Dysfunctional Beliefs and Attitudes about Sleep (DBAS): Validation of a Brief Version (DBAS-16)
Bibliographic record
Abstract
STUDY OBJECTIVE: Sleep related cognitions (e.g., faulty beliefs and appraisals, unrealistic expectations, perceptual and attention bias) play an important role in perpetuating insomnia. This paper presents new psychometric data on an abbreviated version of the Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-16), a 16-item self-report measure designed to evaluate a subset of those sleep related cognitions. DESIGN: Psychometric study of a patient-reported measure of sleep related beliefs based on existing clinical and research databases. PARTICIPANTS: A total of 283 individuals (60% women; mean age of 46.6 years old) with insomnia, including 124 clinical patients and 159 research participants. MEASUREMENTS AND RESULTS: Participants completed the DBAS, Insomnia Severity Index, Beck Depression and Anxiety Inventories, daily sleep diaries for 2 weeks, and 3 nights of polysomnography (research sample only) as part of a baseline assessment. The DBAS-16 was found to be reliable, as evidenced by adequate internal consistency (Cronbach alpha = 0.77 for clinical and 0.79 for research samples) and temporal stability (r = 0.83). The factor structure was similar to the original 30-item version, with 4 factors emerging and reflecting: (a) perceived consequences of insomnia, (b) worry/helplessness about insomnia, (c) sleep expectations, and (d) medication. DBAS total scores were significantly correlated with other self-report measures of insomnia severity, anxiety, and depression, but not with specific sleep parameters. CONCLUSION: The psychometric qualities of this abbreviated DBAS-16 version seem adequate. This patient-reported measure should prove a useful instrument to evaluate the role of sleep related beliefs and attitudes in insomnia and to monitor change on this cognitive variable as a potential moderator of treatment outcome.
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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 | 0.003 | 0.009 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".