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Anthropometric determinants of perfo...
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Kinnunen, David A.
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Anthropometric determinants of performance in the standing long jump.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Anthropometric determinants of performance in the standing long jump./
作者:
Kinnunen, David A.
面頁冊數:
118 p.
附註:
Source: Dissertation Abstracts International, Volume: 64-12, Section: A, page: 4404.
Contained By:
Dissertation Abstracts International64-12A.
標題:
Education, Physical. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3115988
ISBN:
0496634240
Anthropometric determinants of performance in the standing long jump.
Kinnunen, David A.
Anthropometric determinants of performance in the standing long jump.
- 118 p.
Source: Dissertation Abstracts International, Volume: 64-12, Section: A, page: 4404.
Thesis (Ph.D.)--Michigan State University, 2003.
The purpose of this study was to examine the relationship of structural-maturational (SM) variables to performance in the standing long jump from a dynamic systems perspective. The SM variables to be studied were: weight, standing height, sitting height, acrom-radiale length, radio-stylion length, biacromial width, bicristal width, arm girth, thigh girth, calf girth, triceps skinfold, subscapular skinfold, and umbilical skinfold. Derived variables included in the study were: body mass index, sum of skinfolds, triceps + subscapular skinfolds, sit/stand ratio and hip/shoulder ratio. Dynamic systems theory predicts that change results when one or more control parameters are altered (Clark & Phillips, 1993; Peitgen, Jurgens, & Saupe, 1992; Thelen, 1985; Kelso, 1984). Haubenstricker and Branta (1997) suggested that further research into jumping behavior should concentrate on determining the variables, or control parameters, that enhance or limit performance. An analysis of the anthropometric measures on the standing long jump aids in identifying the factors that may drive changes in performance. A systems approach allows us to look at how the many subsystems involved act together to impact performance and at the same time identifies the subsystems where small changes may influence development or performance. In order to fully understand the changes in developing systems, the system sensitive control parameters (e.g., changes in the muscular-skeletal system, the masses and length of the limbs, or other physical characteristics) that drive the system to reorganization should be examined (Clark, 1986). This study included 487 Caucasian participants, 234 males (47%) and 258 females (53%), a subset of the longitudinal Motor Performance Study (MPS) at Michigan State University. Ages ranged from 7 through 18 years. Data were longitudinal in nature and collected semi annually. Regression analysis suggested the following factors act as control parameters for females at age 7---radio-stylion length; females at age 12---triceps + subscapular skinfolds; females at age 16---sum of skin folds and standing height. The percent variance explained by the variables was 10.6%, 9.5%, and 15.3% respectively. The results for the study suggested the following factors act as control parameters for males the age groups and corresponding factors were: at age 7---subscapular skinfolds; age 14---triceps skinfolds, biacromial width and umbilical skinfolds; age 18---triceps + subscapular skinfolds and sitting height. The percent variance explained by the variables was 11.8%, 25.9%, and 19.4% respectively.
ISBN: 0496634240Subjects--Topical Terms:
1018000
Education, Physical.
Anthropometric determinants of performance in the standing long jump.
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The purpose of this study was to examine the relationship of structural-maturational (SM) variables to performance in the standing long jump from a dynamic systems perspective. The SM variables to be studied were: weight, standing height, sitting height, acrom-radiale length, radio-stylion length, biacromial width, bicristal width, arm girth, thigh girth, calf girth, triceps skinfold, subscapular skinfold, and umbilical skinfold. Derived variables included in the study were: body mass index, sum of skinfolds, triceps + subscapular skinfolds, sit/stand ratio and hip/shoulder ratio. Dynamic systems theory predicts that change results when one or more control parameters are altered (Clark & Phillips, 1993; Peitgen, Jurgens, & Saupe, 1992; Thelen, 1985; Kelso, 1984). Haubenstricker and Branta (1997) suggested that further research into jumping behavior should concentrate on determining the variables, or control parameters, that enhance or limit performance. An analysis of the anthropometric measures on the standing long jump aids in identifying the factors that may drive changes in performance. A systems approach allows us to look at how the many subsystems involved act together to impact performance and at the same time identifies the subsystems where small changes may influence development or performance. In order to fully understand the changes in developing systems, the system sensitive control parameters (e.g., changes in the muscular-skeletal system, the masses and length of the limbs, or other physical characteristics) that drive the system to reorganization should be examined (Clark, 1986). This study included 487 Caucasian participants, 234 males (47%) and 258 females (53%), a subset of the longitudinal Motor Performance Study (MPS) at Michigan State University. Ages ranged from 7 through 18 years. Data were longitudinal in nature and collected semi annually. Regression analysis suggested the following factors act as control parameters for females at age 7---radio-stylion length; females at age 12---triceps + subscapular skinfolds; females at age 16---sum of skin folds and standing height. The percent variance explained by the variables was 10.6%, 9.5%, and 15.3% respectively. The results for the study suggested the following factors act as control parameters for males the age groups and corresponding factors were: at age 7---subscapular skinfolds; age 14---triceps skinfolds, biacromial width and umbilical skinfolds; age 18---triceps + subscapular skinfolds and sitting height. The percent variance explained by the variables was 11.8%, 25.9%, and 19.4% respectively.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3115988
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