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Record W2800885480 · doi:10.1093/sleep/zsy061.230

0231 The Impact of At-Home Actigraphy on Performance and Sleepiness in the Lab over 62 Hours of Total Sleep Deprivation

2018· article· en· W2800885480 on OpenAlexfundno aff
Kajsa Carlsson, Alexxa F. Bessey, Lillian Skeiky, N E Prindle, Meredith Armstrong, Jaime K. Devine, Vincent F. Capaldi, Thomas J. Balkin, Tracy Jill Doty

Bibliographic record

VenueSLEEP · 2018
Typearticle
Languageen
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsActigraphySleep deprivationVigilance (psychology)SomnolenceMedicineEffects of sleep deprivation on cognitive performanceAudiologySleep diaryPsychomotor learningSleep (system call)Physical therapySleep lossPsychologyCircadian rhythmCognitionPsychiatryInternal medicineComputer science

Abstract

fetched live from OpenAlex

It is well-established that sleep loss results in reduced cognitive performance and increased sleepiness, and that these effects are reduced by prior sleep extension. The purpose of the present study was to determine the extent to which individual differences in habitual sleep duration likewise mediate subsequent performance and sleepiness during total sleep deprivation (TSD). Sixteen healthy adults participated in this protocol. The study consisted of two phases: 1) An at-home phase consisting of 12 nights of actigraphy monitoring of normal habitual sleep, and 2) An in-lab phase consisting of a baseline night (8 hours time-in-bed) and 62 hour TSD. Subjects were outfitted with a wrist-worn actigraph to wear for both phases of the study. During Phase 2 of the study, subjects performed a 5-minute Psychomotor Vigilance Test (PVT) and also completed the Karolinska Sleepiness Scale (KSS) every three hours. Utilizing the 2B-Alert performance prediction algorithm from the Biotechnology High Performance Computing Software Applications Institute (BHSAI), it was projected that the worst daily performance on the PVT would occur at 0700 after one and two nights of TSD. Therefore, we investigated the relationship between average at-home total sleep time (TST) and in-lab metrics (PVT speed and KSS) collected at these two time points. While there was no significant relationship between at-home TST and PVT speed after one night of TSD, a significant positive relationship was evident after two nights of TSD (r=0.56, p=0.03). The same pattern was evident for the KSS (2 nights of TSD: r=0.53, p=0.04). Sleep patterns of healthy adults measured via at-home actigraphy mediate performance and sleepiness during subsequent sleep deprivation in the laboratory. These findings (a) suggest that individual differences in habitual sleep times do not accurately reflect individual differences in actual sleep need; and (b) underscore the utility of collecting actigraphically-determined sleep data in subjects at home prior to their participation in laboratory studies involving sleep loss. Department of Defense Military Operational Medicine Research Program (MOMRP)

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.293
Teacher spread0.278 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2018
Admission routes1
Has abstractyes

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