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Objectives: To determine base rates of invalid performance on the Test of Memory Malingering (TOMM) in patients with traumatic brain injury (TBI) undertaking rehabilitation who were referred for clinical assessment, and the factors contributing to TOMM failure. Methods: Retrospective file review of consecutive TBI referrals for neuropsychological assessment over seven years. TOMM failure was conventionally defined as performance <45/50 on Trial 2 or Retention Trial. Demographic, injury, financial compensation, occupational, and medical variables were collected. Results: Four hundred and ninety one TBI cases (Median age = 40 years [IQR = 26–52], 79% male, 82% severe TBI) were identified. Overall, 48 cases (9.78%) failed the TOMM. Logistic regression analyses revealed that use of an interpreter during the assessment (adjusted odds ratio [aOR] = 8.25, 95%CI = 3.96–17.18), outpatient setting (aOR = 4.80, 95%CI = 1.87–12.31) and post-injury psychological distress (aOR = 2.77, 95%CI = 1.35–5.70) were significant multivariate predictors of TOMM failure. The TOMM failure rate for interpreter cases was 49% (21/43) in the outpatient setting vs. 7% (2/30) in the inpatient setting. By comparison, 9% (21/230) of non-interpreter outpatient cases failed the TOMM vs. 2% (4/188) of inpatient cases. Conclusions: TOMM failure very rarely occurs in clinical assessment of TBI patients in the inpatient rehabilitation setting. It is more common in the outpatient setting, particularly in non-English-speaking people requiring an interpreter. The findings reinforce the importance of routinely administering stand-alone performance validity tests in assessments of clinical TBI populations, particularly in outpatient settings, to ensure that neuropsychological test results can be interpreted with a high degree of confidence. [ABSTRACT FROM AUTHOR]

Objective: We developed the Shell Game Task (SGT) as a novel Performance Validity Test (PVT). While most PVTs use a forced-choice paradigm with "memory" as the primary domain being assessed, the SGT is a face-valid measure of attention and working memory. We explored the accuracy of the SGT to detect noncredible performance using a simulatordesign study. Participants and Methods: Ninety-four university students were randomly assigned to either best effort (CON) (n=49) or simulating traumatic brain injury (TBI) (SIM) (n=45) conditions. Participants completed a full battery of neuropsychological tests to simulate an actual evaluation, including the Test of Memory Malingering (TOMM) and the SGT. The SGT involves three cups and a red ball shown on the screen. Participants watch as the ball is placed under one of the three cups. Cups are then shuffled. Participants are asked to track the cup that contains the ball and correctly identify its location. We created two difficulty levels (easy vs hard, 20 trials each) by changing the number of times the cups were shuffled. Participants were given feedback (correct vs incorrect) after each trial. At the conclusion of the study, participants were asked about adherence to study directions they were given. Results: Participants with missing data (CON=1; SIM=2) or who reported non-adherence to study directions (CON=2; SIM=1) were removed from analyses. Twenty-five percent in SIM and 0% in CON failed TOMM Trial 2 (<45) suggesting adequate manipulation of groups. Groups were not different in age, gender, ethnicity, or education (all p's>.05). There were 9 participants in each group with concussion/TBI history. TBI history was not significantly related to performance on the SGT in either group, although participants with TBI history tended to do better. Average performances on TOMM Trial 1 (36.62 vs 47.91, p<.001) and TOMM Trial 2 (37.50 vs 49.71, p<.001) were significantly lower in the SIM group. Performance on SGT was also significantly lower in the SIM group across SGT Total Correct (20.17 vs 24.65 of 40, p=.008), SGT Easy (10.60 vs 13.52 of 20, p=.002), and SGT Hard (9.57 vs 11.13 of 20, p=.068). Mixed ANOVA showed a trend towards significant group by SGT difficulty interaction (F(1,86)=3.41, p=.052, np2=.043). There was steeper decline in performance on SGT Hard compared to SGT Easy for CON. ROC analyses suggested adequate but not ideal sensitivity/specificity: scores <8 on SGT Easy (sensitivity=26%; false positive=11%), <7 on SGT Hard (sensitivity=26%; false positive=7%), and <15 on SGT Total (sensitivity=24%; false positive=9%). Conclusions: These preliminary data indicate the SGT may be able to detect malingered TBI. However, additional development of this measure is necessary. Further refinement of difficulty level may improve sensitivity/specificity (e.g., CON mean performance for SGT Easy trails was 13.52, suggesting the items may be too difficult). This study was limited to an online administration due to COVID, which could have affected results; future studies should test inperson administration of the SGT. In addition, performance in clinical control groups (larger samples of individuals with mild TBI, ADHD) should be tested to better determine specificity for these preliminary cutoffs. [ABSTRACT FROM AUTHOR]

Objective: Recent consensus guidelines have advocated for the use of multivariate performance validity assessment on ability-based measures such those used in neuropsychological assessment. Further, previous research has demonstrated that aggregating performance validity indicators may produce superior classification accuracy. The present study builds upon this research by aggregating data from three of the most commonly used performance validity measures (Test of Memory Malingering [TOMM], Rey Fifteen Item Test with recognition trial [FIT plus recognition], and Reliable Digit Span [RDS]) to create a performance validity composite measure in a veteran mild traumatic brain injury (mTBI) population. Participants and Methods: Data of patients evaluated at a VA hospital who had completed the RDS, FIT plus recognition, and TOMM as part of their clinical neuropsychological evaluation were analyzed (n = 20). Two composite performance validity indexes were created: a Single Cutoff Performance Validity Index (SC-PVI), which measures the quantity of failures across performance validity measures (PVMs) by summing the total number of PVM failures, and a Multiple Cutoff Performance Validity Index (MC-PVI) which measures the number of failures as well as degree of failure(s) across measures of performance validity (e.g., a participant would attain a score of 3 if their PVM performance failed to reach a conservative cut point; they would obtain a score of 1 if they met conservative cut point, yet failed to reach a liberal cut point). Results: Only one participant (5%) attained a score of 0 on the SC-PVI (i.e., passing all PVTs using standard cutoffs) and MC-PVI (i.e., passing the most liberal cut points on all three PVMs). Conversely, eight participants (40%) attained a score of 3 on the SC-PVI (i.e., failed all three PVMs) and four participants (20%) attained a score of 9 (i.e., failed the most conservative cut points on all three PVMs). Results showed a significant (p <.001) ordinal association between the two indices (G =.984); however, there was no significant agreement between SC-PVI and MC-PVI models (k = -.087; p =.127). Conclusions: Data revealed discordant findings between the three PVMs utilized. The majority of participants (75%) scored between 2-8 on the MC-PVI, meaning that they did not exceed all liberal cut points or fail all conservative cut points. These "grey area" scores suggest an indeterminate range of performance validity, which cannot be captured by a solitary cut point or neatly classified as pass or fail. The utility of multiple cutoff performance validity models (i.e., aggregating PVMs to consider the severity of failure and number of failures) is that they capture the nuance of these data when determining and discussing the credibility of a profile. Multiple cut point data also highlight how the choice of cutoff influences the outcome of performance validity research and clinical decision making. As such, future research on the classification accuracy of this MC-PVI is needed. [ABSTRACT FROM AUTHOR]