Physical Strength and Performance of Moderate Duration Physical Tasks

Abstract

Previous research has demonstrated a strong relationship (r= .953) between strength and performance on physically demanding U.S. Navy tasks. The earlier work covered tasks lasting <1 min and limited strength measures to static strength. The relationship might be weaker for longer-lasting tasks that required muscle endurance. The earlier estimate also may have been biased by the omission of other aspects of muscle strength. This study related static and dynamic strength to performance on physical tasks lasting 5 to 15 min to test these hypotheses. As expected the association between static strength and task performance was significantly (p < .001) weaker than in the earlier study (r = .86). Omitted variable bias was indicated by the fact that the regression coefficient relating static strength to performance shrank by 25% (i.e., Beta = .69) when dynamic strength was added to the model. Sound models require systematic sampling on both sides of the ability- performance equation. Incompleteness is especially important when a model is the basis for performance enhancement interventions. In this specific instance, the results suggest that omitted variable bias would lead to a 25% overestimation of program effects.

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Document Details

Document Type
Technical Report
Publication Date
Sep 26, 2002
Accession Number
ADA432131

Entities

People

  • Ross R. Vickers

Organizations

  • Naval Health Research Center

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Applied Psychology
  • Behavioral Sciences
  • Coefficients
  • Data Science
  • Equations
  • Factor Analysis
  • Information Science
  • Intervention
  • Measurement
  • Musculoskeletal Physiology
  • Physical Fitness
  • Psychological Phenomena And Processes
  • Psychology
  • Regression Analysis
  • Sampling
  • Task Performance And Analysis
  • Two Dimensional

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Computational Modeling and Simulation
  • Mechanical Engineering/Mechanics of Materials.