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Psychological Injury and Law

, Volume 12, Issue 2, pp 113–126 | Cite as

Demographically Adjusted Validity Cutoffs on the Finger Tapping Test Are Superior to Raw Score Cutoffs in Adults with TBI

  • Laszlo A ErdodiEmail author
  • Brian Taylor
  • Alana G Sabelli
  • Malayna Malleck
  • Ned L Kirsch
  • Christopher A Abeare
Article
  • 34 Downloads

Abstract

This study was designed to develop validity cutoffs within the Finger Tapping Test (FTT) using demographically adjusted T-scores, and to compare their classification accuracy to existing cutoffs based on raw scores. Given that FTT performance is known to vary with age, sex, and level of education, failure to correct for these demographic variables poses the risk of elevated false positive rates in examinees who, at the level of raw scores, have inherently lower FTT performance (women, older, and less educated individuals). Data were collected from an archival sample of 100 adult outpatients (MAge = 38.8 years, MEducation = 13.7 years, 56% men) consecutively referred for neuropsychological assessment at an academic medical center in the Midwestern USA after sustaining a traumatic brain injury (TBI). Performance validity was psychometrically defined using the Word Memory Test and two validity composites based on five embedded performance validity indicators. Previously published raw score-based validity cutoffs disproportionately sacrificed sensitivity (.13–.33) for specificity (.98–1.00). Worse yet, they were confounded by sex and education. Newly introduced demographically adjusted cutoffs (T ≤ 33 for the dominant hand, T ≤ 37 for both hands) produced high levels of specificity (.89–.98) and acceptable sensitivity (.36–.55) across criterion measures. Equally importantly, they were robust to injury severity and demographic variables. The present findings provide empirical support for a growing trend of demographically adjusted performance validity cutoffs. They provide a practical and epistemologically superior alternative to raw score cutoffs, while also reducing the potential bias against examinees inherently vulnerable to lower raw score level FTT performance.

Keywords

Finger tapping test Demographically adjusted cutoffs Performance validity Erdodi Index Modality specificity 

Notes

Funding Information

This research was supported by a Collaborative Research Grant from the Faculty of Arts, Humanities, and Social Sciences at the University of Windsor.

Compliance with Ethical Standards

All data collection, storage, and processing were done in compliance with the Helsinki Declaration.

Conflict of Interest

Drs. Erdodi and Abeare are employed by the University of Windsor. In addition to that, they provide forensic consultation and medicolegal assessments, for which they receive financial compensation.

Human and Animal Rights and Informed Consent

Relevant ethical guidelines regulating research involving human participants were followed throughout the project.

References

  1. Abeare, C., Messa, I., Whitfield, C., Zuccato, B., Casey, J., Rykulski, N., & Erdodi, L. (2018a). Performance validity in collegiate football athletes at baseline neurocognitive testing. The Journal of head trauma rehabilitation,  https://doi.org/10.1097/HTR.0000000000000451.
  2. Abeare, C. A., Messa, I., Zuccato, B. G., Merker, B., & Erdodi, L. A. (2018b). Prevalence of invalid performance on baseline testing for sport-related concussion by age and validity indicator. Advanced online publication. JAMA Neurology, 75, 697–703.  https://doi.org/10.1001/jamaneurol.2018.0031.Google Scholar
  3. Allen, L., & Green, P. (1999). CARB and WMT effort test scores in 57 patients with severe traumatic brain injury. Archives of Clinical Neuropsychology, 14(8), 789.Google Scholar
  4. American Congress on Rehabilitation Medicine. (1993). Definition of mild traumatic brain injury. The Journal of Head Trauma Rehabilitation, 8(3), 86–87.Google Scholar
  5. An, K. Y., Kaploun, K., Erdodi, L. A., & Abeare, C. A. (2017). Performance validity in undergraduate research participants: A comparison of failure rates across tests and cutoffs. The Clinical Neuropsychologist, 31(1), 193–206.  https://doi.org/10.1080/13854046.2016.1217046.Google Scholar
  6. An, K. Y., Charles, J., Ali, S., Enache, A., Dhuga, J., & Erdodi, L. A. (2019). Reexamining performance validity cutoffs within the complex ideational material and the Boston naming test–short form using an experimental malingering paradigm. Journal of Clinical and Experimental Neuropsychology, 41(1), 15–25.Google Scholar
  7. Armistead-Jehle, P., & Denney, R. L. (2015). The detection of feigned impairment using the WMT, MSVt, and NV-MSVT. Applied Neuropsychology. Adult, 22(2), 147–155.  https://doi.org/10.1080/23279095.2014.880842.Google Scholar
  8. Arnold, G., Boone, K. B., Lu, P., Dean, A., Wen, J., Nitch, S., & McPhearson, S. (2005). Sensitivity and specificity of finger tapping test scores for the detection of suspect effort. The Clinical Neuropsychologist, 19(1), 105–120.  https://doi.org/10.1080/13854040490888567.Google Scholar
  9. Ashendorf, L., Clark, E. L., & Sugarman, M. A. (2017). Performance validity and processing speed in a VA polytrauma sample. The Clinical Neuropsychologist., 31(5), 857–866.  https://doi.org/10.1080/13854046.2017.1285961.Google Scholar
  10. Axelrod, B. N., Meyers, J. E., & Davis, J. J. (2014). Finger tapping test performance as a measure of performance validity. The Clinical Neuropsychologist, 28(5), 876–888.  https://doi.org/10.1080/13854046.2014.907583.Google Scholar
  11. Babikian, T., Boone, K. B., Lu, P., & Arnold, G. (2006). Sensitivity and specificity of various digit span scores in the detection of suspect effort. The Clinical Neuropsychologist, 20(1), 145–159.Google Scholar
  12. Baker, D. A., Connery, A. K., Kirk, J. W., & Kirkwood, M. W. (2014). Embedded performance validity indicators within the California verbal learning test, Children’s version. The Clinical Neuropsychologist, 28(1), 116–127.Google Scholar
  13. Bauer, L., Yantz, C. L., Ryan, L. M., Warden, D. L., & McCaffrey, R. J. (2005). An examination of the California verbal learning test II to detect incomplete effort in a traumatic brain injury sample. Applied Neuropsychology, 12(4), 202–207.  https://doi.org/10.1207/s15324826an1204_3.Google Scholar
  14. Bigler, E. D. (2012). Symptom validity testing, effort and neuropsychological assessment. Journal of the International Neuropsychological Society, 18, 632–642.  https://doi.org/10.1017/S1355617712000252.Google Scholar
  15. Blaskewitz, N., Merten, T., & Brockhaus, R. (2009). Detection of suboptimal effort with the Rey complex figure test and recognition trial. Applied Neuropsychology, 16, 54–61.Google Scholar
  16. Boone, K. B. (2009). The need for continuous and comprehensive sampling of effort/response bias during neuropsychological examination. The Clinical Neuropsychologist, 23(4), 729–741.  https://doi.org/10.1080/13854040802427803.Google Scholar
  17. Boone, K. B. (2013). Clinical practice of forensic neuropsychology. New York: Guilford.Google Scholar
  18. Bortnik, K. E., Boone, K. B., Marion, S. D., Amano, S., Ziegler, E., Victor, T. L., & Zeller, M. A. (2010). Examination of various WMS-III logical memory scores in the assessment of response bias. The Clinical Neuropsychologist, 24(2), 344–357.  https://doi.org/10.1080/13854040903307268.Google Scholar
  19. Brooks, B. L., & Ploetz, D. M. (2015). Embedded performance validity on the CVLT-C for youth with neurological disorders. Archives of Clinical Neuropsychology, 30, 200–206.Google Scholar
  20. Bush, S. S., Ruff, R. M., Troster, A. I., Barth, J. T., Koffler, S. P., Pliskin, N. H., et al. (2005). Symptom validity assessment: Practice issues and medical necessity (NAN policy and planning committees). Archives of Clinical Neuropsychology, 20, 419–426.Google Scholar
  21. Bush, S. S., Heilbronner, R. L., & Ruff, R. M. (2014). Psychological assessment of symptom and performance validity, response bias, and malingering: Official position of the Association for Scientific Advancement in psychological injury and law. Psychological Injury and Law, 7(3), 197–205.Google Scholar
  22. Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105.Google Scholar
  23. Carone, D. A. (2008). Children with moderate/ severe brain damage/ dysfunction outperform adults with mild-to-no brain damage on the medical symptom validity test. Brain Injury, 22, 960–971.Google Scholar
  24. Chafetz, M. D., Williams, M. A., Ben-Porath, Y. S., Bianchini, K. J., Boone, K. B., Kirkwood, M. W., Larrabee, G. J., & Ord, J. S. (2015). Official position of the American Academy of clinical neuropsychology Social Security Administration policy on validity testing: Guidance and recommendations for change. The Clinical Neuropsychologist, 29(6), 723–740.Google Scholar
  25. Clark, A. L., Amick, M. M., Fortier, C., Millberg, W. P., & McGlinchey, R. E. (2014). Poor performance validity predicts clinical characteristics and cognitive test performance of OEF/OIF/OND veterans in a research setting. The Clinical Neuropsychologist, 28(5), 802–825.Google Scholar
  26. Committee on Psychological Testing, Including Validity Testing, for Social Security Administration Disability Determinations. (2015). Cognitive Tests and Performance Validity Tests. Retrieved from https://www.ncbi.nlm.nih.gov/books/NBK305230/
  27. Conners, K. C. (2004). Conner’s Continuous Performance Test (CPT II). Version 5 for Windows. Technical Guide and Software Manual. North Tonawada: Multi-Health Systems.Google Scholar
  28. Costabile, T., Bilo, L., DeRosa, A., Pane, C., & Sacca, F. (2018). Dissociative identity disorder: Restoration of executive functions after switch from alter to host personality. Psychiatry and Clinical Neurosciences, 72, 189–190.Google Scholar
  29. Cottingham, M. E., Victor, T. L., Boone, K. B., Ziegler, E. A., & Zeller, M. (2014). Apparent effect of type of compensation seeking (disability vs. litigation) on performance validity test scores may be due to other factors. The Clinical Neuropsychologist, 28(6), 1030–1047.  https://doi.org/10.1080/13854046.2014.951397.Google Scholar
  30. Critchfield, E. A., Soble, J. R., Marceaux, J. C., Bain, K. M., Bailey, K. C., et al. (2018). Cognitive impairment does not cause invalid performance: Analyzing performance patterns among cognitively unimpaired, impaired, and noncredible participants across six performance validity tests. The Clinical Neuropsychologist,  https://doi.org/10.1080/13854046.2018.1508615.
  31. Curtis, K. L., Greve, K. W., & Bianchini, K. J. (2009). The Wechsler adult intelligence scale-III and malingering in traumatic brain injury. Assessment, 16(4), 401–414.Google Scholar
  32. Davis, J. J., & Millis, S. R. (2014). Examination of performance validity test failure in relation to number of tests administered. The Clinical Neuropsychologist, 28(2), 199–214.  https://doi.org/10.1080/13854046.2014.884633.Google Scholar
  33. Delis, D. C., Kramer, J. H., Kaplan, E., & Ober, B. (2000). The California Verbal Learning Test (Second ed.). San Antonio: The Psychological Corporation.Google Scholar
  34. Donders, J. (2005). Performance on the test of memory malingering in a mixed pediatric sample. Child Neuropsychology, 11(2), 221–227.Google Scholar
  35. Donders, J., & Strong, C. H. (2011). Embedded effort indicators on the California verbal learning test – Second edition (CVLT-II): An attempted cross-validation. The Clinical Neuropsychologist, 25, 173–184.Google Scholar
  36. Donders, J., & Strong, C. H. (2013). Does Green’s word memory test really measure memory? Journal of Clinical and Experimental Neuropsychology, 35(8), 827–834.Google Scholar
  37. Donders, J., & Strong, C. H. (2015). Clinical utility of the Wechsler adult intelligence scale – Fourth edition after traumatic brain injury. Assessment, 22(1), 17–22.Google Scholar
  38. Dunn, L. M., & Dunn, D. M. (2007). Peabody Picture Vocabulary Test (Fourth ed.). San Antonio: Pearson.Google Scholar
  39. Erdodi, L. A. (2019). Aggregating validity indicators: The salience of domain specificity and the indeterminate range in multivariate models of performance validity assessment. Applied Neuropsychology. Adult, 26(2), 155–172.  https://doi.org/10.1080/23279095.2017.1384925.Google Scholar
  40. Erdodi, L. A., & Lichtenstein, J. D. (2017). Invalid before impaired: An emerging paradox of embedded validity indicators. The Clinical Neuropsychologist, 31(6–7), 1029–1046.  https://doi.org/10.1080/13854046.2017.1323119.Google Scholar
  41. Erdodi, L. A., & Lichtenstein, J. D. (2019). Information processing speed tests as PVTs. In K. B. Boone (Ed.), Assessment of feigned cognitive impairment. A neuropsychological perspective. New York: Guilford.Google Scholar
  42. Erdodi, L. A., & Rai, J. K. (2017). A single error is one too many: Examining alternative cutoffs on trial 2 of the TOMM. Brain Injury, 31(10), 1362–1368.  https://doi.org/10.1080/02699052.2017.1332386.Google Scholar
  43. Erdodi, L. A., & Roth, R. M. (2017). Low scores on BDAE complex ideational material are associated with invalid performance in adults without aphasia. Applied Neuropsychology. Adult, 24(3), 264–274.  https://doi.org/10.1080/23279095.2017.1298600.Google Scholar
  44. Erdodi, L. A., Kirsch, N. L., Lajiness-O’Neill, R., Vingilis, E., & Medoff, B. (2014a). Comparing the recognition memory test and the word choice test in a mixed clinical sample: Are they equivalent? Psychological Injury and Law, 7(3), 255–263.Google Scholar
  45. Erdodi, L. A., Roth, R. M., Kirsch, N. L., Lajiness-O’Neill, R., & Medoff, B. (2014b). Aggregating validity indicators embedded in Conners’ CPT-II outperforms individual cutoffs at separating valid from invalid performance in adults with traumatic brain injury. Archives of Clinical Neuropsychology, 29(5), 456–466.  https://doi.org/10.1093/arclin/acu026.Google Scholar
  46. Erdodi, L. A., Tyson, B. T., Abeare, C. A., Lichtenstein, J. D., Pelletier, C. L., Rai, J. K., & Roth, R. M. (2016). The BDAE complex ideational material – A measure of receptive language or performance validity? Psychological Injury and Law, 9, 112–120.  https://doi.org/10.1007/s12207-016-9254-6.Google Scholar
  47. Erdodi, L. A., Abeare, C. A., Lichtenstein, J. D., Tyson, B. T., Kucharski, B., Zuccato, B. G., & Roth, R. M. (2017a). WAIS-IV processing speed scores as measures of non-credible responding – The third generation of embedded performance validity indicators. Psychological Assessment, 29(2), 148–157.  https://doi.org/10.1037/pas0000319.Google Scholar
  48. Erdodi, L. A., Lichtenstein, J. D., Rai, J. K., & Flaro, L. (2017b). Embedded validity indicators in Conners’ CPT-II: Do adult cutoffs work the same way in children? Applied Neuropsychology: Child, 6(4), 335–363.  https://doi.org/10.1080/21622965.2016.1198908.Google Scholar
  49. Erdodi, L. A., Seke, K. R., Shahein, A., Tyson, B. T., Sagar, S., & Roth, R. M. (2017c). Low scores on the grooved pegboard test are associated with invalid responding and psychiatric symptoms. Psychology & Neuroscience, 10(3), 325–344.  https://doi.org/10.1037/pne0000103.Google Scholar
  50. Erdodi, L. A., Abeare, C. A., Medoff, B., Seke, K. R., Sagar, S., & Kirsch, N. L.(2018a). A single error is one too many: The Forced Choice Recognition trial on the CVLT-II as a measure of performance validity in adults with TBI. Archives of Clinical Neuropsychology, 33(7), 845–860.  https://doi.org/10.1093/arclin/acx110.
  51. Erdodi, L. A., Dunn, A. G., Seke, K. R., Charron, C., McDermott, A., Enache, A., Maytham, C., & Hurtubise, J. L. (2018b). The Boston naming test as a measure of performance validity. Psychological Injury and Law, 11(1), 1–8.Google Scholar
  52. Erdodi, L. A., Hurtubise, J. L., Charron, C., Dunn, A., Enache, A., McDermott, A., & Hirst, R. (2018c). The D-KEFS trails as performance validity tests. Psychological Assessment, 30(8), 1081–1095.Google Scholar
  53. Erdodi, L. A., Kirsch, N. L., Sabelli, A. G., & Abeare, C. A. (2018d). The grooved pegboard test as a validity indicator – A study on psychogenic interference as a confound in performance validity research. Psychological Injury and Law, 11(4), 307–324.  https://doi.org/10.1007/s12207-018-9337-7.Google Scholar
  54. Erdodi, L. A., Pelletier, C. L., & Roth, R. M. (2018e). Elevations on select Conners’ CPT-II scales indicate noncredible responding in adults with traumatic brain injury. Applied Neuropsychology. Adult, 25(1), 19–28.  https://doi.org/10.1080/23279095.2016.1232262.Google Scholar
  55. Erdodi, L. A., Tyson, B. T., Abeare, C. A., Zuccato, B. G., Rai, J. K., Seke, K. R., Sagar, S., & Roth, R. M. (2018f). Utility of critical items within the recognition memory test and word choice test. Applied Neuropsychology. Adult, 25(4), 327–339.  https://doi.org/10.1080/23279095.2017.1298600.Google Scholar
  56. Etherton, J. L., Bianchini, K. J., Heinly, M. T., & Greve, K. W. (2006). Pain, malingering, and performance on the WAIS-III processing speed index. Journal of Clinical and Experimental Neuropsychology, 28(7), 1218–1237.  https://doi.org/10.1080/13803390500346595.Google Scholar
  57. Gladsjo, J. A., Schuman, C. C., Evans, J. D., Peavy, G. M., Miller, S. W., & Heaton, R. K. (1999). Norms for letter and category fluency: Demographic corrections for age, education, and ethnicity. Assessment, 6(2), 147–178.Google Scholar
  58. Green, P. (2003). Green’s word memory test. Edmonton: Green’s Publishing.Google Scholar
  59. Green, P., & Flaro, L. (2003). Word memory test performance in children. Child Neuropsychology, 9(3), 189–207.Google Scholar
  60. Green, P., Iverson, G. L., & Allen, L. (1999). Detecting malingering in head injury litigation with the word memory test. Brain Injury, 13(10), 813–819.  https://doi.org/10.1080/026990599121205.Google Scholar
  61. Green, P., Flaro, L., & Courtney, J. (2009). Examining false positives on the word memory test in adults with mild traumatic brain injury. Brain Injury, 23, 741–750.Google Scholar
  62. Greiffenstein, M. F., Baker, W. J., & Gola, T. (1994). Validation of malingered amnesia measures with a large clinical sample. Psychological Assessment, 6(3), 218–224.Google Scholar
  63. Greiffenstein, M. F., Baker, W. J., & Gola, T. (1996). Motor dysfunction profiles in traumatic brain injury and post-concussion syndrome. Journal of the International Neuropsychological Society, 2(6), 477–485.Google Scholar
  64. Greve, K. W., Bianchini, K. J., & Doane, B. M. (2006). Classification accuracy of the test of memory malingering in traumatic brain injury: Results of a known-group analysis. Journal of Clinical and Experimental Neuropsychology, 28(7), 1176–1190.Google Scholar
  65. Greve, K. W., Etherton, J. L., Ord, J., Bianchini, K. J., & Curtis, K. L. (2009). Detecting malingered pain-related disability: Classification accuracy of the test of memory malingering. The Clinical Neuropsychologist, 16(2), 179–191.Google Scholar
  66. Grimes, D. A., & Schulz, K. F. (2005). Refining clinical diagnosis with likelihood ratios. The Lancet, 365(9469), 1500–1505.Google Scholar
  67. Guilmette, T.J. (2013). The role of clinical judgment in symptom validity testing. In D. A. Carone ∓S. S. Bush (Eds.), Mild traumatic injury: Symptom validity assessment and malingering (pp. 31–43). New York, NY: Springer.Google Scholar
  68. Haaland, K. Y., Temkin, N., Randahl, G., & Dikmen, S. (1994). Recovery of simple motor skills after head injury. Journal of Clinical and Experimental Neuropsychology, 16(3), 448–456.Google Scholar
  69. Halstead, W. (1947). Brain and intelligence. A quantitative study of the frontal lobes. Chicago: University of Chicago Press.Google Scholar
  70. Heaton, R. K., Smith, H. H., Lehman, R. A., & Vogt, A. T. (1978). Prospects for faking believable deficits on neuropsychological testing. Journal of Consulting and Clinical Psychology, 46(5), 892–900.Google Scholar
  71. Heaton, R. K., Grant, I., & Matthews, C. G. (1991). Comprehensive norms for an expanded Halstead-Reitan Battery. Odessa: Psychological Assessment Resources.Google Scholar
  72. Heaton, R. K., Chelune, G. J., Talley, J. L., Kay, G. G., & Curtis, G. (1993). Wisconsin Card Sorting Test (WCST) manual revised and expanded. Odessa: Psychological Assessment Resources.Google Scholar
  73. Heaton, R. K., Miller, S. W., Taylor, M. J., & Grant, I. (2004). Revised comprehensive norms for an expanded Halstead-Reitan battery: Demographically adjusted neuropsychological norms for African American and Caucasian adults. Lutz: Psychological Assessment Resources.Google Scholar
  74. Heilbronner, R. L., Sweet, J. J., Morgan, J. E., Larrabee, G. J., Millis, S. R., & Conference Participants 1. (2009). American Academy of clinical neuropsychology consensus conference statement on the neuropsychological assessment of effort, response bias, and malingering. The Clinical Neuropsychologist, 23(7), 1093–1129.Google Scholar
  75. Henry, G. K., Helbronner, R. L., Suhr, J., Gornbein, J., Wagner, E., & Drane, D. L. (2018). Illness perceptions predict cognitive performance validity. Journal of the International Neuropsychological Society, 24, 1–11.Google Scholar
  76. Hill, A. B. (1965). The environment and disease: Association or causation? Proceedings of the Royal Society of Medicine, 58, 295–300.Google Scholar
  77. Homann, C. N., Quehenberger, F., Petrovic, K., Hartung, H. P., Ruzicka, E., Homann, B., et al. (2003). Influence of age, gender, education and dexterity on upper limb motor performance in parkinsonian patients and healthy controls. Journal of Neural Transmission, 110, 885–897.  https://doi.org/10.1007/s00702-003-00097.Google Scholar
  78. Hosmer, D. W., & Lemeshow, S. (2000). Applied logistic regression (2nd ed.). New York: Wiley.Google Scholar
  79. Inman, T. H., & Berry, D. T. R. (2002). Cross-validation of indicators of malingering: A comparison of nine neuropsychological tests, four tests of malingering, and behavioral observations. Archives of Clinical Neuropsychology, 17, 1–23.Google Scholar
  80. Iverson, G., Green, P., & Gervais, R. (1999). Using the word memory test to detect biased responding in head injury litigation. Journal of Cognitive Rehabilitation, 17(2), 4–8.Google Scholar
  81. Jones, A. (2013). Test of memory malingering: Cutoff scores for psychometrically defined malingering groups in a military sample. The Clinical Neuropsychologist, 27(6), 1043–1059.Google Scholar
  82. Kalfon, T. B., Gal, G., Shorer, R., & Ablin, J. N. (2016). Cognitive functioning in fibromyalgia: The central role of effort. Journal of Psychosomatic Research, 87, 30–36.Google Scholar
  83. Kim, N., Boone, K. B., Victor, T., Lu, P., Keatinge, C., & Mitchell, C. (2010). Sensitivity and specificity of a digit symbol recognition trial in the identification of response bias. Archives of Clinical Neuropsychology, 25(5), 420–428.  https://doi.org/10.1903/arclin/acq040.Google Scholar
  84. Kirkwood, M. W., Hargrave, D. D., & Kirk, J. W. (2011). The value of the WISC-IV digit span subtest in detecting noncredible effort performance during pediatric neuropsychological examinations. Archives of Clinical Neuropsychology, 26, 377–384.Google Scholar
  85. Kulas, J. F., Axelrod, B. N., & Rinaldi, A. R. (2014). Cross-validation of supplemental test of memory malingering scores as performance validity measures. Psychological Injury and Law, 7(3), 236–244.Google Scholar
  86. Lange, R. T., Iverson, G. L., Brickell, T. A., Staver, T., Pancholi, S., Bhagwat, A., & French, L. M. (2013). Clinical utility of the Conners’ continuous performance test-II to detect poor effort in U.S. military personnel following traumatic brain injury. Psychological Assessment, 25(2), 339–352.Google Scholar
  87. Larrabee, G. J. (2003). Detection of malingering using atypical performance patterns on standard neuropsychological tests. The Clinical Neuropsychologist, 17, 410–425.  https://doi.org/10.1076/clin.17.3.410.18089.Google Scholar
  88. Larrabee, G. J. (2008). Aggregation across multiple indicators improves the detection of malingering: Relationship to likelihood ratios. The Clinical Neuropsychologist, 22, 410–425.  https://doi.org/10.1080/13854040701494987.Google Scholar
  89. Larrabee, G. J. (2012). Assessment of malingering. In G. J. Larrabee (Ed.), Forensic neuropsychology: A scientific approach (Second ed., pp. 116–159). New York: Oxford University Press.Google Scholar
  90. Larrabee, G. J. (2014). Minimizing false positive errors with multiple performance validity tests: Response to Bilder, sugar, and Hellemann. The Clinical Neuropsychologist, 28(8), 1230–1242.Google Scholar
  91. Lichtenstein, J. D., Erdodi, L. A., & Linnea, K. S. (2017). Introducing a forced-choice recognition task to the California verbal learning test – Children’s version. Child Neuropsychology, 23(3), 284–299.  https://doi.org/10.1080/09297049.2015.1135422.Google Scholar
  92. Lichtenstein, J. D., Erdodi, L. A., Rai, J. K., Mazur-Mosiewicz, A., & Flaro, L. (2018a). Wisconsin card sorting test embedded validity indicators developed for adults can be extended to children. Child Neuropsychology, 24(2), 247–260.  https://doi.org/10.1080/09297049.2016.1259402.Google Scholar
  93. Lichtenstein, J. D., Holcomb, M., & Erdodi, L. A. (2018b). One-minute PVT: Further evidence for the utility of the California verbal learning test—Children’s version forced choice recognition trial. Journal of Pediatric Neuropsychology, 4(3–4), 94–104.Google Scholar
  94. Lichtenstein, J. D., Flaro, L., Baldwin, F., Rai, J. K., & Erdodi, L. A. (2019). Further evidence for embedded validity tests in children within the Conners’ continuous performance test – Second edition. Developmental Neuropsychology, 44(2), 159–171.  https://doi.org/10.1080/87565641.2019.1565536.Google Scholar
  95. Lichtenstein, J. D., Greenacre, M. K., Cutler, L., Abeare, K., Baker, S. D., Kent, K., J., Ali, S., & Erdodi, L. A. (2019). Geographic variation and instrumentation artifacts:in search of confounds in performance validity assessment in adults with mild TBI. Advance online publication. Psychological Injury and Law,  https://doi.org/10.1007/s12207-019-0935.
  96. Lippa, S. M., Agbayani, K. A., Hawes, S., Jokic, E., & Caroselli, J. S. (2014). Effort in acute traumatic brain injury: Considering more than Pass/Fail. Rehabilitation Psychology, 59(3), 306–312.Google Scholar
  97. Locke, D. E., Smigielski, J. S., Powell, M. R., & Stevens, S. R. (2008). Effort issues in post-acute outpatient acquired brain injury rehabilitation seekers. NeuroRehabilitation, 23(3), 273–281.Google Scholar
  98. Lu, P. H., Boone, K. B., Cozolino, L., & Mitchell, C. (2003). Effectiveness of the Rey-Osterrieth complex figure test and the Meyers and Meyers recognition trial in the detection of suspect effort. The Clinical Neuropsychologist, 17(3), 426–440.  https://doi.org/10.1076/clin.17.3.426.18083.Google Scholar
  99. Matthews, C. G., & Klove, H. (1964). Instruction manual for the adult neuropsychology test battery (p. 36). Madison: University of Wisconsin Medical School.Google Scholar
  100. Miele, A. S., Gunner, J. H., Lynch, J. K., & McCaffrey, R. J. (2012). Are embedded validity indices equivalent to free-standing symptom validity tests? Achieves of Clinical Neuropsychology, 27(1), 10–22.  https://doi.org/10.1093/arclin/acr084.Google Scholar
  101. Mittenberg, W., Rotholc, A., Russell, E., & Heilbronner, R. (1996). Identification of malingered head injury on the Halstead-Reitan battery. Archives of Clinical Neuropsychology, 11, 271–281.Google Scholar
  102. Newcombe, F. (1969). Missile wounds of the brain. London: Oxford University Press.Google Scholar
  103. Odland, A. P., Lammy, A. B., Martin, P. K., Grote, C. L., & Mittenberg, W. (2015). Advanced administration and interpretation of multiple validity tests. Psychological Injury and Law, 8, 46–63.Google Scholar
  104. Ord, J. S., Boettcher, A. C., Greve, K. J., & Bianchini, K. J. (2010). Detection of malingering in mild traumatic brain injury with the Conners’ continuous performance test-II. Journal of Clinical and Experimental Neuropsychology, 32(4), 380–387.Google Scholar
  105. Pearson. (2009). Advanced Clinical Solutions for the WAIS-IV and WMS-IV – Technical Manual. San Antonio: Author.Google Scholar
  106. Persinger, V. C., Whiteside, D. M., Bobova, L., Saigal, S. D., Vannucci, M. J., & Basso, M. R. (2018). Using the California verbal learning test, second edition as an embedded performance validity measure among individuals with TBI and individuals with psychiatric disorders. Advance online publication. The Clinical Neuropsychologist, 32(6), 1039–1053.  https://doi.org/10.1080/13854046.2017.1419507.Google Scholar
  107. Prigatano, G. P., & Borgaro, S. R. (2003). Qualitative features of finger movement during the Halstead finger oscillation test following traumatic brain injury. Journal of the International Neuropsychological Society, 9(1), 128–133.Google Scholar
  108. Proto, D. A., Pastorek, N. J., Miller, B. I., Romesser, J. M., Sim, A. H., & Linck, J. M. (2014). The dangers of failing one or more performance validity tests in individuals claiming mild traumatic brain injury-related postconcussive symptoms. Archives of Clinical Neuropsychology, 29, 614–624.Google Scholar
  109. Rai, J. K., & Erdodi, L. A. (2019). The impact of criterion measures on the classification accuracy of TOMM-1. Applied Neuropsychology: Adult,   https://doi.org/10.1080/23279095.2019.161.1613994.
  110. Rai, J., An, K. Y., Charles, J., Ali, S., & Erdodi, L. A. (2019). Introducing a forced choice recognition trial to the Rey Complex Figure Test. Psychology and Neuroscience,  https://doi.org/10.1037/pne0000175.
  111. Rapport, L. J., Farchione, T. J., Coleman, R. D., & Axelrod, B. N. (1998). Effects of coaching on malingered motor function profiles. Journal of Clinical and Experimental Neuropsychology, 20(1), 89–97.  https://doi.org/10.1076/jcen.20.1.89.1488.Google Scholar
  112. Reedy, S. D., Boone, K. B., Cottingham, M. E., Glaser, D. F., Lu, P. H., Victor, T. L., Ziegler, E. A., Zeller, M. A., & Wright, M. J. (2013). Cross validation of the Lu and colleagues (2003) Rey-Osterrieth complex figure test effort equation in a large known-group sample. Archives of Clinical Neuropsychology, 28, 30–37.  https://doi.org/10.1093/arclin/acs106.Google Scholar
  113. Reese, C. S., Suhr, J. A., & Riddle, T. L. (2012). Exploration of malingering indices in the Wechsler adult intelligence scale – Fourth edition digit span subtest. Archives of Clinical Neuropsychology, 27, 176–181.Google Scholar
  114. Reitan, R. M. (1955). The relation of the trail making test to organic brain damage. Journal of Consulting Psychology, 19, 393–394.Google Scholar
  115. Reitan, R. M. (1958). The validity of the trail making test as an indicator of organic brain damage. Perceptual and Motor Skills, 8, 271–276.Google Scholar
  116. Reitan, R. M. (1969). Manual for administration of neuropsychological test batteries for adults and children. Indianapolis, IN.Google Scholar
  117. Reitan, R. M., & Wolfson, D. (1985). The Halstead-Reitan Neuropsychological Test Battery: Theory and interpretation. Tucson: Neuropsychology Press.Google Scholar
  118. Ruff, R. M., & Parker, S. B. (1993). Gender-and age-specific changes in motor speed and eye-hand coordination in adults: Normative values for the finger tapping and grooved pegboard tests. Perceptual and Motor Skills, 76(3), 1219–1230.Google Scholar
  119. Schatz, P. (2011). Encyclopedia of neuropsychology: Finger tapping test. New York: Springer New York.Google Scholar
  120. Schutte, C., Axelrod, B. N., & Montoya, E. (2015). Making sure neuropsychological data are meaningful: Use of performance validity testing in medicolegal and clinical contexts. Psychological Injury and Law, 8(2), 100–105.Google Scholar
  121. Schwartz, E. S., Erdodi, L., Rodriguez, N., Jyotsna, J. G., Curtain, J. R., Flashman, L. A., & Roth, R. M. (2016). CVLT-II forced choice recognition trial as an embedded validity indicator: A systematic review of the evidence. Journal of the International Neuropsychological Society, 22(8), 851–858.  https://doi.org/10.1017/S1355617716000746.Google Scholar
  122. Shimoyama, I., Yoshida, A., Yugeta, T., Saeki, N., Hayashi, F., Yoshizaki, H., & Shimizu, R. (2012). Rapid finger-tapping test and aging. International Medical Journal, 19(2), 138–140.Google Scholar
  123. Shura, R. D., Miskey, H. M., Rowland, J. A., Yoash-Gatz, R. E., & Denning, J. H. (2016). Embedded performance validity measures with postdeployment veterans: Cross-validation and efficiency with multiple measures. Applied Neuropsychology. Adult, 23, 94–104.  https://doi.org/10.1080/23279095.2015.1014556.Google Scholar
  124. Slick, D. J., Sherman, E. M. S., & Iverson, G. L. (1999). Diagnostic criteria for malingered neurocognitive dysfunction: Proposed standards for clinical practice and research. The Clinical Neuropsychologist, 13(4), 545–561.Google Scholar
  125. Strauss, E., Sherman, E. M. S., & Spreen, O. (2006). A compendium of neuropsychological tests. New York: Oxford University Press.Google Scholar
  126. Suhr, J. A. (2003). Neuropsychological impairment in fibromyalgia. Relation to depression, fatigue, and pain. Journal of Psychosomatic Research, 55, 321–329.Google Scholar
  127. Suhr, J., & Spickard, B. (2012). Pain-related fear is associated with cognitive task avoidance: Exploration of the cogniphobia construct in a recurrent headache sample. The Clinical Neuropsychologist, 26(7), 1128–1141.  https://doi.org/10.1080/13854046.2012.713121.Google Scholar
  128. Sussman, Z. W., Peterson, R. L., Connery, A. K., Baker, D. A., & Kirkwood, M. W. (2019). Utility of Matrix Reasoning as an embedded performance validity indicator in pediatric mild traumatic brain injury. Applied Neuropsychology: Child, 8(1), 70–75.  https://doi.org/10.1080/21622965.2017.1382359.Google Scholar
  129. Sweet, J. J., Goldman, D. J., & Guidotti Breting, L. M. (2013). Traumatic brain injury: Guidance in a forensic context from outcome, dose response, and response bias research. Behavioural Sciences and the Law, 31, 756–778.Google Scholar
  130. Tan, J. E., Slick, D. J., Strauss, E., & Hultsch, D. F. (2002). How'd they do it? Malingering strategies on symptom validity tests. The Clinical Neuropsychologist, 16(4), 495–505.  https://doi.org/10.1076/clin.16.4.495.13909.Google Scholar
  131. Trueblood, W. (1994). Qualitative and quantitative characteristics of malingered and other invalid WAIS-R and clinical memory data. Journal of Clinical and Experimental Neuropsychology, 14(4), 697–607.  https://doi.org/10.1080/01688639408402671.Google Scholar
  132. Tyson, B. T., Baker, S., Greenacre, M., Kent, K. J., Lichtenstein, J. D., Sabelli, A., & Erdodi, L. A. (2018). Differentiating epilepsy from psychogenic nonepileptic seizures using neuropsychological test data. Epilepsy & Behavior, 87, 39–45.Google Scholar
  133. Wechsler, D. (2008). Wechsler Adult Intelligence Test — Fourth Edition (WAIS-IV). San Antonio: Pearson.Google Scholar
  134. Wechsler, D. (2009). Wechsler Memory Scale — Fourth Edition (WMS–IV). San Antonio: Pearson.Google Scholar
  135. Wilkinson, G. S., & Robertson, G. J. (2006). Wide range achievement test 4. Lutz: Psychological Assessment Resources, Inc.Google Scholar
  136. Williamson, D. J., Holsman, M., Chaytor, N., Miller, J. W., & Drane, D. L. (2012). Abuse, not financial incentive, predicts non-credible cognitive performance in patients with psychogenic non-epileptic seizures. The Clinical Neuropsychologist, 26(4), 588–598.Google Scholar
  137. Wolfe, P. L., Millis, S. R., Hanks, R., Fichtenberg, N., Larrabee, G. J., & Sweet, J. J. (2010). Effort indicators within the California Verbal Learning Test-II (CVLT-II). The Clinical Neuropsychologist, 24(1), 153–168.Google Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Laszlo A Erdodi
    • 1
    Email author
  • Brian Taylor
    • 2
  • Alana G Sabelli
    • 2
  • Malayna Malleck
    • 1
  • Ned L Kirsch
    • 3
  • Christopher A Abeare
    • 1
  1. 1.Department of Psychology, Neuropsychology TrackUniversity of WindsorWindsorCanada
  2. 2.Behaviour-Cognition-Neuroscience ProgramUniversity of WindsorWindsorCanada
  3. 3.Department of Physical Medicine and Rehabilitation, Adult Outpatient Neurehabilitation ProgramUniversity of MichiganAnn ArborUSA

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