ADHERENCE TO PRESCRIBED EXERCISE AND CLINICAL OUTCOMES IN PEOPLE WITH CHRONIC NONSPECIFIC LOW BACK PAIN: A SYSTEMATIC REVIEW AND META-ANALYSIS
Bibliographic record
Abstract
BACKGROUND Exercise is widely accepted as a first-line treatment for chronic non-specific low back pain (CNSLBP). However, the benefits of exercise diminish over time, as does adherence to exercise. It is unclear whether greater exercise adherence is associated with improvements in pain intensity (PI) and functional limitation (FL). We explored the relationship between exercise adherence and patient-reported outcomes in people with CNSLBP. METHODS We conducted a secondary analysis of the Cochrane systematic review, ‘Exercise therapy for chronic low back pain’, using a subset of 24 trials that measured exercise adherence compared to usual care. Random-effects meta-analysis was performed in R for PI and FL at the closest time point post-intervention. We used predefined subgroups of exercise adherence of ‘Good’ (90-100%), ‘Moderate’ (70-89%), or ‘Poor’ (14-69%) adherence. We used the risk of bias judgements provided by Cochrane. RESULTS All trials included were deemed low risk of bias. Compared to usual care, ‘Good’ adherence was associated with reduced PI by 17.83 points on a 100-point scale (95% CI -26.23 to -9.43; I2 = 81.7%) and FL by 9.69 points on a 100-point scale (95% CI -12.64 to -6.74; I2 = 18.9%). ‘Moderate’ adherence was associated with reduced PI by 6.93 points (95% CI -10.43 to -3.44; I2 = 18.3%) and FL by 3.80 points (95% CI -6.10 to -1.49; I2 = 0%). ‘Low’ adherence was associated with reduced PI by 7.50 points (95% CI -19.83 to -4.84; I2 = 89.7%) and FL by 3.35 points (95% CI -10.45 to -3.74; I2 = 82.7%). CONCLUSIONS Greater adherence to exercise is associated with greater improvements in PI and FL in adults with CNSLBP. Further research is needed to understand the causal effect of adherence on patient-reported outcomes. Better reporting of this potentially important exercise parameter in randomised trials is also needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.031 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".