Exploring the impact of mindfulnesss on mental wellbeing, stress and resilience of undergraduate social work students
Bibliographic record
Abstract
Mindfulness is becoming more popular as emerging research demonstrates its benefits for self-care, by cultivating calmness and decreasing stress or anxiety. This pilot study aimed to measure the impact of a six-week Mindfulness course, modelled on the manualised treatment programme developed by Kabat-Zinn on the mental well-being, stress and resilience of undergraduate social work students in Northern Ireland. This was a mixed methods study involving two groups: (1) intervention group participants who attended a six-week Mindfulness course (April–May 2016) and (2) control group participants. Basic socio-demographic data were collected from all participants and all were invited to complete the Warwick-Edinburgh Mental Well-being Scale, the Perceived Stress Scale and the Resilience Scale during weeks 1 and 6. Statistical tests were used to compare mean scores from the scales, and qualitative data were manually analysed using thematic content analysis. Findings indicated significant changes in the scores for well-being, stress and resilience for the intervention group, but not for the control group. Mindfulness may not appeal to all students so it should not be a mandatory component of training, but may be offered as one of the wider approaches to self-care for undergraduate social work degree students.
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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 | 0.002 |
| 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 | 0.001 |
| 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".