Psychophysical and Patient Factors as Determinants of Pain, Function and Health Status in Shoulder Disorders
Bibliographic record
Abstract
Objective: To estimate the extent to which psychophysical quantitative sensory test (QST) and patient factors (gender, age and comorbidity) predict pain, function and health status in people with shoulder disorders. To determine if there are gender differences for QST measures in current perception threshold (CPT), vibration threshold (VT) and pressure pain (PP) threshold and tolerance. Design: A cross-sectional study design. Setting: MacHAND Clinical Research Lab at McMaster University. Subjects: 34 surgical and 10 nonsurgical participants with shoulder pain were recruited. Method: Participants completed the following patient reported outcomes: pain (Numeric Pain Rating, Pain Catastrophizing Scale, Shoulder Pain and Disability Index) and health status (Short Form-12). Participants completed QST at 4 standardized locations and then an upper extremity performance-based endurance test (FIT-HaNSA). Pearson r’s were computed to determine the relationships between QST variables and patient factors with either pain, function or health status. Eight regression models were built to analysis QST’s and patient factors separately as predictors of either pain, function or health status. An independent sample t-test was done to evaluate the gender effect on QST. Results: Greater PP threshold and PP tolerance was significantly correlated with higher shoulder functional performance on the FIT-HANSA (r =0.31-0.44) and lower self-reported shoulder disability (r = -0.32 to -0.36). Higher comorbidity was consistently correlated (r =0.31-0.46) with more pain, and less function and health status. Older age was correlated to more pain intensity and less function (r =0.31-0.57). In multivariate models, patient factors contributed significantly to pain, function or health status models (r 2 =0.19-0.36); whereas QST did not. QST was significantly different between males and females [in PP threshold (3.9 vs . 6.2, p < .001) and PP tolerance (7.6 vs . 2.6, p < .001) and CPT (1.6 vs . 2.3, p =.02)]. Conclusion: Psychophysical dimensions and patient factors (gender, age and comorbidity) affect self-reported and performance-based outcome measures in people with shoulder disorders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".