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Record W3030230086 · doi:10.1093/sleep/zsaa056.950

0954 Sleep of Gifted Children Using Actigraphy

2020· article· en· W3030230086 on OpenAlexaff
Laurianne Bastien, Rachel Théoret, Roger Godbout

Bibliographic record

VenueSLEEP · 2020
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsHôpital Rivière-des-PrairiesUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal
Fundersnot available
KeywordsActigraphyPsychologyNormativeSleep (system call)Developmental psychologyClinical psychologyAudiologyInsomniaMedicinePsychiatry

Abstract

fetched live from OpenAlex

Abstract Introduction Intellectual giftedness is characterized by an intellectual development superior to peers (QI > 120) while emotional and relational development corresponds to the age norms. Anecdotal reports from parents suggest that they sleep poorly compared to typically developing (TD) peers. We measured sleep of gifted children using actigraphy. Methods Thirteen gifted children (10 boys, mean age = 10.58, SD = 2.11) were studied. Giftedness was identified using Renzulli’s three-factor definition of giftedness conceptualise in terms of above-average ability and high levels of task commitment (refined or focused form of motivation), and creativity. Sleep was measured with actigraphy for two weeks and compared to normative data from TD children using T-tests. Results Compared to normative data from TD children, gifted children had a significantly shorter sleep latency (p < 0.001), longer sleep periods (p = 0.001), shorter total sleep time and more wake time after sleep onset (p = 0.03). These differences were present both on week nights and weekend nights except that total sleep time was shorter in gifted children only during weekends (p < 0.001). Conclusion These data suggest that gifted children sleep poorly, and more so upon weekends. Whether this correlates with daytime functioning remains to be determined. Support N/A

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 score0.402
Threshold uncertainty score0.989

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)0.0010.000

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 head0.023
GPT teacher head0.268
Teacher spread0.245 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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