Enhancing Job Motivation through a Targeted Burnout Workshop: A Randomized Controlled Trial
Bibliographic record
Abstract
This study aims to evaluate the effectiveness of an 8-session job burnout workshop designed to enhance job motivation among employees experiencing mild to moderate levels of job burnout. A total of 40 participants with at least one year of work experience in their current role were randomized into either the intervention group, which received the job burnout workshop, or a control group, which did not. The workshop comprised 8 sessions, each lasting 75 minutes, covering topics such as understanding job burnout, its causes and effects, and stress management techniques. Job motivation was measured using the Job Diagnostic Survey (JDS) before and after the intervention. Participants in the intervention group showed a significant improvement in job motivation scores compared to the control group. The findings suggest that targeted interventions, like the job burnout workshop, can effectively enhance job motivation and potentially mitigate feelings of burnout. The job burnout workshop presents a promising approach to improving job motivation among employees suffering from burnout. This intervention could be a valuable component of organizational strategies aimed at enhancing employee well-being and productivity.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".