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Enregistrement W4296326252 · doi:10.1111/jsr.13722

Focus on sleep medicine

2022· editorial· en· W4296326252 sur OpenAlexaboutno aff
Dieter Riemann

Notice bibliographique

RevueJournal of Sleep Research · 2022
Typeeditorial
Langueen
DomainePsychology
ThématiqueSleep and related disorders
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDementiaSleep medicineNeurocognitiveSleep apneaMedicinePsychologyPsychiatryDiseaseGerontologySleep disorderCognitionInternal medicine

Résumé

récupéré en direct d'OpenAlex

Dear members of the European Sleep Research Society (ESRS), Dear readers of the Journal of Sleep Research (JSR), Let me welcome you to the fifth issue of the JSR in 2022. In the meantime, the ESRS conference in Athens has passed and I would like to thank all those who attended in person and celebrated the 50th anniversary of the ESRS. Many of you will have received the special print issue to celebrate the 50th anniversary and I hope you still enjoy browsing through the contents. This fifth issue of JSR in 2022 encompasses a broad variety of articles coming from the fields of sleep research and sleep medicine, although this time there is a majority of articles dealing with sleep medicine topics. Take your time and pick the articles you are most interested in, also browse through the other content please. As I always do, I would like to draw your attention to some of the articles in this issue: Guay-Gagnon et al. (2022) from the University of Montreal present a systematic review and meta-analysis of the relationships between sleep apnea and the risk of dementia. The authors were able to include 11 studies, comprising a sample of over a million patients. It turned out that the patients with sleep apnea had an increased risk of developing any kind of neurocognitive disorder (hazard ratio 1.43). There were also significant risks for Alzheimer's disease and Parkinson's disease but not for other types of dementia, e.g., vascular dementia. This result calls for mechanistic studies trying to explore how and why sleep disordered breathing translates into increased risks for many different types of dementia. Ellithorpe et al. (2022) conducted a study, which since its publication online has received a lot of media attention. They dedicated their efforts to elucidate the relationships between media use before bed and subsequent sleep, by combining objective electroencephalographic sleep measurements and media diaries. They come to the conclusion that bedtime media use might not be as detrimental for sleep as some previous research may have indicated. The authors stress that contextual variables such as the location, multi-tasking and session length may have an important impact here. I assume that this is not the last paper about media use and sleep, especially in adolescents and young adults. I do suggest that further research should not only study associations between media use and sleep but should also look at mechanisms involved. Further work is warranted to delineate how and to what extent media use may have an impact on subsequent sleep. Stricker et al. (2022) provide us with a systematic review of the relationships between perfectionism, measured multidimensionally, and sleep disturbances. This non-meta-analytic approach resulted in 24 relevant empirical studies, and it seems that concerning perfectionism, perfectionistic concerns were robustly linked to sleep disturbance. Relationships between perfectionistic strivings showed comparatively small and inconsistent relationships with sleep quality. So-called cross-sectional mediation analysis revealed that probably psychological distress and dysfunctional cognitive processes might underlie the perfectionistic concerns–sleep disturbance link. This systematic review confirms what is known from previous studies studying perfectionism and sleep and sleep disturbance. Nevertheless, in order to gain causal insights into the relationship, future studies will have to address the interrelationships between perfectionism, its multidimensional measurement and sleep and sleep disturbance in longitudinal studies! Hilditch et al. (2022) investigated an interesting issue, i.e., if polychromatic short-wavelength-enriched light might mitigate sleep inertia during the night following awakening from slow-wave sleep (SWS). In this study 12 young participants, after a period of actigraphy-confirmed sleep, slept 1 night in the sleep laboratory. They were awakened from SWS and immediately exposed to either dim, red ambient light (control) or polychromatic short-wavelength-enriched light for 1 h in a randomised crossover design. The short-wavelength-enriched light condition was the light condition, whereas the red ambient light was considered as a control. It turned out that after exposure to polychromatic short-wavelength-enriched light subjects felt more alert, made fewer mistakes, and even showed improved mood. This is a potentially relevant study for professionals who are on night-shift duty, are allowed to sleep and are at risk being awoken from SWS in case of emergencies. Thus, inertia following awakening from SWS may be counteracted by polychromatic short-wavelength-enriched light. The fifth paper I am going to comment on also deals with the SWS. Simon et al. (2022) investigated whether progressive muscle relaxation (PMR) may increase SWS during a daytime nap. Healthy young adults either underwent progressive muscle relaxation or listened to Mozart music (control) prior to a 90-min nap opportunity. It turned out that after PMR participants spent 10 min more in SWS than the control group. This is equivalent to 125% more time in SWS. There was less time spent in rapid eye movement (REM) sleep. The results are highly interesting with respect how one may enhance SWS during daytime naps and thus probably also enhance the sleep quality of these naps. A replication is necessary before definite practical conclusions can be drawn.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,009
score de la tête « metaresearch » (Gemma)0,004
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesIntégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,163
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0090,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0030,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0020,000
Intégrité de la recherche0,0020,016
Charge utile insuffisante (le modèle a refusé de juger)0,0390,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,052
Tête enseignante GPT0,426
Écart entre enseignants0,375 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

Explorer davantage

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