The impact of leadership hubs on the uptake of evidence-informed nursing practices and workplace policies for HIV care: a quasi-experimental study in Jamaica, Kenya, Uganda and South Africa
Bibliographic record
Abstract
BACKGROUND: The enormous impact of HIV on communities and health services in Sub-Saharan Africa and the Caribbean has especially affected nurses, who comprise the largest proportion of the health workforce in low- and middle-income countries (LMICs). Strengthening action-based leadership for and by nurses is a means to improve the uptake of evidence-informed practices for HIV care. METHODS: A prospective quasi-experimental study in Jamaica, Kenya, Uganda and South Africa examined the impact of establishing multi-stakeholder leadership hubs on evidence-informed HIV care practices. Hub members were engaged through a participatory action research (PAR) approach. Three intervention districts were purposefully selected in each country, and three control districts were chosen in Jamaica, Kenya and Uganda. WHO level 3, 4 and 5 health care institutions and their employed nurses were randomly sampled. Self-administered, validated instruments measured clinical practices (reports of self and peers), quality assurance, work place policies and stigma at baseline and follow-up. Standardised average scores ranging from 0 to 1 were computed for clinical practices, quality assurance and work place policies. Stigma scores were summarised as 0 (no reports) versus 1 (one or more reports). Pre-post differences in outcomes between intervention and control groups were compared using the Mantel Haenszel chi-square for dichotomised stigma scores, and independent t tests for other measures. For South Africa, which had no control group, pre-post differences were compared using a Pearson chi-square and independent t test. Multivariate analysis was completed for Jamaica and Kenya. Hub members in all countries self-assessed changes in their capacity at follow-up; these were examined using a paired t test. RESULTS: Response rates among health care institutions were 90.2 and 80.4 % at baseline and follow-up, respectively. Results were mixed. There were small but statistically significant pre-post, intervention versus control district improvements in workplace policies and quality assurance in Jamaica, but these were primarily due to a decline in scores in the control group. There were modest improvements in clinical practices, workplace policies and quality assurance in South Africa (pre-post) (clinical practices of self-pre 0.67 (95 % CI, 0.62, 0.72) versus post 0.78 (95 % CI, 0.73-0.82), p = 0.002; workplace policies-pre 0.82 (95 % CI, 0.70, 0.85) versus post 0.87 (95 % CI, 0.84, 0.90), p = 0.001; quality assurance-pre 0.72 (95 % CI, 0.67, 0.77) versus post 0.84 (95 % CI, 0.80, 0.88)). There were statistically significant improvements in scores for nurses stigmatising patients (Jamaica reports of not stigmatising-pre-post intervention 33.9 versus 62.4 %, pre-post control 54.7 versus 64.4 %, p = 0.002-and Kenya pre-post intervention 35 versus 51.6 %, pre-post control 34.2 versus 47.8 %, p = 0.006) and for nurses being stigmatised (Kenya reports of no stigmatisation-pre-post intervention 23 versus 37.3 %, pre-post control 15.4 versus 27 %, p = 0.004). Multivariate results for Kenya and Jamaica were non-significant. Twelve hubs were established; 11 were active at follow-up. Hub members (n = 34) reported significant improvements in their capacity to address care gaps. CONCLUSIONS: Leadership hubs, comprising nurses and other stakeholders committed to change and provided with capacity building can collectively identify issues and act on strategies that may improve practice and policy. Overall, hubs did not provide the necessary force to improve the uptake of evidence-informed HIV care in their districts. If hubs are to succeed, they must be integrated within district health authorities and become part of formal, legal organisations that can regularise and sustain them.
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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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".