Professional nurses’ perceptions regarding clinical competence of community service nurses in North West province, South Africa
Bibliographic record
Abstract
BACKGROUND: South African Nursing Council requires nurses who successfully complete their training to perform a year of community service before obtaining registration as professional nurses (Regulation 425). Community service for health professionals was introduced as a strategy to retain newly qualified professionals within the country. The premise is that community service for newly graduated nurses gives them the opportunity to develop skills and acquire knowledge critical in their professional development. AIM: To explore and describe the perceptions of professional nurses as the supervisors of community service nurses (CSNs) during their 12 months of community service. SETTING: Selected hospitals of the North West province, South Africa. METHODS: A qualitative, exploratory and descriptive design was used. The study was conducted between September and November 2018 at three public hospitals in the North West province. Through purposive sampling, 15 professional nurses who supervise CSNs participated in the study. Data were collected in three focus group discussions using semi-structured questions. All focus group discussions were recorded and transcribed for analysis. Data were analysed using Pienaar's four steps of thematic analysis. RESULTS: Three themes emerged: perceptions of clinical competence, challenges impacting clinical competence and suggestions to improve clinical competence. CONCLUSION: It is suggested that even though the majority of CSNs were perceived to be competent and capable of working independently, they still required supervision and mentorship to refine their competency. Furthermore, the study reported similar challenges noted from previous studies that were perceived to be affecting CSNs' ability to deliver quality health care, and therefore recommendations for improvement were made. CONTRIBUTION: The study contributed to the developed the clinical competence evaluation tool which will be of benefit to the future community service nurses in the province.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".