Developing a tool to measure satisfaction among health professionals in sub-Saharan Africa
Bibliographic record
Abstract
BACKGROUND: In sub-Saharan Africa, lack of motivation and job dissatisfaction have been cited as causes of poor healthcare quality and outcomes. Measurement of health workers' satisfaction adapted to sub-Saharan African working conditions and cultures is a challenge. The objective of this study was to develop a valid and reliable instrument to measure satisfaction among health professionals in the sub-Saharan African context. METHODS: A survey was conducted in Senegal and Mali in 2011 among 962 care providers (doctors, midwives, nurses and technicians) practicing in 46 hospitals (capital, regional and district). The participation rate was very high: 97% (937/962). After exploratory factor analysis (EFA), construct validity was assessed through confirmatory factor analysis (CFA). The discriminant validity of our subscales was evaluated by comparing the average variance extracted (AVE) for each of the constructs with the squared interconstruct correlation (SIC), and finally for criterion validity, each subscale was tested with two hypotheses. Two dimensions of reliability were assessed: internal consistency with Cronbach's alpha subscales and stability over time using a test-retest process. RESULTS: Eight dimensions of satisfaction encompassing 24 items were identified and validated using a process that combined psychometric analyses and expert opinions: continuing education, salary and benefits, management style, tasks, work environment, workload, moral satisfaction and job stability. All eight dimensions demonstrated significant discriminant validity. The final model showed good performance, with a root mean square error of approximation (RMSEA) of 0.0508 (90% CI: 0.0448 to 0.0569) and a comparative fit index (CFI) of 0.9415. The concurrent criterion validity of the eight dimensions was good. Reliability was assessed based on internal consistency, which was good for all dimensions but one (moral satisfaction < 0.70). Test-retest showed satisfactory temporal stability (intra class coefficient range: 0.60 to 0.91). CONCLUSIONS: Job satisfaction is a complex construct; this study provides a multidimensional instrument whose content, construct and criterion validities were verified to ensure its suitability for the sub-Saharan African context. When using these subscales in further studies, the variability of the reliability of the subscales should be taken in to account for calculating the sample sizes. The instrument will be useful in evaluative studies which will help guide interventions aimed at improving both the quality of care and its effectiveness.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".