Matheson, L., Bohr, P., & Hart, D. (1998). Use of maximum voluntary effort grip strength testing to identify symptom magnification syndrome in persons with low back pain. Journal of Back and Musculoskeletal Rehabilitation, 10, 125–135.


Functional capacity evaluations often are used in circumstances in which the evaluee’s willingness to put forth full effort may be suspect. Identification of full effort performance has become an important aspect of the functional capacity evaluation of persons with medical impairments. Although the prevalence of less than full effort performance in this population is not known, it is widely assumed to be significant in situations where financial compensation for the medical impairment is involved. When present and associated with biobehavioral factors, less than full effort performance has been shown to affect clinical outcome.

When less than full effort performance is seen, there are several likely causes, including fear of symptom exacerbation, depression, or other affective disorders. It may also be the case that this behavior is part of a pattern of maladaptive behavioral responses that has been called “sick role,” “illness behavior,” “abnormal illness behavior,” and “symptom magnification syndrome.”

Various methods have been used to attempt to identify behavior patterns that may be a cause of sub-maximal performance, including a questionnaire, structured interview, musculoskeletal examination and maximum voluntary effort (MVE) testing. In MVE tests, inconsistency of effort has been taken to be indicative of less than full effort. Many clinicians have accepted the idea that observation of inconsistent behavior is useful in identifying the presence of a maladaptive behavioral response pattern. However, this assumption has not been studied in a sample of impaired persons. The current study investigates the likelihood that inconsistent performance in MVE testing is a significant indicator of the symptom magnification syndrome, defined as “a self-destructive, socially reinforced behavioral response pattern consisting of reports or displays of symptoms which function to control the life circumstances of the sufferer.” Inconsistent performance during MVE testing was studied in a sample of persons who were being treated for occupational injuries within the context of a state workers’ compensation system. These patients were in a treatment circumstance in which behavior during a functional capacity evaluation had the potential to result in financial benefit to the evaluee. Research with this population is important because the situation represents a circumstance in which the application of MVE testing to identify less than full effort performance ought to be most useful.

Grip Strength Consistency as an Indicator of Effort

Isometric grip strength has been measured in medical and occupational settings for many years. Bechtol reported the “bell-shaped curve” that is dependably obtained over the five grip spans that are tested with the JAMAR Hand Dynamometer. An early study which measured the stability of the underlying variable found day-to-day variation in maximum strength within individual subjects of 10% to 15%. This was consistent with variation reported for other isometric strength measures. Kroemer and Marras found that coefficients of variation for repeated measures of grip strength were “remarkably constant” across four different force levels representing proportions of maximum voluntary effort that were tested. The approach which uses peak values as indicators of effort has also been used by Matheson, based on research that identified normal levels of variability of these peak values in samples of disabled persons. This research supported the clinical use of the coefficient of variation statistic with three or more repeated trials as an indicator of consistency of effort.

Other measurement strategies have been studied. Gilbert and Knowlton performed a single-blind study using normal subjects randomly assigned to “sincere effort” and “fake effort” groups to investigate methods to determine maximum voluntary grip contraction with the JAMAR. Using data from force curve read-outs, these researchers found that a configuration analysis of the isometric force curve was the best indicator of effort-group membership for both males and females. For males alone, the slope of the curve to the point of peak and the ratio of peak force to body weight were also statistically significant predictors of effort-group membership. The ratio of average force to peak over a five-second trial was the best predictor of sincerity of effort. Once this factor was entered into a discriminant function analysis, neither the slope to the peak nor the ratio of body mass to peak force made significant contributions to the prediction equation. These researchers also reported a high degree of replication on a test-retest basis with subjects under both test conditions. That is, they challenged the value of the use of low reliability in repeated testing to identify individuals who are putting forth less than full effort.

Niebuhr and Marion tested the hypothesis that less than full effort on the JAMAR is identified by the absence of a bell-shaped curve. This study found that the curve was present but flattened and offset when individuals put forth less than full effort. Hildreth, Breidenbach, Lister, and Hodges tested 100 normal subjects over all five positions on the JAMAR and found a dependable bell-shaped curve which peaks at Position 3, with Position 2 quite close. This same curve was found, although it was displaced, when full effort results from an injured hand were compared with the same subject’s uninjured hand. When uninjured subjects faked an injury with one hand, a flattened curve was found with the faked hand, while the normal bell-shaped curve was found with the normal hand.

Smith, Nelson, Sadoff, and Sadoff identified five variables in the force time curve for tests with the JAMAR using a microcomputer-based data collection system. Testing healthy males and females, who were instructed on a random basis to produce submaximal performance interspersed with maximal performance, these researchers found substantial differences between males and females for the criterion values to determine faking for each of the variables. For the males, individual variables correctly identified sincere effort and discriminated from insincere effort in more than 90% of the trials. For the females, criterion values identified sincere effort more than 90% of the time, but were much less effective in identifying insincere effort. Use of the variables in different combinations substantially improved detection of sincerity and insincerity for both males and females.

Chengalur, Smith, Nelson, and Sadoff applied the Smith et al. strategy to individuals with a variety of unilateral upper extremity injuries. As with the previous study, individual variables were generally less useful than combinations of variables in identifying insincere effort. When used in combination, these researchers found that it was possible to identify 97% of the sincere efforts for the males and between 87% and 100% of the sincere efforts for the females. Identification of insincere efforts using various combinations of the variables ranged from 68% to 85% for the males and from 63% to 83% for the females.

In a study of response to repetitive hand gripping tasks, a significant difference was found when insincere subjects were compared with subjects who were either injured or healthy. An “endurance index” based on force decrement during repetitive power grip successfully differentiated among the groups, with the insincere group demonstrating much less of a force drop-off over multiple repetitions.

The use of test re-test reliability to identify less than full effort performance in an isometric back strength test found no differences that could be attributed to less than full effort. In this study, subjects were asked to “fake a back injury.” This study found that the hypothesis that sub-maximal efforts cannot be reproduced as consistently as a maximum effort was not supported. Subjects were able to consistently reproduce a sub-maximum effort with high reliability even in the absence of performance feedback. Hart and his colleagues have also found that patients receiving treatment for workers’ compensation injuries were able to be reliable with both submaximal and maximal efforts over three repetitions with a static standing arm lift on an isometric strain gauge.

Although the efficacy of maximum voluntary isometric effort testing as an indicator of effort has been studied extensively and has produced equivocal results, the practice continues on a widespread basis. The current study was designed to test the assumption that less than full effort performance with the JAMAR is a useful indicator of symptom magnification syndrome in a sample of persons who have medical impairments for which financial benefit may accrue as a consequence of test results. In order to address this assumption, a research question was developed: Does inconsistency of effort in performance with the JAMAR Hand Dynamometer correlate with other behavioral measures of symptom magnification syndrome?


Subjects and Settings

Data were collected on 300 consecutive adult subjects who were evaluated in three independent, private acute orthopedic rehabilitation clinics. All subjects had been referred to the clinics for a functional capacity evaluation (FCE). The FCE protocol, which adhered to published standards of functional testing has been described elsewhere. Of the original data set, a subset composed of 175 subjects who presented only with symptoms of low back pain and who denied other symptoms was selected. Through this process, all subjects with symptoms involving the cervical and thoracic spine, or symptoms with either hand or upper extremity were excluded. Of this subset, 10 subjects reported left-hand dominance or ambidexterity. Because this study was designed to use normative data as one method to address the research questions, a decision was made to exclude these latter subjects. These subjects were too few to allow determination of normative hand strength references and could not logically be included in the right-hand dominant subjects’ sample. Thus, the focus of the current study was on 165 right-handed subjects (109 males, 56 females) with low back pain, reporting no other symptoms.


Subjects’ demographic data are presented in Table 1. Females were significantly older than the males (F1,163 = 5.83, p =.017), while males were both taller (F1,163 = 89.11, p <.0001) and heavier (F1,163 = 15.96, p <.0001). There was no difference in SMS rating (F1,163 =.36, p =.55).

Table 1. Subject characteristics.
Male (SD)
(n = 109)
Female (SD)
(n = 56)
Age (yrs)38.26 (9.3)41.89 (8.8)
Weight (kgs)89.55 (18.2)77.34 (19.3)
Height (cm)177.82 (10.0)163.55 (7.4)
SMS Rating (%)20.40 (21.4)18.40 (18.0)

Gender Performance Comparisons

Males’ grip data are presented in Table 2 and 3, and grip data for females are presented in Table 4 and 5. One-way analyses of variance indicated that males had significantly greater grip strength in each position than the females (all p <.0001). There was no difference between sexes in coefficient of variation (p >.05) except for position 3 (F1,163 = 4.14, p =.04) on the left and position 5 (F1,163 = 4.00, p =.05) on the left. In both cases, females had greater coefficient of variation scores.

Table 2. Mean grip strength (lbs of force) and coefficient of variation (CV) data for males (n = 109).
Grip PositionRight HandLeft Hand
Mean (SD)CV (SD)Mean (SD)CV (SD)
Position 167.78 (20.1).08 (.06)64.96 (22.7).09 (.10)
Position 2103.54 (29.3).06 (.04)92.96 (29.1).06 (.08)
Position 3100.31 (30.3).06 (.05)93.65 (28.7).05 (.04)
Position 489.71 (25.5).06 (.07)85.65 (25.3).05 (.04)
Position 578.94 (22.7).06 (.05)74.45 (22.0).06 (.05)
Table 3. Mean grip strength for males, presented as percent of maximum for each subject (n = 109).
Grip PositionRight Mean (SD)Left Mean (SD)
Position 164.1 (12.1)65.6 (11.9)
Position 296.4 (6.5)93.0 (10.6)
Position 392.6 (10.0)93.4 (9.6)
Position 483.6 (9.3)86.1 (10.8)
Position 573.6 (8.6)75.1 (10.1)
Table 4. Mean grip strength (lbs of force) and coefficient of variation (CV) data for females (n = 56).
Grip PositionRight HandLeft Hand
Mean (SD)CV (SD)Mean (SD)CV (SD)
Position 143.55 (14.9).10 (.08)38.23 (13.5).08 (.05)
Position 259.63 (23.3).07 (.04)54.77 (21.2).06 (.06)
Position 355.18 (21.2).06 (.04)52.61 (19.6).07 (.05)
Position 450.25 (19.7).07 (.04)46.98 (18.7).06 (.04)
Position 543.50 (16.9).07 (.05)42.27 (18.7).08 (.06)
Table 5. Mean grip strength for females, presented as percent of maximum for each subject (n = 56).
Grip PositionRight Mean (SD)Left Mean (SD)
Position 173.1 (15.2)68.8 (13.0)
Position 296.7 (6.4)95.8 (8.0)
Position 389.4 (10.3)92.4 (9.0)
Position 481.5 (9.6)82.2 (11.0)
Position 570.8 (11.1)75.4 (12.8)

Comparisons of subjects’ grip strength with normative data indicate that the current subjects were approximately one standard deviation below the mean of same-age normal subjects. This is consistent with an earlier study conducted by the senior author that demonstrated grip strength values for disabled persons with the JAMAR which were lower than those found for healthy persons. Likewise, data from the present study describe consistency of effort are similar to findings presented in earlier studies of impaired persons with the JAMAR dynamometer. For both males and females, the coefficients of variation averaged 10 percent or less, with the highest values found in Span 1.

Grip Strength and CV Scores

The relationships among grip strength scores, coefficients of variation for each set of grip strength scores, and SMS ratings were studied with regression analyses, using the SMS percent rating as the dependent variable. Because the grip strength scores were confounded with gender, normative values based on a z-score transformation of each subject’s average score for each set of trials were used. Forward stepwise regressions of average grip strength, average grip strength z-score, average grip strength percent of maximum, and coefficient of variation were made against the SMS rating. These analyses evaluated the contribution that each independent variable made to predicting SMS rating. Standardized partial regression coefficients describe the relative contribution of each variable. Generally, the variables were related to SMS rating in the expected direction, and weak grip strength was a better predictor than a high coefficient of variation. These data are presented in Table 6 for the right hand and Table 7 for the left hand.

Table 6. Comparison of standardized partial regression coefficients for grip strength and coefficient of variation against SMS rating for the right hand.
All listed coefficients are significant at p <.05.
Grip Averagena*nananana
Grip Average
Grip Average % of Maxnana−.192nana
Multiple R2.
*Not included in regression equation because the independent contribution to the equation is non-significant.
Table 7. Comparison of standardized partial regression coefficients for grip strength and coefficient of variation against SMS rating for the left hand.
All listed coefficients are significant at p <.05.
Grip Averagena*nananana
Grip Average
Grip Average % of Maxnana−.174nana
Multiple R2.
*Not included in regression equation because the independent contribution to the equation is non-significant.

Cutpoints as Predictors of SMS

The relationships between grip strength score, coefficients of variation for each set of grip strength scores, and SMS ratings were studied through the use of factorial analysis of variance, using the SMS percent rating as the dependent variable. In order to replicate the use of such data in the clinic, categorical variables were created by using cutpoints for each subject’s grip strength average score and coefficient of variation for each JAMAR position with each hand. The cutpoints were based on normative data derived from each gender sample. For the grip strength scores, the cutpoint was set at less than or equal to the 10th percentile, while for the coefficient of variation scores, the cutpoint was set at greater than the 90th percentile. If a subject’s score was less than or equal to the grip strength cutpoint or exceeded the coefficient of variation cutpoint, it was considered a “hit.” The number of hits for each subject was taken as the grouping variable. The ANOVA for the coefficient of variation (CV) variable yielded a significant effect (F3,161 = 10.74, p <.0001), as did the ANOVA for the grip strength (Grip) variable (F3,161 = 10.40, p <.0001) and the ANOVA for a variable composed of conjoint hits (F3,161 = 12.55, p <.0001). These data are presented in Table 8.

Table 8. SMS Scores based on number of occasions subject was beyond a normative cutpoint; > 90th percentile for CV, <= 10th percentile for grip strength, and number of occasions both were exceeded.
HitsCoefficient of VariationGrip StrengthConjoint Hits
None129.157 (.17)96.16 (.18)144.17 (.18)
One9.221 (.17)35.18 (.17)8.32 (.24)
Two4.412 (.18)14.18 (.15)4.36 (.17)
More23.372 (.26)20.42 (.26)9.52 (.25)

Post hoc Scheffé analyses were conducted. These demonstrate significant differences (p <.05) for the CV variable between the “more” group and each of the other groups. For the Grip variable, significant differences (p <.05) were found only between the “none” and “more” groups. For the Conjoint variable, significant differences (p <.05) also were found only between the “none” and “more” groups.

Performance Profiles as Predictors of SMS

The value of performance profiles as a method to identify the presence of SMS was studied through the use of regression analysis. Profiles were presented to five expert judges. A profile sheet, developed for each subject, described the level of each test over all five sessions, plus the coefficient of variation for each set of three trials. Each score was presented in a graphic that included the mean and standard deviation for each gender for each measurement. Each judge was asked to rate every profile sheet in terms of a five-level scale ranging from “completely dependable” to “completely undependable.” After each judge had independently scored each sheet, intra-class correlations were calculated. The ICC (2,1) was r =.81, indicating good agreement. Given agreement among the judges, the average score for each subject’s rating across all five judges was taken as the judges’ rating variable, and used in a regression analysis as an independent variable to predict SMS rating. This resulted in a regression equation with R2 =.182 (p < .0001). Subsequently, in order to compare the value of the judges’ rating with the best single indicator previously identified (grip strength for right hand fourth position on the JAMAR), a multiple regression analysis was performed which used the judges’ rating and the z-score from this test as independent variables. This combination of variables predicted SMS rating with R2 =.191 (p <.0001). The comparison of standard coefficients for each of the independent variables indicated that the judges’ ratings accounted for almost three times as much variance as the z-score for strength.

Comparison of Decision Accuracy

The sensitivity, specificity and positive predictive value of each strategy was assessed using an SMS rating of greater than 50% as the criterion. Data which describe the effects of this decision strategy are presented in Table 9. This value of the criterion was selected based on a requirement that is imposed in litigation that a diagnosis be based on evidence which indicates that it is “more likely than not” (greater than 50% probability) that the patient has a syndrome. Other values of the criterion could be applied, although this is the most rigorous. At this criterion value, there is a 10% prevalence of SMS in this sample.

Table 9. Accuracy of methods of classification, based on an SMS rating for each subject of 50% or greater as the criterion for identification of the presence of the syndrome.
Accuracy MeasureCoefficient of VariationGrip StrengthConjoint HitsJudges’ Rating
Positive Predictive Value.
Negative Predictive Value.

Although the sensitivity of the coefficient of variation measure was best, the positive predictive value of the “conjoint hits” measure was best. The other variables were intermediate.


Methods for formally identifying patterns of maladaptive behavior have been proposed and are in widespread use. However, this literature has focused on identifying inconsistency of effort in maximum voluntary effort testing with “normal” populations. The current study investigated the validity of maximum voluntary effort grip strength testing for the identification of symptom magnification syndrome in a sample of 165 disabled workers who were receiving workers’ compensation benefits and who were reporting problems with low back pain.

Grip strength and CV scores have been purported to be useful for determining insincere effort. The value of any testing procedure must be considered in terms of several issues, including the use to which the information is to be put. The utility of the information is dependent on the test’s safety, reliability, validity, and practicality. The safety and reliability of maximum voluntary effort grip strength testing with persons with medical impairment has been reported previously. The current study investigated the concurrent validity of this procedure to predict SMS ratings in a sample of disabled males and females presenting for treatment within the context of a workers’ compensation medical clinic. The findings indicate that the absolute value of the subject’s grip strength was not useful in predicting SMS. However, a z-score transformation of the grip strength score to achieve a normative within-gender index resulted in a statistically significant relationship in every grip span. In this study, weak grip strength compared to same-sex values was a better predictor of SMS ratings than CV scores. The predictive value of the CV is inconsistent and weak over all five grip spans. The CV is predictably related to SMS in Span 2, Span 3, and Span 5. The grip strength variable is related to the dependent variable only in the regression equation for Span 3. Although, from a scientific standpoint, both factors could be used to identify insincere effort, neither factor was a strong predictor.

In the study by Smith, Nelson, Sadoff, and Sadoff criterion values for identified variables to determine faking were used to correctly identify sincere effort and discriminate from insincere effort most of the time. The current study found that subjects’ cut point scores were predictive for SMS only when variation from normal values was used as an indicator of SMS. However, these differences may not be clinically useful. The positive predictive value for such measures ranged from .30 to .56, indicating that a positive test result will be correct only 30% to 56% of the time.

Grip strength should follow a bell-shaped curve for the five levels of the dynamometer when the individual is providing maximum effort. Niebuhr and Marion concluded that flattened and offset curves were indicative of individuals putting forth less than full effort. Likewise, Hildreth and his colleagues found that the curves recorded when uninjured subjects faked an injury with one hand were flattened while the normal bell-shaped curve was found with the normal hand. In order to investigate the concurrent validity of such strategies, performance profiles were created for each subject and reviewed by expert judges who rated the profiles based on the shape of the strength curves, comparison of the curves for the right and left hands and the CV scores. Although good agreement was found among the judges, these performance profiles predicted less than 20 percent of the variance in SMS. Similarly, use of these profiles demonstrated sensitivity of 44 percent and positive predictive value of only 41 percent. The judges ratings were the best predictor of SMS in the present study, but positive ratings were incorrect 59 percent of the time. It is clear that these types of ratings from experts are not accurate enough to be considered as the sole criterion for determining less than maximum effort. The utility of this approach is little better than using the grip strength and CV scores alone.

The accuracy of the ability of the four methods of classification to identify SMS was studied by using a reference criterion that would be similar to that found it a court of law. Given this criterion, the sensitivity of the methods ranged from 31 percent to 50 percent. That is, 31 percent to 50 percent of the time that SMS was found in this sample, the methods of classification under study were correct. The specificity of these measures is much better, ranging from 89 percent to 97 percent. That is, when SMS has not been conclusively found, the measures that were studied agreed frequently. However, the positive predictive value of these measures was poor, ranging from 30 percent to 56 percent. In the circumstance in which the subject has a positive score with these methods, the evaluator will be in error 30 percent to 56 percent of the time. This finding is especially troubling given the potential effect of such a decision error on the evaluee. Such procedures will unfairly classify subjects much more frequently than seems reasonable.

The use of maximum voluntary effort testing has been a tool valued by many clinicians. Although the use of maximum voluntary effort testing for detection of insincere effort or for identification of problems with motivation has been scientifically evaluated with normal subjects, the present clinical study raises doubts about its utility in a clinical setting. Specifically, the present study suggests that this method must not be the sole basis for making decisions about the level of effort of injured workers since it explains only a small proportion of the variance. Expert ratings of performance profiles were stronger indicators than grip strength and CV scores in the present study but did not provide overwhelming evidence of SMS. The best approach for determining sincerity of effort may be a combination of measures, although the definitive study of this issue has not been conducted. Future investigations should combine several MVE measures with other forms of functional testing to determine the best method or combination of methods for determining SMS.


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