Continuing Professional Development: Perspectives of Kenyan Nurses and Midwives
Bibliographic record
Abstract
Background: The purpose of this paper is to report the perceptions of continuous professional development by the nurses and midwives in a low resource country. These findings are part of a larger study on the experiences of nurses and midwives providing postpartum care in rural areas of Kenya. Besides being the main healthcare providers in rural areas, nurses in low resource countries have limited access to continuous professional development. Research design: This is a qualitative research guided by critical theory and Foucault’s concepts of power and knowledge. Focused ethnography provided the framework of data collection and analysis. 23 in-depth interviews were contacted, and thematic analysis was used for data analysis. Reflexive memos kept throughout the research process helped to ensure the trustworthiness of data. Findings: This paper will focus on the theme of continuing professional development (CPD) as a resource for a healthy work environment. While the knowledge of the nurses and midwives allowed them to provide care to the mothers and their infants adequately, personal and structural barriers prevented them from participating in continuing professional development. Discussion and Conclusion: A well-prepared nursing and midwifery workforce could have the capacity to transform the health outcomes of their clients through the application of evidence-based practices. Therefore, courses that are context-appropriate and meet the needs of different learners should be available to support the nurses’ and midwives’ professional growth. There is a need for more research on the nurses’ and midwives’ participation in CPD in Kenya, and the effect of CPD on specific health outcomes.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".