Supervisors’ perceptions regarding the Zambian HIV nurse practitioner program and integrating graduates into the Zambian health system: A descriptive cross-sectional survey
Bibliographic record
Abstract
Introduction: The disease burden of HIV and AIDS in Zambia is among the highest in the world. In 2009 the HIV Nurse Practitioner (HNP) program was implemented to address the disease burden of HIV and AIDS that is worsened by a critical shortage of health care workers and in Zambia. The objective of this study was to analyze the perceptions of supervisors of the first three cohorts of graduates of the HNP program regarding the HNP role, the impact of the role on the quality of care for HIV patients and their families, and perceived challenges in integrating the HNP graduates into the Zambian health system. Methods: This paper reports findings from a cross-sectional survey of the supervisors from the first three cohorts of Zambian HNP graduates who completed the program between 2010-2012. Thematic content analysis was used to identify themes from the responses of 60 supervisors. The project received approval from the University of xxx Research Ethics Committee and from the University of xxx Institutional Review Board. Results: The HNP graduates’ supervisors reported an understanding of the role, and a positive perception of the impact of the HNP cadre on the quality of HIV and AIDS care for patients and their families. The perceived challenges to integration of the HNP into the Zambian health system included the need to clarify job descriptions and responsibilities for the new role within the Ministry of Health, addressing issues related to the shortage of nurses to meet other health needs, ensuring appropriate referral of complex cases, and providing ongoing HNP supervision. Discussion: The findings in this study can be used to guide the development of this program and the development of future task-shifting programs to provide comprehensive care to patients with HIV and AIDS.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".