TGMD-2短版:学龄前儿童性别、年龄和BMI的有效性证据

IF 0.8 Q4 PSYCHOLOGY, DEVELOPMENTAL Journal of Motor Learning and Development Pub Date : 2020-08-28 DOI:10.1123/JMLD.2019-0040
P. Bandeira, M. Duncan, Maria Luiza F. Pessoa, Í. Soares, L. R. Silva, J. Mota, C. Martins
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引用次数: 10

摘要

目的:分析低收入学龄前儿童大肌肉动作发展测试(TGMD-2)的效度和信度证据;并研究最终模型与性别、年龄和身体质量指数(BMI)之间的关系。方法:368名3 ~ 5岁学龄前儿童[M = 4.80, SD = 0.48];通过TGMD-2对生活在贫困地区的176名男孩进行了人体测量和运动能力评估。采用双因素模型(12项技能),计算验证性指标。采用贝叶斯准则和复合信度对备选模型进行评价。最后提出的模型与年龄、性别和BMI之间的关系使用网络分析(Mplus 8.0;Rstudio)。结果:对跑、跳、滑、击、投、滚六项技能建立的运动和物体控制双因子模型具有较好的指标,模型值>0.30。性别与投掷(r = - 0.22)和击打(r = - 0.21)之间的关系表明,男孩的表现更好。年龄与滑动(r = 0.23)和跳跃(r = 0.28)呈正相关,BMI与投掷(r = 0.18)呈正相关。结论:TGMD-2短版在低收入学龄前儿童中是有效的。将基本运动技能与性别、年龄和BMI相关联的机器学习分析似乎有助于优化未来的干预措施。
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TGMD-2 Short Version: Evidence of Validity and Associations With Sex, Age, and BMI in Preschool Children
Aim: To analyze the evidence of validity and reliability of the Test of Gross Motor Development, Second Edition (TGMD-2) for low-income preschoolers; and to investigate the associations between the final model with sex, age, and body mass index (BMI). Methods: 368 preschoolers (3–5 years old [M = 4.80, SD = 0.48]; 176 boys) located in deprived areas were assessed for anthropometric measures and motor competence via the TGMD-2. A two-factor model (12 skills) was used and confirmatory indexes were calculated. The Bayesian criteria and the Composite Reliability were employed to evaluate alternative models. Relationships between the final model proposed with age, sex, and BMI were calculated using a network analysis (Mplus 8.0; Rstudio). Results: A two-factor model (locomotion and object control) with adequate values (>0.30) for the six skills (gallop, leap, slide, strike, throw, and roll) presented excellent indexes. Relationships between sex and throwing (r = −.22), and strike (r = −.21), indicated better performance for boys. Positive relationships were found for age with slide (r = 0.23) and hop (r = 0.28), and for BMI with throw (r = 0.18). Conclusion: Validity of a TGMD-2 short version for low-income preschoolers was present. The machine learning analysis to associate fundamental movement skills with gender, age, and BMI seems useful to optimize future interventions.
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来源期刊
Journal of Motor Learning and Development
Journal of Motor Learning and Development Medicine-Orthopedics and Sports Medicine
CiteScore
2.20
自引率
15.40%
发文量
13
期刊介绍: The Journal of Motor Learning and Development (JMLD) publishes peer-reviewed research that advances the understanding of movement skill acquisition and expression across the lifespan. JMLD aims to provide a platform for theoretical, translational, applied, and innovative research related to factors that influence the learning or re-learning of skills in individuals with various movement-relevant abilities and disabilities.
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