Attention Modification in Persons with Fibromyalgia: A Double Blind, Randomized Clinical Trial
Bibliographic record
Abstract
Contemporary models of chronic musculoskeletal pain emphasize the critical roles of fear, anxiety, and avoidance as well as biases in attention in the development and maintenance of chronic pain disability. Evidence supports the influence of individual difference variables such as anxiety sensitivity, pain-related anxiety, and catastrophizing on the pain experience and on pain-related attentional biases. Changes in attentional biases have been associated with treatment gains in patients with clinically significant anxiety. The Attentional Modification Paradigm (AMP) is a modification of the dot-probe paradigm used to facilitate such changes in attentional biases. Given the relationship between chronic musculoskeletal pain and anxiety, AMP may be effective in reducing pain as well. Participants included persons (n = 17) with fibromyalgia and were randomly assigned to either an AMP condition or a control condition. The participants completed two 15-minute AMP sessions per week for 4 weeks. Those in the AMP condition reported statistically significant and substantial reductions on several individual difference variables relative to those in the control condition, and a greater proportion experienced clinically significant reductions in pain. These preliminary results offer a promising new avenue for treating chronic musculoskeletal pain that warrants additional research. Comprehensive results, limitations, and future directions are discussed.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| 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) | 0.008 | 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".