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Predictors of condom use and refusal among the population of Free State province in South Africa
BACKGROUND: This study investigated the extent and predictors of condom use and condom refusal in the Free State province in South Africa. METHODS: Through a household survey conducted in the Free Sate province of South Africa, 5,837 adults were interviewed. Univariate and multivariate survey logist...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3432618/ https://www.ncbi.nlm.nih.gov/pubmed/22639964 http://dx.doi.org/10.1186/1471-2458-12-381 |
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author | Chandran, Thoovakkunon Moorkoth Berkvens, Dirk Chikobvu, Perpetual Nöstlinger, Christiana Colebunders, Robert Williams, Brian Gerard Speybroeck, Niko |
author_facet | Chandran, Thoovakkunon Moorkoth Berkvens, Dirk Chikobvu, Perpetual Nöstlinger, Christiana Colebunders, Robert Williams, Brian Gerard Speybroeck, Niko |
author_sort | Chandran, Thoovakkunon Moorkoth |
collection | PubMed |
description | BACKGROUND: This study investigated the extent and predictors of condom use and condom refusal in the Free State province in South Africa. METHODS: Through a household survey conducted in the Free Sate province of South Africa, 5,837 adults were interviewed. Univariate and multivariate survey logistic regressions and classification trees (CT) were used for analysing two response variables ‘ever used condom’ and ‘ever refused condom’. RESULTS: Eighty-three per cent of the respondents had ever used condoms, of which 38% always used them; 61% used them during the last sexual intercourse and 9% had ever refused to use them. The univariate logistic regression models and CT analysis indicated that a strong predictor of condom use was its perceived need. In the CT analysis, this variable was followed in importance by ‘knowledge of correct use of condom’, condom availability, young age, being single and higher education. ‘Perceived need’ for condoms did not remain significant in the multivariate analysis after controlling for other variables. The strongest predictor of condom refusal, as shown by the CT, was shame associated with condoms followed by the presence of sexual risk behaviour, knowing one’s HIV status, older age and lacking knowledge of condoms (i.e., ability to prevent sexually transmitted diseases and pregnancy, availability, correct and consistent use and existence of female condoms). In the multivariate logistic regression, age was not significant for condom refusal while affordability and perceived need were additional significant variables. CONCLUSIONS: The use of complementary modelling techniques such as CT in addition to logistic regressions adds to a better understanding of condom use and refusal. Further improvement in correct and consistent use of condoms will require targeted interventions. In addition to existing social marketing campaigns, tailored approaches should focus on establishing the perceived need for condom-use and improving skills for correct use. They should also incorporate interventions to reduce the shame associated with condoms and individual counselling of those likely to refuse condoms. |
format | Online Article Text |
id | pubmed-3432618 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-34326182012-09-04 Predictors of condom use and refusal among the population of Free State province in South Africa Chandran, Thoovakkunon Moorkoth Berkvens, Dirk Chikobvu, Perpetual Nöstlinger, Christiana Colebunders, Robert Williams, Brian Gerard Speybroeck, Niko BMC Public Health Research Article BACKGROUND: This study investigated the extent and predictors of condom use and condom refusal in the Free State province in South Africa. METHODS: Through a household survey conducted in the Free Sate province of South Africa, 5,837 adults were interviewed. Univariate and multivariate survey logistic regressions and classification trees (CT) were used for analysing two response variables ‘ever used condom’ and ‘ever refused condom’. RESULTS: Eighty-three per cent of the respondents had ever used condoms, of which 38% always used them; 61% used them during the last sexual intercourse and 9% had ever refused to use them. The univariate logistic regression models and CT analysis indicated that a strong predictor of condom use was its perceived need. In the CT analysis, this variable was followed in importance by ‘knowledge of correct use of condom’, condom availability, young age, being single and higher education. ‘Perceived need’ for condoms did not remain significant in the multivariate analysis after controlling for other variables. The strongest predictor of condom refusal, as shown by the CT, was shame associated with condoms followed by the presence of sexual risk behaviour, knowing one’s HIV status, older age and lacking knowledge of condoms (i.e., ability to prevent sexually transmitted diseases and pregnancy, availability, correct and consistent use and existence of female condoms). In the multivariate logistic regression, age was not significant for condom refusal while affordability and perceived need were additional significant variables. CONCLUSIONS: The use of complementary modelling techniques such as CT in addition to logistic regressions adds to a better understanding of condom use and refusal. Further improvement in correct and consistent use of condoms will require targeted interventions. In addition to existing social marketing campaigns, tailored approaches should focus on establishing the perceived need for condom-use and improving skills for correct use. They should also incorporate interventions to reduce the shame associated with condoms and individual counselling of those likely to refuse condoms. BioMed Central 2012-05-28 /pmc/articles/PMC3432618/ /pubmed/22639964 http://dx.doi.org/10.1186/1471-2458-12-381 Text en Copyright ©2012 Chandran et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Chandran, Thoovakkunon Moorkoth Berkvens, Dirk Chikobvu, Perpetual Nöstlinger, Christiana Colebunders, Robert Williams, Brian Gerard Speybroeck, Niko Predictors of condom use and refusal among the population of Free State province in South Africa |
title | Predictors of condom use and refusal among the population of Free State province in South Africa |
title_full | Predictors of condom use and refusal among the population of Free State province in South Africa |
title_fullStr | Predictors of condom use and refusal among the population of Free State province in South Africa |
title_full_unstemmed | Predictors of condom use and refusal among the population of Free State province in South Africa |
title_short | Predictors of condom use and refusal among the population of Free State province in South Africa |
title_sort | predictors of condom use and refusal among the population of free state province in south africa |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3432618/ https://www.ncbi.nlm.nih.gov/pubmed/22639964 http://dx.doi.org/10.1186/1471-2458-12-381 |
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