On the global and specific nature of psychological need satisfaction and work motivation in predicting employees' wellbeing: a self-determination theory perspective
Bibliographic record
Abstract
Abstract Using data from 708 French-Canadian nurses, the present study relies on self-determination theory (SDT) and its proposed motivation mediation model to examine the associations between need satisfaction, work motivation, and various manifestations of psychological wellbeing (work satisfaction, emotional exhaustion, and turnover intentions). To increase the precision and accuracy of these analyses, we relied on analytic approaches that explicitly account for the dual global/specific nature of both work motivation and need satisfaction. Results revealed that nurses' global psychological need satisfaction, and their specific autonomy and competence satisfaction, were positively associated with their global self-determined work motivation and specific intrinsic motivation. In turn, global self-determined work motivation and specific intrinsic motivation were associated with more desirable outcome levels. Nurses' global need satisfaction and specific autonomy satisfaction were also directly associated with more desirable outcome levels. Our results provided support for a partially mediated version of SDT's motivation mediation model.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".