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Record W3029416242 · doi:10.1093/sleep/zsaa056.405

0408 Myths About Infant, Child, and Adolescent Sleep: Addressing False Beliefs That Hinder Sleep Health During These Crucial Developmental Stages

2020· article· en· W3029416242 on OpenAlexaff
Rebecca Robbins, Lauren Hale, Dean W. Beebe, A R Wolfson, Michael A. Grandner, Jodi A. Mindell, Judith Owens, Ignacio E. Tapia, Kelly C. Byars, Reut Gruber, Hawley E. Montgomery‐Downs, Merrill S. Wise, Mary A. Carskadon

Bibliographic record

VenueSLEEP · 2020
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsDouglas Mental Health University Institute
Fundersnot available
KeywordsSleep (system call)MythologyPsychologyPublic healthSleep medicinePsychiatryMedicineSleep disorderInsomniaNursingComputer scienceLiterature

Abstract

fetched live from OpenAlex

Abstract Introduction Sleep is vital for healthy development from infancy through adolescence. Despite its importance, false beliefs that conflict with scientific evidence (myths) may be common among caregivers and impair sleep health during these crucial stages. Methods Researchers compiled a list of potential myth statements using internet searches of popular press and scientific literature. We utilized a Delphi process with experts (n=12) from the fields of pediatric, sleep, and circadian research and clinical practice. Selection and refinement of myths by sleep experts proceeded in three phases, including: focus groups (Phase 1); email-based feedback to edit, add, or remove myths (Phase 2); and closed-ended questionnaires (Phase 3) where experts rated myths on two dimensions: (1) falseness and (2) public health significance using 5-point Likert scale: 1 (“not at all”) to 5 (“extremely false/important”). Results Thirty-two sleep myths were identified across three developmental categories: infant (14 myths), child (6 myths), and adolescent (12 myths). Mean expert ratings illuminated the most pressing myths in each developmental category: infant sleep (“Sleep training causes psychological harm, including reduced parent-child attachment:” falseness =4.7, s.d.=0.7; public health significance=4.0, s.d.=1.1); child sleep (“Heavy, loud snoring for my child means he’s sleeping deeply:” falseness=4.8, s.d.=0.6; public health significance=4.7, s.d.=0.7), and teenager sleep (“Falling asleep in class means your teenager is lazy and not motivated:” falseness=4.8, s.d.=0.5; public health significance=4.3, s.d.=0.8). Conclusion The current study identified commonly-held myths about infant, child, and adolescent sleep that are not supported by (or worse, counter to) scientific evidence. If unchecked, these myths may hinder sleep at a critical developmental stage. Future research may include public health education to correct myths and promote healthy sleep among infants, children, and teenagers. Support 5T32HL007901

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
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 head0.064
GPT teacher head0.354
Teacher spread0.290 · 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.

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
Published2020
Admission routes1
Has abstractyes

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