Relations between Psychological Needs Satisfaction, Motivation, and Self-Regulated Learning Strategies in Medical Residents: A cross-sectional Study
Bibliographic record
Abstract
This article was migrated. The article was marked as recommended. Residents in the medical field work to fulfil their clinical duties and study to pass exams at the same time. Thus, they need to continuously learn and acquire knowledge in a self-regulated manner that accommodates their busy work schedule. The importance of self-regulated learning (SRL) and its relation to motivation is widely recognized in educational literature, yet it is still not sufficiently explored in medical education literature. The relationship between self-regulated learning (SRL) and motivation has not been sufficiently explored among medical residents. A total of 160 residents from different medical departments at McGill University were asked to complete a questionnaire about their psychological needs satisfaction, motivation to learn, and use of SRL strategies. Our results showed that residents who are more intrinsically motivated reported more utilization of SRL strategies. Results are discussed in terms of their impact on medical education practice as well as their theoretical implications.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".