English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Health-system responsiveness (HSR) measures the experience of health-system users in terms of the non-clinical aspects of the health system. This has been operationalized as a measurable construct in multiple surveys and studies. According to the literature, reporting behaviour may vary systematically across socio-demographic characteristics. In this study we explore the association between education levels and reporting behaviour in terms of HSR in South Africa using data from the World Health Organization Study on Global Ageing and Adult Health for South Africa (WHO SAGE) conducted in 2007 and 2008. We consider the reporting behaviour of 1499 adults aged 50 and older in terms of the reported HSR for their most recent outpatient provider visit during the preceding 12 months. More specifically, we explore whether there are systematic biases in reporting behaviour by education levels and other socio-economic covariates through the use of data from anchoring vignettes. These are questions depicting hypothetical HSR scenarios which provide a fixed benchmark for comparing individuals' own HSR ratings and identifying potential reporting biases. Using a hierarchical-ordered probit model in regression analysis, we found large differences in HSR ratings between the lowest and highest education groups after adjusting for reporting bias using the anchoring vignettes. This finding holds across all seven HSR domains captured in the WHO SAGE dataset. In the most extreme case, individuals with no education are likely to underreport poor HSR by between 2.6 and 9.4% percentage points compared with individuals with secondary schooling or higher. Policy-makers need to take cognizance of potential reporting biases in HSR ratings and make the necessary adjustments to obtain data that are as true and accurate as possible. The need for this is especially acute in a country such as South Africa with large socio-economic inequalities and disparities in access to healthcare.

A comparable yardstick: adjusting for education bias in South African health system responsiveness ratings