MétaCan
Menu
Back to cohort
Record W4378610863 · doi:10.1093/sleep/zsad077.0380

0380 Adults with and without Mild Cognitive Impairment Show Similar Treatment Adherence and Sleep Improvement after Insomnia Therapy

2023· article· en· W4378610863 on OpenAlexaffabout
Allison Morehouse, Kathleen O’Hora, Beatriz Hernandez, Laura C. Lazzeroni, Jamie M. Zeitzer, Leah Friedman, Donn Posner, Clete A. Kushida, Jerome A. Yesavage, Andrea Goldstein‐Piekarski

Bibliographic record

VenueSLEEP · 2023
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInsomniaSleep onset latencySleep onsetCognitive behavioral therapy for insomniaSleep (system call)CognitionRandomized controlled trialCognitive behavioral therapyMedicineSlow-wave sleepSleep diaryEffects of sleep deprivation on cognitive performancePsychologyActigraphyPhysical therapyPsychiatryInternal medicineElectroencephalography

Abstract

fetched live from OpenAlex

Abstract Introduction Non-pharmacological Insomnia Therapies are robustly effective in improving sleep in cognitively intact (CI) older adults. However, it remains unknown whether older adults with mild cognitive impairment (MCI) can engage in insomnia therapy to experience similar sleep improvements. Methods We leveraged an existing dataset derived from a randomized clinical trial (NCT02117388) in older adults with and without MCI to examine differences in treatment adherence and sleep improvements after completing six sessions of insomnia therapy. Healthy older adults with insomnia (n=127, Mage= 69.18, 34.4% male, MCI: n=38 determined by Montreal Cognitive Assessment score< 26) completed a one-week sleep diary at pre-treatment (BL), post-treatment (ET), and six-months post-treatment (6M). Wake after sleep onset (WASO), total sleep time (TST), sleep efficiency (SE), and sleep onset latency (SOL) were calculated from sleep diaries. Treatment consisted of either the behavioral, cognitive, or combined components of Cognitive Behavioral Therapy for Insomnia (CBT-I). Participants rated their treatment adherence at the final treatment session. Linear mixed effects models were used to determine the effect of MCI status, time, and an MCI status-by-time interaction on each sleep outcome while covarying for age and sex. A Benjamini-Hochberg correction was applied to correct for multiple comparisons. Linear regression models controlling for age and sex were used to test group differences in treatment adherence scores. Results Both groups showed significant improvements in all sleep measures from BL to ET and sustained these improvements at 6M (padj’s< 0.016). There were no significant MCI status-by-time interactions for any sleep measure (padj’s > 0.29), suggesting individuals with and without MCI similarly improved their sleep. Further, there were no differences in treatment adherence scores between the CI and MCI groups (b=0.131, p=0.432), suggesting the MCI group engaged in therapy similarly to the CI group. Conclusion These preliminary findings suggest older adults with MCI may be capable of engaging in insomnia therapy to improve their sleep to the same degree as CI older adults. These findings also highlight the need of future research investigating the efficacy of non-pharmacological insomnia therapy on sleep and cognitive outcomes in older adults with MCI. Support (if any) NIMHR01MH101468-01; Mental Illness Research, Education, and Clinical Center (MIRECC) at VAPAHCS

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.274
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueSLEEPSame topicSleep and related disordersFrench-language works237,207