Comparative efficacy of three active treatment modules on psychosocial variables in patients with long-term mechanical low-back pain: a randomized-controlled trial
Bibliographic record
Abstract
Psychosocial factors precipitate and perpetuate the risk of developing long-term Low-Back Pain (LBP) with resultant disability. However, management of psychosocial aspects of LBP still remains a major challenge. This study investigated the effect of static or dynamic back extensors endurance exercise on psychosocial variables of Fear-Avoidance Behaviour (FAB), Pain Self-Efficacy Belief (PSEB) and Back Pain Consequences Belief (BPCB) in patients with LBP. A randomized-controlled trial of 67 patients assigned into McKenzie Protocol (MP) group ( n = 25), MP and Static Endurance Exercise Group (MPSEEG; n = 22); and MP and Dynamic Endurance Exercise Group (MPDEEG; n = 20) was carried out. Treatment was applied thrice weekly for eight weeks. The groups were comparable in general and baseline psychosocial parameters ( p > 0.05). The different regimens had significant effects on all outcome parameters across baseline, 4 th and 8 th week ( p < 0.05). The regimens were comparable in mean change scores on BPCB and FAB at the 4th and 8th week respectively ( p > 0.05). MPDBEEG had higher mean change in PSEB at the 4 th and 8 th week respectively. McKenzie Protocol alone, or in combination with static or dynamic back extensors endurance exercise has comparable effect on FAB, PSEB and BPCB in patients with LBP. The addition of dynamic endurance exercise to the MP led to significantly higher positive effects on PSEB.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".