To Go or To Not Go: Structure Equation Modelling of Healthcare Utilisation among Older Adults in Mpumalanga, South Africa
(2024) MIDM19 20241LUMID International Master programme in applied International Development and Management
Department of Human Geography
- Abstract
- Providing healthcare services for the older rural population in South Africa is a matter of availability and accessibility. This study aims to analyse the factors influencing healthcare utilisation among rural older adults in South Africa using Andersen’s behavioural model of health services use. Structural equation modelling (SEM) with confirmatory factor analysis (CFA) technique will be used to examine which factors significantly influence healthcare utilisation. Data from the HAALSI study, specifically the second wave, were used (N = 4176). The findings show that the enabling and need factors significantly influence healthcare utilisation, with the former having the biggest influence. Vehicle ownership and wealth asset index are found... (More)
- Providing healthcare services for the older rural population in South Africa is a matter of availability and accessibility. This study aims to analyse the factors influencing healthcare utilisation among rural older adults in South Africa using Andersen’s behavioural model of health services use. Structural equation modelling (SEM) with confirmatory factor analysis (CFA) technique will be used to examine which factors significantly influence healthcare utilisation. Data from the HAALSI study, specifically the second wave, were used (N = 4176). The findings show that the enabling and need factors significantly influence healthcare utilisation, with the former having the biggest influence. Vehicle ownership and wealth asset index are found to have a huge impact within the enabling factor, unlike medical coverage. Meanwhile, for need factors, the present self-rated health status was found to have a bigger impact than health compared to the previous year. Contrary to some previous studies, the predisposing factor is found to have little impact on healthcare utilisation. Even so, age, education level, and employment status are found to have a big influence on predisposing factors. After the removal of sex and marital status from the predisposing factors, model fit indices show that Andersen’s model is a good fit. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9167127
- author
- Wibowo, Jessica Irene Wong LU
- supervisor
-
- Stefan Brehm LU
- organization
- course
- MIDM19 20241
- year
- 2024
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- healthcare utilisation, need factors, predisposing factor, enabling factors, rural older adults
- language
- English
- id
- 9167127
- date added to LUP
- 2024-07-24 12:05:58
- date last changed
- 2024-07-24 12:05:58
@misc{9167127, abstract = {{Providing healthcare services for the older rural population in South Africa is a matter of availability and accessibility. This study aims to analyse the factors influencing healthcare utilisation among rural older adults in South Africa using Andersen’s behavioural model of health services use. Structural equation modelling (SEM) with confirmatory factor analysis (CFA) technique will be used to examine which factors significantly influence healthcare utilisation. Data from the HAALSI study, specifically the second wave, were used (N = 4176). The findings show that the enabling and need factors significantly influence healthcare utilisation, with the former having the biggest influence. Vehicle ownership and wealth asset index are found to have a huge impact within the enabling factor, unlike medical coverage. Meanwhile, for need factors, the present self-rated health status was found to have a bigger impact than health compared to the previous year. Contrary to some previous studies, the predisposing factor is found to have little impact on healthcare utilisation. Even so, age, education level, and employment status are found to have a big influence on predisposing factors. After the removal of sex and marital status from the predisposing factors, model fit indices show that Andersen’s model is a good fit.}}, author = {{Wibowo, Jessica Irene Wong}}, language = {{eng}}, note = {{Student Paper}}, title = {{To Go or To Not Go: Structure Equation Modelling of Healthcare Utilisation among Older Adults in Mpumalanga, South Africa}}, year = {{2024}}, }