Visual Attention and Math Performance in Survivors of Childhood Acute Lymphoblastic Leukemia

Visual Attention and Math Performance in Survivors of Childhood Acute Lymphoblastic Leukemia Abstract Objective Attentional and academic difficulties, particularly in math, are common in survivors of childhood acute lymphoblastic leukemia (ALL). Of cognitive deficits experienced by survivors of childhood ALL, attention deficits may be particularly responsive to intervention. However, it is unknown whether deficits in particular aspects of attention are associated with deficits in math skills. The current study investigated relationships between math calculation skills, performance on an objective measure of sustained attention, and parent- and teacher-reported attention difficulties. Method Twenty-four survivors of childhood ALL (Mage = 13.5 years, SD= 2.8 years) completed a computerized measure of sustained attention and response control and a written measure of math calculation skills in the context of a comprehensive clinical neuropsychological evaluation. Parent and teacher ratings of inattention and impulsivity were obtained. Results Visual response control and visual attention accounted for 26.4% of the variance observed among math performance scores after controlling for IQ (p < .05). Teacher-rated, but not parent-rated, inattention was significantly negatively correlated with math calculation scores. Conclusions Consistency of responses to visual stimuli on a computerized measure of attention is a unique predictor of variance in math performance among survivors of childhood ALL. Objective testing of visual response control, rather than parent-rated attentional problems, may have clinical utility in identifying ALL survivors at risk for math difficulties. Attention, Leukemia, Mathematical and numerical skills, Pediatric Introduction Prevalence of childhood cancer survivors in the US has been recently estimated at over 350,000, with 35% of those individuals experiencing neurocognitive dysfunction (Phillips et al., 2015). Deficits in academic performance, particularly math, are among the more commonly reported neurocognitive difficulties among childhood cancer survivors. Among survivors of acute lymphoblastic leukemia (ALL), the most common childhood cancer, math deficits are the most commonly reported academic deficit (Brown et al., 1992, 1996; Brown, Sawyer, Antoniou, Toogood, & Rice, 1999; Moore et al., 2000; Mulhern, Fairclough, & Ochs, 1991; Ochs et al., 1991; Peckham & Meadows, 1988). Attention deficits are also common among survivors of childhood ALL (Buizer, De Sonneville, Van Den Heuvel-Eibrink, & Veerman, 2005; Campbell et al., 2007). Relationships between math performance and attention have been observed among survivors of childhood ALL. These include a relationship between objective math performance and auditory (Kaemingk, Carey, Moore, Herzer, & Hutter, 2010) and visual working memory (Barnes et al., 2014), and relationships between parent-rated attentional difficulties, objective testing of visual sustained attention, and teacher-rated math ability (Buizer, De Sonneville, Van Den Heuvel-Eibrink, & Veerman, 2006). Furthermore, smaller white matter volumes have been found to be correlated with both visual sustained attention and math deficits among survivors of childhood ALL (Reddick et al., 2006). This suggests a common neurophysiological factor underlying deficits in both attention and math performance, specifically the negative impact of cancer treatment on CNS white matter volumes. However, although deficits have been documented on measures of both visual (Buizer et al., 2005; Campbell et al., 2007) and auditory attention (Campbell et al., 2007), it is unknown whether deficits in particular aspects of attention are associated with deficits in math skills among survivors of childhood ALL. When assessing cognitive and academic difficulties, parent report measures are frequently used for logistical reasons including relative ease of administration in comparison to objective cognitive testing. However, brief, objective cognitive testing may be more accurate in identifying cognitive and academic difficulties. Specifically, an investigation of reliability and validity of brief neurocognitive screening for survivors of childhood ALL showed that objective neurocognitive testing accurately predicted IQ as well as reading and math performance; in contrast, parent report did not accurately predict IQ or academic skills (Krull et al., 2008). Interventions focused on improving academic skills have generally targeted academic skills directly. A recent trial demonstrated that among childhood ALL survivors who had not yet demonstrated math deficits, individual math instruction resulted in improved math performance among survivors who received the instruction, and better performance compared to survivors who did not receive instruction (Moore, Hockenberry, Anhalt, McCarthy, & Krull, 2012). Although interventions aimed at improving math skills may be effective, a notable limitation is that these interventions may not generalize to other academic, behavioral, or social difficulties. Should relationships between math skills and earlier-developing, underlying cognitive skills be elucidated, this could create potential for pre-emptive treatment of underlying cognitive difficulties before math and other difficulties become apparent. The current study aimed to further investigate potential relationships between attention and math performance among survivors of childhood ALL. To this end, retrospective review of comprehensive neuropsychological evaluation results was conducted for 24 survivors of childhood ALL who had been referred due to cognitive or academic concerns. Relationships between objective measures of math calculation skills and visual and auditory sustained attention and response control, as well as parent- and teacher-reported inattention, were examined. It was hypothesized that performance on objective measures of sustained attention and parent- and teacher-reported inattention would explain a significant amount of the variance in math skills among survivors of childhood ALL, given their expected level of performance based on measured IQ. Methods Participants Retrospective record review was conducted for 24 children and adolescents (11 male, 13 female) ages 8–18 years. All participants had undergone comprehensive neuropsychological evaluation at a regional academic medical center between April 2008 and August 2016, and had been referred by a physician for cognitive or academic concerns. All patients carried a historical diagnosis of ALL and received chemotherapy treatment as usual. Exclusion criteria included a history of radiation treatment or hematopoetic cell transplant, due to associated risk of adverse effects on cognitive functioning. Twenty-three patients were status post-treatment, and one was receiving maintenance chemotherapy at the time of the evaluation. Three participants were prescribed psychoactive medications at the time of testing: one participant was taking a selective serotonin reuptake inhibitor (sertraline) and a psychostimulant medication (methylphenidate), one was taking an anticonvulsant medication (valproate) and an antipsychotic medication (paliperidone) and one was taking a psychostimulant medication only (dexmethylphenidate). All participants took their regular medications as prescribed on the day of testing. See Table 1 for participant demographics. Table 1. Participant demographic characteristics and standardized test scores Variable  M  SD  Range  Correlation with WJ Calculation  Age at testing (years)  13.5  2.8  8.6–18.4  −.03  Age at diagnosis  3.9  2.8  1.5–15.0  −.15  Time since treatmenta  6.6  2.9  1.0–11.0  .12  Wechsler IQ   FSIQ  97.0  12.9  71–125  .18   VCI  99.7  10.9  78–121  .12   PRI  99.3  14.8  69–136  .21   WMI  97.0  11.2  74–116  .20   PSI  91.2  14.0  65–112  .05  WJ Calculation  103.5  15.9  78–139  —  IVA   Full Scale Attention  75.0  26.5  18–118  .29    Auditory Attention  75.8  23.9  29–108  .23     Auditory Vigilance  78.8  28.0  13–109  .24     Auditory Focus  76.9  19.4  39–116  .06     Auditory Speed  103.5  14.1  76–128  .23    Visual Attention  82.5  23.2  34–123  .29*     Visual Vigilance  84.3  24.8  22–112  .23     Visual Focus  88.5  18.3  42–125  .29*     Visual Speed  94.1  14.1  72–120  .24   Full Scale Response Control  80.5  23.0  7–108  .22    Auditory Response Control  76.3  23.7  13–111  .21     Auditory Prudence  75.7  25.0  17–114  .12     Auditory Consistency  77.7  18.8  19–103  −.004     Auditory Stamina  100.1  22.2  61–148  .22    Visual Response Control  89.9  20.4  29–119  .36*     Visual Prudence  91.3  18.9  41–121  .15     Visual Consistency  92.4  19.1  40–117  .31*     Visual Stamina  96.6  17.2  68–125  .21  Conners-3 Parent   Inattention  59.2  15.0  39–87  −.08   Hyperactivity/Impulsivity  50.0  11.1  41–78  −.01   Learning Problems  60.1  14.8  39–93  −.27   Executive Functioning  58.4  13.4  39–90  .02  Conners-3 Teacher   Inattention  55.9  19.0  40–90  −.39*   Hyperactivity/Impulsivity  57.3  19.4  42–98  −.22   Learning Problems  54.4  15.3  41–86  −.41*   Executive Functioning  54.8  15.3  41–86  −.44*  Variable  M  SD  Range  Correlation with WJ Calculation  Age at testing (years)  13.5  2.8  8.6–18.4  −.03  Age at diagnosis  3.9  2.8  1.5–15.0  −.15  Time since treatmenta  6.6  2.9  1.0–11.0  .12  Wechsler IQ   FSIQ  97.0  12.9  71–125  .18   VCI  99.7  10.9  78–121  .12   PRI  99.3  14.8  69–136  .21   WMI  97.0  11.2  74–116  .20   PSI  91.2  14.0  65–112  .05  WJ Calculation  103.5  15.9  78–139  —  IVA   Full Scale Attention  75.0  26.5  18–118  .29    Auditory Attention  75.8  23.9  29–108  .23     Auditory Vigilance  78.8  28.0  13–109  .24     Auditory Focus  76.9  19.4  39–116  .06     Auditory Speed  103.5  14.1  76–128  .23    Visual Attention  82.5  23.2  34–123  .29*     Visual Vigilance  84.3  24.8  22–112  .23     Visual Focus  88.5  18.3  42–125  .29*     Visual Speed  94.1  14.1  72–120  .24   Full Scale Response Control  80.5  23.0  7–108  .22    Auditory Response Control  76.3  23.7  13–111  .21     Auditory Prudence  75.7  25.0  17–114  .12     Auditory Consistency  77.7  18.8  19–103  −.004     Auditory Stamina  100.1  22.2  61–148  .22    Visual Response Control  89.9  20.4  29–119  .36*     Visual Prudence  91.3  18.9  41–121  .15     Visual Consistency  92.4  19.1  40–117  .31*     Visual Stamina  96.6  17.2  68–125  .21  Conners-3 Parent   Inattention  59.2  15.0  39–87  −.08   Hyperactivity/Impulsivity  50.0  11.1  41–78  −.01   Learning Problems  60.1  14.8  39–93  −.27   Executive Functioning  58.4  13.4  39–90  .02  Conners-3 Teacher   Inattention  55.9  19.0  40–90  −.39*   Hyperactivity/Impulsivity  57.3  19.4  42–98  −.22   Learning Problems  54.4  15.3  41–86  −.41*   Executive Functioning  54.8  15.3  41–86  −.44*  Note: Correlations are Pearson’s r coefficients. *p< .05 **p< .01. M = mean; SD = standard deviation; FSIQ = Full Scale Intelligence Quotient; VCI = Verbal Comprehension Index; PRI = Perceptual Reasoning Index; WMI = Working Memory Index; PSI = Processing Speed Index; WJ = Woodcock Johnson Tests of Achievement 3rd edition; IVA = Integrated Visual and Auditory Continuous Performance Test. FSIQ, VCI, PRI, WMI, and PSI refer to respective WISC-IV or WAIS-IV FSIQ, VCI, PRI, WMI, and PSI. Wechsler, WJ, and IVA scores are standard scores with M = 100 and SD = 15. Conners-3 Parent and Teacher scores are T-scores with M = 50 and SD = 10. aTime since completion of chemotherapy for 23 patients who had completed treatment at the time of the evaluation. Table 1. Participant demographic characteristics and standardized test scores Variable  M  SD  Range  Correlation with WJ Calculation  Age at testing (years)  13.5  2.8  8.6–18.4  −.03  Age at diagnosis  3.9  2.8  1.5–15.0  −.15  Time since treatmenta  6.6  2.9  1.0–11.0  .12  Wechsler IQ   FSIQ  97.0  12.9  71–125  .18   VCI  99.7  10.9  78–121  .12   PRI  99.3  14.8  69–136  .21   WMI  97.0  11.2  74–116  .20   PSI  91.2  14.0  65–112  .05  WJ Calculation  103.5  15.9  78–139  —  IVA   Full Scale Attention  75.0  26.5  18–118  .29    Auditory Attention  75.8  23.9  29–108  .23     Auditory Vigilance  78.8  28.0  13–109  .24     Auditory Focus  76.9  19.4  39–116  .06     Auditory Speed  103.5  14.1  76–128  .23    Visual Attention  82.5  23.2  34–123  .29*     Visual Vigilance  84.3  24.8  22–112  .23     Visual Focus  88.5  18.3  42–125  .29*     Visual Speed  94.1  14.1  72–120  .24   Full Scale Response Control  80.5  23.0  7–108  .22    Auditory Response Control  76.3  23.7  13–111  .21     Auditory Prudence  75.7  25.0  17–114  .12     Auditory Consistency  77.7  18.8  19–103  −.004     Auditory Stamina  100.1  22.2  61–148  .22    Visual Response Control  89.9  20.4  29–119  .36*     Visual Prudence  91.3  18.9  41–121  .15     Visual Consistency  92.4  19.1  40–117  .31*     Visual Stamina  96.6  17.2  68–125  .21  Conners-3 Parent   Inattention  59.2  15.0  39–87  −.08   Hyperactivity/Impulsivity  50.0  11.1  41–78  −.01   Learning Problems  60.1  14.8  39–93  −.27   Executive Functioning  58.4  13.4  39–90  .02  Conners-3 Teacher   Inattention  55.9  19.0  40–90  −.39*   Hyperactivity/Impulsivity  57.3  19.4  42–98  −.22   Learning Problems  54.4  15.3  41–86  −.41*   Executive Functioning  54.8  15.3  41–86  −.44*  Variable  M  SD  Range  Correlation with WJ Calculation  Age at testing (years)  13.5  2.8  8.6–18.4  −.03  Age at diagnosis  3.9  2.8  1.5–15.0  −.15  Time since treatmenta  6.6  2.9  1.0–11.0  .12  Wechsler IQ   FSIQ  97.0  12.9  71–125  .18   VCI  99.7  10.9  78–121  .12   PRI  99.3  14.8  69–136  .21   WMI  97.0  11.2  74–116  .20   PSI  91.2  14.0  65–112  .05  WJ Calculation  103.5  15.9  78–139  —  IVA   Full Scale Attention  75.0  26.5  18–118  .29    Auditory Attention  75.8  23.9  29–108  .23     Auditory Vigilance  78.8  28.0  13–109  .24     Auditory Focus  76.9  19.4  39–116  .06     Auditory Speed  103.5  14.1  76–128  .23    Visual Attention  82.5  23.2  34–123  .29*     Visual Vigilance  84.3  24.8  22–112  .23     Visual Focus  88.5  18.3  42–125  .29*     Visual Speed  94.1  14.1  72–120  .24   Full Scale Response Control  80.5  23.0  7–108  .22    Auditory Response Control  76.3  23.7  13–111  .21     Auditory Prudence  75.7  25.0  17–114  .12     Auditory Consistency  77.7  18.8  19–103  −.004     Auditory Stamina  100.1  22.2  61–148  .22    Visual Response Control  89.9  20.4  29–119  .36*     Visual Prudence  91.3  18.9  41–121  .15     Visual Consistency  92.4  19.1  40–117  .31*     Visual Stamina  96.6  17.2  68–125  .21  Conners-3 Parent   Inattention  59.2  15.0  39–87  −.08   Hyperactivity/Impulsivity  50.0  11.1  41–78  −.01   Learning Problems  60.1  14.8  39–93  −.27   Executive Functioning  58.4  13.4  39–90  .02  Conners-3 Teacher   Inattention  55.9  19.0  40–90  −.39*   Hyperactivity/Impulsivity  57.3  19.4  42–98  −.22   Learning Problems  54.4  15.3  41–86  −.41*   Executive Functioning  54.8  15.3  41–86  −.44*  Note: Correlations are Pearson’s r coefficients. *p< .05 **p< .01. M = mean; SD = standard deviation; FSIQ = Full Scale Intelligence Quotient; VCI = Verbal Comprehension Index; PRI = Perceptual Reasoning Index; WMI = Working Memory Index; PSI = Processing Speed Index; WJ = Woodcock Johnson Tests of Achievement 3rd edition; IVA = Integrated Visual and Auditory Continuous Performance Test. FSIQ, VCI, PRI, WMI, and PSI refer to respective WISC-IV or WAIS-IV FSIQ, VCI, PRI, WMI, and PSI. Wechsler, WJ, and IVA scores are standard scores with M = 100 and SD = 15. Conners-3 Parent and Teacher scores are T-scores with M = 50 and SD = 10. aTime since completion of chemotherapy for 23 patients who had completed treatment at the time of the evaluation. All American Psychological Association (APA) ethical guidelines were followed and Institutional Review Board approval was obtained. Chart review was conducted for all patients who met the inclusion criteria noted above. For inclusion in the current study, participants were required to have completed a Wechsler intelligence test (Wechsler Intelligence Scale for Children 4th Edition [WISC-IV; Wechsler, 2003] or Wechsler Adult Intelligence Scale, 4th edition [WAIS-IV; Wechsler, 2008]), Woodcock-Johnson Tests of Achievement 3rd Edition Calculation subtest (WJ; Mather, 2001), and the Integrated Visual and Auditory Continuous Performance Test (IVA; Sandford & Turner, 2002). Of the participants who had completed each of these measures, the Conners-3 Parent Rating Scale (CPRS; Conners, 2008), a parent-report measure of behavioral symptoms of inattention, impulsivity, and learning problems, was completed for 23 participants. The Conners-3 Teacher Rating Scale (CTRS; Conners, 2008) was completed for 16 participants. Of the 24 participants, 19 completed the WISC-IV and 5 completed the WAIS-IV. For purposes of comparison, FSIQ, VCI, PRI, WMI and PSI will hereafter be used to refer to Full Scale IQ, Verbal Comprehension Index, Perceptual Reasoning Index, Working Memory Index, and Processing Speed Index, respectively, from either Wechsler IQ measure. Measures All participants completed WJ Calculation and IVA; a subset of participants’ parents or teachers completed CPRS or CTRS. See Table 1 for standardized Wechsler IQ, WJ, IVA, CPRS, and CTRS scores. Wechsler intelligence tests provide an estimate of overall cognitive abilities, reported as FSIQ. This global composite score takes into account composite scores for verbal comprehension, perceptual reasoning, working memory, and processing speed. WJ Calculation is a measure of basic mathematical computation, ranging from addition to basic calculus. Standard scores based on age-matched normative samples are used with higher scores indicating better performance relative to the participant’s age. Standard scores have a mean of 100 and a standard deviation of 15. Scores on academic skills testing, including WJ Calculation, are typically correlated with FSIQ. IVA is a computerized continuous performance measure of sustained attention and response control for visual and auditory stimuli. During this test, “1” and “2” are presented in both visual and auditory format in pseudo-random order. Participants are instructed to click a mouse only for a “1” and not for a “2.” Accuracy and reaction times are recorded. Resulting scores include three attention and three response control indices for both visual and auditory modalities, as well as overall visual and auditory attention and response control indices and combined visual and auditory attention and response control indices. Attention indices include: (1) vigilance, based on errors of omission; (2) focus, based on variability of reaction times for correct responses; and (3) speed, based on average reaction time for all correct responses. Response control indices include: (1) prudence, based on errors of commission; (2) consistency, based on variability of all response times; and (3) stamina, based on reaction times of correct responses at the beginning compared to the end of the task. Indices are standard scores based on age- and sex-matched normative samples, with higher scores indicating better performance relative to the participant’s age and sex. CPRS and CTRS are parent and teacher rating scales, respectively, of symptoms common among children with Attention-Deficit/Hyperactivity Disorder. Resulting index scores for both forms include Inattention, Hyperactivity/Impulsivity, Learning Problems, and Executive Functioning. Standardized scores are based on the individual’s age and gender, and are expressed as T-scores with a mean of 50 and a standard deviation of 10. T-scores between 60 and 69 are considered to fall in the high average range of symptoms, and scores ≥70 are considered to fall in the clinically significant range. Analysis Pearson’s r correlation coefficients were calculated for relationships between WJ Calculation, IVA index scores, and CPRS and CTRS scores. Given the high number of IVA index scores and high degree of correlation between many of the subscales, only IVA indices that were significantly positively correlated with WJ Calculation scores were included in further analyses. The amount of variance in WJ Calculation scores accounted for by IVA performance was calculated using hierarchical linear regression with WJ Calculation as the dependent variable. FSIQ scores were entered first to control for expected variation in academic performance based on FSIQ, and IVA index scores were entered second. Results Mean Wechsler IQ index scores and WJ Calculation scores all fell within one standard deviation of the normative mean for these measures. Relatively lower mean scores were observed for processing speed (PSI mean Z = −.60), abilities which are frequently negatively impacted by cancers or treatments involving CNS (Kahalley et al., 2013; Peterson et al., 2008), as well as among children with attentional difficulties (Mayes & Calhoun, 2007; Mayes, Calhoun, Chase, Mink, & Stagg, 2009). Mean IVA scores ranged from 1.7 SD below the normative mean score to .2 SDabove the mean. Specifically, mean visual and auditory speed and stamina (determined by reaction time for correct responses) fell close to the normative mean, between .2 SD above and .4 SD below the normative mean. In contrast, relatively lower mean scores were observed for auditory vigilance, focus, prudence, and consistency (determined by errors of omission and commission and variability in reaction times), which ranged from 1.4 to 1.6 SD below the normative mean. Mean vigilance, focus, prudence, and consistency for visual stimuli ranged from .55 to 1.1 SD below the normative mean. Scores on all measures varied widely, ranging from clinically impaired range to average or above average performance. Similarly, all subscales of parent and teacher report measures (CPRS and CTRS) also showed a wide range of concern, from no concern to clinically significant concern. Mean parent-rated learning problems fell within the high average range of concern, but did not reach the at-risk range of concern. No mean teacher-rated subscales reached the high average range of concern or above. Contrary to expectation, WJ Calculation was not significantly correlated with FSIQ (p = .12), nor was it significantly correlated with any IQ subscale (VCI, p = .20; PRI, p = .09, WMI, p = .09; PSI, p = .36). Age at testing was not correlated with WJ Calculation (p = .84) or with FSIQ (p = .10), and thus was not considered for inclusion in further analyses. See Table 1 for means, standard deviations, ranges, and Pearson’s r correlations with WJ calculation for all measured variables. WJ Calculation was significantly positively correlated with IVA Visual Response Control (r = .36, p < .05), Visual Attention (r = .29, p < .05), Visual Consistency (r = .31, p < .05), and Visual Focus (r = .29, p < .05) indices (see Table 1). As the Visual Consistency and Visual Focus indices are subscales of the Visual Response Control and Visual Attention indices, these were not included in further analyses. Relationship between IVA Visual Response Control and WJ Calculation is shown in Figure 1. Figure 1. View largeDownload slide Scatterplot of Woodcock-Johnson Calculation subtest scores as a function of Integrated Visual and Auditory Continuous Performance Test Visual Response Control subscale scores. Values are standard scores with a mean of 100 and a standard deviation of 15. Figure 1. View largeDownload slide Scatterplot of Woodcock-Johnson Calculation subtest scores as a function of Integrated Visual and Auditory Continuous Performance Test Visual Response Control subscale scores. Values are standard scores with a mean of 100 and a standard deviation of 15. For purposes of comparison, an exploratory analysis was conducted to investigate relationships between IVA performance and three other WJ subscales, each of which were completed by all 24 participants. Specifically, correlations with WJ Letter-Word (a measure of single-word reading accuracy), Passage Comprehension (a measure of reading comprehension requiring the participant to provide a word missing from a written sentence) and Spelling (a measure of written spelling of orally presented words). WJ Letter-Word was positively correlated with the IVA Auditory Focus subscale (r = .43, p < .05), and WJ Spelling was positively correlated with the IVA Full Scale Response Control Quotient (r = .41, p < .05). WJ Passage Comprehension was not significantly correlated with any IVA subscale. WJ Calculation was not significantly correlated with any CPRS index scores, but was significantly negatively correlated with CTRS Inattention (r = −.39, p < .05), Learning Problems (r = −.41, p < .05), and Executive Functioning (r = −.44, p < .05; see Table 1), indicating that poorer math performance was related to higher teacher-rated difficulties in these areas. CPRS Hyperactivity/Impulsivity was significantly positively correlated with IVA Auditory Stamina (r = .31, p < .05), indicating that higher parent-rated impulsivity was associated with better auditory stamina. CTRS Hyperactivity/Impulsivity and Learning Problems were significantly negatively correlated with IVA Visual Speed (r = −.48, p < .05), indicating that higher teacher-rated difficulties were associated with slower visual response speed. CPRS and CTRS Inattention were not significantly correlated with IVA index scores. See Table 2 for correlations between IVA and CPRS/CTRS scores. Table 2. Correlations between IVA scores and parent and teacher rating scales Measure  CPRS/CTRS  Inattention  Hyperactivity/Impulsivity  Learning problems  Executive functioning  IVA   Full Scale Attention  −.04/−.03  .05/−.35  −.07/−.23  −.09/−.15    Auditory Attention  −.06/−.06  .02/−.32  −.06/−.26  −.05/−.28     Auditory Vigilance  .08/−.08  −.07/−.28  .02/−.32  −.03/−.24     Auditory Focus  .01/−.06  .03/.11  −.09/.01  −.06/−.08     Auditory Speed  .10/.02  .27/−.15  −.08/−.36  .10/−.17    Visual Attention  −.04/.05  .15/−.31  .00/−.25  −.13/−.03     Visual Vigilance  −.05/−.32  −.05/−.28  −.004/−.21  −.24/−.28     Visual Focus  .15/.11  .05/−.19  .16/−.19  .05/−.07     Visual Speed  −.21/−.16  .07/−.48*  −.20/−.46*  −.19/−.21   Full Scale Response Control  .16/.08  .02/−.04  .08/.01  .02/.03    Auditory Response Control  .01/.04  .04/−.03  .02/.12  −.09/.07     Auditory Prudence  −.13/−.07  −.13/.09  −.10/.09  −.21/.02     Auditory Consistency  −.07/−.15  −.19/−.13  −.16/−.08  −.22/−.18     Auditory Stamina  .23/.16  .31*/.02  .16/.07  .29/.15    Visual Response Control  .07/−.11  −.08/−.17  −.004/−.20  −.05/−.31     Visual Prudence  .14/−.14  −.11/−.10  .06/−.07  .02/−.22     Visual Consistency  −.10/−.15  −.19/−.30  −.11/−.35  −.11/−.28     Visual Stamina  .10/.10  .08/.02  .10/.09  .06/−.03  Measure  CPRS/CTRS  Inattention  Hyperactivity/Impulsivity  Learning problems  Executive functioning  IVA   Full Scale Attention  −.04/−.03  .05/−.35  −.07/−.23  −.09/−.15    Auditory Attention  −.06/−.06  .02/−.32  −.06/−.26  −.05/−.28     Auditory Vigilance  .08/−.08  −.07/−.28  .02/−.32  −.03/−.24     Auditory Focus  .01/−.06  .03/.11  −.09/.01  −.06/−.08     Auditory Speed  .10/.02  .27/−.15  −.08/−.36  .10/−.17    Visual Attention  −.04/.05  .15/−.31  .00/−.25  −.13/−.03     Visual Vigilance  −.05/−.32  −.05/−.28  −.004/−.21  −.24/−.28     Visual Focus  .15/.11  .05/−.19  .16/−.19  .05/−.07     Visual Speed  −.21/−.16  .07/−.48*  −.20/−.46*  −.19/−.21   Full Scale Response Control  .16/.08  .02/−.04  .08/.01  .02/.03    Auditory Response Control  .01/.04  .04/−.03  .02/.12  −.09/.07     Auditory Prudence  −.13/−.07  −.13/.09  −.10/.09  −.21/.02     Auditory Consistency  −.07/−.15  −.19/−.13  −.16/−.08  −.22/−.18     Auditory Stamina  .23/.16  .31*/.02  .16/.07  .29/.15    Visual Response Control  .07/−.11  −.08/−.17  −.004/−.20  −.05/−.31     Visual Prudence  .14/−.14  −.11/−.10  .06/−.07  .02/−.22     Visual Consistency  −.10/−.15  −.19/−.30  −.11/−.35  −.11/−.28     Visual Stamina  .10/.10  .08/.02  .10/.09  .06/−.03  Note. Pearson’s r correlation coefficients between standardized test scores. *p< .05 **p< .01. FSIQ = Full Scale Intelligence Quotient; VCI = Verbal Comprehension Index; PRI = Perceptual Reasoning Index; WMI = Working Memory Index; PSI = Processing Speed Index; WJ = Woodcock Johnson Tests of Achievement 3rd edition; IVA = Integrated Visual and Auditory Continuous Performance Test; CPRS = Conners Parent Rating Scale; CTRS = Conners Teacher Rating Scale. FSIQ, VCI, PRI, WMI, and PSI refer to respective WISC-IV or WAIS-IV FSIQ, VCI, PRI, WMI, and PSI. Wechsler, WJ, and IVA scores are standard scores with M = 100 and SD = 15. Conners-3 Parent and Teacher scores are T-scores with M = 50 and SD = 10. Table 2. Correlations between IVA scores and parent and teacher rating scales Measure  CPRS/CTRS  Inattention  Hyperactivity/Impulsivity  Learning problems  Executive functioning  IVA   Full Scale Attention  −.04/−.03  .05/−.35  −.07/−.23  −.09/−.15    Auditory Attention  −.06/−.06  .02/−.32  −.06/−.26  −.05/−.28     Auditory Vigilance  .08/−.08  −.07/−.28  .02/−.32  −.03/−.24     Auditory Focus  .01/−.06  .03/.11  −.09/.01  −.06/−.08     Auditory Speed  .10/.02  .27/−.15  −.08/−.36  .10/−.17    Visual Attention  −.04/.05  .15/−.31  .00/−.25  −.13/−.03     Visual Vigilance  −.05/−.32  −.05/−.28  −.004/−.21  −.24/−.28     Visual Focus  .15/.11  .05/−.19  .16/−.19  .05/−.07     Visual Speed  −.21/−.16  .07/−.48*  −.20/−.46*  −.19/−.21   Full Scale Response Control  .16/.08  .02/−.04  .08/.01  .02/.03    Auditory Response Control  .01/.04  .04/−.03  .02/.12  −.09/.07     Auditory Prudence  −.13/−.07  −.13/.09  −.10/.09  −.21/.02     Auditory Consistency  −.07/−.15  −.19/−.13  −.16/−.08  −.22/−.18     Auditory Stamina  .23/.16  .31*/.02  .16/.07  .29/.15    Visual Response Control  .07/−.11  −.08/−.17  −.004/−.20  −.05/−.31     Visual Prudence  .14/−.14  −.11/−.10  .06/−.07  .02/−.22     Visual Consistency  −.10/−.15  −.19/−.30  −.11/−.35  −.11/−.28     Visual Stamina  .10/.10  .08/.02  .10/.09  .06/−.03  Measure  CPRS/CTRS  Inattention  Hyperactivity/Impulsivity  Learning problems  Executive functioning  IVA   Full Scale Attention  −.04/−.03  .05/−.35  −.07/−.23  −.09/−.15    Auditory Attention  −.06/−.06  .02/−.32  −.06/−.26  −.05/−.28     Auditory Vigilance  .08/−.08  −.07/−.28  .02/−.32  −.03/−.24     Auditory Focus  .01/−.06  .03/.11  −.09/.01  −.06/−.08     Auditory Speed  .10/.02  .27/−.15  −.08/−.36  .10/−.17    Visual Attention  −.04/.05  .15/−.31  .00/−.25  −.13/−.03     Visual Vigilance  −.05/−.32  −.05/−.28  −.004/−.21  −.24/−.28     Visual Focus  .15/.11  .05/−.19  .16/−.19  .05/−.07     Visual Speed  −.21/−.16  .07/−.48*  −.20/−.46*  −.19/−.21   Full Scale Response Control  .16/.08  .02/−.04  .08/.01  .02/.03    Auditory Response Control  .01/.04  .04/−.03  .02/.12  −.09/.07     Auditory Prudence  −.13/−.07  −.13/.09  −.10/.09  −.21/.02     Auditory Consistency  −.07/−.15  −.19/−.13  −.16/−.08  −.22/−.18     Auditory Stamina  .23/.16  .31*/.02  .16/.07  .29/.15    Visual Response Control  .07/−.11  −.08/−.17  −.004/−.20  −.05/−.31     Visual Prudence  .14/−.14  −.11/−.10  .06/−.07  .02/−.22     Visual Consistency  −.10/−.15  −.19/−.30  −.11/−.35  −.11/−.28     Visual Stamina  .10/.10  .08/.02  .10/.09  .06/−.03  Note. Pearson’s r correlation coefficients between standardized test scores. *p< .05 **p< .01. FSIQ = Full Scale Intelligence Quotient; VCI = Verbal Comprehension Index; PRI = Perceptual Reasoning Index; WMI = Working Memory Index; PSI = Processing Speed Index; WJ = Woodcock Johnson Tests of Achievement 3rd edition; IVA = Integrated Visual and Auditory Continuous Performance Test; CPRS = Conners Parent Rating Scale; CTRS = Conners Teacher Rating Scale. FSIQ, VCI, PRI, WMI, and PSI refer to respective WISC-IV or WAIS-IV FSIQ, VCI, PRI, WMI, and PSI. Wechsler, WJ, and IVA scores are standard scores with M = 100 and SD = 15. Conners-3 Parent and Teacher scores are T-scores with M = 50 and SD = 10. IVA Visual Response Control and Visual Attention were chosen to be entered into a hierarchical linear regression model based on their significant correlations with WJ Calculation. All entered variables had positive relationships with WJ Calculation. FSIQ was entered into the model first; however, this did not account for a significant amount of variance in WJ Calculation (p = .10). Next, IVA Visual Response Control and Visual Attention were entered together, and accounted for an additional 26.4% of the variance in WJ Calculation (p < .05) above that accounted for by FSIQ. Visual Response Control accounted for a significant portion of this variance (p < .05), whereas Visual Attention did not (p = .94). IVA Visual Response Control and Visual Attention were significantly correlated (r = .53, p < .005); however, there was no indication of significant collinearity between predictor variables (average variance inflation factor = 1.34). Results of this regression model are presented in Table 3. Table 3. Hierarchical linear regression model for WJ calculation   B  SE B  β  Step 1   Constant  61.63  24.19     FSIQ  .43  .25  .35  Step 2   Constant  28.83  24.08     FSIQ  .39  .23  .32   IVA Visual Response Control  .40  .16  .51*   IVA Visual Attention  .01  .15  .02    B  SE B  β  Step 1   Constant  61.63  24.19     FSIQ  .43  .25  .35  Step 2   Constant  28.83  24.08     FSIQ  .39  .23  .32   IVA Visual Response Control  .40  .16  .51*   IVA Visual Attention  .01  .15  .02  Note: R2 = .12 for Step 1, ΔR2 = .26 for Step 2. *p < .05 Table 3. Hierarchical linear regression model for WJ calculation   B  SE B  β  Step 1   Constant  61.63  24.19     FSIQ  .43  .25  .35  Step 2   Constant  28.83  24.08     FSIQ  .39  .23  .32   IVA Visual Response Control  .40  .16  .51*   IVA Visual Attention  .01  .15  .02    B  SE B  β  Step 1   Constant  61.63  24.19     FSIQ  .43  .25  .35  Step 2   Constant  28.83  24.08     FSIQ  .39  .23  .32   IVA Visual Response Control  .40  .16  .51*   IVA Visual Attention  .01  .15  .02  Note: R2 = .12 for Step 1, ΔR2 = .26 for Step 2. *p < .05 Discussion The current study aimed to investigate relationships between math calculation skills and performance on an objective measure of attention and parent- and teacher-reported inattention among survivors of childhood ALL. It was hypothesized that performance on objective measure of sustained attention and parent- and teacher-reported inattention would explain a significant amount of the variance in math skills among childhood ALL survivors beyond expected variation in performance based on IQ. Although scores on all measures varied from clinically impaired to superior, mean IQ, math calculation, and speed and stamina of responding to visual and auditory stimuli all fell within one standard deviation of normative mean scores. Other aspects of visual sustained attention and response control fell between .55 and 1.1 SD below the normative mean, and mean auditory sustained attention and response control was somewhat lower, falling between 1.4 and 1.6 SD below the normative mean. Mean parent-rated learning problems fell within the high average range of concerns. Results indicated that objective measures of attention, specifically response control for visual stimuli, did account for a significant amount of variance in math performance. Significant relationships were observed between math performance and IVA Visual Response Control and Visual Attention index scores; however, only Visual Response Control accounted for a significant amount of variance in math performance after controlling for FSIQ. The apparent relationship between attention and math performance is particularly compelling given the less-robust relationships between IVA and other academic skills: single-word reading and spelling were significantly correlated with one IVA subscale each, and reading comprehension was not correlated with IVA performance. Although teacher-rated inattention, learning problems, and day-to-day executive functioning were significantly negatively correlated with math performance, parent-rated attentional difficulties did not bear statistically significant relationships to math performance. Teacher-rated, but not parent-rated, inattention was significantly negatively correlated with math performance. This indicates that parent perception of inattention may be an indication of a different type of attentional deficit than that associated with math performance. Interestingly, parent-rated hyperactivity/impulsivity was significantly positively correlated with IVA Auditory Stamina, a component of auditory response control, whereas teacher-rated hyperactivity/impulsivity was significantly negatively correlated with IVA Visual Speed, a component of visual sustained attention. This suggests that aspects of auditory attention may be more salient in behavioral difficulties in the home environment (e.g. response to verbal directions), whereas aspects of visual attention may be more salient in the school environment (e.g. attention to written assignments). The relationship between math performance and response control for visual, as opposed to auditory, stimuli, may be related to the particular importance of visual (as opposed to auditory) information processing for the acquisition of math skills (Barnes & Raghubar, 2014; Halberda, Mazzocco, & Feigenson, 2008). The current findings provide further support for the existing literature supporting a relationship between visuospatial and visuomotor skills and math performance. Specifically, longitudinal studies have indicated that visuospatial working memory predicts later math skills in typically developing children (Barnes et al., 2014), and visuomotor integration predicts later math skills in survivors of childhood ALL (Balsamo, Sint, Neglia, Brouwers, & Kadan-Lottick, 2015; Moore et al., 2016). It may be the case that visual attention difficulties are a common factor underlying the relationships between visual working memory, visuomotor integration, and math skills. Furthermore, difficulty regulating responses resulting in variable response times may lead to difficulty in efficient learning of math facts and computational strategies. Existing literature indicates that attentional deficits are common among survivors of childhood ALL; further investigations are needed to clarify potential causal relationships between visual response control deficits and acquisition of math calculation skills. Observed relationships between math performance and objective attention performance, but not with parent-rated inattention, in the current study indicates that objective attention testing may have clinical utility in identifying children at risk for math difficulties should such a causal relationship exist. Additional directions for future studies include whether interventions to improve attention and response control deficits reduce the risk for math and other academic difficulties before they become apparent, in ALL survivors and other pediatric populations. A weakness of the current study is the relatively small sample size which potentially limits the statistical power to detect significant relationships between the variables of interest. Furthermore, the sample employed here consisted of children referred by a physician due to academic or behavioral difficulties. This may limit generalizability of the findings to ALL survivors who are not currently experiencing such difficulties, but may also result in higher clinical utility for children who are experiencing difficulties. The number of correlations calculated here does raise the possibility of Type 1 error, and suggests the importance of replication of the present findings. Of note, two participants were treated with psychostimulant medications and one was treated with antipsychotic and anticonvulsant medication at the time of testing, which may have impacted objective attention performance as well as parent and teacher ratings of behavior. This may have introduced a source of variability in the data and thus limited the ability to detect potential relationships between the variables of interest. The sample was also chosen for relative homogeneity in cancer diagnosis and chemotherapy-only treatment, thus reducing potential variance attributable to the potential impacts of cancer and its treatments on cognitive functioning. Further investigations employing larger sample sizes will be helpful in confirming the current findings. Similarly, it would be clinically relevant to determine whether the relationships between attention and math observed here hold among students who are experiencing educationally significant difficulties in math, as the sample included in the current study performed, on average, within the average range on math testing. Although significant relationships were observed between teacher ratings of attentional difficulties and objective math performance, the current sample size did not allow teacher ratings to be included in regression analysis; further investigation of this relationship with larger sample sizes may be informative. Furthermore, investigation of relationships between attention and math difficulties in non-ALL childhood cancer survivors and other pediatric populations are needed to determine whether the current findings are generalizable to children experiencing academic difficulties with non-ALL etiologies. Likewise, investigations of potential relationships between other academic skills and various aspects of attention in this population may be informative. Results of the current study suggest that routine screening for attentional difficulties among childhood cancer survivors using a brief computerized evaluation may have the potential to identify students at risk for math difficulties. Furthermore, use of an objective measure of attention may be more effective in identifying students at risk for math difficulties than commonly used parent behavioral rating scales. For students experiencing math difficulties, consideration of potential associated visual attention difficulties may be useful in informing selection and execution of math interventions. Should a causal relationship between early-developing visual attention and later math difficulties be borne out, early intervention for attentional difficulties may have potential to reduce risk for future math difficulties in childhood ALL survivors. Funding No funding was used to conduct this study. Conflict of interest The authors report no conflicts of interest. Acknowledgements This study was conducted with the approval of the Institutional Review Board of the University of Michigan Medical School, reference HUM00046285. References Balsamo, L. M., Sint, K. J., Neglia, J. P., Brouwers, P., & Kadan-Lottick, N. S. ( 2015). The association between motor skills and academic achievement among pediatric survivors of acute lymphoblastic leukemia. 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Visual Attention and Math Performance in Survivors of Childhood Acute Lymphoblastic Leukemia

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0887-6177
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1873-5843
D.O.I.
10.1093/arclin/acy002
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Abstract

Abstract Objective Attentional and academic difficulties, particularly in math, are common in survivors of childhood acute lymphoblastic leukemia (ALL). Of cognitive deficits experienced by survivors of childhood ALL, attention deficits may be particularly responsive to intervention. However, it is unknown whether deficits in particular aspects of attention are associated with deficits in math skills. The current study investigated relationships between math calculation skills, performance on an objective measure of sustained attention, and parent- and teacher-reported attention difficulties. Method Twenty-four survivors of childhood ALL (Mage = 13.5 years, SD= 2.8 years) completed a computerized measure of sustained attention and response control and a written measure of math calculation skills in the context of a comprehensive clinical neuropsychological evaluation. Parent and teacher ratings of inattention and impulsivity were obtained. Results Visual response control and visual attention accounted for 26.4% of the variance observed among math performance scores after controlling for IQ (p < .05). Teacher-rated, but not parent-rated, inattention was significantly negatively correlated with math calculation scores. Conclusions Consistency of responses to visual stimuli on a computerized measure of attention is a unique predictor of variance in math performance among survivors of childhood ALL. Objective testing of visual response control, rather than parent-rated attentional problems, may have clinical utility in identifying ALL survivors at risk for math difficulties. Attention, Leukemia, Mathematical and numerical skills, Pediatric Introduction Prevalence of childhood cancer survivors in the US has been recently estimated at over 350,000, with 35% of those individuals experiencing neurocognitive dysfunction (Phillips et al., 2015). Deficits in academic performance, particularly math, are among the more commonly reported neurocognitive difficulties among childhood cancer survivors. Among survivors of acute lymphoblastic leukemia (ALL), the most common childhood cancer, math deficits are the most commonly reported academic deficit (Brown et al., 1992, 1996; Brown, Sawyer, Antoniou, Toogood, & Rice, 1999; Moore et al., 2000; Mulhern, Fairclough, & Ochs, 1991; Ochs et al., 1991; Peckham & Meadows, 1988). Attention deficits are also common among survivors of childhood ALL (Buizer, De Sonneville, Van Den Heuvel-Eibrink, & Veerman, 2005; Campbell et al., 2007). Relationships between math performance and attention have been observed among survivors of childhood ALL. These include a relationship between objective math performance and auditory (Kaemingk, Carey, Moore, Herzer, & Hutter, 2010) and visual working memory (Barnes et al., 2014), and relationships between parent-rated attentional difficulties, objective testing of visual sustained attention, and teacher-rated math ability (Buizer, De Sonneville, Van Den Heuvel-Eibrink, & Veerman, 2006). Furthermore, smaller white matter volumes have been found to be correlated with both visual sustained attention and math deficits among survivors of childhood ALL (Reddick et al., 2006). This suggests a common neurophysiological factor underlying deficits in both attention and math performance, specifically the negative impact of cancer treatment on CNS white matter volumes. However, although deficits have been documented on measures of both visual (Buizer et al., 2005; Campbell et al., 2007) and auditory attention (Campbell et al., 2007), it is unknown whether deficits in particular aspects of attention are associated with deficits in math skills among survivors of childhood ALL. When assessing cognitive and academic difficulties, parent report measures are frequently used for logistical reasons including relative ease of administration in comparison to objective cognitive testing. However, brief, objective cognitive testing may be more accurate in identifying cognitive and academic difficulties. Specifically, an investigation of reliability and validity of brief neurocognitive screening for survivors of childhood ALL showed that objective neurocognitive testing accurately predicted IQ as well as reading and math performance; in contrast, parent report did not accurately predict IQ or academic skills (Krull et al., 2008). Interventions focused on improving academic skills have generally targeted academic skills directly. A recent trial demonstrated that among childhood ALL survivors who had not yet demonstrated math deficits, individual math instruction resulted in improved math performance among survivors who received the instruction, and better performance compared to survivors who did not receive instruction (Moore, Hockenberry, Anhalt, McCarthy, & Krull, 2012). Although interventions aimed at improving math skills may be effective, a notable limitation is that these interventions may not generalize to other academic, behavioral, or social difficulties. Should relationships between math skills and earlier-developing, underlying cognitive skills be elucidated, this could create potential for pre-emptive treatment of underlying cognitive difficulties before math and other difficulties become apparent. The current study aimed to further investigate potential relationships between attention and math performance among survivors of childhood ALL. To this end, retrospective review of comprehensive neuropsychological evaluation results was conducted for 24 survivors of childhood ALL who had been referred due to cognitive or academic concerns. Relationships between objective measures of math calculation skills and visual and auditory sustained attention and response control, as well as parent- and teacher-reported inattention, were examined. It was hypothesized that performance on objective measures of sustained attention and parent- and teacher-reported inattention would explain a significant amount of the variance in math skills among survivors of childhood ALL, given their expected level of performance based on measured IQ. Methods Participants Retrospective record review was conducted for 24 children and adolescents (11 male, 13 female) ages 8–18 years. All participants had undergone comprehensive neuropsychological evaluation at a regional academic medical center between April 2008 and August 2016, and had been referred by a physician for cognitive or academic concerns. All patients carried a historical diagnosis of ALL and received chemotherapy treatment as usual. Exclusion criteria included a history of radiation treatment or hematopoetic cell transplant, due to associated risk of adverse effects on cognitive functioning. Twenty-three patients were status post-treatment, and one was receiving maintenance chemotherapy at the time of the evaluation. Three participants were prescribed psychoactive medications at the time of testing: one participant was taking a selective serotonin reuptake inhibitor (sertraline) and a psychostimulant medication (methylphenidate), one was taking an anticonvulsant medication (valproate) and an antipsychotic medication (paliperidone) and one was taking a psychostimulant medication only (dexmethylphenidate). All participants took their regular medications as prescribed on the day of testing. See Table 1 for participant demographics. Table 1. Participant demographic characteristics and standardized test scores Variable  M  SD  Range  Correlation with WJ Calculation  Age at testing (years)  13.5  2.8  8.6–18.4  −.03  Age at diagnosis  3.9  2.8  1.5–15.0  −.15  Time since treatmenta  6.6  2.9  1.0–11.0  .12  Wechsler IQ   FSIQ  97.0  12.9  71–125  .18   VCI  99.7  10.9  78–121  .12   PRI  99.3  14.8  69–136  .21   WMI  97.0  11.2  74–116  .20   PSI  91.2  14.0  65–112  .05  WJ Calculation  103.5  15.9  78–139  —  IVA   Full Scale Attention  75.0  26.5  18–118  .29    Auditory Attention  75.8  23.9  29–108  .23     Auditory Vigilance  78.8  28.0  13–109  .24     Auditory Focus  76.9  19.4  39–116  .06     Auditory Speed  103.5  14.1  76–128  .23    Visual Attention  82.5  23.2  34–123  .29*     Visual Vigilance  84.3  24.8  22–112  .23     Visual Focus  88.5  18.3  42–125  .29*     Visual Speed  94.1  14.1  72–120  .24   Full Scale Response Control  80.5  23.0  7–108  .22    Auditory Response Control  76.3  23.7  13–111  .21     Auditory Prudence  75.7  25.0  17–114  .12     Auditory Consistency  77.7  18.8  19–103  −.004     Auditory Stamina  100.1  22.2  61–148  .22    Visual Response Control  89.9  20.4  29–119  .36*     Visual Prudence  91.3  18.9  41–121  .15     Visual Consistency  92.4  19.1  40–117  .31*     Visual Stamina  96.6  17.2  68–125  .21  Conners-3 Parent   Inattention  59.2  15.0  39–87  −.08   Hyperactivity/Impulsivity  50.0  11.1  41–78  −.01   Learning Problems  60.1  14.8  39–93  −.27   Executive Functioning  58.4  13.4  39–90  .02  Conners-3 Teacher   Inattention  55.9  19.0  40–90  −.39*   Hyperactivity/Impulsivity  57.3  19.4  42–98  −.22   Learning Problems  54.4  15.3  41–86  −.41*   Executive Functioning  54.8  15.3  41–86  −.44*  Variable  M  SD  Range  Correlation with WJ Calculation  Age at testing (years)  13.5  2.8  8.6–18.4  −.03  Age at diagnosis  3.9  2.8  1.5–15.0  −.15  Time since treatmenta  6.6  2.9  1.0–11.0  .12  Wechsler IQ   FSIQ  97.0  12.9  71–125  .18   VCI  99.7  10.9  78–121  .12   PRI  99.3  14.8  69–136  .21   WMI  97.0  11.2  74–116  .20   PSI  91.2  14.0  65–112  .05  WJ Calculation  103.5  15.9  78–139  —  IVA   Full Scale Attention  75.0  26.5  18–118  .29    Auditory Attention  75.8  23.9  29–108  .23     Auditory Vigilance  78.8  28.0  13–109  .24     Auditory Focus  76.9  19.4  39–116  .06     Auditory Speed  103.5  14.1  76–128  .23    Visual Attention  82.5  23.2  34–123  .29*     Visual Vigilance  84.3  24.8  22–112  .23     Visual Focus  88.5  18.3  42–125  .29*     Visual Speed  94.1  14.1  72–120  .24   Full Scale Response Control  80.5  23.0  7–108  .22    Auditory Response Control  76.3  23.7  13–111  .21     Auditory Prudence  75.7  25.0  17–114  .12     Auditory Consistency  77.7  18.8  19–103  −.004     Auditory Stamina  100.1  22.2  61–148  .22    Visual Response Control  89.9  20.4  29–119  .36*     Visual Prudence  91.3  18.9  41–121  .15     Visual Consistency  92.4  19.1  40–117  .31*     Visual Stamina  96.6  17.2  68–125  .21  Conners-3 Parent   Inattention  59.2  15.0  39–87  −.08   Hyperactivity/Impulsivity  50.0  11.1  41–78  −.01   Learning Problems  60.1  14.8  39–93  −.27   Executive Functioning  58.4  13.4  39–90  .02  Conners-3 Teacher   Inattention  55.9  19.0  40–90  −.39*   Hyperactivity/Impulsivity  57.3  19.4  42–98  −.22   Learning Problems  54.4  15.3  41–86  −.41*   Executive Functioning  54.8  15.3  41–86  −.44*  Note: Correlations are Pearson’s r coefficients. *p< .05 **p< .01. M = mean; SD = standard deviation; FSIQ = Full Scale Intelligence Quotient; VCI = Verbal Comprehension Index; PRI = Perceptual Reasoning Index; WMI = Working Memory Index; PSI = Processing Speed Index; WJ = Woodcock Johnson Tests of Achievement 3rd edition; IVA = Integrated Visual and Auditory Continuous Performance Test. FSIQ, VCI, PRI, WMI, and PSI refer to respective WISC-IV or WAIS-IV FSIQ, VCI, PRI, WMI, and PSI. Wechsler, WJ, and IVA scores are standard scores with M = 100 and SD = 15. Conners-3 Parent and Teacher scores are T-scores with M = 50 and SD = 10. aTime since completion of chemotherapy for 23 patients who had completed treatment at the time of the evaluation. Table 1. Participant demographic characteristics and standardized test scores Variable  M  SD  Range  Correlation with WJ Calculation  Age at testing (years)  13.5  2.8  8.6–18.4  −.03  Age at diagnosis  3.9  2.8  1.5–15.0  −.15  Time since treatmenta  6.6  2.9  1.0–11.0  .12  Wechsler IQ   FSIQ  97.0  12.9  71–125  .18   VCI  99.7  10.9  78–121  .12   PRI  99.3  14.8  69–136  .21   WMI  97.0  11.2  74–116  .20   PSI  91.2  14.0  65–112  .05  WJ Calculation  103.5  15.9  78–139  —  IVA   Full Scale Attention  75.0  26.5  18–118  .29    Auditory Attention  75.8  23.9  29–108  .23     Auditory Vigilance  78.8  28.0  13–109  .24     Auditory Focus  76.9  19.4  39–116  .06     Auditory Speed  103.5  14.1  76–128  .23    Visual Attention  82.5  23.2  34–123  .29*     Visual Vigilance  84.3  24.8  22–112  .23     Visual Focus  88.5  18.3  42–125  .29*     Visual Speed  94.1  14.1  72–120  .24   Full Scale Response Control  80.5  23.0  7–108  .22    Auditory Response Control  76.3  23.7  13–111  .21     Auditory Prudence  75.7  25.0  17–114  .12     Auditory Consistency  77.7  18.8  19–103  −.004     Auditory Stamina  100.1  22.2  61–148  .22    Visual Response Control  89.9  20.4  29–119  .36*     Visual Prudence  91.3  18.9  41–121  .15     Visual Consistency  92.4  19.1  40–117  .31*     Visual Stamina  96.6  17.2  68–125  .21  Conners-3 Parent   Inattention  59.2  15.0  39–87  −.08   Hyperactivity/Impulsivity  50.0  11.1  41–78  −.01   Learning Problems  60.1  14.8  39–93  −.27   Executive Functioning  58.4  13.4  39–90  .02  Conners-3 Teacher   Inattention  55.9  19.0  40–90  −.39*   Hyperactivity/Impulsivity  57.3  19.4  42–98  −.22   Learning Problems  54.4  15.3  41–86  −.41*   Executive Functioning  54.8  15.3  41–86  −.44*  Variable  M  SD  Range  Correlation with WJ Calculation  Age at testing (years)  13.5  2.8  8.6–18.4  −.03  Age at diagnosis  3.9  2.8  1.5–15.0  −.15  Time since treatmenta  6.6  2.9  1.0–11.0  .12  Wechsler IQ   FSIQ  97.0  12.9  71–125  .18   VCI  99.7  10.9  78–121  .12   PRI  99.3  14.8  69–136  .21   WMI  97.0  11.2  74–116  .20   PSI  91.2  14.0  65–112  .05  WJ Calculation  103.5  15.9  78–139  —  IVA   Full Scale Attention  75.0  26.5  18–118  .29    Auditory Attention  75.8  23.9  29–108  .23     Auditory Vigilance  78.8  28.0  13–109  .24     Auditory Focus  76.9  19.4  39–116  .06     Auditory Speed  103.5  14.1  76–128  .23    Visual Attention  82.5  23.2  34–123  .29*     Visual Vigilance  84.3  24.8  22–112  .23     Visual Focus  88.5  18.3  42–125  .29*     Visual Speed  94.1  14.1  72–120  .24   Full Scale Response Control  80.5  23.0  7–108  .22    Auditory Response Control  76.3  23.7  13–111  .21     Auditory Prudence  75.7  25.0  17–114  .12     Auditory Consistency  77.7  18.8  19–103  −.004     Auditory Stamina  100.1  22.2  61–148  .22    Visual Response Control  89.9  20.4  29–119  .36*     Visual Prudence  91.3  18.9  41–121  .15     Visual Consistency  92.4  19.1  40–117  .31*     Visual Stamina  96.6  17.2  68–125  .21  Conners-3 Parent   Inattention  59.2  15.0  39–87  −.08   Hyperactivity/Impulsivity  50.0  11.1  41–78  −.01   Learning Problems  60.1  14.8  39–93  −.27   Executive Functioning  58.4  13.4  39–90  .02  Conners-3 Teacher   Inattention  55.9  19.0  40–90  −.39*   Hyperactivity/Impulsivity  57.3  19.4  42–98  −.22   Learning Problems  54.4  15.3  41–86  −.41*   Executive Functioning  54.8  15.3  41–86  −.44*  Note: Correlations are Pearson’s r coefficients. *p< .05 **p< .01. M = mean; SD = standard deviation; FSIQ = Full Scale Intelligence Quotient; VCI = Verbal Comprehension Index; PRI = Perceptual Reasoning Index; WMI = Working Memory Index; PSI = Processing Speed Index; WJ = Woodcock Johnson Tests of Achievement 3rd edition; IVA = Integrated Visual and Auditory Continuous Performance Test. FSIQ, VCI, PRI, WMI, and PSI refer to respective WISC-IV or WAIS-IV FSIQ, VCI, PRI, WMI, and PSI. Wechsler, WJ, and IVA scores are standard scores with M = 100 and SD = 15. Conners-3 Parent and Teacher scores are T-scores with M = 50 and SD = 10. aTime since completion of chemotherapy for 23 patients who had completed treatment at the time of the evaluation. All American Psychological Association (APA) ethical guidelines were followed and Institutional Review Board approval was obtained. Chart review was conducted for all patients who met the inclusion criteria noted above. For inclusion in the current study, participants were required to have completed a Wechsler intelligence test (Wechsler Intelligence Scale for Children 4th Edition [WISC-IV; Wechsler, 2003] or Wechsler Adult Intelligence Scale, 4th edition [WAIS-IV; Wechsler, 2008]), Woodcock-Johnson Tests of Achievement 3rd Edition Calculation subtest (WJ; Mather, 2001), and the Integrated Visual and Auditory Continuous Performance Test (IVA; Sandford & Turner, 2002). Of the participants who had completed each of these measures, the Conners-3 Parent Rating Scale (CPRS; Conners, 2008), a parent-report measure of behavioral symptoms of inattention, impulsivity, and learning problems, was completed for 23 participants. The Conners-3 Teacher Rating Scale (CTRS; Conners, 2008) was completed for 16 participants. Of the 24 participants, 19 completed the WISC-IV and 5 completed the WAIS-IV. For purposes of comparison, FSIQ, VCI, PRI, WMI and PSI will hereafter be used to refer to Full Scale IQ, Verbal Comprehension Index, Perceptual Reasoning Index, Working Memory Index, and Processing Speed Index, respectively, from either Wechsler IQ measure. Measures All participants completed WJ Calculation and IVA; a subset of participants’ parents or teachers completed CPRS or CTRS. See Table 1 for standardized Wechsler IQ, WJ, IVA, CPRS, and CTRS scores. Wechsler intelligence tests provide an estimate of overall cognitive abilities, reported as FSIQ. This global composite score takes into account composite scores for verbal comprehension, perceptual reasoning, working memory, and processing speed. WJ Calculation is a measure of basic mathematical computation, ranging from addition to basic calculus. Standard scores based on age-matched normative samples are used with higher scores indicating better performance relative to the participant’s age. Standard scores have a mean of 100 and a standard deviation of 15. Scores on academic skills testing, including WJ Calculation, are typically correlated with FSIQ. IVA is a computerized continuous performance measure of sustained attention and response control for visual and auditory stimuli. During this test, “1” and “2” are presented in both visual and auditory format in pseudo-random order. Participants are instructed to click a mouse only for a “1” and not for a “2.” Accuracy and reaction times are recorded. Resulting scores include three attention and three response control indices for both visual and auditory modalities, as well as overall visual and auditory attention and response control indices and combined visual and auditory attention and response control indices. Attention indices include: (1) vigilance, based on errors of omission; (2) focus, based on variability of reaction times for correct responses; and (3) speed, based on average reaction time for all correct responses. Response control indices include: (1) prudence, based on errors of commission; (2) consistency, based on variability of all response times; and (3) stamina, based on reaction times of correct responses at the beginning compared to the end of the task. Indices are standard scores based on age- and sex-matched normative samples, with higher scores indicating better performance relative to the participant’s age and sex. CPRS and CTRS are parent and teacher rating scales, respectively, of symptoms common among children with Attention-Deficit/Hyperactivity Disorder. Resulting index scores for both forms include Inattention, Hyperactivity/Impulsivity, Learning Problems, and Executive Functioning. Standardized scores are based on the individual’s age and gender, and are expressed as T-scores with a mean of 50 and a standard deviation of 10. T-scores between 60 and 69 are considered to fall in the high average range of symptoms, and scores ≥70 are considered to fall in the clinically significant range. Analysis Pearson’s r correlation coefficients were calculated for relationships between WJ Calculation, IVA index scores, and CPRS and CTRS scores. Given the high number of IVA index scores and high degree of correlation between many of the subscales, only IVA indices that were significantly positively correlated with WJ Calculation scores were included in further analyses. The amount of variance in WJ Calculation scores accounted for by IVA performance was calculated using hierarchical linear regression with WJ Calculation as the dependent variable. FSIQ scores were entered first to control for expected variation in academic performance based on FSIQ, and IVA index scores were entered second. Results Mean Wechsler IQ index scores and WJ Calculation scores all fell within one standard deviation of the normative mean for these measures. Relatively lower mean scores were observed for processing speed (PSI mean Z = −.60), abilities which are frequently negatively impacted by cancers or treatments involving CNS (Kahalley et al., 2013; Peterson et al., 2008), as well as among children with attentional difficulties (Mayes & Calhoun, 2007; Mayes, Calhoun, Chase, Mink, & Stagg, 2009). Mean IVA scores ranged from 1.7 SD below the normative mean score to .2 SDabove the mean. Specifically, mean visual and auditory speed and stamina (determined by reaction time for correct responses) fell close to the normative mean, between .2 SD above and .4 SD below the normative mean. In contrast, relatively lower mean scores were observed for auditory vigilance, focus, prudence, and consistency (determined by errors of omission and commission and variability in reaction times), which ranged from 1.4 to 1.6 SD below the normative mean. Mean vigilance, focus, prudence, and consistency for visual stimuli ranged from .55 to 1.1 SD below the normative mean. Scores on all measures varied widely, ranging from clinically impaired range to average or above average performance. Similarly, all subscales of parent and teacher report measures (CPRS and CTRS) also showed a wide range of concern, from no concern to clinically significant concern. Mean parent-rated learning problems fell within the high average range of concern, but did not reach the at-risk range of concern. No mean teacher-rated subscales reached the high average range of concern or above. Contrary to expectation, WJ Calculation was not significantly correlated with FSIQ (p = .12), nor was it significantly correlated with any IQ subscale (VCI, p = .20; PRI, p = .09, WMI, p = .09; PSI, p = .36). Age at testing was not correlated with WJ Calculation (p = .84) or with FSIQ (p = .10), and thus was not considered for inclusion in further analyses. See Table 1 for means, standard deviations, ranges, and Pearson’s r correlations with WJ calculation for all measured variables. WJ Calculation was significantly positively correlated with IVA Visual Response Control (r = .36, p < .05), Visual Attention (r = .29, p < .05), Visual Consistency (r = .31, p < .05), and Visual Focus (r = .29, p < .05) indices (see Table 1). As the Visual Consistency and Visual Focus indices are subscales of the Visual Response Control and Visual Attention indices, these were not included in further analyses. Relationship between IVA Visual Response Control and WJ Calculation is shown in Figure 1. Figure 1. View largeDownload slide Scatterplot of Woodcock-Johnson Calculation subtest scores as a function of Integrated Visual and Auditory Continuous Performance Test Visual Response Control subscale scores. Values are standard scores with a mean of 100 and a standard deviation of 15. Figure 1. View largeDownload slide Scatterplot of Woodcock-Johnson Calculation subtest scores as a function of Integrated Visual and Auditory Continuous Performance Test Visual Response Control subscale scores. Values are standard scores with a mean of 100 and a standard deviation of 15. For purposes of comparison, an exploratory analysis was conducted to investigate relationships between IVA performance and three other WJ subscales, each of which were completed by all 24 participants. Specifically, correlations with WJ Letter-Word (a measure of single-word reading accuracy), Passage Comprehension (a measure of reading comprehension requiring the participant to provide a word missing from a written sentence) and Spelling (a measure of written spelling of orally presented words). WJ Letter-Word was positively correlated with the IVA Auditory Focus subscale (r = .43, p < .05), and WJ Spelling was positively correlated with the IVA Full Scale Response Control Quotient (r = .41, p < .05). WJ Passage Comprehension was not significantly correlated with any IVA subscale. WJ Calculation was not significantly correlated with any CPRS index scores, but was significantly negatively correlated with CTRS Inattention (r = −.39, p < .05), Learning Problems (r = −.41, p < .05), and Executive Functioning (r = −.44, p < .05; see Table 1), indicating that poorer math performance was related to higher teacher-rated difficulties in these areas. CPRS Hyperactivity/Impulsivity was significantly positively correlated with IVA Auditory Stamina (r = .31, p < .05), indicating that higher parent-rated impulsivity was associated with better auditory stamina. CTRS Hyperactivity/Impulsivity and Learning Problems were significantly negatively correlated with IVA Visual Speed (r = −.48, p < .05), indicating that higher teacher-rated difficulties were associated with slower visual response speed. CPRS and CTRS Inattention were not significantly correlated with IVA index scores. See Table 2 for correlations between IVA and CPRS/CTRS scores. Table 2. Correlations between IVA scores and parent and teacher rating scales Measure  CPRS/CTRS  Inattention  Hyperactivity/Impulsivity  Learning problems  Executive functioning  IVA   Full Scale Attention  −.04/−.03  .05/−.35  −.07/−.23  −.09/−.15    Auditory Attention  −.06/−.06  .02/−.32  −.06/−.26  −.05/−.28     Auditory Vigilance  .08/−.08  −.07/−.28  .02/−.32  −.03/−.24     Auditory Focus  .01/−.06  .03/.11  −.09/.01  −.06/−.08     Auditory Speed  .10/.02  .27/−.15  −.08/−.36  .10/−.17    Visual Attention  −.04/.05  .15/−.31  .00/−.25  −.13/−.03     Visual Vigilance  −.05/−.32  −.05/−.28  −.004/−.21  −.24/−.28     Visual Focus  .15/.11  .05/−.19  .16/−.19  .05/−.07     Visual Speed  −.21/−.16  .07/−.48*  −.20/−.46*  −.19/−.21   Full Scale Response Control  .16/.08  .02/−.04  .08/.01  .02/.03    Auditory Response Control  .01/.04  .04/−.03  .02/.12  −.09/.07     Auditory Prudence  −.13/−.07  −.13/.09  −.10/.09  −.21/.02     Auditory Consistency  −.07/−.15  −.19/−.13  −.16/−.08  −.22/−.18     Auditory Stamina  .23/.16  .31*/.02  .16/.07  .29/.15    Visual Response Control  .07/−.11  −.08/−.17  −.004/−.20  −.05/−.31     Visual Prudence  .14/−.14  −.11/−.10  .06/−.07  .02/−.22     Visual Consistency  −.10/−.15  −.19/−.30  −.11/−.35  −.11/−.28     Visual Stamina  .10/.10  .08/.02  .10/.09  .06/−.03  Measure  CPRS/CTRS  Inattention  Hyperactivity/Impulsivity  Learning problems  Executive functioning  IVA   Full Scale Attention  −.04/−.03  .05/−.35  −.07/−.23  −.09/−.15    Auditory Attention  −.06/−.06  .02/−.32  −.06/−.26  −.05/−.28     Auditory Vigilance  .08/−.08  −.07/−.28  .02/−.32  −.03/−.24     Auditory Focus  .01/−.06  .03/.11  −.09/.01  −.06/−.08     Auditory Speed  .10/.02  .27/−.15  −.08/−.36  .10/−.17    Visual Attention  −.04/.05  .15/−.31  .00/−.25  −.13/−.03     Visual Vigilance  −.05/−.32  −.05/−.28  −.004/−.21  −.24/−.28     Visual Focus  .15/.11  .05/−.19  .16/−.19  .05/−.07     Visual Speed  −.21/−.16  .07/−.48*  −.20/−.46*  −.19/−.21   Full Scale Response Control  .16/.08  .02/−.04  .08/.01  .02/.03    Auditory Response Control  .01/.04  .04/−.03  .02/.12  −.09/.07     Auditory Prudence  −.13/−.07  −.13/.09  −.10/.09  −.21/.02     Auditory Consistency  −.07/−.15  −.19/−.13  −.16/−.08  −.22/−.18     Auditory Stamina  .23/.16  .31*/.02  .16/.07  .29/.15    Visual Response Control  .07/−.11  −.08/−.17  −.004/−.20  −.05/−.31     Visual Prudence  .14/−.14  −.11/−.10  .06/−.07  .02/−.22     Visual Consistency  −.10/−.15  −.19/−.30  −.11/−.35  −.11/−.28     Visual Stamina  .10/.10  .08/.02  .10/.09  .06/−.03  Note. Pearson’s r correlation coefficients between standardized test scores. *p< .05 **p< .01. FSIQ = Full Scale Intelligence Quotient; VCI = Verbal Comprehension Index; PRI = Perceptual Reasoning Index; WMI = Working Memory Index; PSI = Processing Speed Index; WJ = Woodcock Johnson Tests of Achievement 3rd edition; IVA = Integrated Visual and Auditory Continuous Performance Test; CPRS = Conners Parent Rating Scale; CTRS = Conners Teacher Rating Scale. FSIQ, VCI, PRI, WMI, and PSI refer to respective WISC-IV or WAIS-IV FSIQ, VCI, PRI, WMI, and PSI. Wechsler, WJ, and IVA scores are standard scores with M = 100 and SD = 15. Conners-3 Parent and Teacher scores are T-scores with M = 50 and SD = 10. Table 2. Correlations between IVA scores and parent and teacher rating scales Measure  CPRS/CTRS  Inattention  Hyperactivity/Impulsivity  Learning problems  Executive functioning  IVA   Full Scale Attention  −.04/−.03  .05/−.35  −.07/−.23  −.09/−.15    Auditory Attention  −.06/−.06  .02/−.32  −.06/−.26  −.05/−.28     Auditory Vigilance  .08/−.08  −.07/−.28  .02/−.32  −.03/−.24     Auditory Focus  .01/−.06  .03/.11  −.09/.01  −.06/−.08     Auditory Speed  .10/.02  .27/−.15  −.08/−.36  .10/−.17    Visual Attention  −.04/.05  .15/−.31  .00/−.25  −.13/−.03     Visual Vigilance  −.05/−.32  −.05/−.28  −.004/−.21  −.24/−.28     Visual Focus  .15/.11  .05/−.19  .16/−.19  .05/−.07     Visual Speed  −.21/−.16  .07/−.48*  −.20/−.46*  −.19/−.21   Full Scale Response Control  .16/.08  .02/−.04  .08/.01  .02/.03    Auditory Response Control  .01/.04  .04/−.03  .02/.12  −.09/.07     Auditory Prudence  −.13/−.07  −.13/.09  −.10/.09  −.21/.02     Auditory Consistency  −.07/−.15  −.19/−.13  −.16/−.08  −.22/−.18     Auditory Stamina  .23/.16  .31*/.02  .16/.07  .29/.15    Visual Response Control  .07/−.11  −.08/−.17  −.004/−.20  −.05/−.31     Visual Prudence  .14/−.14  −.11/−.10  .06/−.07  .02/−.22     Visual Consistency  −.10/−.15  −.19/−.30  −.11/−.35  −.11/−.28     Visual Stamina  .10/.10  .08/.02  .10/.09  .06/−.03  Measure  CPRS/CTRS  Inattention  Hyperactivity/Impulsivity  Learning problems  Executive functioning  IVA   Full Scale Attention  −.04/−.03  .05/−.35  −.07/−.23  −.09/−.15    Auditory Attention  −.06/−.06  .02/−.32  −.06/−.26  −.05/−.28     Auditory Vigilance  .08/−.08  −.07/−.28  .02/−.32  −.03/−.24     Auditory Focus  .01/−.06  .03/.11  −.09/.01  −.06/−.08     Auditory Speed  .10/.02  .27/−.15  −.08/−.36  .10/−.17    Visual Attention  −.04/.05  .15/−.31  .00/−.25  −.13/−.03     Visual Vigilance  −.05/−.32  −.05/−.28  −.004/−.21  −.24/−.28     Visual Focus  .15/.11  .05/−.19  .16/−.19  .05/−.07     Visual Speed  −.21/−.16  .07/−.48*  −.20/−.46*  −.19/−.21   Full Scale Response Control  .16/.08  .02/−.04  .08/.01  .02/.03    Auditory Response Control  .01/.04  .04/−.03  .02/.12  −.09/.07     Auditory Prudence  −.13/−.07  −.13/.09  −.10/.09  −.21/.02     Auditory Consistency  −.07/−.15  −.19/−.13  −.16/−.08  −.22/−.18     Auditory Stamina  .23/.16  .31*/.02  .16/.07  .29/.15    Visual Response Control  .07/−.11  −.08/−.17  −.004/−.20  −.05/−.31     Visual Prudence  .14/−.14  −.11/−.10  .06/−.07  .02/−.22     Visual Consistency  −.10/−.15  −.19/−.30  −.11/−.35  −.11/−.28     Visual Stamina  .10/.10  .08/.02  .10/.09  .06/−.03  Note. Pearson’s r correlation coefficients between standardized test scores. *p< .05 **p< .01. FSIQ = Full Scale Intelligence Quotient; VCI = Verbal Comprehension Index; PRI = Perceptual Reasoning Index; WMI = Working Memory Index; PSI = Processing Speed Index; WJ = Woodcock Johnson Tests of Achievement 3rd edition; IVA = Integrated Visual and Auditory Continuous Performance Test; CPRS = Conners Parent Rating Scale; CTRS = Conners Teacher Rating Scale. FSIQ, VCI, PRI, WMI, and PSI refer to respective WISC-IV or WAIS-IV FSIQ, VCI, PRI, WMI, and PSI. Wechsler, WJ, and IVA scores are standard scores with M = 100 and SD = 15. Conners-3 Parent and Teacher scores are T-scores with M = 50 and SD = 10. IVA Visual Response Control and Visual Attention were chosen to be entered into a hierarchical linear regression model based on their significant correlations with WJ Calculation. All entered variables had positive relationships with WJ Calculation. FSIQ was entered into the model first; however, this did not account for a significant amount of variance in WJ Calculation (p = .10). Next, IVA Visual Response Control and Visual Attention were entered together, and accounted for an additional 26.4% of the variance in WJ Calculation (p < .05) above that accounted for by FSIQ. Visual Response Control accounted for a significant portion of this variance (p < .05), whereas Visual Attention did not (p = .94). IVA Visual Response Control and Visual Attention were significantly correlated (r = .53, p < .005); however, there was no indication of significant collinearity between predictor variables (average variance inflation factor = 1.34). Results of this regression model are presented in Table 3. Table 3. Hierarchical linear regression model for WJ calculation   B  SE B  β  Step 1   Constant  61.63  24.19     FSIQ  .43  .25  .35  Step 2   Constant  28.83  24.08     FSIQ  .39  .23  .32   IVA Visual Response Control  .40  .16  .51*   IVA Visual Attention  .01  .15  .02    B  SE B  β  Step 1   Constant  61.63  24.19     FSIQ  .43  .25  .35  Step 2   Constant  28.83  24.08     FSIQ  .39  .23  .32   IVA Visual Response Control  .40  .16  .51*   IVA Visual Attention  .01  .15  .02  Note: R2 = .12 for Step 1, ΔR2 = .26 for Step 2. *p < .05 Table 3. Hierarchical linear regression model for WJ calculation   B  SE B  β  Step 1   Constant  61.63  24.19     FSIQ  .43  .25  .35  Step 2   Constant  28.83  24.08     FSIQ  .39  .23  .32   IVA Visual Response Control  .40  .16  .51*   IVA Visual Attention  .01  .15  .02    B  SE B  β  Step 1   Constant  61.63  24.19     FSIQ  .43  .25  .35  Step 2   Constant  28.83  24.08     FSIQ  .39  .23  .32   IVA Visual Response Control  .40  .16  .51*   IVA Visual Attention  .01  .15  .02  Note: R2 = .12 for Step 1, ΔR2 = .26 for Step 2. *p < .05 Discussion The current study aimed to investigate relationships between math calculation skills and performance on an objective measure of attention and parent- and teacher-reported inattention among survivors of childhood ALL. It was hypothesized that performance on objective measure of sustained attention and parent- and teacher-reported inattention would explain a significant amount of the variance in math skills among childhood ALL survivors beyond expected variation in performance based on IQ. Although scores on all measures varied from clinically impaired to superior, mean IQ, math calculation, and speed and stamina of responding to visual and auditory stimuli all fell within one standard deviation of normative mean scores. Other aspects of visual sustained attention and response control fell between .55 and 1.1 SD below the normative mean, and mean auditory sustained attention and response control was somewhat lower, falling between 1.4 and 1.6 SD below the normative mean. Mean parent-rated learning problems fell within the high average range of concerns. Results indicated that objective measures of attention, specifically response control for visual stimuli, did account for a significant amount of variance in math performance. Significant relationships were observed between math performance and IVA Visual Response Control and Visual Attention index scores; however, only Visual Response Control accounted for a significant amount of variance in math performance after controlling for FSIQ. The apparent relationship between attention and math performance is particularly compelling given the less-robust relationships between IVA and other academic skills: single-word reading and spelling were significantly correlated with one IVA subscale each, and reading comprehension was not correlated with IVA performance. Although teacher-rated inattention, learning problems, and day-to-day executive functioning were significantly negatively correlated with math performance, parent-rated attentional difficulties did not bear statistically significant relationships to math performance. Teacher-rated, but not parent-rated, inattention was significantly negatively correlated with math performance. This indicates that parent perception of inattention may be an indication of a different type of attentional deficit than that associated with math performance. Interestingly, parent-rated hyperactivity/impulsivity was significantly positively correlated with IVA Auditory Stamina, a component of auditory response control, whereas teacher-rated hyperactivity/impulsivity was significantly negatively correlated with IVA Visual Speed, a component of visual sustained attention. This suggests that aspects of auditory attention may be more salient in behavioral difficulties in the home environment (e.g. response to verbal directions), whereas aspects of visual attention may be more salient in the school environment (e.g. attention to written assignments). The relationship between math performance and response control for visual, as opposed to auditory, stimuli, may be related to the particular importance of visual (as opposed to auditory) information processing for the acquisition of math skills (Barnes & Raghubar, 2014; Halberda, Mazzocco, & Feigenson, 2008). The current findings provide further support for the existing literature supporting a relationship between visuospatial and visuomotor skills and math performance. Specifically, longitudinal studies have indicated that visuospatial working memory predicts later math skills in typically developing children (Barnes et al., 2014), and visuomotor integration predicts later math skills in survivors of childhood ALL (Balsamo, Sint, Neglia, Brouwers, & Kadan-Lottick, 2015; Moore et al., 2016). It may be the case that visual attention difficulties are a common factor underlying the relationships between visual working memory, visuomotor integration, and math skills. Furthermore, difficulty regulating responses resulting in variable response times may lead to difficulty in efficient learning of math facts and computational strategies. Existing literature indicates that attentional deficits are common among survivors of childhood ALL; further investigations are needed to clarify potential causal relationships between visual response control deficits and acquisition of math calculation skills. Observed relationships between math performance and objective attention performance, but not with parent-rated inattention, in the current study indicates that objective attention testing may have clinical utility in identifying children at risk for math difficulties should such a causal relationship exist. Additional directions for future studies include whether interventions to improve attention and response control deficits reduce the risk for math and other academic difficulties before they become apparent, in ALL survivors and other pediatric populations. A weakness of the current study is the relatively small sample size which potentially limits the statistical power to detect significant relationships between the variables of interest. Furthermore, the sample employed here consisted of children referred by a physician due to academic or behavioral difficulties. This may limit generalizability of the findings to ALL survivors who are not currently experiencing such difficulties, but may also result in higher clinical utility for children who are experiencing difficulties. The number of correlations calculated here does raise the possibility of Type 1 error, and suggests the importance of replication of the present findings. Of note, two participants were treated with psychostimulant medications and one was treated with antipsychotic and anticonvulsant medication at the time of testing, which may have impacted objective attention performance as well as parent and teacher ratings of behavior. This may have introduced a source of variability in the data and thus limited the ability to detect potential relationships between the variables of interest. The sample was also chosen for relative homogeneity in cancer diagnosis and chemotherapy-only treatment, thus reducing potential variance attributable to the potential impacts of cancer and its treatments on cognitive functioning. Further investigations employing larger sample sizes will be helpful in confirming the current findings. Similarly, it would be clinically relevant to determine whether the relationships between attention and math observed here hold among students who are experiencing educationally significant difficulties in math, as the sample included in the current study performed, on average, within the average range on math testing. Although significant relationships were observed between teacher ratings of attentional difficulties and objective math performance, the current sample size did not allow teacher ratings to be included in regression analysis; further investigation of this relationship with larger sample sizes may be informative. Furthermore, investigation of relationships between attention and math difficulties in non-ALL childhood cancer survivors and other pediatric populations are needed to determine whether the current findings are generalizable to children experiencing academic difficulties with non-ALL etiologies. Likewise, investigations of potential relationships between other academic skills and various aspects of attention in this population may be informative. Results of the current study suggest that routine screening for attentional difficulties among childhood cancer survivors using a brief computerized evaluation may have the potential to identify students at risk for math difficulties. Furthermore, use of an objective measure of attention may be more effective in identifying students at risk for math difficulties than commonly used parent behavioral rating scales. For students experiencing math difficulties, consideration of potential associated visual attention difficulties may be useful in informing selection and execution of math interventions. Should a causal relationship between early-developing visual attention and later math difficulties be borne out, early intervention for attentional difficulties may have potential to reduce risk for future math difficulties in childhood ALL survivors. Funding No funding was used to conduct this study. Conflict of interest The authors report no conflicts of interest. Acknowledgements This study was conducted with the approval of the Institutional Review Board of the University of Michigan Medical School, reference HUM00046285. References Balsamo, L. M., Sint, K. J., Neglia, J. P., Brouwers, P., & Kadan-Lottick, N. S. ( 2015). The association between motor skills and academic achievement among pediatric survivors of acute lymphoblastic leukemia. 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Archives of Clinical NeuropsychologyOxford University Press

Published: Jan 24, 2018

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