Health Policy and Technology最新文献

{"title":"Global ChatGPT interest across healthcare and education access","authors":"Amrit Kirpalani","doi":"10.1016/j.hlpt.2025.101061","DOIUrl":"10.1016/j.hlpt.2025.101061","url":null,"abstract":"<div><h3>Objectives</h3><div>The rapid adoption of AI tools like ChatGPT has transformed information access, particularly in healthcare. However, engagement with AI may be influenced by factors such as healthcare accessibility and educational resources, with potential implications for misinformation in low-resource settings. This study investigates the relationship between physician density, tertiary education enrollment, and national interest in ChatGPT.</div></div><div><h3>Methods</h3><div>A cross-sectional analysis was conducted using global datasets. Physician density, tertiary education enrollment, GDP, and internet penetration were sourced from WHO, UNESCO, and the World Bank, respectively. The primary outcome, ChatGPT interest scores, was derived from Google Trends. Pearson correlation and multiple linear regression analyses were used to explore associations, controlling for GDP and internet penetration. Logistic regression was employed as a sensitivity analysis, categorizing variables into high and low groups.</div></div><div><h3>Results</h3><div>Data from 100 countries were analyzed. A significant negative correlation was observed between physician density and ChatGPT interest (<em>r</em> = -0.32, <em>p</em> = 0.012). Multiple linear regression confirmed that lower physician density was significantly associated with higher ChatGPT interest (β = -0.2857, <em>p</em> = 0.045). Tertiary education enrollment showed no significant association with ChatGPT interest. Logistic regression supported these findings, with higher physician density significantly reducing the likelihood of high ChatGPT interest (OR = 0.214, <em>p</em> = 0.001).</div></div><div><h3>Conclusion</h3><div>Our study suggests that regions with fewer healthcare professionals may engage more with AI tools like ChatGPT, highlighting the need for careful integration of AI into healthcare systems to prevent misinformation and support equitable access to reliable health information.</div></div><div><h3>Public Interest Summary</h3><div>It is well known that people who have difficulty in accessing healthcare may turn to the internet for medical advice, but it is not yet known if artificial intelligence, like ChatGPT, is being adopted by users for this same purpose. Given the widespread use of ChatGPT, this study explored whether ChatGPT interest in different countries was related to the number of physicians in those countries. We found that in countries with fewer doctors per capita, public interest in ChatGPT tends to be higher. While this does not confirm that people are using ChatGPT specifically for medical advice, it raises important questions about how AI may be filling gaps in access to healthcare. Given the potential for AI to spread inaccurate information, these findings highlight the need for careful regulation to ensure AI tools are used responsibly and do not contribute to misinformation in healthcare.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 5","pages":"Article 101061"},"PeriodicalIF":3.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144338968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Narrative review and bibliometric analysis on infodemics and health misinformation: A trending global issue","authors":"Muhammad Iqhrammullah ,&nbsp;Naufal Gusti ,&nbsp;Asyraf Muzaffar ,&nbsp;Yousef Khader ,&nbsp;Sidik Maulana ,&nbsp;Marius Rademaker ,&nbsp;Asnawi Abdullah","doi":"10.1016/j.hlpt.2025.101058","DOIUrl":"10.1016/j.hlpt.2025.101058","url":null,"abstract":"<div><h3>Background</h3><div>The COVID-19 pandemic exposed how infodemics undermine public health efforts, which subsequently led to the promotion of harmful behaviors. This review aimed to examine major sources of misinformation and explore how demographic and socioeconomic factors affect digital and health literacy, shaping vulnerability to infodemics.</div></div><div><h3>Methods</h3><div>A narrative review was conducted to synthesize evidence on the pathways, sources, and social determinants of health misinformation. Additionally, a bibliometric analysis was performed using Scopus data from 1997 to 2024, analyzed via Bibliometrix and VOSviewer. The analysis focused on publications related to infodemics and health misinformation on digital platforms, mapping thematic clusters, trends, and keyword co-occurrences.</div></div><div><h3>Results</h3><div>Mainstream news media, social media, and scientific journals each play a role in disseminating misinformation, exacerbated by time pressure, algorithmic amplification, and inadequate validation processes. Factors attributable to low digital and health literacy include age, education, income, and internet access, which increase vulnerability to misinformation. The bibliometric analysis revealed exponential growth in related research, peaking during the COVID-19 pandemic. Eight dominant research clusters were identified: Health communication and social media; Infodemiology and data analysis; COVID-19 and misinformation; Public and digital health; Vaccine hesitancy; Risk and infodemic management; Conspiracy theories in social media; and Crisis communication.</div></div><div><h3>Conclusion</h3><div>Infodemics are driven by multi-source digital misinformation and disproportionately affect those with limited literacy. Fact-checking as a mitigation effort can be developed by leveraging artificial intelligence, machine learning, and natural language processing, yet strengthening digital and health literacy remains critical.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 5","pages":"Article 101058"},"PeriodicalIF":3.4,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144480932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating internationally educated nurses into the nursing faculty workforce: a new policy for nursing regulators","authors":"Houssem Eddine Ben-Ahmed ,&nbsp;Intissar Souli ,&nbsp;Emmanuel Akwasi Marfo ,&nbsp;Abir Rebhi","doi":"10.1016/j.hlpt.2025.101057","DOIUrl":"10.1016/j.hlpt.2025.101057","url":null,"abstract":"<div><div>Nursing faculty shortages received less attention in the literature and media outlets compared to registered clinical nursing staff shortages. One may question whether we do not have enough nursing faculty to teach and train students, who will take that responsibility? This critical question should be addressed by nursing leaders, researchers, and key system partners to develop innovative and sustainable policies that reduce nursing faculty shortages. Otherwise, the nursing faculty shortage would negatively affect the quality of nursing education and lead to a declining number of nursing seats, which should be avoided as we need more nurses in the upcoming years. This paper suggested developing a new policy for nursing regulators, titled “Non-clinical Academic Registration Category”, to support internationally educated nurses (IENs) with master's or doctoral degrees who wish to contribute to the nursing faculty workforce. To better understand the context of this policy and its benefits, the paper described the challenges of the registration process experienced by three IENs and the implications of integrating them into the workforce. Through collective and innovative policies, we can empower the future nursing faculty workforce and rationally respond to the ongoing crisis.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 5","pages":"Article 101057"},"PeriodicalIF":3.4,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144321507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The emergence and future of precision public health: a scoping review","authors":"Ms Rebecca Bosward,&nbsp;Annette Braunack-Mayer,&nbsp;Ms Emma Frost,&nbsp;Stacy Carter","doi":"10.1016/j.hlpt.2025.101056","DOIUrl":"10.1016/j.hlpt.2025.101056","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Objectives&lt;/h3&gt;&lt;div&gt;Rapid uptake of big data and technologies in healthcare are transforming methodological capabilities in medicine and public health, giving rise to new fields such as precision public health. We conceptualised precision public health as an emerging technology to understand the emergence of this term and its associated characteristics.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;We undertook a scoping review to collate and analyse existing literature on precision public health. Documents in English that mentioned the exact phrase “precision public health” were searched for in CINAHL, Medline, PubMed, Scopus, Web of Science and Google Scholar. A descriptive statistical analysis was performed on resulting documents to generate an account of precision public health terminology and definitions as well as author and funder characteristics of articles. Data were analysed through a sociotechnical lens, which is an approach for understanding how technologies emerge and disrupt existing systems.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;Precision public health was ill-defined at first but is now stabilising. Using an emerging technology conceptual framework, we identified characteristics of precision public health including rapid growth, incoherence, uncertainty about future impacts and outcomes, and ambiguity about use of terminology. Novelty was contested.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusions&lt;/h3&gt;&lt;div&gt;Definitions of precision public health are continuously changing, and terms have different meanings and uses. Lack of consensus on definitions and terms for precision public health may impact progress of resarch. A single definitions of precision public health is not achievable; however, definitions should be negotiable among stakeholders, acknowledge similarities and differences between stakeholder values and expectations, and reflect research and policy objectives.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Public interest summary&lt;/h3&gt;&lt;div&gt;Precision public health is an emerging field which often relies on data-centric approaches, including artificial intelligence and machine learning, to improve population health outcomes, which potentially disrupt traditional evidence-based research methods and practice. We conducted a scoping review of current literature, and conceptualised precision public health as an emerging technology to understand how it impacts evidence-based practice and how terms and definitions of precision public health have changed over time.&lt;/div&gt;&lt;div&gt;There is currently no consensus around terms and definitions most appropriate for the field and the absence of empirical evidence makes it difficult to evaluate potential future impacts. If precision public health is going to deliver on its promises, researchers and practitioners must be transparent about reporting potential uncertainties, benefits and harms. Definitions should also be open and negotiable among stakeholders in precision public health, and reflect research and policy objectives.&lt;/div&gt;&lt;/div","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 5","pages":"Article 101056"},"PeriodicalIF":3.4,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144291212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI in personalized medicine: Bridging ethical and regulatory gaps in resource-limited settings","authors":"Aliasgar Shahiwala","doi":"10.1016/j.hlpt.2025.101052","DOIUrl":"10.1016/j.hlpt.2025.101052","url":null,"abstract":"","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 5","pages":"Article 101052"},"PeriodicalIF":3.4,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic decision system for ENT surgery waiting list prioritization using M-Score and TOPSIS methodology","authors":"Fabián Silva-Aravena,&nbsp;Jenny Morales","doi":"10.1016/j.hlpt.2025.101036","DOIUrl":"10.1016/j.hlpt.2025.101036","url":null,"abstract":"<div><div>Objective: This study aims to develop and evaluate a dynamic prioritization system to improve surgical waiting list management for otorhinolaryngology (ENT) patients in a high-complexity public hospital in Chile. The proposed model aims to reduce waiting times and improve equity and clinical outcomes by dynamically incorporating changes in patient condition. Methods: We implemented a dynamic scoring system (M-Score), updated weekly using multidimensional biopsychosocial criteria, and integrated it with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to prioritize patients. The evaluation was carried out using Monte Carlo simulations over a 52-week horizon, simulating patient inflows and outflows via a balanced flow model. The stability and performance of the proposed model were compared with a static model and a traditional first-come, first-served (FCFS) protocol. Results: The proposed approach reduced the average waiting time from 130 to 91 days compared to the static model (a 30 % relative and absolute decrease of 39 days) and from 157 to 91 days compared to FCFS (a 42 % relative and absolute reduction of 66 days). The greatest improvements were observed among high-risk patients, whose prioritization was adapted in real time to worsening clinical conditions. Conclusions: Our adaptive prioritization model demonstrates significant improvements in waiting time management, particularly for clinically vulnerable patients. Although the findings support its feasibility, further prospective validation is necessary before clinical implementation. Future research should focus on real-time integration with electronic medical records, scalability between specialties, and evaluation of impacts on patient satisfaction and health outcomes. Lay Summary: ENT patients in public hospitals often face long waiting times that increase health risks. This study introduces a weekly update to the prioritization model using social and health factors of the patient. The system reduced average waiting times by up to 66 days in simulation. High-risk patients were prioritized as their conditions worsened. This approach offers a promising data-driven strategy for improving waitlist management and resource allocation in public healthcare.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 5","pages":"Article 101036"},"PeriodicalIF":3.4,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spillover effects of pain medication tapering in chronic pain patients: a systematic review and consequences for health economic evaluation studies","authors":"Frenn Bultinck ,&nbsp;Nick Verhaeghe ,&nbsp;Max Lelie ,&nbsp;Bo Vandenbulcke ,&nbsp;Elke Wuyts ,&nbsp;Cleo L. Crunelle ,&nbsp;Lisa Goudman ,&nbsp;Maarten Moens ,&nbsp;Koen Putman","doi":"10.1016/j.hlpt.2025.101037","DOIUrl":"10.1016/j.hlpt.2025.101037","url":null,"abstract":"<div><h3>Background</h3><div>Spillover effects of pain medication tapering (PMT) programs in patients with chronic pain (CP) are underexplored. This systematic review presents current research on the study of spillover effects of PMT in patients with CP and provides suggestions for examination of spillover effects in health economic research of PMT. Understanding spillover effects enable wide-ranging assessment of interventions, including its broader impacts.</div></div><div><h3>Methods</h3><div>Literature was searched up to September 2023 in Web of Science, PubMed, Scopus, Embase, PsychINFO, APA PsychNet, Cochrane library, Econlit, and grey literature sources including Google Scholar, CADTH, Mednar and the WHO website. QualSyst was used for Risk of bias assessment. The study protocol was registered prospectively in PROSPERO (CRD42023461763). Results were classified into five domains and incorporated into the expanded impact inventory framework. No funding was obtained.</div></div><div><h3>Results</h3><div>Of 2099 records initially identified, six qualitative studies of varying quality were included. In the healthcare domain, additional demands on healthcare delivery, patients switching between healthcare providers and psychosocial impacts for healthcare providers were key findings. Scientific spillovers entailed evidence-based recommendations, enhanced PMT awareness and knowledge dissemination. Sociological effects encompassed bias affecting underrepresented groups and community-level benefits. No spillovers were found in other categories. Future research should extend beyond patient-centered outcomes to comprehensively assess PMT’s societal impact and reveal indirect benefits currently underrepresented in the literature.</div></div><div><h3>Conclusions</h3><div>Spillover effects of PMT in patients with CP were identified. Considering spillovers can allow policymakers to optimize healthcare policies and resource allocation in healthcare. Inclusion of only six studies is a limitation of this study.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 5","pages":"Article 101037"},"PeriodicalIF":3.4,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144254395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring policy and regulations of clinical AI systems: Views from patients with chronic diseases","authors":"Bijun Wang ,&nbsp;Onur Asan ,&nbsp;Turki Alelyani","doi":"10.1016/j.hlpt.2025.101035","DOIUrl":"10.1016/j.hlpt.2025.101035","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Background&lt;/h3&gt;&lt;div&gt;Artificial Intelligence (AI) has become a transformative force in healthcare, offering opportunities to enhance patient care, improve efficiency, and reduce costs. However, patients' perspectives, which greatly influence the acceptance and implementation of AI technologies, remain under-researched.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Objective&lt;/h3&gt;&lt;div&gt;This study explores patients with chronic conditions’ perspectives on clinical AI systems, focusing on their concerns, government involvement, accountability for potential AI error, and preferences between AI and doctor recommendations. These insights are crucial for tailoring AI technologies to meet patients' needs and expectations and better engage patients in adopting new technologies.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Method&lt;/h3&gt;&lt;div&gt;This study conducted an online open-ended survey with valid responses from 140 patients with chronic conditions, exploring four aspects of clinical AI perspectives. The data was systematically coded and analyzed using an inductive thematic analysis approach to identify emergent themes.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Result&lt;/h3&gt;&lt;div&gt;The majority of participants expressed concerns about the implementation of AI in healthcare (92.86 %), with the top worries including lack of human touch (22.86 %), potential AI bias and fairness (16.43 %), and over-dependence on AI (16.43 %). Regarding responsibility for potential treatment damages, 37.14 % of participants believed that physicians should bear the responsibility, 16.43 % considered AI developers accountable, and 1.42 % viewed the government as the responsible party. Furthermore, 44.57 % suggested that responsibility should be shared among stakeholders. In terms of government role, 51.43 % saw regulation and monitoring as key responsibilities, while 8.57 % perceived no government role in AI healthcare. Finally, around 80 % of patients preferred treatment recommendations from care providers over AI.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;div&gt;The findings suggest patients are looking for a balanced approach between technology and human involvement, with clear accountability and proper regulation. Though most prefer human doctors, an openness to AI's potential indicates an evolving perception. This underscores the need for a governance-inclusive and patient-centric strategy that addresses these aspects to ensure successful AI integration in healthcare.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Lay Summary&lt;/h3&gt;&lt;div&gt;This study explores the opinions of chronic patients on using AI in healthcare. It found that while patients appreciate the potential benefits of AI, they have concerns about losing the personal touch of human doctors, potential biases, and over-reliance on technology. They also believe that accountability for AI errors should be shared among doctors, developers, and the government. The findings highlight the need for careful integration of AI in healthcare, with clear regulations and a focus on patient safety to build trust and acceptance.&lt;/div&gt;&lt;/di","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 5","pages":"Article 101035"},"PeriodicalIF":3.4,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144212819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Health equity in the digital age: Exploring health policy and inclusive digital care","authors":"Jessica A. Coetzer ,&nbsp;Nicole S. Goedhart ,&nbsp;Tjerk Jan Schuitmaker-Warnaar ,&nbsp;Christine Dedding ,&nbsp;Teun Zuiderent-Jerak","doi":"10.1016/j.hlpt.2025.101039","DOIUrl":"10.1016/j.hlpt.2025.101039","url":null,"abstract":"<div><h3>Objectives</h3><div>The digitalisation of care, whilst beneficial for some, also risks exacerbating health inequities if existing health (and social) disparities are not considered. Literature has indicated the broad, systemic causes of digital health inequities could be addressed through policy. This article aims to explore how health inequities are rendered (in)visible in and by digital care policies.</div></div><div><h3>Methods</h3><div>We inductively analysed sixteen Dutch health policy documents focusing on digital care. Employing a constructivist grounded theory approach, we analysed documents to determine how health equity is addressed in relation to digital care.</div></div><div><h3>Results</h3><div>Although Dutch health policies do consider health inequities, it is not always shown in policies as a concept related to digital care. Health policies portray digital care as progressive and innovative, being able to shape healthcare in several positive ways. The risks of digital care are attended to less, with focus being placed mostly on privacy and data-security rather than also paying attention to digital health inequities.</div></div><div><h3>Conclusions</h3><div>Policies either ignore digital health equity entirely or present digital health equity in ways that risk overlooking how digital care may subtly aggravate health inequities. This creates a blind spot in which technological deterministic narratives can be disguised. Current policies could unintentionally perpetuate exclusion by not highlighting the role of digital health inequities as a part of the health equity landscape. Policy needs to allow for digital health inequities to be better recognised, allowing digital care to drive, rather than limit, the possibilities for a more equitable future.</div></div><div><h3>Lay Summary</h3><div>Digital care is increasing in popularity, but risks excluding a significant number of people who usually already experience health inequities. Although Dutch health policy does consider health inequities, it is not shown in policies as a concept related to digital care. As a result, health equity risks being forgotten in the development of digital care. Policies portray digital care as being able to shape healthcare in a number of positive ways but do not address the risks it may pose in widening health inequities. Instead, issues like ensuring privacy receive more attention. By being overly optimistic about technology without being cautious about its other social consequences, achieving aims such as affordable and accessible care could be negatively impacted. Policy needs to allow for digital health inequities to be better recognised, allowing digital care to drive, rather than limit, the possibilities for a more equitable future.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 5","pages":"Article 101039"},"PeriodicalIF":3.4,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144212820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rural digitalization and health outcomes of older adults in China","authors":"Kunkun Duan ,&nbsp;Jing Li","doi":"10.1016/j.hlpt.2025.101038","DOIUrl":"10.1016/j.hlpt.2025.101038","url":null,"abstract":"<div><div>This study investigates the relationship between rural digitalization and older adults' health conditions. Drawing on the China Longitudinal Aging Social Survey 2020 data, using ordinary least squares (OLS) regression analysis, instrumental variable (IV) methods, and propensity score matching (PSM), the present study finds that rural digitalization significantly improves both physical health (β = 0.295, <em>p</em> &lt; 0.001) and reduces depression propensity score (β = -1.540, <em>p</em> &lt; 0.001). Moreover, the impact of rural digitalization development on older adults' health exhibits differences: older adults (80+) and those using the internet gain more benefits; there is more remarkable support for the physical health of less educated older adults, while mental health support is more pronounced for those with higher education levels. The findings underscore the potential of rural digitalization to mitigate health disparities and advocate for inclusive digital policies tailored to vulnerable older populations.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"14 5","pages":"Article 101038"},"PeriodicalIF":3.4,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}