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Infant-Toddler Intervention: The Transdisciplinary Journal (1999), 9 (2), 169 - 184. Development of a Cognitive Assessment Battery for Young Children with Orthopedic Disabilities
Paula Guerette, PhD, Donita Tefft, MA, CCC-SP, Jan Furumasu, BSPT Address correspondence to: Paula Guerette, PhD Rehabilitation Engineering Bonita Hall, Rancho Los Amigos Medical Center 7503 Bonita Street Downey, California 90242 ABSTRACT
Assessing the cognitive skills of young children with physical disabilities can be difficult since most standardized assessment batteries for children under three years of age require specific motor responses to evaluate cognitive skills and are not flexible in administration procedures to accommodate for physical limitations. Further, many existing assessment batteries either do not provide scores for separate cognitive domains, or do not contain enough items to adequately assess children across the entire age range from 18 to 36 months. In order to assess cognitive skills across several domains in children with physical disabilities, an assessment battery with flexible administration materials and procedures was developed. A preliminary battery of 83 items with 148 scorable responses across five cognitive domains (object permanence, cause/effect, problem-solving, spatial relations and symbolic play) was developed. The battery was administered to 26 children with severe physical disabilities between the ages of 20 and 36 months. Rasch analysis was applied to the data to eliminate non-discriminatory, redundant and/or misfit items. This resulted in a final battery with 35 items, all with high internal consistency within their respective cognitive domains. Inter-rater reliability, intra-rater reliability and test-retest reliability were all high. Clinical applications of the battery are discussed. INTRODUCTION Educators and clinicians who work with young children have long recognized the usefulness of cognitive assessment instruments in identifying a child’s developmental strengths and weaknesses, developing educational plans and objectives, establishing early intervention therapies, and measuring progress in cognitive domains. In addition, rehabilitation professionals who work with very young children with physical limitations need to be able to assess cognitive skills for a variety of rehabilitation objectives. There are a number of tools available to assess cognitive skills in infants and young children (e.g., Bayley Scales of Infant Development - II,1 Battelle Developmental Inventory,2 Developmental Activities Screening Inventory - II,3 Carolina Curriculum for Handicapped Infants,4 Uzgiris and Hunt Infant Psychological Developmental Scale - Dunst Revision5). However, difficulties can sometimes exist for the clinician who wishes to assess individual cognitive skill domains in young children with physical limitations. For example, traditional norm-referenced evaluation tools often indicate only a global cognitive developmental age (i.e., scores reflect an average of all cognitive skill areas). One such battery, the Bayley Scales of Infant Development - II1, combines language and other cognitive skills such as object permanence, cause/effect and spatial relations into a single global score, and scores for individual cognitive skills are not readily attainable. Summary scores can sometimes be misleading because children with the same global developmental score may have very different scores across the contributing developmental domains, resulting in widely varied abilities across different learning situations. Further, the evaluation of cognitive skills in a young child with physical disabilities can be challenging since many assessment batteries infer cognitive skills from sensory and motoric responses to tasks presented. In fact, most standardized assessment batteries for children under three years of age require specific motor responses to evaluate cognitive skills and are not flexible in administration procedures, regardless of the child's physical abilities or interest. When a young child with a physical disability is unable to demonstrate an age-appropriate task response, it is often difficult to determine whether the child has not developed these cognitive skills or has developed the skills but is unable to perform the task because of physical limitations. For clinicians and researchers who use this information to make clinical decisions or observe clinical findings, this dilemma can pose a difficult challenge. For example, the current researchers proposed that certain cognitive skills may influence a young child's ability to operate a powered wheelchair. Currently however, because of the difficulty in obtaining an objective measure of these cognitive skills in young children with disabilities, the decision to place a child in powered mobility is typically based on clinicians' experience and/or trial and error. Better knowledge of a child's level of development in these skills could lead clinicians to a more timely placement of young children in powered mobility devices and to improved intervention plans. After examining existing assessment batteries, it was found that no single instrument could adequately assess cognitive skills in children with physical disabilities over the entire age range between birth and age three, that would provide scores for separate cognitive domains, and would be flexible in materials and administration procedures to accommodate physical limitations. In order to evaluate cognitive skills in these children, there was a need for an assessment instrument that could assess these skills without penalizing children for motoric limitations. Thus, the purposes of the current research were as follows: 1) to develop a cognitive assessment tool with flexible task materials and administration procedures to evaluate cognitive skills across various domains in young children with physical disabilities, and 2) to determine which of these cognitive skills can predict powered wheelchair driving ability. A program to teach and evaluate powered mobility skills has been described previously,6 and the results of the comparison between cognitive skills and powered mobility skills are described elsewhere.7 The current article describes the development of the cognitive assessment battery. METHODS Selection of Cognitive Domains 'Piagetian-based' assessment instruments8-10 often assess critical concepts assumed to be the foundations for later learning. A Piagetian-based framework of sequential stage development within distinctly different skill domains allows the clinician to determine a child's developmental strengths and weaknesses across various cognitive domains, such as object permanence, problem solving, receptive language and seriation. Despite criticisms of Piaget’s cognitive developmental theory (e.g., neglect of the role of social or cultural factors,11,12 disregard for postadolescent development,13 underestimate of the competence of children14 ), this is nevertheless a well researched and validated theory of infant/toddler cognitive development.15-17 Cognitive development of children from birth to 36 months of age is encompassed by Piaget’s Sensorimotor and early Preoperational stages. Development in the Sensorimotor stage (birth to 24 months) involves integrating motor and sensory movements that eventually lead to representational or symbolic abilities. During the early phase of the Preoperational Stage (2 to 4 years), children learn to use internal cognitive images to organize thoughts logically and become active problem solvers. At each stage of development, a typical child demonstrates specific behavioral attributes across cognitive skill domains (e.g., operational causality, means-ends relations, object permanence, seriation). Normally developing children progress through each domain in a hierarchical manner but may achieve different stages of development simultaneously across domains. A Piagetian based developmental approach has been found to be appropriate for children with a diverse range of disabilities (e.g., mild to profound developmental delays, cerebral palsy, limb deficiencies, and visual or hearing impairments). For example, in a study of 21 children ages 17-44 months who were physically affected by thalidomide,18 all children 18 months and older had successfully achieved Piaget’s highest level object permanence; only the youngest two who were 17 months had not yet reached this level. In reviews of research on this topic,5,19 it was found that children with diverse disabilities typically acquire behaviors in the same sequential stage development as able-bodied children, but may differ in the rate at which skills are attained and in the final level of mastery. Other research has also found that the developmental sequence for symbolic play was similar among children with Down syndrome and normally developing children.20 Twelve Piagetian-based developmental skill domains representing the sensory-motor and preconceptual stages were considered for inclusion in the current assessment battery (see Table 1). It was believed that some of these areas would be less likely to relate to wheelchair operation skills (e.g., numbers, vocal imitation). Since it was not practical to evaluate children with disabilities across all twelve domains due to the length of time to conduct such an evaluation and the limited patience and attention span of children in this age range, it was determined that a subset of domains would be selected for inclusion. To establish content validity and determine the most appropriate cognitive domains to be included, ten experts in the field of early child development, occupational therapy, speech pathology and powered mobility were asked to rate the twelve developmental skill domains in terms of their presumed relevance to powered mobility skills. Based on these ratings, a subset of five domains (cause/effect, object permanence, problem-solving, spatial relations, symbolic play) was selected. A brief description of these cognitive skill domains is presented in Table 2.
Item Selection To identify items in these five domains for inclusion in the battery, existing cognitive assessment batteries were reviewed. It was determined that no single existing assessment battery contained an adequate number of items across the age span of 18 to 36 months (range where children might be able to operate a powered wheelchair) and could be modified for use with children with physical disabilities. Thus, items from various tests were used to create a continuum in each domain that would assess this entire age range. The preliminary assessment battery incorporated 73 tasks from several standardized developmental batteries5,10,21-23 along the five cognitive domains identified. This battery was then pilot tested with three children, and necessary revisions in item content were made. For example, items in the spatial relations domain that required physical locomotion (e.g., ‘Child makes a simple detour to obtain a desired object’) were replaced by items at the same age range that evaluated spatial relations without emphasizing physical movement, and items were added to better assess the upper end of the symbolic play scale (i.e., play with mini toys). The final battery included 83 tasks evaluating cause/effect, object permanence, problem solving, spatial relations and symbolic play. Items in the cause/effect scale assess development through 21 months and items in the object permanence scale ‘ceiling’ at 23 months, the ages at which these skills are believed to be fully developed and integrated into more complex domains. The other three scales include items assessing development through 36+ months. Several tasks had multiple scoring levels depending on the nature of the child’s response, for a total of 148 scorable responses across the entire battery. Examples of items are included in Table 3.
Modification of Item Administration Tests with standard procedures for administration and response often require modification for use by people with functional impairments.24 Since the battery was being developed for use with children with functional limitations, it was essential that the response requirements not penalize children with motor disabilities. Therefore, the assessment battery materials were modifiable where appropriate to accommodate various physical limitations. Modifications of materials, positioning or environment were made to allow children to lift, move, or manipulate the objects, however, care was taken to insure that the basic task premise always remained the same. For example, one task assessing spatial relations required the child to stack large plastic rings on a long plastic dowel. During assessment of children who were too weak to lift the plastic rings or who had limited range of motion, small, lightweight styrofoam rings and a shorter dowel were substituted. During a problem solving task that required children to dangle a long chain to insert it into a small opening, shorter chains were used for children who were unable to lift their arms above chest height. For a child with almost no upper extremity movement, the three-screen object permanence task was conducted with one-inch squares of construction paper, vertically positioned on a small shelf instead of napkins placed on the table. If a child physically attempted the critical component of a task and demonstrated the intent of the task, the test administrator was permitted to complete the movement to reward the child and limit frustration. For example, during a task assessing problem solving and tool use, if a child picked up a stick and attempted (but was physically unable) to obtain an out-of-reach object using the stick, the test administrator used the stick to pull the object to the child. Modifications were also made in the children’s physical positioning during assessment to maximize upper extremity range of motion. One child was evaluated in a gravity-reducing position, lying on his side, while another child was assessed in a standing position, leaning on the assessment table. PARTICIPANTS Participants included 26 children (20 male, 6 female) between the ages of 20 months and 36 months, with various physical disabilities. The average age at the time of cognitive assessment was 28.3 months. Children were recruited from clinics at a large rehabilitation medical center in Los Angeles and from the California Children Services, an agency providing school-based physical and occupational therapy services. Table 4 presents the participants’ diagnoses. Only children with diagnoses not typically associated with severe cognitive and/or sensory-motor impairments were included (e.g., muscle disease, spinal cord injury, arthrogryposis). This served to minimize the potential influence of sensorimotor integration problems which may occur with conditions with central nervous system involvement (e.g., cerebral palsy, acquired brain injury). Diagnoses classified as 'other' include burn/amputee, polio, spina bifida, osteogenesis imperfecta and femur hyplasis syndrome. Children’s hand function varied from completely functional to a minimal or non-functional grasp. For example, children with muscle disease had a weak grasp and limited active reach. Children with arthrogryposis who had no functional grasp compensated by moving their arms and hands via trunk movement or picked up objects with their teeth. All children were positioned to maximize the functional use of their arms (e.g., sitting, standing, lying down) prior to administration of the assessment battery. All participants were unable to ambulate at the time of participation in the study.
PROCEDURE Information on functional status (e.g., ability to lift arms, range of reach, grasping ability, trunk control, functional position to manipulate objects) obtained from referring clinicians was reviewed prior to assessment to determine whether any modified items should be used; additional modifications were made in five cases to accommodate physical limitations identified during the actual assessment (e.g., a miniature scale version of the three-piece formboard was made out of styrofoam for a child with limited strength and range of motion). All children were evaluated in a location free from distraction in their primary language. The administrator started at the mid-point of each developmental scale and then administered items below or above on the scale based on the child's initial responses to obtain a basal and/or a ceiling score, a common approach for developmental assessments. Generally, all items on a scale were administered before beginning the next scale, however, the battery allows deviation from this protocol as necessary to maintain a child's interest and attention. The order of scale presentation was as follows: object permanence, cause/effect, problem solving, spatial relations, and symbolic play. Each item was administered the number of times specified in the original test batteries. The battery was administered over one to three sessions, depending on the child's attention span, and generally took between 1½ and 3 hours to complete. These sessions were completed within a two-week period. All sessions were videotaped and later reviewed and scored. The score received on each item was based on the nature of the child's response. If a child performed the task correctly the required number of times, she received a 'correct' for this task. If a child performed a task fewer than the required number of times or was unable to perform a task at all, she received an 'incorrect' score for this task. Data from ten children were scored independently by two raters to establish an index of interrater agreement, and the videotaped responses made by nine children during the original assessment were rescored eight to twelve months later by one of the original raters to determine 'drift' or intrarater consistency in ratings over time. In addition, the test battery was re-administered to three children within two weeks of the original assessment to evaluate test-retest reliability. Item scores were then analyzed using Rasch analysis to determine internal consistency and item dimensionality and to create hierarchical scales of items across each domain. ITEM ANALYSIS Internal consistency and item dimensionality. Rasch analysis is useful in developing measurement scales that have a hierarchic, unidimensional structure.25 This means that each scale is comprised of a set of tasks representing increasingly more difficult items along the same dimension -- in the present case, the five cognitive domains. Thus, a child who has mastered a higher-level task will have mastered previous lower-level tasks. It has been suggested that Rasch measurement techniques are ideal for applications in early childhood assessment,26 and this technique has recently been used to scale a pediatric disability inventory (PEDI),27 a mental/motor assessment battery (Bayley-II)1 and a functional assessment battery for children with developmental disabilities (WeeFIM).28 Rasch analysis also provides a means for clustering data such that redundant or 'misfit' items can be identified and excluded from a scale. Redundant items are those that measure the same skill at the same level of difficulty, while misfit items are those that do not perform consistently (i.e., difficult items that are passed by children at lower cognitive stages, easy items that are missed by children at higher cognitive stages). Items in which all children or no children scored correctly are also eliminated because they provide no discrimination among the childrens' abilities. Theoretically, the items that remain all measure something along a single, unidimensional skill domain. Rasch analysis was applied to the developmental data in each of the five cognitive domains using the program BIGSTEPS,29 and 113 items were eliminated. These items were either redundant with other items in terms of level of difficulty (i.e., multiple items in a domain assessed the same developmental level) or were misfit (i.e., demonstrated inconsistency in overall performance or incongruity with the underlying dimension). After deletion of these items, the remaining 35 items demonstrated high internal consistency within their respective scales. For each of the scales, the subject separation score (an index of the ability to discriminate between children of different levels of development) and reliability measures indicated that the children were well spaced out along the cognitive developmental continuum measured by that domain. Item separation scores (an index of how well items are sufficiently spread out to define distinct levels of difficulty in each cognitive domain) also indicated that items were well spaced out along the stages of development represented by children ages 18 to 36 months (see Table 5).
Scaled Scores. Rasch analysis was also used to transform the original item (logit) scores to scaled scores on a 0 to 100 distribution, with zero corresponding to an inability to succeed on any items, and 100 reflecting the ability to succeed on all items in a domain. Children are expected to move along the continuum in a hierarchical manner, and a score at any point in this hierarchy provides an index of mastery along the domain. In other words, although it may be intuitively obvious to the clinician that a task such as nesting five cups by size is more difficult than completing a three-piece formboard, the scaled scores provide an objective index of the relative difficulty of these two tasks and of the child’s level of cognitive development along each particular cognitive domain. Appendix A shows the items remaining in each of the scales, their relative position and item scale score in ascending order of difficulty, as well as the approximate developmental age attributed to the task as indicated in the developmental assessment battery of origin. RESULTS Interrater Agreement. The Kappa statistic was used to analyze responses on the reduced battery to determine the proportion of agreement (or interchangeability of raters' scores) between raters.30 Kappa scores ranged from .64 to .92 across the five scales (see Table 6). Z-scores were then calculated to test the hypothesis that the agreement is predicted by chance. Scores for all five domains were found to have significant agreement above chance. It has been suggested that Kappa scores of .75 and above represent excellent interrater agreement above chance, and scores between .40 and .75 represent fair to good agreement above chance.31 All domains had good to excellent inter-rater agreement.
. . . . . ** p < .01 Intrarater Consistency. In cases where raters make observations and score different children performing the same tasks over a long period of time, ratings can ‘drift’ and become more lenient or more stringent. The Kappa statistic was used to determine consistency in a single rater’s scores of the same event, rescored eight to twelve months after the original scoring via re-review of the videotapes. Kappa scores for drift ranged from .64 to .86 (see Table 7). Z-scores indicated that the consistency of ratings for all five cognitive domains was significantly above chance. The Kappas for problem solving and spatial relations fell into the category considered to be excellent agreement above chance, and the scores for cause/effect, object permanence and symbolic play fell in the fair to good consistency range.
. . . . . *p < .05 ** p < .01 Test/Retest Reliability. The consistency of children's performance across time was determined by using the Kappa statistic. While the number of children was small (n=3), there was significant consistency across the two test administrations for two of the domains and marginally significant consistency in a third domain; although not significant, the remaining two domains had fairly high agreement across the two test administrations. Table 8 shows the Kappa scores for test-retest reliability.
. . . . . ^ p < .10 ** p < .01 DISCUSSION Analysis of the items in the cognitive developmental assessment battery indicates that a hierarchy of items exists that adequately differentiates developmental level and provides separate cognitive domain scores along the five cognitive domains in young children with severe physical disabilities. The final battery consists of 35 items that can be modified in administration and/or materials to accommodate a wide range of physical limitations. Children with severe limitations in reach, grasp, upper body strength and range of motion were able to attempt the tasks in the current battery. The revised battery takes approximately 30 to 45 minutes to administer and with the diversity of tasks presented, is well within the patience and attention span of children between the ages of 18 and 36 months. The revised battery demonstrated high internal consistency among items, as was evidenced by the scores on the Rasch analysis. In addition, there was good agreement on all five scales, both across raters and within a single rater across time. Test-retest reliability was significant for three domains, however, the problem-solving and spatial relations scales did not show significant agreement upon re-administration. There are several possible explanations for this. One possibility is that children ‘learned’ the tasks from the first trial to the second, and thus performed differently on these scales. However, in review of the data, this only occurred for two items in the spatial relations scale and none on the problem solving scale. A second explanation is that there was an actual developmental difference that occurred in these domains over the two week interval between testing. During this short time period however, any developmental changes that might have occurred were not likely to be significant. The most likely explanation is that the difference can be attributed to the small number of subjects who were re-tested (due to time and financial constraints). The latter is most likely the case since there was 88% consistency in performance (21 of 24 items) on the spatial relations scale and 91% consistency (19 of 21 items) on the problem-solving scale between time one and time two. As clinicians often observe, it is not unusual for a child to demonstrate different developmental ages across various cognitive scales. Nor is it unusual for children of the same chronological age to demonstrate dissimilar developmental abilities. Assessing individual cognitive skills in very young children with disabilities allows therapists to use this information to assist in clinical decision-making. It also allows clinicians and parents to target skills that may be lacking and develop a program of intervention through appropriate developmental play activities. For example, in the current assessment battery, for a child who is delayed in object permanence skills, repeated hiding and revealing of objects behind towels or under other toys may be of benefit. One method that can facilitate the development of object permanence is to hide a wind-up toy that continues to make noise while out of sight. This capitalizes on the sense of sound to help the child learn that the object still exists though out of sight. For a child who is having difficulty with cause/effect, the use of toys or objects in the home that produce tangible, interesting effects (e.g., a water pistol that squirts water, a flashlight, a doorbell) can help reinforce this concept. Parents and clinicians can demonstrate the use of an object then then verbally tell child what to do to activate it. If a child performs poorly in problem-solving skills, clinicians and parents can provide opportunities for problem-solving during daily routines. The child may be allowed to attempt activities such as eating or dressing independently. If the child gets ‘stuck,’ she should be given an opportunity to solve the problem independently before assistance is offered. Verbal or gestural cues, or even demonstration, can be used to avert frustration, but it is important to allow and encourage the child to attempt the task in as many ways as possible. Similar interventions can be used for a child who performs poorly in other domains such as spatial relations or symbolic play. Describing how things fit together or into one another during daily activities can help develop spatial awareness. When cooking, parents can describe how lids fit on pots or how toast fits in the toaster, or while bathing, how the plug fits into the drain or a peg man in a bath toy. During therapy or play, the child can be encouraged to put objects into containers designed for their fit, such as crayons into the box, toy milk bottles in a carrier or soap in a soap dish. To foster play skills, the child can be set up with a toy or activity similar to one the parent is doing while nearby (e.g., if adult is on telephone, the child can be given a play phone to mimic adult). The clinician or parent can also ‘model’ various play behaviors such as asking a doll if she wants to eat and then responding for the doll. Play activities can be initiated and demonstrated by an adult and then the child can be encouraged to continue to play alone. Different cognitive scores across skill domains may offer some explanation as to why children who receive the same global developmental age score on commonly used developmental tests may demonstrate widely different abilities to perform certain tasks (e.g., operating a powered wheelchair functionally). An example of this was observed in the current research. Two children of approximately the same chronological age and overall developmental age were observed to have identical scores in cause/effect, object permanence, and symbolic play, and approximately the same developmental score in spatial relations. However, one of these children scored significantly higher in the problem-solving area (42 months as compared to 20 months). When evaluated on the powered mobility test, this child performed significantly better. While other factors may have also contributed to this, knowledge of developmental levels in relevant cognitive skills can assist in clinical decision-making and in the preparation of appropriate intervention strategies. Establishing an assessment battery for use with children with physical disabilities may be useful for other populations such as children with physical limitations who also have cognitive developmental delays, since studies have indicated that cognitive development occurs in the same sequence but at a different rate for this population.19 However, it is important to note that different types of responses may be required of children with severe physical, cognitive and/or sensory-motor limitations (e.g., ‘yes/no’ responses, eye gaze responses), which may alter the nature of the assessment. Since the number of children evaluated in the present study was small, the results must be viewed as preliminary. Further research is needed to determine if these domains remain predictive and are valid and appropriate for use in other populations. A multi-site follow-up study is underway to validate the current assessment battery. In addition, a modified version of the battery is also being tested with children with cognitive and/or sensory-motor integration problems (e.g., children with cerebral palsy) to determine its utility in this group. ACKNOWLEDGMENTS Funding for research was provided by the National Institute on Disability and Rehabilitation Research (NIDRR), U.S. Department of Education, Grant No. H133E00015. Opinions expressed in this paper are those of the authors and should not be construed to represent opinions or policies of NIDRR. REFERENCES 1. Psychological Corporation. Bayley Scales of Infant Development - II. San Antonio, TX: Harcourt, Brace & Company; 1993. 2. Newborg J, Stock J, Wnek L. Battelle Developmental Inventory. Allan, TX: DLM Teaching Resources; 1984. 3. Fewell R, Langley B. Developmental Activities Screening Inventory - II. Austin, TX: Pro-Ed; 1984. 4. Johnson-Martin N, Jens KG, Attermeier SM. Carolina Curriculum for Handicapped Infants and Infants at Risk. Baltimore, MD: Paul H. 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J Early Interven, 1992;16:87-95. 27. Haley SM, Ludlow LH, Coster WJ. Pediatric evaluation of disability inventory: Clinical interpretation of summary scores using Rasch rating scale methodology. In: Granger CV, Gresham GE, eds, Physical Medicine and Rehabilitation Clinics of North America: New Developments in Functional Assessment. Philadelphia, PA: WB Saunders Company; 1993:529-540. 28. Msall ME, DiGaudio KM, Duffy LC. Use of functional assessment in children with developmental disabilities. In: CV Granger, GE Gresham, eds, Physical Medicine and Rehabilitation Clinics of North America: New Developments in Functional Assessment. Philadelphia, PA: W.B. Saunders Company; 1993:517-528. 29. Wright BD, Linacre JM. BIGSTEPS: A Rasch-Model Computer Program. Chicago, IL: Mesa Press; 1991. 30. Fleiss JL. Statistical methods for rates and proportions (2nd Ed). New York: John Wiley & Sons; 1981. 31. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics, 1977;33:159-174. APPENDIX A-- Items remaining after Rasch Analysis
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