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The efficiency and accuracy of a rapid qualitative tool to ascribe socio-economic status in communities in South Africa – a cross-sectional study.
Thesis (MA)--Stellenbosch University, 2020.
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| Format: | Thesis |
| Language: | en_ZA |
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Stellenbosch : Stellenbosch University
2020
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| _version_ | 1867613958308888576 |
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| access_status_str | Open Access |
| author | Nel, Melissa |
| author2 | Hoddinott, Graeme |
| author_browse | Hoddinott, Graeme Nel, Melissa |
| author_facet | Hoddinott, Graeme Nel, Melissa |
| author_sort | Nel, Melissa |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MA)--Stellenbosch University, 2020. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/109318 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:44:24.894Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/109318 The efficiency and accuracy of a rapid qualitative tool to ascribe socio-economic status in communities in South Africa – a cross-sectional study. Nel, Melissa Hoddinott, Graeme Dunbar, Rory Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Sociology and Social Anthropology. Social status -- South Africa -- Mathematical models Social status -- South Africa -- Measurement Social surveys -- South Africa Social service -- Communities -- South Africa South Africa -- Social conditions Poverty -- South Africa -- Econometric models SES (Socio-economic status) QASES (Qualitative Ascription of SES) UCTD Thesis (MA)--Stellenbosch University, 2020. 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. AFRIKAANSE OPSOMMING: Sosio-ekonomiese status (SES) is ʼn gevestigde konstruksie. Laer-SES word konsekwent met verhoogde gesondheidsuitdagings geassosieer. SES is belangrik vir sosiale beleid- en gesondheidsintervensies en daarom word voortdurend gepoog om die meting daarvan te verbeter.Ek het die verskillende praktyke van SES-skaalkonstruksie en -meting geïdentifiseer. Die oorvloed van verskillende skale en maatstawwe skep teenstrydighede met die navorsing. Geldigheid en betroubaarheid is uitdagingend vir baie SES-skale, veral in laer- tot middelinkomste-lande (LMIL). Vanweë die gebrek aan ’n veralgemeende SES-skaal, kom kruisvergelyking in verskillende kontekste met baie voorwaardes voor. Boonop word probleme tydens die uitvoering van navorsing, wat handel oor die versameling van grootskaalse data, ondervind. Die data-insamelingsproses is arbeidsintensief, tydrowend, duur en ingewikkeld as verskillende norme en ekonomiese stelsels in ag geneem word.Ek het ’n alternatiewe SES-meetproses ondersoek wat vinniger en meer bruikbaar is vir gesondheidsintervensie en beleidsbeplanning. Hierdie benadering word die “kwalitatiewe toeskrywing van SES (QASES)” genoem waarin data vinnig en waarnemend versamel word. SES word dan aan plaaslike woonbuurte deur die navorsingspan toegeskryf.Ek het sekondêre data op ʼn verkennende en vergelykende wyse ontleed. Hierdie data is met behulp van die QASES-maatstaf en ʼn individuele standaard-SES-opname ingesamel. Eerstens het ek eksperimente uitgevoer om die doeltreffendheid van QASES in vergelyking met ’n individuele vlak SES-opname te bepaal. Ek het hipotetiese kontekstuele scenario's van ’n klein en groot studiegebied geskep. Albei metodes is op die studiegebiede toegepas en die proses van data-insameling is ten opsigte van arbeid, koste en tydsvereistes bepaal. Tweedens het ek korrelasie-analise (Spearman's rho) op die bestaande data toegepas waar QASES en ’n standaard-SES-opname in 9 studiegemeenskappe van Suid-Afrika gebruik is. Ek het die sterkte van assosiasies tussen die QASES-skaal en ʼn standaard-SES-opname bepaal. Daar is beraam dat QASES ongeveer 1.5x goedkoper en 2x vinniger is as ’n individuele vlak SES-opname om te implementeer, wat QASES meer bruikbaar maak. Daarbenewens het die korrelasie tussen QASES en die standaard SES-maatstaf ʼn sterk, positiewe assosiasie getoon (r = 0.753, n = 142, p = 0.000). Daarom kan QASES as ʼn plaasvervanger vir standaard SES-data- insameling gebruik word, veral in LMIL. Ek beveel aan dat die studie herhaal word om die QASES-instrument verder te ontwikkel. Masters 2020-11-27T14:42:00Z 2021-01-31T19:44:30Z 2020-11-27T14:42:00Z 2021-01-31T19:44:30Z 2020-12 Thesis http://hdl.handle.net/10019.1/109318 en_ZA Stellenbosch University xv, 171 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Social status -- South Africa -- Mathematical models Social status -- South Africa -- Measurement Social surveys -- South Africa Social service -- Communities -- South Africa South Africa -- Social conditions Poverty -- South Africa -- Econometric models SES (Socio-economic status) QASES (Qualitative Ascription of SES) UCTD Nel, Melissa The efficiency and accuracy of a rapid qualitative tool to ascribe socio-economic status in communities in South Africa – a cross-sectional study. |
| title | The efficiency and accuracy of a rapid qualitative tool to ascribe socio-economic status in communities in South Africa – a cross-sectional study. |
| title_full | The efficiency and accuracy of a rapid qualitative tool to ascribe socio-economic status in communities in South Africa – a cross-sectional study. |
| title_fullStr | The efficiency and accuracy of a rapid qualitative tool to ascribe socio-economic status in communities in South Africa – a cross-sectional study. |
| title_full_unstemmed | The efficiency and accuracy of a rapid qualitative tool to ascribe socio-economic status in communities in South Africa – a cross-sectional study. |
| title_short | The efficiency and accuracy of a rapid qualitative tool to ascribe socio-economic status in communities in South Africa – a cross-sectional study. |
| title_sort | efficiency and accuracy of a rapid qualitative tool to ascribe socio economic status in communities in south africa a cross sectional study |
| topic | Social status -- South Africa -- Mathematical models Social status -- South Africa -- Measurement Social surveys -- South Africa Social service -- Communities -- South Africa South Africa -- Social conditions Poverty -- South Africa -- Econometric models SES (Socio-economic status) QASES (Qualitative Ascription of SES) UCTD |
| url | http://hdl.handle.net/10019.1/109318 |
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