The role of community engagement and involvement for community empowerment in health settings: the case of Ingwavuma community, KwaZulu-Natal, South Africa.
Bibliographic record
Abstract
Community Engagement (CE) in health research can improve a community's ability to address its own health needs and health inequalities, while ensuring that researchers understand community priorities. However, if effective CE processes are not used, communities will not be empowered to make effective decisions about their own health and wellbeing. This study is based on community-based health research projects; the Malaria and Bilharzia in South Africa (MABISA) and Tackling Infections Disease Burden in Africa-South Africa (TIBA-SA) implemented by the KwaZulu-Natal Ecohealth Program (KEP). I evaluated CE processes and outcomes, with a focus on schistosomiasis and malaria in a rural community of Ingwavuma, uMkhanyakude district in KwaZulu-Natal. The research approach was both qualitative and quantitative (mixed methods) with data collected through 34 in-depth interviews, 4 focus group discussions and 338 household questionnaires. Data was collected from heads of households, community advisory board members, community research assistants, primary school principal and KEP research team (including the project principal investigator and administrators). Data was collected in line with the five-stages of Community Engagement Vancouver Coastal Health framework. Data was analysed using QSR International Pty Ltd, NVivo 12 Pro and Chi-square tests were performed to assess associations between demographic variables and respondents’ knowledge and information of projects. The Principal Investigators informed the community about the project through community leaders (headmen) before the project commencement. As community members were involved at every stage of the process, from conceptualisation to dissemination, the study provided empirical evidence that collaborative partnerships lead to win-win outcomes. Involving headmen (indunas), CAB members, and CRAs in the project ensured shared goals, reciprocity, and mutual benefit, demonstrating the project's intention to help the community. Nearly half (48%) of the surveyed community members had never heard of MABISA. Ninety-four percent (94%) and ninety-seven percent (97%) of respondents had heard of bilharzia and malaria. Nearly the same proportions knew how both diseases are transmitted, thus demonstrating empowerment of community members on schistosomiasis and malaria issues. This study contributed to the understanding of best practices for community empowerment. The study provided information on how communities can positively influence their lives and manage their health problems. Such information can be extracted from the thesis and presented in vernacular language from the area. Furthermore, the thesis provided information of empowering researchers on how they can empower communities through effective engagement. Policy briefs that can be generated from the thesis provided useful information on community empowerment to policymakers and other stakeholders.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".