Cross-cultural adaptation and measurement properties of the Patient-Rated Tennis Elbow Evaluation for the Persian language
Bibliographic record
Abstract
Introduction The Patient-Rated Tennis Elbow Evaluation (PRTEE) questionnaire is a tool designed for self-assessment of forearm pain and disability in patients with tennis elbow. The aims of this study were to translate and cross-culturally adapt the PRTEE questionnaire into Persian and evaluate its reliability and construct validity. Methods The PRTEE questionnaire was translated into and cross-culturally adapted to Persian in 90 consecutive patients with tennis elbow, according to well-established guidelines. Reliability was tested by means of test–retest and internal consistency. The measurement error was measured by calculating the standard error of measurement. Based on the standard error of measurement, the minimum detectable change was calculated. To evaluate construct and convergent validity, correlation with the PRTEE with the Disabilities of the Arm, Shoulder and Hand questionnaire and Visual analogue scale was used. Results In the process of cross-cultural adaptation, two items (6 and 8) were modified. In item 6, the term “door knob” was changed to “turn a key”, and in the item 8, “cup of coffee” was changed to “cup of milk”. Item-total correlations were greater than 0.55 (ranged from 0.55 to 0.76), internal consistency was high (Cronbach’s alpha, 0.94) and a high intraclass correlation coefficient (0.98) indicated excellent reliability of the P-PRTEE. The standard error of measurement and minimum detectable change were 5.40 and 14.24, respectively. The Persian version of the PRTEE questionnaire (P-PRTEE) shows strong construct and convergent validity ( r values = 0.85, p < 0.05). Conclusions The P-PRTEE is valid and reliable in assessing disability and pain in Persian patients with tennis elbow. The excellent psychometric properties of the P-PRTEE endorse the use of this questionnaire in clinical settings.
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.
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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".