Need Fulfillment and Resilience Mediate the Relationship between Mindfulness and Coping in Medical Students
Bibliographic record
Abstract
Theory: Medical programs have turned to mindfulness-based initiatives to help reduce student distress and promote healthy coping within the learning environment. However, little attention has been paid to how fulfillment of medical students’ basic psychological needs (autonomy, competence, and relatedness) impacts their capacity to be mindful and cope with stress. Self-Determination Theory (SDT) posits that mindfulness facilitates adaptive coping and wellness, in large part because of need fulfillment. Hypotheses: Using SDT as a lens, it is hypothesized that medical students’ resilience and, to a greater extent, need fulfillment in medical school, will mediate the relationship between their mindfulness and coping reactions to stress. Method: One-hundred-ninety-seven medical students from the University of Saskatchewan were recruited to participate in this study: 71 first year, 58 second year, and 36 third and fourth year, each. Students completed an anonymous survey, measuring need fulfillment in medical school, mindfulness, resilience, and frequent use of various adaptive and maladaptive coping strategies. We assessed the extent that need fulfillment and resilience mediated the relationship between mindfulness and coping styles. Results: Need satisfaction and resilience fully mediated the relationship between mindfulness and adaptive coping. Conversely, need frustration and resilience partially mediated the relationship between mindfulness and maladaptive coping. Need fulfillment was a stronger mediator than resilience in both coping models. Conclusions: Findings suggest that increased supports for medical students’ resilience and basic psychological needs may promote their mindfulness, and in turn, their ability to respond more adaptively and less maladaptively to stressors they face in medical school.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".