Browsing Masters Degrees (Sociology and Social Anthropology) by browse.metadata.advisor "Dunbar, Rory"
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- ItemThe efficiency and accuracy of a rapid qualitative tool to ascribe socio-economic status in communities in South Africa – a cross-sectional study.(Stellenbosch : Stellenbosch University, 2020-12) Nel, Melissa; Hoddinott, Graeme; Dunbar, Rory; Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Sociology and Social Anthropology.ENGLISH ABSTRACT: Socio-economic status (SES) is a well-established construct. Lower SES is consistently associated with increased health challenges. SES is important to social policy and health interventions and, therefore, constant effort is made to improve its measurement. I identified the varied practices of standard SES scale construction and measurement. The phletora of different scales and measures creates research inconsistencies. Validity and reliability are challenges for many SES scales, especially in lower to middle income countries (LMICs). Due to the lack of a generalised SES scale, cross-comparison in different contexts comes with many caveats. Additionally, difficulties are experienced when carrying out research that deals with the collection of large-scale data. The data collection process is labour intensive, time consuming, expensive, and complicated by differing norms and economic systems. I explored an alternative SES measuring process that is quicker and more operationally useful for health intervention and policy planning. This approach is called the “Qualitative Ascription of SES (QASES)” in which data are collected rapidly and observationally and then SES is ascribed to local neighbourhoods by the research staff. My data analysis was exploratory and comparative of secondary data that were collected using the QASES measure and a standard SES survey at individual-level. Firstly, I ran experiments to determine the efficiency of QASES compared to an individual-level SES survey. I created hypothetical contextual scenarios of a small study area and a large study area. I applied both methods to the study areas and determined the data collection processes in terms of labour, costs and time requirements. Secondly, I applied correlation analysis (Spearman’s rho) to the existing data where QASES and a standard SES survey was used in 9 study communities of South Africa. I determined the strength of associations between the QASES scale and a standard SES survey. I estimated that QASES is approximately 1.5x cheaper and 2x faster to implement than an individual-level SES survey, which makes QASES more operationally useful. In addition, the correlation between QASES and the standard SES measure showed a strong, positive association (r=0.753, n=142, p=0.000). Therefore, I found that the QASES approach can be used as a substitute for standard SES data collection, especially in LMICs. I recommend that the study should be replicated to further develop the QASES tool.