The Influence Of Exercise Volume In Chronic Non-specific Low Back Pain Rehabilitation
Bibliographic record
Abstract
Approximately 80% of North Americans suffer from low back pain, and 85% of these are diagnosed as chronic non-specific low back pain (CLBP). In 2005, the economic cost associated with back pain was ∼$38 million as reported by Workers' Compensation Board-Alberta. PURPOSE: To determine the impact of 3 different volumes of CLBP rehabilitation (exercise therapy) on the outcome measures of strength, pain, and quality of life (QOL). METHODS: One hundred and twenty (N=30/group) CLBP males were randomly assigned to one of the following groups: 2 days/wk (2D), 3 days/wk (3D), 4 days/wk (4D) rehabilitation, or Control (C; no rehabilitation). Rehabilitation group participants completed a 2-wk exercise familiarization period. Musculoskeletal (repetition maximum) testing occurred following familiarization at baseline, wks 8 and 12. The participant's pain (11-point visual analogue scale; VAS) and QOL (Short Form-36: Physical and Mental Composite Summaries) were measured at baseline, wks 8 and 12. RESULTS: The p-level was set at ≤0.05. There were no significant differences between groups at baseline, but significant differences were present within groups across time and between groups on strength, pain, and QOL (Table). All rehabilitation groups were significantly different than the control group at wk 12.TABLECONCLUSION: A volume of 4 days/wk demonstrated greater improvement in outcome measures, especially pain and QOL, than either 2 or 3 day/wk programs. Sponsored by the Augustana Research grant.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".