A New Educational Program could Reduce Disability and Improve Quality of Life in Patients with Chronic Low Back Pain
Bibliographic record
Abstract
This randomized clinical trial examined the efficacy of a designed educational program versus oral drug treatment in Iran. A total of 197 patients with chronic low back pain were randomized into either intervention group (n = 97) receiving a five 2 hour– session educational program followed by continued monthly booster sessions and telephone counseling plus medication or to control group (n = 100) receiving just medication. At baseline and 3 months of follow up, participants completed demographic characteristic questionnaires as well as three other questionnaires including Short – form General Health Survey (SF-36 item), Quebec Disability Scale (QDS) and Ronald – Morris Disability Questionnaire (RDQ). Data were analyzed by SPSS 18. The two groups were comparable at baseline in terms of all baseline characteristics and the mean scores of the scales. However, after three months, the intervention group was significantly different from control group in all subscales of SF-36, QDS and RDQ (P values < 0.05). Furthermore, this study showed a statistically significant difference between two groups (P< 0.05) in terms of mean difference scores for SF -36, RDQ and QDS over time. The findings revealed that the designed educational program could improve all quality of life domains and reduce disability in chronic low back pain patients during a period of 3 months.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".