Dataset from Ark Consortium - Understanding kidney disease in rural central Uganda - Findings from a qualitative study.

dc.contributor.authorSaraladevi, Naicker
dc.contributor.authorJune, Fabian
dc.contributor.authorWorking group ARK Consortium,
dc.contributor.otherSeeley, Janet
dc.contributor.otherKabunga, Elizabeth
dc.contributor.otherLaurie, Tomlinson
dc.contributor.otherLiam, Smeeth
dc.contributor.otherMoffat, Nyirenda
dc.contributor.otherRobert, Newton
dc.contributor.otherRobert, Kalyesubula
dc.contributor.otherDominic, Bukenya
dc.contributor.otherJoseph Ssembatya
dc.descriptionThe data collection and methodology of dataset are described as follows. As part of a multicentre study on kidney disease (ARK) undertaken in Malawi, South Africa and Uganda we undertook a social science component in Uganda to gather information on people's understandings and perceptions of a diagnosis of kidney dysfunction, treatment and treatment seeking. We recruited 46 people who had been given information about kidney dysfunction and had been found to have some, usually early, signs of mild impairment. Data were collected during two in-depth interviews. Most participants had heard of the condition, but half denied knowledge of the health status of their kidneys or receiving results of tests from the clinic team. This response may have been linked to a lack of symptoms, for those with early stage kidney dysfunction. The treatment people reported receiving caused some uncertainty about condition severity. This may be because several people were treated for other conditions (such as urinary tract infections) and did not require treatment specifically for kidney disease. In our study, participants assessed illness severity based on symptoms and treatment and compared with the progression of other conditions. Data has been collected and stored in REDcap see Maré I, Kramer B, Hazelhurst S, Nhlapho M, Zent R, Harris P, Klipin M Electronic Data Capture System (REDCap) for Health Care Research and Training in a Resource-Constrained Environment: Technology Adoption Case Study JMIR Med Inform 2022;10(8):e33402URL:, DOI: 10.2196/33402 for a full description of REDcap research data storage and management processes.en_ZA
dc.description.librarianZintle Darazaen_ZA
dc.description.sponsorshipLAT was funded by a Wellcome Trust intermediate clinical fellowship [101143/Z/13/Z]. DB, RN and JS are partly funded by the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement and is also part of the EDCTP2 programme supported by the European Union. JS acknowledges the support of THRiVE-2, a DELTAS Africa grant # DEL-15-011 from Wellcome Trust [grant number # 107742/Z/15/Z] and the UK government.en_ZA
dc.facultyHealth Sciencesen_ZA
dc.funderGlaxoSmithKline Africa NCD Open Lab Programme. Grant number: 8111en_ZA
dc.rightsThe rights to the dataset reside in the terms and conditions of grant, the university of the witswatersrand IP policy, and with the researchers in light of the ethical clearance reciceveden_ZA
dc.schoolSchool of Clinical Medicineen_ZA
dc.subjectAfrica South of the Saharaen_ZA
dc.subjectKidney Failure, Chronicen_ZA
dc.titleDataset from Ark Consortium - Understanding kidney disease in rural central Uganda - Findings from a qualitative study.en_ZA
dc.title.alternativeDataset from - Understanding kidney disease in rural central Uganda – Findings from a qualitative studyen_ZA
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