Efficacy of perceptive rehabilitation in the treatment of chronic nonspecific low back pain through a new tool: a randomized clinical study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the efficacy of a perceptive rehabilitative approach, based on a new device, with regard to pain and disability in patients with chronic nonspecific low back pain. DESIGN: Single blind, randomized, controlled trial. SETTING: An outpatient academic hospital. PATIENTS: Seventy-five patients with chronic low back pain. INTERVENTIONS: Patients were randomized into three groups. Twenty-five subjects received 10 sessions in one month, based on specific perceptive exercises that were performed on a suitably developed device. Twenty-five patients entered a Back School programme. Twenty-five patients comprised a control group that received the same medical and pharmacological assistance as the other groups. MAIN OUTCOME MEASURES: Pain was assessed using the Visual Analogue Scale and McGill Pain Questionnaire. Disability was evaluated using the Oswestry Disability Index and Waddell Disability Index. All measurements were recorded before treatment, at the end of the study, and at 12 and 24 weeks. RESULTS: General pain relief was recorded in all the groups, which was elicited more quickly in the perceptive treatment group; significant differences in pain scores were observed at the end of treatment (P < 0.001 for visual analogue scale and P = 0.001 for Questionnaire) versus the other groups. Disability scores in the perceptive group did not differ significantly from those in the other group, whereas these scores significantly differed between Back School and control groups at the follow-ups (P < 0.01 for both scales). CONCLUSION: Perceptive rehabilitation has immediate positive effects on pain. Back School reduces disabilities at follow-up.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".