Psychometric properties and cross-cultural adaptation of the Patient-Rated Tennis Elbow Evaluation (PRTEE); a systematic review and meta-analysis
Bibliographic record
Abstract
To synthesize and appraise the evidence on the translation, cross-cultural adaptation, and psychometric properties of the Patient-Rated Tennis Elbow Evaluation (PRTEE). Five electronic databases were searched from 1999 to 2021. Two independent reviewers assessed the risk of bias and quality of the included studies using the COSMIN recommended guidelines. The overall quality of the evidence on each psychometric property was provided using the GRADE approach. Twenty-one studies met the criteria for inclusion in this review. The PRTEE was translated and cross-culturally adapted to 13 languages and cultures. High quality of evidence supports sufficient pooled results for test-retest reliability (0.96(CI: 0.94–0.97)), construct validity (against Disabilities of the Arm, Shoulder, and Hand (DASH): 0.81(CI: 0.76–0.85), against Visual Analogue Scale (VAS): 0.70 (0.62–0.74)), and responsiveness of the PRTEE. The overall rating of the structural validity and internal consistency (0.96(CI: 0.94–0.97)) was indeterminate, and the quality of evidence was low and moderate, respectively. Regarding measurement error, the overall rating of the summarized results (Standard error of measurement (SEM): 3.1 (1.8 to 4.4) and Minimal Detectable Change (MDC95): 8.9 (5.3–12.5)) was sufficient, and the quality of evidence was moderate. Moderate to high quality evidence supports adequate psychometric properties of the PRTEE in terms of internal consistency, test-retest reliability, measurement error, hypothesis testing for construct validity, and responsiveness.Implications for RehabilitationThe PRTEE can measure the construct of pain and disability at a single time-point and detect changes over time precisely.The PRTEE can be used in clinical setting for patients with acute, subacute, and chronic Lateral Elbow Tendinopathy (LET), athletes who suffer from elbow pain and tennis players. The PRTEE can measure the construct of pain and disability at a single time-point and detect changes over time precisely. The PRTEE can be used in clinical setting for patients with acute, subacute, and chronic Lateral Elbow Tendinopathy (LET), athletes who suffer from elbow pain and tennis players.
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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 | 0.062 | 0.143 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.027 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".