2 resultados para qualitative data

em Bioline International


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For a long time, electronic data analysis has been associated with quantitative methods. However, Computer Assisted Qualitative Data Analysis Software (CAQDAS) are increasingly being developed. Although the CAQDAS has been there for decades, very few qualitative health researchers report using it. This may be due to the difficulties that one has to go through to master the software and the misconceptions that are associated with using CAQDAS. While the issue of mastering CAQDAS has received ample attention, little has been done to address the misconceptions associated with CAQDAS. In this paper, the author reflects on his experience of interacting with one of the popular CAQDAS (NVivo) in order to provide evidence-based implications of using the software. The key message is that unlike statistical software, the main function of CAQDAS is not to analyse data but rather to aid the analysis process, which the researcher must always remain in control of. In other words, researchers must equally know that no software can analyse qualitative data. CAQDAS are basically data management packages, which support the researcher during analysis.

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Background: The aim of this study was to assess the quality of rapid HIV testing in South Africa. Method: A two-stage sampling procedure was used to select HCT sites in eight provinces of South Africa. The study employed both semi-structured interviews with HIV testers and observation of testing sessions as a means of data collection. In total, 63 HCT sites (one HIV tester per site) were included in the survey assessing qualification, training, testing practices and attitudes towards rapid tests. Quantitative data was analysed using descriptive statistics and qualitative data was content analysed. Results: Of the 63 HIV testers, 20.6% had a nursing qualification, 14.3% were professional counsellors, 58.7% were lay HIV counsellors and testers and 6.4% were from other professions. Most HIV testers (87.3%) had had a formal training in testing, which ranged between 10-14 days, while 6 (9.5%) had none. Findings revealed sub-standard practices in relation to testing. These were mainly related to non-adherence to testing algorithms, poor external quality control practices, poor handling and communication of discordant results. Conclusion: Quality of HIV rapid testing may be highly compromised through poor adherence to guidelines as observed in our study.