0380 Does TST Appreciably Change During or After CBT-I?
Bibliographic record
Abstract
Most standardized approaches to CBT-I conduct sleep restriction in two phases. Phase 1 involves matching sleep ability to sleep opportunity. Phase 2 involves the titration of sleep opportunity to increase TST. When treatment occurs over 4-8 sessions, it is commonly the case that SL and WASO are substantially reduced but TST is only minimally affected. In the long term, however, it has been shown that TST increases substantially (by about 1 hour in the 6-24 months following treatment). In order to evaluate how modal mean TST effects are, an archival analyses was undertaken to assess what percentage of subjects met or exceeded baseline TST at the end of, or following, treatment. Data were drawn from a RCT conducted to assess the value of maintenance therapies for persistent insomnia. The CBT-I arm of the study had two stages. All subjects initially received six weekly sessions and then were randomized to maintenance CBT-I (once monthly) or to no additional treatment. The present analyses assessed the percentage of subjects that 1) exceeded baseline TST or 2) achieved > 30 min. increases in TST at post treatment and/or at each of 4 follow-up assessments (3, 6, 12, 24 months). Note: The monthly sessions were not focused on increasing TST but included additional sleep restriction when SE% fell below 85%. Irrespective of the treatment condition (acute vs. acute + maintenance therapy), 45.4% of subjects reached or exceeded baseline TST by the end of acute treatment. Over time the percentage increased to 85.9%. In contrast, 17.4% of subjects achieved > 30 min TST by the end of acute treatment and this only increased to 57.8% over time. More than 40% of subjects do not increase TST by 30 or more minutes during acute treatment or over time. Such data raise the question of whether higher dose CBT-I (additional sessions focused on upward titration) might be useful for accelerating TST increases, extending the potential effect to a larger subset of patients, and/or increasing the magnitude of the TST effects. R01AG041783; K24AG055602; R01AT003332
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".