A systematic review and meta-analysis exploring the efficacy of mindfulness-based interventions on quality of life in people with multiple sclerosis
Bibliographic record
Abstract
Abstract Background Quality of life (QoL) is commonly impaired among people with multiple sclerosis (PwMS). The aim of this study was to evaluate via meta-analysis the efficacy of Mindfulness-based interventions (MBIs) for improving QoL in PwMS. Methods Eligible randomized controlled trials (RCTs) were identified via searching six major electronic databases (MEDLINE, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials, AMED, and PsycINFO) in April 2022. The primary outcome was QoL. Study quality was determined using the Cochrane Collaboration risk of bias tool. Meta-analysis using a random effects model was undertaken. Effect sizes are reported as Standardized Mean Difference (SMD). Prospero ID: 139835. Results From a total of 1312 individual studies, 14 RCTs were eligible for inclusion in the meta-analysis, total participant n = 937. Most studies included PwMS who remained ambulatory. Cognitively impaired PwMS were largely excluded. Comorbidities were inconsistently reported. Most MBIs were delivered face-to face in group format, but five were online. Eight studies ( n = 8) measured MS-specific QoL. In meta-analysis, overall effect size (SMD) for any QoL measure ( n = 14) was 0.40 (0.18–0.61), p = 0.0003, I 2 = 52%. SMD for MS-specific QoL measures ( n = 8) was 0.39 (0.21–0.57), p < 0.0001, I 2 = 0%. MBI effect was largest on subscale measures of mental QoL ( n = 8), SMD 0.70 (0.33–1.06), p = 0.0002, I 2 = 63%. Adverse events were infrequently reported. Conclusions MBIs effectively improve QoL in PwMS. The greatest benefits are on mental health-related QoL. However, more research is needed to characterize optimal formatting, mechanisms of action, and effects in PwMS with more diverse social, educational, and clinical backgrounds.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".