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Record W4293010944 · doi:10.1016/j.jshs.2022.08.003

Associations between meeting 24-hour movement guidelines and quality of life among children and adolescents with autism spectrum disorder

2022· article· en· W4293010944 on OpenAlexaffabout
Chuidan Kong, Aiguo Chen, Sebastian Ludyga, Fabian Herold, Seán Healy, Mengxian Zhao, Alyx Taylor, Notger G. Müller, Arthur F. Kramer, Sitong Chen, Mark S. Tremblay, Liye Zou

Bibliographic record

VenueJournal of sport and health science/Journal of Sport and Health Science · 2022
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsAgricultural Research Institute of OntarioUniversity of Ottawa
FundersShenzhen University
KeywordsAutism spectrum disorderMedicineObservational studyConfidence intervalAutismOdds ratioQuality of life (healthcare)Cross-sectional studyClinical psychologyPsychologyDemographyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The Canadian 24-hour movement behavior (24-HMB) guidelines suggest that a limited amount of screen time use, an adequate level of physical activity (PA), and sufficient sleep duration are beneficial for ensuring and optimizing the health and quality of life (QoL) of children and adolescents. However, this topic has yet to be examined for children and adolescents with autism spectrum disorder (ASD) specifically. The aim of this cross-sectional observational study was to examine the associations between meeting 24-HMB guidelines and several QoL-related indicators among a national sample of American children and adolescents with ASD. METHODS: Data were taken from the 2020 U.S. National Survey of Children's Health dataset. Participants (n = 956) aged 6-17 years and currently diagnosed with ASD were included. The exposure of interest was adherence to the 24-HMB guidelines. Outcomes were QoL indicators, including learning interest/curiosity, repeating grades, adaptive ability, victimization by bullying, and behavioral problems. Categorical variables were described with unweighted sample counts and weighted percentages. Age, sex, race, preterm birth status, medication, behavioral treatment, household poverty level, and the educational level of the primary caregivers were included as covariates. Odds ratio (OR) and 95% confidence interval (95%CI) were used to present the strength of association between adherence to 24-HMB guidelines and QoL-related indicators. RESULTS: Overall, 452 participants (45.34%) met 1 of the 3 recommendations, 216 (22.65%) met 2 recommendations, whereas only 39 participants (5.04%) met all 3 recommendations. Compared with meeting none of the recommendations, meeting both sleep duration and PA recommendations (OR = 3.92, 95%CI: 1.63-9.48, p < 0.001) or all 3 recommendations (OR = 2.11, 95%CI: 1.03-4.35, p = 0.04) was associated with higher odds of showing learning interest/curiosity. Meeting both screen time and PA recommendations (OR = 0.15, 95%CI: 0.04-0.61, p < 0.05) or both sleep duration and PA recommendations (OR = 0.24, 95%CI: 0.07-0.87, p < 0.05) was associated with lower odds of repeating any grades. With respect to adaptive ability, participants who met only the PA recommendation of the 24-HMB were less likely to have difficulties dressing or bathing (OR = 0.11, 95%CI: 0.02-0.66, p < 0.05) than those who did not. For participants who met all 3 recommendations (OR = 0.38, 95%CI: 0.15-0.99, p = 0.05), the odds of being victimized by bullying was lower. Participants who adhered to both sleep duration and PA recommendations were less likely to present with severe behavioral problems (OR = 0.17, 95%CI: 0.04-0.71, p < 0.05) than those who did not meet those guidelines. CONCLUSION: Significant associations were found between adhering to 24-HMB guidelines and selected QoL indicators. These findings highlight the importance of maintaining a healthy lifestyle as a key factor in promoting and preserving the QoL of children with ASD.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.094
GPT teacher head0.394
Teacher spread0.300 · 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 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

Citations71
Published2022
Admission routes2
Has abstractyes

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