MétaCan
Menu
Back to cohort
Record W4396769251 · doi:10.3390/nu16101434

Effects of Functional Strength Training Combined with Aerobic Training on Body Composition, Physical Fitness, and Movement Quality in Obese Adolescents

2024· article· en· W4396769251 on OpenAlexaff
Zhihai Wang, Huihui Ma, Weiwei Zhang, Yufeng Zhang, Layale Youssef, Marcelo A. S. Carneiro, Chao Chen, Dan Wang

Bibliographic record

VenueNutrients · 2024
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsUniversité de Montréal
FundersShanghai University of Sport
KeywordsAnthropometryAerobic exercisePhysical therapyMedicineBody mass indexPhysical fitnessGrip strengthBody fat percentageAnalysis of varianceCircumferenceRepeated measures designFat massInternal medicineMathematics

Abstract

fetched live from OpenAlex

This study aimed to compare the effects of 12 weeks of functional strength training combined with aerobic training (TG) and traditional resistance training combined with aerobic training (CG) on the body composition, physical fitness, and movement quality of obese adolescents. Forty participants were randomly assigned to either the TG group (n = 20) or the CG group (n = 20). Each group underwent training five times per week, lasting 120 min each time, over a total period of 12 weeks. All participants followed a strict dietary program. Anthropometric parameters, body composition, physical fitness, and movement quality were evaluated at baseline and after intervention. A two-way repeated measures ANOVA observed a significant interaction between time and group for body mass (p = 0.043), body fat percentage (p = 0.045), body mass index (p = 0.025), neck circumference (p = 0.01), chest circumference (p = 0.027), left-hand grip strength (p = 0.043), right-hand grip strength (p = 0.048), standing broad jump (p = 0.044), and total Functional Movement Screen score (p = 0.003), and the improvement was greater for TG in comparison to CG. TG was found to be more effective than CG in enhancing body composition, physical fitness, and movement quality in obese adolescents.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.019
GPT teacher head0.280
Teacher spread0.262 · 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

Citations16
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueNutrientsSame topicChildren's Physical and Motor DevelopmentFrench-language works237,207