0397 Randomized Controlled Trial of Telehealth in Older Adults: Technology-assisted CBTi+, CBTi, and Sleep Hygiene
Bibliographic record
Abstract
Abstract Introduction Of 34M US adults affected by insomnia, 75% are older adults. Cognitive Behavioral Therapy for Insomnia (CBTi) is recommended because polypharmacy and fall risks accompany pharmacotherapies. We evaluated telehealth CBTi with an interactive patient-therapist application, SleepSpace, which integrates data from wearables and Internet of Things (IoT) devices. Methods This RCT (NCT05015803) followed community-dwelling participants 60-90 years old with an Insomnia Severity Index (ISI) score ≥11. Absence of mild cognitive impairment was affirmed with the Montreal Cognitive Assessment (MoCA) Blind v.8 (score ≥ 18). Participants wore actigraphy and an Apple Watch throughout and independently completed a weekly electronic ISI. They attended 7 weekly, ~1hr video-conference sessions (1 intake, 6 procedural) with a clinical therapist. Participants were randomly assigned to one of 3 study conditions (age-, gender-stratified): 1) education about sleep hygiene only (20%; “Hygiene”), 2) telehealth CBTi (40%; “CBTi”), and 3) telehealth CBTi with phone/IoT platform application enhancement (40%; “CBTi+”) including meditations, sound machines, smart light bulbs, an electronic diary, with visualizations, metrics, and wearable data shared with participants in the CBTi+ condition. Linear mixed models compared ISI change across time by group. Results Of 60 individuals enrolled, 54 were randomized and retained (39F, mean±SD age=71±4y). ISI slopes for both CBTi (-.09/day) and CBTi+ (-.09/day) declined at a significantly steeper rate than Hygiene (-.05/day; each p<.05), but did not differ from one another. Significantly more CBTi+ participants exhibited full remission (ISI < 8; 18/21, 85.7%) than in the Hygiene group (5/11, 45.4%; p=.03 Fisher’s Exact); CBTi alone (16/22, 72.7%) did not significantly differ from Hygiene, although with limited statistical power. Diary-reported sleep measures to calculate self-reported sleep efficiency (sSE) in the final week at end of treatment revealed differences in mean±SD for Hygiene (81±05%) vs. CBTI (88±07%), and vs. CBTI+ (90±04%, p< 0.05, t-test). Conclusion This research supports the efficacy of a remote, technology-assisted telehealth CBTi platform to improve insomnia symptoms comparable to standard telehealth-CBTi in older adults with insomnia. The platform provides enhanced data access for therapists and opportunities for data-driven engagement with patients. Support (if any) R44 AG056250, UL1TR002014
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".