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Record W4401216995 · doi:10.3390/bs14080661

Shyness, Sport Engagement, and Internalizing Problems in Chinese Children: The Moderating Role of Class Sport Participation in a Multi-Level Model

2024· article· en· W4401216995 on OpenAlexaff
Rumei Zhao, Xiaoxue Kong, Mingxin Li, Xinyi Zhu, Jiyueyi Wang, Wan Ding, Xuechen Ding

Bibliographic record

VenueBehavioral Sciences · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsMcMaster University
FundersNational Natural Science Foundation of China
KeywordsShynessPsychologyClass (philosophy)Developmental psychologySocial psychologyAnxietyComputer science

Abstract

fetched live from OpenAlex

The relations between shyness and internalizing problems have been mainly explored at the individual level, with little known about its dynamics at the group level. This study aims to examine the mediating effect of individual-level sport engagement and the moderating effect of class-level sport participation in the relations between shyness and internalizing problems. The participants were 951 children attending primary and middle school from grade 3 to grade 7 (Mage = 11 years, 509 boys) in urban areas of China. Cross-sectional data were collected using self-report assessments. Multi-level analysis indicated that (1) shyness was positively associated with internalizing problems; (2) sport engagement partially mediated the relations between shyness and internalizing problems; and (3) class sport participation was a cross-level moderator in the mediating relations between shyness, sport engagement, and internalizing problems. Shy children in classes with a higher level of sport participation tend to have less sport engagement and more internalizing problems than those in classes with a lower level of sport participation. These findings illuminate implications from a multi-level perspective for shy children's adjustment in a Chinese context. The well-being of shy children could be improved by intervening in sport activity, addressing both individual engagement and group dynamics, such as class participation.

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)0.002
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 score0.060
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.153
GPT teacher head0.416
Teacher spread0.263 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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