Psycho-Social Characteristics of Children with Prenatal Alcohol Exposure, Compared to Children with Down Syndrome and Typical Children

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1 J Dev Phys Disabil (2012) 24: DOI /s ORIGINAL ARTICLE Psycho-Social Characteristics of Children with Prenatal Alcohol Exposure, Compared to Children with Down Syndrome and Typical Children Erin L. Way & Johannes Rojahn Published online: 25 February 2012 # Springer Science+Business Media, LLC 2012 Abstract The aim of this study was to extend the literature on cognitive and psychosocial adjustment and on facial processing in children with Prenatal Alcohol Exposure (PAE). Twenty-five children with PAE, 23 neurotypical children, and 13 children with Down syndrome matched on sex and mental age participated. Parents or guardians completed the Conners Comprehensive Behavior Rating Scale for Parents and the Social Responsiveness Scale; participants completed facial processing tasks. Using MANOVAs, the PAE group had substantially higher standard scores on all CBRS-P and SRS subscales compared with the typical group, and on almost all of them compared with the Down syndrome group. A large portion of individuals in the PAE group had clinically significant scores on the CBRS-P subscales, including ADHD, conduct and oppositional/defiant disorder, autism spectrum disorder, major depression, manic episodes, generalized and separation anxiety and phobias. Using a MANCOVA, no group differences were found in facial processing between the PAE and the neurotypical groups. Many children with PAE had scores that exceeded cut-offs for autism spectrum disorders, ADHD, conduct disorder, oppositional/defiant disorder, major depression, manic episodes, generalized and separation anxiety, and phobias. In addition, academic, language and mathematics problems were noted relative to typical children. Finally, children with PAE performed just as well on the facial processing tasks as a group of younger typical children of equal mental age. That means that facial processing by children with PAE was corresponded with their mental age. Keywords Prenatal alcohol exposure. Fetal alcohol syndrome. Facial processing. ADHD. Conduct disorder. Oppositional defiant disorder. Autism. Major depression. Mania. Generalized anxiety. Separation anxiety. Social behavior. Academic problems E. L. Way Alvernia University, Reading, PA, USA erin.way@alvernia.edu J. Rojahn (*) George Mason University, Fairfax, VA, USA jrojahn@gmu.edu

2 248 J Dev Phys Disabil (2012) 24: Prenatal alcohol exposure (PAE) has deleterious effects on brain development with the potential to cause serious and chronic deficits in cognitive, motor and behavioral functioning (Riley et al. 2011). Fetal Alcohol Spectrum Disorders (FASD) is an umbrella term that encompasses a variety of neuro-developmental outcomes that include fetal alcohol syndrome (FAS), partial FAS (pfas), alcohol-related neuro-developmental disorder (ARND), and alcohol-related birth defects (ARBD) (Greenbaum et al. 2009; Mattson et al. 2011; Riley et al. 2011; Ryan and Ferguson 2006). FASD prevalence estimates vary from study to study ranging in the US from one to seven per 1,000 births (Riley et al. 2011). Children with PAE often have borderline to mild intellectual disabilities (Jacobson and Jacobson 2002; Streissguth et al. 1991; Weinberg 1997) and deficits in executive function and related cognitive abilities such as attention, problem solving and planning, inhibitory control, and working memory. Other problems have been reported in language and math skills, visuo-spatial coordination, and motor skills (e.g., Burden et al. 2005a, b; Kodituwakku et al. 2001a, b; Mattson et al. 2006). For a comprehensive literature review on neuropsychological and behavioral features associated with PAE see Mattson et al. (2011). Emotional and behavioral problems are also frequently observed in individuals with PAE, often to the extent that they reach diagnostic significance. These include hyperactivity (e.g., Aronson et al. 1997; Mick et al. 2002; Crocker et al. 2009), conduct problems and oppositional behavior (e.g., Fryer et al. 2007; Ryanand Ferguson 2006; Steinhausen et al. 2003; Weinberg 1997), depression (e.g., Fryer et al. 2007), and anxiety (Steinhausen et al. 2003). It is, therefore, not surprising that poor academic achievement is also common among children with PAE (Fryer et al. 2007). In addition, children with PAE tend to have impaired socio-emotional competence (Crocker et al. 2009; McGee et al. 2009; Thomas et al. 1998; Whaley et al. 2001) and other autism-like traits (e.g., Bishop et al. 2007; Harris,MacKay,& Osborn, 1995; Mukherjee et al. 2011). Mukherjee et al. (2011) have speculated that autism-like traits may actually account for socio-emotional difficulties in individuals with PAE. The ability to decode non-verbal social information is important to social interaction and thus has been presumed to be a critical component of socio-emotional competence (Halberstadt et al. 2001). Many studies have relied on facial emotion recognition tasks as a proxy for socio-emotional adjustment in many different clinical populations, including schizophrenia (Feinberg et al. 1986; Heimberg et al. 1992), depression (Gilboa-Schechtman et al. 2004; Gur et al. 1992), social phobia (Gilboa- Schechtman et al. 1999), Huntington disease (Sprengelmeyer et al. 1997), senile dementia (Brosgole et al. 1983), alexithymia (Lane et al. 1996; McDonald and Prkachin 1990), psychosomatic disorders (Gerhards 1998). There is also a growing body of evidence about deficits in processing facial cues in general and facially displayed emotions in particular among populations with intellectual and/or developmental disabilities. These associations are found, foremost among individuals with autism (Bar-Haim et al. 2006; Behrmann et al. 2006; Farran et al. 2011; Volkmar et al. 1989; Webb et al. 2006), but also with Williams syndrome (Karmiloff-Smith et al. 1995, 2004; Plesa-Skewerer et al. 2005), Down syndrome (Kasari et al. 2001; Kasari and Sigman 1996; Smith and Dodson

3 J Dev Phys Disabil (2012) 24: ; Wishart et al. 2007), and with non-specified intellectual disabilities (Rojahn et al. 1995). Despite the perception of sociability as a strength of individuals with Down syndrome (Wishart et al. 2007), several studies point to limitations in facial emotion processing (Kasari et al. 2001; Williams et al. 2005; Wishart et al. 2007). These deficits emerge as early as 3 to 4 years of age, and unlike the pattern of development for typically developing individuals, individuals with Down syndrome do not show continuing improvement with increasing mental or chronological age (Wishart et al. 2007). This lack of improvement in emotion recognition and labeling may have applications for research on children with PAE because several studies report arrested socialemotional development in children with prenatal alcohol exposure (Coggins et al. 2003; J. L. Jacobson and S. W. Jacobson 2002; Kelly et al. 2000; Streissguth et al. 1991; Thomas et al. 1998). More recently, a few studies on facial processing in PAE have appeared in the literature as well. Greenbaum et al. (2009) examined the relationship between social cognition, emotion processing, behavior problems, and social skills. They compared 33 children with PAEs (mean age09.2 years; mean IQ085.1) with 30 children with ADHD (mean age09.3 years; mean IQ0104.3), and 34 typically developing children (mean age08.9 years; mean IQ0114.3) on a battery of social-cognition tasks. Participants ranged from six to 13 years of age. The authors concluded that children with PAE had weaker social cognition and facial emotion processing ability than the ADHD group and the typical control group. In another study, Siklos (2010) compared 22 children and adolescents with PAE (ages 8 to 14; mean IQ084.7, SD08.3) and a control group of typically developing peers matched on chronological age and sex (mean IQ0110.1, SD010.8). Siklos (2010) found that the PAE group had greater difficulties than the typically developing group in recognizing emotions from facial expressions. It is crucial to point out that neither Greenbaum et al. (2009) nor Siklos (2010) incorporated control groups that were mental age (or IQ) matched with the PAE group. Hence, strictly speaking neither one of those studies allows us to determine whether the facial processing shortcoming by the PAE group was due to the mental age of its members, or whether other factors were responsible (i.e. the autistic like behaviors observed in prior studies of children with PAE). Also, neither study featured a facial processing control task to distinguish between processing faces in general from processing affective cues in faces, a distinction of potential importance (Rojahn et al. 1995). This project is a variation of the studies by Greenbaum et al. (2009) and Siklos (2010). We set out to examine to what extent cognitive abilities, comorbid psychiatric conditions, behavior problems, and socio-emotional abilities are related to facial processing, and specifically emotion recognition skills in individuals with PAE. The main difference is that we compared a group of children with PAE with a group of neurotypical children and a group of children with Down syndrome of similar mental age. The Down syndrome group was chosen to provide a comparison group with a similar level of developmental disability. We also employed emotion and non-emotion related facial processing tasks, by which we attempted to determine whether potential deficits in the PAE group occur in facial processing in general, or in facial emotion processing in particular.

4 250 J Dev Phys Disabil (2012) 24: Method Participants PAE Group Twenty-five individuals with a clinically confirmed prenatal alcohol exposure volunteered to participate in the PAE group. There were 7 males and 18 females; the mean chronological age was 8.8 years (SD02.3; ranging from 5.5 to 14.4); the mean PPVT standard score was 85.7 (SD020.4; ranging from 49 to 123); four participants had PPVT scores below 70, an approximate cut off for intellectual disability. The mean PPVT mental age equivalence was 6.7 years (SD02.3, ranging from 2.1 to 12.0). PAE participants were recruited from the National Organization on Fetal Alcohol Syndrome (NOFAS) in Washington, D.C. and its affiliates in three East Coast states (Virginia, Maryland, and North Carolina) and one Midwestern state (Ohio) (See Table 1 for more demographic information). While all participants had a FASD diagnosis, information on the diagnostic process was not available. Nine children (36%) were diagnosed with Fetal Alcohol Syndrome (FAS), seven (28%) reported a Partial Fetal Alcohol Syndrome (pfas) diagnosis, and five children (20%) reported a diagnosis of Alcohol Related Neuro-Developmental Disorder (ARND). The remaining four children (16%) were diagnosed with abnormal brain development (structural and functional anomalies) and had confirmed prenatal alcohol exposure; thus these individuals were identified as having a FASD, but had not received one of the recognized diagnoses (FAS, pfas, ARND, ARBD) on the Spectrum. The children were almost exclusively in the custody of a non-birth parent (96%), and 90% of the 21 parents/guardians reported that their child had been placed into the current home within the first 2½years of life (62% within the first year). Among 14 (56%) participants who were taking psychotropic and/or anticonvulsant medication, 13 took some form of psychotropic medication (Risperdal, clonidine, concerta, focaline, abilify, tenex, Adderall, Stratera, Methylin) and five took anticonvulsant medication (Lamictal, Keppra, Seroquil, Oxcarbazepine, Depakote). Seven received more than one type of medication; and four took both psychotropic and anticonvulsant medication. Six PAE participants did not take any psychotropic or anticonvulsant medication and no information was available for five participants. Neurotypical Group Twenty-three children, 11 male and 12 female with a mean age of 6.4 years (SD02.1; ranging between 2.5 and 9.8) were individually matched with a PAE participant on sex and mental age (PPVT-III developmental age equivalent within the 68% confidence interval of the PAE participant). The average developmental age was 6.67 (SD02.41; ranging from 2.07 to 11.09), and the mean PPVT standard score was (SD09.2; ranging from 91 to 123). Neurotypical participants were recruited from local pre-schools and after school programs in two East Coast States of the US. None of the participants in the neurotypical group were taking medication based on parent report.

5 J Dev Phys Disabil (2012) 24: Down Syndrome Group This group was composed of 14 individuals with Down syndrome, three male and 11 female with a mean age of 9.8 years (SD01.9; ranging from 6.3 to 11.8). They were matched to participants from the PAE group on chronological and mental age. The mean PPVT-III mental age was 5.5 years (67.1 months, SD , range 40 to 104 months) and their mean PPVT-III standard score was 64.9 (SD011.5, ranging from 40 to 83). Each individual of the Down syndrome group was matched to a PAE participant on developmental age within the 68% confidence interval. Participants were recruited through parent support groups and professionals in Virginia, North Carolina, and Tennessee. All participants had a diagnosis of Down syndrome, but information on genetic subtyping was not available. Parents reported that the diagnosis of their child had been based on formalized karyotype analysis. One participant with Down syndrome took a psychotropic medication. Assessment Instruments Peabody Picture Vocabulary Test III (PPVT III) The PPVT-III (Dunn et al. 1997) is a widely used, standardized test of English language receptive vocabulary (word knowledge). A study by Hodapp and Gerken (1999) in 7 to 11.5 year old children found correlations between PPVT-III and the Wechsler Intelligence Scale for Children-III (WISC-III) standard scores ranging from.56 to.88, with the highest correlation between the WISC-III Verbal IQ and the PPVT-III, and the lowest between the WISC-III Processing Speed and the PPVT-III. The main reason to choose the PPVT-III was that it provides a developmental age equivalent score that has been used as the measure of mental age (MA). Social Responsiveness Scale (SRS) The SRS (Constantino and Gruber 2005) assesses reciprocal social behavior in five domains: Social Awareness, Social Cognition, Social Communication, Social Motivation, and Autistic Mannerisms. A person familiar with the target individual s behaviors rates the severity/frequency with which the individual performs the behaviors, ranging from: 10 Not True to 40 Almost Always True. Raw scores are converted into standard T-scores. T-scores of 59 or less fall into the normal range; T-scores between 60 and 75 (or one SD above the mean) reflect mild to moderate problems; and T-score of 76 or higher (or two SDs above the mean) are indicative of severe problems. In addition to the SRS total score, domain scores are calculated. The SRS can be used to assess social responsiveness in individuals between 4 and 18 years-of-age and is often used to screen for autism spectrum disorders.internal consistency for the SRS items with a sample of children which included some diagnosed with autism spectrum disorders and some with other psychiatric conditions produced a coefficient of.97 (Constantino and Gruber 2005; Venn 2007). The testretest reliability over a period of 17 months was also high (.85 for males,.77 for females). Discriminant analyses revealed scoring high on the SRS was significantly

6 252 J Dev Phys Disabil (2012) 24: associated with an autistic disorder, but not with intelligence or other recognized psychiatric disorders/conditions (Constantino and Gruber 2005). Scores on the SRS and the Autism Diagnostic Interview-Revised (ADI-R, Lord et al. 1994) were highly associated when completed on the same individual (Constantino and Gruber 2005). The SRS was included in this study to test for the presence of autistic behaviors, which if found in the group with PAE would be consistent with the findings of others studies (Mukherjee et al. 2011). The SRS was chosen over other assessments of autistic behaviors because deficient social interaction skills are commonly reported in children with PAE and the SRS provides information on reciprocal social behaviors (Constantino and Gruber 2005) which are presumably related to facial emotion recognition. Conners Comprehensive Behavior Rating Scale for Parents (CBRS-P) The Conners CBRS-P (Conners 2008) is a normed and standardized parent rating scale that was designed to assess mental and behavior problems in individuals between six and 18-years-of age. Items are scored on a four-point Likert-type frequency scale ranging from 00 Not true at all (never, seldom) to 30 Very much true (very often, very frequently). The Conners CBRS-P has eight Symptom scales: Emotional Distress (which includes the subdomains Upsetting Thoughts, Worrying, andsocial Problems), Aggressive Behaviors, Academic Difficulties-Total, Academic Difficulties-Language, Academic Difficulties-Math, Hyperactivity/Impulsivity, Separation Fears, and Perfectionistic and Compulsive Behaviors. There are also two Rational subscales: Violence Potential, and Physical Symptoms. Finally, there are 12 clinical Psychiatric Disorders subscales that correspond with Axis-I disorders of the Diagnostic and Statistical Manual, 4th edition, Text Revision (DSM-IV-TR; American Psychiatric Association 2000): Attention-Deficit/Hyperactivity (ADHD) Disorder-Inattentive, ADHD-Impulsive, Conduct Disorder, Oppositional Defiant Disorder, Major Depressive Episode, Manic Episode, Generalized Anxiety, Separation Anxiety, Social Phobia, Obsessive-Compulsive Disorder, Autistic Disorder, and Asperger s Disorder. The CBRS-P has good internal consistency (Cronbach s alphas ranging from.78 to.95 across the eight symptom scales and alphas ranging from.73 to.93 across the 12 DSM-IV-TR scales) (Conners 2008). Two to four week test-retest reliability ranged from.70 to.96 across the domains and from.66 to.95 across the DSM-IV-TR disorders, which is evidence to support its reliability across time. Discriminant analyses revealed 78.4% of the individuals assessed were correctly classified using the CBRS-P (Conners 2008). Facial Processing Tasks The facial processing tasks consisted of two experimental tasks (or emotion facial processing tasks) and two control tasks (or non-emotion facial processing tasks). In order to control for a potential confound, the tasks were presented in two paradigms, matching-to-sample and labeling. The images for these four tasks were selected from the NimStim database (Tottenham et al. 2009), a collection of frontal view color photographic portraits of young adults of both sexes of Caucasian, African American,

7 J Dev Phys Disabil (2012) 24: and Asian ethnicity. The photographs were modified so that only the face proper (without hair) was visible. Emotion Tasks The emotion tasks consisted of 33 trials (five practice and 28 test trials), each consisting of a labeling and a matching-to-sample component. During each trial participants were first shown a face positioned at the top center on the computer screen, approximately 3 in height, against a white background. Each emotion task trial started with emotion labeling. The participants were instructed to look at the face presented on the screen and to name the emotion displayed by the face. The faces had happy, sad, angry, afraid, or calm (neutral) expressions. Correct responses were acknowledged by the experimenter and incorrect responses were rectified to ensure that the subsequent matching-to-sample task was equal for all participants, regardless whether they had labeled the expression correctly or not. After the labeling, the trial continued with the emotion matching component. The face used during labeling remained on the screen and now functioned as the sample stimulus. Five new faces appeared in a row across the bottom of the screen (the correct match and four distractors). They were roughly of equal size as the matching stimulus. Each of the five faces displayed one of those five emotions. The participant had to point to the face in the bottom row that showed the same emotion as displayed by the sample. Across trials each of the five emotions was represented in each of the five positions of the array. The position of the emotions depicted by the matching stimuli was randomized across trials. Both portions of the emotion task took about 30 min to complete. Non-Emotion Tasks The non-emotion facial processing tasks also consisted of a matching-to-sample and a labeling task. In the gender task (labeling), participants were asked to identify the person s sex. The task consisted of 24 trials (2 practice and 22 test trials) and all faces displayed a neutral expression. The gender task served as the control task for the labeling portion of the emotion task. The identity task (matching) consisted of 18 trials (3 practice and 15 test trials) in which the participants were first shown a sample-face at the top center of the screen. Then five faces of the same sex and ethnicity as the sample appeared underneath screen (the correct match and four different individuals faces to serve as distractors). The correct match was an alternate photograph of the sample. All faces displayed a neutral expression.. The identity task served as the control task for the matching-tosample portion of the emotion task. The responses on the facial processing tasks of each participant were converted into percent correct scores. Procedure The parent or guardian of each participating child completed the CBRS-P, the SRS and a demographics survey while the primary investigator administered the PPVT-III and the facial processing tasks. The facial processing task was administered either at the participants homes or in a center. Stimuli were presented on a 2006 Gateway MX6426 Notebook PC with a 15.4 in. screen. The participants were seated at arms-

8 254 J Dev Phys Disabil (2012) 24: length directly in front of the laptop screen to allow the child to point to their choice of response (if they desired) Consistent with the response options for the PPVT-III, both verbal (stating the number under the face) and non-verbal (pointing to the face) responses were acceptable. Since we were not interested in a direct comparison of the four tasks, the tasks were presented in a fixed sequence starting with the gender task (presented first lest the participants become familiar with the Nimstim faces), followed by the identity task, and then followed by the emotion tasks. Results Statistical analyses were performed with the PASW Statistics18 software for Windows. As expected, the groups differed in their chronological age (one-way ANOVA F [2] 013.2, p<.001, with the Down syndrome group being the oldest, followed by the PAE group, and trailed by the neurotypical group. Table 1 Demographic information by group PAE Neurotypical Down syndrome n % n % n % Gender Female Male Age groups (in yrs.) 2.5 through through through Ethnicity Caucasian African American Multi-racial Other Not reported Other diagnoses Learning Disability ADHD Mood Disorder Anxiety Disorder Autistic Spectrum Intellectual Disability Epilepsy

9 J Dev Phys Disabil (2012) 24: Table 2 Descriptive Statistics and Group Differences of the PPVT-III, SRS, Conners CBRS-P, and the Facial Processing Tasks PAE Neurotypical Down syndrome Statistical Group Comparisons 1 n M SD n M SD n M SD Age in months DS>PAE>NT PPVT Standard Score NT>PAE>DS Age Equivalent (mos.) PAE, NT, DS SRS Total SRS Score PAE>DS>NT Social Awareness PAE, DS>NT Social Cognition PAE>DS>NT Communication PAE>DS>NT Social Motivation PAE>NT, DS Autistic Mannerisms PAE>DS>NT CBRS-P empirical Emotional Distress PAE>NT>DS Upsetting Thoughts PAE>NT>DS Worrying PAE>NT>DS Social Problems PAE>DS>NT Aggressive Behaviors PAE>NT>DS Academic Difficulties PAE, DS>NT Language PAE, DS>NT Mathematics PAE, DS>NT Hyperactive/Impulsive PAE>NT, DS Separation Fears PAE>NT, DS Perfectionistic/Compulsive PAE>NT, DS CBRS-P rational Violence Potential PAE>NT, DS Physical Symptoms PAE>NT, DS CBRS-P psychiatric disorders ADHD-Inattentive PAE>DS>NT ADHD-Impulsive PAE>NT, DS Conduct PAE>NT, DS Oppositional/Defiant PAE>NT, DS Major Depressive PAE>NT, DS Manic Episode PAE>NT, DS Generalized Anxiety PAE>NT, DS Separation Anxiety PAE>NT, DS Social Phobia PAE>NT, DS Obsessive/Compulsive PAE>NT, DS Autistic PAE>DS>NT Asperger PAE>DS>NT

10 256 J Dev Phys Disabil (2012) 24: Table 2 (continued) PAE Neurotypical Down syndrome Statistical Group Comparisons 1 n M SD n M SD n M SD Facial processing task Gender (labeling) PAE, NT, DS Identity (matching) PAE, NT>DS Emotion (labeling) PAE, NT, DS Emotion (matching) PAE, NT>DS SRS social responsiveness scale; CBRS-P Conners comprehensive behavior rating scale for parents; PAE prenatal alcohol exposure; 1 0all group differences were on the.001 level, except when specified otherwise in the text Peabody Picture Vocabulary Test (PPVT) PPVT-III standard scores were different across groups (one-way ANOVA F [2]0 34.1, p<.001. Post hoc comparisons using Gabriel s procedure for uneven group sizes showed that the neurotypical group had significantly higher PPVT-III standard scores than the PAE group, which in turn had significantly higher scores than the Down syndrome group (all p<.001). However, no statistically significant group differences were found in PPVT age equivalence (F [2]02.4 p0.12). Means and standard deviations of the three groups are presented in Table 2. Social Responsiveness Scale (SRS) To compare groups on their SRS total standard scores (Social Responsiveness), a oneway ANOVA was computed. Significant group differences were found (F [2, 54] , p<.001). Post hoc comparisons using Gabriel s procedure showed that the PAE had significantly higher SRS total standard scores than the Down syndrome group, and that the Down syndrome group had significantly higher scores than the neurotypical group (all p<.001). Figure 1 presents the SRS mean T-scores and standard deviations. A MANOVA was computed to compare the two groups on the five subscales standard scores. The multivariate test was significant, λ0.15 (F [10, 96]015.1, p<.001)between-subjects-effects showed that the three groups differed on all five subscales (p<.001). The PAE had significantly higher scores than the neurotypical group on all five SRS subscales, while the Down syndrome group had higher scores than the neurotypical group on the subscales Social Cognition, Social Communication, and Autistic Mannerisms. The PAE group had statistically higher scores than the Down syndrome group on all but the Social Awareness subscale. Conners Comprehensive Behavior Rating Scale for Parents (CBRS-P) Symptom Scales Figure 2 shows the mean T-scores and standard deviations of select CBRS-P Symptom scales. A MANOVA was computed to compare the three groups

11 J Dev Phys Disabil (2012) 24: Fig. 1 Mean T-scores and standard deviations of the Social Responsiveness Scale subscales. Scores between the lower horizontal and the upper horizontal lines indicate mild to moderate problems, scores above the higher horizontal line fall into the severe problems range on the standard scores of the 11 empirical Symptom Scales. The multivariate effect for the groups was significant λ0.13 (F [22, 80] 06.5, p<.001). Tests of betweensubjects-effects showed group differences on all subscales at the.001 significance level, except for the subscales Upsetting Thoughts and Separation Fears, where the groups differed only on the.01 level. Pairwise group comparisons of the Academic Difficulties, Language, and Mathematics subscales showed higher scores for the PAE group and the Down syndrome group compared to the neurotypical group, without significant group differences between the PAE and Down syndrome groups. On the Social Problems scale the PAE group had higher scores than the Down syndrome group, which in turn had higher scores than the neurotypical group. On the subscales Hyperactive/Impulsive, Separation Fears, and Perfectionistic/Compulsive, the PAE group had higher scores compared to the two other groups, without differences between the neurotypical and the Down syndrome groups. The final remaining four subscales, Emotional Distress, Upsetting Thoughts, Worrying, and Aggressive Behaviors showed higher PAE scores compared to the neurotypical group, which in turn had higher scores than the Down syndrome group (See Table 2). Rational Scales Another MANOVA compared the CBRS Rational scales scores of the three groups. The multivariate test was significant, λ0.43 (F [4, 100]013.4, p<.001). Tests of between-subjects-effects showed that the groups differed

12 258 J Dev Phys Disabil (2012) 24: Fig. 2 Mean T-scores and standard deviations of select CBRS-P Symptom scales. The horizontal like indicates two standard deviations above the mean. The horizontal line indicates two standard deviations above the mean significantly from one another on both the Violence Potential (F [2] , p<.001, and Physical Symptoms (F [2] 019.2, p<.001) scales. Post hoc pairwise comparisons using Gabriel s procedure found that the PAE group had significantly higher scores than the other two groups (p<.001), which did not differ from one another. Psychiatric Disorders Scales Figure 3 shows mean T-scores and standard deviations of the CBRS-P Psychiatric Disorders scores. The groups were compared with respect to the T-scores of the 12 Psychiatric Disorders subscales by a MANOVA. The multivariate test was significant, λ0.14 (F [24, 80] 05.7, p<.001). Tests of between-subjects-effects showed group differences at the.001 significance level for all but the Separation Anxiety Disorder and Obsessive Compulsive Disorder subscales which differed at the.01 level. Pairwise comparisons of the subscales ADHD- Inattentive Type, Autistic Disorder, and Asperger s Disorder (p<.05) found the PAE group had higher scores than the Down syndrome group, which had higher scores than the neurotypical group. For all other CBRS-P Psychiatric Disorders subscales, the PAE group had significantly higher scores than the two other groups, which did not differ from one another; they were: ADHD - Hyperactive-Impulsive Type, Oppositional Defiant Disorder, Conduct Disorder, Major Depressive Episode, Manic Episode, Generalized Anxiety Disorder, Separation Anxiety Disorder, Social Phobia, and Obsessive Compulsive Disorder (p<.01).

13 J Dev Phys Disabil (2012) 24: Fig. 3 Mean T-scores and standard deviations of CBRS-P Psychiatric Disorders scales. The horizontal line indicates two standard deviations above the mean Facial Processing Tasks Figure 4 shows mean percent correct scores and standard deviations for the Facial Processing Tasks. The three groups differed in terms of their chronological age. Since mental age was experimentally controlled, a MANCOVA was computed with the four facial processing task scores (two emotion tasks and two non-emotion tasks) as the dependent variables, the three groups as the independent variable, and mental age as the control variable. The multivariate effects for groups (λ0.42 (F [8, 110] 07.4, p<.001) and for age (λ0.72 (F [4,55]05.4, p<.01)weresignificant.between group effects showed that the groups differed significantly from one another on all four tasks: gender (labeling) task (F [2, 62] 06.9, p<.01), identity (matching) task (F [2, 62] 024.0, p<.001), emotion (labeling) task (F [2, 62] 012.7, p<.001), and emotion (matching) task (F [2, 62] 031.3, p<.001). Post hoc pairwise comparisons with Gabriel s procedure showed that the PAE and the neurotypical group did not differ on any of the four facial processing subtests, while the Down syndrome group has significantly lower scores on all four subtests than the other two groups. Although mental age difference across groups did not reach statistical significance (as designed), group means were nonetheless quite different in absolute terms (see Table 2). Therefore, in order to be conservative and risk over-control, we computed another MANCOVA with chronological age and their PPVT standard score as the control variables. The multivariate effects for groups (λ0.62; (F [8, 108]03.7, p<.01), for age (λ0. 56; (F [4, 45]05.6, p<.001) and for PPVT standard score

14 260 J Dev Phys Disabil (2012) 24: Fig. 4 Facial Processing Tasks: Mean percent correct scores and standard deviations. Label0labeling task, mts0matching task (λ0.67; (F [4, 54] 06.8, p<.001) were significant. Between group effects showed that the groups differed significantly from one another only on the two matching-tosample tasks, i.e., the identity (matching) task (F [2, 57] 07.7, p<.01), and emotion (matching) task (F [2, 57] 014.0, p<.001). No group differences were found on the two labeling tasks. Post hoc pairwise comparisons with Gabriel s procedure showed that the PAE and the neurotypical group did not differ on the two matching tasks, while the Down syndrome group had significantly lower scores than the other two groups on the matching tasks. Predicting Facial Processing Skills In order to identify predictors that independently accounted for facial processing performance in the entire sample of participants (above and beyond cognitive abilities as represented by the PPVT-III standard score), we first computed bivariate Pearson correlations between the PPVT-III standard score, the SRS subscale T-scores, the CBRS-P subscale T-scores, and an aggregated facial processing task percent correct score that combined a person s performance across all four tasks. Besides the PPVT- III standard score (r0.47, p<.001), five CBRS-P subscale scores were significantly correlated with facial processing: Academic Difficulties (r0.40, p<.01), Language

15 J Dev Phys Disabil (2012) 24: (r0.38, p<.01), Mathematics (r0.35, p<.01), Autistic Disorder (r0.35, p<.01), and Asperger s Disorder (r0.27, p<.05). In the next step a stepwise hierarchical multiple regression analysis was computed. Those five CBRS-P scores that were correlated with facial processing in the bivariate computations were simultaneously entered as predictors in the first step of the regression analysis, followed by the PPVT-III standard score in step two. Table 3 summarizes the regression analysis results and shows that only the PPVT-III standard score predicted performance on the facial processing task. The ANOVAs were significant at p<.01 at both steps. In a next step we repeated the same calculations, however this time for the PAE group only. Significant bivariate Pearson correlations were found between the aggregated facial processing task score and the PPVT-III standard score (r0.51, p<.05), and the CBRS-P subscales Upsetting Thoughts (r0.64, p<.001), Academic Difficulties (r0.53, p<.01), ADHD/Inattentive (r0.41, p<.05), Obsessive/Compulsive (r0.60, p<.01), Autistic Disorder (r 0.66, p<.01) and Asperger s Disorder (r0.64, p<.01). Table 3 shows that not a single variable independently predicted performance on the facial processing task. The ANOVAs were significant at p<.05 at both steps. Discussion Mental, Behavior, Academic, and Social Problems Our data show that children with PAE tended to have considerable social problems reminiscent of the autism spectrum. According to SRS parent ratings the PAE group Table 3 Predicting performance on the facial processing tasks (Outcome Variable) with hierarchical multiple regression from the PPVT-III standard score, and from CBRS subscales scores with significant bivariate correlations with the outcome variable for the total sample and for the PAE group only Group predictors Step 1 Step 2 ΔR 2 β ΔR 2 β Total sample 0.22** 0.47*** Academic difficulties Language Mathematics Autistic Asperger s 1.08* 0.65 PPVT-III standard score 0.64*** PAE 0.53* 0.02 Academic difficulties Autistic Asperger s Upsetting thoughts Obsessive/Compulsive ADHD-Inattentive PPVT-III standard score 0.22

16 262 J Dev Phys Disabil (2012) 24: had significant difficulties with important aspects of social behavior. In fact, only 4.3% had SRS total scores in the normal range, while 65.2% had scores in the severe range. The PAE group means were also in the severe range on three of the five SRS subscales: Social Cognition, Social Communication, and Autistic Mannerisms. Similarly, the PAE group had elevated scores on the CBRS-P subscales Social Problems, Autistic Disorder, and Asperger Disorder, thus providing a validation of the data across both instruments. These results on the SRS and the CBRS-P are consistent with earlier reports that many children with PAE have difficulties with social behavior and, therefore, lack meaningful relationships with others (Bishop et al. 2007; Kodituwakku et al. 2001a, b; McGee et al. 2009; Thomas et al. 1998; Mukherjee et al. 2011; Whaley et al. 2001). According to the CBRS-P manual (Conners 2008), a clinical evaluation for a psychiatric disorder is strongly recommended if a child has a T- score above 60 and shows certain associated symptoms. According to those criteria more than half of the individuals in the PAE group were flagged for a clinical evaluation for an autism spectrum disorder. Based on the information reported by parents (Table 1), two of the children in the PAE group actually had a diagnosis of Autism, and one of Pervasive Developmental Disorder-Not Otherwise Specified (PDD NOS). An additional six PAE participants had a sensory processing disorder based on parent report. In addition to the high scores on the CBRS-P subscales Autistic Disorder and Asperger Disorder, children in the PAE group generally had significantly elevated scores on eight of the remaining 10 Psychiatric Disorders subscales. PAE group means were in the clinical range for ADHD-Inattentive, ADHD-Impulsive, Conduct Disorder, Oppositional Defiant Disorder, Major Depressive Episode, Manic Episode, Generalized Anxiety, and Obsessive-Compulsive Disorder. The children in the PAE group were significantly more likely to be flagged for further clinical evaluation than the other two groups. Twenty-three (92%) of the PAE group met both the symptom count and the T-score above 60 for at least one of the Psychiatric Disorders subscales. Twenty (80%) individuals of the PAE group were identified as being at risk for more than one psychiatric diagnosis. For 20 individuals, an evaluation for ADHD would have been indicated. Further evaluation for an externalizing behavior disorder (Oppositional Defiant Disorder, Conduct Disorder) was indicated for nearly half (48%) of these individuals from the PAE group and over half of them (64%) should have been evaluated for an anxiety disorder (Generalized Anxiety Disorder, Separation Anxiety Disorder, Social Phobia, or Obsessive Compulsive Disorder). In contrast, only two (8%) neurotypical individuals met Conners (2008) criteria indicating further evaluation was warranted. Both of these individuals only met the combined criteria for one DSM-IV-TR diagnosis (one ADHD and one Conduct Disorder). In fact, thirteen (52%) of the children in the PAE group had documented attention and executive functioning impairment. Parents of ten PAE participants reported their child met the diagnostic criteria for ADHD (Table 1). An additional three children had documented attention and executive functioning impairment but did not report the child receiving a diagnosis of ADHD. Only one child in the DS group had a diagnosis of ADHD based on parent report. None of the parents of children in the neurotypical group had an ADHD diagnosis. Parent report revealed two PAE participants did have anxiety disorders (PTSD, OCD). In addition, two children also had a mood disorder diagnosis based on parent report. None of the children in the DS or TD groups seemed at risk for a mood or anxiety order.

17 J Dev Phys Disabil (2012) 24: Our finding that children with PAE had significantly higher ADHD scores than the other two groups is consistent with several other studies (e.g., Howell et al. 2006; J. L. Jacobson and S. W. Jacobson 2002; O Leary 2004; Streissguth et al. 1991, 1998; Weinberg 1997). Similarly, our finding of significantly higher scores for Conduct Disorder and Oppositional Defiant Disorder in the children with a PAE diagnosis corroborates several previous reports (Howell et al. 2006; J. L. Jacobson and S. W. Jacobson 2002;O Connor et al. 2002;O Connor and Paley 2006;O Leary 2004; Ryan and Ferguson 2006; Streissguth et al. 1991, 1998; Weinberg 1997). Consistent with prior findings of elevated rates of depression associated with prenatal alcohol exposure (e.g. Fryer et al. 2007), the children with a PAE diagnosis in this study had higher scores on the Major Depressive Episode subscale. Our data also showed that many children in the PAE group had academic difficulties (i.e., language and mathematics problems) relative to typical children, yet their scores in those areas were not statistically higher than those of the children with Down syndrome. Learning disabilities were also more prevalent in the PAE participants in our study. Parent reports revealed that five children (20%) in the PAE group had a learning disability; but only one child in each of the DS and TD groups had a learning disability. Facial Processing Compared with the chronologically younger, but mental-age matched neurotypical children our PAE group showed no performance deficits on any of the four facial processing tasks. It is important to note that our results are not inconsistent with the results by Siklos (2010) and Greenbaum et al. (2009), who reported facial processing differences of their PAE samples. However, these researchers compared their PAE groups to same-age and cognitively unimpaired control group. This means that if individuals with PAE had facial processing skills deficits, they did so to the extent of their cognitive deficiency. Surprising to us was that the multiple and severe comorbid conditions of the PAE group (reflected in the elevated CBRS-P and SRS scores) did not affect the facial processing skills. Considering, for instance, that autism is known for problems with facial processing (Bar-Haim et al. 2006; Behrmann et al. 2006; Farran et al. 2011; Volkmar et al. 1989; Webb et al. 2006), the elevated autism and Asperger s disorder scores would have been a reasonable basis for the hypothesis that facial processing should be compromised in the PAE group. Not only did many in the PAE group have clinically significant autism spectrum features, they also had other comorbid externalizing and internalizing problems, some of which have also been found to be associated with facial processing deficits. Yet none of these characteristics explained the facial processing performances in these three groups. We also found that in comparing the PAE group and the neurotypical group there were no relative differences between the emotion task and the non-emotion task performances. This means that there was no evidence of an emotion-specific facial processing deficit in the PAE group, as reported by Rojahn et al. (1995) in adults with intellectual disabilities of unspecified etiology. When we attempted to identify predictors of facial processing performance in the combined three groups, the only predictor was the PPVT-III score. However, when

18 264 J Dev Phys Disabil (2012) 24: we repeated the analyses for the PAE group only, no single independent predictor emerged, which may have been an artifact of decreased statistical power due to the smaller group size. The Down syndrome group, on the other hand, showed the expected poorer performance on all four facial processing tasks when compared to the neurotypical and the PAE group, even when chronological age was controlled for statistically. This is also consistent with previous studies (e.g., Kasari et al. 2001; Kasari and Sigman 1996; Smith and Dodson 1996; Wishart et al. 2007). Also, there was no evidence of an emotion-specific facial processing deficit in the Down syndrome group. Limitations One could argue that this study would have benefited from at least one other control group, namely a typically developing group matched on chronological age with the PAE group. However, as the studies by Greenbaum et al. (2009) and Siklos (2010) showed, we anticipated that the PAE would perform less well on the facial processing tasks than their developmentally typical same age peers. We also anticipated that they would be more vulnerable in terms of social reciprocity, and that they would have more mental and behavioral problems. Ideally, we would have wanted to have both mental age matched and a chronological age matched control group, but this was not feasible for us. A comparison with a mental-age matched group seemed therefore more pertinent. Also, it cannot be ruled out that self-selected participation may have led to biased samples, threatening the external validity of our findings. Especially in the PAE group, it may be that those families experiencing more extreme academic, behavioral and mental difficulties may be more inclined to participate in a research project than the average family with a child with PAE. Another concern is that we had only one source of information for the emotional and behavioral information on our participants, in this case parents and guardians. Parental ratings tend to be biased (e.g., Hartman et al. 2007) and can affect measurement (Greenbaum et al. 1994). Future studies should consider additional ratings from multiple sources, such as teachers and clinicians. The Social Responsiveness Scale (SRS) has been established as a measure of social skills specifically in the Autism population. Although the SRS has not been established as a reliable and valid measure outside of the autistic population, the finding of elevated SRS total score and elevated scores on all 5 subscales compared to the other two groups combined with elevated scores on the Autistic Disorder and Asperger Disorder on the CBRS suggests the PAE group does exhibit behaviors consistent with Autism. This finding of elevated scores on measures of autistic behaviors is further supported by the higher rates of ASD diagnoses in the PAE participants. Future research should continue to explore these autistic behaviors in PAE groups using other measures. Facial processing tasks that use static images as stimulus material have been criticized for a potential lack of ecologically validity. While this may be true, we do not believe that the findings of this study were seriously obscured by the type of facial processing task we chose. Earlier research has shown that performance on facial processing tasks with static images very similar to the ones used in our study

19 J Dev Phys Disabil (2012) 24: was associated with social adjustment in a population with autism (Garcia-Villamisar et al. 2010) and non-specific intellectual disabilities (Rojahn et al. 2006). Summary and Future Recommendations Considering these methodological limitations, our conclusions must be viewed with some caution. However, we can summarize that many children with PAE received parent ratings that were much higher than we found in the control group of mental age matched typical children and these parent ratings were indicative of significant mental, behavioral, and social problems. Indeed, it is likely that many would meet criteria for one or more clinical diagnoses, including autism spectrum disorders, ADHD, conduct disorder, oppositional/defiant disorder, major depression, manic episodes, generalized and separation anxiety, or phobias. In addition, many had academic difficulties (language and mathematics problems) relative to typical children, yet not more than children with Down syndrome. Finally, if children with PAE have facial processing deficits, they only do so to the extent that they have cognitive/intellectual impairment. Acknowledgments The authors wish to thank all the families and the children who volunteered to participate. We also wish to acknowledge the support from the following organizations that were integral in participant recruitment: National Organization for Fetal Alcohol Syndrome (NOFAS), Double ARC NOFAS of Ohio, the Fullerton Genetics Center in Ashville, North Carolina, the International Adoption Center in Fairfax, Virginia, and the Washington, D.C. chapter of the Families for Russian and Ukrainian Adoption (FRUA), Down Syndrome Network of Montgomery County (DSNMC), the Down Syndrome Association of Greater Richmond (DSAGR), the Northern Virginia chapter of Parents of Down Syndrome, the Triangle Down Syndrome Network (TDSN) in Raleigh, NC, and the Down Syndrome Awareness Group of East Tennessee, Northern Virginia Jewish Community Center (JCCC), the George Mason University Child Development Center, and the Fairfax United Methodist Church Preschool. Thank you also to the Western Psychological Services (WPS) and George Mason University Center for Psychological Services for providing the standardized measures used in this study at discounted or no cost. References American Psychiatric Association (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: Author. Aronson, M., Hagberg, B., & Gillberg, C. (1997). Attention deficits and autistic spectrum problems in children exposed to alcohol during gestation: a follow-up study. Developmental Medicine and Child Neurology, 39, Bar-Haim, Y., Shulman, C., Lamy, D., & Reuveni, A. (2006). Attention to eyes and mouth in high functioning autism. Journal of Autism and Developmental Disorders, 36, Behrmann, M., Avidan, G., Leonard, G. L., Kimchi, R., Luna, B., Humphreys, K., & Minshew, N. (2006). Configural processing in autism and its relationship to face processing. Neuropsychologia, 4, Bishop, S., Gahagan, S., & Lord, C. (2007). Re-examining the core features of autism: a comparison of autism spectrum disorder and fetal alcohol spectrum disorder. Journal of Child Psychology and Psychiatry, 48, doi: /j x. Brosgole, L., Kurucz, J., PlaHovinsak, T. J., Sprotte, C., & Haveliwala, Y. (1983). Facial and postural affect recognition in senile elderly persons. International Journal of Neuroscience, 22, Burden, M. J., Jacobson, S. W., & Jacobson, J. L. (2005a). Relation of prenatal alcohol exposure to cognitive processing speed and efficiency in childhood. Alcoholism, Clinical and Experimental Research, 29, Burden, M. J., Jacobson, S. W., Sokol, R. J., & Jacobson, J. L. (2005b). Effects of prenatal alcohol exposure on attention and working memory at 7.5 years of age. Alcoholism, Clinical and Experimental Research, 29,