Pub Date : 2026-01-16DOI: 10.1016/j.hlpt.2026.101156
Ana Rita Sequeira , Marcello Antonini , Bernardo Andretti
<div><h3>Objective</h3><div>This study investigates the extent to which individual characteristics and preferences towards vaccine attributes and societal restrictions influence vaccination behaviour in a representative Brazilian population.</div></div><div><h3>Method</h3><div>We conducted a discrete choice experiment (DCE) involving 3,001 Brazilian respondents from July to September 2022 through an online panel. The DCE involved five vaccine features and two social restriction features. Participants were presented to a sequence of binary choices of hypothetical vaccination programs, with an option to opt-out. We performed multiple regression models to investigate the predictors of vaccination and opt-out decisions. We also performed a latent class logit model to estimate trade-offs between vaccination attributes and societal restrictions across groups.</div></div><div><h3>Results</h3><div>Our regression results identified that gender, religiosity, income, political orientation and trust in public health institutions were important predictors of vaccination decisions in Brazil. Our latent class models indicated significant heterogeneity and detected four main classes: (i) left-leaning, pro restrictions, who showed strong preferences for vaccine features such as its effectiveness (62.4%); (ii) left-leaning, pro mandates, who showed strong support for societal restrictions (19.5%); (iii) centrists, pragmatics, who were opposed to restrictions but supportive of vaccine features (11.4%); (iv) right-leaning, vaccine refusers, who showed a willingness to opt-out from vaccination programmes and did not show any preferences for vaccine features (6.7%).</div></div><div><h3>Conclusions</h3><div>Our findings suggest that the Brazilian population had overall high willingness to accept vaccines and displayed high trust in public health authorities. Nonetheless, the presence of a non-negligible proportion of cautious and hesitant groups may prevent the effectiveness of vaccination campaigns in the future.</div></div><div><h3>Lay summary</h3><div>This study investigated the factors that influence people’s decisions to get vaccinated in Brazil. We asked 3,001 participants to choose between different vaccination programs with various features, including vaccine effectiveness and the presence of social restrictions. We found that factors such as gender, income, religion, political views, and trust in public health institutions affected people’s vaccination decisions. The study also identified four groups: one strongly supports vaccines and their characteristics, one supports both vaccines and social restrictions, another prefers vaccines but dislikes restrictions, and a fourth is more hesitant-refuser about vaccines and more likely to opt out of vaccination. Overall, most Brazilians showed high trust in vaccines and public health advice. However, a small but significant group remains hesitant and refusing, which could pose challenges for future vaccination efforts
{"title":"Vaccination preferences and predictors of vaccine hesitancy in Brazil: A discrete choice experiment","authors":"Ana Rita Sequeira , Marcello Antonini , Bernardo Andretti","doi":"10.1016/j.hlpt.2026.101156","DOIUrl":"10.1016/j.hlpt.2026.101156","url":null,"abstract":"<div><h3>Objective</h3><div>This study investigates the extent to which individual characteristics and preferences towards vaccine attributes and societal restrictions influence vaccination behaviour in a representative Brazilian population.</div></div><div><h3>Method</h3><div>We conducted a discrete choice experiment (DCE) involving 3,001 Brazilian respondents from July to September 2022 through an online panel. The DCE involved five vaccine features and two social restriction features. Participants were presented to a sequence of binary choices of hypothetical vaccination programs, with an option to opt-out. We performed multiple regression models to investigate the predictors of vaccination and opt-out decisions. We also performed a latent class logit model to estimate trade-offs between vaccination attributes and societal restrictions across groups.</div></div><div><h3>Results</h3><div>Our regression results identified that gender, religiosity, income, political orientation and trust in public health institutions were important predictors of vaccination decisions in Brazil. Our latent class models indicated significant heterogeneity and detected four main classes: (i) left-leaning, pro restrictions, who showed strong preferences for vaccine features such as its effectiveness (62.4%); (ii) left-leaning, pro mandates, who showed strong support for societal restrictions (19.5%); (iii) centrists, pragmatics, who were opposed to restrictions but supportive of vaccine features (11.4%); (iv) right-leaning, vaccine refusers, who showed a willingness to opt-out from vaccination programmes and did not show any preferences for vaccine features (6.7%).</div></div><div><h3>Conclusions</h3><div>Our findings suggest that the Brazilian population had overall high willingness to accept vaccines and displayed high trust in public health authorities. Nonetheless, the presence of a non-negligible proportion of cautious and hesitant groups may prevent the effectiveness of vaccination campaigns in the future.</div></div><div><h3>Lay summary</h3><div>This study investigated the factors that influence people’s decisions to get vaccinated in Brazil. We asked 3,001 participants to choose between different vaccination programs with various features, including vaccine effectiveness and the presence of social restrictions. We found that factors such as gender, income, religion, political views, and trust in public health institutions affected people’s vaccination decisions. The study also identified four groups: one strongly supports vaccines and their characteristics, one supports both vaccines and social restrictions, another prefers vaccines but dislikes restrictions, and a fourth is more hesitant-refuser about vaccines and more likely to opt out of vaccination. Overall, most Brazilians showed high trust in vaccines and public health advice. However, a small but significant group remains hesitant and refusing, which could pose challenges for future vaccination efforts","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 3","pages":"Article 101156"},"PeriodicalIF":3.7,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080734","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}
Pub Date : 2026-01-15DOI: 10.1016/j.hlpt.2026.101165
Kamaljeet, Abhishek Vijukumar, Sourabh Kosey
Background
RWE is an essential complement to RCTs, enhancing external validity, reflect long-term outcomes, and reflect the everyday clinical practice. RWE is increasingly being integrated into the decision-making process of health technology assessment (HTA) agencies and payers worldwide; however, methodological, ethical, and operational barriers remain.
Aim
The aim of this review is to propose a five-pillar to support the systematic and transparent integration of RWE into pharmacoeconomic evaluation and to demonstrate policy relevance through cross-national case studies.
Methods
A narrative analysis was conducted, based on the literature identified in PubMed, Scopus, Web of science, and Google scholar (2015–2024), as well as policy documents obtained at HTA bodies. Inclusion criteria focused on studies an reports addressing the use of RWE in pharmacoeconomic or HTA. Sweden, Germany, and Canada were selected as the case studies to illustrate the registry-based, digital health-driven, and post-launch reimbursement models to RWE implementation. The five-pillar framework was developed through synthesis of these sources and cross-referencing with existing guidance, including ISPOR Good Practices, STaRT-RWE, CanREValue.
Findings
The proposed framework is structured around five pillars: data preparedness and infrastructure, methodological rigour, analytical integration in economic models, stakeholder alignment and transparency, and governance, ethics, and lifecycle feedback. The framework adds value beyond existing approaches by emphasizing data interoperability, ethical safeguards, and adaptive real-time reassessment. The case studies illustrated the enhancement of external validity in oncology (Sweden), the facilitation of adaptive reimbursement processes of digital health interventions (Germany), and the post-launch funding modification in rheumatology (Canada) through RWE.
Conclusion
RWE can be integrated in pharmacoeconomic analyses through a systematic, policy-relevant approach defined by the five-pillar framework. Despite the limitation associated with a narrative review design and the focus on high-income country examples, it sets up a basis on which future empirical validation in diverse contexts, including low- and middle-income countries. Such practices have the potential to enhance inclusiveness, transparency, and sustainability in healthcare decision-making within an era of value based care.
研究背景：随机对照试验是随机对照试验的重要补充，可增强外部效度，反映长期结果，并反映日常临床实践。RWE越来越多地被纳入世界各地卫生技术评估机构和付款人的决策过程；然而，方法、伦理和操作上的障碍仍然存在。本综述的目的是提出一个五大支柱，以支持将RWE系统和透明地整合到药物经济学评估中，并通过跨国案例研究证明政策相关性。方法基于PubMed、Scopus、Web of science和谷歌scholar（2015-2024）检索到的文献，以及HTA机构获取的政策文件，进行叙事分析。纳入标准侧重于在药物经济学或HTA中使用RWE的研究和报告。瑞典、德国和加拿大被选为案例研究，以说明基于注册的、数字健康驱动的和启动后的报销模式对RWE实施的影响。五支柱框架是通过综合这些资源并与现有指南（包括ISPOR良好实践、STaRT-RWE、CanREValue）交叉参考而开发的。建议的框架围绕五个支柱构建：数据准备和基础设施、方法严谨性、经济模型中的分析集成、利益相关者的一致性和透明度、治理、道德和生命周期反馈。该框架通过强调数据互操作性、道德保障和自适应实时重新评估，在现有方法之外增加了价值。案例研究表明，通过RWE提高了肿瘤学领域的外部有效性（瑞典），促进了数字健康干预措施的适应性报销流程（德国），以及风湿病学领域启动后的资金调整（加拿大）。结论rwe可以通过五支柱框架定义的系统的、与政策相关的方法纳入药物经济学分析。尽管叙述性审查设计存在局限性，而且侧重于高收入国家的例子，但它为未来在不同背景下（包括低收入和中等收入国家）进行实证验证奠定了基础。在以价值为基础的护理时代，这种做法有可能增强医疗保健决策的包容性、透明度和可持续性。
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Pub Date : 2026-01-10DOI: 10.1016/j.hlpt.2026.101155
Carin A. Uyl-de Groot , Nicolas S.H. Xander , Tom Belleman , Emily A. Burger , Robin Doeswijk , Isabelle Durand-Zaleski , Benjamin P. Geisler , Oliver Groene , Anne Hendrickx , Pia S. Henkel , Renaud Heine , Mirjana Huić , Mauro Melli , Kate Morgan , Monica Racovița , Gauthier Quinonez , Maureen P.M.H. Rutten-van Mölken , Tomáš Tesař , Frederick W. Thielen , Peter Schneider , Eline Aas
<div><h3>Objectives</h3><div>Disparities in access to potential innovative health technologies (pIHTs) persist across Europe due to differing healthcare budgets, pricing policies, and health technology assessment (HTA) practices. The ASCERTAIN project aims to reduce these inequalities by developing integrated pricing, cost-effectiveness, and reimbursement approaches that enhance affordability, long-term sustainability, and timely patient access.</div></div><div><h3>Methods</h3><div>The project applies a mixed-methods approach, including literature review, stakeholder surveys, interviews, and focus groups, to ensure relevance across diverse health systems. It integrates access-based pricing, value-driven HTA, and adaptable reimbursement models into a practical, open-access ACCESS2MEDS Toolbox. This includes access-based pricing frameworks, cost-effectiveness models, and budget impact and reimbursement analyses, all adaptable to country-specific conditions to reduce uncertainty and improve transparency. Tools are co-created with patients, developers, clinicians, and policymakers and will be tested and validated using three use cases representing high-impact areas of innovation: precision oncology medicines, cell and gene therapies, and next-generation sequencing tests.</div></div><div><h3>Results</h3><div>Outputs will include validated tools enabling improved evaluation of clinical benefit, cost-effectiveness, and financial sustainability, strengthening value-based decision-making across Europe. Innovative access- and outcome-based pricing strategies will support responsible innovation while encouraging fair reimbursement and improved budget control. Policy roadmaps will guide the adoption of equitable access models and support system-level implementation.</div></div><div><h3>Conclusions</h3><div>ASCERTAIN will provide a harmonized framework that balances cost control, innovation incentives, and patient-centered care. By facilitating consistent, evidence-based pricing and reimbursement decisions, the project supports fair and sustainable access to pIHTs across Europe, with continued multi-stakeholder collaboration driving its wider adoption and real-world impact.</div></div><div><h3>Public interest abstract</h3><div>Many lifesaving medical breakthroughs, like advanced cancer therapies and gene treatments, are becoming available, but not everyone in Europe can access them equally. Differences in healthcare funding and pricing decisions mean that patients in some countries wait much longer for the care they need. The ASCERTAIN project is working to change this. By bringing together patients, health technology developers, clinicians, and policymakers, the project is creating new tools to help health systems decide how to pay for cutting-edge technologies in a fair and affordable way. These tools also make sure that these technologies are paid for based on how well they work for patients in real life. By improving transparency and reducing financial pr
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Pub Date : 2026-01-10DOI: 10.1016/j.hlpt.2026.101154
Aregawi G. Gebremariam , Beidemaryam W. Admasu , Dereje Abegaz , Atnafu Gebremeskel Sore , Francesco Paolucci
Objectives
This study examined public preferences for COVID-19 vaccines in Russia to inform future pandemic strategies, contextualizing within the country’s unique historical and socio-political landscape.
Methods
A nationally representative Discrete Choice Experiment (DCE) was conducted with 3,010 Russian respondents. Participants evaluated hypothetical vaccine profiles varying across attributes: effectiveness, side-effect risk, protection duration, origin, approval time, social restrictions, and mandates. Preferences were analysed using a Multinomial Logit (MNL) model and a Latent Class Model (LCM) to capture heterogeneity.
Results
Respondents preferred vaccines with higher effectiveness (60%, 70% and 90% vs. 40%) and longer protection. Severe side effects significantly reduced vaccine appeal. Russian-made vaccines were strongly favoured, while EU, UK, and US vaccines were less preferred. Vaccines with shorter approval times were preferred. Less stringent social restrictions and mandates were also preferred. The LCM identified two classes: a pro-vaccine group (52%) responsive to both vaccine and policy attributes, and a non-supportive group (48%) more sceptical and likely to opt out. Trust in institutions, vaccine attitudes, and political values significantly influenced class membership.
Conclusions
COVID-19 vaccine preferences in Russia reflected concerns over efficacy, safety, origin, and governance. Nationalistic attitudes and historical mistrust toward foreign institutions may have shaped preferences. Policy tools such as mandates were more effective when paired with high-quality vaccines. Tailored communication and community-based engagement are essential to address diverse concerns and promote uptake.
Lay Summary
We asked over 3,000 people in Russia to choose between different COVID-19 vaccine options and related policies. People preferred vaccines that worked well, protected for longer, and had a low chance of serious side effects. Many strongly preferred vaccines made in Russia over those from other countries, showing pride in local science and possible distrust of foreign sources. They also liked vaccines that were approved quickly and linked to fewer social restrictions. We found two main groups: just over half were generally in favour of vaccination, while almost half were more doubtful and often chose not to vaccinate. Trust in government, healthcare, and political views were key factors in these decisions. To improve vaccine uptake in future health crises, it will be important to provide safe, effective vaccines and to communicate in ways that address the concerns of both supportive and sceptical groups.
本研究调查了俄罗斯公众对COVID-19疫苗的偏好，并结合该国独特的历史和社会政治环境，为未来的大流行战略提供信息。方法采用具有全国代表性的离散选择实验（DCE）对3010名俄罗斯受访者进行调查。与会者评估了不同属性的假设疫苗概况：有效性、副作用风险、保护持续时间、来源、批准时间、社会限制和授权。使用多项Logit （MNL）模型和潜在类别模型（LCM）分析偏好以捕获异质性。结果应答者对有效率较高（60%、70%和90% vs. 40%）和保护期较长的疫苗有较高的偏好。严重的副作用大大降低了疫苗的吸引力。俄罗斯制造的疫苗受到强烈青睐，而欧盟、英国和美国的疫苗则不那么受欢迎。批准时间较短的疫苗是首选。不那么严格的社会限制和规定也是可取的。LCM确定了两类：支持接种疫苗的群体（52%）对疫苗和政策属性都有反应，而不支持接种疫苗的群体（48%）更持怀疑态度，更有可能选择退出。对机构的信任、对疫苗的态度和政治价值观显著影响了班级成员。结论俄罗斯对covid -19疫苗的偏好反映了对有效性、安全性、来源和治理的担忧。民族主义态度和对外国机构的历史不信任可能形成了偏好。授权等政策工具与高质量疫苗相结合时更为有效。量身定制的沟通和基于社区的参与对于解决各种关切和促进吸收至关重要。我们让3000多名俄罗斯人在不同的COVID-19疫苗选择和相关政策之间做出选择。人们更喜欢那些效果好、保护时间长、产生严重副作用几率低的疫苗。与其他国家的疫苗相比，许多人更喜欢俄罗斯生产的疫苗，这显示出对当地科学的自豪感和可能对外国来源的不信任。他们还喜欢那些迅速获得批准、与社会限制联系较少的疫苗。我们发现了两个主要群体：刚刚超过一半的人普遍支持接种疫苗，而几乎一半的人持怀疑态度，往往选择不接种疫苗。对政府、医疗保健和政治观点的信任是这些决定的关键因素。为了在未来的卫生危机中提高疫苗的吸收率，重要的是提供安全、有效的疫苗，并以解决支持和怀疑群体关切的方式进行沟通。
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Pub Date : 2025-12-17DOI: 10.1016/j.hlpt.2025.101152
Ibrahim Alfayoumi , Mesfin G. Genie , Surachat Ngorsuraches
Objectives
The objective of this study was to examine how the US public traded off between COVID-19 vaccines and policy restrictions.
Methods
This study used data from an online-based discrete choice experiment (DCE) study on public preferences for COVID-19 vaccines and related policy restrictions. The study included five vaccine characteristics: effectiveness, duration of protection, risk of severe side effects, approval time, and country of origin, and two policy features: social activities restrictions and vaccine mandate for returning to work. Preferences were estimated using multinomial logit and latent class models.
Results
Overall results showed that people preferred vaccines with higher effectiveness, higher duration of protection, lower risk of severe side effects, and vaccines manufactured in the US. They preferred some or no restrictions of social activities relative to full lockdowns but preferred a vaccine mandate relative to “no mandate”. The latent class model revealed two distinct classes, including a “pro-vaccine” class (77 %) and a “vaccine-hesitant” class (23 %). Respondents with higher institutional trust, more positive attitudes towards vaccines, and greater personal and social exposure to COVID-19 were more likely to be pro-vaccine. This group was also characterized by a higher likelihood of being fully vaccinated and was less likely to be females.
Conclusions
This study demonstrated heterogeneity of preferences for COVID-19 vaccines and policy restrictions. These findings suggested the need for vaccination strategies and policy restrictions that are responsive to distinct population segments.
Public Interest Summary
This study explored how the public in the US made decisions about COVID-19 vaccines and policy restrictions. We used data from a survey that asked over 3000 adults to choose between different vaccine options and related policies, such as requiring vaccines for work or limiting social events. People generally preferred vaccines that were more effective, lasted longer, and had fewer side effects. They also preferred vaccines made in the US or Europe compared to those made in China. They preferred no or some restrictions of social activities but supported vaccine requirements for returning to work. The results showed that people had different preferences depending on their trust in institutions, previous experiences with COVID-19, and their attitudes towards vaccines. This information can help policymakers design future strategies that match what different groups of people prefer, potentially leading to more acceptance.
{"title":"Shots or shutdowns? Public preferences for COVID-19 vaccines and societal restrictions in the US","authors":"Ibrahim Alfayoumi , Mesfin G. Genie , Surachat Ngorsuraches","doi":"10.1016/j.hlpt.2025.101152","DOIUrl":"10.1016/j.hlpt.2025.101152","url":null,"abstract":"<div><h3>Objectives</h3><div>The objective of this study was to examine how the US public traded off between COVID-19 vaccines and policy restrictions.</div></div><div><h3>Methods</h3><div>This study used data from an online-based discrete choice experiment (DCE) study on public preferences for COVID-19 vaccines and related policy restrictions. The study included five vaccine characteristics: effectiveness, duration of protection, risk of severe side effects, approval time, and country of origin, and two policy features: social activities restrictions and vaccine mandate for returning to work. Preferences were estimated using multinomial logit and latent class models.</div></div><div><h3>Results</h3><div>Overall results showed that people preferred vaccines with higher effectiveness, higher duration of protection, lower risk of severe side effects, and vaccines manufactured in the US. They preferred some or no restrictions of social activities relative to full lockdowns but preferred a vaccine mandate relative to “no mandate”. The latent class model revealed two distinct classes, including a “pro-vaccine” class (77 %) and a “vaccine-hesitant” class (23 %). Respondents with higher institutional trust, more positive attitudes towards vaccines, and greater personal and social exposure to COVID-19 were more likely to be pro-vaccine. This group was also characterized by a higher likelihood of being fully vaccinated and was less likely to be females.</div></div><div><h3>Conclusions</h3><div>This study demonstrated heterogeneity of preferences for COVID-19 vaccines and policy restrictions. These findings suggested the need for vaccination strategies and policy restrictions that are responsive to distinct population segments.</div></div><div><h3>Public Interest Summary</h3><div>This study explored how the public in the US made decisions about COVID-19 vaccines and policy restrictions. We used data from a survey that asked over 3000 adults to choose between different vaccine options and related policies, such as requiring vaccines for work or limiting social events. People generally preferred vaccines that were more effective, lasted longer, and had fewer side effects. They also preferred vaccines made in the US or Europe compared to those made in China. They preferred no or some restrictions of social activities but supported vaccine requirements for returning to work. The results showed that people had different preferences depending on their trust in institutions, previous experiences with COVID-19, and their attitudes towards vaccines. This information can help policymakers design future strategies that match what different groups of people prefer, potentially leading to more acceptance.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 2","pages":"Article 101152"},"PeriodicalIF":3.7,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926951","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}
Pub Date : 2025-12-17DOI: 10.1016/j.hlpt.2025.101150
Fumu Wang , Jianjian Ding , Rongfa Li , Xiaochong Shen , Haiming Wang , Yuhui Wang
{"title":"The impact and challenges of diagnosis-related groups (DRGs) payment reform on china's healthcare system: A critical analysis","authors":"Fumu Wang , Jianjian Ding , Rongfa Li , Xiaochong Shen , Haiming Wang , Yuhui Wang","doi":"10.1016/j.hlpt.2025.101150","DOIUrl":"10.1016/j.hlpt.2025.101150","url":null,"abstract":"","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 2","pages":"Article 101150"},"PeriodicalIF":3.7,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791698","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}
Pub Date : 2025-12-16DOI: 10.1016/j.hlpt.2025.101151
Stefano Bruzzo-Gallardo , James A. Gillespie , Brian Kelly , Francesco Paolucci
Objectives
This study investigates how Australians make trade-offs between vaccine characteristics and social-restriction mandates to inform future pandemic preparedness policy. We identify attributes influencing vaccine uptake and assess how demographic and behavioural factors shape attitudes to vaccination in Australia's post-COVID-19 context.
Methods
We analysed 3004 Australian responses from the VaxPref international survey and discrete choice experiment (DCE). Participants completed 12 choice scenarios comparing hypothetical vaccines varying across seven attributes: five vaccine characteristics and two social-restriction mandates. Multinomial logit (MNL) and latent class (LC) models estimated preference parameters and identified population subgroups.
Results
Vaccine effectiveness was the strongest uptake driver, with preferences increasing progressively from 40 % to 90 % effectiveness. Safety concerns significantly reduced acceptance, and Western-manufactured vaccines (EU, UK, USA) were preferred over Chinese alternatives. Latent class analysis revealed two distinct groups: a pro-vaccine majority (Class 1) (81.6 %) and a minority (Class 2) (19.4 %) with a strong preference for the opt-out alternative across choice tasks. The latter demonstrated higher sensitivity to both positive and negative attributes, suggesting more analytical decision-making. Pro-vaccine class membership was associated with trust towards public health bodies, newspapers and social media, COVID-19 exposure, and right-leaning political self-placement, while risk aversion and cognitive skills were negatively associated.
Conclusions
Effective pandemic preparedness requires recognising heterogeneous decision-making approaches. While the pro-vaccine majority responds to institutional trust and simplified messaging, a minority requires detailed, transparent communication addressing specific concerns. Investment in vaccine effectiveness, safety monitoring, and differentiated communication strategies may be efficient policy approaches for increasing uptake.
{"title":"Understanding vaccine acceptance in Australia: Evidence from the VaxPref discrete choice experiment","authors":"Stefano Bruzzo-Gallardo , James A. Gillespie , Brian Kelly , Francesco Paolucci","doi":"10.1016/j.hlpt.2025.101151","DOIUrl":"10.1016/j.hlpt.2025.101151","url":null,"abstract":"<div><h3>Objectives</h3><div>This study investigates how Australians make trade-offs between vaccine characteristics and social-restriction mandates to inform future pandemic preparedness policy. We identify attributes influencing vaccine uptake and assess how demographic and behavioural factors shape attitudes to vaccination in Australia's post-COVID-19 context.</div></div><div><h3>Methods</h3><div>We analysed 3004 Australian responses from the VaxPref international survey and discrete choice experiment (DCE). Participants completed 12 choice scenarios comparing hypothetical vaccines varying across seven attributes: five vaccine characteristics and two social-restriction mandates. Multinomial logit (MNL) and latent class (LC) models estimated preference parameters and identified population subgroups.</div></div><div><h3>Results</h3><div>Vaccine effectiveness was the strongest uptake driver, with preferences increasing progressively from 40 % to 90 % effectiveness. Safety concerns significantly reduced acceptance, and Western-manufactured vaccines (EU, UK, USA) were preferred over Chinese alternatives. Latent class analysis revealed two distinct groups: a pro-vaccine majority (Class 1) (81.6 %) and a minority (Class 2) (19.4 %) with a strong preference for the opt-out alternative across choice tasks. The latter demonstrated higher sensitivity to both positive and negative attributes, suggesting more analytical decision-making. Pro-vaccine class membership was associated with trust towards public health bodies, newspapers and social media, COVID-19 exposure, and right-leaning political self-placement, while risk aversion and cognitive skills were negatively associated.</div></div><div><h3>Conclusions</h3><div>Effective pandemic preparedness requires recognising heterogeneous decision-making approaches. While the pro-vaccine majority responds to institutional trust and simplified messaging, a minority requires detailed, transparent communication addressing specific concerns. Investment in vaccine effectiveness, safety monitoring, and differentiated communication strategies may be efficient policy approaches for increasing uptake.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 2","pages":"Article 101151"},"PeriodicalIF":3.7,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791695","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}
Pub Date : 2025-12-12DOI: 10.1016/j.hlpt.2025.101149
Monica Moroni , Lisa Novello , Giulia Malfatti , Lorenzo Gios , Roberto Bonmassari , Maurizio Del Greco , Massimiliano Maines , Michele Moretti , Sandro Inchiostro , Federica Romanelli , Elisabetta Racano , Tania Elena Maggi , Valentina Fiabane , Adele Compagnone , Lorena Filippi , Roberta Pasquini , Marta Betta , Lucia Pavanello , Andrea Manica , Diego Cagol , Giuseppe Jurman
Background
The integration of Artificial Intelligence (AI) into healthcare services and technologies offers substantial potential for personalised medicine. The Autonomous Province of Trento (Italy) provides a unique setting for AI-driven healthcare research, due to its unified healthcare system, advanced IT infrastructure, and strong public-private collaborations. This paper explores an initiative aimed at improving healthcare accessibility and promoting innovation through AI in three clinical domains: Cardiology, Diabetic Retinopathy, and Paediatric Ophthalmology.
Methods
The project employs a structured approach, involving specialised working groups addressing clinical needs, AI techniques, legal and ethical compliance and data management. The initiative aims to develop predictive models aligned with European and national data protection regulations.
Results
Three primary clinical objectives were defined: estimating individual risk profiles in heart failure patients, personalising screening intervals for diabetic retinopathy, and supporting early diagnosis of anterior segment opacities in infants. Data relevant for the selected outcomes were identified. A dedicated platform for compliant, secure and structured access to data was developed. A data analysis plan was designed, including data processing, models selection, optimization and evaluation. All research protocols were approved by the local Ethics Committee.
Discussion
The initiative investigates the AI potential to improve clinical outcomes and establish a sustainable, personalised healthcare system. Key challenges include data accessibility, regulatory compliance, and adherence to ethical standards. The project's comprehensive framework offers a model for broader applications. Future research will focus on model validation and expanding the initiative to other clinical domains.
Public Interest Summary
This article presents the "Digital Health and Artificial Intelligence" project, an initiative funded by The Autonomous Province of Trento (Italy) to enhance healthcare accessibility and foster innovative healthcare models using technology and Artificial Intelligence (AI). The current work presents the design and preparatory work for the implementation of three AI-based solutions for research purposes, encompassing three areas: i) Cardiology, ii) Diabetic Retinopathy, and iii) Paediatric Ophthalmology. The paper outlines the legal and organizational frameworks, mathematical modelling and data management emphasising the necessity of cross-disciplinary endeavour and collaboration. Overall, this project represents a forward-looking initiative promoting research conducted on citizen data to address healthcare needs through innovative AI-driven approaches in line with legal and ethical standards.
{"title":"Digital health and artificial intelligence: a research approach to enable sustainable and personalised local healthcare","authors":"Monica Moroni , Lisa Novello , Giulia Malfatti , Lorenzo Gios , Roberto Bonmassari , Maurizio Del Greco , Massimiliano Maines , Michele Moretti , Sandro Inchiostro , Federica Romanelli , Elisabetta Racano , Tania Elena Maggi , Valentina Fiabane , Adele Compagnone , Lorena Filippi , Roberta Pasquini , Marta Betta , Lucia Pavanello , Andrea Manica , Diego Cagol , Giuseppe Jurman","doi":"10.1016/j.hlpt.2025.101149","DOIUrl":"10.1016/j.hlpt.2025.101149","url":null,"abstract":"<div><h3>Background</h3><div>The integration of Artificial Intelligence (AI) into healthcare services and technologies offers substantial potential for personalised medicine. The Autonomous Province of Trento (Italy) provides a unique setting for AI-driven healthcare research, due to its unified healthcare system, advanced IT infrastructure, and strong public-private collaborations. This paper explores an initiative aimed at improving healthcare accessibility and promoting innovation through AI in three clinical domains: Cardiology, Diabetic Retinopathy, and Paediatric Ophthalmology.</div></div><div><h3>Methods</h3><div>The project employs a structured approach, involving specialised working groups addressing clinical needs, AI techniques, legal and ethical compliance and data management. The initiative aims to develop predictive models aligned with European and national data protection regulations.</div></div><div><h3>Results</h3><div>Three primary clinical objectives were defined: estimating individual risk profiles in heart failure patients, personalising screening intervals for diabetic retinopathy, and supporting early diagnosis of anterior segment opacities in infants. Data relevant for the selected outcomes were identified. A dedicated platform for compliant, secure and structured access to data was developed. A data analysis plan was designed, including data processing, models selection, optimization and evaluation. All research protocols were approved by the local Ethics Committee.</div></div><div><h3>Discussion</h3><div>The initiative investigates the AI potential to improve clinical outcomes and establish a sustainable, personalised healthcare system. Key challenges include data accessibility, regulatory compliance, and adherence to ethical standards. The project's comprehensive framework offers a model for broader applications. Future research will focus on model validation and expanding the initiative to other clinical domains.</div></div><div><h3>Public Interest Summary</h3><div>This article presents the \"Digital Health and Artificial Intelligence\" project, an initiative funded by The Autonomous Province of Trento (Italy) to enhance healthcare accessibility and foster innovative healthcare models using technology and Artificial Intelligence (AI). The current work presents the design and preparatory work for the implementation of three AI-based solutions for research purposes, encompassing three areas: i) Cardiology, ii) Diabetic Retinopathy, and iii) Paediatric Ophthalmology. The paper outlines the legal and organizational frameworks, mathematical modelling and data management emphasising the necessity of cross-disciplinary endeavour and collaboration. Overall, this project represents a forward-looking initiative promoting research conducted on citizen data to address healthcare needs through innovative AI-driven approaches in line with legal and ethical standards.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 2","pages":"Article 101149"},"PeriodicalIF":3.7,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791699","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}
Pub Date : 2025-12-10DOI: 10.1016/j.hlpt.2025.101148
Yevgen Bogodistov , Mesfin Genie , Ayman Fouda
<div><h3>Objectives</h3><div>Vaccine acceptance is often studied in relation to clinical characteristics such as efficacy, safety, and side effects. In this study, we argue that acceptance is also influenced by the psychological distance (PD) at which vaccine information is communicated. Specifically, we investigate and compare how temporal, social, spatial, and hypothetical dimensions of PD shape individuals’ willingness to accept a vaccine in Singapore and South Korea.</div></div><div><h3>Methods</h3><div>We conducted a Discrete Choice Experiment (DCE) in Singapore and South Korea to assess how variations in PD framing influence vaccination decisions. The design allowed us to test both direct effects and interactions across the four PD dimensions, capturing linear and non-linear influences on decision-making.</div></div><div><h3>Results</h3><div>Our findings provide substantive but not uniform support for the proposed role of psychological distance in shaping vaccine preferences. While several effects are consistent with rational evaluation of vaccine attributes (e.g., higher effectiveness, longer protection, and fewer societal restrictions), we also identify interaction and non-linear patterns that suggest more complex perceptual processes beyond immediate utility. Most theorised PD effects were supported; however, the expected spatial-distance relationship was not observed, likely because respondents’ perceptions of vaccine quality and geopolitical trustworthiness outweighed simple geographical proximity.</div></div><div><h3>Conclusions</h3><div>The way vaccine information is communicated, particularly in terms of psychological distance, can significantly influence the public’s response. We recommend that policymakers not only consider each PD dimension in their messaging but also strive for consistency across them. Communicating vaccine-related information at an appropriate and congruent psychological distance may enhance public trust and increase vaccine uptake.</div></div><div><h3>Public interest summary</h3><div>Why people accept or reject vaccines is not just about how effective or safe the vaccine is; it also depends on how the information is communicated. We explored how psychological distance (how close or far something feels in terms of time, social connection, location, or likelihood) affects vaccine decisions in Singapore and South Korea. Using a Discrete Choice Experiment, we found that people’s willingness to be vaccinated was influenced by practical factors (such as how long a vaccine had been tested) and by how near or far the message made the vaccine seem. Interestingly, geographical distance did not matter as much, possibly because political impressions of vaccine-producing countries were more important. The study shows that clear, consistent, and relatable communication can make a real difference. Policymakers who present vaccine information in ways that feel close and relevant to people’s everyday lives may boost public tru
{"title":"Understanding vaccine acceptance through construal-level theory of psychological distance: Evidence from Singapore and South Korea","authors":"Yevgen Bogodistov , Mesfin Genie , Ayman Fouda","doi":"10.1016/j.hlpt.2025.101148","DOIUrl":"10.1016/j.hlpt.2025.101148","url":null,"abstract":"<div><h3>Objectives</h3><div>Vaccine acceptance is often studied in relation to clinical characteristics such as efficacy, safety, and side effects. In this study, we argue that acceptance is also influenced by the psychological distance (PD) at which vaccine information is communicated. Specifically, we investigate and compare how temporal, social, spatial, and hypothetical dimensions of PD shape individuals’ willingness to accept a vaccine in Singapore and South Korea.</div></div><div><h3>Methods</h3><div>We conducted a Discrete Choice Experiment (DCE) in Singapore and South Korea to assess how variations in PD framing influence vaccination decisions. The design allowed us to test both direct effects and interactions across the four PD dimensions, capturing linear and non-linear influences on decision-making.</div></div><div><h3>Results</h3><div>Our findings provide substantive but not uniform support for the proposed role of psychological distance in shaping vaccine preferences. While several effects are consistent with rational evaluation of vaccine attributes (e.g., higher effectiveness, longer protection, and fewer societal restrictions), we also identify interaction and non-linear patterns that suggest more complex perceptual processes beyond immediate utility. Most theorised PD effects were supported; however, the expected spatial-distance relationship was not observed, likely because respondents’ perceptions of vaccine quality and geopolitical trustworthiness outweighed simple geographical proximity.</div></div><div><h3>Conclusions</h3><div>The way vaccine information is communicated, particularly in terms of psychological distance, can significantly influence the public’s response. We recommend that policymakers not only consider each PD dimension in their messaging but also strive for consistency across them. Communicating vaccine-related information at an appropriate and congruent psychological distance may enhance public trust and increase vaccine uptake.</div></div><div><h3>Public interest summary</h3><div>Why people accept or reject vaccines is not just about how effective or safe the vaccine is; it also depends on how the information is communicated. We explored how psychological distance (how close or far something feels in terms of time, social connection, location, or likelihood) affects vaccine decisions in Singapore and South Korea. Using a Discrete Choice Experiment, we found that people’s willingness to be vaccinated was influenced by practical factors (such as how long a vaccine had been tested) and by how near or far the message made the vaccine seem. Interestingly, geographical distance did not matter as much, possibly because political impressions of vaccine-producing countries were more important. The study shows that clear, consistent, and relatable communication can make a real difference. Policymakers who present vaccine information in ways that feel close and relevant to people’s everyday lives may boost public tru","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 2","pages":"Article 101148"},"PeriodicalIF":3.7,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791694","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}
Health knowledge is crucial for preventing or delaying frailty, yet the interplay between knowledge and frailty remains unclear in the oldest-old population, where frailty may influence what and how individuals learn about health.
Objective
To investigate the relationship between health knowledge and prefrailty among individuals aged 85 and older, using real-world data from IoT-based health quizzes.
Methods
Eighty-three community-dwelling adults aged ≥85 participated in tablet-based quizzes on 180 health topics, generating over 24,000 responses between November 2020 and December 2022. Missing data were addressed through multiple imputation. A convergent mixed-methods approach combined ridge regression to identify knowledge areas associated with frailty and topic modeling to extract latent health themes.
Results
Prefrail individuals exhibited greater knowledge of acute and condition-specific topics (e.g., heat stroke, blood pressure), while broader health themes (e.g., disease prevention, long-term nutrition) were similarly distributed across frailty groups. No topics were identified where non-frail individuals consistently outperformed pre-frail counterparts.
Conclusions
Frailty may shape health knowledge by prompting a goal-driven, selective retention of immediately relevant information, rather than indicating a general knowledge decline. IoT-generated, ecologically valid data, analyzed through a mixed methods lens, offers promising insights to inform needs-based health education strategies for both frail and non-frail oldest-old individuals.
{"title":"Prefrailty and health knowledge in the Oldest-Old: A mixed-methods analysis using IoT-based health quizzes","authors":"Yukari Yamada , Tadahisa Okuda , Tomoe Uchida , Tatsuyoshi Ikenoue , Jun Otsuka , Takeo Nakayama , Shingo Fukuma","doi":"10.1016/j.hlpt.2025.101147","DOIUrl":"10.1016/j.hlpt.2025.101147","url":null,"abstract":"<div><h3>Scientific abstract Background</h3><div>Health knowledge is crucial for preventing or delaying frailty, yet the interplay between knowledge and frailty remains unclear in the oldest-old population, where frailty may influence what and how individuals learn about health.</div></div><div><h3>Objective</h3><div>To investigate the relationship between health knowledge and prefrailty among individuals aged 85 and older, using real-world data from IoT-based health quizzes.</div></div><div><h3>Methods</h3><div>Eighty-three community-dwelling adults aged ≥85 participated in tablet-based quizzes on 180 health topics, generating over 24,000 responses between November 2020 and December 2022. Missing data were addressed through multiple imputation. A convergent mixed-methods approach combined ridge regression to identify knowledge areas associated with frailty and topic modeling to extract latent health themes.</div></div><div><h3>Results</h3><div>Prefrail individuals exhibited greater knowledge of acute and condition-specific topics (e.g., heat stroke, blood pressure), while broader health themes (e.g., disease prevention, long-term nutrition) were similarly distributed across frailty groups. No topics were identified where non-frail individuals consistently outperformed pre-frail counterparts.</div></div><div><h3>Conclusions</h3><div>Frailty may shape health knowledge by prompting a goal-driven, selective retention of immediately relevant information, rather than indicating a general knowledge decline. IoT-generated, ecologically valid data, analyzed through a mixed methods lens, offers promising insights to inform needs-based health education strategies for both frail and non-frail oldest-old individuals.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"15 2","pages":"Article 101147"},"PeriodicalIF":3.7,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841018","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}
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