An Exploratory Study on the Effect of Pain Interference and Attentional Interference on Neuromuscular Responses During Rapid Arm Flexion Movements
Bibliographic record
Abstract
OBJECTIVES: This study examined the effect of pain interference and attentional interference on the anticipatory postural adjustments of trunk muscles in patients with nonspecific chronic low back pain. METHODS: Fifty-nine patients performed rapid flexion movements of the right arm under 6 conditions, namely a control condition and conditions with different attention demands. The latency between the activations of the shoulder and different trunk muscles, as measured with surface electromyography, was used as the outcome. Using repeated measures analysis of variance, attention conditions and group comparisons were tested between those who scored high and low on pain intensity, fear of movement, or pain catastrophizing. RESULTS: There were significant (although minimal) interactive effects but significant and potentially clinically relevant group and attention main effects. The group with the lowest scores showed delayed activity (14 to 29 ms) relative to those with higher scores. One attention-demanding condition delayed (20 to 35 ms) the latencies of some trunk muscles relative to the control condition, namely the one that was the most attention-demanding according to the reaction time results. DISCUSSION: These findings suggest that patients with chronic low back pain, who are characterized by higher scores on some pain-related variables (visual analog scale, Tampa Scale of Kinesiophobia, Pain Catastrophizing Scale), react favorably to protect the spine from further pain and injuries but would be at greater risk of injury when performing a complex physical task requiring more attention demand.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".