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Record W4282825733 · doi:10.3390/biology11060910

Effects of a Physical Literacy Breaks (PLBreaks) Program on Physical Literacy and Body Composition in Portuguese Schoolchildren: A Study Protocol

2022· article· en· W4282825733 on OpenAlexaboutno aff
María Mendoza-Muñoz, Jorge Carlos‐Vivas, Santos Villafaina, José A. Parraça, Alejandro Vega-Muñoz, Nicolás Contreras-Barraza, Armando Raimundo

Bibliographic record

VenueBiology · 2022
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsnot available
FundersUniversidad Andrés Bello
KeywordsPortugueseCompetence (human resources)LiteracyPhysical activityComposition (language)Health literacyProtocol (science)BiologyPhysical therapyPsychologyMedicinePedagogyAlternative medicineSocial psychology

Abstract

fetched live from OpenAlex

(1) Background: Several studies have shown that active breaks have led to different improvements in their participants. However, no studies have assessed how they affect physical literacy (PL). (2) Aims: Therefore, this study will examine the effect of the PLBreaks programme on school children's PL and body composition. (3) Methods: A parallel-group randomised controlled trial will be conducted with assessments of PL (Canadian Assessment of Physical Literacy Development) and body composition (height, bodyweight, fat mass and fat-free mass) before and after an active breaks programme. PLBreak programme will run for 3 months and will be carried out 3 days a week for 20 min each day. The PLBreaks programme will consist of two blocks of 10 min of different physical activities (PA). The first block will be focused on the acquisition of knowledge and healthy life habits that will contribute to the development of the domains of knowledge and understanding and daily activity. The second block will be focused on physical competence and motivation throughout games. (4) Conclusions: The present study will investigate the efficacy of PLBreaks in schoolchildren in improving their PL and body composition. If the efficacy of the program is demonstrated, including the programme in public education programmes can be possible. This could be a scientific breakthrough in terms of health-related PA improvement and adherence, as well as the prevention of diseases associated with inactivity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.007
GPT teacher head0.341
Teacher spread0.334 · 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.

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

Citations8
Published2022
Admission routes1
Has abstractyes

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