Resistance Training Increases the Variability of Strength Test Scores

Abstract

Informal observations made while conducting a meta-analysis of resistance training programs suggested that the between-person variation in strength test scores is greater after training than before. This study treated the informal observation as a hypothesis to be evaluated. The odds were 2.5:1 that the standard deviation after training would be larger than the standard deviation before training if a sample underwent resistance training, compared with 1:1 odds for control groups in training studies. This difference supported the study hypothesis. Extending the analysis to subcategories based on age, gender, training experience, and training program characteristics, the training effect was present in all subgroups, but it was significantly stronger in some than others (e.g., older or novice lifters). The training effect did not increase with program length. This fact and the weak effect in experienced lifters suggested that the training effect might be a product of neuromuscular adaptations occurring early in training. Whatever its source, the training effect seldom will change inferences about whether resistance training has increased the strength of program participants, but it could be important when predicting how training affects the ability to meet basic performance standards.

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Document Details

Document Type
Technical Report
Publication Date
Jun 08, 2009
Accession Number
ADA515121

Entities

People

  • Amanda C. Barnard
  • Linda K. Hervig
  • Ross R. Vickers

Organizations

  • Naval Health Research Center

Tags

DTIC Thesaurus Topics

  • Behavioral Sciences
  • Computations
  • Data Analysis
  • Data Science
  • Department Of Defense
  • English Language
  • Health
  • Information Science
  • Literature Surveys
  • Nonparametric Statistics
  • Observation
  • Public Health
  • Resistance
  • Standards
  • Statistical Analysis
  • Statistics
  • Training

Readers

  • Exercise and Sports Science.
  • Instructional Design and Training Evaluation.
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks