Search Results (2,039)

Background: In Canada, racialized communities, including African, Caribbean, and Black (ACB) people, are disproportionately affected by HIV and COVID-19. Experiencing multiple forms of discrimination in healthcare settings compromises care engagement and health outcomes. The objective of this study was to assess the forms of discrimination ACB people experienced during the COVID-19 pandemic, discrimination levels experienced before and during the pandemic and the demographic factors associated with the increased experiences of discrimination among ACB people when accessing healthcare services during the pandemic. Methods: Data were collected via an online survey co-led by the Public Health Agency of Canada, University of Ottawa, ACB community leaders and researchers across Canada. Participants were recruited via email contact. To be eligible, a participant had to be living in Canada, be aged 18 years or older, be able to read English or French, and self-identify as an ACB individual. The survey captured information on access to health services and experiences of multiple forms of discrimination before and during the pandemic. We used multivariable logistic regression to identify factors associated with discrimination. Results: Of 1556 participants, 39.6% were aged 25–39, 42.7% were resident in Ontario, and 63.2% were of African origin. Prior to the COVID-19 pandemic, 62.1% reported having experienced at least one form of discrimination in a healthcare setting. During the COVID-19 pandemic, over 66% reported having experienced at least a form of discrimination, with 25% reporting a perceived increase in the frequency with which they experienced discrimination. The perceived increase in the frequency of discrimination was 10.8%, 15.3%, 15.9%, 17.0%, 18.1%, 18.7%, and 31.2% among participants who reported having experienced sexual orientation-, gender-, substance use-, disability-, age-, economic status-, and race-based discrimination, respectively. In the multivariate logistic regression, the odds of reporting increased experiences of discrimination in participants aged 50 and above were 0.38 times (95%CI: 0.21, 0.69) those in participants who were 31–40 years of age. Conclusions: The proportion of participants who reported an increased experience of discrimination during the pandemic was high. Although there is variation in levels of experienced discrimination, the different forms of discrimination (race-, gender-, sexual orientation-, substance use-, economic status-, disability- and age-based discrimination) that participants experienced are alarming. This underscores the need for concerted efforts to address multiple forms of discrimination in healthcare settings to improve care engagement and health equity among ACB communities. There was a significant association between perceived increased experience of discrimination and only one sociodemographic factor—older age (50 and above); other factors contributing to participants’ perceived increased experience of discrimination when accessing healthcare services need to be explored. Full article

The study investigates the interrelationship between the performance of the regional economy in Italy and the multidimensionality of wellbeing, as defined by the ISTAT Benessere Equo e Sostenibile (BES) model. Based on panel data from 19 Italian regions and 2 autonomous provinces—Trentino and Bolzano (2012–2023)—the research aims to explore whether there is a link between regional GDP and the three BES dimensions: Benessere (B), Equità (E), and Sostenibilità (S). The innovative contribution of this paper is not the creation of a novel theoretical model, but a multilayered empirical approach that combines panel data methods, machine learning, and clustering. This approach makes it possible to reveal nonlinearities, complex interactions, and regional heterogeneity in BES–GDP relationships. The analysis of the Benessere dimension based on k-Nearest Neighbors reveals nonlinear dynamics related to health, mobility, security, digital access, and socio-economic conditions. Furthermore, cluster analysis identifies territorial development regimes according to the Benessere dimension. The Equità dimension is estimated using boosting regression and clustering models that emphasize the role of income, poverty risk, healthcare pressure, labour-market participation, youth exclusion, deprivation, and access to essential services. Finally, the Sostenibilità dimension is explored using boosting regression and random forest models to estimate interactions among environmental quality, climate stress, energy transition, innovation, digital skills, service reliability, and regional economic performance. The findings demonstrate a structural connection between well-being, equity, sustainability, and the economic performance of Italian regions. The results also confirm the hypothesis that Italy has multiple development regimes that differ geographically. Full article

Background: Gender discrimination in sport remains a persistent global issue, reflected in women’s limited participation, leadership representation, media visibility, salary equity, and personal safety. These forms of discrimination also negatively affect athletes’ psychological well-being, mental health, and overall sports experience. Despite growing scholarly attention over the past three decades, a comprehensive quantitative synthesis of this research area has been lacking. Methodology: A bibliometric analysis of 397 peer-reviewed documents published between 1995 and 2026 was conducted using the Scopus database. Data were analysed through the Bibliometric R package 4.2.1 and Biblioshiny interface. Science-mapping techniques including keyword co-occurrence, thematic clustering, thematic evolution, and collaboration network analysis were combined with performance indicators such as annual publication output, leading sources, author productivity, and citation impact. Results: Scientific production increased markedly after the mid-2010s, involving 187 sources and 1106 authors, with rising collaboration and citation influence. Core research themes included gender inequality, leadership exclusion, media representation, harassment and abuse, and structural discrimination in sports systems. Importantly, many of these themes are directly linked to reduced athlete well-being, including increased stress, anxiety, and decreased participation. Recent thematic developments highlighted intersectionality, safeguarding, inclusion, governance, and athlete welfare. Conclusion: Research on discrimination against women in sport has evolved into a multidisciplinary, policy-relevant field. Addressing gender discrimination is essential not only to achieving equity but also to improving athletes’ subjective well-being and long-term participation in sport. However, significant gaps remain, particularly in Global South contexts and intervention-based studies, indicating the need for stronger evidence-driven strategies to advance gender equity, inclusion, and ethical governance in sport. Full article

Background/Objectives: Cancer patterns in low-resource and crisis-affected settings are poorly characterized, particularly among socioeconomically vulnerable populations. This study aimed to describe cancer distribution, age at diagnosis, and barriers to care among patients presenting to a non-governmental organization (NGO) in Tripoli, Lebanon. Methods: We conducted a retrospective analysis of patients with histopathologically confirmed cancers presenting to a single NGO. Sociodemographic, clinical, and behavioral data were extracted from medical records. Socioeconomic status (SES) was assessed using a validated composite scale. Age-standardized proportions (ASPs) were calculated using GLOBOCAN and WHO standard weights. Barriers to care were categorized into financial, geographic, system-level, and sociocultural domains. Associations were assessed using chi-square tests and regression models. Results: Breast cancer was the most common malignancy (32.0%), followed by colorectal (CRC: 9.8%). A total of 440 patients were included. Colorectal cancer (CRC) was the second-most common malignancy, with 37% of cases occurring before age 50. Breast cancer accounted for nearly half of female cancers. Smoking-related malignancies, particularly bladder and lung cancers, were prominent. Sex differences were cancer-specific, with male sex associated with bladder cancer but not overall cancer distribution. Barriers to care were highly prevalent: 97.3% reported at least one financial barrier, 95.4% system-level barriers, and 72.4% geographic barriers. Low SES was significantly associated with geographic barriers (p < 0.001). Conclusions: Cancer patterns in this vulnerable population are characterized by early-onset disease, a high burden of smoking-related cancers, and pervasive barriers to care. These findings highlight the importance of integrating SES and access-related variables into cancer surveillance systems and support the development of targeted, equity-focused interventions. Full article

Background/Objectives: Obesity is a chronic, relapsing disease with a widening gap between clinical need and the availability of specialist care. Artificial intelligence (AI) may enable earlier risk detection, more precise phenotyping, and scalable behavioural support across obesity treatment pathways. This narrative review synthesises contemporary AI applications across the obesity care continuum and evaluates their translational readiness. Methods: A targeted search of PubMed/MEDLINE and Google Scholar (January 2024–January 2026) was conducted, complemented by citation chaining. Evidence was synthesised across four domains: (1) risk prediction and screening, (2) environmental and behavioural determinants, (3) multimodal phenotyping and precision stratification, and (4) AI-enabled lifestyle interventions and behavioural coaching (AIBC). Results: Electronic health record (EHR)-based models demonstrate clinically useful discrimination for early risk identification. Multimodal approaches refine stratification beyond body mass index (BMI)-centric classification. AI-enabled behavioural coaching (AIBC) platforms show emerging evidence of clinically meaningful weight loss, including non-inferiority to human coaching; however, long-term effectiveness, generalisability, and equity remain insufficiently established. Conclusions: AI is positioned to become a core enabler of personalised obesity pathways. Safe translation requires external validation, bias auditing, transparent reporting, human oversight, and post-deployment surveillance aligned with clinical guidelines and regulatory expectations. Full article

Background: Artificial intelligence (AI) is reshaping oncology at every stage of the cancer care pathway, from population-level screening through molecular diagnosis, treatment planning, and post-treatment surveillance. Despite an exponential growth in AI oncology publications exceeding 5000 peer-reviewed studies annually, a critical and persistent gap separates demonstrated algorithmic performance from genuine patient benefit. Most published evidence derives from retrospective, single-institution studies conducted in curated dataset environments that systematically differ from real-world clinical deployment conditions. This comprehensive review examines the translational maturity of AI applications across 18 major malignancies, providing an evidence-stratified, cross-cancer assessment of where AI has fulfilled, approaches, or remains far from fulfilling its transformative potential in oncological care. Methods: A structured narrative review was conducted across PubMed/MEDLINE, Embase, IEEE Xplore, and the Cochrane Library, supplemented by regulatory grey literature including FDA 510(k) decision summaries, CE Technical Files, and ClinicalTrials.gov. Search terms combined cancer site-specific terminology with AI methodology terms and translational outcome descriptors. Studies were only included if they applied an AI or machine learning methodology to a defined clinical oncological task, reported a clearly specified performance evaluation, and involved human subjects or human-derived clinical data. Evidence quality was assessed using QUADAS-2, PROBAST, and Cochrane RoB 2. A five-tier translational readiness framework, grounded in the NIH T0–T4 translational spectrum and CONSORT-AI/SPIRIT-AI guidelines, was applied a priori to enable cross-cancer comparison. A rigorous distinction was maintained between diagnostic accuracy and clinical utility, defined as demonstrated impact on clinical decision-making or patient-centered outcomes. Results: Across all 18 malignancies, AI development varied profoundly by cancer type. Breast cancer and prostate cancer (Tier 1) represent the most mature AI ecosystems, with multiple FDA-cleared tools for mammographic screening and digital pathology achieving prospective multi-institutional validation; however, randomized evidence demonstrating reduced cancer-specific mortality remains absent. Lung, hepatocellular, and melanoma AI (Tier 2) have achieved regulatory milestones but face documented performance disparities across demographic subgroups, including DermaSensor’s 20.7% specificity in primary care settings and HCC model failures in non-viral disease etiologies. Colorectal, glioma, pancreatic, and ovarian cancers (Tier 3) exhibit technical maturity without clinical clarity: colorectal CADe systems increase adenoma detection but meta-analyses of 18,232 patients across 21 RCTs fail to demonstrate improvement in advanced neoplasia detection or cancer incidence reduction. A full study-level presentation of pooled estimates, confidence intervals, and heterogeneity statistics for each cited randomized evidence base across all cancer types would extend beyond the intended scope and format of this cross-cancer narrative review. Gastric, esophageal, cervical, bladder, head and neck, and endometrial cancers (Tier 4) demonstrate promising single-institutional or geographically restricted results without multi-institutional external validation, particularly notable for cervical cancer AI’s transformative potential in low- and middle-income countries constrained by absent regulatory frameworks. Hematologic malignancies, sarcoma, and pediatric solid tumors (Tier 5) face structural barriers, workflow incompatibility in hematopathology, extreme rarity in sarcoma (>70 subtypes, <15,000 US cases annually), and irreducible ethical constraints in pediatric data governance, that cannot be resolved through algorithmic refinement alone. Conclusions: Oncological AI has not yet fulfilled its clinical promise. Across all five translational tiers, a single finding is consistent: diagnostic accuracy is not a surrogate for patient benefit. AI tools with high sensitivity and specificity have repeatedly failed to demonstrate equivalent reductions in cancer-specific mortality, overdiagnosis, or procedural harm under real-world outcome scrutiny. Simultaneously, documented performance disparities across races, ethnicity, disease etiology, and geographic setting reveal that current AI systems risk amplifying the very health inequities they are positioned to resolve. Bridging this translational gap requires three coordinated systemic shifts: regulatory frameworks mandating post-market outcome surveillance as a condition of clinical clearance; prospective trial designs measuring patient-centered endpoints rather than diagnostic concordance alone; and sustained infrastructure investment in federated data governance, demographically inclusive training datasets, and LMIC-accessible regulatory pathways. AI holds genuine potential to reduce cancer mortality on a global scale—but only if held to the evidentiary and equity standards that the stakes of oncological care demand. Full article

International literature has documented a sustained increase in female representation in higher education; however, less is known about how this process unfolds in segmented and highly privatized systems such as Chile’s. Evidence also remains limited on how gender parity varies across institutional types and disciplinary fields. This study examines the evolution of the Gender Parity Index (GPI) in Chilean universities between 2010 and 2024, disaggregating trends by institutional subsystem and field of knowledge. Using administrative data from the Higher Education Information System and a longitudinal panel of 49 universities, the analysis combines descriptive indicators and mixed-effects models to identify long-term trajectories. The results show a sustained increase in female participation in first-year enrollment, total enrollment, and undergraduate graduation. Institutional patterns differ markedly: increases are strongest in non-traditional private universities, more gradual in state universities, and relatively stable in traditional private institutions. At the disciplinary level, persistent horizontal segregation remains evident, with female overrepresentation in education, health, and social sciences, and male predominance in technology-related fields. These findings provide novel longitudinal evidence on gender stratification in Chilean and Latin American higher education and underscore the need for institutionally differentiated gender equity policies aligned with Sustainable Development Goals 4 and 5. Full article

Background/Objectives: Women+ (e.g., women and individuals assigned female at birth) experience disproportionate health risks and persistent gaps in access to care. Women+ health research remains significantly underfunded and understudied, contributing to inequities in diagnosis, treatment, and outcomes. This study aims to collaboratively identify and prioritize the most pressing unanswered research questions related to women+ health in the Maritime provinces of Canada. Methods: This study will use a modified Priority Setting Partnership (PSP) methodology based on the James Lind Alliance framework. A mixed-methods participatory approach will be used, including bilingual online surveys (French, English) and a one-day consensus workshop. Participants will include women+, healthcare professionals, researchers, policymakers, and the public residing in the Maritime provinces (Nova Scotia, New Brunswick, and Prince Edward Island). An initial survey will collect research uncertainties through open-ended questions. A second survey will rank verified uncertainties, followed by a facilitated workshop to achieve consensus on the Top 10 research priorities. Descriptive statistics will summarize participant demographics. Anticipated Results: This project is expected to generate a collaboratively developed Top 10 list of research priorities for women+ health in the Maritimes, which will be used to prioritize future research related to women+ health. Conclusions: By centering women+ voices and engaging diverse interest holders, this study will establish a shared regional research agenda to guide future research, funding, and policy initiatives for women+ health research. Full article

Background: Robotic-assisted surgery (RAS) has progressively expanded in gynecologic practice. Although its technical advantages are recognized, its economic sustainability and equitable accessibility remain debated. Methods: This clinical update provides a critical narrative review of current evidence on RAS in gynecology, integrating data on clinical outcomes, cost-effectiveness, diffusion patterns, and health equity across different healthcare settings. Results: In both benign and oncologic indications, RAS demonstrates consistent perioperative advantages over open surgery, including reduced blood loss, shorter hospital stay, and lower conversion rates. In routine cases, outcomes are largely comparable to conventional laparoscopy. However, robotic approaches appear particularly beneficial in complex scenarios, such as obesity, advanced malignancy, and technically demanding procedures. Economic evidence is heterogeneous. Short-term hospital-based studies report higher direct costs for RAS, especially in benign surgery. Conversely, cost–utility models in oncologic settings suggest that RAS may achieve acceptable cost-effectiveness when long-term outcomes, quality-adjusted life years, and institutional volume are considered. Accessibility remains strongly influenced by reimbursement policies, procedural volume, infrastructure, and workforce training. In the absence of structured reimbursement frameworks, robotic surgery may contribute to socioeconomic and geographic disparities. Conclusions: RAS represents an important component of modern gynecologic surgery, particularly in high-complexity and high-risk cases in which its technical advantages may translate into meaningful perioperative benefit. Its long-term sustainability depends on appropriate patient selection, institutional volume, reimbursement models, and health system organization. Future research incorporating long-term and societal economic perspectives is required to support balanced and equitable implementation. Full article

The COVID-19 pandemic generated an unprecedented volume of spatially and temporally resolved data, enabling rapid development of spatio-temporal models for surveillance, forecasting, and policy support. However, the evolution, geographic distribution, and equity implications of these models remain insufficiently synthesized. This study presents a global systematic review of 363 peer-reviewed studies published between January 2020 and August 2025 using publicly available data. Following PRISMA 2020 guidelines, studies were classified by geographic scale, modeling approach, data streams, and analytical purpose. The results indicate that Bayesian and compartmental models remained dominant throughout the pandemic, although methodological diversity increased over time with the growing use of machine learning and hybrid frameworks integrating mobility, environmental, and socio-demographic data. Data integration was more common than previously reported. Approximately 30% of studies relied on a single data stream, while 70% incorporated multiple sources, although most multi-source approaches combined only two data types and relatively few studies integrated three or more. Geographic coverage was uneven, with a strong concentration of studies in high-income regions and persistent underrepresentation of low- and middle-income contexts. Models incorporating finer spatial scales and socio-demographic variables more frequently supported geographically targeted interpretation of risk, vulnerability, testing access, and intervention needs. Overall, the findings highlight the importance of multi-source data integration, improved geographic representativeness, and transparent uncertainty communication, alongside the need for FAIR-aligned and equity-aware data infrastructures to strengthen future pandemic preparedness. Full article

The United States faces a worsening maternal mortality crisis that starkly contrasts with trends in other high-income nations. Maternal mortality rates (MMRs) have more than doubled over the past two decades, rising from 9.65 deaths per 100,000 live births in 1999–2002 to 23.6 in 2018–2021, with approximately 700 deaths annually. Black and American Indian/Alaska Native women experience maternal mortality rates two to three times higher than their White counterparts, reflecting persistent structural inequities rather than biological differences. This narrative review synthesizes current evidence on the underlying drivers of racial inequities in maternal mortality and evaluates evidence-based interventions and policy strategies to address these disparities. A comprehensive literature review between 2000 and 2025 was conducted using databases including PubMed, Scopus, Web of Science, and Google Scholar, focusing on studies examining clinical, social, and structural determinants of maternal health outcomes, as well as evidence-based interventions and maternal health policy. Targeted searches of policy reports and grey literature were also performed to identify relevant policy initiatives and system-level interventions. Key contributors to disparities include underlying health conditions, postpartum mental health inequities, provider shortages, and limited access to postpartum care, with pregnancy-associated breast cancer (PABC) representing a less common but clinically significant risk factor that warrants further investigation in the context of racial inequities. Structural racism and socioeconomic disparities further exacerbate inequities through differential access to care, treatment bias, and barriers to healthcare utilization. System-level challenges, including workforce shortages, maternity care deserts, and the absence of federally mandated paid maternity leave, disproportionately impact marginalized populations. Although policy initiatives such as Medicaid postpartum coverage extensions, the Maternal Health Momnibus Act, and Maternal Mortality Review Committees represent important progress, they remain insufficient without broader structural reform. Evidence-based interventions, including midwife- and doula-led care, community-based peer support, and culturally tailored mental health programs, demonstrate measurable improvements in maternal outcomes. Outcomes of this review highlight the need for a comprehensive, equity-centered approach to reducing maternal mortality disparities, emphasizing structural reform, expanded access to care, strengthened data systems, and community-driven solutions. Full article

(1) Background/Objectives: Over one billion individuals globally live with mental health conditions, yet the treatment gap exceeds 75% in low- and middle-income countries. Large language model (LLM)-based conversational agents have emerged as a potentially scalable solution, though the evidence base remains nascent and largely pre-clinical. This review synthesises barriers and facilitators to their implementation in mental healthcare using the Consolidated Framework for Implementation Research (CFIR). (2) Methods: Eight databases were searched from January 2022 to January 2026. Study selection was managed using Covidence. Two reviewers independently screened, extracted, and appraised studies using the Mixed Methods Appraisal Tool. Directed content analysis guided by CFIR was used for synthesis. (3) Results: Twenty-seven studies (three RCTs, nine mixed methods, eight qualitative, four cross-sectional, three observational) comprising >22,000 participants across 12 countries met inclusion criteria. Five barrier domains (27 sub-themes) and four facilitator domains (22 sub-themes) were identified. Inadequate crisis detection (reported in 21/27 studies) and 24/7 availability (reported in 26/27 studies) are the most frequently reported barriers and facilitators, respectively. These figures represent study-level reporting frequencies, not population-level prevalence estimates. CFIR mapping revealed universal coverage for Knowledge and Beliefs (100%) and Patient Needs and Resources (96%) but critical gaps in the Process domain (Evaluating: 7%; Champions: 11%). (4) Conclusions: LLM-based conversational agents demonstrate substantial promise but present critical safety deficiencies. A tiered implementation framework, independent safety certification, and equity-sensitive design are recommended. Full article

Whether urban park supply effectively responds to residents’ actual use remains a critical issue for public service provision, residents’ health and well-being, and spatial equity in high-density cities. Conventional assessments based on static population data may fail to capture dynamic patterns of human activity, potentially obscuring mismatches between service provision and real demand. This study integrates mobile phone signaling data into a supply–demand assessment framework to evaluate urban park systems from a dynamic population perspective. The framework is applied to Shenzhen as a representative high-density megacity. Park supply is measured by service capacity, coverage, and accessibility, while demand is derived from observed visitation behavior. A Supply–Demand Ratio (SDR) index, combined with Getis-Ord Gi* analysis, is employed to identify spatial patterns of mismatch. The results reveal substantial supply–demand imbalances that are not captured by traditional static indicators, with approximately 30.9% of communities identified as significant cold spots. High-density central areas exhibit a persistent deficit in park services despite relatively high coverage levels, whereas peripheral areas with abundant ecological resources show relative surpluses. These patterns are closely associated with urban functional structure, population mobility, and jobs–housing separation. By uncovering the divergence between nominal accessibility and actual use, this study highlights the limitations of place-based planning approaches and underscores the need for a people-centered perspective. The findings point to the importance of shifting from “opportunity equity” to “outcome equity” in evaluating and improving urban public service provision to foster sustainable urban development. Full article

Black children and youth in Canada often hold high educational aspirations; however, systemic biases, deficit-based perceptions, and structural barriers limit their opportunities. These challenges, linked to anti-Black racism, migration-related disruptions, and socioeconomic inequities, contribute to lower engagement, underrepresentation, and reduced access to equitable educational resources. This scoping review examines these intersecting factors to inform equity-focused policy and practice. Following the Arksey and O’Malley framework and reported according to PRISMA-ScR guidelines, this review analyzed 96 studies published from database inception to May 2024, including 55 qualitative, 37 quantitative, and 4 mixed-methods studies. Bibliometric analysis was used to summarize study characteristics, while a thematic synthesis guided by intersectionality identified patterns in barriers, experiences, and interventions. Findings indicate that Black children and youth face persistent barriers, including systemic racism, disproportionate disciplinary practices, and Eurocentric curricula, with inequities further shaped by intersections of race, immigration status, and socioeconomic position. At the same time, mentorship, sponsorship, and community networks support academic resilience. Reported interventions include anti-racism training for educators and school stakeholders, culturally responsive curricula, mentorship initiatives, mental health supports, and financial aid. Advancing equity for Black children and youth in Canada requires systemic reform, culturally responsive pedagogy, and intersectionality-informed policies. Future research should prioritize participatory and longitudinal designs to generate evidence on effective and scalable strategies that foster educational opportunity and well-being. Full article

Background: Dengue is a common mosquito-borne disease in Thailand and poses an increased risk of severe illness among adults. The TAK-003 quadrivalent dengue vaccine is newly introduced in Thailand and has demonstrated promising efficacy. This study aimed to assess intention to receive the vaccine, knowledge, attitudes, and associated factors with TAK-003 among participants. Methods: A cross-sectional study was conducted from September 2024 to July 2025 among Thai adults aged ≥20 years living in rural areas of Chiang Mai. Individuals with prior dengue vaccination were excluded. Binary logistic regression identified factors associated with intention to the receive vaccine. Results: A total of 482 participants were enrolled. The mean age was 61.3 years (SD 11.5), and 73.2% (n = 353) were female. Most participants had primary education or lower (64.3%, n = 310), and 62.9% (n = 303) reported a monthly household income < 10,000 THB (314 USD). The intention to receive the TAK-003 vaccine was 68.7% (n = 331). Only 31.5–35.1% correctly answered dengue treatment questions, and 38.6% believed they would contract dengue within five years. Concerns regarding vaccine side effects (76.1%) and efficacy (56.4%) were common. Local healthcare providers were the most trusted source of vaccine information (78.0%), followed by doctors (49.2%). Prior influenza vaccination (aOR 1.57, 95% CI 1.02–2.41) and more positive attitudes toward dengue vaccination (aOR 1.06, 95% CI 1.02–1.10) were associated with intention to receive the vaccination. Conclusions: Intention to vaccinate with the TAK-003 vaccine among adults in rural Chiang Mai was moderate. These findings can inform community-based vaccination programs and strategic planning for dengue vaccine rollout in rural northern Thailand. Full article