An investigation of the relationship between measures of pain intensity, pain affect, and disability, in patients with shoulder dysfunction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: Numerous outcomes measures can be used to capture and differentiate change in different constructs comprising recovery. Consequently, patients are often burdened by completing a number of measures which involves considerable time and effort. The purpose of this longitudinal, observational study was to identify the number of dimensions in a battery of self-report findings in a patient population who received shoulder injections to investigate the association of the instruments. METHODS: Ninety-nine subjects, with diagnoses of adhesive capsulitis, labral injuries, rotator cuff injuries, and osteoarthritis completed outcomes measures including five different forms of pain intensity measures, the McGill Short Form Questionnaire, and the Disabilities of the Arm, Shoulder, and Hand Questionnaire. Change scores were calculated at 4 weeks and an exploratory factor analysis (EFA) with varimax rotation was used to analyze dimensionality. The relationship between the raw scores of the seven measures was investigated using a correlation matrix. RESULTS: The EFA yielded only one factor and the raw score correlations demonstrated very strong, significant associations. The finding of a single factor suggests that in this sample of patients, only one dimension of change, most likely a change in pain, is represented by the seven individual outcomes measures. DISCUSSION: In this isolated example, one outcomes measure would have been sufficient in determining outcome and could have reduced the administrative burden to the caregivers and the patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 it