Attrition and Adherence in the Online Treatment of Chronic Insomnia
Bibliographic record
Abstract
This study examined the ability of the Theory of Planned Behavior (TPB; Ajzen, 1985 Ajzen, I. 1985. “From intentions to actions: A theory of planned behaviour.”. In Action control: From cognition to behavior Edited by: Kuhl, J. and Beckmann, J. 11–39. Heidelberg, , Germany: Springer. [Crossref] , [Google Scholar]) and the Transtheoretical Model of Behavior Change (TTM; Prochaska & DiClemente, 1983 Prochaska, J. O. and DiClemente, C. C. 1983. Stages and processes of self-change in smoking: Towards an integrated model of change. Journal of Consulting and Clinical Psychology, 51: 390–395. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) to explain adherence and attrition in an online treatment program for chronic insomnia. Responses to questionnaire measures of the TPB and TTM were used to predict adherence and dropout over the subsequent 5 weeks of treatment. Results showed that there was a 17% dropout rate and that perceived behavioral control, social support, and intention to complete the program were significantly associated with adherence to sleep hygiene homework. Attrition was predicted only by symptom severity and psychiatric comorbidity. Implications are that these models should be considered to maximize adherence.
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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 | 0.011 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".