Child Neuropsychology A Journal on Normal and Abnormal Development in Childhood and Adolescence
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Performance on the Test of Memory Malingering in children with neurological conditions Danielle M. Ploetz, Anya Mazur-Mosiewicz, Michael W. Kirkwood, Elisabeth M.S. Sherman & Brian L. Brooks To cite this article: Danielle M. Ploetz, Anya Mazur-Mosiewicz, Michael W. Kirkwood, Elisabeth M.S. Sherman & Brian L. Brooks (2014): Performance on the Test of Memory Malingering in children with neurological conditions, Child Neuropsychology, DOI: 10.1080/09297049.2014.986446 To link to this article: http://dx.doi.org/10.1080/09297049.2014.986446
Published online: 11 Dec 2014.
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Child Neuropsychology, 2014 http://dx.doi.org/10.1080/09297049.2014.986446
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Performance on the Test of Memory Malingering in children with neurological conditions Danielle M. Ploetz1, Anya Mazur-Mosiewicz1,2, Michael W. Kirkwood3, Elisabeth M.S. Sherman1,4,5, and Brian L. Brooks1,5,6 1
Neurosciences Department (Brain Injury and Rehabilitation Programs), Alberta Children’s Hospital, Calgary, AB, Canada 2 Clinical Psychology Doctoral Program, Chicago School of Professional Psychology, Chicago, IL, USA 3 Department of Physical Medicine & Rehabilitation, University of Colorado School of Medicine & Children's Hospital Colorado, Aurora, CO, USA 4 Copeman Healthcare Centre, Calgary, AB, Canada 5 Departments of Paediatrics and Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada 6 Behaviour and the Developing Brain Program, Alberta Children’s Hospital Research Institute, Calgary, AB, Canada Despite increasing interest in the use of performance validity tests with youth, relatively little is known about how children and adolescents with neurological diagnoses perform on these measures. The purpose of this study was to examine performance on the Test of Memory Malingering (TOMM) in a general pediatric neurologic sample. Data were obtained from 266 consecutive patients (mean age = 13.0, SD = 3.7, range = 5–18) referred for a neuropsychological assessment in a tertiary care pediatric hospital. As part of a broader neuropsychological battery, patients were administered the TOMM. In this sample, 94% of children passed the TOMM. Pass rate was 87% for 5–7 year-olds but was ≥ 90% for all other ages. Children with a history of stroke had the lowest pass rate (86%), with other diagnostic groups scoring ≥ 90%, including epilepsy, traumatic brain injury, and hydrocephalus. Lower TOMM performance was related to slower processing speed and weaker memory performance. The results support using the TOMM with children and adolescents who have neurological diagnoses. Caution may still be warranted when interpreting scores in those who are younger and/or who have more significant cognitive difficulty. Keywords: Performance validity; Symptom Validity; Effort Testing; Children; Adolescents; Malingering.
Clinicians and researchers continue to examine the utility of performance validity tests (PVTs) in pediatric neuropsychological assessments. Although PVTs are not yet standard tools in clinical assessment, these measures are gaining traction in neuropsychological Address correspondence to Brian L. Brooks, PhD, Neurosciences Department (Brain Injury and Rehabilitation Programs), Alberta Children’s Hospital, 2888 Shaganappi Trail NW, Calgary, Alberta, Canada T3B 6A8. E-mail: [email protected]
© 2014 Taylor & Francis
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assessment (Kirkwood, 2012). Most available stand-alone PVTs were originally developed with adults; however, research is supporting the use of several of these PVTs with youth. For example, some evidence in youth supports the use of the Amsterdam ShortTerm Memory Test (ASTM; Schmand & Lindeboom, 2004; see Rienstra, Spaan, & Schmand, 2010), Computerized Assessment of Response Bias (CARB; Allen, Conder, Green, & Cox, 1997; see Courtney, Dinkins, Allen, & Kuroski, 2003), Dot Counting Test (DCT; Rey 1941; see Martin, Haut, Stainbrook, & Franzen, 1995), Word Memory Test (WMT; Green, 2003; see Green & Flaro, 2003; Gunn, Batchelor, & Jones, 2010), Medical Symptom Validity Test (MSVT; Green, 2004; see Carone, 2008; Kirkwood & Kirk, 2010), Nonverbal Medical Symptom Validity Test (NV-MSVT; Green, 2008; see Green, Flaro, Brockhaus, & Montijo, 2012), 21-Item Test (Iverson, 1998; see Martin et al., 1995), and Victoria Symptom Validity Test (VSVT; Slick, Hopp, Strauss, & Thompson, 1997; see Brooks, 2012). Of all stand-alone PVTs, the Test of Memory Malingering (TOMM; Tombaugh, 1996) has the most published support for its utility with children and adolescents (DeRight & Carone, 2013), although further evidence is needed. In normally developing school-age children (Constantinou & McCaffrey, 2003; Rienstra et al., 2010) and when children are asked to perform optimally (Blaskewitz, Merten, & Kathmann, 2008; Gunn et al., 2010), TOMM passing rates range from 97% to 100%. For clinical samples of children diagnosed with medical and/or psychological disorders, studies using the TOMM are relatively consistent in regards to findings with healthy children (and adult samples). Namely, mixed clinical groups have reported passing rates of 97% for ages 6–16 years (Donders, 2005), 96% for those 5–16 years (Kirk et al., 2011), and 94% for children between the ages of 6–19 years (Brooks, Sherman, & Krol, 2012). Some studies do suggest relatively lower pass rates (86% in a study by Loughan, Perna, & Hertza, 2012; 88% by Perna & Loughan, 2013; and 87% for youth ages 6–18 years, Loughan & Perna, 2014). A closer look at TOMM performance across specific diagnostic groups suggests variable pass rates in different neurological and psychiatric conditions. Specifically, 90% of children diagnosed with epilepsy are able to pass the TOMM (MacAllister, Nakhutina, Bender, Karantzoulis, & Carlson, 2009) with different passing rates for other groups, including 85% for conduct disorder, 92% for affective disorders, 83% for traumatic brain injury (TBI), 93% for attention deficit/hyperactivity disorder (ADHD), 88% for pervasive developmental disorders (PDD), 76% for intellectual disability (ID), and 100% for children with learning disabilities (Loughan & Perna, 2014). The lower passing rate for those with an ID has also been demonstrated in other studies (59% passing; Hurley, Deal, & Taylor, 2006). Despite the aforementioned variability with some diagnostic groups and lower performance by those with an ID, it is clear that the TOMM can be passed by most children, that it can be a potential PVT for use in assessments, and that it would benefit from more research for use with specific populations (e.g., stroke, hydrocephalus). The purpose of this study was to analyze performance on the TOMM in a large group of children and youth with neurological conditions with varying ages, intellectual levels, and diagnoses. It was hypothesized that children and adolescents with neurological disorders would have pass rates on the TOMM consistent with prior pediatric research (i.e., ≥ 90%). Those children and adolescents with a neurological condition, as well as a diagnosis of ID, were not expected to pass at the same rates based on previous literature discussed above.
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METHODS
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Participants Participants included 266 consecutively referred children and adolescents between the ages of 5 and 18 years who underwent neuropsychological assessments at a tertiary care hospital. An earlier version of this same case series has been previously published (Brooks et al., 2012). The treating neurologist or neurosurgeon provided diagnoses for each participant, which included epilepsy, traumatic brain injury (TBI; split into concussion and complicated mild-to-severe TBI), stroke, and hydrocephalus. There was also a group of children with various neurological diagnoses that did not fit into one of the larger diagnostic groups (i.e., “general neurology”). Informed consent was obtained from parents and those participants who were 18 years of age with assent from those under 18 years. Measures The TOMM (Tombaugh, 1996) is a forced-choice visual recognition PVT consisting of two learning trials (Trial 1 and Trial 2) and a retention trial (Trial 3). For the purpose of this investigation, overall performance was coded as “pass” or ”fail” based on the TOMM manual cut-off criteria (Tombaugh, 1996) and previous research with pediatric neurology patients (e.g., if a patient passed Trial 1 [i.e., ≥ 45], then the remaining trials were not administered; Brooks et al., 2012). Participants were also administered other measures of neurocognitive functioning, including tests of intellectual abilities and processing speed (Full-Scale IQ [FSIQ] and Processing Speed Indices from the Wechsler Preschool and Primary Scale of Intelligence, third edition [WPPSI-III; Wechsler, 2004], Wechsler Intelligence Scale for Children, fourth edition [WISC-IV; Wechsler, 2003], Wechsler Adult Intelligence Scale, third/fourth edition [WAIS-III/IV; Wechsler, 1997a, 2008]), recall memory for a list of words (Long Delay Free Recall from the California Verbal Learning Test, Children’s Version [CVLT-C; Delis, Kramer, Kaplan, & Ober, 1994], or California Verbal Learning Test, second edition [CVLT-II; Delis, Kramer, Kaplan, & Ober, 2000]), stories (Stories Delayed from the Children’s Memory Scale [Cohen, 1997] or Logical Memory II from Wechsler Memory Scale, third/fourth edition [WMS-III/IV; Wechsler, 1997b; Wechsler, 2009]), or faces (Faces Delayed from the Children’s Memory Scale [CMS; Cohen, 1997] or Faces II from WMS-III [Wechsler, 1997b]). It is important to note that not all participants were administered all measures of neurocognitive functioning in this clinical sample. Analyses Analyses primarily included descriptive techniques based on pass or fail classification on the TOMM. Descriptives of the performances on measures of cognitive abilities, as well as correlations between raw scores on the TOMM, demographics, and cognitive tests were included. Due to the negatively skewed raw TOMM scores, the current study used Spearman’s rho (ρ) for examination of correlations. Alpha was set a priori at p < .05. RESULTS Demographic variables for this sample are presented in Table 1. In this sample of children and adolescents with neurological diagnoses, mean age was 13.0 (SD = 3.7).
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Table 1 Demographic Variables for the Pediatric Sample. Demographics
Mean
SD
Range
Age (years)
13.0
3.7
5.0–18.4
Parent Education (years) -Mother -Father
13.9 13.9
2.5 2.7
6–20 6–20
%
Sex -Male -Female
53 47
Ethnicity -Caucasian -Middle Eastern -Asian -Hispanic -Mixed -First Nations -Other -Not Reported
56.8 3.4 3.8 2.6 1.1 1.1 1.9 28.6
Diagnosis -Epilepsy -Concussion -Complicated Mild-to-Severe TBI* -General Neurology -Stroke -Hydrocephalus
36.8 14.7 13.2 16.5 13.9 4.9
*Included all patients with positive neuroimaging findings.
Table 2 TOMM Performance in Pediatric Neurology Patients. TOMM Trials Trial 1 Trial 2 Trial 3
n
Mean
SD
Range
266 86 58
46.9 46.9 47.0
4.7 6.3 6.1
19–max 20–max 22–max
Parents had a mean level of education that fell within the range of some postsecondary school. The sample was roughly split between males and females and most participants were Caucasian. Over one third of this sample had a diagnosis of epilepsy with nearly an even-split of other diagnostic groups with the exception of hydrocephalus (which was a small percentage of the overall group at 4.9%). Performance on the TOMM is presented in Table 2. The mean performance on Trial 1 was 46.9 (SD = 4.7) with 83% passing this initial trial. For Trial 2, the mean performance was 46.9 (SD = 6.3). For Trial 3, mean performance was 47.0 (SD = 6.1). When considering overall classification on the TOMM according to the manual, 94% of this sample passed the TOMM. After a review of all clinical data in the cases that did not pass the TOMM, 9 out of 16 were deemed true positives for noncredible effort (see Table 3 for more details). These cases included children who responded near chance levels or displayed other unequivocal evidence of noncredible responding during the evaluation. Those that were considered false
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Table 3 Demographic and Testing Information About Those that were Categorized as “Fail” on the TOMM.
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Patient Age/Gender Diagnosis TP/FP 5M 7M 8M 12M 14F 15F
Stroke TBI Epilepsy General General TBI
TP TP TP TP TP TP
15M 17F 18F 5F 7M 8F
Stroke TBI General Epilepsy Stroke General
TP TP TP FP FP FP
8M 8F
Epilepsy Stroke
FP FP
11M 17F
Stroke Epilepsy
FP FP
Reasons Below chance performance; not engaged Unwilling to guess; refusal to respond Shut down easily At chance performance levels Anxiety and upset at the start of testing, likely affected compliance Failed two PVTs; VSVT was at chance performance and Trial 2 performance on TOMM was worse than Trial 1 Chance performance on PVTs Failed two PVTs (one at chance performance) but had Average IQ Better on visual memory tests; disinterested; fatigued Cooperative; low functioning (FSIQ = 66); attention poor Autistic-like behavior; low functioning (GAI = 61) Poor attention; low functioning (based on previous assessment, nonverbal intellectual abilities were first percentile)1; Global Developmental Delay; consistent with previous assessment Cooperative, learning problems, low functioning (GAI = 49) Motivated by stickers, severe inattention; low functioning (GAI = 71) Cooperative; appeared confused; low functioning (GAI = 44) Low functioning (GAI = 54), motivated
Notes. GAI = general ability index. This patient’s intellectual abilities were derived from a previous assessment that only included percentile scores.
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positives were typically young (e.g., less than 8 years of age), had lower intellectual abilities and were described as motivated and cooperative during the assessment. In this sample of children and adolescents with neurological diagnoses, the overall IQ index was 86.1 (SD = 19.9; range 40–129) and 18.7% of participants with available FSIQ data (n = 163) had scores within the range of intellectual disability (IQ ≤ 70). On processing speed indices, overall processing speed was 83.9 (SD = 17.9; range 42–146). On memory testing, verbal memory for words had a mean z-score of -0.5 (SD = 1.3; range = ‒4–2), story memory had a mean scaled score of 9.7 (SD = 4.2; range = 1–17), and memory for faces had a mean scaled score of 8.7 (SD = 3.7; range = 1–17). Correlations suggested that better TOMM performance was related to faster processing speed (ρ = 0.172, p < .01) and stronger memory skills (verbal memory word list: ρ = .227, p < .01; story memory: ρ = .243, p < .01; faces memory: ρ = .191, p = .026). Percentages of participants passing the TOMM, stratified for various groups, are presented in Table 4. In the youngest group (n = 31; 5–7 years), 87% passed the TOMM. The other age groups passed at a rate > 90% (92% in ages 8–10 [n = 52]; 97% in ages 11– 13 [n = 58]; the oldest group [n = 125; ages 14–18] had an overall pass rate of 95%). Children with IQ scores below or equal to 70 (n = 35) had 94% pass, children with IQ scores 71–84 (n = 39) had 95% pass, and children with IQ scores 85 or above (n = 89) had 99% passing the TOMM. However, some caution is warranted with the IQ analyses because only 89% of the 103 with missing IQ scores passed the TOMM. Examining performance across different diagnostic groups suggested that children with epilepsy (n = 98) had 96% pass, children with a TBI (n = 74) had 96% pass (100% and 91% for concussion and complicated mild-to-severe TBI groups, respectively), children with stroke (n = 37) had
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Table 4 Percent Passing the TOMM by Age Group, Intelligence Level, and Neurological Diagnosis. % Below cut-off % Below cut-off deemed false deemed true positive positives
% Pass Rate Excluding True Positives^
Sample size
% Overall Pass rate*
Overall Summary
n = 266
94
3
3
97
Age Groups 5–7 8–10 11–13 14–18
n n n n
87 92 97 95
7 6 2 1
6 2 1 4
93 94 98 99
IQ IQ IQ IQ
n = 35 n = 39 n = 89
94 95 99
6 3 0
0 2 1
94 97 100
n = 98 n = 39 n = 35
96 100 91
3 0 0
1 0 9
97 100 100
n = 37 n = 13 n = 44
86 100 91
9 0 2
5 0 7
91 100 98
Groups ≤ 70 71–84 85 or above
Diagnostic Groups Epilepsy Concussion Complicated Mild-to-Severe TBI Stroke Hydrocephalus General Neurology
= = = =
31 52 58 125
*Overall pass rate was based on the TOMM manual and/or cut-off scores suggested by Brooks et al. (2012): TBI = traumatic brain injury. ^Pass rates that exclude 9 that were determined to be true positives (i.e., not providing adequate effort).
86% pass, children with hydrocephalus (n = 13) had 100% pass, and children in the heterogeneous “general neurology” group (n = 44) had 91% pass the TOMM. DISCUSSION The current study demonstrates that 94% of this large and diverse pediatric neurologic sample was able to pass the TOMM based on cut-off scores established for adults. This is consistent with other research that suggests children and adolescents with clinical diagnoses are capable of passing the TOMM at similar rates to adult populations (Donders, 2005; Kirk et al., 2011; Loughan & Perna, 2014; MacAllister et al., 2009) and provides additional support for the use of the TOMM as a PVT with youth in neuropsychological assessments. The TOMM was originally developed for use with patients 16 years and older (Tombaugh, 1996), so clinical administration and interpretation with the youngest age groups is often done with caution. In the present study, the youngest group (5–7 years) had the lowest pass rate and fell just below the expected 90% level (87%). Pass rates in the current sample of 5- to 7-year-olds were similar to the results observed by Donders (2005) for 6- to 8-year-olds with mixed diagnoses, where 91% passed the TOMM. The remaining age groups (8–18 years) had pass rates ranging from 92–97% and were all comparable in their performances. The passing rates for most of the youth in this study are similar to the rates reported by several prior studies (i.e., Brooks et al., 2012; Kirk et al., 2011; Loughan et al., 2012; MacAllister et al., 2009). The age-based pass rates suggest
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that the TOMM tasks and instructions are relatively well understood by children and adolescents, and the test is appropriate for this age group. However, slightly lower pass rates in the youngest children (5–7 years), coupled with the known correlations between age and PVT performance in several studies (Brooks, 2012; Donders, 2005; Kirk et al., 2011), do suggest that using the TOMM with these ages may overidentify invalid scores (i.e., false positives). At age 8 and older, TOMM pass rates are greater than 90% and can be used with confidence to help determine validity of performance. Further examination of the 5- to 7-year age range suggests that perhaps the confidence for using the TOMM can encompass those who are age 6 or older. Our sample, though limited by size of each age group, suggests 90% or better pass rates for those aged 6 and 7. The 5-year-olds had a pass rate of 78%, but only had 2 out of 9 failures. Larger sample sizes of children in this age group that have a neurological condition should be examined before making definitive statements. The administration and interpretation of PVTs in children with cognitive disability need to be done judiciously. In the present study, TOMM pass rates ranged from 94% for those with extremely low IQs to 99% in those with broadly normal IQ scores. Consistent with existing literature for PVTs in youth (Brooks, 2012; Constantinou, Bauer, Ashendorf, Fisher, & McCaffrey, 2005; Donders, 2005; Kirk et al., 2011; Loughan & Perna, 2014; MacAllister et al., 2009), performance on the TOMM (specifically Trial 1) in the present pediatric sample was positively correlated with cognitive functioning. However, this is contradictory to previous studies reporting lower passing rates for those with an ID (e.g., Loughan & Perna, 2014). Although the lowest intellectual group had an adequate pass rate in the present study, caution is still warranted when administering the TOMM (or other PVTs) to those with extremely low IQ (or other frank neurocognitive impairment) because there is inconsistent evidence about the passing rates for these individuals. Interestingly, in adults, motivation has been found to strongly influence PVT performance in low-functioning individuals. Chafetz, Prentkowski, and Rao (2011) found that adults with low IQs consistently passed PVTs when motivated to look good on testing (to find work or to reunify with their children) and failed PVTs at much higher rates when seeking disability compensation. Loughan and Perna (2014) suggested that the pass rates may vary across diagnostic groups in their study of youth with those having a conduct disorder, TBI, intellectual disability, and pervasive developmental disorder having pass rates below 90% (i.e., affective disorder, ADHD, and learning disability had pass rates > 90%). In the present study, only 86% of patients with a history of stroke (33/37) passed the TOMM, but otherwise 91–100% of patients with epilepsy, TBI, hydrocephalus, and mixed diagnoses passed the TOMM. The slightly lower than desired pass rate in children with a prior stroke is difficult to explain, although this is only based on a small sample of 37 patients. Performances across the other diagnostic groups in the current study were relatively similar to previous literature. In the current study, youth diagnosed with epilepsy had slightly better pass rates on the TOMM (96%) compared to the epilepsy sample reported by MacAllister and colleagues (2009) (90%). This difference could be related to more true positives in the MacAllister et al. sample. In other words, there were more children who were providing noncredible effort than in our sample thus leading to a lower overall passing rate on the TOMM. Interestingly, 100% of the patients identified with a concussion passed the TOMM. This is contrasted with a 78% pass rate in the Loughan and Perna (2014) TBI sample (note: the exact severity of the Loughan and Perna TBI sample was not specified).
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Although an initial thought may be that the TOMM is insensitive to detecting inadequate compliance in youth with a TBI, Kirkwood and Kirk (2010) reported the same pass rate of 83% on the MSVT for their pediatric mild TBI sample. Concordance between the TOMM and MSVT pass rates suggest that the sensitivity of the two PVTs may be comparable in pediatric TBI samples. The reasons behind different pass rates for TBI patients in the current sample compared to the Loughan and Perna (2014) sample are not fully known, but one possible explanation could be that the severity of the injury was more severe. Regardless, the current results do indicate that children in this setting who sustained a concussion are quite capable of valid performance on the TOMM. Furthermore, 91% of patients with a more substantial TBI based on positive neuroimaging findings passed the TOMM, which would be roughly consistent with the 95% pass rate of children with moderate-to-severe brain injuries on the MSVT demonstrated by Carone (2008). These results should be interpreted in the context of several limitations. First, the sample sizes for some of the subgroups were small. The potential problem with small sample sizes across the subgroup analyses is that having only a few patients fall below the cut-off score can result in a rather large percentage being deemed to have failed. Second, although every child included in this study received the TOMM, not every child received every cognitive test. As a result, there are some analyses with missing data that should be cautiously interpreted. Third, this was a sample of consecutively referred patients who were evaluated by neuropsychologists within a Canadian tertiary care hospital setting, which may not be representative of patients assessed in other settings. This study adds further information to the growing body of literature that supports PVT use in pediatric neuropsychological assessments. Children and adolescents with neurological diagnoses are able to pass the TOMM at similar rates as adults. Because the pass rates for some subsamples were not above the desired 90% mark, we do suggest some caution with those children who are younger and/or have lower intellectual abilities. It will be important to continue building the research evidence that demonstrates the utility of the TOMM, and other PVTs, in a variety of settings and with diverse patient populations. Original manuscript received June 13, 2014 Revised manuscript accepted November 6, 2014 First published online December 9, 2014
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Loughan, A. R., & Perna, R. (2014). Performance and specificity rates in the Test of Memory Malingering: An investigation into pediatric clinical populations. Applied Neuropsychology: Child, 3, 26–30. doi:10.1080/21622965.2012.670584 Loughan, A. R., Perna, R., & Hertza, J. (2012). The value of the wechsler intelligence scale for children-fourth edition digit span as an embedded measure of effort: An investigation into children with dual diagnoses. Archives of Clinical Neuropsychology, 27(7), 716–724. doi:10.1093/arclin/acs072 MacAllister, W. S., Nakhutina, L., Bender, H. A., Karantzoulis, S., & Carlson, C. (2009). Assessing effort during neuropsychological evaluation with the TOMM in children and adolescents with epilepsy. Child Neuropsychology, 15(6), 521–531. doi:10.1080/09297040902748226 Martin, R. C., Haut, J. S., Stainbrook, T., & Franzen, M. D. (1995). Preliminary normative data for objective measures to detect malingered neuropsychological deficits in a population of adolescent patients [Abstract]. Archives of Clinical Neuropsychology, 10, 364–365. doi:10.1093/ arclin/10.4.364 Perna, R., & Loughan, A. R. (2013). Children and the Test of Memory Malingering: Is one trial enough? Child Neuropsychology, 19(4), 438–447. doi:10.1080/09297049.2012.731500 Rey, A. (1941). L’examen psychologique dans les cas d’encephalopathie traumatic. Archives de Psychologie, 28, 286–340. Rienstra, A., Spaan, P. E., & Schmand, B. (2010). Validation of symptom validity tests using a “child-model” of adult cognitive impairments. Archives of Clinical Neuropsychology, 25(5), 371–382. doi:10.1093/arclin/acq035 Schmand, B., & Lindeboom, J. (2004). Amsterdam Short-Term Memory Test. Leiden: Pits Test. Slick, D., Hopp, G., Strauss, E., & Thompson, G. (1997). The Victoria Symptom Validity Test. Odessa, FL: PAR. Tombaugh, T. (1996). Test of Memory of Malingering (TOMM). North Tonawanda, NY: MultiHealth Systems. Wechsler, D. (1997a). Wechsler Adult Intelligence Scale (3rd ed.). Administration and Scoring Manual. San Antonio, TX: The Psychological Corporation. Wechsler, D. (1997b). Wechsler Memory Scale (3rd ed.). San Antonio, TX: The Psychological Corporation. Wechsler, D. (2003). Wechsler Intelligence Scale for Children (4th ed.). San Antonio, TX: The Psychological Corporation. Wechsler, D. (2004). Wechsler Preschool and Primary Scale of Intelligence (3rd ed.). Canadian. San Antonio, TX: The Psychological Corporation. Wechsler, D. (2008). Wechsler Adult Intelligence Scale (4th ed.). San Antonio, TX: Pearson. Wechsler, D. (2009). Wechsler Memory Scale—Fourth Edition (WMS–IV) Technical and Interpretive Manual. San Antonio, TX: Pearson.
ISSN: 0929-7049 (Print) 1744-4136 (Online) Journal homepage: http://www.tandfonline.com/loi/ncny20
Performance on the Test of Memory Malingering in children with neurological conditions Danielle M. Ploetz, Anya Mazur-Mosiewicz, Michael W. Kirkwood, Elisabeth M.S. Sherman & Brian L. Brooks To cite this article: Danielle M. Ploetz, Anya Mazur-Mosiewicz, Michael W. Kirkwood, Elisabeth M.S. Sherman & Brian L. Brooks (2014): Performance on the Test of Memory Malingering in children with neurological conditions, Child Neuropsychology, DOI: 10.1080/09297049.2014.986446 To link to this article: http://dx.doi.org/10.1080/09297049.2014.986446
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Child Neuropsychology, 2014 http://dx.doi.org/10.1080/09297049.2014.986446
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Performance on the Test of Memory Malingering in children with neurological conditions Danielle M. Ploetz1, Anya Mazur-Mosiewicz1,2, Michael W. Kirkwood3, Elisabeth M.S. Sherman1,4,5, and Brian L. Brooks1,5,6 1
Neurosciences Department (Brain Injury and Rehabilitation Programs), Alberta Children’s Hospital, Calgary, AB, Canada 2 Clinical Psychology Doctoral Program, Chicago School of Professional Psychology, Chicago, IL, USA 3 Department of Physical Medicine & Rehabilitation, University of Colorado School of Medicine & Children's Hospital Colorado, Aurora, CO, USA 4 Copeman Healthcare Centre, Calgary, AB, Canada 5 Departments of Paediatrics and Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada 6 Behaviour and the Developing Brain Program, Alberta Children’s Hospital Research Institute, Calgary, AB, Canada Despite increasing interest in the use of performance validity tests with youth, relatively little is known about how children and adolescents with neurological diagnoses perform on these measures. The purpose of this study was to examine performance on the Test of Memory Malingering (TOMM) in a general pediatric neurologic sample. Data were obtained from 266 consecutive patients (mean age = 13.0, SD = 3.7, range = 5–18) referred for a neuropsychological assessment in a tertiary care pediatric hospital. As part of a broader neuropsychological battery, patients were administered the TOMM. In this sample, 94% of children passed the TOMM. Pass rate was 87% for 5–7 year-olds but was ≥ 90% for all other ages. Children with a history of stroke had the lowest pass rate (86%), with other diagnostic groups scoring ≥ 90%, including epilepsy, traumatic brain injury, and hydrocephalus. Lower TOMM performance was related to slower processing speed and weaker memory performance. The results support using the TOMM with children and adolescents who have neurological diagnoses. Caution may still be warranted when interpreting scores in those who are younger and/or who have more significant cognitive difficulty. Keywords: Performance validity; Symptom Validity; Effort Testing; Children; Adolescents; Malingering.
Clinicians and researchers continue to examine the utility of performance validity tests (PVTs) in pediatric neuropsychological assessments. Although PVTs are not yet standard tools in clinical assessment, these measures are gaining traction in neuropsychological Address correspondence to Brian L. Brooks, PhD, Neurosciences Department (Brain Injury and Rehabilitation Programs), Alberta Children’s Hospital, 2888 Shaganappi Trail NW, Calgary, Alberta, Canada T3B 6A8. E-mail: [email protected]
© 2014 Taylor & Francis
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assessment (Kirkwood, 2012). Most available stand-alone PVTs were originally developed with adults; however, research is supporting the use of several of these PVTs with youth. For example, some evidence in youth supports the use of the Amsterdam ShortTerm Memory Test (ASTM; Schmand & Lindeboom, 2004; see Rienstra, Spaan, & Schmand, 2010), Computerized Assessment of Response Bias (CARB; Allen, Conder, Green, & Cox, 1997; see Courtney, Dinkins, Allen, & Kuroski, 2003), Dot Counting Test (DCT; Rey 1941; see Martin, Haut, Stainbrook, & Franzen, 1995), Word Memory Test (WMT; Green, 2003; see Green & Flaro, 2003; Gunn, Batchelor, & Jones, 2010), Medical Symptom Validity Test (MSVT; Green, 2004; see Carone, 2008; Kirkwood & Kirk, 2010), Nonverbal Medical Symptom Validity Test (NV-MSVT; Green, 2008; see Green, Flaro, Brockhaus, & Montijo, 2012), 21-Item Test (Iverson, 1998; see Martin et al., 1995), and Victoria Symptom Validity Test (VSVT; Slick, Hopp, Strauss, & Thompson, 1997; see Brooks, 2012). Of all stand-alone PVTs, the Test of Memory Malingering (TOMM; Tombaugh, 1996) has the most published support for its utility with children and adolescents (DeRight & Carone, 2013), although further evidence is needed. In normally developing school-age children (Constantinou & McCaffrey, 2003; Rienstra et al., 2010) and when children are asked to perform optimally (Blaskewitz, Merten, & Kathmann, 2008; Gunn et al., 2010), TOMM passing rates range from 97% to 100%. For clinical samples of children diagnosed with medical and/or psychological disorders, studies using the TOMM are relatively consistent in regards to findings with healthy children (and adult samples). Namely, mixed clinical groups have reported passing rates of 97% for ages 6–16 years (Donders, 2005), 96% for those 5–16 years (Kirk et al., 2011), and 94% for children between the ages of 6–19 years (Brooks, Sherman, & Krol, 2012). Some studies do suggest relatively lower pass rates (86% in a study by Loughan, Perna, & Hertza, 2012; 88% by Perna & Loughan, 2013; and 87% for youth ages 6–18 years, Loughan & Perna, 2014). A closer look at TOMM performance across specific diagnostic groups suggests variable pass rates in different neurological and psychiatric conditions. Specifically, 90% of children diagnosed with epilepsy are able to pass the TOMM (MacAllister, Nakhutina, Bender, Karantzoulis, & Carlson, 2009) with different passing rates for other groups, including 85% for conduct disorder, 92% for affective disorders, 83% for traumatic brain injury (TBI), 93% for attention deficit/hyperactivity disorder (ADHD), 88% for pervasive developmental disorders (PDD), 76% for intellectual disability (ID), and 100% for children with learning disabilities (Loughan & Perna, 2014). The lower passing rate for those with an ID has also been demonstrated in other studies (59% passing; Hurley, Deal, & Taylor, 2006). Despite the aforementioned variability with some diagnostic groups and lower performance by those with an ID, it is clear that the TOMM can be passed by most children, that it can be a potential PVT for use in assessments, and that it would benefit from more research for use with specific populations (e.g., stroke, hydrocephalus). The purpose of this study was to analyze performance on the TOMM in a large group of children and youth with neurological conditions with varying ages, intellectual levels, and diagnoses. It was hypothesized that children and adolescents with neurological disorders would have pass rates on the TOMM consistent with prior pediatric research (i.e., ≥ 90%). Those children and adolescents with a neurological condition, as well as a diagnosis of ID, were not expected to pass at the same rates based on previous literature discussed above.
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METHODS
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Participants Participants included 266 consecutively referred children and adolescents between the ages of 5 and 18 years who underwent neuropsychological assessments at a tertiary care hospital. An earlier version of this same case series has been previously published (Brooks et al., 2012). The treating neurologist or neurosurgeon provided diagnoses for each participant, which included epilepsy, traumatic brain injury (TBI; split into concussion and complicated mild-to-severe TBI), stroke, and hydrocephalus. There was also a group of children with various neurological diagnoses that did not fit into one of the larger diagnostic groups (i.e., “general neurology”). Informed consent was obtained from parents and those participants who were 18 years of age with assent from those under 18 years. Measures The TOMM (Tombaugh, 1996) is a forced-choice visual recognition PVT consisting of two learning trials (Trial 1 and Trial 2) and a retention trial (Trial 3). For the purpose of this investigation, overall performance was coded as “pass” or ”fail” based on the TOMM manual cut-off criteria (Tombaugh, 1996) and previous research with pediatric neurology patients (e.g., if a patient passed Trial 1 [i.e., ≥ 45], then the remaining trials were not administered; Brooks et al., 2012). Participants were also administered other measures of neurocognitive functioning, including tests of intellectual abilities and processing speed (Full-Scale IQ [FSIQ] and Processing Speed Indices from the Wechsler Preschool and Primary Scale of Intelligence, third edition [WPPSI-III; Wechsler, 2004], Wechsler Intelligence Scale for Children, fourth edition [WISC-IV; Wechsler, 2003], Wechsler Adult Intelligence Scale, third/fourth edition [WAIS-III/IV; Wechsler, 1997a, 2008]), recall memory for a list of words (Long Delay Free Recall from the California Verbal Learning Test, Children’s Version [CVLT-C; Delis, Kramer, Kaplan, & Ober, 1994], or California Verbal Learning Test, second edition [CVLT-II; Delis, Kramer, Kaplan, & Ober, 2000]), stories (Stories Delayed from the Children’s Memory Scale [Cohen, 1997] or Logical Memory II from Wechsler Memory Scale, third/fourth edition [WMS-III/IV; Wechsler, 1997b; Wechsler, 2009]), or faces (Faces Delayed from the Children’s Memory Scale [CMS; Cohen, 1997] or Faces II from WMS-III [Wechsler, 1997b]). It is important to note that not all participants were administered all measures of neurocognitive functioning in this clinical sample. Analyses Analyses primarily included descriptive techniques based on pass or fail classification on the TOMM. Descriptives of the performances on measures of cognitive abilities, as well as correlations between raw scores on the TOMM, demographics, and cognitive tests were included. Due to the negatively skewed raw TOMM scores, the current study used Spearman’s rho (ρ) for examination of correlations. Alpha was set a priori at p < .05. RESULTS Demographic variables for this sample are presented in Table 1. In this sample of children and adolescents with neurological diagnoses, mean age was 13.0 (SD = 3.7).
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Table 1 Demographic Variables for the Pediatric Sample. Demographics
Mean
SD
Range
Age (years)
13.0
3.7
5.0–18.4
Parent Education (years) -Mother -Father
13.9 13.9
2.5 2.7
6–20 6–20
%
Sex -Male -Female
53 47
Ethnicity -Caucasian -Middle Eastern -Asian -Hispanic -Mixed -First Nations -Other -Not Reported
56.8 3.4 3.8 2.6 1.1 1.1 1.9 28.6
Diagnosis -Epilepsy -Concussion -Complicated Mild-to-Severe TBI* -General Neurology -Stroke -Hydrocephalus
36.8 14.7 13.2 16.5 13.9 4.9
*Included all patients with positive neuroimaging findings.
Table 2 TOMM Performance in Pediatric Neurology Patients. TOMM Trials Trial 1 Trial 2 Trial 3
n
Mean
SD
Range
266 86 58
46.9 46.9 47.0
4.7 6.3 6.1
19–max 20–max 22–max
Parents had a mean level of education that fell within the range of some postsecondary school. The sample was roughly split between males and females and most participants were Caucasian. Over one third of this sample had a diagnosis of epilepsy with nearly an even-split of other diagnostic groups with the exception of hydrocephalus (which was a small percentage of the overall group at 4.9%). Performance on the TOMM is presented in Table 2. The mean performance on Trial 1 was 46.9 (SD = 4.7) with 83% passing this initial trial. For Trial 2, the mean performance was 46.9 (SD = 6.3). For Trial 3, mean performance was 47.0 (SD = 6.1). When considering overall classification on the TOMM according to the manual, 94% of this sample passed the TOMM. After a review of all clinical data in the cases that did not pass the TOMM, 9 out of 16 were deemed true positives for noncredible effort (see Table 3 for more details). These cases included children who responded near chance levels or displayed other unequivocal evidence of noncredible responding during the evaluation. Those that were considered false
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Table 3 Demographic and Testing Information About Those that were Categorized as “Fail” on the TOMM.
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Patient Age/Gender Diagnosis TP/FP 5M 7M 8M 12M 14F 15F
Stroke TBI Epilepsy General General TBI
TP TP TP TP TP TP
15M 17F 18F 5F 7M 8F
Stroke TBI General Epilepsy Stroke General
TP TP TP FP FP FP
8M 8F
Epilepsy Stroke
FP FP
11M 17F
Stroke Epilepsy
FP FP
Reasons Below chance performance; not engaged Unwilling to guess; refusal to respond Shut down easily At chance performance levels Anxiety and upset at the start of testing, likely affected compliance Failed two PVTs; VSVT was at chance performance and Trial 2 performance on TOMM was worse than Trial 1 Chance performance on PVTs Failed two PVTs (one at chance performance) but had Average IQ Better on visual memory tests; disinterested; fatigued Cooperative; low functioning (FSIQ = 66); attention poor Autistic-like behavior; low functioning (GAI = 61) Poor attention; low functioning (based on previous assessment, nonverbal intellectual abilities were first percentile)1; Global Developmental Delay; consistent with previous assessment Cooperative, learning problems, low functioning (GAI = 49) Motivated by stickers, severe inattention; low functioning (GAI = 71) Cooperative; appeared confused; low functioning (GAI = 44) Low functioning (GAI = 54), motivated
Notes. GAI = general ability index. This patient’s intellectual abilities were derived from a previous assessment that only included percentile scores.
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positives were typically young (e.g., less than 8 years of age), had lower intellectual abilities and were described as motivated and cooperative during the assessment. In this sample of children and adolescents with neurological diagnoses, the overall IQ index was 86.1 (SD = 19.9; range 40–129) and 18.7% of participants with available FSIQ data (n = 163) had scores within the range of intellectual disability (IQ ≤ 70). On processing speed indices, overall processing speed was 83.9 (SD = 17.9; range 42–146). On memory testing, verbal memory for words had a mean z-score of -0.5 (SD = 1.3; range = ‒4–2), story memory had a mean scaled score of 9.7 (SD = 4.2; range = 1–17), and memory for faces had a mean scaled score of 8.7 (SD = 3.7; range = 1–17). Correlations suggested that better TOMM performance was related to faster processing speed (ρ = 0.172, p < .01) and stronger memory skills (verbal memory word list: ρ = .227, p < .01; story memory: ρ = .243, p < .01; faces memory: ρ = .191, p = .026). Percentages of participants passing the TOMM, stratified for various groups, are presented in Table 4. In the youngest group (n = 31; 5–7 years), 87% passed the TOMM. The other age groups passed at a rate > 90% (92% in ages 8–10 [n = 52]; 97% in ages 11– 13 [n = 58]; the oldest group [n = 125; ages 14–18] had an overall pass rate of 95%). Children with IQ scores below or equal to 70 (n = 35) had 94% pass, children with IQ scores 71–84 (n = 39) had 95% pass, and children with IQ scores 85 or above (n = 89) had 99% passing the TOMM. However, some caution is warranted with the IQ analyses because only 89% of the 103 with missing IQ scores passed the TOMM. Examining performance across different diagnostic groups suggested that children with epilepsy (n = 98) had 96% pass, children with a TBI (n = 74) had 96% pass (100% and 91% for concussion and complicated mild-to-severe TBI groups, respectively), children with stroke (n = 37) had
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Table 4 Percent Passing the TOMM by Age Group, Intelligence Level, and Neurological Diagnosis. % Below cut-off % Below cut-off deemed false deemed true positive positives
% Pass Rate Excluding True Positives^
Sample size
% Overall Pass rate*
Overall Summary
n = 266
94
3
3
97
Age Groups 5–7 8–10 11–13 14–18
n n n n
87 92 97 95
7 6 2 1
6 2 1 4
93 94 98 99
IQ IQ IQ IQ
n = 35 n = 39 n = 89
94 95 99
6 3 0
0 2 1
94 97 100
n = 98 n = 39 n = 35
96 100 91
3 0 0
1 0 9
97 100 100
n = 37 n = 13 n = 44
86 100 91
9 0 2
5 0 7
91 100 98
Groups ≤ 70 71–84 85 or above
Diagnostic Groups Epilepsy Concussion Complicated Mild-to-Severe TBI Stroke Hydrocephalus General Neurology
= = = =
31 52 58 125
*Overall pass rate was based on the TOMM manual and/or cut-off scores suggested by Brooks et al. (2012): TBI = traumatic brain injury. ^Pass rates that exclude 9 that were determined to be true positives (i.e., not providing adequate effort).
86% pass, children with hydrocephalus (n = 13) had 100% pass, and children in the heterogeneous “general neurology” group (n = 44) had 91% pass the TOMM. DISCUSSION The current study demonstrates that 94% of this large and diverse pediatric neurologic sample was able to pass the TOMM based on cut-off scores established for adults. This is consistent with other research that suggests children and adolescents with clinical diagnoses are capable of passing the TOMM at similar rates to adult populations (Donders, 2005; Kirk et al., 2011; Loughan & Perna, 2014; MacAllister et al., 2009) and provides additional support for the use of the TOMM as a PVT with youth in neuropsychological assessments. The TOMM was originally developed for use with patients 16 years and older (Tombaugh, 1996), so clinical administration and interpretation with the youngest age groups is often done with caution. In the present study, the youngest group (5–7 years) had the lowest pass rate and fell just below the expected 90% level (87%). Pass rates in the current sample of 5- to 7-year-olds were similar to the results observed by Donders (2005) for 6- to 8-year-olds with mixed diagnoses, where 91% passed the TOMM. The remaining age groups (8–18 years) had pass rates ranging from 92–97% and were all comparable in their performances. The passing rates for most of the youth in this study are similar to the rates reported by several prior studies (i.e., Brooks et al., 2012; Kirk et al., 2011; Loughan et al., 2012; MacAllister et al., 2009). The age-based pass rates suggest
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that the TOMM tasks and instructions are relatively well understood by children and adolescents, and the test is appropriate for this age group. However, slightly lower pass rates in the youngest children (5–7 years), coupled with the known correlations between age and PVT performance in several studies (Brooks, 2012; Donders, 2005; Kirk et al., 2011), do suggest that using the TOMM with these ages may overidentify invalid scores (i.e., false positives). At age 8 and older, TOMM pass rates are greater than 90% and can be used with confidence to help determine validity of performance. Further examination of the 5- to 7-year age range suggests that perhaps the confidence for using the TOMM can encompass those who are age 6 or older. Our sample, though limited by size of each age group, suggests 90% or better pass rates for those aged 6 and 7. The 5-year-olds had a pass rate of 78%, but only had 2 out of 9 failures. Larger sample sizes of children in this age group that have a neurological condition should be examined before making definitive statements. The administration and interpretation of PVTs in children with cognitive disability need to be done judiciously. In the present study, TOMM pass rates ranged from 94% for those with extremely low IQs to 99% in those with broadly normal IQ scores. Consistent with existing literature for PVTs in youth (Brooks, 2012; Constantinou, Bauer, Ashendorf, Fisher, & McCaffrey, 2005; Donders, 2005; Kirk et al., 2011; Loughan & Perna, 2014; MacAllister et al., 2009), performance on the TOMM (specifically Trial 1) in the present pediatric sample was positively correlated with cognitive functioning. However, this is contradictory to previous studies reporting lower passing rates for those with an ID (e.g., Loughan & Perna, 2014). Although the lowest intellectual group had an adequate pass rate in the present study, caution is still warranted when administering the TOMM (or other PVTs) to those with extremely low IQ (or other frank neurocognitive impairment) because there is inconsistent evidence about the passing rates for these individuals. Interestingly, in adults, motivation has been found to strongly influence PVT performance in low-functioning individuals. Chafetz, Prentkowski, and Rao (2011) found that adults with low IQs consistently passed PVTs when motivated to look good on testing (to find work or to reunify with their children) and failed PVTs at much higher rates when seeking disability compensation. Loughan and Perna (2014) suggested that the pass rates may vary across diagnostic groups in their study of youth with those having a conduct disorder, TBI, intellectual disability, and pervasive developmental disorder having pass rates below 90% (i.e., affective disorder, ADHD, and learning disability had pass rates > 90%). In the present study, only 86% of patients with a history of stroke (33/37) passed the TOMM, but otherwise 91–100% of patients with epilepsy, TBI, hydrocephalus, and mixed diagnoses passed the TOMM. The slightly lower than desired pass rate in children with a prior stroke is difficult to explain, although this is only based on a small sample of 37 patients. Performances across the other diagnostic groups in the current study were relatively similar to previous literature. In the current study, youth diagnosed with epilepsy had slightly better pass rates on the TOMM (96%) compared to the epilepsy sample reported by MacAllister and colleagues (2009) (90%). This difference could be related to more true positives in the MacAllister et al. sample. In other words, there were more children who were providing noncredible effort than in our sample thus leading to a lower overall passing rate on the TOMM. Interestingly, 100% of the patients identified with a concussion passed the TOMM. This is contrasted with a 78% pass rate in the Loughan and Perna (2014) TBI sample (note: the exact severity of the Loughan and Perna TBI sample was not specified).
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Although an initial thought may be that the TOMM is insensitive to detecting inadequate compliance in youth with a TBI, Kirkwood and Kirk (2010) reported the same pass rate of 83% on the MSVT for their pediatric mild TBI sample. Concordance between the TOMM and MSVT pass rates suggest that the sensitivity of the two PVTs may be comparable in pediatric TBI samples. The reasons behind different pass rates for TBI patients in the current sample compared to the Loughan and Perna (2014) sample are not fully known, but one possible explanation could be that the severity of the injury was more severe. Regardless, the current results do indicate that children in this setting who sustained a concussion are quite capable of valid performance on the TOMM. Furthermore, 91% of patients with a more substantial TBI based on positive neuroimaging findings passed the TOMM, which would be roughly consistent with the 95% pass rate of children with moderate-to-severe brain injuries on the MSVT demonstrated by Carone (2008). These results should be interpreted in the context of several limitations. First, the sample sizes for some of the subgroups were small. The potential problem with small sample sizes across the subgroup analyses is that having only a few patients fall below the cut-off score can result in a rather large percentage being deemed to have failed. Second, although every child included in this study received the TOMM, not every child received every cognitive test. As a result, there are some analyses with missing data that should be cautiously interpreted. Third, this was a sample of consecutively referred patients who were evaluated by neuropsychologists within a Canadian tertiary care hospital setting, which may not be representative of patients assessed in other settings. This study adds further information to the growing body of literature that supports PVT use in pediatric neuropsychological assessments. Children and adolescents with neurological diagnoses are able to pass the TOMM at similar rates as adults. Because the pass rates for some subsamples were not above the desired 90% mark, we do suggest some caution with those children who are younger and/or have lower intellectual abilities. It will be important to continue building the research evidence that demonstrates the utility of the TOMM, and other PVTs, in a variety of settings and with diverse patient populations. Original manuscript received June 13, 2014 Revised manuscript accepted November 6, 2014 First published online December 9, 2014
REFERENCES Allen, L. M., Conder, R. L., Green, P., & Cox, D. R. (1997). Manual for the Computerized Assessment of Response Bias. Durham, NC: CogniSyst. Blaskewitz, N., Merten, T., & Kathmann, N. (2008). Performance of children on symptom validity tests: TOMM, MSVT, and FIT. [Controlled Clinical Trial, Research Support, Non-U.S. Gov’t]. Archives of Clinical Neuropsychology, 23(4), 379–391. doi:10.1016/j.acn.2008.01.008 Brooks, B. L. (2012). Victoria Symptom Validity Test performance in children and adolescents with neurological disorders. Archives of Clinical Neuropsychology, 27(8), 858–868. doi:10.1093/ arclin/acs087 Brooks, B. L., Sherman, E. M. S., & Krol, A. L. (2012). Utility of TOMM Trial 1 as an indicator of effort in children and adolescents. Archives of Clinical Neuropsychology, 27(1), 23–29. doi:10.1093/arclin/acr086
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