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Record W4296326252 · doi:10.1111/jsr.13722

Focus on sleep medicine

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

Bibliographic record

VenueJournal of Sleep Research · 2022
Typeeditorial
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaSleep medicineNeurocognitiveSleep apneaMedicinePsychologyPsychiatryDiseaseGerontologySleep disorderCognitionInternal medicine

Abstract

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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.

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)0.009
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.163
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0020.016
Insufficient payload (model declined to judge)0.0390.001

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 head0.052
GPT teacher head0.426
Teacher spread0.375 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEditorial

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
Published2022
Admission routes1
Has abstractyes

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