Primary care provider's job satisfaction and organizational commitment after COVID-19 restrictions ended: A mixed-method study using a mediation model
Bibliographic record
Abstract
Objectives: More and more countries have decided to cancel most or even all COVD-19 restrictions. However, it is unclear how ending of restrictions will affect primary care providers' job satisfaction and organizational commitment. Our objectives are to explore the current status and possible change in primary care providers' job satisfaction and organizational commitment after massive restriction policies ended in China. Methods: This was a mixed-method study that utilized structured questionnaires and semi-structured qualitative individual interviews. The 20-item Minnesota Satisfaction Questionnaire (MSQ) and 25-item organizational commitment survey were adopted to assess job satisfaction and organization commitment. Descriptive statistics and mediation models, as well as inductive thematic analysis, were used to analyze quantitative and qualitative data. Results: A total of 18 interviews and 435 valid survey responses were included in our analysis. The average scores for job satisfaction and organizational commitment were 80.6 and 90.8. The thematic analysis revealed one major theme: ethical and moral responsibility to provide care as primary care providers, on which we established a mediation model. The mediation analysis revealed that normative commitment could positively affect the other four dimensions of organizational commitment and job satisfaction. The direct effect of affective commitment on job satisfaction was significant (LLCI = 0.11, ULCI = 0.31), and the mediators were identified to have a partial mediating effect instead of a total mediating effect. Conclusion: After COVID-19 restrictions end, the job satisfaction and organizational commitment of primary care providers will return to levels before the pandemic and during this estimated process, a brief rise in resignation is predictable. The normative commitment positively affects the other four dimensions of organizational commitment and job satisfaction for primary care providers, which suggests a possible way to motivate primary care providers when restrictions end.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 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".