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PENGARUH KONSELING SLEEP HYGIENE DALAM MENINGKATKAN KUALITAS TIDUR ANAK USIA 3-24 BULAN

2022· article· en· W4315699386 on OpenAlexaff
Fitri Wahyuni, Rini Rahmayanti, Nurleny Nurleny, Sri Wahyuningsih, Bayu Wandira, Nur Nilam Sari

Bibliographic record

VenueJurnal Ilmiah Keperawatan Imelda · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Methods and Impacts
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsSleep hygieneMoodIrritabilitySleep (system call)ImpulsivityPsychologyOverweightClinical psychologyMedicinePhysical therapyObesityDevelopmental psychologyCognitionPsychiatrySleep quality

Abstract

fetched live from OpenAlex

Sleep problems in childhood have been found to be associated with memory and learning impairments, irritability, difficulties in mood modulation, attention and behavioral problems, hyperactivity and impulsivity. Short sleep duration has been found to be associated with overweight and obesity. This research describes the protocol of a behavioral intervention planned to promote healthier sleep in infants. Methods: The study is a 1:1 parallel group single-blinded randomized controlled trial enrolling a total of 24 infants at 3-24 months of age. The main eligibility criterion is the infant’s sleep lasting on average less than 15 h per 24 h (daytime and nighttime sleep). The main outcome assessed is the between group difference in average nighttime self-regulated sleep duration (the maximum amount of time the child stays asleep or awake without awakening the parents), at ages 6, 12 and 24 months, evaluated by means of activity diary records and questionnaires. Result: The negative impact of inadequate and insufficient sleep on children’s physical and mental health are unquestionable, as well as its impact on cognitive function, academic performance and behavior. It is hoped that this study will demonstrate a beneficial effect on children's sleep behavior.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0190.002

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 head0.374
Teacher spread0.322 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2022
Admission routes1
Has abstractyes

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