Cognitive-Behavioral Therapists’ Experience on Relevance of Sleep and Sleep Disorders in Training and Clinical Practice: A Survey Study from Italy
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Based on previous data reporting the status of health professionals' training about sleep clinical psychophysiology, insomnia, and its treatment in the US and Canada, this paper aims at providing a snapshot of the Italian situation, considering health professionals qualified to offer cognitive behavioral therapy (CBT). Adding information on different countries is important, as national health systems differ significantly, and distinct evidence-based pathways for change may be proposed. METHODS: Two hundred and thirteen CBT professionals (180 females; 33 males) answered a 5 min survey about their training and experience in recognizing and treating behavioral sleep disorders in their practice. The questionnaire was diffused through the mailing list of the Italian Behavioral and Cognitive Therapy Society (Società Italiana di Terapia Comportamentale e Cognitiva, SITCC) throughout December 2023 and January 2024. RESULTS: A total of 213 participants completed the survey. Only a minor proportion of respondents (37.1%) reported having received training for diagnosis and treatment of insomnia or other behavioral sleep disorders. Familiarity with psychological therapeutics for sleep was mainly associated with knowledge of sleep hygiene rules, relaxation, and mindfulness techniques, but not with core CBT strategies for insomnia (i.e., sleep restriction and stimulus control) and sleep regulation. The less familiar therapeutics were those for pediatric insomnia. CONCLUSIONS: The results of this study highlight scarce knowledge and consideration of sleep problems in CBT practice in Italy. As insomnia is prevalent, an independent mental disorder, and a predictor for mental and somatic comorbid conditions, these findings underscore an urgency to enlarge and strengthen CBT professionals' training on sleep psychophysiology, sleep clinical psychology, insomnia, behavioral sleep problems, and their treatment.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".