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Access to appropriate healthcare among disadvantaged populations in countries with universal healthcare requires a critical understanding of the relationships between poverty, social exclusion and health in the local context. The qualitative study explored the experiences of healthcare utilization in an inner-city impoverished community living in slum conditions in Hong Kong. Interviews with 40 slum residents in one of the poorest neighbourhoods in the city explored the following domains: experience and perceptions of the community, housing conditions, informal social capital and support system, interactions with community workers, and experiences in utilizing social and healthcare services. Framework analysis was conducted to identify local themes under the model of healthcare utilization: approachability, acceptability, availability and accommodation, affordability and appropriateness. Despite the subsidized public healthcare system, multiple barriers were identified. Low literacy of healthcare systems was prevalent. Specifically, structural barriers relating mainly to the availability, accommodation and affordability of health services were salient to impede access to healthcare. The barriers related to healthcare providers primarily stemmed from the interactions of healthcare providers, perceived stigma and the lack of patient-centred care. In addition, poverty-related sociocultural norms and personal beliefs of healthcare were found to be significant barriers to healthcare access. Despite the well-established subsidized public healthcare system, healthcare inequity was evident. Lack of quality healthcare access needs to be addressed by providing social and educational resources that facilitate collective efficacy for healthcare, community engagement from public sectors and person-centred care with healthcare providers.
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http://dx.doi.org/10.1093/heapro/daab195 | DOI Listing |
Health Expect
October 2025
Murdoch Children's Research Institute, Parkville, Victoria, Australia.
Introduction: Despite high coverage of routine childhood vaccines, uptake of the human papillomavirus (HPV) vaccine in the Pacific Island nation of Tonga has been slow. Culturally appropriate communication resources on the importance, safety, and effectiveness of the HPV vaccine are critical to support acceptance and uptake. To develop these resources, it is important to understand what people want to know.
View Article and Find Full Text PDFJ Robot Surg
September 2025
Orlando Health Advanced Robotic Surgery Center, Orlando, FL, USA.
Teleproctoring offers a remote alternative to traditional surgical mentoring, addressing logistical barriers in robotic surgery education. We conducted a prospective trial to assess the feasibility and trainee perception of teleproctoring using the Proximie platform. Eighteen surgeons with limited robotic experience performed a standardized enterotomy closure on synthetic bowel models using the da Vinci Si system, while receiving real-time remote guidance from an expert located 2570 km away.
View Article and Find Full Text PDFJ Ethn Subst Abuse
September 2025
Department of Psychology and Center on Alcohol, Substance use, And Addiction (CASAA), University of New Mexico, Albuquerque, NM, USA.
Background: American Indian and Alaska Native (AI/AN) communities experienced a disproportionate increase in opioid-related fatal and non-fatal poisonings during the COVID-19 pandemic. Access to treatment, such as medications for opioid use disorder (MOUD), became even more critical, although research among this population is limited. We completed qualitative interviews with substance use disorder (SUD) treatment providers (i.
View Article and Find Full Text PDFJAMA
September 2025
Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
J Am Coll Cardiol
August 2025
Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Cardiology, Kaiser Permanente Santa Clara Medical Center, Santa Clara, California, USA. Electronic address:
Background: Accurate measurement of echocardiographic parameters is crucial for the diagnosis of cardiovascular disease and tracking of change over time; however, manual assessment requires time-consuming effort and can be imprecise. Artificial intelligence has the potential to reduce clinician burden by automating the time-intensive task of comprehensive measurement of echocardiographic parameters.
Objectives: The purpose of this study was to develop and validate open-sourced deep learning semantic segmentation models for the automated measurement of 18 anatomic and Doppler measurements in echocardiography.