Improving Postoperative Care Through Mindfulness-Based and Isometric Exercise Training Interventions: Systematic Review
Bibliographic record
Abstract
BACKGROUND: Mindfulness-based cognitive therapy and isometric exercise training (IET) interventions are relatively new approaches to maintain physical functioning, alleviate pain, prevent joint stiffness and muscular atrophy, and positively influence other postoperative care outcomes. OBJECTIVE: The aim of this review was to identify the impacts of mindfulness-based interventions (MBIs) and IET and, more specifically, their combination, which have not previously been assessed to our knowledge. METHODS: Studies were identified by searching the PubMed and Cochrane databases within the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) algorithm format and using relevant keyword combinations, which resulted in 39 studies meeting the inclusion criteria. RESULTS: In general, MBI was shown to positively impact both pain relief and physical functioning, while IET positively impacted physical functioning. Numerous other benefits, including improved quality of life and decreased postoperative opioid use, were also described from both interventions; however, further research is needed to confirm these findings as well as to determine other possible benefits. No studies were found that combined MBI and IET. CONCLUSIONS: Despite many positive results from each individual intervention, there is a lack of information about how the combination of MBI and IET might impact postoperative care. The combination of these two interventions might prove to be more effective than each individual intervention alone, and the findings from this review show that they could even be complementary. Going forward, research should be expanded to study the possible benefits of the combination of MBI and IET in postoperative care routines as well as other possible combinations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.072 | 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 teacher head, 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".