Bibliographic record
Abstract
The following is a review of literature concerning the place of mindfulness, a non-judging present-moment awareness, and techniques by which to invoke it, in Canadian healthcare. Central to the discussion are the effects of mindfulness on personal and interpersonal well-being. Mindfulness has been found to positively impact a wide range of measures of personal health including stress, anxiety, affect, and healthy lifestyle choices. It also presents benefits to interpersonal relationships by promoting empathy, compassion and attentiveness, which in turnfacilitate healthy physician-patient relationships and high quality of medical care.At present, mindfulness-based therapies are applied to a wide range of psychiatric and somatic illnesses with impressive efficacy. With recent growth in research interest, new worthwhile applications of mindfulness such as mindfulness training for physicians as a means to prevent burnout and compassion fatigue continue to be uncovered. Recent investigations of mechanisms underlying the effects of mindfulness are also discussed. There exists an emerging emphasis onthe disempowerment of maladaptive cognitions as determinants of behaviour, leaving the individual free to skillfully, consciously and deliberately navigate her mental life. Given the evidently remarkable potential for mindfulness to promote health, its increased utilization among patients, physicians, and the population at large is advocated in this writing.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".