union citizens to use digital instruments to take a more active role in managing their health and well-being creates the base for this overview.</p><p><strong>Objective: </strong>This paper aims to conduct an overview of existing assessment tools for measuring dHL and recommend strategies for choosing relevant assessment tools.</p><p><strong>Methods: </strong>This study was carried out as a mixed method study initiated by a scoping review (10 scientific databases, 14 databases with grey literature and 14 predefined reports) in addition to three papers published after finalisations the literature search in IDEAHL, followed by a qualitative workshop study and a final analysis combining results.</p><p><strong>Results: </strong>The literature search resulted in 33 papers on dHL instruments, that was analyzed together with three recently published reviews and findings from a workshop with 13 champions (understood as professionals with expertise in HL and dHL) from five countries (Spain, Denmark, Sweden, Australia, and Germany) representing the health sector or health literacy research. Future tools should adapt to the latest trends and technologies, considering attitudes towards digital health and trust in its services. They should identify beneficiaries of digital health services, measure the impact of dHL interventions, and objectively evaluate functional skills. These tools should be evidence-based, validate instruments, interpret dHL results, and capture diverse experiences to reveal health behaviour changes.</p><p><strong>Conclusions: </strong>The eHealth Literacy Scale (eHEALS), despite being the most frequently utilized tool, has limitations in scope and adaptability. Future tools need to reflect digital trends, encompassing individual skills. However, it is important to note that the 'adequacy' of dHL is context-specific and relies on healthcare systems and the technology provided, particularly the user interface. The focus should be on health improvement, not just elevating dHL levels. A comprehensive approach to dHL assessments addressing diversity and relevance is crucial. Ethical considerations in dHL, including privacy and data security, are important due to potential feeli
{"title":"Choosing the Best Digital Health Literacy Measure for Research: Mixed Methods Study.","authors":"Charlotte Brun Thorup, Mika Uitto, Kerryn Butler-Henderson, Sarah Wamala-Andersson, Merja Hoffrén-Mikkola, Diana Schack Thoft, Lisa Korsbakke Emtekær Hæsum, Gabriela Irrazabal, Laura Pruneda González, Katja Valkama","doi":"10.2196/59807","DOIUrl":"10.2196/59807","url":null,"abstract":"<p><strong>Background: </strong>The global demographic shift towards longer life expectancy and complex health needs is increasing the number of people with chronic diseases, placing pressure on health and care systems. With the digitalization of healthcare, digital Health Literacy (dHL), or the use of digital skills in health, is gaining importance. It involves navigating digital health information, using digital tools effectively, and making informed health decisions. Measuring dHL can help identify gaps and develop strategies to improve dHL and health, ensuring citizens equal opportunity to participate in a digital healthcare system. The European project \"The Improving Digital Empowerment for Active and Healthy Living (IDEAHL)\" with the objective to empower European Union citizens to use digital instruments to take a more active role in managing their health and well-being creates the base for this overview.</p><p><strong>Objective: </strong>This paper aims to conduct an overview of existing assessment tools for measuring dHL and recommend strategies for choosing relevant assessment tools.</p><p><strong>Methods: </strong>This study was carried out as a mixed method study initiated by a scoping review (10 scientific databases, 14 databases with grey literature and 14 predefined reports) in addition to three papers published after finalisations the literature search in IDEAHL, followed by a qualitative workshop study and a final analysis combining results.</p><p><strong>Results: </strong>The literature search resulted in 33 papers on dHL instruments, that was analyzed together with three recently published reviews and findings from a workshop with 13 champions (understood as professionals with expertise in HL and dHL) from five countries (Spain, Denmark, Sweden, Australia, and Germany) representing the health sector or health literacy research. Future tools should adapt to the latest trends and technologies, considering attitudes towards digital health and trust in its services. They should identify beneficiaries of digital health services, measure the impact of dHL interventions, and objectively evaluate functional skills. These tools should be evidence-based, validate instruments, interpret dHL results, and capture diverse experiences to reveal health behaviour changes.</p><p><strong>Conclusions: </strong>The eHealth Literacy Scale (eHEALS), despite being the most frequently utilized tool, has limitations in scope and adaptability. Future tools need to reflect digital trends, encompassing individual skills. However, it is important to note that the 'adequacy' of dHL is context-specific and relies on healthcare systems and the technology provided, particularly the user interface. The focus should be on health improvement, not just elevating dHL levels. A comprehensive approach to dHL assessments addressing diversity and relevance is crucial. Ethical considerations in dHL, including privacy and data security, are important due to potential feeli","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e59807"},"PeriodicalIF":5.8,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143803349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p><strong>Background: </strong>An estimated 93% of adults in the United States access the internet, with up to 80% looking for health information. However, only 12% of US adults are proficient enough in health literacy to interpret health information and make informed health care decisions meaningfully. With the vast amount of health information available in multimedia formats on social media platforms such as YouTube and Facebook, there is an urgent need and a unique opportunity to design an automated approach to curate online health information using multiple criteria to meet the health literacy needs of a diverse population.</p><p><strong>Objective: </strong>This study aimed to develop an automated approach to assessing the understandability of patient educational videos according to the Patient Education Materials Assessment Tool (PEMAT) guidelines and evaluating the impact of video understandability on viewer engagement. We also offer insights for content creators and health care organizations on how to improve engagement with these educational videos on user-generated content platforms.</p><p><strong>Methods: </strong>We developed a human-in-the-loop, augmented intelligence approach that explicitly focused on the human-algorithm interaction, combining PEMAT-based patient education constructs mapped to features extracted from the videos, annotations of the videos by domain experts, and cotraining methods from machine learning to assess the understandability of videos on diabetes and classify them. We further examined the impact of understandability on several dimensions of viewer engagement with the videos.</p><p><strong>Results: </strong>We collected 9873 YouTube videos on diabetes using search keywords extracted from a patient-oriented forum and reviewed by a medical expert. Our machine learning methods achieved a weighted precision of 0.84, a weighted recall of 0.79, and an F<sub>1</sub>-score of 0.81 in classifying video understandability and could effectively identify patient educational videos that medical experts would like to recommend for patients. Videos rated as highly understandable had an average higher view count (average treatment effect [ATE]=2.55; P<.001), like count (ATE=2.95; P<.001), and comment count (ATE=3.10; P<.001) than less understandable videos. In addition, in a user study, 4 medical experts recommended 72% (144/200) of the top 10 videos ranked by understandability compared to 40% (80/200) of the top 10 videos ranked by YouTube's default algorithm for 20 ramdomly selected search keywords.</p><p><strong>Conclusions: </strong>We developed a human-in-the-loop, scalable algorithm to assess the understandability of health information on YouTube. Our method optimally combines expert input with algorithmic support, enhancing engagement and aiding medical experts in recommending educational content. This solution also guides health care organizations in creating effective patient education materials for underserved healt
{"title":"Promoting Health Literacy With Human-in-the-Loop Video Understandability Classification of YouTube Videos: Development and Evaluation Study.","authors":"Xiao Liu, Anjana Susarla, Rema Padman","doi":"10.2196/56080","DOIUrl":"https://doi.org/10.2196/56080","url":null,"abstract":"<p><strong>Background: </strong>An estimated 93% of adults in the United States access the internet, with up to 80% looking for health information. However, only 12% of US adults are proficient enough in health literacy to interpret health information and make informed health care decisions meaningfully. With the vast amount of health information available in multimedia formats on social media platforms such as YouTube and Facebook, there is an urgent need and a unique opportunity to design an automated approach to curate online health information using multiple criteria to meet the health literacy needs of a diverse population.</p><p><strong>Objective: </strong>This study aimed to develop an automated approach to assessing the understandability of patient educational videos according to the Patient Education Materials Assessment Tool (PEMAT) guidelines and evaluating the impact of video understandability on viewer engagement. We also offer insights for content creators and health care organizations on how to improve engagement with these educational videos on user-generated content platforms.</p><p><strong>Methods: </strong>We developed a human-in-the-loop, augmented intelligence approach that explicitly focused on the human-algorithm interaction, combining PEMAT-based patient education constructs mapped to features extracted from the videos, annotations of the videos by domain experts, and cotraining methods from machine learning to assess the understandability of videos on diabetes and classify them. We further examined the impact of understandability on several dimensions of viewer engagement with the videos.</p><p><strong>Results: </strong>We collected 9873 YouTube videos on diabetes using search keywords extracted from a patient-oriented forum and reviewed by a medical expert. Our machine learning methods achieved a weighted precision of 0.84, a weighted recall of 0.79, and an F<sub>1</sub>-score of 0.81 in classifying video understandability and could effectively identify patient educational videos that medical experts would like to recommend for patients. Videos rated as highly understandable had an average higher view count (average treatment effect [ATE]=2.55; P<.001), like count (ATE=2.95; P<.001), and comment count (ATE=3.10; P<.001) than less understandable videos. In addition, in a user study, 4 medical experts recommended 72% (144/200) of the top 10 videos ranked by understandability compared to 40% (80/200) of the top 10 videos ranked by YouTube's default algorithm for 20 ramdomly selected search keywords.</p><p><strong>Conclusions: </strong>We developed a human-in-the-loop, scalable algorithm to assess the understandability of health information on YouTube. Our method optimally combines expert input with algorithmic support, enhancing engagement and aiding medical experts in recommending educational content. This solution also guides health care organizations in creating effective patient education materials for underserved healt","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e56080"},"PeriodicalIF":5.8,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143811606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: The prevalence of mental health difficulties among young people has risen in recent years, with 75% of mental disorders emerging before the age of 24 years. The identification and treatment of mental health issues earlier in life improves later-life outcomes. The COVID-19 pandemic spurred the growth of digital mental health interventions (DMHIs), which offer accessible support. However, young people of different ethnicities face barriers to DMHIs, such as socioeconomic disadvantage and cultural stigma.
Objective: This review aimed to summarize and evaluate the engagement with and effectiveness of DMHIs among young people of different ethnicities.
Methods: A systematic search was conducted in MEDLINE, Embase, and PsycINFO for studies published between January 2019 and May 2024, with an update in September 2024. The inclusion criteria were participants aged <25 years using DMHIs from various ethnic backgrounds. Three reviewers independently screened and selected the studies. Data on engagement (eg, use and uptake) and effectiveness (eg, clinical outcomes and symptom improvement) were extracted and synthesized to compare findings. Studies were assessed for quality using the Mixed Methods Appraisal Tool.
Results: The final search yielded 67 studies, of which 7 (10%) met inclusion criteria. There were 1853 participants across the 7 studies, all from high-income countries. Participants were predominantly aged 12 to 25 years, with representation of diverse ethnic identities, including Black, Asian, Hispanic, mixed race, and Aboriginal individuals. Engagement outcomes varied, with culturally relatable, low-cost interventions showing higher retention and user satisfaction. Linguistic barriers and country of origin impeded the effectiveness of some interventions, while near-peer mentorship, coproduction, and tailored content improved the effectiveness of DMHIs. While initial results are promising, small sample sizes, heterogeneity in outcome assessments, and a paucity of longitudinal data impeded robust comparisons and generalizability.
Conclusions: DMHIs show potential as engaging and effective mental health promotional tools for young people of different ethnicities, especially when coproduced and culturally relatable. Initial data suggest that interventions facilitating near-peer mentoring, linguistic adaptation, low cost, and cultural relatability have improved engagement and effectiveness. Future research should focus on developing a consensus definition of DMHIs, exploring DMHIs in children aged <12 years, and conducting detailed qualitative and quantitative research on use factors and treatment efficacy of DMHIs for young people of different ethnicities.
{"title":"Exploring Engagement With and Effectiveness of Digital Mental Health Interventions in Young People of Different Ethnicities: Systematic Review.","authors":"Rinad Bakhti, Harmani Daler, Hephzibah Ogunro, Steven Hope, Dougal Hargreaves, Dasha Nicholls","doi":"10.2196/68544","DOIUrl":"https://doi.org/10.2196/68544","url":null,"abstract":"<p><strong>Background: </strong>The prevalence of mental health difficulties among young people has risen in recent years, with 75% of mental disorders emerging before the age of 24 years. The identification and treatment of mental health issues earlier in life improves later-life outcomes. The COVID-19 pandemic spurred the growth of digital mental health interventions (DMHIs), which offer accessible support. However, young people of different ethnicities face barriers to DMHIs, such as socioeconomic disadvantage and cultural stigma.</p><p><strong>Objective: </strong>This review aimed to summarize and evaluate the engagement with and effectiveness of DMHIs among young people of different ethnicities.</p><p><strong>Methods: </strong>A systematic search was conducted in MEDLINE, Embase, and PsycINFO for studies published between January 2019 and May 2024, with an update in September 2024. The inclusion criteria were participants aged <25 years using DMHIs from various ethnic backgrounds. Three reviewers independently screened and selected the studies. Data on engagement (eg, use and uptake) and effectiveness (eg, clinical outcomes and symptom improvement) were extracted and synthesized to compare findings. Studies were assessed for quality using the Mixed Methods Appraisal Tool.</p><p><strong>Results: </strong>The final search yielded 67 studies, of which 7 (10%) met inclusion criteria. There were 1853 participants across the 7 studies, all from high-income countries. Participants were predominantly aged 12 to 25 years, with representation of diverse ethnic identities, including Black, Asian, Hispanic, mixed race, and Aboriginal individuals. Engagement outcomes varied, with culturally relatable, low-cost interventions showing higher retention and user satisfaction. Linguistic barriers and country of origin impeded the effectiveness of some interventions, while near-peer mentorship, coproduction, and tailored content improved the effectiveness of DMHIs. While initial results are promising, small sample sizes, heterogeneity in outcome assessments, and a paucity of longitudinal data impeded robust comparisons and generalizability.</p><p><strong>Conclusions: </strong>DMHIs show potential as engaging and effective mental health promotional tools for young people of different ethnicities, especially when coproduced and culturally relatable. Initial data suggest that interventions facilitating near-peer mentoring, linguistic adaptation, low cost, and cultural relatability have improved engagement and effectiveness. Future research should focus on developing a consensus definition of DMHIs, exploring DMHIs in children aged <12 years, and conducting detailed qualitative and quantitative research on use factors and treatment efficacy of DMHIs for young people of different ethnicities.</p><p><strong>Trial registration: </strong>PROSPERO CRD42024544364; https://tinyurl.com/yk5jt8yk.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e68544"},"PeriodicalIF":5.8,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143803485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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