Clinical Significance of the Vineland Adaptive Behavior Scale-II in Children With Developmental Disabilities
Article information
Abstract
Objective
This study compared adaptive functioning measured by the Korean version of Vineland Adaptive Behavior Scales, Second Edition (K-VABS-II), in preschool children with developmental disabilities (DD) and those with typical development (TD). We also examined the correlation of K-VABS-II adaptive profiles with developmental and behavioral assessments.
Methods
Two hundred preschool children (73 females and 127 males, mean age 54.7±9.1 months) were recruited from special educational centers, community-based daycare centers, and kindergartens. Eighty-one with DD comprising 61 with autism spectrum disorder, 63 with intellectual disability, 12 with language disorder, and 119 with TD were included. Their developmental profiles were measured by the Psychoeducational Profile-Revised (PEP-R), Preschool Receptive-Expressive Language Scale (PRES), K-VABS-II, Social Responsiveness Scale (SRS), and the Korean version of the Childhood Autism Rating Scale (K-CARS). The parent completed the Child Behavior Checklist (CBCL), and Aberrant Behavior Checklist (ABC).
Results
The K-VABS-II Adaptive Behavior Composite and all domain scores of K-VABS-II differed significantly between children with DD and TD (all p<0.001). In most domains, K-VABS-II had moderate-to-strong correlations with PEP-R, PRES, K-CARS, and SRS. The Maladaptive Behavior Index domain of K-VABS-II had moderate correlations with behavioral assessments, including CBCL and ABC.
Conclusion
These findings suggest that K-VABS-II is useful in evaluating developmental levels and adaptive and maladaptive behaviors of preschool children with DD. K-VABS-II also had significant correlations with cognitive, language, social, and behavioral assessments.
INTRODUCTION
Adaptive behavior defines the ability of an individual to meet daily living responsibilities and respond to the needs of others [1] as well as to function within their environment daily, including social, conceptual, and practical abilities [2]. A delay in adaptive behavior limits the expected maturity, learning, independence, and social responsibility of a specified age in a socio-culturally oriented context [3]. The Centers for Disease Control and Prevention defines developmental disabilities (DD) as conditions due to impairments in physical, learning, language, or behavior. ACCESSDD is a generic term that encapsulates a broad range of conditions, such as neurodevelopmental disorder described in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR). In young children, developmental delays can occur simultaneously in many areas and change with time, with a varying rate of change from area to area. Thus, distinguishing DD as a subdivided neurodevelopmental disorder is often challenging, so their identification in young children is important. For children with DD, adaptive behavior is important for development assessment, including level of functioning, and for treatment planning.
Thorough evaluation of the developmental level and adaptive behavior is often difficult in children, especially those with DD. Children with DD commonly have difficulty engaging in developmental assessments and following directions. Directly assessing children with autism spectrum disorder (ASD) owing to their lack of understanding of test situations, distractions in the environment, perseverative responding, a lack of familiarity with the testing environment, a lack of social response to the examiner, and frustration with performance as test items become harder [4]. For children with intellectual disability (ID), participating in developmental assessments may also be difficult given the challenges with executive function, preference for predictable routines and people, sensorimotor delays, and communication deficits caused by language, speech, and/or social-emotional delays [5]. Therefore, assessing their developmental level and adaptive behavior through their parents is essential in addition to direct testing. Moreover, children who participate well in the evaluation also need to balance their assessment with that of their parents. Thus, parent-completed assessments play an important role in clinical settings to assess the developmental level and adaptive behavior of preschool children.
One of the most globally favored parent-completed measures of assessment is the Vineland Adaptive Behavior Scales, Second Edition (VABS-II) [6]. However, the Social Maturity Scale (SMS) has been used the longest in Korea before the introduction of the Korean version of VABS-II (K-VABS-II) in 2015 [7]. Since the Korean version of the SMS (K-SMS) was standardized in 1985, it was considered to not reflect the latest research and altered norms regarding self-help skills. The VABS-II has advantages over SMS in that it provides an additional measure of motor skills and maladaptive behavior. Moreover, VABS-II can estimate standard scores for each domain, in addition to adaptive composite scores, whereas SMS only calculates a social quotient based on social age. Hwang et al. [7] thus standardized the K-VABS-II.
Studies have aimed to determine whether VABS-II can be used to identify children with DD and evaluate their developmental level and adaptive behavior. Most studies on the clinical utility of Vineland Adaptive Behavior Scales (VABS) or VABS-II were conducted in Western countries. A previous study reported that VABS is a useful tool for Dutch children and adolescents with ID, including all levels of ID and a wide age range [8]. Another study suggested that VABS is an effective assessment for identifying adaptive behavior profiles in Canadian children with ASD with varying cognitive abilities [9]. Balboni et al. [10] reported that certain item subsets in VABS-II may help identification of Italian preschool children with ASD and discrimination between these children and peers with nonautistic neurodevelopmental disorder. Only a few previous studies have suggested that VABS could be adapted to the cultural context of Eastern countries [11,12]. Moreover, in the existing studies, the sample size of the patient group was relatively small compared to Western studies, and the studies included a limited number of assessment tools. Since culture shapes what is considered adaptive behavior, it is important to examine whether VABS-II identifies children with DD and assesses their developmental level and adaptive behavior across a variety of cultures.
In this study, we aimed to find out the usefulness of KVABS-II in evaluating the developmental level and adaptive behavior of children with DD from Asian cultures. We also assessed the concurrent validity of K-VABS-II by comparing it with the comprehensive developmental and behavioral assessments in children who have DD and typical development (TD).
METHODS
Participants and procedure
This study included 200 preschool-aged children, ranging from 34 to 77 months old, upon consent from their parents. The children were enrolled at special educational centers, community-based daycare centers, and kindergartens from May 1, 2020, to July 31, 2020. Exclusion criteria included severe fine or gross motor problems that prevented them from participating in psychometric tests, a history of neurologic diseases such as cerebral palsy, or any sensory disturbances (i.e., hearing, vision, smell, or taste).
Diagnoses were confirmed by board-certified child and adolescent psychiatrists based on the DSM-5 and relevant developmental assessments. When a diagnosis of ID was confirmed, a diagnosis of language disorder (LD) was not applicable. ASD, ID, and LD were included in DD in this study. Because the children in our study were relatively young (mean age, 54.7± 9.1 months; range, 34 to 77 months) and a substantial portion of our sample fell outside the appropriate age range for diagnosis, we excluded attention-deficit/hyperactivity disorder and tic disorder from our definition of DD for this particular study, although they are also neurodevelopmental disorders. TD was defined as cases where caregivers reported no developmental concerns and standardized assessments showed no evidence of developmental delay. In cases where there was a discrepancy between caregiver reports and assessment findings, a child psychiatrist conducted a follow-up evaluation to rule out DD such as ASD, ID, and LD, and to confirm that the child’s development was within the normal range for their age. Of the 200 children who were enrolled, 81 were diagnosed with DD and 119 showed TD. Children with DD comprised 6 with ASD, 13 with ID, 7 with LD, 50 with ASD and ID, and 5 with ASD and LD. The study was approved by the Institutional Review Board of Asan Medical Center (2020-0386).
Measures
The VABS-II is a semi-structured interview involving checklists or clinical interviews completed by caregivers who regularly observe adaptive behaviors [6]. There are five domains: Communication, Daily Living Skills, Social Skills, Motor Skills, and Maladaptive Behavior Index (MBI) (optional). Standardized scores with a mean of 100 and a standard deviation (SD) of 15 are provided for four domains (Communication, Daily Living Skills, Social Skills, and Motor Skills) and overall standard VABS-II Adaptive Behavior Composite Score (ABCS). Lower standardized scores indicate a lower level of adaptive functioning. V-scale scores with a mean of 15 and a SD of 3 are calculated for the MBI domain and each subdomain. Our study used the K-VABS-II, which was standardized and validated [7].
Psychoeducational Profile-Revised (PEP-R) [13] is used to assess developmental levels in children. The PEP-R assesses seven scales of development: Imitation, Perception, Fine Motor, Gross Motor, Hand–Eye Coordination, Cognitive Performance, and Cognitive Verbal. The Developmental Quotient (DQ) is obtained to assess the overall developmental level. PEP-R demonstrated inter-rater and test–retest reliability, and concurrent validity [14-16]. We used the translated Korean version of PEP-R [17].
The Preschool Receptive-Expressive Language Scale (PRES), standardized and validated in Korean, evaluates language development in preschool-age children by measuring receptive and expressive language [18]. A delay in the language age measured by PRES of more than 12 months compared with the chronological age was defined as a significant delay. Language quotients are calculated to compare the level of language development in children of different ages for receptive and expressive language separately.
The Childhood Autism Rating Scale (CARS) comprises 15 items, which the clinician scores from 1 to 4 according to the behavior of the child. A higher total score indicates higher severity. CARS demonstrated inter-rater reliability of 0.71, internal consistency of 0.94, and acceptable validity [19]. The Korean version of the Childhood Autism Rating Scale (K-CARS) was a highly reliable test and had discriminant validity [20].
The Social Responsiveness Scale (SRS) is used to assess autistic social impairment and provides a continuous measure of social ability. The SRS is a 65-item on a 4-point Likert scale, completed by parents or teachers, and comprises five domains: Social Awareness, Social Cognition, Social Communication, Social Motivation, and Autistic Mannerisms. Higher scores indicate more severe social impairments. SRS had adequate internal consistency and inter-rater reliability, and extensive validity data [21]. We used the translated Korean version of the SRS [22].
The Child Behavior Checklist (CBCL) for ages 1.5–5 was used to measure behavioral and emotional problems. CBCL is a 99-item scale completed by parents and assesses the seven subscales: Emotionally Reactive, Anxious/Depressed, Somatic Complaints, Withdrawn, Sleep Problems, Attention Problems, and Aggressive Behaviors. These seven subscales are calculated as two combined scales comprising: Internalizing Problems and Externalizing Problems, and Total Problems. CBCL had high test–retest reliability and validity23 and was standardized and validated in Korean [24].
The Aberrant Behavior Checklist (ABC) is a rating scale to assess behavioral problems in individuals with DD. This instrument contains a 58-item scale on a 4-point scale that resolves into five subscales: Irritability, Lethargy/Social Withdrawal, Stereotypical Behavior, Hyperactivity/Noncompliance, and Inappropriate Speech [25]. ABC had good test–retest reliability and internal consistency, and validity was established for most ABC subscales [26]. Our study used the validated Koreantranslated version of the ABC [27].
Statistical analysis
Descriptive statistics were calculated, and the results were compared between children with DD and TD. Student’s t-test was used for continuous variables and chi-squared test was used for categorical variables. Student’s t-test examined differences in K-VABS-II and PEP-R, PRES, K-CARS, SRS, CBCL, and ABC scores between DD and TD, and analysis of covariance was used to adjust for age and sex. Additionally, we performed Pearson’s correlation analysis to examine concurrent validity between K-VABS-II and the other developmental and behavioral assessment instruments between DD and TD. In general, Pearson’s correlation coefficients from 0 to 0.3 (or 0 to -0.3) are negligible; those from 0.31 to 0.5 (or -0.31 to -0.5) are weak; from 0.51 to 0.7 (or -0.51 to -0.7) are moderate; from 0.71 to 0.9 (or -0.71 to 0.9) are strong correlations; and correlations >0.9 (or <-0.9) are considered very strong [28].
All statistical analyses were performed using SPSS Software (version 23.0; IBM Corp., Armonk, NY, USA) and the R Statistical Software (version 4.1.3; R Foundation for Statistical Computing, Vienna, Austria).
RESULTS
The overall demographic and clinical characteristics of the DD and TD groups are summarized in Table 1. Children with TD (age=52.3±8.5 months) were significantly younger than those with DD (age=58.3±8.8 months; p<0.001), and the two groups had significantly different sex distributions: 58 children with DD (71.6%) and 69 with TD (58.0%) were boys (χ2=3.86, p=0.049). Age and sex were adjusted for further analyses. The DD group had a significantly lower K-VABS-II ABCS than the TD group (57.9±14.5 vs. 92.6±12.9; p<0.001). In the PEP-R DQ, PRES Receptive Language Quotient, and PRES Expressive Language Quotient (ELQ), DD children had significantly lower scores than TD children (p<0.001). Regarding the SRS Total score, K-CARS, CBCL Total Problems, and ABC Total score, DD had significantly higher scores than TD (p<0.001).
The K-VABS-II domain and subdomain scores were compared between the DD and TD groups (Table 2). Among the four domains (Communication, Daily Living Skills, Social Skills, and Motor Skills) and corresponding subdomains, children with DD had significantly lower scores than those with TD after adjustment for age and sex (adjusted p<0.001). Children with DD had significantly higher scores in the MBI domain and Internalizing Behaviors and Externalizing Behaviors subdomains than those with TD after adjustment for age and sex (adjusted p<0.001).
There were statistically significant correlations between all K-VABS-II domains and subdomains except between Externalizing Behaviors and Gross Motor subdomains among the total 200 children (Figure 1). Correlations between K-VABS-II domains and subdomains in DD and TD, respectively, are presented in Supplementary Figures 1 and 2.
Pearson’s correlation coefficients between K-VABS-II domains and subdomains, PEP-R subscales, PRES domains, KCARS, and SRS domains were calculated among the 200 children (Figure 2). Moderate-to-strong correlations were observed between K-VABS-II domains and subdomains, and PEP-R subscales (ranging from -0.569 [K-VABS-II MBI and PEP-R Gross Motor] to 0.897 [K-VABS-II ABCS and PEP-R DQ]) except for the Externalizing Behaviors subdomain of K-VABSII. Moderate-to-strong correlations were also observed between K-VABS-II domains and subdomains, and PRES domains (ranging from 0.528 [K-VABS-II Written and PRES ELQ] to 0.779 [K-VABS-II Expressive and PRES ELQ]) except for the K-VABS-II Motor Skills domain and Domestic, Gross Motor, Externalizing Behaviors, and Internalizing Behaviors subdomains. Between K-VABS-II domains and subdomains and K-CARS, moderate-to-strong correlations (ranging from -0.616 [K-VABS-II Gross Motor] to -0.834 [K-VABS-II ABCS]) except for the Externalizing Behavior subdomain of K-VABSII. Moderat-to-strong correlations between the K-VABS-II domains and subdomains, and SRS domains (ranging from -0.512 [K-VABS-II Motor Skills and SRS Social Cognition] to -0.717 [K-VABS-II Expressive and SRS Social Communication]) except for the Written and Domestic subdomains and a few subdomains of Motor Skills and MBI domains of K-VABS-II. Correlations between K-VABS-II domains and subdomains, PEPR subscales, PRES domains, K-CARS, and SRS domains in DD and TD, respectively, are presented in Supplementary Figures 3 and 4.
We calculated Pearson’s correlation coefficients between the MBI domain and Internalizing Behaviors and Externalizing Behaviors subdomains of K-VABS-II, and Total Problems, Externalizing Problems, and Internalizing Problems of CBCL and Total score and six subscales of ABC among the 200 children (Figure 3). The MBI domain showed moderate correlations between the CBCL scales (range: 0.536 [Externalizing Problems] to 0.616 [Total Problems]) and ABC Total score and subscales (range: 0.517 [Irritability] to 0.641 [Total score]) except for Inappropriate Speech. The Internalizing Behaviors subdomain of K-VABS-II showed moderate correlations between the Total Problems (r=0.585, p<0.001) and Internalizing Problems (r=0.596, p<0.001) scales of CBCL, and Total score (r=0.603, p<0.001), Lethargy (r=0.616, p<0.001), Stereotypical Behavior (r=0.518, p<0.001) subscales of ABC. In contrast, the Externalizing Behaviors subdomain of K-VABSII had weak correlations with CBCL scales (range: 0.271 [Internalizing Problems] to 0.389 [Externalizing Problems]) and Total score and subscales of ABC (range: 0.198 [Inappropriate Speech] to 0.390 [Hyperactivity]).
DISCUSSION
Our study showed lower K-VABS-II ABCS and all domain scores of K-VABS-II in children with DD than in TD, suggesting that K-VABS-II is useful for evaluating the developmental level and adaptive behavior of preschool children with DD. In addition, K-VABS-II was significantly associated with other developmental and behavioral assessments in preschool children with DD and TD. Across most domains, K-VABS-II had moderate-to-strong correlations with developmental assessments such as PEP-R, PRES, K-CARS, and SRS. The MBI domain of K-VABS-II also had moderate correlations with emotional and behavioral assessments, including CBCL and ABC.
Our study revealed that children with DD had lower adaptive functioning than those with TD. A standardization study [7] of the K-VABS-II showed that K-VABS-II displayed good test– retest reliability and concurrent validity with K-SMS, Korean Wechsler Intelligence Scale for Children-IV (K-WISC-IV), and Korean Wechsler Adult Intelligence Scale-IV (K-WAISIV). Another Korean study [29] reported that K-VABS-II ABCS and Full Scale Intelligence Quotient (FSIQ) measured by KWISC-IV or K-WAIS-IV had strong positive correlations in participants with ID, and K-VABS-II ABCS showed significant discrimination between the normal and ID populations. Previous studies [11,12] suggested that Vietnamese and Indonesian versions of the VABS could be adapted to their cultural settings and operationalized. The findings of these studies in combination with our own suggest that VABS-II is useful, even in non-Western countries, for evaluating the adaptive behavior of children and discriminating DD from TD.
In our study, K-VABS-II ABCS and all domains showed a significant correlation with PEP-R DQ and the subscales. Another study [30] similarly reported that each VABS domain score had a strong correlation with PEP-R Developmental Score. Another study [15] revealed that the developmental score of the Chinese version of PEP-R was significantly correlated with the domain scores of the Hong Kong-Based Adaptive Behavior Scale, which was modeled after the VABS. In addition to PEP-R, VABS or VABS-II have been studied alongside several other cognitive assessments. A previous study [31] reported that all correlations between domain and subdomain scores of VABS-II and Bayley-III Cognitive standard scores were statistically significant in 125 toddlers with ASD. Similarly, Scattone et al. [32] revealed no statistical difference between VABS-II ABCS and cognitive scores of Bayley-III. In another study, primary index scores and FSIQ of Wechsler Preschool and Primary Scales of Intelligence, Fourth Edition and VABS-II domains showed moderately high correlations in children with ID and negligible to moderately high correlations in children with ASD [33]. Additionally, K-VABS-II ABCS and FSIQ measured by K-WISC-IV or K-WAIS had strong positive correlations in individuals with ID [29]. Furthermore, Dacey et al. [34] reported that most of the correlations observed between the Fourth Edition of the Stanford–Binet Intelligence Scale Test composite and area scores and VABS ABCS were significant. These findings therefore suggested that VABS-II has significant correlations with PEP-R and other cognitive assessments. Performing cognitive assessments for children can be challenging for many reasons, but the VABS-II, which is completed by parents, can effectively provide indicators of cognitive function as well as reliable information about adaptive behavior.
The majority of K-VABS-II domains and subdomains showed significant correlations with the level of social development measured by SRS and severity scores of ASD measured by KCARS in the current study. Previous research found that the SRS Total score and all domains were correlated significantly with VABS-II domains and subdomains in children and adolescents [35]. Similarly, other studies demonstrated a strong correlation between SRS Total score and VABS ABCS in preschool children with ASD [36]. Other research reported that VABS ABCS had significant correlations with the Social Communication Questionnaire and the Children’s Communication Checklist, as well as SRS in children with ASD [37]. These results are consistent with our findings showing K-VABS-II to have significant correlations with assessment for social development.
A previous study showed that children with low levels of ASD, measured by the Autism Diagnostic Observation Schedule (ADOS), scored higher in all VABS domains than children with moderate or high levels of ASD [38]. Another study suggested an association between higher ADOS scores for social and communication symptoms of ASD and lower Adaptive Behavior Assessment System-II composite scores [39]. Based on these findings, our study suggests that social impairment impacts adaptive functioning, and more severe symptoms of ASD are predictive of lower adaptive functioning in children. Therefore, interventions targeting social and communication skills should be prioritized because they can lead to improvements in adaptive functioning.
In our study, maladaptive behavior measured by K-VABSII had was significantly associated with behavioral and emotional assessments, including CBCL and ABC. Sparrow also reported significant correlations between the behavioral problem domain of VABS-II and the Behavior Assessment System for Children, Second Edition in preschool children [40]. These results support the accurate reflection of MBI in VABS-II emotional and behavioral problems in preschoolers. Our results suggest that K-VABS-II is a useful tool to easily identify behavioral and emotional problems while performing developmental assessments.
In the current study, the MBI domain and Internalizing Behaviors subdomain of K-VABS-II were well-correlated with the adaptive functioning of K-VABS-II and other assessments measuring cognitive, language, and social developments, especially in DD. Emotional and behavioral problems are likely to be associated with the level of adaptive functioning [8,41]. Previous studies also identified a significant relationship between deficits in selective attention, executive functions, or general intelligence with emotional and behavioral problems [41-44]. Children with language impairment are reported to have greater behavioral problems than children without such impairment [45,46]. Prior studies have also revealed that social skills positively correlate with emotional and behavioral traits such as emotional regulation and social confidence [47,48]. Taken together, the results of our study suggest that children with DD who have low adaptive, cognitive, language, and social development should be monitored for emotional and behavioral problems.
Several limitations should be considered when interpreting our findings. First, children with ID or LD only account for a relatively small proportion of the DD population. The utility of K-VABS-II in identifying each disorder could not be established. Second, we did not include other conditions such as cerebral palsy or sensory abnormalities, which had originally been considered a DD. However, rather than focusing on the effects of gross motor or sensory impairments, we aimed to examine the utility of the K-VABS-II, based on cognitive, language, and social developments. Third, our study did not include the entire age range of K-VABS-II. However, our study remains meaningful because it is aimed at identifying developmental delays early using K-VABS-II. Fourth, the third edition of VABS is now available. However, VABS-II is widely used in many countries, so the findings of this study have significance.
Despite these limitations, the strength of our study comes from a relatively large sample of Asian, rather than Western, preschool children.
In conclusion, K-VABS-II is useful to evaluate not only the developmental level and adaptive behaviors but also the maladaptive behaviors of preschool children with DD. Additionally, K-VABS-II had significant correlations with cognitive, language, social, and behavioral assessments. Our findings suggest that K-VABS-II is also effectively applicable in Asian cultural contexts.
Supplementary Materials
The Supplement is available with this article at https://doi.org/10.30773/pi.2024.0140.
Notes
Availability of Data and Material
The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.
Conflicts of Interest
The authors have no potential conflicts of interest to disclose.
Author Contributions
Conceptualization: Hyo-Won Kim. Data curation: Gyeongwon Park, Jichul Kim, Taeyeop Lee. Formal analysis: Gyeongwon Park. Funding acquisition: Hyo-Won Kim. Investigation: Hyo-Won Kim. Methodology: Gyeongwon Park, Hyo-Won Kim. Project administration: Hyo-Won Kim. Resources: Hyo-Won Kim. Software: Gyeongwon Park. Supervision: Hyo-Won Kim. Validation: Hyo-Won Kim. Visualization: Gyeongwon Park, Taeyeop Lee. Writing—original draft: Gyeongwon Park. Writing—review & editing: Hyo-Won Kim.
Funding Statement
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT (NRF2020R1A5A8017671).
Acknowledgements
The authors are grateful to all the children and families who participated in this research. This research would not have been possible without their involvement.