AMERICAN JOURNAL ON INTELLECTUAL AND DEVELOPMENTAL DISABILITIES 2015, Vol. 120, No. 4, 273–288

EAAIDD DOI: 10.1352/1944-7558-120.4.273

The Association of Intelligence, Visual-Motor Functioning, and Personality Characteristics With Adaptive Behavior in Individuals With Williams Syndrome Trista J. Fu, Alan J. Lincoln, Ursula Bellugi, and Yvonne M. Searcy

Abstract Williams syndrome (WS) is associated with deficits in adaptive behavior and an uneven adaptive profile. This study investigated the association of intelligence, visual-motor functioning, and personality characteristics with the adaptive behavior in individuals with WS. One hundred individuals with WS and 25 individuals with developmental disabilities of other etiologies were included in this study. This study found that IQ and visual-motor functioning significantly predicted adaptive behavior in individuals of WS. Visual-motor functioning especially predicted the most amount of unique variance in overall adaptive behavior and contributed to the variance above and beyond that of IQ. Present study highlights the need for interventions that address visual-motor and motor functioning in individuals with WS. Key Words: Williams syndrome; adaptive behavior; visual-motor functioning; intelligence Williams syndrome (WS) is a neurodevelopmental disorder characterized by a distinctive cognitive and personality profile (Bellugi, Ja¨rvinen-Pasley, Doyle, Reilly, & Korenberg, 2007; Mervis & John, 2010). The cognitive phenotype of WS is characterized by relative strengths in auditory rote memory and language, and relative weakness in visuospatial perception, construction, and integration. Individuals with WS often have extreme difficulty with tasks involving visual-spatial construction such as drawing and block design (pattern construction; Hudson & Farran, 2010; Mervis, 1999; Nagai, Inui, & Iwata, 2011). WS is also associated with motor planning deficits, which might play a role in their poor visual-motor performance (Elliott, Welsh, Lyons, Hansen, & Wu, 2006). In addition, individuals with WS have an unusual personality profile associated with high sociability, overfriendliness, empathy, and excessive anxiety (Doyle, Bellugi, Korenberg, & Graham, 2004; Dykens, 2003; Ja¨rvinen-Pasley et al., 2010; Tager-Flusberg & Sullivan, 2000). The syndrome results in mild to moderate intellectual or learning T. Fu et al.

disability (Bellugi, Lichtenberger, Jones, Lai, & St. George, 2000). Adaptive behavior refers to the attainment of developmentally appropriate milestones in skills that promote independence and help individuals cope with the demands of their everyday environment (Liss et al., 2001; Szatmari, Bryson, Boyle, Streiner, & Duku, 2003). Research has demonstrated that WS is associated with deficits in adaptive behavior (Di Nuovo, Buono, 2011; Howlin, Davies, & Udwin, 1998; Mervis & KleinTasman, 2000). Gosch and Pankau (1994) found that children with WS obtained significantly lower scores in adaptive behavior compared to their IQ and chronological age (CA) matched counterparts with nonspecific intellectual disability (ID). Another study (Davies, Howlin, & Udwin, 1997) also found that, despite having a similar degree of general cognitive impairment, relatively few individuals with WS were able to attain a reasonable level of independence, or cope with the demands of employment when compared to groups of adults with other intellectually disabling 273

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genetic disorders (i.e., Down syndrome and PraderWilli syndrome). Furthermore, it has been reported that individuals with WS have uneven profiles in different domains of adaptive functioning, as measured by the Vineland Adaptive Behavior Scales (VABS; Sparrow, Balla, & Cicchetti, 1984). Overall, the adaptive profile of the children with WS is consistent with their cognitive profile in which communication and social interaction are the areas of strength whereas daily living and motor domains are the areas of weakness (Greer, Brown, Pai, Choudry, & Klein, 1997; Mervis, 1999). However, for adults with WS, although they still exhibit a relative strength in Socialization, their performance in the Communication domain is relatively lower than their performance in the Daily Living domain on the VABS (Howlin et al., 1998). Additionally, their adaptive motor functioning was unknown since the motor domain on the VABS is only applicable for children under 6 years old. Mervis and Klein-Tasman (2000) argue that the motor deficits of children with WS, combined with the impairments in visual-spatial integration, contribute to their difficulties with performing daily living skills, such as dressing, cleaning, preparing food, and telling time. In addition, some investigators (Davies et al., 1997; Mervis & Klein-Tasman, 2000) have stated that the behavioral and personality characteristics associated with WS such as, anxiety, social disinhibition, and low tolerance for frustration, appear to limit affected individuals’ level of self-care ability and community independence. The primary purpose of this study was therefore to systematically investigate the effects of these variables on adaptive behavior in individuals with WS with an emphasis on the role of visualmotor deficits. By identifying predictors of adaptive behavior in individuals with WS, this study may help to design appropriate interventions for individuals with WS.

Method Participants Participants included 100 individuals with WS (43 males, 57 females; mean age 28.23 years, SD 5 10.63, range 12–53 years) and 25 individuals with developmental disabilities (DD) with other etiologies (the mean age of the DD group was 21.24 years old; 10 males, 15 females; mean age 21.24 years, SD 5 10.16; age range 12–46). All the WS 274

participants and 13 individuals with DD were identified from an existing database at the Laboratory for Cognitive Neuroscience (LCN) of the Salk Institute. The remaining 12 DD participants were recruited from the community because a power analysis indicated that more participants in the DD group were needed in order to detect an effect. Only individuals who had concurrent IQ and Scales of Independent Behavior-Revised (SIB-R; Bruininks, Woodcock, Weatherman, & Hill, 1996) scores in the database were included for evaluation in this study. The DD group consisted of 3 with Down syndrome, 2 with Seizure disorder, 1 with Rare Chromosome disorder, 1 with Tourette’s disorder 1 with Cerebral palsy, 4 with Pervasive developmental disorder-not otherwise specified, and 13 with developmental disability of unknown etiology.

Procedures Adaptive behavior was measured by the SIB-R. The SIB-R is a questionnaire designed to measure various areas of adaptive and maladaptive behaviors from infancy through adulthood. It was normed on 2,000 individuals and has adequate reliability and validity (Bruininks et al., 1996). It can be administered in a structured interview or by a checklist procedure. In the current study, participants’ parents or caregivers completed a SIB-R checklist to provide data on participants’ functional independence and adaptive behavior in home, social, school, work, and community settings. The SIB-R assesses four areas of adaptive behavior and provides standard scores (cluster scores): Social Interaction and Communication Skills, Personal Living Skills, Community Living Skills, and Motor Skills. Validity studies of the SIB-R that focused on correlations with other tests of adaptive behavior have shown correlation coefficients ranging from .66 to .81, and the reliability of the SIB-R was found to range from .95 to .98 (Bruininks et al., 1996). IQ was measured by the Wechsler Intelligence Scale for Children, Revised Edition (WISCR; Wechsler, 1974), and Third Edition (WISC-III; Wechsler, 1991), and the Wechsler Adult Intelligence Scale, Revised Edition (WAIS-R; Wechsler, 1981) and Third Edition (WAIS-III; Wechsler, 1997). Because individuals with WS often exhibit deficits in visual-motor functioning and visual-spatial perception, Full IQ might not reflect their true intellectual ability (Bellugi et al., Adaptive Behavior in Williams Syndrome

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2000). Therefore, in the current study, in order to minimize the impact of WS participants’ poor visual-motor skills, abbreviated IQ scores focused on verbal ability were calculated according to the test manual instructions (Sattler, 2002) and used instead of the original Full IQ scores. Abbreviated scores were derived from a three-subtest shortform combination, which consisted of Information, Similarities, and Vocabulary. This combination is the only proposed WISC/WAIS three-subtest short form that does not include the subscales involving motor components such as, Block Design, Digit Symbol-Coding, and Digit Span (Sattler, 2002). It also has a good reliability (r 5 .937) and validity (r 5 .829; Sattler, 2002). The Sattler Supplement provides the rationale behind short forms, and tables (Table A-25) to turn sums of scaled scores into estimates of a full scale IQ. An explanation of the procedure used to obtain the estimated Deviation Quotients can be found in Exhibit 8-4, on pages 256257 in the Sattler Supplement (Sattler, 2002). Visual-motor functioning was assessed by the Berry-Buktenica Developmental Test of VisualMotor Integration, 4th Edition (VMI; Beery, 1997). The VMI is a visual-spatial integration task with a motor component in which the subject is asked to copy increasingly complex geometric designs. Visual–motor integration is the degree to which visual perception and finger-hand movements are well coordinated (Beery, 1997). Inadequate development of either of these abilities may be responsible for a poor performance on the VMI. Additionally, poor performance on the VMI can also be due to inadequate integration of visual and motor systems even though they may individually be functioning adequately (Beery, 1997). Validity studies of VMI that focused on correlations with other tests of visual motor integration have shown correlation coefficients ranging from .29 with the Comprehensive Tests of Basic Skills to .93 in some studies with the Bender Gestalt test (Beery, 1997). The overall average reliability of the VMI was found to be 0.92 (Beery, 1997). The VMI has an 18-item version for ages 3 to 7 and a 27-item version for use with preschool children through age 18. The individual obtains a score of one for each item that meets the criteria for scoring as described in the manual for the VMI. If the individual’s reproduction of the figure does not meet the criteria, he or she is given a score of zero for that item on the test. The raw score is obtained by adding the scores for individual items until the ceiling is established. T. Fu et al.

EAAIDD DOI: 10.1352/1944-7558-120.4.273

The raw score obtained by the individual is then compared to the age appropriate standard scores. Because individuals with WS often score below the standard score floor on this measure, raw scores were utilized in the current study. Although VMI only has norms up to age 18, adult individuals with WS in this study were also administered with this measure due to their deficits in visual spatial area. Specific personality characteristics examined in this study included high sociability and heightened anxiety. High sociability was measured by the Social Closeness subscale on the short form of Multidimensional Personality Questionnaire (MPQ; Tellegen, 1985) and the Social Approach score on the Salk Institute Sociability Questionnaire (SISQ; Jones et al., 2000). Heightened anxiety was measured by the Stress Reaction subscale on the MPQ and the Anxious/Depressed score on the Child Behavior Checklist (CBCL; Achenbach & Rescorla, 2001) The MPQ (Tellegen, 1985) is a personality inventory that has been used for investigating the genetic, neurobiological, and psychological substrates of personality (Patrick, Curtin, & Tellegen, 2002). It was originally designed as a self-report measure for adults and was later modified as a parent-report measure (Harkness, Tellegen, & Waller, 1995). The MPQ assesses three higher order dimensions of personality: Positive Emotionality (PEM), Negative Emotionality (NEM), and Constraint (CON). Positive Emotionality and Negative Emotionality are linked with mood and involve tendencies towards positive and negative emotions. Specifically, the Positive Emotionality personality traits include the following primary traits: Wellbeing, Social Potency, Achievement, and Social Closeness. The Negative Emotionality traits include: Stress Reaction (general anxiousness), Alienation, and Aggression. The personality dimension of Constrain pertains to the characteristics of impulsivity and behavioral regulation. Its primary traits include Control versus Impulsivity, Harm Avoidance, and Traditionalism (conservatism). Although the reliability and validity of this shortened parent version is unknown, the MPQ original version is a psychometrically sound, wellvalidated measure (Patrick, Cutin, & Tellegen, 2002). It has demonstrated alpha coefficients ranging from .81 to .91 for the primary trait scales, and 30-day test-retest reliability ranging from .82 to .92. Validity was demonstrated on the basis of convergent and discriminant validity with 275

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various constructs measured by other instruments (Patrick et al., 2002). The current study utilized the parent-report version of the MPQ. Parents or caregivers rated participants on a 4-point scale that asked them to describe the participants on a particular trait. Klein-Tasman and Mervis (2003) contrasted the personality profiles of children with WS and children with developmental disabilities of other etiology by using the MPQ. They found children with WS were rated significantly higher than the children in the mixed etiology group on Social Closeness (affiliation) and Stress Reaction (general anxiousness) subscales. High scorers on the Social Closeness Scale describe themselves as: Sociable, liking to be with people; taking pleasure in and valuing close personal ties; warm and affectionate; turning to others for comfort and help. High scorers on the Stress Reaction Scale describe themselves as: Tense and nervous; sensitive and vulnerable; prone to worry and feeling anxious; irritable and easily upset; having changing moods; feeling miserable without reason; being troubled by feelings of guilt and unworthiness. The SISQ is an exploratory experimental tool developed at the Salk Institute’s Laboratory for Cognitive Neuroscience to assess behaviors associated with sociability. Parents or caregivers are asked to rate their child’s specific social abilities on a 7-point Likert scale, where 1 5 much less than same-aged children and 7 5 much more than sameaged children. Scores reflect the average of the questions in each category. Questionnaire items are designed to provide a global measure of sociability and to measure two aspects of sociability, Social Approach Behavior and Social Emotional Behavior. Items assessing Social Approach Behavior are grouped for analysis into two types: (a) those items that assess the child’s tendency to approach family members or others encountered frequently (an Approach Familiars score), and (b) those items that assess the child’s tendency to approach people unknown to them (yielding an Approach Strangers score). Social Emotional items ask parents to rate their child’s tendency to empathize with or comment on the emotional states of others, the accuracy of their emotional evaluations of others, their eagerness to please other people, and their abilities to remember names and faces of those they have met for the first time. For each participant, the Global Sociability score is the sum of 12 items; the Social Emotional score is the sum of 4 items; Approach 276

Familiars, 3 items; and Approach Strangers, 5 items. Although the psychometric property of the SISQ is not yet known, Salk studies (ZitzerComfort, Doyle, Masataka, Korenberg, & Bellugi, 2007) have found that the SISQ overall scores show high correlations with the MPQ on social dimensions such as Social Potency and Social Closeness for WS participants. This provides preliminary evidence of its convergent validity. The CBCL is a parent-report questionnaire for children ages 6 to 18. It is a 112-item behavior checklist. The behavior inventory is scored on the basis of behavior in the past 6 months. It measures behavioral and emotional problems in childhood. The problem behavior items are rated on 3-point scales (2 5 very true or often true of the child; 1 5 somewhat or sometimes true; 0 5 not true of the child.) Scores above 65 are considered in the clinical range. There are two broad band, factoranalytically derived dimensions of child problem behavior, Internalizing and Externalizing. Reliability for this measure has been reported as ranging from .95 to 1.00 for test-retest, .93 to .96 for interrater agreement, and .78 to .97 for internal consistency (Achenbach & Rescorla, 2001). Even though the CBCL was designed for children 6 to 18 years of age, in this study, its use was extended to adult participants. Other studies have also applied the CBCL to adult individuals with DD (Dykens, Hodapp, Walsh, & Nash, 1992; Reiss & Benson, 1985).

Results Descriptive Statistics The means and standard deviations for the WS and DD groups on the age, estimated IQ (short form), and VMI are presented in Table 1. An ANOVA indicated significant differences in age between groups, F(1, 123) 5 8.804, p 5 .004. To control for the effect of age, ANCOVA and MANCOVA was used to replace ANOVA and MANOVA in examining hypotheses. There were no significant differences in estimated IQ between the WS and DD groups. Visual-motor functioning was examined using the VMI. A one-way ANOVA showed a significant difference in the VMI standard scores between the two groups. The WS group performed significantly worse compared to the DD group, F(1, 122) 5 7.37, p 5 .008. Personality characteristics were measured using the CBCL, the MPQ, and the SISQ. However, Adaptive Behavior in Williams Syndrome

EAAIDD DOI: 10.1352/1944-7558-120.4.273

AMERICAN JOURNAL ON INTELLECTUAL AND DEVELOPMENTAL DISABILITIES 2015, Vol. 120, No. 4, 273–288

Table 1 Descriptive Statistics of Age, IQ, and VMI Scores for the WS and DD Groups Age/IQ/VMI Age WS (n 5 100) DD (n 5 25) Estimated IQ WS (n 5 100) DD (n 5 21) VMI WS (n 5 100) DD (n 5 24)

M

SD

28.23 21.24

10.63 10.16

76.10 73.55

10.14 7.62

49.56 54.33

7.17 9.81

F

p

8.804

.004

1.183

.279

7.370

.008

Note. WS 5 Williams syndrome; VMI 5 Berry-Buktenica Developmental Test of Visual-Motor Integration, 4th ed.; DD 5 developmental disability. Estimated IQ scores were calculated based on a three-subtest, short-form combination, which consisted of Information, Similarities, and Vocabulary subtest in the Wechsler Intelligence Scale for Children, Rev. ed., Wechsler Intelligence Scale for Children, Third ed., Wechsler Adult Intelligence Scale, Rev. ed., and Wechsler Adult Intelligence Scale, Third ed.; VMI standard scores were used in the analysis.

some participants did not complete all the measures, so there are different sample sizes for each measurement. One-way ANOVA indicated significant differences between groups in SISQ Social Approach scores, F(1,120) 5 67.37, p 5 .01, Social Emotional scores, F(1, 120) 5 36.89, p 5 .01, and Global Sociability scores, F(1, 120) 5 61.16, p 5 .01. Significant differences between groups were also found in MPQ Social Closeness scores, F(1, 96) 5 30.18, p 5 .01. However, no significant group differences were detected in the CBCL scores. In relation to the standardization

sample, none of the mean T-scores (Total Problem, Internalizing, Externalizing Behaviors) in the WS group was elevated. The means and standard deviations are presented in Table 2.

Differences in Adaptive Profile Between WS and DD Groups The first hypothesis predicted significant differences in adaptive behavior between WS and DD groups while the effects of age were partialled out. A one-way ANCOVA was conducted to test group differences in SIB-R Broad Independence scores

Table 2 Means and Standard Deviations of SISQ, MPQ, and CBCL for the WS and DD Groups Measures SISQ social approach WS (n 5 97) DD (n 5 25) MPQ social closeness WS (n 5 76) DD (n 5 22) MPQ stress reduction WS (n 5 76) DD (n 5 22) CBCL anxious/depressed WS (n 5 91) DD (n 5 24)

M

SD

5.72 3.87

.91 1.31

3.64 2.95

.46 .67

3.05 2.91

.77 .73

58.75 56.63

7.62 7.59

F

p

67.373

.000

30.177

.000

.605

.438

1.475

.227

Note. SISQ 5 Salk Institute Sociability Questionnaire; MPQ 5 Multidimensional Personality Questionnaire; CBCL 5 Child Behavior Checklist; WS 5 Williams syndrome; DD 5 developmental disability.

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while controlling for age. The ANCOVA was significant, F(1,122) 5 6.988, p5.009, partial g2 5 .054. The WS group had a significantly lower adjusted mean score (M 5 48.47) compared to the adjusted mean of the DD group (M 5 60.84), which suggests that individuals with WS have an adaptive functioning deficit compared to the DD group. Furthermore, a one-way MANCOVA was conducted. The nominal independent variable was group status, and the dependent variables were four SIB-R cluster scores. The main effect of group status, Wilk’s L 5 .766, F(4, 117) 5 8.943, p , .001, multivariate g2 5 .234 indicated a significant effect on the combined dependent variables. The covariate significantly influenced the combined dependent variables, Wilk’s L 5 .886, F(4, 117) 5 3.752, p 5 .007, multivariate g2 5 .114. Follow-up univariate ANOVA results indicated that the variables of SIB-R Personal Living Skills scores, F(1, 120) 5 7.03, p 5 .009, partial g2 5 .055, and Motor Skills scores, F(1, 120) 5 14.084, p , .001, partial g2 5 .105 were significantly affected by group status. In addition, the SIB-R Social Interaction and Communication Skills scores was significantly affected by the covariate of age, F(1, 120) 5 7.274, p 5 .008, partial g2 5 .057. Table 3 presents the adjusted and unadjusted group means for SIB-R cluster scores. Comparison of adjusted means of the Personal Living Skills scores and the Motor Skills scores indicated that participants in the WS group have lower scores in these two adaptive behavior domains. However, no significant differences were found between the WS and DD groups in their SIB-R Social Interaction and Communication Skills Cluster scores, F(1, 120) 5 .472, p 5 .494, partial g2 5 .004 and Community Living Skills Cluster scores, F(1, 120) 5 1.457, p 5 .230, partial g2 5 .012.

Predictors of Adaptive Behavior in the WS Group Hypothesis two predicted that when controlling for age, intelligence would predict the most unique variance in adaptive behavior in individuals with WS. Visual-motor functioning and personality characteristics (including high sociability and heightened anxiety) are expected to account for additional variance above and beyond that caused by intelligence. This was analyzed using hierarchical multiple regression. Before running hierarchical multiple regression analysis, factor analysis was conducted to create a personality factor score that could be used in regression. This personality variable was based on four subscales from three personality and behavioral measures: the Social Closeness and the Stress Reduction subscales of the MPQ, the Social Approach score of the SISQ, and the Anxious/ Depressed score from the CBCL. Principle components analysis was conducted utilizing a varimax rotation. The analysis produced a twocomponent solution, which was evaluated with the following criteria: eigenvalue, variance, scree plot, and residuals. Criteria indicated a two-component solution was appropriate. After rotation, the first component accounted for 37.59% of the total variance in the original variables, whereas the second component accounted for 33.42%. (Table 4 presents the loadings for each component.) The first component consisted of two of the four variables: the Social Approach Score from the SISQ and the Social Closeness Score from the MPQ. These variables had positive loadings and addressed High Sociability in WS. The second component included the remaining two variables of Anxious/ Depressed scores on the CBCL and Stress Reduction scores on the MPQ. Both variables had

Table 3 Adjusted and Unadjusted Group Means for SIB-R Cluster Scores for WS and DD Groups WS (n 5 98) SIB-R cluster scores Social interaction and communication skills Community living skills Personal living skills Motor skills

DD (n 5 25)

Adjusted M

Unadjusted M

Adjusted M

Unadjusted M

67.52 50.38 58.67 52.74

66.94 50.26 58.37 52.69

64.74 55.97 69.37 71.31

67.00 56.48 70.56 71.48

Note. SIB-R 5 Scales of Independent Behavior-Revised; WS 5 Williams syndrome; DD 5 developmental disability. Using age as covariate.

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Table 4 Component Loadings Component

Loading

Component 1: High sociability Social approach scores on SISQ Social closeness score on MPQ Component 2: Heightened anxiety Anxious/depressed scores on CBCL Stress reduction scores on MPQ

.842 .841 .844 .770

Note. SISQ 5 Salk Institute Sociability Questionnaire; CBCL 5 Child Behavior Checklist; MPQ 5 Multidimensional Personality Questionnaire.

positive loadings. This component was labeled Heightened Anxiety. These two component scores were generated and used in the regression. Hierarchical multiple regression was then conducted with all WS participants who had a complete data set (n 5 69). The assumptions of normality, linearity, and homoscedasticity were met. Five hierarchical multiple regressions were employed to test the relative influence of IQ, visual-motor functioning, and personality characteristics on SIB-R’s Broad Independence Score and four Cluster Scores. For each regression, participant’s age was entered in the first block,

estimated IQ was entered in the second block, visual-motor functioning was entered in the third block. Finally, personality characteristics, including two component scores generated through factor analysis, was entered in the last block. For SIB-R Broad Independence Score, the regression result indicated when age was controlled for, IQ accounted for a significant 9.4% of the variance. Taking IQ into account, the VMI uniquely and significantly accounted for an additional 15.9% of the variance. Finally, taking IQ and VMI into account, personality characteristics accounted for an additional nonsignificant amount, 6.3% of the variance. The final model of four predictors (age, IQ, VMI, and personality factor scores) significantly predicted SIB-R Broad Independence score in WS participants, and accounted for 31.9% of the variance (26.5% adjusted for number of variables and degrees of freedom; see Tables 5 & 6). For SIB-R Social Interaction and Communication Cluster Score, the regression result indicated that when age was controlled for, IQ accounted for a significant 15.6% of the variance. Taking IQ into account, VMI explained an additional nonsignificant 2.8% of the variance. Finally, taking the IQ and VMI into account, personality characteristics explained

Table 5 Model Summary Predicting SIB-R Broad Independence Score in WS Group R

R2

R2adj

DR2

Fchg

p

df1

df2

.057 .311 .506 .565

.003 .097 .256 .319

2.012 .070 .222 .265

.003 .094 .159 .063

.217 6.845 13.897 2.900

.643 .011 ,.001 .062

1 1 1 2

67 66 65 63

Model 1. 2. 3. 4.

Age Estimated IQ VMI Personality factor scores

Note. N 5 69. SIB-R 5 Scales of Independent Behavior-Revised; WS 5 Williams syndrome; VMI 5 Berry-Buktenica Developmental Test of Visual-Motor Integration, 4th ed.

Table 6 Coefficients for Model Variables Predicting SIB-R Broad Independence Score in WS Variables Age Estimated IQ VMI Personality factor score 1 Personality factor score 2

B

b

T

Bivariate r

Partial r

2.488 .524 2.948 2.368 25.067

2.278 .270 .473 .122 2.262

22.450* 2.095* 3.967*** 1.155 22.185*

2.057 .287 .453 .090 .000

2.295 .255 .447 .144 2.265

Note. SIB-R 5 Scales of Independent Behavior-Revised; WS 5 Williams syndrome; VMI 5 Berry-Buktenica Developmental Test of Visual-Motor Integration, 4th ed. *p , .05. **p , .01. ***p , .001.

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an additional nonsignificant 6.1% of variance. The final model significantly predicted SIB-R Social Interaction and Communication Cluster score. This model accounted for 31% of variance (25.6% adjusted for number of variables and degrees of freedom; see Tables 7 & 8). For SIB-R Personal Living Skills Cluster Score, the regression result indicated that when age was controlled for, IQ accounted for a nonsignificant 5% of the variance. Taking IQ into account, VMI accounted for an additional significant 13.7% of the variance. Finally, taking the IQ and VMI into account, personality characteristics accounted for an additional nonsignificant 5.9% of variance. The final model

significantly predicted SIB-R Personal Living Skills Cluster scores. This model accounted for 25.5% of variance (19.5% adjusted for number of variables and degrees of freedom; see Tables 9 & 10). For SIB-R Community Living Skills Score, IQ accounted for a significant 13.4% of the variance. Taking IQ into account, the VMI uniquely and significantly accounted for an additional 6.6% of the variance, and once entered, no other variable contributed any uniquely significant variance. The final model accounted for 25.6% of the variance; see Tables 11 and 12. Finally, for SIB-R Motor Skills Cluster Score, VMI was the most significant predictor and accounted for a significant 22.6% of the variance. Once this variable was

Table 7 Model Summary Predicting SIB-R Social Interaction and Communication Cluster Scores in WS Group Model 1. 2. 3. 4.

Age Estimated IQ VMI Personality factor scores

R

R2

R2adj

DR2

Fchg

p

df1

df2

.255 .471 .499 .557

.065 .221 .249 .310

.051 .198 .214 .256

.065 .156 .028 .061

4.670 13.246 2.385 2.800

.034 .001 .127 .068

1 1 1 2

67 66 65 63

Note. N 5 69. SIB-R 5 Scales of Independent Behavior-Revised; WS 5 Williams syndrome; VMI 5 Berry-Buktenica Developmental Test of Visual-Motor Integration, 4th ed.

Table 8 Coefficients for Model Variables Predicting SIB-R Social Interaction and Communication Cluster Scores in WS Variables Age Estimated IQ VMI Personality factor score 1 Personality factor score 2

B

b

T

Bivariate r

Partial r

2.703 .823 1.146 3.240 23.834

2.431 .456 .198 .180 2.213

23.770*** 3.514*** 1.647 1.688 21.766

2.255 .331 .228 .126 .086

2.429 .405 .203 .208 2.217

Note. SIB-R 5 Scales of Independent Behavior-Revised; WS 5 Williams syndrome; VMI 5 Berry-Buktenica Developmental Test of Visual-Motor Integration, 4th ed. *p , .05. **p , .01. ***p , .001.

Table 9 Model Summary Predicting SIB-R Personal Living Skills Cluster Score in WS Group Model 1. 2. 3. 4.

Age Estimated IQ VMI Personality factor scores

R

R2

R2adj

DR2

Fchg

p

df1

df2

.093 .242 .443 .505

.009 .059 .196 .255

2.006 .030 .159 .195

.009 .050 .138 .058

.589 3.498 11.126 2.465

.445 .066 .001 .093

1 1 1 2

67 66 65 63

Note. N 5 69. SIB-R 5 Scales of Independent Behavior-Revised; WS 5 Williams syndrome; VMI 5 Berry-Buktenica Developmental Test of Visual-Motor Integration, 4th ed.

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Table 10 Coefficients for Model Variables Predicting SIB-R Personal Living Skills Cluster Score in WS Variables Age Estimated IQ VMI Personality factor score 1 Personality factor score 2

B

b

T

Bivariate r

Partial r

2.450 .328 2.43 1.47 24.516

2.293 .193 .445 .087 2.267

22.465* 1.430 3.569*** .783 22.215*

2.093 .198 .387 .068 2.041

2.297 .177 .410 .098 2.259

Note. SIB-R 5 Scales of Independent Behavior-Revised; WS 5 Williams syndrome; VMI 5 Berry-Buktenica Developmental Test of Visual-Motor Integration, 4th ed. *p , .05. **p , .01. ***p , .001.

entered, no others contributed significantly unique variance. The final model accounted for 26.3% of variance; see Tables 13 and 14.

Adaptive Behavior and Correlates In the current study, the correlations between estimated IQ and standard scores on each of the three SIB-R domains were all positive and significant, except for the motor domain. More specifically, the correlation between IQ and the Community Living Skills was the largest, followed by the correlations between IQ and Social Interaction and Communication Skills as well as between IQ and the Personal Living Skills domain. In the DD

group, estimated IQ was only significantly correlated with the Community Living Skills (r 5 .44, p , .05) and not correlated with any other SIB- R cluster scores; see Table 15. VMI raw scores were significantly and positively correlated with SIB-R Broad Independence score as well as all Cluster Scores in the WS group. However, there was not a significant correlation between the SIB-R Scores and VMI in the DD group; see Table 16. An exploratory analysis was conducted to examine the relationship between the SIB-R and personality measures. In both WS and DD group, SIB-R scores were not significantly correlated with SISQ Social Approach score, MPQ Social

Table 11 Model Summary Predicting SIB-R Community Living Skills Cluster Score in WS Group Model 5. 6. 7. 8.

Age Estimated IQ VMI Personality factor scores

R

R2

R2adj

DR2

Fchg

p

df1

df2

.037 .367 .448 .506

.001 .135 .201 .256

2.014 .108 .163 .196

.001 .133 .066 .055

.090 10.017 5.282 2.301

.765 .002 .025 .109

1 1 1 2

66 65 64 62

Note. N 5 69. SIB-R 5 Scales of Independent Behavior-Revised; WS 5 Williams syndrome; VMI 5 Berry-Buktenica Developmental Test of Visual-Motor Integration, 4th ed.

Table 12 Coefficients for Model Variables Predicting SIB-R Community Living Skills Cluster Score in WS Variables Age Estimated IQ VMI Personality factor score 1 Personality factor score 2

B

b

T

Bivariate r

Partial r

2.379 .715 1.848 2.482 24.29

2.227 .386 .307 .135 2.234

21.904 2.856** 2.460* 1.211 21.848

2.037 .350 .356 .081 .033

2.235 .341 .298 .152 2.229

Note. SIB-R 5 Scales of Independent Behavior-Revised; WS 5 Williams syndrome; VMI 5 Berry-Buktenica Developmental Test of Visual-Motor Integration, 4th ed. *p , .05. **p , .01. ***p , .001.

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Table 13 Model Summary Predicting SIB-R Motor Skills Cluster Score in WS Group R

R2

R2adj

DR2

Fchg

p

df1

df2

.021 .052 .479 .513

.000 .003 .229 .263

2.015 2.028 .193 .204

.000 .002 .227 .034

.030 .147 18.811 1.424

.864 .703 .000 .248

1 1 1 2

66 65 64 62

Model 9. Age 10. Estimated IQ 11. VMI 12. Personality factor scores

Note. N 5 69. SIB-R 5 Scales of Independent Behavior-Revised; WS 5 Williams syndrome; VMI 5 Berry-Buktenica Developmental Test of Visual-Motor Integration, 4th ed.

Closeness scale and Stress Reduction scale, and CBCL Anxiety/Depression score.

Discussion This study presents an initial attempt at using a theoretically driven approach to examine the additive contribution of multiple factors (i.e., IQ, visual-motor functioning, and personality characteristics) thought to impact adaptive behavior outcomes in individuals with WS. By sampling a group of individuals with a wide age range, a greater level of understanding of the complex factors impacting adaptive outcomes of adolescents and adults with WS was sought.

Findings Related to Descriptive Statistics In the current study, WS participants were found to be severely impaired on the VMI, and performed significantly worse than participants in the DD group. This study also found a unique personality profile in WS participants with high sociability, overfriendliness, and empathy, consistent with previous studies (Doyle et al., 2004; Dykens, 2003; Ja¨rvinen-Pasley et al., 2010; TagerFlusberg & Sullivan, 2000). For example, in the present study it was found that individuals in the

WS group had significantly higher scores in Social Approach scores on SISQ and the Social Closeness Scale on MPQ, compared to individuals in the DD group. However, current study contradicts previous reports of heightened anxiety as well as other psychopathology associated with this syndrome (Klein-Tasman & Mervis, 2003; Stinton, Elison, & Howlin, 2010). For example, there was no significant difference in the Stress Reduction Scale on the MPQ between the WS and DD group. This is in contrast to the results of a previous study focused on children with WS done by Tager-Flusberg and Sullivan (2000). Additionally, on CBCL, none of the mean of Tscores (Total Problem, Internalizing Behaviors, and Externalizing Behaviors) in the WS group was elevated in relation to the standardization sample. This inconsistency might be due to the current study using adolescent and adult samples, whereas the previous studies used child samples. As individuals with WS age, they might experience less anxiety or have learned how to better cope with anxiety The second reason might be that CBCL simply was not able to correctly capture the picture of psychopathology experienced by adults with WS because it was originally designed to test children and adolescents.

Table 14 Coefficients for Model Variables Predicting SIB-R Motor Skills Cluster Score in WS Variables Age Estimated IQ VMI Personality factor score 1 Personality factor score 2

B

b

T

Bivariate r

Partial r

2.261 2.132 3.653 1.905 23.879

2.141 2.065 .554 .093 2.191

21.188 2.480 4.428*** .839 21.516

.021 .051 .443 .113 2.070

2.149 2.061 .490 .106 2.189

Note. SIB-R 5 Scales of Independent Behavior-Revised; WS 5 Williams syndrome; VMI 5 Berry-Buktenica Developmental Test of Visual-Motor Integration, 4th ed. *p , .05. **p , .01. ***p , .001.

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Table 15 Correlations Between Adaptive Behavior and Estimated IQ for WS and DD Groups WS Estimated IQ SIB-R Clusters SIB-R broad independence SIB-R motor skills SIB-R social interaction/ communication SIB-R personal living SIB-R community living

DD Estimated IQ

Pearson r

Significance

Pearson r

Significance

.297** (n 5 100) .030 (n 5 99)

.003 .769

.274 (n 5 21) .039 (n 5 21)

.229 .866

.370** (n 5 100) .205* (n 5 100) .392** (n 5 99)

.000 .041 .000

.142 (n 5 21) .337 (n 5 21) .443* (n 5 21)

.539 .135 .044

Note. SIB-R 5 Scales of Independent Behavior-Revised; WS 5 Williams syndrome; DD 5 developmental disability. *Correlation is significant at the 0.05 level (2-tailed). **Correlation is significant at the 0.01 level (2-tailed).

Findings Related to the Adaptive Behavior Profile of Williams Syndrome The current study indicated that the WS and DD groups differed significantly in their SIB-R scores. This is consistent with the findings of other studies demonstrating that WS is associated with deficits in adaptive behavior when compared to IQ-matched and chronological age (CA) matched counterparts with nonspecific ID (Gosch & Pankau, 1994; Howlin, Davies, & Udwin, 1998; Mervis & Klein-Tasman, 2000). More specifically, the results of the current study found that compared to the DD group, individuals with WS have significantly lower scores on the Personal Living Skills Cluster Score and Motor Skills Cluster Score. This suggested that the poor visual-motor functioning, poor motor skills (Gosch & Pankau, 1994; Mervis & Klein-Tasman, 2000), and the motor planning deficits (Elliott, Welsh, Lyons, Hansen, & Wu, 2006) might have

a significant impact on the adaptive behavior of individuals with WS, especially in the domains of adaptive behavior that requires more motor components and fewer social components. It is worth noting that the findings of the current study suggest that this deficit in the motor area of adaptive behavior exists in all age groups in WS. Previous studies all used the VABS to measure adaptive behaviors, and the Motor skills on the VABS are only applicable for children less than 6 years. The results of the current study also suggest that individuals with WS do not have significantly higher scores in their Social Interaction and Communication Skills Cluster Scores and the Community Living Skills Cluster Scores on SIB-R than do individuals with the DD group. Previous studies all used the VABS to assess adaptive behavior and this measure assesses communication and socialization domains separately. Individuals with WS appeared to have better performance in the socialization area but not

Table 16 Correlations Between Adaptive Behavior and VMI Raw Score for WS and DD Groups WS VMI

SIB-R broad independence SIB-R motor skills SIB-R social interaction/ communication SIB-R personal living SIB-R community living

DD VMI

Pearson r

Significance

Pearson r

Significance

.488** (n 5 100) .408** (n 5 99)

.00 .00

2.131 (n 5 24) 2.091 (n 5 24)

.543 .674

.321** (n 5 100) .403** (n 5 100) .464** (n 5 99)

.001 .00 .00

2.036 (n 5 24) 2.012 (n 5 24) .015 (n 5 24)

.866 .957 .946

Note. SIB-R 5 Scales of Independent Behavior-Revised; WS 5 Williams syndrome; DD 5 developmental disability; VMI 5 Berry-Buktenica Developmental Test of Visual-Motor Integration, 4th ed. *Correlation is significant at the 0.05 level (2-tailed). **Correlation is significant at the 0.01 level (2-tailed).

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necessarily in the communication area. The current study used SIB-R, which has a combined social interaction and communication skills score and might not reflect the strength of socialization in WS.

Findings Related to the Predictors of Adaptive Behavior in WS Regression results indicate that in a model controlling for age, IQ, and visual-motor functioning were the best predictors of overall adaptive behavior and the Community Living Skills. Visual-motor functioning predicted the most unique variance in overall adaptive behavior and contributed to the variance above and beyond that of IQ and the other predictors. Personality characteristics did not make any significant contribution. In the Social Interaction and Communication Skills Cluster Score, IQ was the only predictor that contributed significantly to the variance after controlling for age. Neither visual-motor functioning nor personality characteristics contributed significantly to explanations of the variance in this domain of adaptive behavior that requires social component. In SIBR Personal Living Skills Cluster Score and Motor Skills Cluster Score, visual-motor functioning was the only predictor that contributed significantly to the variance after controlling for age. The final model including age, IQ, visual-motor functioning, and personality characteristics significantly predicted the overall adaptive behaviors and the four Cluster Scores. IQ and adaptive behavior. In the current study, IQ significantly predicted the largest amount of unique variance in the SIB-R Social Interaction and Communication Skills. It also contributed significantly to the variance in overall adaptive behavior. These results supported the hypothesis and suggested that IQ is a good predictor of overall adaptive behavior and in the social domain of adaptive behavior in individuals with WS. This supports previous findings that IQ was significantly related to adaptive behavior, especially in relation to individuals with DD (Davies et al., 1997; Liss et al., 2001; Mervis, Klein-Tasman, & Mastin, 2001; Sattler, 2002). On the other hand, IQ did not contribute significantly to the variance in the SIB-R Personal Living Skills and Motor Skills. This is likely due to the fact that the IQ score used here is estimated IQ based on three verbal subdomains. It does not 284

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have any motor or visual-motor components and therefore does not contribute to the variance in the Personal Living Skills. Correlation results indicated that the correlations between estimated IQ and standard scores on the SIB-R domains were all positive and significant, except for Motor Skills. More specifically, the correlation between IQ and Community Living Skills was the highest, followed by the correlations between IQ and Social Interaction and Communication Skills, and then the correlations between IQ and the Personal Living Skills domain. It is worth noting that the IQ scores used in the current study were estimated IQ scores based on three verbal subscales. However, when FSIQ was used to examine the relationship between IQ and adaptive behavior cluster scores in WS, similar results were still found. The correlation results were somewhat consistent with a previous study done by Davies and colleagues (1997) on an adult sample with WS. They found that the correlation between IQ and the Communication domain of the VABS was the highest, followed by the correlations between IQ and Daily Living Skills and the correlations between IQ and the Socialization domain. It is interesting to note that the communication and social domains are combined in one cluster score in SIB-R. However, the correlations found in the current study were not consistent with those of the study conducted by Mervis et al. (2001) on a sample of 4- through 8-year olds with WS. In their study, cognitive ability was not found to be significantly correlated with the Socialization domain on VABS, but it was significantly correlated with Communication, Daily Living Skills, and Motor Skills. This might suggest that IQ is associated with Socialization domain of adaptive behavior in the adult and adolescent population, but not in the young child population. It might be that the ability to appreciate rules of social engagement, which is associated with IQ, may lead to better adaptive social functioning in adults with WS. Visual-motor functioning and adaptive behavior. In the current study, visual-motor functioning predicted the greatest amount of unique variance in overall adaptive behavior and contributed to the variance above and beyond that of IQ and the other predictors. This suggested that visual-motor functioning has a potentially significant impact on adaptive behavior in individuals with WS, as suggested by Adaptive Behavior in Williams Syndrome

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other researchers (Mervis & Klein-Tasman, 2000). When subdomains of adaptive behavior were further examined, visual-motor functioning contributed significantly to the variance in the Personal Living Skills, Motor Skills, and Community Living Skills while not contributing significantly to the variance in the Social Communication and Interaction Skills. However, correlation results indicated that VMI scores were significantly and positively correlated with SIB-R Broad Independence score and all Cluster Scores in the WS group. More specifically, the correlation between VMI and Community Living Skills was the highest, followed by the correlations between VMI and Motor Skills as well as between VMI and the Personal Living Skills domain. The correlation between VMI and Social Interaction and Communication Skills was the lowest. The findings suggested that Community Living Skills were not only strongly associated with IQ but also strongly correlated with visual-motor functioning. Community Living Skills involve time, money, basic work skills, and home/community orientation skills. It is reasonable that both cognitive ability and visual-motor functioning play an important role in obtaining adequate community living skills. On the other hand, significant relationship between VMI and Social Interaction and Communication Skills also supports the finding that motor deficits and dyspraxia might be associated with social, communicative, and behavior impairment in WS (Dziuk et. al., 2007; Lincoln, Searcy, Jones, & Lord, 2007). For example, Lincoln and colleagues (2007) found that many children with WS demonstrated problems in using gestures, pointing, showing, and spontaneously initiating joint attention despite making efforts to gain and sustain the attention of others. The results of the current study also suggested that the relationship between VMI and SIB-R scores is unique to individuals with WS, since such correlations were not found in the DD group. More studies need to be done to examine the relationship between adaptive behavior, motor coordination, and visual-spatial ability in individuals with WS and how this relationship affects the development of adaptive behavior in various domains. Personality characteristics and adaptive behavior. In the current study, personality characteristics did not make any unique and significant contribution to the variance in overall adaptive behavior or any cluster scores. Heightened anxiety T. Fu et al.

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was one of the personality characteristics associated with WS (Klein-Tasman & Mervis, 2003). However, Anxious/Depressed scores on the CBCL were not significantly correlated with SIB-R. This finding contradicted research done by Davies, Howlin, & Udwin (1997), who found in an interview study that in addition to the cognitive characteristics, the personality characteristics associated with WS, such as anxiety, might cause problems in the workplace. High sociability was the other personality characteristic of WS that was entered into the regression in addition to anxiety. Correlation results revealed that SIB-R Broad Independence Score and all Cluster Scores were not significantly correlated with SISQ Social Approach score or MPQ Social Closeness and Stress Reduction subscales. This result did not suggest that high sociability had an impact on adaptive behavior, as argued by some researchers (Davies et al., 1997; Mervis and Klein-Tasman, 2000). The reason behind this discrepancy might be partially due to the issues of validity with the personality measures used in this study. For example, CBCL was originally developed only to test children and adolescents, and SISQ was an exploratory and experimental measure which has never been tested outside of the lab. Therefore, the validity of these measures might be compromised and so the effects of personality characteristics to adaptive behavior were not observed here. The present study made contributions to the existing literature of adaptive behavior in WS. This study was the first to examine the association of intelligence, visual-motor functioning, and personality characteristics with adaptive behavior in individuals with WS. The current study also used an adaptive behavior measure that was different from measures used in previous studies, and therefore was uniquely able to assess motor skills in adolescents and adults with WS. In terms of clinical implications, this study suggests that visual-motor functioning contributes to the variance in adaptive behavior above and beyond that of intelligence and is associated with all aspects of adaptive behavior. Therefore, interventions targeting visual-motor or motor skills may be most helpful, as these areas significantly relate to adaptive behavior. Instructional protocols to improve daily living, community living, and self-help skills of individuals with WS should be developed to optimize motor skill acquisition. 285

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Although this study made contributions to the current literature on adaptive behavior and how it relates to the distinctive cognitive and personality profile of WS, it also had some limitations. First, several of the pertinent measures came from parent/caregiver reports, raising the issue of shared method variance. Future studies should incorporate more objective measurements to assess adaptive behavior, such as observations of adaptive behavior during a standardized task. Second limitation is related to the validation issues with personality measures. For example, the SISQ is an exploratory experimental tool and only has preliminary evidence of its convergent validity (Zitzer-Comfort et al., 2007). Also, the reliability and validity of the shortened parent version of the MPQ is unknown although its original version is psychometrically sound (Patrick et al., 2002). Furthermore, the validity of the CBCL might be reduced in the current study since its use was extended to adult participants with DD. Future studies should use ABCL instead of CBCL to assess social behavioral functioning in adults with WS. Also, the newly developed CBCL DSM-IV anxiety scale can be used to replace the CBCL anxiety/depression scale. Future studies should also incorporate personality or social-behavioral functioning measures that are designed or modified specifically for individuals with DD. Future research is needed to replicate and expand upon the current study. It is important for future studies to continue examining which specific aspects of motor and visual-motor components are contributing to the motor deficits seen in WS. Another important direction is to explore other factors associated with adaptive behavior in WS. Although in the present study, the final model of intelligence, visual-motor functioning, and personality characteristics significantly predicted adaptive behavior, there was still nearly 69% of the variance in adaptive functioning unaccounted for. Therefore, exploration of other factors (i.e., environmental and biological factors) is warranted. By examining the relative influences of different factors on adaptive behavior in individuals with WS, it may be possible to lay the foundation for the development of more specific treatment studies in individuals with this disorder.

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Received 11/8/2013, accepted 8/22/2014. This article is based on the doctoral dissertation titled The Association of Intelligence, Visual-Motor Functioning, and Personality Characteristics with Adaptive Behavior in Individuals with Williams Syndrome, by Trista J. Fu under the direction of Alan J. Lincoln. Part of this article has been presented as a poster at the annual Convention of American Psychological Association in 2012. This project was supported by a grant from the National Institutes of Health (PO1 HD33113) awarded to Ursula Bellugi. We thank the participants and their families for their participation in this study. Authors: Trista J. Fu, College of Education, National Chengchi University, Taiwan (R.O.C); Alan J. Lincoln, California School of Professional Psychology, Alliant International University, San Diego, CA, USA; Ursula Bellugi, Laboratory for Cognitive Neuroscience at The Salk Institute for Biological Studies, La Jolla, CA, USA; and Yvonne M. Searcy, Laboratory for Cognitive Neuroscience at The Salk Institute for Biological Studies, La Jolla, CA, USA. Correspondence concerning this article should be addressed to Trista J. Fu, College of Education at National Chengchi University, NO.64, Sec.2, ZhiNan Rd., Wenshan District, Taipei City 11605, Taiwan (R.O.C) (e-mail: [email protected]).

Adaptive Behavior in Williams Syndrome