Neurobehavioral Functioning in Children with Fetal Alcohol Spectrum Disorder

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Neurobehavioral Functioning in Childrenwith Fetal Alcohol Spectrum DisorderCarmen Rasmussen a , Kathy Horne b & Adrienne Witol ca University of Alberta, Edmonton, Albertab Glenrose Rehabilitation Hospital and University of Alberta,Pediatrics, Edmonton, Albertac University of Alberta, Pediatrics and Stollery Children's Hospital,Edmonton, AlbertaPublished online: 03 Feb 2007.

To cite this article: Carmen Rasmussen , Kathy Horne & Adrienne Witol (2006) NeurobehavioralFunctioning in Children with Fetal Alcohol Spectrum Disorder, Child Neuropsychology: A Journalon Normal and Abnormal Development in Childhood and Adolescence, 12:6, 453-468, DOI:10.1080/09297040600646854

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Child Neuropsychology, 12: 453–468, 2006Copyright © Taylor & Francis Group, LLCISSN: 0929-7049 print / 1744-4136 onlineDOI: 10.1080/09297040600646854

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NEUROBEHAVIORAL FUNCTIONING IN CHILDREN WITH FETAL ALCOHOL SPECTRUM DISORDER

Carmen Rasmussen,1 Kathy Horne,2 and Adrienne Witol31University of Alberta, Edmonton, Alberta, 2Glenrose Rehabilitation Hospital andUniversity of Alberta, Pediatrics, Edmonton, Alberta, 3University of Alberta, Pediatricsand Stollery Children’s Hospital, Edmonton, Alberta

Neurobehavioral functioning of 50 Canadian children diagnosed with Fetal Alcohol Spec-trum Disorder (FASD) was evaluated. The aims of this study were to identify specific areasof weakness in neurobehavioral functioning, to examine whether neurobehavioral func-tioning was related to various predictor variables, and to determine which measures differ-entiated between children given a brain score of 2 (possible dysfunction) and 3 (probabledysfunction). Participants displayed difficulties with many aspects of intelligence, memory,executive functioning, and attention. Measures of Full scale and Verbal IQ, as well asmemory for faces and numbers differentiated between children with a brain 2 and 3 rank-ing. An interesting pattern of strengths and weaknesses emerged as well as significant dif-ferences related to ethnic background, gender, and age. Aboriginal children and Caucasianchildren with FASD do not appear to show the same pattern of strengths and weaknesses inneurobehavioral functioning.

Prenatal alcohol abuse is one of the largest causes of preventable brain injury inchildren (National Institute of Alcohol Abuse and Alcoholism, 1990). Children with FetalAlcohol Spectrum Disorder (FASD) may have deficits in physical, behavioral, emotional,and/or social functioning as a result of prenatal alcohol exposure (see Streissguth &O’Malley, 2000 for a review). Many also have deficits of vision, hearing, speech, andlocomotor function, as well as structural and functional brain damage and many secondarydisabilities including mental health problems, trouble with law, confinement, alcohol anddrug abuse, and dropping out of school (Streissguth, 1997). The emotional, social, andeconomic costs of FASD are lifelong for affected individuals, their families, and the com-munity. Characterization of the social, genetic, and comorbid factors that contribute toalcohol abuse during pregnancy, to understanding the pathophysiological mechanisms thatresult in FASD, and to development of effective treatment and preventative strategieshave been disturbingly inadequate.

The term FASD is not intended for use as a clinical diagnosis, but it is an umbrellaterm used to describe the full range of outcomes observed among individuals with prenatal

We would like to thank Jeffrey Bisanz for methodological advice and comments on a previous draft ofthis manuscript.

Address correspondence to Carmen Rasmussen, Department of Pediatrics, University of Alberta, 137Glenrose Rehabilitation Hospital, 10230-111 Ave, Edmonton, Alberta T5G 0B7. Tel: (780) 735-7999, ext15631. Fax: (780) 735-7907. E-mail: [email protected]

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454 C. RASMUSSEN ET AL.

alcohol exposure. Streissguth and O’Malley (2000) noted difficulties associated with face-based diagnoses because not all children prenatally exposed to alcohol show facial dys-morphology and thus recommended the use of the umbrella term FASD. Furthermore,Central Nervous System (CNS) deficits do not necessarily differ among those previouslydiagnosed with Fetal Alcohol Syndrome (FAS) and Fetal Alcohol Effects (FAE) (Mattson& Riley, 1998; Sampson, Streissguth, Bookstein, & Barr, 2000). Diagnosis now focusesmore on CNS deficits, emphasizing the necessity to identify the unique neurobehavioralprofile of these individuals to determine precise diagnostic criteria.

Neuropsychological impairments in FASD include lower IQ, achievement deficits,and learning problems (Streissguth, Barr, Sampson, & Bookstein, 1994), deficitsin memory, attention, visual-spatial abilities, declarative learning, processing speed(Carmichael Olson, Feldman, Streissguth, Sampson, & Bookstein, 1998) as well as lan-guage and motor delays (for a review see Mattson & Riley, 1998). Children and adultswith FASD also have deficits in executive functioning in the areas of cognitive flexibility,inhibition, planning, strategy use, verbal reasoning, set-shifting, working memory, andfluency (Carmichael Olson et al., 1998; Mattson, Goodman, Caine, Delis, & Riley, 1999;Schonfeld, Mattson, Lang, Delis, & Riley, 2001, see Rasmussen, 2005 for a review).However, less is known about the profile of strengths and weakness in particular areas ofneurobehavioral functioning in individuals with FASD.

There can also be difficulty assessing and diagnosing FASD in a clinical setting.Enhanced assessment and diagnosis of FASD are necessary in order to develop a sensi-tive, reliable, and valid screening tool. This research project addresses issues of develop-ing a neurobehavioral profile, refining assessment and diagnosis, as well as providinginformation about possible cultural differences in FASD. Participating children were diag-nosed using the Fetal Alcohol Syndrome Diagnostic and Prevention Network (FAS DPN)4-digit coding system developed at the University of Washington (Astley & Clarren,1999). However, there is limited research regarding this model’s utility with a Canadianpopulation. Cultural differences can impact the validity of many psychometric measures.Consequently, careful examination and determination of local normative samples for newassessment models are typically recommended as part of developing an effective diagnos-tic model. Also, more information is needed on the types of CNS deficits that differentiatebetween children given a brain-functioning score of 2 (possible dysfunction) and 3 (prob-able dysfunction). Furthermore, certain demographic characteristics may be associatedwith FASD, which warrant further investigation.

In this study psychological assessment results were analysed in the areas of intelli-gence, memory, executive functioning, and attention in children and adolescents diag-nosed with FASD. There were three major goals in this study: first, to determinewhether a distinct pattern of strengths and weaknesses emerged to better understand theneurobehavioral sequelae of individuals with FASD; second, to examine whether per-formance on the neurobehavioral tests was related to various predictor variables includ-ing age, ethnicity (Aboriginal, Caucasian), gender, as well as growth, face, and brainscores; third, to compare those children given a brain score of 2 (possible dysfunction)and 3 (probable dysfunction) in order to determine which tests differentiated betweenthose with different brain dysfunction classifications. The information gained fromthese analyses is imperative to better understand the profile of FASD in Canada as wellas possible cultural differences in FASD characteristics. This research has implicationsfor refinements to the assessment process in order to address the most salient diagnosticfeatures of FASD. Information from this study may help guide future assessment and

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NEUROBEHAVIORAL FUNCTIONING IN CHILDREN WITH FASD 455

research by indicating key areas that might warrant further investigation to enhance thediagnostic process.

METHOD

Participants

Fifty Canadian children clinically diagnosed with Fetal Alcohol Spectrum Disorder(FASD) through the Glenrose Rehabilitation Hospital FASD Clinical Services partici-pated in the study. The participants were a clinical referred sample. Demographic charac-teristics of the sample are presented in Table 1 and 2. The diagnostic process involvedassessments conducted by a multidisciplinary team (Psychologist, Speech-LanguagePathologist, Occupational Therapist, Social Worker, and Developmental Pediatrician)using a combination of approaches including formal standardized and nonstandardizedmeasures, rating scales, interviews, clinical observations, photographic analysis, andinformation from families, caretakers, preschools, schools, and community clinicians.Diagnoses were made using the Fetal Alcohol Syndrome Diagnostic and Prevention Net-work (FAS DPN) 4-digit coding system developed at the University of Washington(Astley & Clarren, 1999). This system ranks diagnostic information in the areas of growthdeficiency, facial phenotype, brain dysfunction, and alcohol use. The magnitude ofexpression of each diagnostic feature is ranked independently on a 4-point Likert scale,with 1 reflecting complete absence of the FAS feature and 4 reflecting a strong “classic”presence of the FAS feature. For all 50 participants prenatal alcohol exposure was con-firmed, with alcohol use scores of 3 or 4. Rankings of growth deficiency and facial pheno-type were made by a Developmental Pediatrician.

Relevant to this study are brain rankings of 2 and 3, which are considered intermedi-ate categories between brain 1, no evidence of brain damage, and brain 4 referring to braindamage confirmed by traditional medical approaches. Brain 3 ranking refers to probablebrain dysfunction and was assigned when psychometric results indicated significant defi-ciencies across multiple functions. Brain 3 criteria require that there be a “hit” in three or

Table 1 Demographic Characteristics of Sample.

NMean Age

(in years: months)Age Range

(in years: months) Ethnicity (n) Living Arrangement (n)

50 9:5 6:0 to 15:7 Caucasian (14) Foster parent (22)20 males Aboriginal (35) Biological mother (11)30 females Other (1) Guardian (8)

Biological father (4)Adopted parent (4)Grandparent (1)

Table 2 Age, Gender, and Ethnicity Across Levels of Brain Functioning.

Age Gender Ethnicity

Brain 2 8:8 10 males, 15 females 19 Aboriginal, 6 CaucasianBrain 3 10:2 8 males, 12 females 12 Aboriginal, 7 CaucasianBrain 4 10:6 2 males, 3 females 4 Aboriginal, 1 Caucasian

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more of the following areas: sensory/motor, communication, attention, intellectual,academic achievement, memory, executive functioning, and adaptive functioning. A “hit”is defined as a test result of minus two or more standard deviations below the mean. TheFAS DPN 4-digit coding system requires “hits” in at least three domains to assign a rankingof brain 3. The coding system does not require that specific domains need to be a “hit” for abrain 3 ranking because there is not a specific pattern of required “hits” that have been iden-tified, nor is there any weighting of domains to suggest relative importance for the diagno-sis. Even if there is more than one test score of – 2SD in a domain, only one “hit” is countedfor that domain. A brain 3 ranking is still assigned when there are “hits” in more than threedomains. In other words, more “hits” does not lead to a ranking of Brain 4, which isassigned only when specified “hard” medical criteria are reached. These criteria includemicrocephaly, structural abnormalities, and/or other evidence of hard neurological find-ings. Brain 3 is a very broad category of probable brain dysfunction, called “static encepha-lopathy” in the Washington FAS DPN Coding system. It is intended to reflect a wide rangeof difficulties most likely related to diffuse nonspecific brain dysfunction.

Brain 2 refers to possible brain dysfunction and was assigned when current data didnot support a ranking of 3 or 4, despite strong suggestion of underlying brain damagebased on histories of behavioral and/or cognitive problems. Some patients were too youngto receive a full range of assessments. For others some preliminary test results were signif-icant but did not meet diagnostic criteria of minus two standard deviations in three or moreareas. For a brain 2 ranking, called “neurobehavior disorder” in the Washington FAS DPNCoding system, there is indication of concern suggesting possible brain dysfunction, butthe criterion of three “hits” is not reached. Ranking of brain 2 has been most challengingclinically. For example some children may have received test results within the range of 11/2 to almost 2 standard deviations below the mean across three or more domains, yet donot meet criterion of three “hits” of −2 SD to receive a brain 3 ranking. Clinically we con-sider FASD to be a developmental diagnosis in that not all characteristics are necessarilyevident at a young age yet can emerge as demands increase for more abstract, higher ordercognitive processing and more complex and independent academic, social, and otherdemands of daily functioning.

Although assessment results from a Speech-Language Pathologist and OccupationalTherapist in the sensory/motor and communication domains were used to determine thebrain score, only the psychology results were analyzed in this study. Because only chil-dren with confirmed prenatal alcohol exposure are seen in the clinic, participants had analcohol exposure score of 3 or 4. As evident in Table 3, of the 50 children with confirmedalcohol exposure, the vast majority showed no growth or facial abnormalities and scored 1for unlikely, yet none of the children scored 1 for brain dysfunction.

Table 3 Percentage of Children Scoring 1, 2, 3, or 4 in each FASD Diagnostic Category.

Score Growth Face Brain Alcohol

1 92% (46) 66% (33) 0% (0) 0% (0)2 4% (2) 16% (8) 50% (25) 0% (0)3 2% (1) 18% (9) 40% (20) 62% (31)4 2% (1) 0% (0) 10% (5) 38% (19)

Note: For Growth, Face, and Brain a scores were: 1- unlikely, 2- possible, 3- probable, 4-definate. For Alcoholexposure: 1- none, 2- unknown, and 3- and 4- confirmed.

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Materials and Procedures

All 50 children were administered an intelligence test. However, for all other measuresonly subsets of children (24 or more) were administered the tests. Only psychology testsadministered to 24 or more children were included in the analyses, which allowed analysisof the intellectual, memory, executive functioning, and attention domains. The tests thatwere administered usually depended on the age of the children and their level of functioning.

Wechsler Intelligence Scale for Children-Third Edition (WISC-III). TheWISC-III was administered individually to test general intelligence of 40 children witha mean age (in years:months) 10:2 (range 6:0 to 15:7). Canadian norms were used. Onthe Wechsler tests Full scale, Performance, and Verbal Scales have a mean of 100 andstandard deviation of 15 and subtests have a mean of 10 and standard deviation of 3.Standard scores from 90 to 110 were considered to be in the Average Range, scoresfrom 80 to 89 to be in the Low Average Range, and scores of 70 to 79 to be in theBorderline Range.

Wechsler Preschool and Primary Scale of Intelligence-Revised (WPPSI-R).

The WPPSI-R was administered to 10 children aged (in years:months) 6:5 (range 6:0 to 7:3).Children’s Memory Scale (CMS). The CMS was administered to 24 children

with a mean age of 10:5 (range 6:0 to 15:7). The CMS yields six index scores; visual imme-diate, visual delayed, verbal immediate, verbal delayed, attention/concentration, and learn-ing. Each Index scores had a mean of 100 and a standard deviation of 15. Index standardscores range from 50 to 150. The Children’s Memory Scale was co-normed with the WISC-III. Score ranges for Average, Below Average, and Borderline categories are based onWISC-III criteria that was described in the preceding section. The index scores are com-prised of different subtests, each with a mean of 10 and standard deviation of 3. The CMSdot locations subtest yields a learning, total, and long delay score. The stories subtest has animmediate, delayed, and delayed recognition memory score. The faces subtest has an imme-diate and delayed memory score. The word pairs subtest yields a learning, total, long delay,and delayed recognition score. The number and sequences subtests both have a total score.The two subtests that measure visual memory (dot locations and faces) combine to yieldvisual immediate and visual delayed index scores. Similarly, scores from stories and wordpairs yield the immediate and delayed verbal index scores. The numbers and sequences sub-tests combine to form an attention/concentration index score. The learning subtest from dotlocations and words pairs combine to form a learning index score and the delayed recogni-tion from stories and word pairs combine to form a delayed recognition index score.

Behavioral Rating Inventory of Executive Function (BRIEF). The parentBRIEF was completed on 31 children with a mean age of 10:1 (range 6:0 to 15:7) and theteacher BRIEF was completed on 26 children with a mean age of 9:8 (range 6:0 to 15:3).The BRIEF is a report of executive function behaviors including inhibition, set shifting,emotional control, working memory, planning, organizational skills, and monitoringskills. Both the parent/guardian and teacher completed the BRIEF. Scores on the BRIEFhave a mean of 50 and standard deviation of 10, with higher scores indicating more diffi-culty. Abnormally elevated scores suggesting clinical significance are indicated byT-scores of 65 or greater that is at least 1.5 standard deviations above the mean.

Parent and Teachers Conners’ Ratings Scales-Revised (CRS-R). The par-ent Conners was completed on 24 children with a mean age of 10:4 (range 6:0 to 15:7) andthe teacher Conners was completed on 25 children with a mean age of 9:8 (range 6:0 to15:3). The Conners’ rating scale was used to screen children for symptoms of ADHD. The

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subscales of the Conners provide measures for various behavioral characteristics includingoppositionality, cognitive problems, inattention, hyperactivity, anxiety, perfectionism,social problems, and psychosomatic tendencies. Scores on the Conners have a mean of 50and standard deviation of 10, with higher scores indicating more difficulty. Again, clini-cally elevated scores are indicated by T-scores of 65 or greater (1.5 SD above the mean).

RESULTS

Data Analysis

The results section is organized by each domain that was measured; intelligence,memory, executive functioning, and attention. For each test, performance across the dif-ferent subtests was examined to determine if a unique profile or pattern emerged. Then,any significant relations between test performance and any of the predictor variables (age,gender, ethnicity, and brain, face, and growth scores) were examined. Lastly, childrenwith a brain 2 and 3 were compared on the measures.

First examined were correlations among the independent predictor variables todetermine if any relations existed. Age was correlated with ethnicity (1: Caucasian, 2:Aboriginal), r(49) = .38, p < .01, indicating that, in general, the older children tended to beAboriginal. Growth deficiency correlated with facial phenotype r(49) = .36, p < .05, indi-cating that children with more severe growth deficiency also show more facial characteris-tics. There were no other significant correlations between the predictor variables.

Intelligence

For analyses with Full, Verbal, and Performance IQ the results from the WISC-III andWPPSI-R were combined. However, for subtest analyses only subtests from the WISC-IIIwere used because the subtests differ between the WISC-III and WPPSI-R and the samplesize on the WPSSI-R was too small for separate subtest analyses. See Table 4 for the WISC-III IQ scores across different levels of Brain scores and see Table 5 for the average WPPSI-R IQ scores. As measured with the WISC-III and WPPSI-R children showed Low Average

Table 4 Mean (SD) Full Scale, Verbal and Performance IQ on the WISC-III for the different Brain Classifications(N = 40).

Brain Full Scale IQ Verbal IQ Performance IQ

2 85.5 (2.2) 85.6 (2.3) 89.1 (2.3)3 79.8 (2.0) 76.6 (3.0) 88.7 (2.9)4 58.8 (1.4) 55.8 (3.2) 66.8 (3.2)

Table 5 Mean Full Scale, Verbal and Performance IQ on theWPPSI-R (N = 10).

WPPSI-R Mean (SD)

Full Scale IQ 86.6 (89.9)Verbal IQ 83.3 (7.7)Performance IQ 93.5 (14.5)

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to Borderline Full scale IQ, Performance IQ, and Verbal IQ (See Table 6). Mean Perfor-mance IQ was significantly higher than Verbal IQ, F (1, 49) = 17.95, p < .01. In fact, 41.7%(20) of the children had a clinically significant Performance-Verbal split with PerformanceIQ being higher, whereas only 6.3% (3) had a significant split with Verbal IQ higher, andthe rest of the children showed no difference. This discrepancy appears to be mediated byethnic background, because, of the 20 children who showed higher Performance than Ver-bal IQ, 75% (15) were Aboriginal. For Aboriginal children mean Performance IQ was muchhigher than Verbal IQ, F(1, 34) = 23.08, p < .01. For Caucasian children, however, therewas no difference between Performance and Verbal IQ, F (1, 13) = 1.5, p = 0.3.

Mean performance on the Verbal and Performance subtests of the WISC-III are alsopresented in Table 7. All Verbal subtests except Information were below average,although there was no statistical difference among the Verbal subtests F(5, 33) = 1.01, p >.05. All Performance subtests were within the low average to normal range, and againthere was no statistical difference among the subtests F(5, 30) = 2.17, p > .05.

Correlations between the IQ measures and independent predictor variables wereconducted. Brain dysfunction was significantly correlated with full IQ (r = −.65), Perfor-mance IQ (r = −.45), and Verbal IQ (r = −.62), ps < .01. Thus, IQ decreased as brain dys-function increased. All other correlations were nonsignificant, but the correlation betweenage and Verbal IQ approached significance, r = −.25, p = .08. Because age was correlatedwith ethnicity we also conducted this correlation with ethnicity partialled out, and now thecorrelation between age and Verbal IQ was significant (r = −.33, p < .05 ). Thus, VerbalIQ appears to be lower with age among children with FASD.

Among the subtests, performance on the comprehension subtest was correlated withboth age (r = −.39, p < .05) and ethnicity (r = .38, p < .05). When ethnicity was partialled

Table 6 Mean Full Scale, Verbal, and Performance IQ on theWISC-III and WPPSI-R Combined (N = 50).

WPPSI-R Mean (SD)

Full Scale IQ 80.9 (11.4)Verbal IQ 78.7 (13.4)Performance IQ 87.5 (13.2)

Table 7 Mean Performance on the Subtests of the WISC-III.

Mean (SD)

V-Information 7.92 (12.0)V-Similarities 6.81 (3.3)V-Arithmetic 5.82 (2.6)V-Vocabulary 5.72 (3.14)V-Comprehension 5.60 (3.3)V-Digit Span 6.50 (2.3)P-Picture Completion 8.03 (2.9)P-Picture Arrangement 8.18 (2.8)P-Coding 7.05 (2.6)P-Block Design 7.46 (3.1)P-Object Assembly 7.97 (3.3)P-Symbol Search 8.89 (3.3)

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out, age was still highly correlated with comprehension (r = −.54, p < .01). Thus, perfor-mance on comprehension was lower with age. Likewise, when age was partialled out, eth-nicity was still correlated highly with comprehension (r = .54, p < .01) and now also withsimilarities (r = .41, p < .05). These results, suggest than Aboriginal children with FASDappear to perform lower than Caucasian children with FASD on comprehension and simi-larities. None of the predictor variables correlated with the Performance subtests.

Next, children with brain 2 and 3 were compared on IQ. Children with brain 2 (M =86.28, SD = 8.7) had a higher Full scale IQ than those with brain 3 (M = 79.7, SD = 8.4),F(1, 44) = 6.56, p < .05. Children with brain 2 also had a higher Verbal IQ (M = 85.0, SD =8.6) than those with brain 3 (M = 76.65, SD = 12.7), F(1, 44) = 6.78, p < .05. The twogroups did not differ on Performance IQ.

Memory

Mean performance on all subtests and index scores of the CMS are presented inTable 8. There was a significant effect across the seven index scores, F(6, 18) = 4.58, p < .01.Performance was in the borderline range on attention/concentration and verbal delay andin the low average range on verbal immediate, but only marginally below average on theother index scores. Thus, performance on attention/concentration subtests (numbers andsequences) are particularly difficult for individuals with FASD, as are measures of verbaldelayed memory (stories and word pairs subtests).

The next analysis was a 2(Condition: verbal, visual) × 2(Type: immediate, delayed)repeated measures ANOVA on the index scores to determine whether performance

Table 8 Average Scores on the Children’s Memory Scale (subtests are indented)

Score (SD)

Visual Immediate Index 88.14 (14.9)Dot locations 9.47 (2.9)Faces 7.25 (2.6)

Visual Delayed Index 91.43 (13.7)Dot locations 10.04 (3.2)Faces 8.05 (2.7)

Verbal Immediate Index 84.86 (13.7)Stories 8.10 (2.6)Word pairs 7.20 (2.8)

Verbal Delayed Index 75.5 (15.5)Stories 7.15 (3.4)Word pairs 6.65 (3.7)

Attention/Conc. Index 74.21 (12.5)Numbers 6.83 (2.5)Sequences 5.28 (2.5)

Learning Index 89.43 (14.2)Dot locations learning 8.92 (2.9)Word pairs learning 7.50 (3.1)

Delayed Rec Index 91.93 (12.7)Storied delayed rec 8.45 (2.06)Word pairs delayed rec 8.90 (3.5)

Note: All index scores have a mean of 100 and standard deviation of 15, andall scaled subtest scores have a mean of 10 and standard deviation of 3.

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differed across condition and type. There was no effect of condition or type, but there wasa condition by type interaction, F(1, 18) = 4.52, p < .05. The source of this interaction wasthat for visual index scores, delayed memory was higher than immediate memory,whereas for verbal index scores immediate memory was higher than delayed memory.Next, we conducted two repeated measures ANOVAs to determine whether performancediffered among the visual and verbal subtests. There was an effect across the visual sub-tests, F(3, 19) = 50.6, p < .01, in that performance was highest on dot locations delayedand immediate, and performance was lowest on faces immediate and delayed. There wasno effect across the verbal subtests, F(3, 10) = 1.22, p = .31.

Correlations were conducted among the predictor variables and CMS index scores.Ethnicity was significantly correlated with the visual immediate (r = −.51, p < .05) and visualdelayed in index scores (r = −.65, p < .01). All other correlations were nonsignificant. Thecorrelations between ethnicity and visual immediate (r = −.50, p < .05) and visual delayedindex scores (r = −.64, p < .01) were still highly significant even when age was partialled out.Thus, the Aboriginal children performed higher than the Caucasian children on visual mem-ory tasks. The correlations with ethnicity and verbal index scores were nonsignificant, but inthe opposite direction. To further explore this difference we compared Aboriginal and Cauca-sian children on both verbal and visual index scores and found that on visual memory theAboriginal children (M = 101.00, SD = 10.8) performed significantly higher than the Caucasianchildren (M = 85.50, SD = 11.5), F(1, 16) = 8.74, p < .01. In contrast, Caucasian children (M =97.91, SD = 12.6) performed much higher than Aboriginal children (M = 74.36, SD = 19.1),F(1, 16) = 4.67, p < .05 on verbal memory (see Figure 1). Thus, the generally higher perfor-mance on visual over verbal memory evident in Table 2 may be due to the fact that the major-ity of the sample was Aboriginal and may not be unique to FASD.

Next children with a brain 2 and 3 were compared on all subtests of the CMS. Chil-dren with a brain 3 scored significantly lower (M = 6.0, SD = 2.7) than those with a brain2 (M = 8.5, SD = 1.9) on the faces immediate memory subtest, F(1, 17) = 4.74, p < .05,and close to significant (M = 9.5, SD = 1.5 and M = 7.1, SD = 3.3, respectively), on thefaces delayed subtest, F(1, 17) = 3.63, p = .08. Children with a brain 3 (M = 4.2, SD = 0.8)

Figure 1 Performance of Aboriginal and Caucasian children on the visual and verbal indexes of the CMS.

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also scored lower than those with a brain 2 (M = 5.1, SD = 0.7) on the numbers forwardsubtest F(1, 15) = 5.55, p, .05. Children with a brain 2 and 3 did not differ on any of theother subtests.

Executive Functioning

For both the parent and teacher BRIEF scores the majority scales were within theAbnormally Elevated range (at least 1.5 SD above the mean), reflecting difficulty withexecutive functioning. See Figure 2. Validity scores were within the acceptable range forall the parents and teachers BRIEFs. Two repeated measures ANOVAs were conducted todetermine whether performance differed among the subtests separately for parent andteacher forms. There was a subtest effect on the parent form, F (7, 29) = 4.22, p < .01, inthat scores were highest (indicating most difficulty) on plan/organize and working mem-ory and lowest on organization of materials and shifting. There was no subtest effect forthe teacher form, F(7, 24) = 1.29, p = .26. Furthermore, teacher ratings (M = 81.48, SD =17.1) were higher than parent ratings (M = 71.78, SD = 11.7) on the Global ExecutiveComposite score of the BRIEF, t (53) = 2.69, p < .01.

Gender was highly correlated with all parent scores (rs = .48 to .56, ps < .01). Thus, par-ents of girls reported more difficulty with executive function than parents of boys. Subsequentanalysis of the means revealed that overall girls scored higher than boys, but this differencewas only significant on the parent form. No other correlations with the predictor variables weresignificant. Children with a brain 2 and 3 did not differ on the parent or teacher BRIEF.

Attention

Scores on both the teacher and parent Conners were within the clinical range (atleast 1.5 SD above the mean). See Figure 3. Gender correlated with the teacher inattentivescore (r = .43, p < .05), indicating that girls tended to have higher inattentive scores than

Figure 2 Parent and teacher ratings of executive functioning measured with the BRIEF.

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boys. No other correlations with the predictor variables were significant. Children withbrain 2 and 3 did not differ on any of the Conners’ scores.

DISCUSSION

The goal of this research was to examine the neurobehavioral profile of a sample ofCanadian children diagnosed with FASD to identify specific areas of weakness, and todetermine whether neurobehavioral functioning was related to various predictor variablesincluding age, ethnicity (Aboriginal, Caucasian), gender, as well as diagnostic ratings ofgrowth, face, and brain scores. Children given a brain score of 2 (possible dysfunction)and 3 (probable dysfunction) were also compared to determine which psychological testsdifferentiated between different classifications of brain dysfunction. These results haveimplications for assessment, diagnosis, understanding the profile of FASD, and for identi-fying cultural differences.

All children were diagnosed using the FAS DPN model (Astley & Clarren, 1999),which provides 4-digit rankings of growth deficiency, facial phenotype, brain dysfunction,and alcohol exposure. All 50 children with confirmed prenatal alcohol exposure showedevidence of brain dysfunction, but very few children showed evidence of growth or facialabnormalities. In fact, 92% of the children showed no growth deficiency and 66% showedno facial characteristics. This finding supports the notion that relatively few children prena-tally exposed to alcohol actually show the growth and facial abnormalities previouslyrequired to diagnose FAS (Sampson et al., 2000) and stresses the importance of the newterm FASD. Many researchers have found that the neuropsychological deficits occur to thesame degree among children with no facial and growth abnormalities (FAE) and those withfacial and growth abnormalities (FAS) (Mattson et al., 1998; Sampson et al., 2000). Thisstudy adds to previous research, suggesting that brain dysfunction is one of the most impor-tant determinants of FASD diagnoses and diagnosis should not be dependent on growth offacial characteristics. Poor cognitive functioning appears to be a more sensitive indicator ofacquired brain injury than growth and facial characteristics. Comparison to normativescores revealed significant differences in cognitive functioning for children exposed toalcohol. Group differences and the results for each domain are reviewed below.

Figure 3 Parent and teacher ratings of ADHD measured with the Conner’s rating scale.

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Intelligence

Mean Full scale IQ scores fell in the Below Average range. Performance waspoorest on the comprehension subtest followed by vocabulary and arithmetic and high-est on symbol search and picture arrangement. Age correlated negatively with Verbal IQand with the comprehension subtest, indicating that on tests of Verbal IQ, and specifi-cally comprehension, older children with FASD showed more difficulty (relative to thenorm) than younger children with FASD. Thus, difficulty on some verbal tasks appearsto be more pronounced with age in FASD. The brain dysfunction ranking also correlatedwith IQ and children with a brain 2 had higher Full scale and Verbal IQ than those witha brain 3.

Both the comprehension and similarities subtests correlated with ethnicity indicat-ing that Aboriginal children with FASD performed lower than Caucasian children onthese subtests. Overall, performance IQ was significantly higher than Verbal IQ. How-ever, this finding appears to be related to ethnic background, as the Aboriginal childrenshowed mean Performance IQ scores higher than Verbal IQ, but the Caucasian childrenshowed no difference. Thus, this Verbal-Performance split appears to hold only for theAboriginal children with FASD. This finding has been frequently reported amongAboriginal individuals without FASD (Beiser & Gotowiec, 2000, see Rasmussen, Sher-man, & Baydala, 2004, for a review). In their review, Mattson and Riley (1998) notedthat there have been many discrepancies in the literature on Performance and Verbal IQwith some researchers finding Performance higher than Verbal whereas others foundVerbal higher than Performance IQ. Perhaps, these inconsistencies may be mediated bythe ethnic background of the sample, but more research is needed to substantiate theseclaims.

Memory

Children with FASD showed weakness on many subtests of the CMS. Among theindex scores, performance was well below average on attention/concentration, followedby verbal delayed and immediate memory. The attention/comprehension index is com-prised of the numbers and sequences subtests, which were particularly difficult for chil-dren with FASD. Both immediate auditory attention and verbal information processingspeed appear to be areas of difficulty for this sample. In terms of performance on memorysubtests, a unique profile emerged among the visual but not the verbal subtests. For visualsubtests, performance was lowest on faces immediate and faces delayed subtests and high-est on dot locations. Memory for faces may be a particular area of weakness for childrenwith FASD. Furthermore, the memory for faces and the numbers forward subtests werethe only subtests to differentiate between children with a brain 2 and 3.

Aboriginal children with FASD performed higher than Caucasian children on visualmemory tasks; however, on tests of verbal memory, Aboriginal children performed morepoorly than Caucasian children. Thus, a completely different memory profile emergeddepending on the ethnicity of the FASD sample. For Aboriginal children with FASD ver-bal memory is a weakness but visual memory is average, in contrast, for Caucasian chil-dren with FASD, visual memory is a weakness but verbal memory is average. Previousresearchers have found visual-spatial memory deficits among children with FASD (Kaemingk& Halverson, 2000; Uecker & Nadel, 1996). Thus, the lower verbal memory than visualmemory may be due to that fact that many children were Aboriginal and may not be

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unique to FASD. Aboriginal individuals without FASD have been reported to have highervisual-spatial memory than verbal memory (see Rasmussen et al., 2004 for a review).

Executive Functioning

The children with FASD showed elevated scores on both the parent and teacherBRIEF indicating deficits in executive functioning. In general, teacher ratings were higher(indicating more difficulty) than parent ratings. Thus, children with FASD may showmore difficulty with executive functioning in school than at home. One possible reason forthis finding is that the school environment may place extra demands on executive func-tioning as the child is in an environment that requires focusing attention, set-shifting (i.e.,switching classes and tasks), planning, and the child must be highly organized to keep ontask and not fall behind the rest of the class. Also, teachers may be more likely to identifyproblems when comparing the child to other children in the class as opposed to parentsdetermining if a behavior is problematic at home.

On the parent form, the children had most difficulty with plan/organizing followedby working memory and least difficulty with shifting followed by organization of materi-als. Thus, it appears that plan/organizing and working memory are particularly difficultfor children with FASD. Both skills require sequencing and linking various steps togetherin a timely fashion. These difficulties may be analogous to those problems identified bythe Children’s Memory Scale Attention/Concentration Index score that were discussedpreviously. Working memory has been previously noted to be a specific area of difficultyin children with FASD (Jacobson et al., 1998; Kodituwakku et al., 1995; Streissguth, Barr, &Sampson, 1990).

On the parent form, girls were rated as having more executive functioning difficul-ties than boys. Thus, it appears that at least at home, parents of girls are reporting moredifficulty with executive functioning than parents of boys. This finding may reflect partic-ular a bias among parents of girls or it may be that girls with FASD display more seriousdeficits in executive functioning than boys. To our knowledge no other researchers havefound such gender differences in executive functioning, thus further research is warranted.Neither the parent nor teacher BRIEF differentiated between children given a brain 2 and3 ranking. Scores on the BRIEF were very high (indicating deficits) for both those with abrain 2 and 3, thus it appears even if there were to be a difference it is not detectable onthis scale as both are near the ceiling. However, it also may be that executive functioningis severely impacted in FASD even at lower levels of brain dysfunction (brain 2) whereasother cognitive abilities (i.e., IQ) are less severely affected at lower levels of dysfunction.If so, this finding highlights the significance of the impact of prenatal alcohol exposure onexecutive functioning.

Attention

The children showed marked difficulties with attention on both the parent and teacherConners’ rating forms. On the teacher form, girls had higher inattentive scores than boys,which is consistent with previous research (Biederman & Faraone, 2004). Children with abrain 2 and 3 did not differ on the Conners’ ratings scales. Similar to the results of theBRIEF, the lack of a difference between brain 2 and 3 may reflect a ceiling effect or it maybe that like executive functioning, attention is also significantly impacted at lower levels ofbrain dysfunction, and thus is a significant weakness for children with FASD.

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Conclusions and Implications

The individuals with FASD showed difficulties on many aspects of intelligence,memory, executive functioning, and attention. On some measures a unique profileemerged. For instance, distinct deficits were found on memory for Numbers andSequences, and among visual memory, tests of Memory for Faces were the most diffi-cult. In other words, Children with FASD appear to have greater difficulty on tasksstressing auditory attention skills, information processing speed, and certain aspects ofvisual memory. In keeping with these difficulties, children showed most difficulty withthe BRIEF Plan/Organize and Working Memory scales. Difficulties with auditory atten-tion and information processing speed can impact the amount of information a child isable to absorb. Typical teaching rate may be too rapid for children with FASD, resultingin large amounts of missed information. Slowing down and providing repetition andother ways to help children pick up on missed information may be particularly importantfor children with FASD. Finally, Performance on Verbal IQ and comprehension alsoappeared to worsen (relative to the norm) with age. Verbal IQ and Comprehension areboth sensitive to both developmental and academic experiences. Children with FASD donot progress at the same rate as children without acquired brain injury. Children withFASD may be less able to benefit from these types of didactic experiences and requiremore direct remedial type training.

Some unique cultural effects also emerged. The finding of higher Performance overVerbal IQ appears to be due to the fact that the majority of the sample was Aboriginal andmay not be specific to FASD. On the memory test, for Aboriginal children, visual memorywas higher than verbal memory (which was below average), but for Caucasian childrenverbal memory was higher than visual memory (which was below average). This findinghas implications for intervention with Aboriginal and Caucasian children with FASD.Aboriginal children with FASD appear to have strengths in visual memory and thus wouldlikely benefit from the use of picture and visual cue to remember details, steps of tasks,and daily activities. In school and at home these children may find it very difficult whengoals or tasks are verbally stated to them without a visual aide. For Caucasian childrenwith FASD, this is not to discourage visual memory aids as any memory aid may be help-ful. But for these children it may be beneficial to build on their verbal memory strengths interms of verbally recalling lists and using verbal coding to remember things. Their deficitsin visual memory may lead to various difficulties ranging from finding their way, organiz-ing their room, or remembering details of pictures and patterns, and thus any other aide inthese areas would likely provide an advantage. Similarly, these difficulties may translateto additional problems in classes that stress visual memory and processing of informationsuch as higher level mathematics, science, and geometry.

This study was an attempt to better understand neuropsychological profiles of Cana-dian children and adolescents with FASD. Unique effects related to the ethnic backgroundof the sample emerged, which have strong implications for both diagnosis and treatment.Aboriginal children with FASD may display a different profile of strengths and weak-nesses than Caucasian children with FASD and further research in this area is warranted.These results have implications for refinements to the assessment process and have high-lighted specific areas in which further research is needed. Of particular interest are the var-ious tests that differentiated between brain 2 and 3 scoring criteria. Executive functioningskills appear to be very sensitive even at lower brain scores. In our sample Full scale andVerbal IQ scores as well as the numbers and memory for faces subtests of the CMS

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differentiated between brain 2 and 3. Academic funding criteria that are dependent on Fullscale IQ scores may result in missing children with pervasive executive functioning defi-cits that can be equally limiting academically and socially. Additional research in this areais sorely needed, as having tangible, measurable descriptors for each category will help toimprove diagnostic accuracy and subsequently treatment planning and resource allocation.Limitations of this study include the small sample size, not all children being administeredevery measure, and a sample based on children referred due to suspected problems. How-ever, due to difficulties obtaining an appropriate sample, small sample sizes are relativelycommon in the research on FASD.

In summary, FASD, a Canadian health concern, impacts affected individuals andtheir families, as well as the communities and health care systems serving these children.Management of childhood FASD-related difficulties that persist or worsen in adult lifenow consumes large amounts of resources within health care facilities, education systems,and the community. Compared to what is known about outcomes, there is relatively littleknown about accurate diagnosis, particularly with adolescents. For many children withFASD, early diagnosis and subsequent intervention can help ameliorate the emotional,financial, and societal impacts felt throughout the lifespan. Findings of this study enhanceunderstanding of assessment and diagnostic considerations for FASD, as well as suggest-ing areas needing further research.

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Documents

Neurobehavioral Functioning in Children with Fetal Alcohol Spectrum Disorder