What do Physical Fitness Tests Measure?—A Review of Factor Analytic Studies

Nicks, Delmer C.; Fleishman, Edwin A.

doi:10.1177/001316446202200109

Cited by 32 publications

(13 citation statements)

References 68 publications

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“…This is another in a series of studies (Hempel & Fleishman, 1955;Nicks & Fleishman, 1960;Fleishman, Thomas, and Munroe, 1961) concerned with the isolation and definition of factors in physical proficiency.…”

mentioning

confidence: 99%

The Dimensions of Physical Fitness. A Factor Analysis of Strength Tests

Fleishman¹,

Kremer²,

Shoup³

1961

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mentioning

confidence: 99%

The Dimensions of Physical Fitness. A Factor Analysis of Strength Tests

Fleishman¹,

Kremer²,

Shoup³

1961

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“…Skeletal muscle function indices have been advocated for the assessment of nutritional status (Nicks and Fleishman, 1962;Brozek, 1984). Changes in muscle function have been shown to be more sensitive to changes in dietary patterns than traditionally measured nutritional variables (Lopes et al, 1982;Russell et al, 1983;Vaz et al, 1996).…”

Section: Introductionmentioning

confidence: 99%

Seasonal variations in the relationship between mid-upper arm circumference and maximum voluntary contraction among ethiopian farmers

Lemma

2007

Eur J Clin Nutr

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Objectives: To determine the nature of the relationship between mid-upper arm circumference (MUAC) and maximum voluntary contraction (MVC) in pre-and post-harvest seasons among adult Ethiopian farmers. Subjects/Methods: A total of 491 healthy adult men aged 18-60 years were recruited at pre-harvest season and followed up at post-harvest season. Anthropometric measurements (weight, MUAC, biceps/triceps skinfold thickness and forearm circumference) were obtained using standard techniques and arm muscle circumference (AMC)/arm muscle area (AMA) was calculated. MVC of both arms was measured using a handgrip dynamometer. Paired t-test was used to compare means, and linear regression to investigate the relationship between MUAC and MVC. Results: Maximum voluntary contraction showed statistically significant correlation with MUAC. Grip strength (MVC) demonstrated a linear increase from under-nourished to normal subjects across MUAC classes. Paradoxically, mean MVC of both arms declined significantly during the post-harvest season. However, the relationship between MUAC and MVC held tight in the post-harvest season as seen in the pre-harvest period. Conclusions: This study has highlighted that under-nourished adult men have reduced functional ability (strength) in all seasons. In addition, strength increases in a linear fashion as MUAC increases during both seasons. More work examining the relationship between functional ability and anthropometric indices in adults from different developing countries is needed to address use and cutoffs for grip strength.

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“…Vickers (1995Vickers ( , 1996 found that muscle strength accounted for 91% of the variance in overall performance for a set of physically demanding U.S. Navy tasks. The virtual 1:1 correspondence between strength and physical performance was surprising because strength is only one of several well-documented physical abilities (Fleishman, 1964;Hogan, 1991;Myers, Gebhardt, Crump, & Fleishman, 1993;Nicks & Fleishman, 1962). These other abilities seem likely to account for more than 9% of the variance in physical task performance.…”

Section: Introductionmentioning

confidence: 99%

“…This dimension indicates the maximum force that a muscle group can generate for a brief period. Factor analyses have identified other physical abilities that are logically related to task performance (Fleishman, 1964;Hogan, 1991;Myers et al, 1993;Nicks & Fleishman, 1962). In fact, Fleishman (1964) identified 7 additional factors, including 3 other strength factors (e.g., dynamic strength, explosive strength).…”

Section: Introductionmentioning

confidence: 99%

“…The second hypothesis was that the estimated relationship between static strength and performance is biased when dynamic strength is omitted from the model. Assuming that dynamic strength would be positively related to both static strength (Nicks & Fleishman, 1962;Myers, Gebhardt, Crump, & Fleishman, 1993) and to performance, the bias should be positive. Adding dynamic strength to the model, therefore, will further weaken the relationship between static strength and performance.…”

Section: Introductionmentioning

confidence: 99%

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Physical Strength and Performance of Moderate Duration Physical Tasks

Vickers¹

2002

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SUMMARY ProblemValid models of physical task performance could be useful for selection into Navy jobs and for computer simulations of combat performance. Simple models are desirable, but of little value if they are inaccurate. Previous studies indicated that strength predicted more than 90% of the variance in performance on a wide range of physically demanding U.S. Navy tasks. This finding implies that strength is the only ability to consider for Navy selection and modeling purposes. However, the tasks studied previously lasted at most a few minutes. Work physiology principles predict that longer lasting tasks will have a more complex causal structure in which strength and endurance both are important. ObjectivesThe primary goals of this study were to (a) demonstrate that strength is a less powerful performance predictor when tasks last longer than 1 min, and (b) evaluate the hypothesis that the initial strength-performance estimate was biased by the omission of other physical abilities from the predictive equation. ApproachStructural equation modeling was applied to data from a study of steelworkers. Task performance measures included lifting, carrying, and shoveling tasks lasting 5 min to 15 min. Physical ability measures included the static strength dimension from earlier research and a dynamic strength dimension. Structural equation models were constructed to estimate the relationship between physical abilities and performance. ResultsStatic strength strongly predicted performance (β = .86), but this association was significantly (p < .001) lower than the estimate obtained in prior studies of shorter tasks. Adding dynamic strength (i.e., sit-ups, pull-ups) improved overall criterion prediction slightly (semipartial r = .13) even though it lowered the estimated effect of static strength by 25% (β = .69). ConclusionsThe effects of physical abilities on task performance can be estimated accurately only after careful selection of tasks and ability tests. The analysis procedures must provide methods of formulating and testing specific models that combine theoretical considerations with prior empirical findings. Most prior studies of physical abilities and task performance do not meet these criteria. The resulting estimates of the impact of physical ability on performance are likely to be biased. The biases can undermine the accuracy of screening batteries and/or lead to suboptimal performance enhancement interventions. Strength and Moderate Duration Tasks

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What do Physical Fitness Tests Measure?—A Review of Factor Analytic Studies

Cited by 32 publications

References 68 publications

The Dimensions of Physical Fitness. A Factor Analysis of Strength Tests

The Dimensions of Physical Fitness. A Factor Analysis of Strength Tests

Seasonal variations in the relationship between mid-upper arm circumference and maximum voluntary contraction among ethiopian farmers

Physical Strength and Performance of Moderate Duration Physical Tasks

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