A systematic review and meta-analysis of meditative interventions for informal caregivers and health professionals
Bibliographic record
Abstract
BACKGROUND: Burnout, stress and anxiety have been identified as areas of concern for informal caregivers and health professionals, particularly in the palliative setting. Meditative interventions are gaining acceptance as tools to improve well-being in a variety of clinical contexts, however, their effectiveness as an intervention for caregivers remains unknown. AIM: To explore the effect of meditative interventions on physical and emotional markers of well-being as well as job satisfaction and burnout among informal caregivers and health professionals. DESIGN: Systematic review of randomised clinical trials and pre-post intervention studies with meditative interventions for caregivers. DATA SOURCES: PubMed, EMBASE, CINAHL and PsycINFO were searched up to November 2013. Of 1561 abstracts returned, 68 studies were examined in full text with 27 eligible for systematic review. RESULTS: Controlled trials of informal caregivers showed statistically significant improvement in depression (effect size 0.49 (95% CI 0.24 to 0.75)), anxiety (effect size 0.53 (95% CI 0.06 to 0.99)), stress (effect size 0.49 (95% CI 0.21 to 0.77)) and self-efficacy (effect size 0.86 (95% CI 0.5 to 1.23)), at an average of 8 weeks following intervention initiation. Controlled trials of health professionals showed improved emotional exhaustion (effect size 0.37 (95% CI 0.04 to 0.70)), personal accomplishment (effect size 1.18 (95% CI 0.10 to 2.25)) and life satisfaction (effect size 0.48 (95% CI 0.15 to 0.81)) at an average of 8 weeks following intervention initiation. CONCLUSIONS: Meditation provides a small to moderate benefit for informal caregivers and health professionals for stress reduction, but more research is required to establish effects on burnout and caregiver burden.
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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 | 0.016 | 0.052 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.023 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".