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Record W4412785728 · doi:10.1186/s12887-025-05916-x

Effectiveness of affordances on physical literacy and quality of life: investigating the nonlinear approach of fundamental movement skills and a selection of handball sports skills

2025· article· en· W4412785728 on OpenAlexaboutno aff
Saeed Valadi, Jalal Dehghanizadeh, Carl Gabbard, John Cairney

Bibliographic record

VenueBMC Pediatrics · 2025
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsnot available
FundersUrmia University
KeywordsPsychological interventionLiteracyAffordanceQuality of life (healthcare)Physical educationQuality (philosophy)MedicineIntervention (counseling)Medical educationHealth literacyApplied psychologyPhysical therapyPsychologyPedagogyNursingCognitive psychologyHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: This study investigated the effectiveness of interventions utilizing non-linear pedagogy for fundamental movement skills (NP-FMS) and a selection of handball sports skills (NP-HSS) on children's physical literacy and quality of life. METHODS: A cohort of 130 children, aged 8-10 years, was randomly assigned to two experimental groups and one control group. Physical Literacy and quality of life were evaluated before and after the intervention using the Canadian Assessment of Physical Literacy tool and the Pediatric Quality of Life Inventory. RESULTS: The findings revealed that both interventions, NP-FMS and NP-HSS, significantly influence the levels of physical literacy and quality of life. Furthermore, a significant improvement in physical literacy led to a notable enhancement in quality of life. Additionally, the interactive effect of age and group on physical literacy was found to be significant. CONCLUSIONS: Leveraging core principles of ecological dynamics through the deliberate integration of non-linear pedagogy and the constraint-led approach enables educators to systematically enrich affordance-rich environments, thereby fostering physical literacy and supporting improvements in children's overall quality of life.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.303
Teacher spread0.291 · 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.

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

Citations4
Published2025
Admission routes1
Has abstractyes

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