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Exploring the Impact of Self-Efficacy, Social Support, and Environmental Barriers on Physical Activity Behaviour among School-Age Children: A Structural Equation Model

2025· article· W7117333966 on OpenAlexaff
Betül Beyza Çolak, Eren Timurtaş, Mehmet Inceer, Mi̇ne Gülden Polat

Bibliographic record

VenueClinical and Experimental Health Sciences · 2025
Typearticle
Language
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsMcGill University
Fundersnot available
KeywordsStructural equation modelingPhysical activityTest (biology)Social influenceSocial supportHealth behaviorPhysical activity level

Abstract

fetched live from OpenAlex

Objective: More than 80% of children do not meet the recommended levels of physical activity, which can have long-term health consequences. This study aimed to investigate the relationships between self-efficacy, social support, environmental barriers, and physical activity behavior in school-aged children. Methods: A cross-sectional survey study was conducted among secondary school children aged 9–14. Online surveys were administered to both children and their parents to assess children's physical activity levels, perceived self-efficacy, social support, and environmental barriers. Structural equation modeling (SEM) was employed to test the theoretical model and examine the direct and indirect effects of these factors on physical activity. Results: The model we defined based on self-efficacy, social support and environmental barriers showed acceptable fit values (X2/sd=1.94, SRMR=0.06, GFI=0.92, AGFI=0.89, RMSEA=0.05, CFI=0.92 and NFI=0.84). The direct effect of the self-efficacy on physical activity level was found to be statistically significant (β=0.42, p

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 categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.005
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.097
GPT teacher head0.425
Teacher spread0.328 · 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; both teacher heads agree on what is shown here.

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
Published2025
Admission routes1
Has abstractyes

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