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What influences the perceived access to healthcare services? An investigation using Structural Equation Modeling

Dados Bibliográficos

ID22076852
AutoresMurat Topbas (0000-0003-4047-4027, Karadeniz Technical University), Irem Dilaver (0000-0002-9962-7908, Karadeniz Technical University), Serdar Karakullukcu (0000-0001-7673-7699, Karadeniz Technical University), Füsun Yalçın (0000-0002-2669-1044, Akdeniz University), Fusun Yalcin (Akdeniz University), Husniye Ebru Colak (Karadeniz Technical University), Elif Bahcekapili (Karadeniz Technical University), Nazım Ercüment Beyhun (0000-0002-4664-9070, Karadeniz Technical University), Nazim Ercument Beyhun (Karadeniz Technical University), Mehmet Topsakal (0000-0002-7880-0740, Directorate of Health), Yavuz Cakiroglu (Directorate of Health), Erdem Sen (Directorate of Health)
Ano2026
Volume14
Páginas1844139-1844139
Data de publicação2026-06-04
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoFrontiers in Public Health (JOURNAL)
Identificadores do periódicoISSN: 2296-2565 • E-ISSN: 2296-2565
EditoraFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2026.1844139
PMID42326952
OpenAlexW7163579137
IdiomaEN
Referências citadas59

Background: Access to healthcare is a fundamental determinant of public health sustainability. Current literature on healthcare access tends to focus largely on vulnerable groups and objective indicators where access is defined through service utilization. When the literature on "perceived access to healthcare" is examined, it is observed that perceived access is generally treated as a determining factor explaining health outcomes or behaviors. However, the investigation of the socioeconomic, self-rated health, health literacy and spatial features that shape this perception itself within a holistic framework remains a less focused area in the literature. Methodologically, perceived access to healthcare is often defined with a limited number of variables or specifically within particular disease groups. Especially in regions such as Trabzon, where rugged topography and geographical barriers are intertwined with socio-cultural dynamics, analyzing the factors shaping the individual's perception of access within a comprehensive framework will offer a significant contribution to the literature. This study aims to integrate multidimensional factors -including socioeconomic status (SES), self-rated health, health literacy, health-seeking behavior, and travel time-into a comprehensive structural framework for the first time in the literature; to validate their effects through Structural Equation Modeling (SEM), and to uncover the spatial dependence patterns in access. Methods: This reearch was conducted with 1,491 adults. Data were analyzed using Structural Equation Modeling (SEM) to evaluate multidimensional pathways, and geospatial analysis was performed to determine spatial dependence patterns. Results: The results of the research demonstrate that health literacy and professional health-seeking behavior are the primary elements strengthening the perception of access, whereas online health-seeking and increased travel time weaken this perception. One of the most original findings of the study is that the direct negative effect of SES on access is balanced through health literacy; this indicates that cognitive capacity can mitigate socioeconomic disadvantages. Spatial models confirm that while the general perceived access to healthcare is shaped by personal factors, the "accessibility" dimension exhibits a spatial dependence tied to local topography within a 1-km radius. Conclusion: Consequently, these findings scientifically support that health planning should shift from macro-scale strategies toward micro-spatial interventions aimed at minimizing physical barriers at the neighborhood and street levels. Integrating approaches that improve health literacy with interventions that minimize travel barriers will play a fundamental role in reducing health inequalities

Geospatial analysis · Health care · Health literacy · Literacy · Perception · Socioeconomic status · Structural equation modeling · Health disparities and outcomes · Healthcare Policy and Management · Healthcare Systems and Reforms

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