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. Author manuscript; available in PMC: 2020 Oct 14.
Published in final edited form as: J Int Neuropsychol Soc. 2020 May 27;26(9):932–938. doi: 10.1017/S1355617720000351

Patterns of Cognitive Test Scores and Symptom Complaints in Persons with TBI Who Failed Performance Validity Testing

Mark Sherer 1, Angelle M Sander 2,1, Jennie Ponsford 3, Leia Vos 4,5, Julia MP Poritz 6, Esther Ngan 7, Luis Leon Novelo 7
PMCID: PMC7554049  NIHMSID: NIHMS1578595  PMID: 32456725

Abstract

Objective:

Determine clinically meaningful subgroups of persons with traumatic brain injury (TBI) who have failed performance validity testing.

Method:

Study participants were selected from a cohort of 674 participants with definitive medical evidence of TBI. Participants were those who failed performance validity testing (the Word Memory Test, using the standard cut-offs). Participants were administered cognitive tests and self-report questionnaires. Test and questionnaire results were summarized as 12 dimension scores. Cluster analysis using the k means method was performed.

Results:

Cluster analysis for the 143 retained participants indicated 3 subgroups. These subgroups differed on patterns of scores. Subgroup 1 was impaired for memory and had no excessive complaints. Subgroup 2 had impaired memory and processing speed as well as concern regarding cognition function. Subgroup 3 showed impairment on all cognitive tests and excess complaints in multiple areas.

Conclusions:

These results provide a preliminary basis for improved understanding of poor performance validity.

Keywords: Performance Validity, Traumatic Brain Injury, Cognitive Tests, Self-report Questionnaires, Subgroups


Inclusion of performance validity tests (PVTs) as part of neuropsychological evaluations is now the standard of care in clinical neuropsychology (Bush et al., 2005; Heilbronner et al., 2009; Larrabee, 2012). These measures supplement standard cognitive tests by providing an indication of the extent to which the respondent gave a full effort to obtain valid scores. Failed performance validity testing generally indicates that the respondent did not give a full effort on cognitive testing. Note that failed performance validity is not synonymous with malingering as the latter requires the “presence of a substantial external incentive.” (Slick, Sherman, & Iverson, 1999). While PVTs are most relevant to objective cognitive testing, persons who fail PVTs may report excessive complaints on self-report measures (Lippa, Pastorek, Romesser, et al., 2014).

Researchers have identified factors that may influence PVT performance. Such factors include malingering, somatoform disorder, psychological distress, perceived unfairness of the evaluation, boredom, and inadequate language proficiency among others (Bashem, Rapport, Miller, et al., 2014; Greher & Wodushek, 2017; Lippa, 2018). Henry et al. (2018) found that patient health beliefs were associated with validity test failure. Patients who endorsed beliefs that cognitive effort makes symptoms worse were more likely to show poor performance validity. Patients who endorsed beliefs that symptoms are due to an illness or injury as opposed to being normal experiences were also more likely to show poor performance validity. Thus, failure on PVTs is complex and different factors may result in a range of patterns of results (Chafetz, Williams, Ben-Porath, et al., 2015).

In a treatment context, the clinician has ongoing responsibility for the patient even if the patient shows poor performance validity. Some persons with clear medical documentation of moderate or severe traumatic brain injury (TBI) fail PVTs. Some of these individuals have true neurocognitive deficits (Larrabee, 2014) that may contribute to poor performance validity. Dismissal of the need for treatment in such cases can be deleterious; yet, it can be challenging to develop an appropriate treatment plan. In many cases, persons without true cognitive impairment may be experiencing emotional distress related to an injury. Of course, in some cases, persons referred for treatment may simply be malingering for secondary gain. Thus, the interpretation of failure on PVT tests can be complex, and the interaction of cognitive impairment, emotional distress, and motivational factors must be considered.

Investigations of patterns of cognitive test results indicate that persons who show invalid performance have cognitive test results that are distinct from persons who give valid effort (Frazier, Youngstrom, Naugle, et al., 2007). Also, as found by Lippa et al. (2014), persons with invalid performance on cognitive tests report more complaints on self-report measures. These findings suggest that there may be different patterns of cognitive test scores and self-report among persons with invalid performance.

In our previous work (Sherer, Sander, Nick, et al., 2015; Sherer, Nick, Sander, et al., 2017; Sherer, Ponsford, Hicks, et al., 2017), we identified 12 dimensions of signs and symptoms of TBI that can be derived from the 18 tests and questionnaires. The combinations of test scores and questionnaire results that composed each dimension are described in the Method section. Cluster analysis of the 12 dimension scores for 504 persons with TBI identified 5 subgroups (Sherer, Nick, et al., 2017). Scores on the 12 dimensions were plotted to generate profiles of TBI subgroups. These 5 subgroups differed on cognitive performance, subjective complaints, environmental supports, and performance validity. Almost all persons with failed performance validity were clustered in the same subgroup so that it was not possible to examine patterns of dimension scores within subgroups with invalid performance.

Morin and Axelrod (2017) examined sub-classes (subgroups) of a large cohort of participants who were administered both cognitive tests and measures of emotional functioning and personality. Four subgroups were identified, with members of one subgroup generally showing invalid performance, markedly impaired cognitive performance, and numerous emotional complaints. The three other subgroups had low rates of poor performance validity with less extreme scores on cognitive tests and fewer emotional complaints. As with the Sherer et al. (2017) study, this analysis did not reveal subgroups of persons with invalid performance.

The present investigation sought to extend prior findings by identifying subgroups of persons who showed poor performance validity. We carried out this aim by studying a cohort of persons with TBI who failed performance validity testing when administered a battery of cognitive tests, self-report measures, and scales assessing environmental supports. We hypothesized that clinically meaningful subgroups with distinct patterns of test and questionnaire performance could be identified. We expected that the clinical profiles of these subgroups would have implications for clinical management.

Method

Participants

This study is a secondary analysis of a dataset originally developed for a study that identified dimensions of objective cognitive test scores and self-reported cognitive, emotional, and physical symptoms as well as environmental supports. (Sherer, et al., 2015; Sherer, Nick, et al., 2017) Participants in the original studies were recruited at rehabilitation centers in Houston, Birmingham, and Detroit in the U.S. as well as, Melbourne, Australia (Sherer, Ponsford, et al., 2017). This research was carried out in accord with all relevant human subjects’ protection guidelines including the Helsinki Declaration. The research was reviewed and approved by ethics committees at all participating sites including approval by the Baylor College of Medicine IRB at the primary study site.

Participants who were included for study: (a) had definitive, medical documentation of TBI occurring greater than 6 months prior to assessment, (b) were 18 to 64 years old, (3) had capacity to give informed consent, and (d) had ability to complete study measures in English. Diagnosis of TBI was based on history of head trauma with one or more of (a) observed loss of consciousness, (b) post-traumatic amnesia, and (c) trauma related findings on CT scan. Persons with a pre-existing medical or psychiatric condition that would affect performance on the assessment were excluded from study. For this investigation, only those persons who failed performance validity testing were retained.

Procedures

For the parent study for this secondary analysis, medical and research records were examined for demographic (age, education, race/ethnicity) and injury characteristics (PTA, length of stay, first available GCS). Participants completed 36 cognitive tests and self-report questions. Using data reduction techniques and cluster analyses, 12 dimensions of participant experience after TBI were derived from 18 measures. These dimensions and the tests/questionnaires that defined them were: (1) Memory – Wechsler Adult Intelligence Scale – IV Letter-Number Sequencing (Wechsler, 2008), Rey Auditory Verbal Learning Test total words for learning trials 1–5 (Rey, 1958), (2) Cognitive Processing Speed – Trail Making Test Part A (Reitan & Wolfson, 1985), Wechsler Adult Intelligence Scale – IV Coding (Wechsler, 2008), (3) Verbal Fluency – FAS (Gladsjo et al., 1999), (4) Self-reported Cognitive Symptoms – Traumatic Brain Injury-Quality of Life (TBI-QOL; Tulsky et al., 2016) Cognition-General Concerns, (5) Independence and Self-esteem – TBI-QOL Self-evaluation, TBI-QOL Independence, (6) Resilience – TBI-QOL Resilience, (7) Emotional Distress – TBI-QOL Anxiety, TBI-QOL Emotional and Behavioral Dyscontrol, (8) Postconcussive Symptoms – Neurobehavioral Symptom Inventory (Cicerone & Kalmar, 1995), (9) Physical Symptoms – TBI-QOL Headache, TBI-QOL Pain Interference, (10) Physical Functioning – TBI-QOL Upper Extremity, (11) Economic and Family Support – Economic Quality of Life (Tulsky et al., 2015), Family Assessment Device General Functioning (Epstein, Baldwin, & Bishop, 1983), (12) Performance Validity – Word Memory Test (Green, 2007). A more detailed description of data extracted from records, cognitive tests, questionnaires, and the performance validity test can be obtained by referring to Sherer, Sander, Nick, et al. (2015).

For neuropsychological tests, raw scores were converted to standardized scores utilizing adjustment for age, education, sex, and race/ethnicity as available in the WAIS-IV (Wechsler, 2008), Heaton, Miller, Taylor, and Grant (2004), and Schmidt (1996) norm sets. For the TBI-QOL, look-up tables were used to covert raw scores to T-scores (Tulsky et al., 2016). The reference sample for TBI-QOL measures was composed of persons with TBI. A similar look-up table was used for the Economic Quality of Life scale. Raw scores were used for the Neurobehavioral Symptom Inventory and the Family Assessment Device. An index of performance validity was calculated by averaging the scores from the three easy subtests of the Word Memory Test as recommended by Green (2007). Persons retained for this investigation were those who “failed” the Word Memory Test based on standard cutoffs.

Statistical Analysis

Given the similarity in results with regard to demographic and injury characteristics as well as subgroup profiles shown in an earlier investigation (Sherer, Ponsford, et al., 2017), the US and Australian samples were combined. Dimension scores from the combined sample were submitted to K-means cluster analysis with Euclidean distance. The number of clusters was selected using both variance ratio criterion (Caliński & Harabasz, 1974) and “global max” gap statistics (Tibshirani, 2001). Both approaches indicated that three was the optimal number of clusters. Profiles for subgroups were created by plotting the 12 mean dimensions scores for persons in each subgroup. Note that dimension scores were based on normalized z-scores for the 18 tests and questionnaires for the original cohort of 504. Summary statistics for identified subgroups were calculated for demographic and injury severity data as well as for the individual test and questionnaire scores for the 18 study measures.

Results

Study Sample Descriptions and Comparisons

The total cohort included 170 persons with TBI from Australia and 504 from the U.S. for a combined sample of 674. There were 21 persons with missing WMT scores (US n=13, Australia n=8) resulting in a sample size of 653. Of these, 143 (US n=117, Australian n=26) showed poor performance validity as indicated by failure of the WMT as determined by application of the standard cut-offs. These 143 participants formed the study cohort for this investigation.

K means cluster analysis of the 12 dimension scores for the 143 participants resulted in identification of three clusters (subgroups). Subgroups were labeled 1, 2, and 3 for convenience. Note that for each dimension score, lower scores indicated poorer performance (e.g., more impaired cognitive abilities, more complaints on self-report measures). Comparisons for demographic, injury severity, and performance validity values for the three subgroups are shown in Table 1. The three subgroups did not differ on gender, race, injury severity (Glasgow Coma Scale, duration of post-traumatic amnesia), age, years of education, or time since injury. While all three subgroups showed invalid performance, a difference was found in the overall WMT score (p < .001). Tukey multiple comparison testing showed that Subgroup 3 showed worse overall performance on the WMT than subgroups 1 or 2.

Table 1.

Comparison of the 3 Subgroups on Demographics, Injury Severity, Cognitive Tests, and Questionnaires

Subgroup 1 (n=43) Subgroup 2 (n=55) Subgroup 3 (n=45) Anova p-value
Categorical Descriptors N (%) N (%) N(%)
Gender 0.317
 Male 37 (86%) 42 (76%) 33 (73%)
 Female 6 (14%) 13 (24%) 12 (27%)
Race 0.211
 White 28 (65%) 26 (47%) 25 (56%)
 Non-white 15 (35%) 29 (53%) 20 (44%)
GCS Group 0.666
 Mild (13–15) 12 (28%) 17 (31%) 13 (29%)
 Moderate (9–12) 4 (9%) 7 (13%) 5 (11%)
 Severe (3–8) 16 (37%) 17 (31%) 15 (33%)
 Intubated 10 (23%) 6 (11%) 3 (7%)
 Medicated 1 (2%) 3 (6%) 3 (7%)
 Missing 0 (0%) 5 (9%) 6 (13%)
Continuous Descriptors Mean (SD) Mean (SD) Mean (SD) Anova p-value
 Age (y) 41.5 (13.7) 40.2 (10.9) 40.4 (12.9) 0.863
 Years of Education (y) 12.6 (2.5) 12.2 (2.2) 11.7 (2.1) 0.233
 Time since injury (y) 5.9 (6.2) 7.4 (6.9) 7.0 (7.9) 0.559
 PTA duration (d) 39.5 (39.8) 31.1 (37.6) 33.4 (34.3) 0.579
Measures Mean (SD) Mean (SD) Mean (SD) Anova p-value Tukey comparisons Cohenrisonsn jury orssg
Letter-number Sequencing 7.7 (3.1) 7.7 (2.7) 5.5 (2.8) 0.001 1, 2 > 3 0.7; 0.8
RAVLT Trials 1–5 26.5 (12.7) 29.3 (16.2) 23.5 (13.0) 0.132 N/A N/A; N/A
Trails A 43.3 (10.8) 41.9 (10.3) 36.7 (13.6) 0.019 1 > 3 0.5; N/A
Coding 7.2 (2.7) 6.6 (2.1) 5.4 (2.6) 0.005 1 > 3 0.6; N/A
Verbal Fluency (FAS) 41.7 (11.4) 45.0 (9.9) 33.2 (11.9) 0.001 1, 2 > 3 0.7; 1.1
TBI-QOL Cognition 43.5 (6.8) 34.1 (4.6) 28.4 (4.9) 0.001 1 > 2 > 3 2.6; 1.2
TBI-QOL Self-esteem 55.6 (6.6) 47.0 (6.3) 39.7 (7.8) 0.001 1 > 2 > 3 2.2; 1.0
TBI-QOL Independence 56.9 (7.5) 45.1 (5.2) 41.5 (6.9) 0.001 1 > 2 > 3 2.1; 0.6
TBI-QOL Resilience 55.7 (8.8) 46.2 (5.7) 41.5 (8.0) 0.001 1 > 2 > 3 1.7; 0.7
TBI-QOL Anxiety 47.8 8.3) 58.1 (7.6) 64.9 (6.8) 0.001 1 < 2 < 3 −2.3; −0.9
TBI-QOL Emot Behav Dys 47.7 (7.4) 55.2 (8.1) 63.3 (10.1) 0.001 1 < 2 < 3 −1.8; −0.9
Neurobehavioral Symptom 0.5 (0.3) 1.2 (0.4) 2.0 (0.6) 0.001 1 < 2 < 3 −3.3; −1.6
TBI-QOL Headache 43.6 (7.7) 53.4 (7.5) 57.5 (7.4) 0.001 1 < 2 < 3 −1.8; −0.5
TBI-QOL Pain Interference 47.6 (7.9) 59.6 (6.4) 63.7 (10.2) 0.001 1 < 2 < 3 −1.7; −0.5
TBI-QOL Upper Extremity 49.0 (7.9) 43.2 (6.4) 38.2 (6.2) 0.001 1 > 2 > 3 1.5; 0.8
Economic Quality of Life 60.4 (11.6) 50.4 (10.2) 47.2 (10.9) 0.001 1 > 2, 3 1.2; N/A
FAD General Functioning 1.8 (0.4) 2.1 (0.5) 2.4 (0.5) 0.001 1 < 2 < 3 −1.2; −0.5
Word Memory Test 78.9 (9.7) 78.1 (8.7) 67.6 (13.3) 0.001 1, 2 > 3 1.0; 0.9

Note: GCS = Glasgow Coma Scale, SD = standard deviation, y = years, PTA = post-traumatic amnesia, d = days, RAVLT = Rey Auditory Verbal Learning Test, TBI-QOL = Traumatic Brain Injury Quality of Life, Emot Behav Dys = Emotional and Behavioral Disturbance

For all cognitive tests, higher scores indicate more intact function. For the TBI-QOL Anxiety, Emotional and Behavioral Dyscontrol, Headache, and Pain Interference scales, higher scores indicate greater severity of symptoms. Also, for the Neurobehavioral Symptom Inventory and Family Assessment Device, higher scores indicate greater severity of symptoms. For all other symptom measures, higher scores indicate more intact function.

Pairwise comparisons were only reported when the overall Anova was significant and effect sizes were only reported when the pairwise comparison was significant.

As Subgroup 3 obtained the most impaired scores for all cognitive measures and the most symptomatic scores for all self-report measures, this group was used as the reference group for calculation of the effects sizes (Cohen’ d). Effects sizes ≤ 0.20 are small, > .20 but less than 0.80 moderate, and ≥ 0.80 large. (Cohen, 1988)

Profile plots for the three subgroups are presented in Figure 1. Persons in subgroup 1 and subgroup 2 scored similarly on cognitive tests. However, subgroup 2 participants reported higher levels of complaints on cognitive, emotional, physical, and environmental support dimensions. Subgroup 3 participants scored more poorly on cognitive tests and reported more complaints than either subgroup 1 or subgroup 2.

Figure 1.

Figure 1.

Profile plots for the three subgroups

To further demonstrate between group differences, we examined mean scores for the individual cognitive tests and self-report measures. Using greater than one standard deviation below the normative mean as indicating impairment, examination of the scores for the Rey Auditory Verbal Learning Test Trials 1–5 revealed that all three subgroups were markedly impaired with scores greater than 2 standard deviations below the normative mean. Subgroup 1 scored grossly within normal limits for all remaining cognitive tests. Subgroup 2 also showed impairment on the Wechsler Adult Intelligence Scale – IV Coding subtest. Subgroup 3 obtained scores that were impaired or markedly impaired on all cognitive tests. For self-report measures, Subgroup 1 scored similarly to a large cohort of persons with TBI from the TBI-QOL calibration sample (Tulsky et al., 2016). Subgroup 2 scored similarly to other persons with TBI on most self-report measures, but reported concern about cognition and elevated neurobehavioral complaints. Subgroup 3 showed high levels of concern regarding cognitive function, anxiety, and emotional and behavioral control. This group also reported disruption of activities by pain and decreased upper extremity function. They reported a moderate level of neurobehavioral complaints. These results are shown in Table 1 including Anova’s comparing the 3 groups, pairwise comparisons, and key effect sizes.

Discussion

The primary aim of this investigation was achieved as distinct subgroups of persons with failed performance validity were identified. These three subgroups differed in clinically meaningful ways on cognitive performance and symptom complaints. One group scored within one standard deviation of the normative mean on all cognitive tests except for the test that is clearly a memory test (RAVLT Trials 1–5 Total) and within one standard deviation of the mean scores from TBI-QOL calibration sample on all TBI-QOL measures. A second group scored in the impaired range for memory and the Wechsler Coding subtest while reporting much greater concern about cognitive function than the TBI-QOL calibration sample. A final group scored in the impaired range on all cognitive tests and reported substantial concern regarding cognitive function, self-esteem, and upper extremity motor function on the TBI-QOL.

While the cluster profiles provide information regarding various patterns of cognitive scores and complaints, they do not reveal factors that might contribute to these different profiles. Clinical examination of persons with failed performance validity should include a comprehensive history of factors such as litigation status, applications for disability compensation, pre-injury psychiatric history, family or other relationship dynamics that might provide secondary gain, apparent change in personal adjustment, and/or degree of psychological distress following injury. Test taking behavior should be carefully observed to detect evidence of boredom, or irritation with testing procedures.

Clinical intervention with persons who fail performance validity may be challenging. It is possible that factors that contribute to invalid performance may make patients more difficult to engage in treatment. Clinicians should be careful to listen to and acknowledge the patient’s point of view. Presentation of medical information that shows that patient complaints are improbable should be carried out with attention to the patient’s ability and willingness to entertain this information.

While admittedly speculative, we offer possible treatment implications of the subgroup profiles. For Subgroup 1, interventions might focus on providing the sorts of recommendations that are applicable for the general population. These could include memory and organizational strategies using smart phone or other technologies as well as a focus on regular exercise, proper diet, and sleep hygiene depending on the patient’s complaints. The emphasis should be on self-management of perceived impairments and complaints.

For Subgroup 2, the initial focus of intervention could be on emotional distress using education or psychotherapy. Treatments that help persons with TBI to cope with their emotional distress and work towards realistic, value-oriented goals may be helpful.

Subgroup 3 members are likely to be the most difficult to engage in treatment. Here, creation of a strong therapeutic alliance with family or close others may be helpful. The social influence that can be brought to bear by the patient’s social support network may be effective in enhancing engagement in treatment.

The treatment recommendations above are based on the clinical experience of the authors and require validation by additional investigation. Before this effort, the subgroup structure identified in this investigation should be cross-validated by additional research.

The present investigation has several limitations. The study cohort was drawn from persons with TBI who were living in the community and were not seeking treatment. The average interval from injury to study evaluation was 6.8 years. The majority of study participants sustained moderate or severe TBI rather than mild TBI. Information regarding whether participants were engaged in litigation or disability claims related to their injuries was not obtained. Persons with deficits due to prior neurologic illness or injury and those with severe psychiatric disturbance were excluded from this study. These factors may limit the applicability of study findings to other groups of persons with TBI and failed performance validity. Participants were not administered symptom validity tests and these tests may have contributed to understanding of the patterns of scores on subjective complaints. In addition, for this investigation, participants were only administered one performance validity measure. Best practice for clinical evaluations is administration of multiple measures of performance validity to provide converging evidence regarding adequacy of effort and to avoid reliance on a single measure that might be failed due to actual cognitive impairment rather than poor performance validity. (Board of Directors, 2007)

The findings of this investigation are an initial step toward a more sophisticated and individualized approach to managing patients with medically proven TBI and invalid performance on neuropsychological evaluation. Effective management of these persons may lead to improved quality of life for the patient and family/close others as well as decreased burden on healthcare resources. Further investigation is needed to build on this initial step. Future studies would benefit from examining participants who were seeking treatment.

Acknowledgements

This research was partially supported by a grant from the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR grant number 90DPTB0016). NIDILRR is a Center within the Administration for Community Living (ACL), Department of Health and Human Services (HHS). The contents of this article do not necessarily represent the policy of NIDILRR, ACL, HHS, and you should not assume endorsement by the Federal Government.

Footnotes

All authors declared no conflict of interest regarding this manuscript.

References

  1. Bashem JR, Rapport LJ, Miller JB, Hanks RA, Axelrod BN, & Millis SR (2014). Comparison of five performance validity indices in bona fide and simulated traumatic brain injury. The Clinical Neuropsychologist, 28(5), 851–875. [DOI] [PubMed] [Google Scholar]
  2. Board of Directors. (2007). American Academy of Clinical Neuropsychology (AACN) practice guidelines for neuropsychological assessment and consultation. The Clinical Neuropsychologist, 21, 209–231. [DOI] [PubMed] [Google Scholar]
  3. Bush SS, Ruff RM, Troster AI, Barth JT, Koffler SP, Pliskin NH, … Silver CH (2005). Symptom validity assessment: Practice issues and medical necessity. Archives of Clinical Neuropsychology, 20(4), 419–426. [DOI] [PubMed] [Google Scholar]
  4. Caliński T & Harabasz J (1974) A dendrite method for cluster analysis. Communications in Statistics. 3(1), 1–27. [Google Scholar]
  5. Chafetz MD, Williams MA, Ben-Porath YS, Bianchini KJ, Boone KB, Kirkwood MW, Larrabee GJ, & Ord JS (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. [DOI] [PubMed] [Google Scholar]
  6. Cicerone KD & Kalmar K (1995). Persistent postconcussion syndrome: The structure of subjective complaints after mild traumatic brain injury. Journal of Head Trauma Rehabilitation, 10(3), 1–17. [Google Scholar]
  7. Cohen J (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum. [Google Scholar]
  8. Epstein NB, Baldwin L, & Bishop DS (1983). The McMaster Family Assessment Device. Journal of Marital and Family Therapy, 9, 171–180. [Google Scholar]
  9. Frazier TW, Youngstrom EA, Naugle RI, Haggerty KA, Busch RM (2007). The latent structure of cognitive symptom exaggeration on the Victoria Symptom Validity Test. Archives of Clinical Neuropsychology, 22, 197–211. [DOI] [PubMed] [Google Scholar]
  10. Gladsjo JA, Schuman CC, Evans JD, Peavy GM, Miller SW, & Heaton RK (1999). Norms for letter and category fluency: Demographic corrections for age, education, and ethnicity. Assessment, 6, 147–178. [DOI] [PubMed] [Google Scholar]
  11. Green P (2007). The pervasive influence of effort on neuropsychological tests. Physical Medicine and Rehabilitation Clinics of North America, 18, 43–68. [DOI] [PubMed] [Google Scholar]
  12. Greher MR & Wodushek TR (2017). Performance validity testing in neuropsychology: Scientific basis and clinical application – a brief review. Journal of Psychiatric Practice, 23(2), 134–140. [DOI] [PubMed] [Google Scholar]
  13. Heaton RK, Miller SW, Taylor MJ, & Grant I (2004. Revised Comprehensive Norms for an Expanded Halstead-Reitan Battery: Demographically Adjusted Neuropsychological Norms for African American and Caucasian Adults. Lutz, FL: Psychological Assessment Resources. [Google Scholar]
  14. Heilbronner RL, Sweet JJ, Morgan JE, Larrabee GJ, Millis SR, & Conference Participants. (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. [DOI] [PubMed] [Google Scholar]
  15. Henry GK, Heilbronner RL, Suhr J, Gornbein J, Wagner E, & Drane DL (2018). Illness perceptions predict cognitive performance validity. Journal of the International Neuropsychological Society, 24(7), 735–745. [DOI] [PubMed] [Google Scholar]
  16. Larrabee GJ (2012). Performance validity and symptom validity in neuropsychological assessment. Journal of the International Neuropsychological Society, 18(4), 625–630. [DOI] [PubMed] [Google Scholar]
  17. Larrabee GJ (2014). Assessment of malingering In Larrabee GJ (Ed.), Forensic Neuropsychology: A scientific approach (2nd ed.) (116–159). New York: Oxford. [Google Scholar]
  18. Lippa SM (2018). Performance validity testing in neuropsychology: a clinical guide, critical review, and update on a rapidly evolving literature. The Clinical Neuropsychologist, 32(3), 391–421. [DOI] [PubMed] [Google Scholar]
  19. Lippa SM, Pastorek NJ, Romesser J, Linck J, Sim AH, Wisdom NM, & Miller BI (2014). Ecological validity of performance validity testing. Archives of Clinical Neuropsychology, 29(3), 236–244. [DOI] [PubMed] [Google Scholar]
  20. Morin RT, & Axelrod BN (2017). Use of latent class analysis to define groups based on validity, cognition, and emotional functioning. The Clinical Neuropsychologist, 31(6–7), 1087–1099. [DOI] [PubMed] [Google Scholar]
  21. Reitan RM & Wolfson D (1985). The Halstead-Reitan Neuropsychological Test Battery: Theory and Clinical Interpretation. Tucson, Arizona: Neuropsychology Press. [Google Scholar]
  22. Rey A (1958). L’examin Clinique en psychologie. Paris, France: Presses Universitaires de France. [Google Scholar]
  23. Sherer M, Nick TG, Sander AM, Melguizo M, Hanks R, Novack TA … Tang X (2017). Groupings of persons with traumatic brain injury: A new approach to classifying traumatic brain injury in the post-acute period. Journal of Head Trauma Rehabilitation, 32(2), 125–133. [DOI] [PubMed] [Google Scholar]
  24. Sherer M, Ponsford J, Hicks A, Leon-Novelo L, Ngan E, & Sander AM (2017). Cross-validation of a classification system for persons with traumatic brain injury in the posthospital period. Journal of Head Trauma Rehabilitation, 32(5), E17–E25. [DOI] [PubMed] [Google Scholar]
  25. Sherer M, Sander AM, Nick TG, Melguizo MS, Tulsky DS, Kinsala P, Hanks R, & Novack TA (2015). Key dimensions of impairment, self-report, and environmental supports in persons with traumatic brain injury. Rehabilitation Psychology, 60(2), 138–146. [DOI] [PubMed] [Google Scholar]
  26. Slick DJ, Sherman EMS, & Iverson GL (1999)). Diagnostic criteria for malingered neurocognitive dysfunction: Proposed standards for clinical practice and research. The Clinical Neuropsychologist, 13(4), 545–561. [DOI] [PubMed] [Google Scholar]
  27. Schmidt M (1996). Rey Auditory Verbal Learning Test (RAVLT): A Handbook. Los Angeles: Western Psychological Services. [Google Scholar]
  28. Sweet JJ & Meyer DG (2014). Trends in forensic practice and research In Larrabee GJ(Ed.), Forensic Neuropsychology: A scientific approach (2nd ed.) (501–516). New York: Oxford. [Google Scholar]
  29. Tibshirani R, Walther G, & Hastie T (2001). Estimating the number of clusters in a date set via the gap statistic. Journal of the Royal Statistical Society, Series B, 63 (2), 411–423. [Google Scholar]
  30. Tulsky DS, Kisala PA, Lai J-S, Carlozi N, Hammel J, & Heinemann AW (2015). Developing an item bank to measure economic quality of life for individuals with disabilities. Archives of Physical Medicine and Rehabilitation, 96(4), 604–613. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Tulsky DS, Kisala PA, Victorson D, Carlozzi N, Bushnik T, Sherer M,…Cella D (2016). TBI-QOL: Development and calibration of items banks to measure patient reported outcomes following traumatic brain injury. Journal of Head Trauma Rehabilitation, 31(1), 40–51. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Wechsler D (2008). Wechsler Adult Intelligence Scale – Fourth Edition (WAIS-IV). San Antonio, Texas: Pearson. [Google Scholar]

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