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Detection of Insincere Grips: Multivariate Analysis Approach Dr Bhoomiah Dasari University of Southampton Southampton SO17 1BJ United Kingdom

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Presentation on theme: "Detection of Insincere Grips: Multivariate Analysis Approach Dr Bhoomiah Dasari University of Southampton Southampton SO17 1BJ United Kingdom"— Presentation transcript:

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3 Detection of Insincere Grips: Multivariate Analysis Approach Dr Bhoomiah Dasari University of Southampton Southampton SO17 1BJ United Kingdom

4 Introduction A standardized grip strength assessment can provide us with quantifiable and objective information on clients hand functions (Kuzala & Vargo, 1991) Measurement of grip strength is a basis to use in the physical medicine to assess patients work capacities and progress of rehabilitation (Gilbert & Knowlton, 1983). Functional Hand evaluation is a kind of performance test, its validity, therefore relies heavily on the cooperation or sincerity of the subjects being assessed.

5 Previous studies of Grip sincerity Static Isometric Grip Test Approach (Stokes 1983, Stoke et. al 1995, Niebuhr and Marion 1987, Niebuhr and Marion 1990) Rapid Alternate Grip Test Approach (Hildreth, Breidenbach, Lister and Hodges 1989, Joughin et al 1993) Coefficient of Variation Approach (Bechtol 1954, Robinson et al 1993, Fairfax, Balnave & Adams 1995) Sustain Grip Test Approach (Kroemer & Marras 1980, Gilbert and Knowlton 1983, Smith et al 1989, Chengalur et al 1990)

6 Chenglaurs Method (1990) The EVAL system by Greenleaf Medical Systems was used in this research Typical Force-Time Curve For Sincere & Fake Condition Time (Sec) Grip Strength (Lbs) Fake Trial Sincere Trial P=Peak force A=average of plateau SD=SD of plateau

7 The discriminators (Chengalur,1990) Derived from data obtained from the sustain grip test D1. Ratio: 100 * A / P (greater – more sincere) D2. Coefficient of Variation: 100 * SD of Plateau / Mean of Plateau (smaller – more sincere) D3 called Ratio Difference. It was devised for comparison between major & minor hand (Maj / Min) characteristics. (for healthy subjects only: greater – more sincere) D4: Peak-Average Difference: {(P-A) * 100 }/ (P *A) (smaller – more sincere) D5: Peak-Average Root Difference : (smaller – more sincere)

8 Criterion value (method proposed by Chengalur,1990) *Remarks: Stand for the cut-off point using 95% confidence level (If subject has D4 score equal or less than the cut-off point, it is 95% sure the subject lies within the sincere group) D4 Score for Sincere And Fake Trial – hypothetical (smaller – more sincere) D4 Score Frequency Sincere Trial Fake Trial Zone I Zone II cut-off point

9 Objectives of current study To test the applicability of Chengalurs methods and its findings in Chinese subjects. To explore the use of multivariate analysis (logistic regression) on the raw data obtained in the sustain grip test to detect faking.

10 Demographic Profile of Healthy Subjects (Group 1)

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12 Demographic Profile of Ex-hand Injured Patients (Group 2)

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14 Test Procedure All subjects are taught to do the sustain grip test using the EVAL System. All subjects were randomized into 2 subgroups – subgroup 1a perform sincere grip and then fake grip, while subgroup 1b perform fake grips first and then sincere grip, etc. For fake grips, subjects are assigned randomly a faking ratio of 25%, 50%, or 75% of maximum grip strength.

15 Test Procedure Findings from sustain grip tests were converted into the discriminator, i.e. D1, D2, D4, D5. (D3 was used to healthy subjects only). % of accurate detection of sincere and fake group by using the Chengulars method and Logistic regression was estimated and compared.

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17 Instrumentation The EVAL system by Greenleaf Medical Systems was used in this research Typical Force-Time Curve For Sincere & Fake Condition Time (Sec) Grip Strength (Lbs) Fake Trial Sincere Trial P=Peak force A=average of plateau SD=SD of plateau

18 Hypothetical distribution of D4 showing the application of criterion value in determining fake and sincere group Remarks: the cut-off point Zone I:Under the blue curve - true sincere grip (87.5%) Under the red curve - false sincere grip (type II error, 21.2%) Zone II:Under the blue curve - false fake grip (type I error, 12.5%) Under the red curve - true fake grip (77.8%) Hypothetical distribution of D4 (male) 0 D4 Value Frequency Sincere Grip Fake Grip Zone I Zone II 1.10

19 Percentage of successful detection of fake grip by Discriminant Analysis (Group 1-healthy subjects)

20 Percentage of successful detection of fake grip by Logistic Regression (Group 1-healthy subjects)

21 Percentage of successful detection of fake grip by Discriminant Analysis (Group 2-Ex-patients)

22 Percentage of successful detection of fake grip by Logistic Regression (Group 2-Expatients)

23 Percentage of successful detection of fake grip by Discriminant Analysis (Groups 1 & 2)

24 Percentage of successful detection of fake grip by Logistic Regression (Groups 1 & 2)

25 Results-Summary Both methods, i.e. Discriminant Analysis and Logistic Regression can detect between 90%- 100% sincere grips. For subjects, who performed at 20% or 50% of their maximum grips, it was possible to detect 92% faking in males and 86.5% in female by using logistic regression method. True sincere True faking

26 Conclusions It is possible to obtain better prediction accuracy by using the multivariate statistical method of approach (Logistic regression). It is also possible to formulate a mathematical model for detecting the faking grip. This, however will depend on a larger sample for developing a more reliable formula for clinical and medico-legal application.

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