Reliability and validity of the Brief Pain Inventory-Short Form in individuals with rotator cuff-related shoulder pain
Bibliographic record
Abstract
Purpose To investigate the test–retest reliability and construct validity of the Brief Pain Inventory-Short Form (BPI-SF) in individuals with rotator cuff-related shoulder pain (RCRSP).Methods Sixty-one participants with RCRSP completed the BPI-SF twice with an interval of two to seven days and Shoulder Pain and Disability Index (SPADI) at the initial visit. The BPI-SF pain severity subscale, pain interference subscale, and stand-alone pain severity items were analysed using intraclass correlation coefficients (ICCs) and minimal detectable change at the 95% confidence interval (MDC95). The construct validity of BPI-SF was assessed against SPADI using Pearson’s correlation.Results The BPI-SF pain severity and pain interference subscales presented moderate test–retest reliability (ICC = 0.73, 0.53) and MDC95 were 2.05 and 2.36. All stand-alone BPI-SF pain severity items presented a moderate reliability (ICC = 0.62, 0.70). BPI-SF interference items presented poor to moderate reliability (ICC = 0.39, 0.68). The correlation coefficients between the BPI-SF and SPADI subscales or total scores were large (r = 0.61, 0.75).Conclusions BPI-SF pain severity and pain interference subscales have a moderate reliability in individuals with RCRSP. BPI-SF pain severity and interference subscales showed high construct validity in individuals with RCRSP. MDC95 values are useful metrics for interpreting a true change in BPI-SF scores following interventions in individuals with 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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".