The Influence of Pain-Related Fear on Peak Muscle Activity and Force Generation During Maximal Isometric Trunk Exertions
Bibliographic record
Abstract
In Brief Study Design. A cross-sectional study of peak activation of trunk muscles in 20 participants with chronic low back pain. Objective. To determine how pain-related fear influences peak activation of abdominal and trunk extensor muscles during maximal isometric trunk exertions. Summary of Background Data. The pain adaptation model and the pain-spasm-pain model have been proposed to explain differences in trunk muscle activation between healthy participants and those with chronic low back pain. However, there is no clear consensus in the literature in support of either model, and there are no studies that have examined the role of pain-related fear on muscle activity in the context of these 2 models. Methods. Participants with chronic low back pain performed a series of maximal isometric exertions into extension, flexion, rotation right and left, and side-bend right and left from a tall kneeling position with the spine in a neutral posture. A doubly multivariate MANCOVA was conducted with a between subject factor of group (high pain-related fear, low pain-related fear), a within subject factor of direction (extension, flexion, rotation left and right, side bend left and right), McGill Pain Questionnaire ratings entered as covariates, and peak EMG for all 10 trunk muscles entered as dependent variables. Results. Averaged across all pull directions and all 10 trunk muscles assessed, participants with high pain-related fear had peak EMG that was only 49.5% of participants with low fear. Additionally, we found significantly smaller peak force for isometric exertions in flexion, side-bend right, and side-bend left directions. Conclusion. Pain-related fear is associated with increased disability, in theory, because of avoidance behavior and disuse. Our data suggest that participants high in pain-related fear specifically avoid activation of the abdominal muscles during maximal isometric trunk exertions. The influence of pain-related fear on peak activation of 10 trunk muscles of individuals with chronic back pain is assessed during maximal isometric trunk exertions in a neutral spine posture. Participants with high pain-related have smaller peak activation of their trunk muscles compared to participants with low pain-related fear. The pattern of avoidance may be a significant contributing factor in their continuing disability.
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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 | 0.001 |
| 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".