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Psychotherapists' Ethical Dilemmas Regarding Online and Face-to-Face Psychotherapy During the COVID-19 Pandemic: Survey Study. COVID-19大流行期间心理治疗师关于在线和面对面心理治疗的伦理困境:调查研究
IF 6 2区 医学
Journal of Medical Internet Research Pub Date : 2025-09-17 DOI: 10.2196/69154
Emilia Rutkowska, Joanna Furmańska, Cristiana C Marques, Maria João Martins, Håkan Lane, Johannes Meixner
{"title":"Psychotherapists' Ethical Dilemmas Regarding Online and Face-to-Face Psychotherapy During the COVID-19 Pandemic: Survey Study.","authors":"Emilia Rutkowska, Joanna Furmańska, Cristiana C Marques, Maria João Martins, Håkan Lane, Johannes Meixner","doi":"10.2196/69154","DOIUrl":"10.2196/69154","url":null,"abstract":"<p><strong>Background: </strong>During the COVID-19 pandemic, mental health professionals were forced to find an appropriate way of working with patients that would ensure the continuity of therapy while considering the restrictions aimed at counteracting the spread of the virus. Online therapy has become an increasingly popular and common form of psychotherapeutic work. Emerging scientific studies have confirmed the positive effects of remote psychotherapeutic work. Nevertheless, modifying traditional and well-known forms of therapy or introducing completely new forms of remote therapy have been associated with several ethical concerns and challenges for psychotherapists.</p><p><strong>Objective: </strong>Due to the COVID-19 pandemic and the emerging epidemiological restrictions and recommendations, as well as new recommendations from psychotherapeutic associations, this study aimed to investigate the following: (1) Have psychotherapists experienced ethical dilemmas related to working online and face-to-face during the COVID-19 pandemic? (2) Was the occurrence of these dilemmas related to the therapists' personal characteristics, such as age, sex, professional experience, or therapeutic approach? (3) What specific ethical dilemmas do psychotherapists point to in conducting online and face-to-face therapy during the COVID-19 pandemic?</p><p><strong>Methods: </strong>We conducted an international study with 177 psychotherapists from 4 European countries (Sweden, Poland, Germany, and Portugal) using a web-based survey. The psychotherapeutic approaches represented in the sample were cognitive-behavioral, integrative, psychodynamic-psychoanalytic, systemic, existential and gestalt, and Ericksonian therapy, among others. An interview comprising closed and open questions was used to collect data on psychotherapists' personal characteristics, professional functioning, and ethical dilemmas encountered during online and face-to-face therapy.</p><p><strong>Results: </strong>Ethical dilemmas related to online therapy were reported by 58.7% (104/177) of therapists, while dilemmas related to face-to-face therapy were reported by 61% (108/177). The study showed that these dilemmas were independent of the personal and professional characteristics of therapists. Dilemmas related to online therapy were concern about online therapy, the issue of privacy and confidentiality of sessions, the effectiveness of online therapy, the issue of limitations that may hinder clinical work, and concerns related to the broader systemic and institutional context. In contrast, for the face-to-face form, ethical dilemmas mainly concerned health and safety, limitations in communication and quality of relationships due to wearing masks, and technical and logistical limitations.</p><p><strong>Conclusions: </strong>The issues considered here have not lost their relevance, because despite the lifting of restrictions related to the pandemic, some of the described dilemmas are similar to ","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e69154"},"PeriodicalIF":6.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12489403/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145080789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Development of a Recommendation Engine to University Student Mental Health Support Aligned With Stepped Care: Longitudinal Cohort Study. 从数据到护理:一个推荐引擎的开发,以大学生心理健康支持与阶梯护理相一致。
IF 6 2区 医学
Journal of Medical Internet Research Pub Date : 2025-09-17 DOI: 10.2196/72669
Pedro Velmovitsky, Charles Keown-Stoneman, Kaylen J Pfisterer, Julia Hews-Girard, Joseph Saliba, Shumit Saha, Scott Patten, Nathan King, Anne Duffy, Quynh Pham
{"title":"Development of a Recommendation Engine to University Student Mental Health Support Aligned With Stepped Care: Longitudinal Cohort Study.","authors":"Pedro Velmovitsky, Charles Keown-Stoneman, Kaylen J Pfisterer, Julia Hews-Girard, Joseph Saliba, Shumit Saha, Scott Patten, Nathan King, Anne Duffy, Quynh Pham","doi":"10.2196/72669","DOIUrl":"10.2196/72669","url":null,"abstract":"<p><strong>Background: </strong>Mental health challenges are prevalent among Canadian higher education students, with significant rates of depression and anxiety often going untreated due to reduced early detection, stigmatizing beliefs, and practical barriers. The U-Flourish longitudinal electronic survey study launched in 2018 engages new cohorts of incoming undergraduate students and repeatedly collects data about mental health and well-being and access to support.</p><p><strong>Objective: </strong>U-Flourish survey data provide a unique opportunity to train evidence-based prediction risk models and a personalized recommendation engine to signpost students to indicated mental health support based on their own data.</p><p><strong>Methods: </strong>Two approaches were integrated in developing the risk prediction models and recommendation engine: (1) clinically defined rules by experts in the field to detect current and predict the risk of future anxiety and depression and to signpost students to appropriate care using a stepped care approach and based on clinical factors (ie, self-harm and suicidal thoughts, symptom levels, and lifetime history); and (2) machine learning models, trained with additional data including family history, early adversity, and stress indicators, to predict future risks of clinically significant depression (9-item Patient Health Questionnaire) and anxiety (7-item Generalized Anxiety Disorder questionnaire). Models were created using the XGBoost algorithm and a 70:30 ratio for training and testing with 10-fold cross-validation.</p><p><strong>Results: </strong>In total, 27.5% of students at entry to university from 2018 to 2023 were identified as having potentially clinically significant levels of anxiety and depression and signposted to university mental health services based on the clinically defined rules. Optimizing thresholds to reduce false negatives, the machine learning models predicted anxiety and depression over the year in students screening negative at baseline with accuracy comparable with reported clinical screening as evidenced by sensitivity ≥90% for all models trained. Models had high negative predictive value (≥89%), balanced against low specificity. Individuals identified at risk for anxiety or depression were signposted primarily to self-guided resources supporting proactive prevention. Model findings also demonstrated that abbreviated screens (2-item Patient Health Questionnaire [PHQ-2] and 2-item Generalized Anxiety Disorder Questionnaire [GAD-2]), with potential to reduce respondent burden and improve adherence, can be used without compromising sensitivity. Indeed, PHQ-2 displayed a 90% sensitivity and GAD-2 displayed a 92% sensitivity. Shapley additive explanations analyses revealed other predictive factors including childhood trauma, family history of mental illness, and functional impairment associated with reported depression and anxiety symptoms.</p><p><strong>Conclusions: </strong>The risk pre","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":" ","pages":"e72669"},"PeriodicalIF":6.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12489415/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144789370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Digital Health Intervention in Snakebite Management: Scoping Review. 蛇咬伤管理中的数字健康干预:范围审查。
IF 6 2区 医学
Journal of Medical Internet Research Pub Date : 2025-09-17 DOI: 10.2196/71378
Anwesha Dash, Sushmita Kerketta, Geetanjali Mallick, Jaideep Menon, Srikanta Kanungo, Sanghamitra Pati
{"title":"Digital Health Intervention in Snakebite Management: Scoping Review.","authors":"Anwesha Dash, Sushmita Kerketta, Geetanjali Mallick, Jaideep Menon, Srikanta Kanungo, Sanghamitra Pati","doi":"10.2196/71378","DOIUrl":"10.2196/71378","url":null,"abstract":"<p><strong>Background: </strong>Snakebite envenoming is a neglected tropical disease that causes significant morbidity and mortality, with an estimated 81,410-137,880 deaths annually, primarily in rural, low-resource settings. Digital health interventions, particularly mobile apps (mobile-based health apps), offer innovative solutions to improve snakebite management through real-time guidance, antivenom stock tracking, and telemedicine.</p><p><strong>Objective: </strong>This scoping review aims to (1) systematically map existing digital mobile-based health interventions for snakebite management and (2) evaluate their key functionalities, accessibility, and geographical distribution.</p><p><strong>Methods: </strong>We conducted a systematic search (January 2024) across PubMed, Google Scholar, ResearchGate, Google Search, and the Google Play Store. The results were screened using the following criteria: mobile-based health apps providing structured guidance for snakebite management (first aid, treatment protocols, antivenom mapping) were included while studies not in the English language and studies on apps lacking clinical guidance were excluded. Data extraction focused on app features (snake identification, first aid protocols), accessibility (operating system compatibility, cost), multilingual support, and user feedback. Regional app availability was verified via VPN for country-specific stores (eg, India, Nigeria). Narrative synthesis was used to categorize findings by functionality, regional distribution, and implementation challenges. The results were presented using a PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart to illustrate the screening process, complemented by summary tables for a clear and detailed overview of the findings.</p><p><strong>Results: </strong>The search resulted in a total of 237 records, of which 227 underwent primary screening after removing duplicates. After full-text review, 135 reports were excluded, resulting in the inclusion of a total of 16 apps. All 16 apps provided first aid protocols, with most including snake identification tools (n=14, 88%) such as artificial intelligence-driven photo recognition. Additionally, over half mapped antivenom stocks (n=9, 56%) and a majority integrated emergency contacts (n=11, 69%). A total of 15 apps (94%) were free to access, and 10 (62%) supported Android. Most of the apps were available in India (n=11, 69%), while South Africa had very few, despite the burden, highlighting a clear geographical disparity. Urban users praised real-time guidance (85% positive reviews), but rural usability was hindered due to internet dependency (40% of rural users) and language barriers (65% misinterpretation was noted in regions where English was not the primary language).</p><p><strong>Conclusions: </strong>Digital health apps have demonstrated the potential to reduce snakebite mortality through education and emergency support. However, scalability can on","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e71378"},"PeriodicalIF":6.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12443350/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145080657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Predicting Engagement Patterns With Connected Wearable Devices in a Health System: Survival Analysis. 预测医疗系统中可穿戴设备的参与模式:生存分析。
IF 6 2区 医学
Journal of Medical Internet Research Pub Date : 2025-09-17 DOI: 10.2196/78507
Allistair Clark, Gillian Gresham, Joshua Pevnick, Raymond Duncan, Mitchell Kamrava, Michael Sobolev
{"title":"Predicting Engagement Patterns With Connected Wearable Devices in a Health System: Survival Analysis.","authors":"Allistair Clark, Gillian Gresham, Joshua Pevnick, Raymond Duncan, Mitchell Kamrava, Michael Sobolev","doi":"10.2196/78507","DOIUrl":"10.2196/78507","url":null,"abstract":"<p><strong>Background: </strong>The rapid advancement and widespread adoption of wearable devices provide opportunities to collect longitudinal objective activity and health data and integrate the information directly into a patient's electronic health record (EHR). Patterns of engagement and factors associated with the use and nonuse of wearable devices are currently not well understood.</p><p><strong>Objective: </strong>This study aimed to quantify the number of patients still engaged and using wearable devices at 1 year since each patient's first day of use across a cohort collected over 6 years. We then aimed to identify demographic and behavioral factors that statistically significantly predict the likelihood of staying engaged and using wearable devices within the same 1-year time span since first use.</p><p><strong>Methods: </strong>We analyzed connected device data from a large, nonprofit academic medical center, which began to incorporate wearable device data into the EHR system in April 2015. We conducted a survival analysis to evaluate time to early disengagement among connected device users and identify factors associated with long-term (1 y) engagement in multivariable Cox proportional hazard regression models.</p><p><strong>Results: </strong>The analysis included 8616 patients (mean age 45, SD 14.36 y; median 21, IQR 34-55 y; men: n=4489, 52.1%; women: n=4126, 47.9%) with available connected device data (eg, step counts) from the EHR between 2015 and 2022. A total of 5870 (68.13%) patients were engaged with active connected devices in the EHR at 1 year. Multivariable Cox regression models indicated no statistically significant differences between gender groups and race categories. Younger age categories (18-34 y) and lower median daily step counts (<5000) were associated with statistically significant increased hazards for early disengagement at 1 year.</p><p><strong>Conclusions: </strong>The ongoing development of new sensors and algorithms presents opportunities to expand the capabilities of wearable devices, making them even more integral to health care delivery. It is important to quantify and enhance engagement to maximize the benefits of this technology and inform future use of the technology to improve health outcomes.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e78507"},"PeriodicalIF":6.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12489408/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145080850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Design Thinking Approach for Transnational Adaptation of 2 Mobile Mental Health Apps: Tutorial for Researchers and Practitioners. 两种移动心理健康应用程序跨国适应的设计思维方法:研究人员和从业者指南。
IF 6 2区 医学
Journal of Medical Internet Research Pub Date : 2025-09-17 DOI: 10.2196/77048
Sylvie Bernaerts, Tom Van Daele, Christian Korthé Carlsen, Søren Lange Nielsen, Jolanda Schaap, Yvette Roke
{"title":"A Design Thinking Approach for Transnational Adaptation of 2 Mobile Mental Health Apps: Tutorial for Researchers and Practitioners.","authors":"Sylvie Bernaerts, Tom Van Daele, Christian Korthé Carlsen, Søren Lange Nielsen, Jolanda Schaap, Yvette Roke","doi":"10.2196/77048","DOIUrl":"10.2196/77048","url":null,"abstract":"<p><strong>Unlabelled: </strong>Digital mental health solutions have great potential to enhance mental health care. However, barriers at the level of users, interventions, and context hinder engagement and uptake. Involving users in the design, adaptation, and implementation process has been put forward as a potential solution; however, instructions and examples on how to do so are limited. One potential framework is design thinking. Although design thinking is a common approach in the business community, its use for guiding development and adaptation processes is not yet a common practice in the context of digital mental health. Unsurprisingly, it is difficult to find concrete instructions on how to do this, even more so in an international context. Therefore, the SUPER (Successful User Participation Examples and Recommendations) project aimed to develop guidelines for entrepreneurs and mental health organizations on how to involve end users and mental health care professionals in the transnational development, implementation, and adaptation of mental health technology. This paper describes the design thinking process that led to those guidelines and how these can be undertaken by researchers, practitioners, or developers in the context of digital mental health. The process is illustrated with 2 adaptations of digital mental health solutions following this approach, executed by the SUPER consortium in the Netherlands and in Denmark. The learnings from these 2 pilots are provided in the form of key considerations and highlights of issues experienced during both design thinking processes. The overall aim is to guide practitioners, developers, and researchers toward better development and international adaptation of digital mental health.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e77048"},"PeriodicalIF":6.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12443347/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145080617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An Image-Voice Dietary Assessment System for Estimating Individual Nutrient Intakes in Cambodian Women and Children: Relative Validity, Reliability, and Acceptability Study. 用于估计柬埔寨妇女和儿童个人营养摄入量的图像-语音膳食评估系统:相对效度,可靠性和可接受性研究。
IF 6 2区 医学
Journal of Medical Internet Research Pub Date : 2025-09-17 DOI: 10.2196/65939
Megan E Rollo, Janelle L Windus, Samantha J Stewart, Connor T Dodd, Marc T P Adam, Kerith Duncanson, Tracy L Burrows, Kim Colyvas, Clare E Collins
{"title":"An Image-Voice Dietary Assessment System for Estimating Individual Nutrient Intakes in Cambodian Women and Children: Relative Validity, Reliability, and Acceptability Study.","authors":"Megan E Rollo, Janelle L Windus, Samantha J Stewart, Connor T Dodd, Marc T P Adam, Kerith Duncanson, Tracy L Burrows, Kim Colyvas, Clare E Collins","doi":"10.2196/65939","DOIUrl":"10.2196/65939","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Individual-level dietary intake data are fundamental for developing nutrition policy and programs. In low- and lower-middle-income countries, proxy measures of individual intake (household consumption and expenditure surveys and food balance sheets) are often used, with limited implementation of new technology-assisted applications.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;We aimed to determine the relative validity, test-retest reliability, and acceptability of the Voice-Image Solution for Individual Dietary Assessment (VISIDA) system in a sample of Cambodian women and their children aged ≤5 years.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Mothers and one of their children were recruited from 3 locations (rural, semirural, and urban) in Siem Reap province, Cambodia. Dietary intake data were collected for each participant using 2 methods across 3 recording periods over approximately 4 weeks. In week 1, intake was recorded using VISIDA for 3 nonconsecutive days, followed by 3 interviewer-administered, multiple-pass 24-hour recalls collected in weeks 2 to 3. In week 4, VISIDA was used again to collect a 3-day food record. After the third intake recording period, the mothers completed a feedback survey. Differences in estimated nutrient intakes for the 3 recording periods for mothers and children were examined using a linear mixed model approach.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The analysis included 210 participants (n=119, 56.7% mothers and n=91, 43.3% children). Estimated mean nutrient intakes reported in both VISIDA recording periods were mostly lower compared to intakes reported using the 24-hour recalls. Compared to the 24-hour recalls, statistically significant differences were found for the VISIDA recording periods for 80% (16/20) of nutrients for mothers and 32% (6/19) of nutrients for children. Nutrient intakes estimated from both VISIDA recording periods showed no statistically significant differences for mothers and children. For mothers, the differences of model weighted marginal means in energy intakes (kcal) were -296 (95% CI -410 to -181; VISIDA period 1 minus 24-h recall), -274 (95% CI -390 to -158; VISIDA period 2 minus 24-h recall), and -22 (95% CI -131 to 87; VISIDA period 1 minus VISIDA period 2). For children, the differences in model weighted marginal means in energy intakes (kcal) were -158 (95% CI -227 to -89; VISIDA period 1 minus 24-h recall), -127 (95% CI -198 to -57; VISIDA period 2 minus 24-h recall), and -31 (95% CI -98 to 37; VISIDA period 1 minus VISIDA period 2). Most mothers reported that the VISIDA smartphone app was \"easy to use\" (68/108, 63%) or \"very easy to use\" (23/108, 21.3%) for collecting dietary intake data.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The VISIDA system produced lower estimates of nutrient intakes when compared to the 24-hour recalls in a sample of mothers and children in Siem Reap province, Cambodia. However, the estimated nutrient intakes for the 2 VISIDA recording periods were sim","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e65939"},"PeriodicalIF":6.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12489410/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145075429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Practical Guide to Using Futures Methods in Health Care: Approaches, Applications, and Case Studies. 在医疗保健中使用未来方法的实用指南:方法,应用和案例研究。
IF 6 2区 医学
Journal of Medical Internet Research Pub Date : 2025-09-16 DOI: 10.2196/82820
Bertalan Mesko, Tamás Kristóf, Pranavsingh Dhunnoo, Nóra Árvai, Gellért Katonai
{"title":"A Practical Guide to Using Futures Methods in Health Care: Approaches, Applications, and Case Studies.","authors":"Bertalan Mesko, Tamás Kristóf, Pranavsingh Dhunnoo, Nóra Árvai, Gellért Katonai","doi":"10.2196/82820","DOIUrl":"10.2196/82820","url":null,"abstract":"<p><p>Researchers and health care institutions have increasingly applied structured futures methods-such as the futures wheel, scenario analysis, forecasting, and horizon scanning-to systematically explore, generate, and prepare for multiple possible futures. However, discussions around the future of medicine, specialties, or therapeutic areas have often relied on the subjective opinions or perspectives of key opinion leaders rather than on future strategies, policies, visions, and scenarios that are grounded in rigorous and established methods. This underscores the need for futures methods to be widely adopted and effectively incorporated into both medical practice and health care policymaking. Integrating structured foresight techniques into strategic planning enables clinicians and policymakers to transition from reactive decision-making to proactive, plausible approaches that shape a more resilient and adaptive health care system. Our goal with this paper is to provide a methodological guide that is supported by case studies, demonstrating how futures methods can be systematically applied in health care. By offering practical examples, we intend to empower medical professionals, health care leaders, researchers, patients, and policymakers with the tools to anticipate and navigate future challenges and opportunities more effectively.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e82820"},"PeriodicalIF":6.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485254/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145069585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Understanding Economic Decision-Making in Digital Therapeutics Development: Qualitative Approach. 理解数字治疗发展中的经济决策:定性方法。
IF 6 2区 医学
Journal of Medical Internet Research Pub Date : 2025-09-16 DOI: 10.2196/79746
Yoann Sapanel, L Martin Cloutier, Alec Morton, Sapphire Lin, Gyula Seres, Dean Ho
{"title":"Understanding Economic Decision-Making in Digital Therapeutics Development: Qualitative Approach.","authors":"Yoann Sapanel, L Martin Cloutier, Alec Morton, Sapphire Lin, Gyula Seres, Dean Ho","doi":"10.2196/79746","DOIUrl":"10.2196/79746","url":null,"abstract":"<p><strong>Background: </strong>Digital therapeutics (DTx) represent a transformative shift in health care delivery, offering software-driven, evidence-based therapeutic interventions. Despite their potential, adoption remains low across health care systems, partly due to insufficient economic evidence. Significant knowledge gaps persist regarding stakeholders' approaches to economic decisions in DTx development, with prior studies also indicating limited consideration of economic factors in early DTx development stages, particularly from researchers.</p><p><strong>Objective: </strong>This study investigates how researchers approach decision-making regarding factors that influence the economic impact of DTx during technological development and clinical validation phases, examining the underlying mechanisms and contextual conditions that shape these processes.</p><p><strong>Methods: </strong>Using a critical realism philosophical stance, 17 semistructured interviews were conducted with researchers involved in DTx development, including research engineers (n=5), health systems and social science researchers (n=6), clinician-researchers (n=4), and practitioner-researchers (n=2). The research approach combined deductive and inductive coding, followed by abductive and retroductive inference processes to identify generative mechanisms underlying observed decision-making patterns. Qualitative system dynamics modeling was applied to visualize causal loop relationships through triangulated data sources.</p><p><strong>Results: </strong>Three interrelated generative mechanisms were identified that shape researchers' decision-making regarding economic considerations: (1) the professional norms, operating through reinforcing loops that systematically prioritize clinical validation while marginalizing economic considerations; (2) the researcher experience, revealing how professional training and limited economic literacy create cognitive biases that obscure economic factors; and (3) the DTx adoption uncertainties, demonstrating how implementation concerns influence development decisions through both reinforcing and balancing feedback loop dynamics. These mechanisms explain why, despite growing recognition of the importance of economic evidence, economic considerations remain peripheral in researchers' decision frameworks.</p><p><strong>Conclusions: </strong>This study reveals complex interactions between institutional structures, intrapersonal factors, and implementation uncertainties that systematically deprioritize economic considerations in DTx development. The identified mechanisms provide valuable intervention points for strengthening the development process toward a more comprehensive assessment of clinical, technical, and economic value throughout the DTx lifecycle to ultimately enhance their adoption in health care systems.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e79746"},"PeriodicalIF":6.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485261/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145075391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Public Perspectives on Palliative and Hospice Care: Social Media Content Analysis Using Topic Modeling and Multiclass Sentiment Analysis. 公众对缓和与安宁疗护的看法:使用主题模型与多阶层情绪分析的社交媒体内容分析。
IF 6 2区 医学
Journal of Medical Internet Research Pub Date : 2025-09-16 DOI: 10.2196/70836
Aeri Kim, Kyungmi Woo
{"title":"Public Perspectives on Palliative and Hospice Care: Social Media Content Analysis Using Topic Modeling and Multiclass Sentiment Analysis.","authors":"Aeri Kim, Kyungmi Woo","doi":"10.2196/70836","DOIUrl":"10.2196/70836","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Palliative care enhances dignity and quality of life for patients with serious illnesses by managing distressing symptoms and supporting families. However, inadequate awareness and misconceptions often hinder patients and their families from accessing these services. Understanding of public perspectives on palliative and hospice care can facilitate the development of targeted educational resources and awareness campaigns. As social media becomes an important source of health information, analyzing such publicly available web-based sources can yield valuable insights into perceptions of palliative and hospice care.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study analyzed public perspectives posted on a popular social media platform in South Korea to understand perceptions, challenges, needs, and sentiments related to palliative and hospice care.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Data were collected from Naver Knowledge iN, a popular web-based public forum in South Korea, encompassing 34,501 texts posted between 2002 and 2024. After applying inclusion and exclusion criteria, 9072 relevant perspectives were analyzed. Contextualized topic modeling was used to identify themes, and the optimal model was selected based on coherence, diversity scores, and expert feedback. In addition, multiclass sentiment analysis using a fine-tuned Korean bidirectional encoder representations from transformers (KoBERT) model classified sentiments into 6 categories. The multiclass sentiment model's performance was evaluated using accuracy, precision, recall, and F&lt;sub&gt;1&lt;/sub&gt;-score.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Social media discussions on palliative and hospice care have increased steadily over time. Topic modeling identified 9 themes, with \"ethical and legal concerns\" and \"medical care in hospitals\" peaking in recent years, suggesting growing public interest in these areas. \"Emotional and psychological support\" emerged as the predominant theme, reflecting a significant need for psychosocial assistance among patients and their families. Sentiment analysis revealed that \"sadness,\" \"anxiety,\" and \"neutral\" were common emotions across many topics. Notably, themes such as \"emotional and psychological support,\" \"disease treatment outcomes and prognosis,\" \"medical care in hospitals,\" \"financial issues,\" and \"symptom management\" were predominantly associated with \"sadness,\" while \"administrative and volunteer services,\" \"ethical and legal concerns,\" and \"nutrition management\" were more closely linked with \"anxiety.\"&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This study highlights public concerns about palliative and hospice care in South Korea, including ethical dilemmas, caregiving burden, and emotional distress. Findings underscore the need for communication strategies that address informational, emotional, and psychological needs. Culturally sensitive, interactive communication tools, such as artificial intelligence-powered chatbots and public educatio","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e70836"},"PeriodicalIF":6.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485256/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145075407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
New Doc on the Block: Scoping Review of AI Systems Delivering Motivational Interviewing for Health Behavior Change. 新文件:为健康行为改变提供动机性访谈的人工智能系统的范围审查。
IF 6 2区 医学
Journal of Medical Internet Research Pub Date : 2025-09-16 DOI: 10.2196/78417
Zev Karve, Jacob Calpey, Christopher Machado, Michelle Knecht, Maria Carmenza Mejia
{"title":"New Doc on the Block: Scoping Review of AI Systems Delivering Motivational Interviewing for Health Behavior Change.","authors":"Zev Karve, Jacob Calpey, Christopher Machado, Michelle Knecht, Maria Carmenza Mejia","doi":"10.2196/78417","DOIUrl":"10.2196/78417","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Artificial intelligence (AI) is increasingly used in digital health, particularly through large language models (LLMs), to support patient engagement and behavior change. One novel application is the delivery of motivational interviewing (MI), an evidence-based, patient-centered counseling technique designed to enhance motivation and resolve ambivalence around health behaviors. AI tools, including chatbots, mobile apps, and web-based agents, are being developed to simulate MI techniques at scale. While these innovations are promising, important questions remain about how faithfully AI systems can replicate MI principles or achieve meaningful behavioral impact.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This scoping review aimed to summarize existing empirical studies evaluating AI-driven systems that apply MI techniques to support health behavior change. Specifically, we examined the feasibility of these systems; their fidelity to MI principles; and their reported behavioral, psychological, or engagement outcomes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We systematically searched PubMed, Embase, Scopus, Web of Science, and Cochrane Library for empirical studies published between January 1, 2018, and February 25, 2025. Eligible studies involved AI-driven systems using natural language generation, understanding, or computational logic to deliver MI techniques to users targeting a specific health behavior. We excluded studies using AI solely for training clinicians in MI. Three independent reviewers screened and extracted data on study design, AI modality and type, MI components, health behavior focus, MI fidelity assessment, and outcome domains.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Of the 1001 records identified, 15 (1.5%) met the inclusion criteria. Of these 15 studies, 6 (40%) were exploratory feasibility or pilot studies, and 3 (20%) were randomized controlled trials. AI modalities included rule-based chatbots (9/15, 60%), LLM-based systems (4/15, 27%), and virtual or mobile agents (2/15, 13%). Targeted behaviors included smoking cessation (6/15, 40%), substance use (3/15, 20%), COVID-19 vaccine hesitancy, type 2 diabetes self-management, stress, mental health service use, and opioid use during pregnancy. Of the 15 studies, 13 (87%) reported positive findings on feasibility or user acceptability, while 6 (40%) assessed MI fidelity using expert review or structured coding, with moderate to high alignment reported. Several studies found that users perceived the AI systems as judgment free, supportive, and easier to engage with than human counselors, particularly in stigmatized contexts. However, limitations in empathy, safety transparency, and emotional nuance were commonly noted. Only 3 (20%) of the 15 studies reported substantially significant behavioral changes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;AI systems delivering MI show promise for enhancing patient engagement and scaling behavior change interventions. Early evidence supports t","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e78417"},"PeriodicalIF":6.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485255/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145075447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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