0536 Motivation at Pretreatment and its Correlates in a Trial of Digital CBT For Insomnia: Preliminary Findings
Bibliographic record
Abstract
Abstract Introduction Pretreatment motivation is a critical variable in any intervention seeking to modify behaviors. Lack of motivation may hamper the effects of cognitive-behavioral therapy for insomnia (CBT-I), especially when delivered online. This study aims to investigate baseline correlates of pretreatment motivation and its influence on treatment outcomes in the context of digitalized CBT-I. Methods This is a secondary analysis of an ongoing pragmatic trial conducted in primary care clinics of Québec City, Canada. The trial was designed to assess the efficacy of a stepped-care intervention for chronic insomnia in which participants received a digital CBT-I (SHUTi), alone or in addition to sleep medication they were already using. Pre-treatment motivation was measured using two items based on the perceived importance of improving sleep and readiness to change behaviors to improve sleep (Score range: 0 to 20; cronbach’s alpha 0.79). Baseline questionnaires included an extended version of Insomnia Severity Index (ISI), Fatigue Severity Scale (FFS), Generalized Anxiety Disorder (GAD-7) and Patient Health Questionnaire (PHQ-9). Treatment outcome was measured by a change in ISI scores (i.e. ISI post - ISI pre). Results A total of 28 participants were included in the analysis. All participants preferentially selected ISI either as monotherapy (n=13)or in combination with their usual sleep medication (n=15). Participants’ motivation before treatment was high (Mean: 18.04; SD: 1.93). We did not find any associations between motivation and ISI score change or incidence of dropout. However, baseline fatigue was positively correlated with pretreatment motivation (r = 0.51, p = 0.005) and more severe insomnia symptoms were also associated with higher motivation (r=0.43, p=0.03). Specifically, perceived importance was associated with both nighttime and daytime insomnia symptoms while readiness for behavioral change was only associated with daytime impairments on energy, mood and social activities (all p = 0.01). Baseline anxiety and depressive symptoms were not correlated with motivation. Conclusion Insomnia-related daytime impairments and elevated fatigue levels appear to be linked to pretreatment motivation, especially for behavioral changes. Further study with greater statistic power is warranted to understand the relationship between participants’ motivation and treatment adherence or outcomes. Support CIHR0083000212
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".