Introduction/Objective: Transnational populations from the Association of Southeast Asian Nations are crossing borders regardless of whether their status is legal or undocumented, to receive health services in the border regions of Thailand. The implications and challenges of transnational mobility and the utilization of public health facilities in Thailand’s border regions are therefore investigated in this study. Methods: Four public health facilities were selected, located in 2 economically-active border areas in Northern Thailand: Mae Sai–Tachileik at the Thailand–Myanmar border and Chiang Saen–Ton Phueng at the Thailand–Lao PDR border. Qualitative data were obtained from in-depth interviews with 8 medical and non-medical hospital staff responsible for implementing facility-level policies and providing health services for the transnational population. Results: Five themes were identified through analysis of the implications and challenges for transnational mobility and the utilization of public health facilities under study: contextual determinants of illness in specific border areas; uncompensated care as opposed to financial management in serving the transnational population; health service opportunities for the transnational population; cross-border collaboration on public health; and the remaining challenges of transnational mobility in border regions. Conclusion: Conventional content analysis with interpretative induction of in-depth interview data offers recommendations for improving the capacity of border health facilities to reduce the burden placed upon them to provide services to the transnational population.

Background: Health consciousness is a critical determinant of individuals’ engagement in health behaviors, while social capital influences health-related questions. This study aims to explore the relationship between social capital-comprising social participation, social trust, social networks, and social reciprocity, and health consciousness in China, with particular emphasis on regional variations.Methods: This study utilizes data from the 2021 Chinese Social Survey (CSS2021) and employs descriptive analysis, binary logistic regression, and subsample regression to examine the effects of social capital on health consciousness, with a focus on regional differences across China.Results: There are significant regional differences in health consciousness among Chinese residents. Overall, the proportion of residents exhibiting a high level of health consciousness accounted for more than half (67.3%), with eastern China leading at 68.8% and the western region at a lower level of 64.3%. Social participation, social trust, and social reciprocity were found to significantly influence health consciousness. Regionally, the eastern region was influenced by social participation, social trust, and social networks; the central region by social participation alone; and the western region by social reciprocity (p < 0.05). In terms of socio-demographic and economic characteristics, the eastern region’s health consciousness was significantly influenced by age, gender, education, family economic status, and happiness. In the central region, factors included gender, marital status, education, family economic status, recent medical experience, and social equity cognition. In the western region, marital status, education, income group, family economic status, and social insurance satisfaction were significant factors (p < 0.05).Conclusion: This study highlights significant regional disparities in health consciousness among Chinese residents with variations closely linked to socioeconomic development. Social capital, including social participation, social trust, social networks, and social reciprocity, plays a crucial role, with its impact varying across regions. Factors such as age, gender, education, income, and family economic status influence health consciousness differently depending on the region. The findings underscore the need for region-specific health policies that address socioeconomic factors and strengthen social capital, aiming to improve health consciousness and public health outcomes across China.

This study investigates elements of social capital in the Thai communities for social entrepreneurship and explores the characteristics and patterns of social capital mobilization through a survey of social enterprises. The study uses the qualitative approach based on cross-sectional data, non-participatory observation, focus group discussions, and semi-structured in-depth interviews. Representatives were taken from three social enterprises engaged in the business of hospitality, herbal products, and organic vegetables. The elements of social capital that emerged had two dimensions: the value-based and knowledge-based dimensions. The value-based dimension consisted of generosity, trust, harmony, industriousness, honesty, perseverance, and forgiveness, while the knowledge-based dimension involved learning ability, the ability to deliver knowledge, local wisdom, and the use of technology. The characteristics and patterns of social capital mobilization that emerged began from the categorization of related communities, the connection building through mediation, dialogue, trust in the social spirit of the communities, and the use of community capacity unto the generation of positive outcomes in those communities. All told, both social enterprises and the communities greatly benefited from the social capital generated.

Background: Rapid population aging has increased the demand for integrated care for older adults, particularly in rural areas where older adults frequently experience chronic illness, frailty, and limited access to healthcare. Caregivers, both formal and informal, play a central role in supporting the wellbeing of older adults but often face substantial physical, emotional, and financial burdens. Understanding caregiver support is therefore essential to strengthening integrated care for rural older adult populations. Objective: To identify factors influencing caregiver support within integrated care for older adults in rural areas and to highlight evidence gaps for future research. Methods: A scoping review was conducted following the Arksey and O’Malley framework. Four databases (PubMed, Scopus, Wiley Online Library, and Taylor & Francis) were searched for English-language studies published between 2014 and 2024. Of 371 records identified, 25 studies met the inclusion criteria and were analyzed by research type, methodology, caregiver type, and caregiver support factors. Results: Nineteen caregiver support factors were identified and categorized into five domains: social and community, financial, e-health, policy, and spatial. Key challenges included limited education and training opportunities, financial strain, restricted access to telehealth services, inadequate policy support, and transportation barriers. Informal caregivers, primarily family members, predominated in rural settings and experienced greater caregiving burdens due to limited institutional and service support. Conclusion: Caregiver support is a critical component of effective integrated care for older adults in rural areas. Strengthening social and community networks, financial assistance, e-health infrastructure, and policy frameworks is essential to reducing caregiver burden and improving outcomes for older adults. Future research should prioritize context-specific caregiver support strategies tailored to rural settings.

This study reviews the development of Thailand’s Medical Hub policy and explores the recommendations and proposals for operational integration of the Medical Hub policy to mitigate the impact on the national health system, including exemplification of the medical personnel shortage in the public sector and the potential brain drain to the private sector. The scope of this study covers the implementation of the first strategic plan, “Medical Hub of Asia (2004–2008)” and the second strategic plan, “Thailand as a World Class Health Care Provider (2010–2014).” This study investigates secondary information on Thailand’s Medical Hub policy from official documents and research. It also employs purposive sampling of select experts and experienced professionals from the public and private sectors and civil society who are pertinent to the implementation of the Medical Hub policy to participate in the in-depth interviews. Inclusively, the Medical Hub policy should be implemented based on the engagement of the public and private sectors and civil society to reduce the impact on Thailand’s national health system.

Background: In China, which has the world’s largest and one of the fastest-aging populations, multimorbidity has become a major public health challenge. Older individuals with multiple chronic conditions experience poor health outcomes, increased healthcare utilization, and substantial financial pressure. This study investigates of the financial burden on older inpatients with multimorbidity. Methods: Utilizing 2022 inpatient data from a Chinese city (covering 4 secondary and 2 tertiary hospitals), this study employed descriptive statistics (means, standard deviations, medians, and interquartile ranges), comparative tests (chi-square, t -test, ANOVA), and multiple linear regression to identify key drivers of medical costs and out-of-pocket expenses for older inpatients with multimorbidity. Results: The study revealed a high multimorbidity rate of 73.8% among 106,202 inpatients aged ≥50 years from six Chinese hospitals in 2022. The average total hospitalization cost was 10,318 yuan, with an out of pocket expense (OOPE) of 4,558 yuan. Descriptive analysis showed the largest patient proportion was aged 60–69 years (38.4%) and most had 2–4 chronic conditions. Analysis of medical expenses identified significant variations. Patients with urban employee insurance had higher total costs but lower OOPE (24.99% proportion) compared to those with urban–rural resident insurance (50.89% proportion). Treatment in tertiary hospitals and longer hospital stays were strongly associated with higher costs. Multiple regression confirmed hospital level, length of stay, and surgical intervention were the most significant positive predictors of total costs. For OOPE, health insurance type, hospital level, and length of stay were major influencing factors. Conclusion: Multimorbidity is highly prevalent and imposes a substantial financial burden on older inpatients. Strengthening prevention, optimizing insurance design, and improving integrated care are essential for promoting healthcare equity and sustainability in China.