Translation and Validation of the Arabic Version of the Athlete Sleep Screening Questionnaire
Bibliographic record
Abstract
Sleep improves the cognitive and physical performance of athletes. A detailed questionnaire that detects sleep disruptions is required to identify sleep-deprived athletes. This study evaluates the translated Athlete Sleep Screening Questionnaire (ASSQ), a tool suggested by the International Olympic Committee, among Arabic-speaking athletes. The ASSQ was translated into Arabic and examined for floor or ceiling effects, internal consistency, and validity among Arabic-speaking athletes. The Arabic Pittsburgh Sleep Quality Index (PSQI) was employed to assess convergent validity. Ninety athletes (28.9% women) participated and completed this study’s questionnaires. The Cronbach’s alpha for the ASSQ-Sleep Difficulty Score (SDS) was 0.435, and that of the ASSQ-chronotype was 0.632. The SDS and chronotype subset of the ASSQ demonstrated excellent test-retest reliability, with intraclass correlation coefficients of 0.84 and 0.938, respectively. The ASSQ-SDS correlated positively with the PSQI (0.734, p = 0.001). The ASSQ-chronotype was inversely associated with the PSQI (p = 0.001). This study’s findings can assist clinicians in assessing sleep disorders in sports. The Arabic version of the ASSQ has satisfactory psychometric qualities and can identify clinically relevant sleep problems in athletes.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".