Do psychosocial factors predict the persistence of shoulder pain?
Bibliographic record
Abstract
Background and aims: The key mechanisms involved in the development of persistent shoulder pain are still not clearly understood. Even if psychosocial factors have been shown to be associate with chronicization of musculoskeletal pain, few studies have explored the impact of these factors in the persistence of rotator cuff related shoulder pain (RCRSP). The aim of this study was to identify the psychosocial risk factors associated with persistence of pain in individuals with RCRSP after an education program targeting shoulder pain self-management. Methods: Fifty-nine participants with persistent RCRSP completed this study (43.9±11.5years; 61%women; 70% had pain duration > 1year). Using the RedCap web application, all participants filled questionnaires covering a biopsychosocial spectrum: Brief Resilience Scale (BRS), Perceived Stress Scale (PSS-10), Disabilities of the Arm, Shoulder, and Hand Questionnaire (QuickDASH), Patient-Health Questionnaire – 9 (PHQ-9), General Anxiety Disorder – 7 (GAD-7), Pain Catastrophizing Scale (PCS), Pain Self-Efficacy Questionnaire (PSEQ) and Multidimensional Scale of Perceived Social Support (MSPSS). Thereafter, participants took part in an educational program aimed at promoting self-management of shoulder pain that included two meetings with a physiotherapist. After 3 months, participants filled the QuickDASH and, based on their scores, were classified as having persistent shoulder pain (score>11) or as recovered (score=0-11). Results: The symptoms of 24 participants (~41%) were considered resolved at 3 months. A binomial logistic regression demonstrated that only PSEQ was associated with symptoms resolution (p=.04). Lower level of self-efficacy was associated with persistent pain at 3 months (Odds Ratio= 1.08 95%Confidence Interval (CI): 1.00, 1.17. No variables predicted persistent RCRSP. Conclusions: Pain self-efficacy was the most important factor in avoiding the development of persistent RCRSP.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".