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Published on: July 27, 2015
Detection of a "faked" strength task effort in volunteers using a computerized exercise testing system
D A Fishbain1, E Abdel-Moty, R B Cutler
1Department of Psychiatry, University of Miami School of Medicine, and the Comprehensive Pain and Rehabilitation Center at South Shore Hospital, Miami Beach, Florida 33139, USA.
Summary
Researchers developed a method to distinguish between genuine maximal strength efforts and faked efforts using a computerized exercise testing system (CETS). This technique shows promise for identifying genuine maximal exertion in research settings.
Area of Science:
- Exercise Physiology
- Biomechanics
- Sports Science
Background:
- Differentiating between maximal voluntary effort and simulated effort is crucial in exercise and sports science research.
- Previous methods for detecting faked efforts have limitations, necessitating the development of more objective techniques.
- Isokinetic computerized exercise testing systems (CETS) offer a controlled environment to measure various strength parameters.
Purpose of the Study:
- To develop and validate an experimental method for distinguishing between 'best' (maximal) and 'faked' strength efforts.
- To identify specific CETS variables that can reliably discriminate between these two effort types in male and female volunteers.
- To assess the predictive validity of the developed discrimination method.
Main Methods:
- Thirty-four healthy volunteers performed both maximal and faked efforts on a CETS for shoulder press and pull-down exercises.
- Statistical analyses, including paired t-tests, multiple correlations, and stepwise discriminant analysis, were used to identify discriminating variables.
- The developed discriminant function was tested for accuracy, sensitivity, and specificity in classifying efforts, including a predictive validity subgroup.
Main Results:
- Discriminant analysis identified distinct CETS variables for males (duty cycle down, work weight/down, peak value up) and females (average power up, 40% repetition down, duty cycle up).
- The discriminant function achieved high classification accuracy: 77.14% for males and 90.63% for females in the initial analysis.
- In the predictive validity test, the function correctly classified 75% of efforts, with sensitivities of 83.3% and specificities of 66.7%.
Conclusions:
- The developed experimental method using CETS variables shows potential for reliably discriminating between faked and best strength efforts.
- The identified CETS variables and discriminant functions offer a promising tool for researchers studying maximal voluntary contractions.
- Further research with larger participant groups is recommended to confirm and refine this discrimination method.
