Detection of a "faked" strength task effort in volunteers using a computerized exercise testing system.

Abstract

The objective of this study was to develop an experimental method to separate a "faked" strength effort from a "best" effort in volunteers. Thirty-four pain-free volunteers (18 males, 16 females) performed a shoulder press and pull-down on an isokinetic computerized exercise testing system (CETS), giving a best effort followed by a faked effort. Two months later, a randomly selected subgroup (6 males) repeated the experiment to test the predictive validity of the derived variables. In the statistical analysis, best efforts were first compared with fake efforts by paired ttest for 80 CETS variables for males and females separately. Variables showing a strong difference between the best and faked effort were then selected for further analysis. In the second step of the analysis, the method of multiple correlations (r2 method) was used to reduce the number of redundant CETS variables to five in both the male and female groups. In the third step, a stepwise discriminant analysis was used to select predictor variables for the male and female groups. For the variables selected by the discriminant analysis for both males and females, sensitivities and specificities were calculated. Finally, the developed discriminant formula was used in the predictive validity part of the study to determine the sensitivities and specificities of the developed method. The discriminant analysis selected the following CETS variables for male and female groups, respectively: duty cycle down, work weight/down, peak value up (males); and average power up, 40% repetition down, duty cycle up (females). For males, using their three variables, the discriminant function classified 77.14% of the efforts correctly with 88.9% sensitivity and 64.7% specificity. For females, using their three variables, the discriminant function classified 90.63% of the efforts correctly with 100% sensitivity and 81.3% specificity. In the predictive validity group, the discriminant function classified 75% of the efforts correctly with 83.3% sensitivity and 66.7% specificity. This pilot study indicates that the method developed here may be useful in the experimental study for the discrimination between faked and best efforts on this isokinetic CETS machine. Future studies using this method will need to involve a larger number of volunteers.