The effects of midwives’ job satisfaction on burnout, intention to quit and turnover: a longitudinal study in Senegal
Bibliographic record
Abstract
BACKGROUND: Despite working in a challenging environment plagued by persistent personnel shortages, public sector midwives in Senegal play a key role in tackling maternal mortality. A better understanding of how they are experiencing their work and how it is affecting them is needed in order to better address their needs and incite them to remain in their posts. This study aims to explore their job satisfaction and its effects on their burnout, intention to quit and professional mobility. METHODS: A cohort of 226 midwives from 22 hospitals across Senegal participated in this longitudinal study. Their job satisfaction was measured from December 2007 to February 2008 using a multifaceted instrument developed in West Africa. Three expected effects were measured two years later: burnout, intention to quit and turnover. Descriptive statistics were reported for the midwives who stayed and left their posts during the study period. A series of multiple regressions investigated the correlations between the nine facets of job satisfaction and each effect variable, while controlling for individual and institutional characteristics. RESULTS: Despite nearly two thirds (58.9%) of midwives reporting the intention to quit within a year (mainly to pursue new professional training), only 9% annual turnover was found in the study (41/226 over 2 years). Departures were largely voluntary (92%) and entirely domestic. Overall the midwives reported themselves moderately satisfied; least contented with their "remuneration" and "work environment" and most satisfied with the "morale" and "job security" facets of their work. On the three dimensions of the Maslach Burnout Inventory, very high levels of emotional exhaustion (80.0%) and depersonalization (57.8%) were reported, while levels of diminished personal accomplishment were low (12.4%). Burnout was identified in more than half of the sample (55%). Experiencing emotional exhaustion was inversely associated with "remuneration" and "task" satisfaction, actively job searching was associated with being dissatisfied with job "security" and voluntary quitting was associated with dissatisfaction with "continuing education". CONCLUSIONS: This study found that although midwives seem to be experiencing burnout and unhappiness with their working conditions, they retain a strong sense of confidence and accomplishment in their work. It also suggests that strategies to retain them in their positions and in the profession should emphasize continuing education.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".