Moroccan validation of the dysfunctional beliefs and attitudes about sleep (DBAS-16) scale
Bibliographic record
Abstract
The international DBAS-16 questionnaire is an instrument that measures dysfunctional beliefs and attitudes toward sleep in the general population. It was initially developed in English in Canada by Charles Morin's team. This study aims to translate and adapt the DBAS-16 questionnaire on beliefs and attitudes toward sleep into Moroccan languages (Tamazight and Arabic) and validate it on 174 participants. From September 2019 to March 2020, 174 Moroccan participants in three cities- Fes, Kénitra, and Khémisset- participated in the adaptation and validation of DBAS-16. We translated, adapted, and validated the test into Moroccan Tamazight and Arabic according to the recommendations of “Beaton et al.” We evaluated the acceptability, reliability, central tendency, and validity of DBAS-16 in the Moroccan Arabic dialect version. Acceptability and reproducibility were satisfactory. The internal coherence was strong (Cronbach α = 0.773). The average overall score (standard deviation) on the Moroccan DBAS-16 scale was 1.71. The sub-scale scores were 2.20 for Consequences, 2.07 for Worry/Helplessness, 2.75 for Sleep Expectation, and 2.23 for Medication. Our study's results were similar to those of other countries. Moroccan versions of DBAS-16 will facilitate further studies on sleep attitudes in Morocco and elsewhere.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.003 | 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".