Engagement among physicians fighting COVID-19: the mediating role of autonomy
Bibliographic record
Abstract
BACKGROUND: Keeping and improving work engagement among physicians fighting COVID-19 is important to healthy medical systems. In line with the job demands-resources model, optimism was expected to positively relate with job resources, leading to higher work engagement. However, the underlying mechanism between optimism, autonomy and work engagement has not been explored. AIMS: To examine whether optimism has a positive impact on work engagement via autonomy among physicians fighting COVID-19 in China. METHODS: This study was conducted among physicians in March 2020. A convenience sample was used to recruit physicians from the Wuhan Leishenshan Hospital and Wuhan Jinyintan Hospital. One hundred and four Chinese physicians working in the COVID-19 epidemic completed a survey measuring levels of autonomy, optimism and work engagement. The PROCESS macro (model 4) was used to test hypotheses about mediation. RESULTS: This current study found that optimism was related to increased autonomy, and autonomy was related to increased work engagement. The results of the bias-corrected bootstrap method suggested the indirect effect of optimism on work engagement via autonomy (Effect = 0.16, SE = 0.08, lower level confidence interval = 0.04, upper level confidence interval = 0.37), indicating a mediated relationship, in which autonomy is one mechanism to explain the link between optimism and increased work engagement. CONCLUSIONS: This study follows an observational design, with in-depth analysis of the relationship between optimism, autonomy and work engagement. When management implements strategies to improve work engagement among physicians working in the COVID-19 epidemic, the mediating impact of autonomy on the association between optimism and work engagement should be considered.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".