Factors influencing the job satisfaction of nurses working in obstetric units in public hospitals in Kenya
Bibliographic record
Abstract
Introduction: The literature demonstrates that little research has been conducted to explore job satisfaction among nurses working in obstetric units in Kenya. The perception of job satisfaction by nurses is influenced by the environment in which they work.Methods: A cross-sectional survey design was used to carry out the study. The study tools included the work quality index (WQI) and the demographic data questionnaires. Convenience sampling method was. Data were analyzed using the SPSS version 20. The items in the WQI were organized into six subscales and Cronbach’s alpha was calculated to obtain the reliability coefficient of each subscale. An independent t-test was used to compare the subscales scores for the male and female participants. ANOVA was conducted to compare the level of satisfaction with the six subscales and the participants’ characteristics. Pearson’s product-moment correlation coefficient was calculated to assess if there was any relationships, the magnitude and the direction of the relationship between the six subscales.Results: Nurses are most satisfied with the perception that the work associated with their position provides them with the opportunity to be of service to others and least satisfied with receiving enough time to complete indirect patient care tasks. There are no significant differences in the overall level of satisfaction between males and females though males are more satisfied with autonomy of practice and professional role enactment. The six subscales strongly and positively correlate with one another.Conclusions: Nurses working in the obstetric units are relatively dissatisfied with most of the aspects of the work environment. The more educated nurses are less satisfied than less educated nurses. Since all aspects of job satisfaction are interrelated, emphasis should be put on each of them so as to create a satisfying work environment for nurses working in obstetric units.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".