0512 Impact of a Patient Decision-Aid When Selecting Insomnia Treatments and Factors Associated with Decisional Conflict: Preliminary Findings from an Ongoing Pragmatic Clinical Trial
Bibliographic record
Abstract
Abstract Introduction Preferences play an important role in determining insomnia treatment outcomes, but the validity of patient choice is rarely assessed. Uninformed preferences can lead to decisional conflict, which can negatively impact on treatment initiation, adherence, and subsequent outcomes. The current study aims to evaluate the impact of integrating a patient decision-aid as part of a pragmatic clinical trial and to identify baseline covariates associated with clinically significant decisional conflict (CSDC). Methods Secondary analysis of an ongoing pragmatic clinical trial for a two-stage cognitive behavioral therapy for insomnia (CBT-I) intervention was undertaken. Participants were referred from primary care clinics in Quebec City, Canada. Upon enrolment, participants were guided by a decision-aid, outlining the risks and benefits of prospective treatment options, when selecting their preferred arm of treatment in Phase 1. Options included SHUTi, SHUTi combined with an existing medication or continuing usual treatment with medication alone. Participants also completed a battery of sleep and mental health measures at baseline. Prior to treatment initiation, the 4-item SURE (Sure of myself; Understand information; Risk-Benefit ratio; Encouragement) scale was administered to screen for CSDC. Relationships between CSDC and baseline covariates were explored using Pearson correlations. Results Of the 55 participants initially enrolled, 94.5% (n=52) of participants preferentially selected SHUTi, either as sole treatment (n=24) or in combination with an existing medication (n=28), over usual treatment with medication alone (n=3). Overall, CSDC was only reported by 5.5% (n=3) of the sample population, with no group differences observed, suggesting effective clarification of treatment options through the decision-aid. Interestingly, higher SURE scores (i.e. less decisional conflict) were negatively correlated with depressive symptoms (r= -0.295, n= 55, p= 0.029) and anxiety symptoms (r= -0.301, n= 55, p= 0.026). Correlations with age, insomnia symptoms, duration of insomnia and fatigue were not statistically significant. Conclusion The patient decision-aid appeared to resolve decisional conflict for 94.5% (n=52) of participants. Findings allude to the potential influence of emotional status on information processing pathways in an insomnia context, warranting further research. Support Research supported by a grant from the Canadian Institutes of Health Research (CIHR-IRSC:0441002152).
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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 | 0.036 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".