Archives of Clinical Neuropsychology 29 (2014) Eamonn Arble*, Jeffrey Kuentzel, Douglas Barnett. Wayne State University, Detroit, MI, USA

Transcription

1 Archives of Clinical Neuropsychology 29 (2014) Convergent Validity of the Integrated Visual and Auditory Continuous Performance Test (IVA+Plus): Associations with Working Memory, Processing Speed, and Behavioral Ratings Eamonn Arble*, Jeffrey Kuentzel, Douglas Barnett Wayne State University, Detroit, MI, USA *Corresponding author at: Wayne State Psychology Clinic, Wayne State University, 60 Farnsworth, Detroit, MI 48202, USA. Tel.: ; fax: address: (E. Arble). Abstract Accepted 16 February 2014 Though the Integrated Visual and Auditory Continuous Performance Test (IVA + Plus) is commonly used by researchers and clinicians, few investigations have assessed its convergent and discriminant validity, especially with regard to its use with children. The present study details correlates of the IVA + Plus using measures of cognitive ability and ratings of child behavior (parent and teacher), drawing upon a sample of 90 psychoeducational evaluations. Scores from the IVA + Plus correlated significantly with the Working Memory and Processing Speed Indexes from the Fourth Edition of the Wechsler Intelligence Scales for Children (WISC-IV), though fewer and weaker significant correlations were seen with behavior ratings scales, and significant associations also occurred with WISC-IV Verbal Comprehension and Perceptual Reasoning. The overall pattern of relations is supportive of the validity of the IVA + Plus; however, general cognitive ability was associated with better performance on most of the primary scores of the IVA + Plus, suggesting that interpretation should take intelligence into account. Keywords: IVA; ADHD; CPT; WISC-IV; Psychoeducational assessment Introduction Convergent validity of the Integrated Visual and Auditory Continuous Performance Test (IVA + Plus) associations with working memory, processing speed, and behavioral ratings. Continuous performance tests (CPTs) were developed to assess sustained attention and impulsivity via performance on a mundane automated task, with most CPTs focusing solely upon attention in the visual modality. The general format of these tasks requires the examinee to monitor simple information (e.g., light flashing or symbol presented on a computer screen), to respond to the appearance of a predetermined target stimulus, and to disregard the appearance of foils and/or distractor stimuli. By measuring the ability to refrain from responding to distractor stimuli, as well as the capacity to focus selectively on relevant information (i.e., the target stimulus), it is hoped that CPTs can provide objective measures of inattention and impulsivity, the core impairments in Attention-Deficit/Hyperactivity Disorder (ADHD; American Psychiatric Association, 2013). The use of CPTs in clinical assessment, especially for primary attentional problems such as ADHD, has been recommended and become commonplace (Borgaro et al., 2003; Rapport, Chung, Shore, Denney, & Isaacs, 2000). Although CPTs have been shown to successfully discriminate children or adults with ADHD from non-clinical counterparts, their ability to differentiate ADHD from other clinical disorders is sometimes poor (Nichols & Waschbusch, 2004; Solanto, Etefia, & Marks, 2004). For instance, in a study of 100 clinic-referred children, McGee, Clark, and Symons (2000) found a rate of agreement between CPT failures and diagnosed ADHD of 52%. Other validity issues persist, such as failures to document relations An earlier version of this paper was presented on May 30, 2010, at the Annual Convention of the Association for Psychological Science, Boston, MA, USA. # The Author Published by Oxford University Press. All rights reserved. For permissions, please journals.permissions@oup.com. doi: /arclin/acu006 Advance Access publication on 30 March 2014

2 E. Arble et al. / Archives of Clinical Neuropsychology 29 (2014) between CPT variables and scores on clinical instruments designed to assess facets of inattention. For example, Naglieri, Goldstein, Delauder, and Schwebach (2005) reported no significant correlations between scores on the popular Conners CPT (1994) and behavioral ratings made by parents and teachers in a sample of 117 children referred for psychological evaluation. Alloway and colleagues (2009), with a sample of 46 children with ADHD Combined subtype, failed to find significant correlations between CPT scores and teacher-rated behavioral ratings of ADHD features. However, other studies have documented associations between CPT scores and ADHD symptoms (e.g., Epstein et al., 2003). There are several issues that may account for these mixed findings. Studies that include CPTs use a variety of methods for measuring ADHD symptoms, ranging from teacher ratings, to self-report, to diagnostic interviews with parents. These methods are subject to their own reliability and validity shortcomings (e.g., Solanto & Alvir, 2009). It is also likely that these methods capture different facets of ADHD features, and these facets may have differing degrees of association with CPT variables (Barkley & Murphy, 2010). Another issue is that a variety of different CPTs have been developed, and the diverse content and structure among them may contribute to dissimilar patterns of associations with features of impulsivity and inattention (Epstein et al., 2003). It is also possible that CPT scores do not show consistently strong relations with symptoms of ADHD because CPTs tend to tap constructs other than what they are intended to measure. For example, in some cases, CPT performance could depend more on the general intelligence level (Tinius, 2003), or motivation/effort (Quinn, 2003), than on levels of impairment resulting from ADHD features. In fact, in a comprehensive review of the literature, Riccio, Reynolds, and Lowe (2001) found a wide range of correlations between CPT performance and scores from different cognitive measures, ranging from 2.66 to.67, with the majority of validity coefficients falling between 2.30 and.30. However, these authors also highlighted a small number of factor analytic studies (e.g., Aylward, Gordon, & Verhulst, 1997), showing that CPT scores and measures of intelligence loaded on separate factors. The present study examines the convergent and discriminant correlates of the primary scores yielded by the Integrated Visual and Auditory Continuous Performance Test (IVA + Plus; Sandford & Turner, 2004). The IVA + Plus is unique among CPTs because of its simultaneous testing of performance in auditory and visual modalities. During the test s approximately 15-min duration, participants are asked to click a mouse when the number 1 is presented (either aurally or visually) and refrain from clicking when the number 2 is presented. During different blocks of trials, the ratio of targets to foils varies (i.e., sometimes 1 is presented frequently, other times it is rarely presented), as a period of frequent targets followed by a period of infrequent targets would be expected to pull for impulsive responding. The IVA + Plus provides a wide range of scores, including both basic scale scores and composite quotient scores that are derived from the basic scales. The Full-Scale Response Control Quotient and the Full-Scale Attention Quotient represent higherorder scores, summarizing information found in the basic scales. According to the test developers (Sandford & Turner, 2004), the Full-Scale Response Control Quotient is derived from three scales taken from each of the Auditory and Visual modalities (six scales in total). These scales measure impulsivity or response inhibition (Prudence based on errors of commission), general reliability and variability of reaction times (Consistency), and the ability to sustain effort and attention over time (Stamina based on reaction time for trials toward the end of the test when compared with reaction time for early trials). Additional information may be gleaned by examining these scores in the Auditory and Visual domains separately. Similarly, the Full-Scale Attention Quotient is derived from three Auditory and three Visual modality scores namely Vigilance (errors of omission), Focus (variability in processing speed), and Speed (mean reaction time for correct responses). Two other quotient scores are the Sustained Attention Quotients (Auditory and Visual). In addition to basic and quotient scores, the IVA + Plus produces numerous supplemental scores. Among them is Fine Motor Regulation, a count of excessive off-task mouse-clicks by the examinee (i.e., hyperactivity). The Comprehension scores, based on the occurrence of idiopathic errors (e.g., random responding), may have the potential to be particularly sensitive to primary problems with inattention or impulsivity (Sandford & Turner, 2004). The IVA + Plus was normed on a group of 1,700 participants, ages 6 and above, from a wide geographical background (Sandford & Turner, 2004). Ethnic variability in the norms is unknown, but gender-specific norms are provided. Available research on the IVA + Plus suggests that it may be comparable with the Conners CPT in terms of positive predictive power (Edwards, 1998). Corbett and Constantine (2006) found that the IVA + Plus was able to differentiate children with autism spectrum disorders (ASDs) and those with ADHD from controls, and though 93% of the ASD children s IVA + Plus scores suggested the presence of ADHD, they were found to have significantly higher levels of impulsivity than their ADHD counterparts. The IVA + Plus is quite commonly used by researchers, especially in neuropsychological or cognitive rehabilitation studies with adult populations, yet relatively few investigations have been conducted that detail its psychometric properties. Most published studies concerned with the validity of the IVA + Plus have tested its ability to correctly classify members of specific diagnostic groups. Though this research provides an important start, additional evidence for the validity of IVA + Plus scores would be provided if the scores were found to be related to other measures of attentional processes, and if IVA + Plus scores were further shown to be unrelated to measures of other constructs that theoretically should not be tapped by a CPT (Nichols & Waschbusch, 2004).

3 302 E. Arble et al. / Archives of Clinical Neuropsychology 29 (2014) One such study is the Corbett and Constantine investigation (2006) that examined children with ASDs, children with ADHD, and typically developing controls. These authors did find two moderate associations in the expected direction between the Full-Scale Attention Quotient and parent ratings of attention problems. However, the Full-Scale Response Control Quotient was unrelated to most parent ratings of inattention and impulsivity, with the exception of one modest correlation in the unexpected direction (i.e., IVA + Plus Response Control scores increased with parent ratings of attention problems). Further, little is known about how IVA + Plus scores may relate to measures of cognitive ability, such as IQ, or to academic achievement. Tinius (2003) reported a strong association between the Full-Scale Attention Quotient and Full-Scale IQ (FSIQ; r ¼.64) among adults with ADHD, but also found that IQ was unrelated to IVA + Plus scores in mild traumatic brain injury (TBI) and control groups. Although published reviews have suggested that overall IQ scores are only reduced modestly by the presence of ADHD (Jepsen, Fagerlund, & Mortensen, 2009; Schuck & Crinella, 2005), specific IQ domain or index scores (those that may be more sensitive to inattention and/or impulsivity) would be expected on average to be lower than other IQ domains in individuals with attentional or impulsive difficulties. For example, the Technical and Interpretive Manual for the WISC-IV (Wechslser, 2003) reports that both the Working Memory Index (WMI) and the Processing Speed Index (PSI) were lower in a sample of 89 children with clinically significant problems of inattention or impulsivity when compared with scores obtained by matched controls. Furthermore, recent research suggests that ADHD is associated with a relative weakness in working memory and processing speed (e.g., Dovis, Oord, Wiers, & Prins, 2013; Katz, Brown, Roth, & Beers, 2011). Thus, correlations in the expected direction between IVA + Plus scores and WMI and PSI scores would be supportive of the validity of the IVA + Plus. On the other hand, strong correlations with FSIQ scores, and with the two other index scores, which are not believed to be as sensitive to attentional impairments (i.e., the Verbal Comprehension Index [VCI] and Perceptual Reasoning Index [PRI]), might call into question the validity of the IVA + Plus, indicating that poor performance on the task could result from lower general intelligence. The separate Visual and Auditory domain scores yielded by the IVA + Plus further provide the opportunity to make predictions about modality-specific associations with WISC-IV (the Fourth Edition of the Wechsler Intelligence Scales for Children) scores. Because the WMI is comprised of auditory subtests, whereas the PSI is primarily visual, we expect that Auditory IVA + Plus scores will be more strongly associated with WMI scores, whereas Visual IVA + Plus scores will show larger associations with PSI scores. Important evidence for IVA + Plus validity would also come from convergent correlations with behavioral ratings of inattention and impulsivity made by observers. In the present study, we explore the relations among IVA + Plus scores and ratings made by both parents and teachers. We present relations with checklist scales that are designed to directly measure symptoms of inattention, but also with scales that tap features that may expected to be associated with attentional difficulties and disinhibition (e.g., rule-breaking behavior), as well as scales that tap other clinical concerns that could affect attention and concentration (e.g., depression, anxiety). Finally, we report on IVA + Plus associations with academic performance (rated by teachers), as no studies could be located that provide information on how IVA + Plus scores may relate to the important functional domain of scholastic achievement (Molina et al., 2009). Method This research project was approved by the Wayne State University Human Investigation Committee. An archival database was created based on a review of psychoeducational evaluations conducted at our psychology training clinic. Participants The psychology training clinic is located in a large Midwestern city, where services are provided to a primarily lower SES community. The 90 consecutive cases in the sample ranged in age from 6 to 16, with an average age of years (SD ¼ 2.79). Boys were somewhat more common than girls (61.9% of the sample), and the most common ethnicities were African American (50.0%) and Caucasian (42.9%), with the remaining children categorized as Asian, Hispanic/Latino, or Other. The median annual household income was $32,000. The modal education level for mothers of the evaluated children was partial college completed (35%), and for fathers, it was high school completed (30%). The most common reason for referral was academic problems (e.g., suspected learning disorder), comprising 48.8% of the cases, followed by suspected ADHD (31%). A smaller number of children (10.7%) were referred because of behavior problems (e.g., suspected Oppositional Defiant Disorder) and 8.3% of the sample was evaluated for intellectual giftedness. Ultimately, 23% of the sample received a diagnosis of ADHD, with an additional 3% receiving a likely ADHD diagnosis, indicating that ADHD symptoms were noted and addressed via recommendations, but that a Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR; American Psychiatric Association, 2000) diagnosis was not applied in the report (several reports in our

4 sample identified symptoms in lieu of a formal diagnosis). In addition to children receiving a diagnosis of ADHD, the following diagnoses were also given: Learning Disorders (n ¼ 10), Expressive Language Disorder (n ¼ 1), Developmental Coordination Disorder (n ¼ 1), Conduct Disorder (n ¼ 1), and Oppositional Defiant Disorder (n ¼ 2). In many instances, no diagnosis was given, though the absence of a diagnosis was not taken as equivalent to an absence of clinical difficulties. Information regarding the use of medication was not recorded. Measures E. Arble et al. / Archives of Clinical Neuropsychology 29 (2014) Consecutive cases that included the IVA + Plus and the WISC-IV (Wechsler, 2003) were selected (N ¼ 90). The requirement that the assessment include both the WISC-IV and the IVA + Plus not only restricted the range of ages among the participants, but also ensured that none of the assessments took place before In the case of the WISC-IV, the test is appropriate for children between the ages of 6 and 16. In the case of the IVA + Plus, the clinic did not employ the measure until Teacher ratings of reading performance for the sample were taken from the Teacher Rating Forms (TRFs; Achenbach & Rescorla, 2001), though not all the assessments in our sample included the TRF (n ¼ 65). The TRF asks responding teachers to evaluate a student s academic competence, adaptive functioning, and behavioral and emotional difficulties. The TRF test manual reports internal consistency values for the broad and syndrome scales as ranging between 0.72 and Because the TRF academic ratings consist of a single item for each academic domain, internal consistency cannot be calculated. However, the TRF test manual reports a 16-day test retest reliability value of 0.93 for these ratings of academic competence. Most batteries also included the Child Behavior Checklist (parent ratings of child behavior; CBCL; Achenbach & Rescorla, 2001; n ¼ 82), a measure designed and validated alongside, and ideally used in conjunction with, the TRF. The CBCL manual provides estimates of internal consistency ranging from 0.78 to 0.97 for its major scales. Because cases were selected exclusively upon the presence of the IVA + Plus and the WISC-IV, and because the batteries were designed solely based upon clinical judgment (i.e., subsequent research possibilities were not considered), the present authors exercised no influence over the batteries included measures, as is characteristic of archival research. Results Descriptive Statistics IVA + Plus scores are standardized to have a mean of 100 and a standard deviation of 15. Notably, 10 of 25 of the IVA + Plus mean scores generated in our sample (Table 1) fall one or more standard deviations below the standardization sample s means. In the cases of Auditory and Visual Comprehension, our sample s means fell in the moderately impaired ranges, according to the Interpretation Manual (Sandford & Turner, 2004). Additionally, all but two of the standard deviations produced by our sample were higher than those of the IVA + Plus normative sample, with some over twice the standard sample s. Moreover, failure to achieve a minimum level of performance on the IVA + Plus invalidates particular scores, resulting in 17 of 90 participants (18.8%) having some missing data (as can be seen in Table 1). Thus, all analyses were computed using a list-wise deletion, omitting cases from the analysis if they lacked a valid score in an included variable. Of note, our differences from the standardization sample were expected, given that our sample consisted of clinically referred children. Furthermore, when reviewing clinically referred children, it is expected that profiles indicating various strengths and weaknesses should be observed. Thus, although the Full-Scale Response Control Quotient and Full-Scale Attention Quotient demonstrated modest levels of internal consistency (Cronbach s alpha 0.66 and 0.69, respectively), this is likely a reflection of the discrepant patterns of strengths and weaknesses produced in the current sample. Perhaps also due to the clinical nature of the sample, six IVA + Plus variables required transformation because they deviated substantially from normal distribution: Auditory and Visual Prudence, Auditory and Visual Vigilance, Auditory Sustained Attention Quotient, and Fine Motor Regulation. These scores were logarithmically transformed, resulting in variables that adequately approximated normality (skew ranged from to 0.67, whereas kurtosis ranged from to 0.28). Subsequent to these transformations, it was determined that the sample satisfied all assumptions of normality, as none of the values of skew or kurtosis exceeded 2 (Curran, West, & Finch, 1996). Mean WISC-IV index scores, as well as the FSIQ, ranged from 90.5 to 98.6, and their standard deviations were close to 15 (Table 2). Mean T-scores from the TRF were all below 60, with the exception of the Attention Problems scale (60.7, SD ¼ 7.21). The same pattern was seen with mean CBCL scores, where the only scale above 60 was Attention Problems (64.8, SD ¼ 10.12). Investigations of convergent validity for measures with multiple primary scales usually require the computation of many correlation coefficients. In the following sections, we highlight the correlations that are most relevant to the issue of the IVA + Plus s

5 304 E. Arble et al. / Archives of Clinical Neuropsychology 29 (2014) Table 1. Descriptive statistics for IVA + Plus, WISC-IV, CBCL, and TRF scores Scale name N Minimum Maximum Mean SD Full-Scale Response Control Quotient Auditory Response Control Quotient Visual Response Control Quotient Auditory Prudence Auditory Consistency Auditory Stamina Visual Prudence Visual Consistency Visual Stamina Full-Scale Attention Quotient Auditory Attention Quotient Visual Attention Quotient Auditory Vigilance Auditory Focus Auditory Speed Visual Vigilance Visual Focus Visual Speed Auditory Comprehension Visual Comprehension Auditory Sensory/Motor Visual Sensory/Motor Sustained Auditory Attention Quotient Sustained Visual Attention Quotient Fine Motor Regulation WISC-IV Full-Scale IQ WISC-IV Verbal Comprehension Index WISC-IV Perceptual Reasoning Index WISC-IV Working Memory Index WISC-IV Processing Speed Index CBCL Internalizing Problems CBCL Externalizing Problems CBCL Anxious/Depressed CBCL Withdrawn/Depressed CBCL Somatic Complaints CBCL Social Problems CBCL Thought Problems CBCL Attention Problems CBCL Rule-Breaking Behavior CBCL Aggressive Behavior TRF Internalizing Problems TRF Externalizing Problems TRF Anxious/Depressed TRF Withdrawn/Depressed TRF Somatic Complaints TRF Social Problems TRF Thought Problems TRF Attention Problems TRF Rule-Breaking Behavior TRF Aggressive Behavior Notes: TRF and CBCL scores are T-scores. TRF ¼ Teacher Rating Form; CBCL ¼ Child Behavior Checklist; WISC-IV ¼ Wechsler Intelligence Scale for Children-Fourth Edition. validity. We also note when correlations that were expected did not occur. To protect against the emergence of Type I errors, a significance level of p,.01 was employed. In the present study, findings of meaningful and consistent patterns of correlations in the predicted direction, and consideration of the magnitude of the correlation coefficients, provide evidence regarding the validity of the IVA + Plus.

6 Table 2. Correlations between IVA + Plus and WISC-IV index scores E. Arble et al. / Archives of Clinical Neuropsychology 29 (2014) Full-Scale IQ Verbal Comprehension Index Perceptual Reasoning Index Working Memory Index Processing Speed Index Full-Scale Response Control Quotient.29*.14.27*.40***.12 Auditory Response Control Quotient.29*.16.25*.41***.15 Visual Response Control Quotient.23*.11.23*.33**.06 Auditory Prudence.25*.21.24* Auditory Consistency.32** ***.32** Auditory Stamina Visual Prudence Visual Consistency.29*.22.26*.26*.20 Visual Stamina Full-Scale Attention Quotient.42***.37***.24*.46***.31** Auditory Attention Quotient.26*.23*.07.34**.28* Visual Attention Quotient.47***.42***.34**.47***.24* Auditory Vigilance.23*.25*.04.30**.21 Auditory Focus.29*.13.25*.42***.19 Auditory Speed Visual Vigilance.39***.36**.30**.37***.19 Visual Focus.35**.25*.32**.40***.11 Visual Speed.24*.30* Auditory Comprehension.40***.38***.26*.44***.31** Visual Comprehension.54***.49***.44***.52***.34*** Auditory Sensory/Motor Visual Sensory/Motor Sustained Auditory Attention Quotient *.23* Sustained Visual Attention Quotient.43***.35**.35**.45***.26* Fine Motor Regulation.33**.30**.12.42***.37*** *p,.05. **p,.01. ***p,.001. Consideration of Group Differences To determine if the relationships of the IVA + Plus with the WISC-IV and CBCL were driven by confounding demographic factors, three one-way between-groups MANOVAs were performed. In each case, five global dependent variables were used: WISC-IV FSIQ, CBCL Internalizing, CBCL Externalizing, IVA + Plus Full-Scale Response Control Quotient, and IVA + Plus Full-Scale Attention Quotient. The independent variables employed in these analyses were gender, ethnicity (comparing only Caucasians and African Americans due to the small sample size of the remaining groups), and age (dichotomized into 11 and younger and older than 11 ). Across these tests, the only statistically significant difference was between Caucasian and African-American children on the combined dependent variables: F(5, 56) ¼ 3.04, p ¼.017; Wilk s Lambda ¼ 0.79; partial eta squared ¼ Given that the MANOVA s tests of between-subjects effects involve multiple analyses, we employed a standard Bonferoni adjustment (Tabachnick & Fidell, 1996). When the results for the dependent variables were considered separately, the only difference to reach statistical significance using a Bonferroni adjusted alpha level of 0.01 was FSIQ: F(1, 60) ¼ 8.36, p ¼.005, partial eta squared ¼ Inspection of the mean scores indicated that Caucasian children (M ¼ 100.3, SD ¼ 16.18) demonstrated a higher mean FSIQ than did African-American children (M ¼ 87.64, SD ¼ 14.46). The variables of age, ethnicity, and sex were also examined as potential confounding variables in the relationship between primary scores from the IVA + Plus (i.e., Full-Scale Response Control and the Full-Scale Attention) and those from the WISC-IV FSIQ and the CBCL Withdrawn/Depressed scale, utilizing the Baron and Kenny (1986) method. In all moderation analyses, the addition of the interaction term did not result in a significant change in F-values, and all moderators failed to reach significance (20.60 B 1.12, n.s.). Relations Between IVA + Plus Response Control Scores and WISC-IV Scores The primary IVA + Plus Response Control scores exhibited small to moderate associations with FSIQ in our sample, but these correlations failed to achieve significance at the p,.01 level (Table 2). Significant relations were seen in the case of the WISC-IV

7 306 E. Arble et al. / Archives of Clinical Neuropsychology 29 (2014) Index scores, as IVA + Plus Response Control scores were associated with the WISC-IV WMI, although this was more evident for the Auditory modality than for the Visual. The Full-Scale Response Control Quotient correlated with the WMI at r ¼.40 (p,.001). The Auditory Response Control Quotient correlated quite strongly with the WMI (r ¼.41, p,.001), driven primarily by one of its three components (Consistency), whereas the Visual Response Control Quotient yielded a significant but smaller correlation with the WMI. The IVA + Plus Response Control scores were less strongly related to the other WISC-IV Index scores. Relations Between IVA + Plus Attention Scores and WISC-IV Scores Several significant relations were observed between IVA + Plus Attention scores and FSIQ. The Full-Scale Attention Quotient correlated fairly strongly with FSIQ (r ¼.42, p,.001), driven more by the Visual Attention Quotient than the Auditory Attention Quotient, the latter failing to achieve significance at p,.01 (Table 2). Many of the IVA + Plus Attention scores were associated with the WISC-IV WMI. The Full-Scale Attention Quotient was quite strongly related to the WMI (r ¼.46, p,.001), driven somewhat more by the Visual Attention Quotient than the Auditory Attention Quotient. The PRI was associated with several IVA + Plus Attention scores. A significant correlation was found with the Visual Attention Quotient (r ¼.34, p,.01), as opposed to the Auditory Attention Quotient. The VCI also exhibited associations with IVA + Plus Attention scores. The Full-Scale Attention Quotient correlated with the VCI at r ¼.37 (p,.001), driven by its association with the Visual Attention Quotient. Finally, several smaller but significant associations with the PSI were noted. Relations Between Other IVA + Plus Scores and WISC-IV Scores Additional IVA + Plus scales of interest include the Comprehension scales, identified by Sandford and Turner (2004) as particularly sensitive to ADHD, the Sensory-Motor scale (simple reaction time), Fine Motor Regulation (a potential indicator of hyperactivity), and the Sustained Attention Quotients. Comprehension scores, which reflect idiopathic errors and/or random responding (Sandford & Turner, 2004), were strongly related to FSIQ (Visual, r ¼.54; Auditory, r ¼.40, both ps,.001). The Sensory-Motor scales, in contrast, were unrelated to FSIQ. Fine Motor Regulation was modestly related to FSIQ (r ¼.33, p,.01). Interestingly, the two Sustained Attention Quotients exhibited differing degrees of association with FSIQ, as Visual was quite strongly correlated, whereas Auditory was not. Several of these additional IVA + Plus scales were shown to be strongly associated with some of the WISC-IV Index Scores. Visual Comprehension exhibited the following relations with the four WISC-IV Indexes: VCI, r ¼.49; PRI, r ¼.44; WMI, r ¼.52; PSI, r ¼.34 (all ps,.001). The corresponding associations for Auditory Comprehension were not as strong, but followed a similar pattern: VCI, r ¼.38 (p,.001); WMI, r ¼.44 (p,.001); PSI, r ¼.31 (p,.01). The Sensory-Motor scales were unrelated to the four WISC-IV Index scores, but Fine Motor Regulation showed appreciable relations with VCI, WMI, and PSI. Finally, given their differential associations with FSIQ, the Sustained Attention Quotient s correlations were unsurprising. For the Auditory Sustained Attention Quotient, there were only small associations with WMI and PSI, whereas for Visual Sustained Attention significant correlations were observed with the VCI and PRI. Relations Between IVA + Plus Scores and CBCL Scores IVA + Plus scores were compared with parental ratings of their children s behavior as measured by the CBCL (Achenbach & Rescorla, 2001). There were no associations with the CBCL Internalizing and Externalizing scales (Table 3). Similarly, correlations with the Withdrawn/Depressed Syndrome scale failed to achieve significance at the p,.01 level. These associations indicate that children who were rated by their parents as more withdrawn and/or depressed trended toward poorer response control during the IVA + Plus task, but the strength of this association is tenuous. None of the remaining correlations between IVA + Plus score and CBCL scores achieved significance at p,.01. Relations Between IVA + Plus Response Control Scores and TRF Scores We correlated teacher ratings of children s classroom behaviors with the same set of IVA + Plus scores (Table 3). None of the IVA + Plus Response Control scores were significantly related to the TRF (Achenbach & Rescorla, 2001) Externalizing or Internalizing scores. Similarly, the primary Response Control scores were for the most part unrelated to TRF Syndrome Scale Scores, with the important exception of the Withdrawn/Depressed scale. The Withdrawn/Depressed scale s correlations with the Full-Scale Response Control Quotient and the Auditory Response Control Quotient were as follows (respectively): r ¼ 2.45, p,.001; r ¼ 2.48, p,.001. The direction of these substantial correlations indicates more depressive symptoms among children who responded impulsively on the IVA + Plus.

8 Table 3. Correlations between IVA + Plus and CBCL/ TRF scores Internalizing problems Externalizing problems Anxious/ depressed Withdrawn/ depressed Somatic complaints Social problems Thought problems Attention problems Rule-breaking behavior Aggressive behavior Full-Scale Response 2.14/ / / */2.45*** 2.05/ / / / / /2.05 Control Auditory Response 2.13/2.28* 2.05/ / */2.48*** 2.06/ / / / / /2.06 Control Quotient Visual Response 2.13/ / / */2.34* 2.04/ / / */ /.01.00/2.02 Control Quotient Auditory Prudence 2.11/ / / /2.34* 2.03/ / / / / /.07 Auditory Consistency 2.02/ / / / / / /.01.02/ / /2.11 Auditory Stamina 2.07/ / / /2.33* 2.09/ / / / / /2.02 Visual Prudence 2.05/ / / /2.32* 2.02/ / / / / /.01 Visual Consistency 2.14/ / / / / / / / / /2.08 Visual Stamina 2.06/.08.02/ / / / / / / /.01.09/.03 Full-Scale Attention.09/ / / /.04.13/.14.05/ / / / /2.11 Quotient Auditory Attention.10/ / /.09.02/.06.13/.19.07/ / / / /2.16 Quotient Visual Attention.07/.07.03/ */ /.01.09/.05.04/ / /.07.05/.01.05/2.03 Quotient Auditory Vigilance.10/ / /.06.05/.18.18/.18.11/ / / / /2.14 Auditory Focus 2.12/ /.07.07/ /2.40** 2.15/ / / / / /.02 Auditory Speed.22/.31* 2.08/ /.18.16/.28*.19/.33*.13/ / / / /2.19 Visual Vigilance 2.01/.12.03/.03.20/ /.12.01/.04.03/ / /.17.00/.01.06/.02 Visual Focus 2.04/ / / /2.36**.03/ /2.29* 2.05/ / / /2.10 Visual Speed.15/ / /.21.13/.11.17/.30*.09/ / / / /2.08 Auditory 2.01/ /2.26* 2.12/ /2.28* 2.00/ / / /2.28*.02/ /2.19 Comprehension Visual Comprehension.06/ / / /2.25*.04/.02.01/ / / / /2.10 Auditory Sensory/.12/.30* 2.04/.00.11/.22.22/.27* 2.06/ /.10.13/.12.01/.11.03/.00.03/.16 Motor Visual Sensory /Motor 2.13/ / */ / / / / / / /2.21 Sustained Auditory.04/ / / / / / / / / /2.15 Attention Quotient Sustained Visual.14/.10.07/.02.25*/ /.03.13/.02.07/ / /.11.09/.04.09/2.02 Attention Quotient Fine Motor Regulation.00/ / /.12.00/ / / / / / /2.15 *p,.05. **p,.01. ***p,.001. E. Arble et al. / Archives of Clinical Neuropsychology 29 (2014) Downloaded from at Wayne State University on May 8, 2014

9 308 E. Arble et al. / Archives of Clinical Neuropsychology 29 (2014) Relations Between IVA + Plus Attention Scores and TRF Scores Most IVA + Plus Attention scores were unrelated to the TRF Internalizing and Externalizing scores, although some components of the Attention Quotients showed associations with TRF Syndrome scores. Auditory Focus (variability in reaction time) correlated with the Withdrawn/Depressed scale, as did the Visual Focus scale. These findings indicate unreliable or erratic reaction times among children rated by teachers as withdrawn and/or depressed. Relations Between Other IVA + Plus Scores and TRF Scores Only a few significant but small correlations occurred between the other IVA + Plus scores and any TRF scores (Table 3). Relations Between IVA Scores and Academic Performance Controlling for IQ TRF forms provide ratings of scholastic performance in several primary academic subjects. This afforded the ability to examine the degree to which IVA + Plus scores could predict teacher ratings of academic performance beyond the variance explained by IQ (i.e., incremental validity). The academic subjects for which we had the most complete data were math (n ¼ 52) and reading (n ¼ 41). Zero-order correlations between TRF academic performance ratings and IVA scores are presented in Table 4. Significant IVA + Plus correlations occurred more frequently with Math performance than with Reading, but both IVA + Plus scores tapping inattention and those designed to capture impulsivity showed associations with academic performance, as did some Attribute scores such as Comprehension. The most robust associations, where an IVA + Plus score was significantly correlated with both Reading and Math, were with the Comprehension and Focus scores. We conducted two hierarchical regressions predicting Reading, and two predicting Math, each time controlling for IQ by entering it in the first step, followed by the IVA + Plus scores of interest in the second step. In predicting Reading performance, the combination of the IVA + Plus Auditory (beta ¼ 0.159, t ¼ 0.816, n.s.) and Visual (beta ¼ 0.044, t ¼ 0.215, n.s.). Comprehension scores did not explain significant variance beyond the large contribution of IQ (beta ¼ 0.615, t ¼ 4.800, p,.001). In the second regression equation predicting Reading performance, the two Focus scores were unable to add significant Table 4. Correlations between IVA + Plus and TRF ratings of academic performance Reading Full-Scale Response Control Quotient.07.32* Auditory Response Control Quotient.12.33* Visual Response Control Quotient Auditory Prudence Auditory Consistency Auditory Stamina Visual Prudence Visual Consistency Visual Stamina Full-Scale Attention Quotient Auditory Attention Quotient Visual Attention Quotient.30.33* Auditory Vigilance Auditory Focus.27.38* Auditory Speed * Visual Vigilance Visual Focus.38*.41** Visual Speed Auditory Comprehension.33*.36** Visual Comprehension.40*.41** Auditory Sensory/Motor Visual Sensory/Motor Sustained Auditory Attention Quotient Sustained Visual Attention Quotient Fine Motor Regulation Math *p,.05. **p,.01.

10 E. Arble et al. / Archives of Clinical Neuropsychology 29 (2014) predictive ability beyond IQ (Auditory Focus: beta ¼ , t ¼ , n.s.; Visual Focus: beta ¼ 0.238, t ¼ 1.199, n.s.; FSIQ: beta ¼ 0.574, t ¼ 3.786, p,.001). Similar results occurred when predicting Math performance from Comprehension and IQ scores (Auditory Comprehension: beta ¼ 0.007, t ¼ 0.039, n.s.; Visual Comprehension: beta ¼ 0.150, t ¼ 0.774, n.s.; FSIQ: beta ¼ 0.575, t ¼ 4.736, p,.001), and when predicting Math performance from Focus and IQ scores (Auditory Focus: beta ¼ 0.201, t ¼ 1.250, n.s.; Visual Focus: beta ¼ 0.038, t ¼ 0.230, n.s.; FSIQ: beta ¼ 0.611, t ¼ 4.941, p,.001). Discussion Based on our sample of clinically referred, urban children and adolescents, we found modest supportive evidence for the convergent and discriminant validity of several key scores from the IVA + Plus CPT of sustained behavior and attention regulation. In support of the IVA + Plus validity, variance attributable to the WMI accounted for 16% of the variance in the Full-Scale Response Control Quotient scores, and 21% of the variance in Full-Scale Attention Quotient scores. However, IVA + Plus Response Control scores were not significantly related to PSI scores, and IVA + Plus Attention scores produced small correlations with the PSI, sharing about 6% 10% of its variance. Overall, these findings are supportive of the validity of the IVA + Plus, as children with poorer working memory, measured with a well-validated index of attention and concentration (Weiss, Saklofske, & Prifitera, 2005), tended to have poorer performances on the IVA + Plus, at least when primary IVA + Plus scores were examined. Similarly, children with slower processing speed, which in part reflects sustained attention and has been shown to be diminished in children with ADHD (Wechsler, 2003), also demonstrated poorer performance on the IVA + Plus, although to a lesser degree than those with lower working memory scores. However, IVA + Plus scores were also associated with WISC-IV FSIQ scores, particularly in regard to the Attention scales. FSIQ accounted for nearly 18% of the variance in the IVA + Plus Full-Scale Attention Quotient, and about 8% of the variance in the Full-Scale Response Control Quotient. This indicates that having high general intelligence may confer an advantage for children on the IVA + Plus, especially when it comes to the Attention scales, and suggests that the IQ of the examinee should be taken into consideration when IVA + Plus scores are interpreted. The IVA + Plus Interpretation Manual does recommend this, but specifies that the adjustment should be based on the examinee s Performance IQ. The test developers suggest that examiners should consider comparing examinees with very high Performance IQ s to an older bracket of the normative sample (i.e., enter an older chronological age for the client into the scoring program so as to compare with mental age peers; Sandford & Turner, 2004, p. 79). For examinees with low Performance IQ s, a similar adjustment in the opposite direction is recommended by the test authors. We agree with Riccio, Reynolds, and Lowe (2001) that this method may be questionable, as it seems more based in clinical judgment than in empirical research, but our findings do suggest that clinicians should keep the child s FSIQ in mind when evaluating IVA + Plus scores. Furthermore, such advice appears highly congruent with the DSM s recommendation to account for a child s developmental level before arriving at a diagnosis of ADHD. Nevertheless, evidence suggesting some merit in highlighting the PIQ (represented in the WISC-IV by the PRI) was seen in significant correlations with several IVA + Plus Attention Quotient scores. When secondary IVA + Plus scores were examined, several additional strong associations with FSIQ were observed. Most notably, FSIQ accounted for 29% of the variance in the IVA + Plus Visual Comprehension score. This correlation (r ¼.54) approaches the typical degree of association between IQ scores and criterion measures (Meyer et al., 2001; Wechsler, 2003). The IVA + Plus developers indicate that Comprehension scores reflect unusual errors of omission and commission and suggest that moderately low Comprehension scores may be indicative of ADHD, whereas very low scores on these scales result from random responding. Our results further suggest that very low IVA + Plus Comprehension scores may not be unexpected when examinee IQ is low. Indeed, Comprehension scores were found to be predictive of performance on math and reading (rated by teachers), but these associations were eliminated when IQ was controlled for. The issue is complicated by our recognition that IQ CPT relations occur in both directions, so that the IVA + Plus is not an entirely intelligence-free instrument, but IQ tests also are not attention and impulsivity-free. That the association between IVA + Plus Comprehension scores and teacher-rated performance on math and reading disappeared when controlling for IQ is interesting, but need be tempered by the recognition that teacher ratings do not offer a perfect analog to actual student performance. The TRF offers the teacher s assessment of the student s performance at that time and does not indicate that the child will not improve (indeed, an assessment of the child as performing below average likely prompts an intervention in the hopes of improving performance). Further, a child s academic performance is not always a reflection of ability and may instead reflect low motivation, disinterest, concerns at home, or any other number of circumstances that could change. Nonetheless, academic ratings on the TRF have been found to discriminate between children referred for mental health services and demographically similar children who were not clinically referred (Achenbach & Rescorla, 2001) and appear predictive of academic performance even in subsequent years (Teisl, Mazzocco, & Myers, 2001).

11 310 E. Arble et al. / Archives of Clinical Neuropsychology 29 (2014) Errors of omission and commission during the IVA + Plus task showed an interesting pattern of relations with WISC-IV scores. Prudence scores (errors of commission) were largely unrelated to WISC-IV FSIQ and the four Index scores, indicating that the ability to refrain from impulsive responding did not differ by the intelligence level in our sample. The expected associations with the WMI and PSI were not seen. On the other hand, errors of omission (Vigilance) showed more evidence of overlap with intellectual abilities, especially in the visual modality, where 15% of the variance was accounted for by FSIQ. This may indicate that good performance on the tasks that comprise the WISC-IV requires more vigilance (alertness, attentiveness) than ability to inhibit impulsive responding. An additional prediction we made was that a pattern of associations would be seen whereby visual IVA + Plus scores and visual WISC-IV indices (PRI, PSI) would tend to be related, whereas auditory IVA + Plus scores would be more strongly related to auditory WISC-IV indices (VCI, WMI). Support for this hypothesis was mixed. The Auditory Attention Quotient s only correlation achieving significance at p,.01 was with the WMI, and the same pattern was observed with the Auditory Response Control Quotient. However, although the Visual Response Control Quotient only demonstrated a significant relationship with the WMI, the Visual Attention Quotient was more strongly correlated with the VCI than with the PRI or the PSI. The Comprehension scales typified our mixed results, as Auditory Comprehension was most strongly associated with the WMI and the VCI (expected), but the same pattern occurred for Visual Comprehension (an unexpected finding). Overall, having strong working memory conferred an advantage in IVA + Plus performance more for the auditory modality than for the visual when it came to the Quotient scores, but not for the secondary scores. The fact that auditory working memory was associated with both auditory and visual IVA + Plus scores may be seen as consistent with a growing body of evidence that attentional resources are central or supramodal, so that differing CPT performances across modalities would not necessarily be expected (Borgaro et al., 2003; Cacace & McFarland, 2006; Shalev, Ben-Simon, Mevorach, Cohen, & Tsal, 2011). We expected that additional evidence for the IVA + Plus s validity would be seen in associations with behavioral checklist scores from parents and teachers. However, little convergent validity evidence was found, as none of the associations achieved significance at p,.01. Several significant correlations between the CBCL/TRF Withdrawn/Depressed scale and IVA + Plus Response Control scores occurred, indicating that children rated by parents or teachers as withdrawn and/or depressed were likely to exhibit impulsivity on the IVA + Plus. Examination of secondary IVA + Plus scores revealed an inconsistent pattern of associations with CBCL and TRF scores. Studies reporting a lack of convergence between performance on tests of executive functioning and behavioral ratings are appearing more frequently in the literature (Barkley & Murphy, 2010), even in samples of patients with frontal lobe lesions or traumatic brain injuries. Barkley and colleagues argue that measuring ratings of executive functioning may be more informative than measuring performance on executive functioning tests, because ratings may be more strongly associated with outcomes (e.g., occupational functioning). These authors call into question the ecological validity of tests of executive functioning. According to this perspective, the fact that we found little convergence between IVA + Plus scores and ratings made by parents and teachers is reasonable, because these two assessment methods tap different levels in the hierarchical organization of executive functioning (Barkley & Murphy, 2010). Clinically, therefore, when performance on a CPT is within normal limits, but behavioral ratings by parents, teacher, or self-report are suggestive of ADHD (assuming that there is no reason to question the validity of these behavioral ratings), it would be advisable to place more weight on the checklist evidence than on the CPT results when formulating a diagnosis, especially if the client has a higher IQ. It may be that the client s good performance on the CPT represents the upper bounds of his/her ability to sustain attention and refrain from impulsive responding (for roughly 15 min) and that this optimal level of performance was made possible due to the novelty and/or structure of the testing situation (Jepsen, Fagerlund, & Mortensen, 2009), the one-on-one attention provided by the examiner, or higher motivation than is typical in other settings where the ADHD symptoms have been observed (Schuck & Crinella, 2005). Conversely, if CPT performance is poor, but there is little observational or rating scale evidence for ADHD features, then a variety of other explanations for the low CPT scores must be ruled out, including inadequate effort during the test (Quinn, 2003). Our findings indicate that low IQ should be considered and that depressed mood may also impair performance on a CPT (Sandford & Turner, 2004), but few published studies of children have addressed this. In a review, Riccio, Reynolds, and Lowe (2001) concluded that, although virtually any childhood disorder that compromises the integrity or function of the central nervous system is likely to impair CPT performance, these authors also stress that CPTs tend not to be sensitive to disorders of mood or affect, barring the presence of mania or psychosis. In the present study, one small correlation (r ¼.26) indicated better Visual Attention performance on the IVA + Plus in children with parent-rated anxiety/depression, and slower simple reaction time in the visual modality. More notably, as mentioned above, we found a pattern of correlations, indicating that children rated by parents as being withdrawn and/or depressed tended to perform poorly on some IVA + Plus scales (most appreciably on several Response Control scales), and those rated as withdrawn/depressed by teachers also had considerably lower Response Control scores and more variable focus in terms of reaction times. Although an association between depression and increased impulsivity may seem counter-intuitive, we wonder whether or not the presence of depressive symptoms interfered with examinees

12 E. Arble et al. / Archives of Clinical Neuropsychology 29 (2014) effort or motivation, resulting in failures to inhibit responding. More research is clearly needed on the question of how mood symptoms may affect performance on CPTs. We agree with the developers of the IVA + Plus that it can be helpful to ask examinees a few questions about their experience during the test ( Did you try very hard to do your best on this test? Were you confused about when it was correct to click the mouse? ) in order to more fully interpret their scores. It is also important to observe the examinee carefully while he or she is performing the CPT task. Sandford (1994) has developed two brief checklists for these purposes (one is self-report and the other is an examiner-completed behavior rating scale), although research on their psychometric properties is needed. Response inhibition, vigilance/sustained attention, and working memory are among the strongest and most consistent executive functioning deficits associated with ADHD (Wilcutt, Pennington, Olson, Chhabildas, & Hulslander, 2005). Thus, our findings on the whole are supportive of the IVA + Plus validity, as a consistent pattern of substantial associations occurred between many of the IVA + Plus primary scores and working memory as measured by the WISC-IV. Our findings also allow us to assume some degree of reliability for many of the IVA + Plus scores, as the pattern of associations with WISC-IV scores indicates a level of consistency of measurement. The relations we documented with FSIQ, a very stable measure of intelligence (Bartoi et al., in press), imply that IVA + Plus scores such as the Visual Attention Quotient, the Visual Sustained Attention Quotient, and Visual Comprehension are themselves likely to be relatively stable. The IVA + Plus Interpretation Manual (Sandford & Turner, 2004) presents test retest data (1 4-week interval) that are consistent with this suggestion, as Attention scores tended to be more temporally stable than Response Control scores. Our use of archival clinical assessment data did not permit us to examine issues of diagnostic utility with respect to IVA + Plus scores. This is because the IVA + Plus data we investigated were part of the assessment information used by clinicians in formulating their clients diagnoses, rendering any tests of the IVA + Plus accuracy tautological. More research on the ability of the IVA + Plus to correctly classify children (and adults) with ADHD is needed, and we strongly recommend that these investigations test the IVA + Plus capacity to discriminate those with ADHD from members of other diagnostic groups (e.g., individuals with mood disorders, learning disorders, TBI), rather than from healthy controls. Further, future research would do well to examine the IVA + Plus relation with other important measures of interest (e.g., a second CPT, tests of executive functioning), as well as to investigate if these relationships are consistent across various demographic groups. Finally, there are many additional secondary and supplemental IVA + Plus scores that we did not examine (Sandford & Turner, 2004). We focused on the main scores that other studies have reported on, and several additional scores that had received less attention in the literature (e.g., Comprehension), but space considerations did not permit the examination of other IVA + Plus scores that might have allowed better understanding of the IVA + Plus s psychometric properties. Similarly, analyses of the relations between WISC-IV subtests and IVA + Plus scores would provide a more fine-grained picture in terms of which abilities each IVA + Plus score is likely to be tapping. In light of these knowledge gaps, along with the recognized limits on diagnostic sensitivity and specificity and ecological validity that apply to any CPT, clinical users of the IVA + Plus must remain attentive to these considerations. Funding Funding for the present research was provided by the Wayne State University Psychology Department. Conflict of Interest None declared. Acknowledgements We would like to express our heartfelt appreciation to Lesley A. Hetterscheidt and Lynn Shaouni for their assistance with this project. References Achenbach, T. M., & Rescorla, L. A. (2001). Manual for the ASEBA school-age forms and profiles. Burlington, VT: University of Vermont, Research Center for Children, Youth, & Families. Alloway, T. P., Gathercole, S. E., Holmes, J., Place, M., Elliott, J. G., & Hilton, K. (2009). The diagnostic utility of behavioral checklists in identifying children with ADHD and children with working memory deficits. Child Psychiatry and Human Development, 40, American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: Author. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: Author.

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