Relation Between Adherence and Outcome in the Group Treatment of Insomnia
Bibliographic record
Abstract
This study evaluated adherence to group cognitive behavioral treatment in 50 adults with chronic insomnia. Adherence was measured using questionnaire data, consistency of sleep scheduling, and % of sessions attended. Results showed that therapists' rated 48% of participants as "very much" to "extremely" adherent. Using stepwise regression, only therapist-rated adherence explained a significant amount of variance in post-treatment outcome. Therapist-rated adherence predicted post-treatment ratings of sleep-related impairment, dysfunctional beliefs about sleep, and overall sleep quality (but not actual sleep duration or efficiency). Using a multivariate analysis of variance (MANOVA) procedure, results revealed that a diagnosis of dysthymia, based on a structured clinical interview, was associated with reduced adherence and less improvement in sleep-onset latency and sleep efficiency, but that scores on a dimensional measure of depression were not associated with either adherence or outcome. Implications of these findings are that the practice of treatment techniques is related to an improved perception of sleep and more healthy and appropriate beliefs about the causes of poor sleep. Therapists should continue to pay close attention to the adherence behavior of those with insomnia, particularly if they are depressed.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".