Is a Behavioral Graded Activity Program More Effective Than Manual Therapy in Patients With Subacute Neck Pain?
Bibliographic record
Abstract
STUDY DESIGN: A randomized clinical trial. OBJECTIVE: To compare the effectiveness of a behavioral graded activity program with manual therapy in patients with subacute (4-12 weeks) nonspecific neck pain. SUMMARY OF BACKGROUND DATA: Neck pain is a common complaint, for which many conservative therapies are available in primary care. There is strong evidence for manual therapy in combination with exercises. Psychosocial factors are also believed to play a role in chronic pain. The evidence of the effectiveness of a program focused on these factors is still unknown. METHODS: A randomized clinical trial was conducted, involving 146 patients with subacute nonspecific neck pain. The BGA program can be described as a time-contingent increase in activities from baseline toward predetermined goals. Manual therapy consists of specific spinal mobilization techniques and exercises. Primary outcomes were global perceived effect, the Numerical Rating Scale for pain and the Neck Disability Index. Secondary outcomes were the Tampa Scale for Kinesiophobia, the 4 Dimensional Symptom Questionnaire, and the Pain Coping and Cognition List. Measurements were carried out at baseline and 6, 13, 26, and 52 weeks after randomization. Data are analyzed according to the intention-to-treat principle, using multilevel analysis. RESULTS: The success rates at 52 weeks, based on the GPE were 89.4% for the BGA program and 86.5% for MT. This difference was not statistically significant. For pain and disability, a difference was found in favor of the BGA program; mean difference for pain = 0.99 (95% CI 0.15-1.83) and mean difference for NDI = 2.42 (95% CI 0.52-4.32). All other differences between the interventions in the primary and secondary outcomes were not statistically significant. CONCLUSION: Based on this trial it can be concluded that there are only marginal, but not clinically relevant, differences between a BGA program and MT.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| 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 | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".