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Global research trends in physical literacy and their efficacy on motor competence: A bibliometric study

2025· article· W4415297929 on OpenAlexaboutno aff
Veena S Nair, Rubashini Ramakrishnan

Bibliographic record

VenueInternational Journal of Sports Health and Physical Education · 2025
Typearticle
Language
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialPacePsychological interventionPublishingLiteracyGrassrootsCognitionPhysical fitness

Abstract

fetched live from OpenAlex

Physical literacy, which is defined as the complete integration of physical skill, motivation, confidence, knowledge, and understanding, has emerged as a central idea in the fields of health, education, and sports sciences. Physical learning, in contrast to traditional performance models, places an emphasis on meaningful physical activity throughout one's entire life by establishing connections between the physical, cognitive, psychological, and social domains. In light of the fact that physical inactivity is on the rise all over the world, which is a factor that contributes to obesity, cardiovascular risk, and a decrease in well-being, this is especially pertinent. There is evidence that children and adolescents who have a greater PL have superior motor competence, executive skills, and academic performance. On the other hand, children and adolescents who have a low PL are related with behaviors that are more sedentary and have poorer psychosocial outcomes. PL integration varies over the world, with Canada and Australia leading the pace while many underdeveloped regions lag behind. This study examines global PL research trends from 2017 to 2025 using bibliometric analysis, focusing on PL's effects on cognitive development and motor ability. The findings emphasize rapid publishing growth, famous authors, and major theme groupings. The analysis also shows research gaps, emphasizing the need for grassroots policy integration and longitudinal interventions to maximize person-centered care's lifetime effects.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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), Bibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.896
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
Bibliometrics0.0150.016
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.037
GPT teacher head0.476
Teacher spread0.439 · 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

Labeled directly by 2 models reading the full record.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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