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Record W3210761802 · doi:10.1101/2021.10.21.21265019

Effects of cognitive behavioral therapy for insomnia on subjective and objective measures of sleep and cognition

2021· preprint· en· W3210761802 on OpenAlexaff
Aurore A. Perrault, Florence B. Pomares, Dylan Smith, Nathan Cross, Kirsten Gong, Antonia Maltezos, Margaret M. McCarthy, Emma Madigan, Lukia Tarelli, Jennifer J. McGrath, Josée Savard, Sophie Schwartz, Jean‐Philippe Gouin, Thien Thanh Dang‐Vu

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversité LavalInstitut Universitaire de Gériatrie de MontréalRoyal Ottawa Mental Health CentreUniversity of OttawaConcordia UniversityCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal
Fundersnot available
KeywordsInsomniaSleep onset latencyPolysomnographyCognitionPsychologySleep (system call)Clinical psychologyCognitive behavioral therapy for insomniaSleep onsetRandomized controlled trialPhysical therapyAudiologyCognitive behavioral therapyMedicinePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

ABSTRACT Study Objectives To assess the effects of Cognitive Behavioral Therapy for insomnia (CBTi) on subjective and objective sleep, sleep-state misperception as well as self-reported and objective cognitive performance. Methods We performed a randomized controlled trial with a treatment group and a wait-list control group to assess changes in insomnia symptoms after CBTi (8 sessions/3 months) in 62 participants with chronic insomnia. To this end, we conducted a multimodal investigation of sleep and cognition including subjective measures of sleep difficulties (Insomnia Severity Index (ISI), sleep diaries) and cognitive functioning (Sahlgrenska Academy Self-reported Cognitive Impairment Questionnaire), objective assessments of sleep (polysomnography recording, cognition (attention and working memory tasks), and sleep-state misperception measures, collected at baseline and at 3-months post-randomization. At 6 months post-randomization, we collected similar data from the wait-list group after CBTi. We also assessed ISI one year after CBTi in both groups. Our main analysis investigated changes in sleep and cognition after 3 months (treatment versus wait-list group). In secondary analyses, we pooled data from both groups to observe changes after CBTi. Results ISI score was reduced and self-reported sleep quality improved after CBTi (treatment group at 3 months and pooled groups after CBTi). Sleep misperception in sleep onset latency and sleep duration decreased after CBTi. In contrast, objective sleep, objective and subjective cognitive functioning did not improve after CBTi. Conclusions We showed that CBTi has a beneficial effect on variables pertaining to the subjective perception of sleep, which is a central feature of insomnia. However, we observed no significant effect of CBTi on measures of cognitive functioning. STATEMENT OF SIGNIFICANCE Nighttime sleep difficulties and daytime cognitive impairment are the two main complaints of individuals suffering from insomnia. We investigated the effects of Cognitive Behavioral Therapy for insomnia (CBTi) on these two aspects of chronic insomnia, using both self-reported and objective measures, as well as sleep-state misperception (i.e., the discrepancy between self-reported and objective sleep). We showed significant changes after CBTi in insomnia severity, subjective sleep quality and perception of sleep, while no consistent benefit emerged for objective measures of sleep and assessments of cognitive functioning. CBTi thus appears to primarily benefit subjective sleep quality as well as the alignment between subjective and objective estimates of sleep.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.320
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations5
Published2021
Admission routes1
Has abstractyes

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