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Record W3202384817 · doi:10.1371/journal.pone.0258144

Factors related to lower limb performance in children and adolescents aged 7 to 17 years: A systematic review with meta-analysis

2021· review· en· W3202384817 on OpenAlexaff
Paulo Francisco de Almeida‐Neto, Vitória Monteiro Monte Oliveira, Dihogo Gama de Matos, Ísis Kelly dos Santos, Adam Baxter‐Jones, Vanessa Carla Monteiro Pinto, Tatianny de Macêdo Cesário, Felipe J. Aidar, Paulo Moreira Silva Dantas, Breno Guilherme de Araújo Tinôco Cabral

Bibliographic record

VenuePLoS ONE · 2021
Typereview
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversity of SaskatchewanUniversity of Manitoba
FundersUniversidade Estadual do CearáUniversidade Federal do Rio Grande do NorteConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsObservational studyChecklistMeta-analysisSystematic reviewCINAHLMEDLINEScopusMedicineData extractionSample size determinationStrengthening the reporting of observational studies in epidemiologyPsychologyDemographyPsychological interventionBiologyPsychiatryInternal medicineStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: The literature identifies several factors that are associated with lower limb performance (LLP). However, there is little consensus on which factors have the major associations with LLP. OBJECTIVE: Examine, analyze and summarize the scientific evidence on the factors associated with the performance of LLP in children and adolescents of both sexes aged between 7 and 17 years. DESIGN: This systematic review was conducted following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement and was registered in PROSPERO. DATA SOURCES: A systematic literature search of five electronic databases (i.e., SPORTDiscus, PubMed, CINAHL, Google Scholar, and SCOPUS) with date restrictions was conducted (2010 to 2021). ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Eligibility criteria included (i) a study published between 2010 and 2021; (ii) a research study with observational design; (iii) a study analyzing LLP; and (iv) a sample composed of young people between 7 and 17 years old (regardless of sex). ANALYSES: Literature analysis was carried out in English and Portuguese between 2018 and 2021, "blindly" by two researchers. For data sorting, Rayyan® was used. Data extraction and evidence analysis were performed "blindly", using the Loney scale. The minimum items for observational studies were analyzed by the STROBE checklist. Meta-analyses were conducted based on age group (Childhood [7 to 11 Yrs] and Adolescence [12 to 17 Yrs]) and puberty stages (i.e., Prepupertal and Pubertal). The heterogeneity between the samples of the studies was assessed using the "Cochran's Q" and "I^2" statistics. Meta-regression analyses were performed to check the factors related to heterogeneity of the studies and to check the associations between chronological age and LLP. RESULTS: The literature search resulted in 1,109,650 observational studies of which 39 were included in this review. Through Meta-analysis and Meta-regressions, it was possible to indicate that advancing chronological age related to increased LLP (p<0.01), and that in relation to puberty stages pubertal subjects had higher LLP than their pre-pubertal peers (p<0.01). DISCUSSION: The main findings of the present systematic review suggest that as chronological age advances (childhood to adolescence), neuromuscular systems mature and this may be due to advancing puberty, which is also associated with an increase in LLP. CONCLUSION: The factors associated with lower limbs performance are still inconsistent in the literature. However, advancing chronological age and stage of puberty are both associated with increased lower limbs performance. TRIAL REGISTRATION: ID-PROSPERO-CRD42020137925.

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)0.017
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.050
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0180.035
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.091
GPT teacher head0.310
Teacher spread0.219 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations14
Published2021
Admission routes1
Has abstractyes

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