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Effects of repeated cryostimulation exposures on sleep and wellness in healthy young adults

2024· article· en· W4401350237 on OpenAlexaff
Coralie Arc‐Chagnaud, Olivier Dupuy, Manuela Garcia, Laurent Bosquet, Romain Bouzigon, Robin Pla, Arc-Chagnaud Coralie, B. Quentin, Enéa Carina, Pichon Aurélien, Tanneau Maxence et Theurot Dimitri, Couvertier Marien, M. Mathias, Sauvet Fabien, Morales-Artacho Antonio, Mathieu Nédélec, Pasquier Florane, Poignard Mathilde et Ruffault Alexis, Benoît Dugué

Bibliographic record

VenueCryobiology · 2024
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversité de Montréal
FundersNational Radio Research AgencyAgence Nationale de la Recherche
KeywordsMoodMedicineSleep (system call)AnxietySleep qualityPhysical therapyRepeated measures designInsomniaClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

The aim of this study was to evaluate the effects of daily whole-body cryostimulation (WBC) sessions during 5 consecutive days on wellness and sleep parameters in healthy young men and women. Twenty healthy subjects (9 women; 11 men) aged 23.1 ± 2.6 years old participated in this randomized protocol, with 5 consecutive days with (CRYO) or without WBC (CONT) exposure. Sleep was analyzed over the 5 nights in each condition. Sleep quality and quantity were assessed via actimetry, cerebral activity and questionnaires. Nocturnal heart rate variability (HRV) was also recorded and questionnaires were given to assess wellness and mood. Repeated WBC exposures had a beneficial impact on mood and anxiety. It also improved subjective sleep quality (scored from 3.6 ± 0.5 pre to 3.9 ± 0.3), especially in women. Also, repeated WBC sessions modulated sleep architecture by increasing slow wave sleep duration (+7.3 ± 16.8 min) during the nights without impacting other sleep parameters, nor nocturnal HRV. In conclusion, repeated WBC seems to be an effective strategy to improve slow wave sleep duration in healthy young subjects. The reported psychological improvements may better benefit women than men.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.630
Threshold uncertainty score0.414

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 head0.006
GPT teacher head0.276
Teacher spread0.270 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

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