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Research Article: Functional Assessment

Functional Assessment and Care of Children with Neurodevelopmental Disabilities

Ottenbacher, Kenneth J., PhD; Msall, Michael E., MD; Lyon, Nancy, RN, PNP; Duffy, Linda C., PhD; Ziviani, Jenny, PhD; Granger, Carl V., MD; Braun, Susan, MLS, OTR

Author Information
American Journal of Physical Medicine & Rehabilitation: March-April 2000 - Volume 79 - Issue 2 - p 114-123
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Abstract

Functional assessment in children is defined by McCabe and Granger1 as "an effort to systematically describe and measure a child's abilities and limitations when performing the activities of daily living" (p. 121). Several authors have discussed the advantages of functional assessment over testing developmental status in children with chronic developmental disabilities.2-4 Two widely used pediatric functional assessments are the Functional Independence Measure for Children (WeeFIM™)5 and the Pediatric Evaluation of Disability Inventory.6 Each instrument measures functional abilities, considering the use of special equipment and amount of caregiver assistance. The Pediatric Evaluation of Disability Inventory includes 197 items evaluating the following three domains: self-care, mobility, and social functions; and it requires approximately 1 hr to administer. The WeeFIM™ instrument includes 18 items and can be administered in 15 min or less. Both assessments examine levels of functional independence; however, the WeeFIM instrument is more appropriate as a frontline assessment because of its ease in administration and brevity. The Pediatric Evaluation of Disability Inventory provides comprehensive information regarding the child's functional abilities but is more complex to administer and score. The current investigation focuses on the Wee™ instrument and its relationship to other commonly used assessments of developmental status in children.

The ultimate goal of the WeeFIM instrument is to "measure changes in function over time to weigh the burden of care in terms of physical, technologic, and financial resources" (p. 41).7 Recent reports on the reliability and validity of the WeeFIM instrument indicate that the assessment has excellent consistency across raters and provides scores that are stable over time.8, 9 Good equivalence reliability has also been demonstrated between WeeFIM ratings obtained from direct observation and from reports by parents and teachers.10, 11

One objective of this investigation was to compare parent and teacher ratings of amount of assistance required to complete activities of daily living (ADL) with scores from three commonly used pediatric assessments, i.e., the Battelle Developmental Screening Inventory (BDSIT),12 the Vineland Adaptive Behavior Scales (VABS),13 and the WeeFIM.5 We were specifically interested in the ability of these commonly used assessments to predict "burden of care" as determined by the amount of assistance required for children with disabilities to complete routine ADL. A second objective was to examine the relationship among total scores and subscale ratings on the three pediatric assessment instruments in a sample of children with developmental disabilities.

METHODS

Subjects

A total of 205 children with developmental disabilities, who ranged in age from 11 to 87 mo, participated in the investigation. All children had a confirmed medical diagnosis and were receiving treatment and/or developmental child support services in early intervention or school-based programs.

The sample was recruited from three early childhood education programs and developmental disabilities/rehabilitation facilities in Western New York. All three facilities included educational day programs designed specifically for children with disabilities. Many of the children were mainstreamed into day programs that included children without disabilities. All children included in the sample received occupational, speech, or physical therapy as part of their Individualized Educational Programs or Individualized Family Service Plans. A proportional sampling plan was used to ensure that children were evenly distributed based on severity, type of disability, and age. The most common medical impairments were cerebral palsy, prematurity, Down syndrome, spina bifida, epilepsy, and genetic disorders. Severity of disability was based on scores from standardized developmental assessments including the Bayley Scales of Mental and Motor Development,14 the Clinical Adaptive Test/Clinical Linguistic Auditory Milestone Scale15, 16 and the McCarthy Scales.17 The children were tested with the appropriate instrument, based on medical condition, by licensed professionals at their initial entry into the healthcare service delivery system. Scores on these assessments were available in the children's healthcare and/or educational records. Information on socioeconomic status was collected based on demographic factors including educational level, occupation of parents, availability of transportation, use of paid outside help in the home, and presence of a telephone.

Consent. The study protocol was reviewed and approved by the appropriate institutional review boards. All parents and teachers participating in the investigation granted written informed consent before providing information about the children in their care.

Instruments

The children participating in the investigation were evaluated by using three commonly administered pediatric assessment instruments and a parental/teacher survey that examines the amount of assistance required to perform basic daily living tasks. Each of these instruments is described below.

Functional Independence Measure for Children. The WeeFIM instrument is a pediatric functional assessment derived from the items of the Functional Independence Measure (FIMM).5, 18-20 The WeeFIM instrument was developed to evaluate and track functional independence in children ages 6 mo to 7 yr, across health, developmental, educational, and community settings.18, 19 Key characteristics of the WeeFIM instrument are the use of a minimal data set, emphasis on consistent actual performance, and the ability to be used by multiple disciplines.5, 18, 19

The WeeFIM instrument contains 18 items divided into the following six areas: self-care, sphincter control, transfers, locomotion, communication, and social cognition. The motor subscale includes the areas of self-care, sphincter control, transfer, and locomotion and contains 13 items. The remaining two areas (communication and social cognition) comprise the cognitive subscale. A seven-level ordinal rating system ranging from 7 (complete independence) to 1 (total assistance) is used to rate the WeeFIM instrument. A rating from 1 to 4 indicates that the child requires some level of assistance from another person to complete the activity. A rating of 5 means the child requires supervision or adult cues to set up the task. A rating of 6 means that the child can complete the activity independently but may require an assistive device, more than a reasonable amount of time, or safety is a concern. Figure 1 presents the WeeFIM items and rating protocol.

Figure 1
Figure 1:
Sample WeeFIM™ Instrument Rating Form. Adapted from the Functional Independence Measure for Children (WeeFIM).5

The WeeFIM instrument can be administered either through direct observation, interview, or a combination of observation and interview. Each item must be rated. No zeros or nonapplicable ratings can be given. The minimum possible total rating is 18 (total dependence in all skills), and the maximum possible is 126 (complete independence in all skills). The WeeFIM instrument is designed to be used by a variety of professionals. Training is recommended to ensure appropriate administration and rating (see below). Validity and interrater reliability have been examined in various studies and found to be excellent.8-11

Battelle Developmental Inventory Screening Test. The original Battelle Developmental Inventory (BDI) assesses the following five domains of child development: personal-social, adaptive, motor, communication, and cognition.12 Although the BDI has a developmental framework, it samples functional content such as dressing, toileting, and mobility. In contrast to the WeeFIM instrument, the BDI examines the child's skill level and does not include a scale that considers adaptive equipment or physical assistance.

The BDI results in a total score as well as scores in each of the developmental areas. The test profile provides the following several different types of information: percentile ranks, age equivalents, z scores, developmental quotients, T scores, and normal curve equivalents. The BDI is designed to assess the development of children from birth to 8 yr of age. Information can be obtained through interviews with caregivers, observation, or structured assessment. Sexton et al.21 found that the data collected through interviews do not compromise the validity of the total score. Also, the BDI provides specific adaptations for children with visual, hearing, and/or motor disabilities.

The BDI includes a large item pool (341 test items) and requires 2 hr to complete. A modified version, the Battelle Developmental Inventory Screening Test (BDIST) has been developed as a short version of the BDI.22 The BDIST consists of 96 items and can be administered in approximately 30 to 35 min. Feldman et al.23 report that the BDIST is a strong predictor of performance on the BDI. The BDIST was used in this study.

The reliability and validity of the BDI and BDIST have been examined by several investigators12, 22, 23 and reported to be adequate, with interrater and test-retest reliability ranging from r = 0.71 to r = 0.99. Content validity (r = 0.70-0.90) and concurrent validity have also been established (r = 0.75-0.93).23

Vineland Adaptive Behavior Scales. The VABS is designed to assess personal and social sufficiency of individuals with and without disabilities from birth to adulthood.13 The VABS is administered by a semistructured interview with a caregiver or person who knows the client well. The VABS measures adaptive behavior in four domains, i.e., communication, daily living skills, socialization, and motor skills. An optionally administered domain of maladaptive behavior can be included. The VABS is designed to be administered by professionals with graduate degrees and specific experience and training both in assessment of individuals and in test interpretation. A background in human development and in test construction and measurement, plus experience with developmental disabilities, is expected for proficient administration of the VABS.13

The standard version of the VABS consists of 301 items and requires 45 to 60 min to administer. The scoring options include the following: 0 = the activity is never performed; 1 = the activity is sometimes performed, or performed with partial success; 2 = the activity is usually or habitually performed; n = no opportunity to perform the activity; and DK = do not know (the interview respondent has no knowledge of the client's performance). Administration of the standard VABS results in a series of derived scores (converted raw scores that have uniform meaning from domain to domain and for all ages). The derived scores are based on a national standardization sample and performance of supplementary norm groups.13 Derived scores obtained for each of the four adaptive behavior domains include standard scores, bands of error, national percentile ranks, and stanines and age equivalents.13

The following three forms of reliability have been reported for the VABS: internal consistency (split-half reliability), test-retest reliability, and interrater reliability.13, 22, 24 Internal consistency for the four domains ranged from 0.76 to 0.99.22, 24 Testretest reliability for the four domains ranges from 0.76 to 0.93. The range of interrater reliability values for the VABS is reported as 0.62 to 0.78.24, 25 With the exception of a moderate interrater reliability correlation of 0.62 for the domain of socialization, the overall reliability of the VABS is considered very good.25

The construct validity of the Vineland has been examined by investigating the profiles of persons with and without identified disabilities.23-26 Factor analytic studies have also been conducted to examine construct validity.25 Concurrent validity studies have been conducted by using intelligence and achievement tests. High correlations have been found between these tests and the domain of communication on the VABS.26

Amount of Assistance Questionnaire. Information on the amount of assistance required by a child to complete standard daily living tasks was obtained from the parents and teachers by using the Amount of Assistance Questionnaire (AAQ). The AAQ was developed by Msall,27 and a copy of the complete instrument may be obtained from the second author. The AAQ includes three sections and takes approximately 15 min to complete. The first section contains 15 questions that ask the respondent (parent or teacher) to rate the child's performance on motor, language, self-care, play, and social/emotional function compared with other children his or her age. The directions for this section ask "compared to other children your child's age, how would you describe your child's development in the following areas?" (for example, gross motor, i.e., walking, stair climbing, and running). Each item is rated on a 5-point scale with 1 = significantly behind other children, and 5 = considerably ahead of other children. The second section of the AAQ requests information on services the child is receiving, e.g., speech/language, physical therapy, or occupational therapy. Information requested includes time in therapy, frequency of therapy visits, perceived advancement in therapy, and developmental progress. The final section of the questionnaire contains seven questions directly related to amount of assistance for the following areas: eating, dressing, toileting, and locomotion. Three questions ask the respondent to compare the child's performance time with other children his/her age. The directions ask, "compared to other children your child's age, how much time does your child take to complete the following activities?" The items rated are eating, dressing, and toileting. The items are rated on a 5-point scale with 1 = considerably less time than average, and 5 = considerably more time than average. The next four questions ask the respondent (parent or teacher) "how much assistance does your child need in completing the following activities?" This question is also rated on a 5-point scale with 1 = none (0% assistance) and 5 = total assistance (100%). The items rated include eating, dressing, toileting, and locomotion.

Procedure

Parents were initially interviewed by a trained rater in the facility where the child received intervention or follow-along services. The purpose of the study was explained and each parent provided with an information sheet. In cases where neither parent was available, the assessment was administered to a caregiver designated by the parent as familiar with the child's functional abilities. In all cases where the parent was not available, the interview was completed with the child's teacher.

The assessments were administered according to the established protocol for each instrument. The WeeFIM instrument was administered to all 205 children by using parental or teacher report. The BDIST12,22 was administered to 101 children and the VABS13 to 104 children. Whether a specific child was assessed by using the BDIST or the VABS was determined by a random process (coin flip). The order of the administration was alternated so that approximately one-half the children were administered the WeeFIM instrument first. The two assessments were not administered the same day to avoid fatigue and rater bias. The AAQ27 was completed by the parent or teacher during the first testing session.

Interviewers were blind to the child's health status and previous scores on developmental tests before the initial assessment. The date and time of all assessments were recorded and every effort was made to schedule the second assessment on the same day of the week and at approximately the same time as the initial assessment. The same person (parent or teacher) interviewed initially was also interviewed during the second assessment. The protocol for administering the WeeFIM instrument, BDIST, and VABS was part of a larger investigation of the validity and reliability of the WeeFIM instrument and this is the reason all three instruments were not administered to all 205 children. The results of the reliability and validity analysis are available in other sources.8, 9

Interviewers. The primary interviewer who collected most of the WeeFIM data and all the BDIST and AAQ data from the parents or teachers for the 205 children was a pediatric nurse practitioner with more than 20 years experience in developmental disabilities and rehabilitation. Other interviewers who collected WeeFIM information were health, developmental, or rehabilitation professionals with at least 3 years of experience working with children with disabilities and their families. Each interviewer completed training in the administration of the WeeFIM instrument that included review of the administration and scoring protocol and viewing a 25-min videotape.28 Successful completion of the training required 90% agreement with case-study material. If the 90% criterion on the first assessment was not achieved after training, the protocol was repeated. Each interviewer recorded a minimum of two "pilot" WeeFIM assessments to establish the interview format.

Data Analysis

Descriptive statistics for the subscale and total scores for the WeeFIM instrument, BDIST, VABS, and AAQ were computed. The interrater reliability of the AAQ was examined by using intraclass correlation statistics. The Spearman correlation coefficient (ρ) was used to examine the covariance of ratings among the instruments. A regression equation was developed to determine which test scores and demographic variables were the best predictors of amount of assistance required to complete basic daily living tasks.

RESULTS

Demographic Characteristics

Most children in the sample were white (70%), with 21% African American, 6% Hispanic, and 3% other. A total of 133 were male and 72 were female. No predetermined method for division of male and female subjects was used, because previous published research on the WeeFIM instrument does not indicate significant performance differences between male and female children.18, 19 The final sample involved 71 children from 11 to 36 mo of age, 81 children from 37 to 60 mo, and 53 children from 61 to 87 mo.

As noted previously, severity of disability was determined based on scores obtained by the children on standardized instruments when they initially entered the healthcare delivery system. Sixty-eight children (33%) had original standardized scores on the Bayley Scales, the Clinical Adaptive Test/Clinical Linguistic Auditory Milestone Scale, or the McCarthy Scales between −1.0 and −2.0 SD below the mean (mild disability). A total of 104 children (51%) had standardized developmental scores between −2.1 and −3.0 SD (moderate disability), and 33 children (16%) had standardized scores greater than −3.0 SD below the mean (severe disability). Additional demographic information for the sample is included in Table 1.

TABLE 1
TABLE 1:
Demographic information for sample of children with developmental disabilities (n = 205)

Reliability and Validity

The AAQ has been used in previous investigations,27, 29 but the psychometric properties have not been examined comprehensively. For this reason, the test-retest reliability of the AAQ was examined for 30 children with disabilities. The sample of children for the reliability study ranged from 12 to 82 mo (mean = 45.12 mo; SD = 13.23 mo) and included 18 males and 12 females. These 30 children were not part of the larger sample of 205 children administered the WeeFIM instrument and other assessments. There were no statistically significant differences between the reliability sample (n = 30) and the larger sample (n = 205) on any demographic variables.

The AAQ was administered as a face-to-face interview with the parents (n = 19) or teachers (n = 11) of the children twice over a period of 10 days by an occupational therapist with 20 yr of experience in developmental disabilities. The questionnaire responses were collected and placed in sealed envelopes after each administration. The questionnaire ratings were not summed until all data had been collected. The reliability data were analyzed by using an intraclass correlation approach (model 3,1) and revealed intraclass correlation values ranging from 0.82 to 0.97 for individual items. There were no statistically significant differences in total amount of assistance ratings provided by teachers vs. parents (t = 0.67; p = not significant).

The validity of the AAQ was examined by comparing ratings for the questionnaire to levels of severity in the 205 children. A total score is not derived from the AAQ. Rather, a pattern of performance across items in the three sections is used to identify areas in which the child is not performing at the same level as his or her peers or requires more than the usual amount of time or assistance to complete basic ADL tasks. For this investigation, the focus was on amount of assistance required to perform basic ADL tasks (burden of care); thus, data from the final section of the AAQ were of primary interest. A rating for this section of the questionnaire was obtained by summing four questions from the AAQ. The questions asked the caregiver to rate (on a five-point scale; see above) the amount of assistance required to perform four basic ADL skills, i.e., dressing, eating, toileting, and locomotion. The combined ratings for the questions ranged from 4 (no assistance needed) to 20 (total or 100% assistance required for all four tasks). The AAQ score was compared with the levels of severity and the results are presented in Figure 2. One-way analysis of variance with least squares difference post hoc tests revealed that there was a statistically significant (p < 0.05) difference between the amount of assistance required for each level of severity.

Figure 2
Figure 2:
Amount of Assistance Questionnaire (AAQ) combined item ratings across three levels of severity in a sample of children with developmental disabilities.

As expected, those children with the most severe disabilities (>3.0 SD) required the most assistance. The correlation between amount of assistance (AAQ) and severity of disability was statistically significant (ρ = 0.57; p < 0.005). The combined AAQ rating, based on the four areas of eating, dressing, toileting, and locomotion, was used in all subsequent analyses.

The correlation between AAQ ratings and socioeconomic status score was nonsignificant (ρ = 0.08). As expected, the correlation between AAQ and age was statistically significant (r = 0.47; p < 0.05) with younger children requiring more assistance. There was a statistically significant difference in AAQ ratings between females and males (F = 2.67; p < 0.05) with females rated as requiring more assistance than males. Severity of disability and age were examined as potential moderator variables interacting with gender. There was no statistically significant correlation between gender and severity of disability, or gender and age. The difference between AAQ ratings across ethnic groups was not statistically significant (F = 2.56; p = 0.06). African-American children, however, were rated as requiring less assistance (mean = 9.78) than white (mean = 11.86) or Hispanic (mean = 11.75) children.

Table 2 includes correlation coefficients for the BDIST, VABS, WeeFIM, and AAQ items described above. Inspection of Table 2 indicates that the total AAQ variable was most highly correlated with the total WeeFIM rating (r = 0.91) but was also significantly correlated with a number of other subscale scores from all three instruments. In general, the correlations with amount of assistance items were lower for the VABS than for either the WeeFIM instrument or the BDIST. The lowest correlations for subscale scores and amount of assistance ratings were found for the cognitive and communication scores in all three pediatric assessments. In contrast, the highest correlations were associated with the self-care, motor, and/or locomotion subscales.

TABLE 2
TABLE 2:
Correlation coefficients showing association among Amount of Assistance Questionnaire (AAQ) items and scores on the WeeFIM™ instrument,Battelle Developmental Inventory Screening Test (BDIST), and Vineland Adaptive Behavior Scales (VABS)

The correlations among the three pediatric assessments were quite high for total scores. The correlation (r) between total WeeFIM ratings and BDIST total score was 0.92, and for the WeeFIM rating and VABS total score, the correlation (r) was 0.89. A correlation between the BDIST and VABS was not available, because these two instruments were not administered to the same children.

To further examine the AAQ ratings, two multiple regression analyses were conducted. One regression equation was completed for the 101 children who were tested by using the WeeFIM and the BDIST. A second regression equation was developed by using data from the 104 children who were administered the WeeFIM instrument and the VABS. The predictor variables entered into the regression equations included child's age, severity of disability, socioeconomic status, gender, race, total WeeFIM rating, and either total BDIST raw score (n = 101) or VABS composite score (n = 104). For the VABS regression, the composite score used in the analysis did not include the maladaptive behavior subscale score. The maladaptive behavior subscale score was poorly correlated with other VABS items. This subscale is optional and, when added to the VABS composite score, it substantially lowered the correlation with total AAQ ratings (Table 2).

A backward stepwise regression with replacement was conducted by using Systat (version 7.0, SPSS, Chicago, IL). An alpha level of 0.05 was set for entrance into the regression equation. The regression equations revealed that the WeeFIM total rating was the single best predictor followed by severity of disability. These were the only two predictor variables reaching the 0.05 alpha level in both regression equations. In the equation including the BDIST data (n = 101), the total WeeFIM ratings and severity of disability category comprised 88% of the variance in AAQ ratings (r = 0.94). In the second regression equation that used VABS data (n = 104), the total WeeFIM ratings and severity of disability were again the only statistically significant predictor variables, comprising 83% of the variance in total AAQ ratings (r = 0.91).

DISCUSSION

Correlations between total subscale and total scores for the three pediatric assessments were generally strong, which indicated a degree of consistency across the three measures. The WeeFIM instrument total ratings and severity of disability were found to be the best predictors of amount of assistance as rated by parents or teachers. The combination of WeeFIM total rating and severity of disability (mild, moderate, or severe) comprised 88% of the variance in total amount of assistance ratings in the sample of children who completed the WeeFIM instrument and the BDIST (n = 101). In the sample of children tested with the WeeFIM instrument and the VABS (n = 104), the WeeFIM total rating and severity of disability explained 83% of the variance in total AAQ ratings. The strongest bivariate correlation was between total AAQ scores and total WeeFIM ratings (r = 0.91). All six of the WeeFIM subscale ratings (self-care, sphincter control, transfers, locomotion, communication, and social cognition) and all the BDIST subscale scores displayed statistically significant correlations with AAQ total scores (p < 0.001). In contrast, only two of the correlation coefficients for subscale scores of the VABS were greater than 0.70.

Examination of resource consumption associated with severity of disability is an important topic and considerable research is being published in various areas of adult rehabilitation related to this issue.30-33 The current study is an initial attempt to begin linking clinical assessment based on functional abilities to resource consumption in children. Resources as defined in this investigation are equated to amount of assistance provided by an adult to help a child achieve a specific daily living task. Severity of disability and WeeFIM instrument total ratings were the two variables found to share significant variance with AAQ ratings. Severity of disability was operationalized as scores that were more than 1 SD below the mean (mild disability), more than 2 SD below the mean (moderate disability), or greater than 3 SD below the mean (severe disability) on standardized developmental assessments administered when the child began receiving special healthcare services. The instruments included the Bayley Scales,14 the Clinical Adaptive Test/Clinical Linguistic Auditory Mile-stone Scale,16 and/or the McCarthy Scales,17 and provided a broad indication of severity of disability with a strong cognitive component. In future research, it will be important to examine severity of disability more carefully and to determine if the relationship between severity of disability and AAQ ratings is influenced by diagnostic grouping or medical condition. For instance, is the relationship between severity of disability and AAQ rating different for children with primary motor impairments (cerebral palsy) vs. those with communication or cognitive impairments? Both diagnostic groups might have a classification of severe disability (i.e., >3 SD), but the functional implications for ADL would be different for the two groups. The small number of children classified as having severe disability (n = 33) and the presence of co-morbidities in the current sample prevented a detailed examination of this topic.

Many questions remain to be resolved regarding the issue of assistance required for managing daily living tasks and resource consumption in children with chronic disabilities. Additional research is needed to confirm the reliability and validity of the AAQ or to develop new methods of determining assistance required and resources used by children with developmental disabilities. An algorithm is needed to equate amount of assistance necessary to complete specific daily living tasks in terms of time required and cost incurred. A replication of this study, using other methods of resource consumption, such as minutes per day of help to complete specific tasks or costs for assistive devices, would be useful. Additional research is also needed in areas beyond basic self-care to determine resource implications in the broader context of childhood disability. For example, Squires et al.34 recently addressed practical issues involved in selecting developmental screening and assessment instruments. Aylward35 also discussed the process of selecting developmental screening and assessment instruments and their relevance to clinical or educational practice. He emphasized the importance of understanding conceptual distinctions among instruments and proposed an evaluation matrix that includes the following variables: results of the assessment, environment, the area of function assessed, age of the child, and medical history. An important variable not included in the evaluation matrix proposed by Aylward35 is resource consumption.

The ability to relate assessment results to resource use is an important consideration in the evaluation of adults with chronic disabilities and is emerging as an issue in pediatric assessment and rehabilitation.32, 33, 36 The WeeFIM instrument is easy to use, can be administered in a short period of time by a variety of professionals, and has demonstrated an initial relationship with perceived amount of assistance required to complete basic daily living tasks as rated by parents and teachers. If this relationship is confirmed, it will help establish the WeeFIM instrument as useful to assess functional independence in children with disabilities and to identify support required by their families and caregivers.

REFERENCES

1. McCabe M, Granger C: Content validity of a pediatric functional independence measure. Appl Nurs Res 1990;3:120-2
2. Dunn W: Measurement of function: actions for the future. Am J Occup Ther 1993;47:357-9
3. Haley S, Hallenborg S, Gans B: Functional assessment in young children with neurological impairments. Top Early Child Spec Educ 1989;9:106-26
4. Coster WJ, Haley SM: Conceptualization and measurement of disablement in infants and young children. Infant Young Child 1992;4:11-22
5. Guide for the Uniform Data Set for Medical Rehabilitation for Children (WeeFIM), Version 4.0-Community/Outpatient. Buffalo, NY 14214, State University of New York at Buffalo, 1993.
6. Haley SM, Coster WJ, Ludlow LH, et al: Pediatric Evaluation of Disability Inventory (PEDI), Version 1.0. Boston, New England Medical Center Hospitals, 1992
7. Braun S, Granger CV: A practical approach to functional assessment in pediatrics. Occup Ther Pract 1991;2:46-51
8. Ottenbacher KJ, Taylor ET, Msall, ME, et al: The stability and equivalence reliability of the Functional Independence Measure for Children (WeeFIM). Dev Med Child Neurol 1996;38:907-16
9. Ottenbacher KJ, Msall ME, Lyon NR, et al: Interrater agreement and stability of the Functional Independence Measure for Children (WeeFIM): use in children with developmental disabilities. Arch Phys Med Rehabil 1997;78:1309-25
10. Sperle PA, Ottenbacher KJ, Braun S, et al: Equivalency reliability of the Functional Independence Measure for Children (WeeFIM) administration methods. Am J Occup Ther 1997;51:35-41
11. DiScala C, Grant CC, Brooke MM, et al: Functional outcome in children with traumatic brain injury: agreement between clinical judgement and the functional independence measure. Am J Phys Med Rehabil 1992;71:145-8
12. Newborg J, Stock K, Wnek L, et al: Battelle Developmental Inventory. Allen, DLM Teaching Resources, 1984
13. Sparrow S, Balla D, Cicchetti D: Vineland Adaptive Behavior Scales Interview Edition: Survey Form Manual. Circle Pines, American Guidance Service, 1984
14. Bayley N: Bayley Scales of Infant Development, ed 2. San Antonio, The Psychological Corporation, 1994
15. Hoon AH, Pulsifier MB, Goplan R, et al: Clinical Adaptive Test/Clinical Linguistic Auditory Milestone Scales in early cognitive assessment. J Pediatr 1993;113:S1-8
16. Rossman MJ, Hyman SL, Rorabaugh ML, et al: The CAT/CLAMS assessment for early intervention services. Clin Pediatr 1994;33:404-9
17. McCarthy DA: Manual for the McCarthy Scales of Children Abilities. New York, Psychological Corp., 1972
18. Msall ME, DiGaudio K, Duffy LC, et al: WeeFIM: normative sample of an instrument for tracking functional independence in children. Clin Pediatr 1994;33:431-8
19. Msall ME, DiGaudio K, Rogers BT, et al: The Functional Independence Measure for Children (WeeFIM): conceptual basis and pilot use in children with developmental disabilities. Clin Pediatr 1994;33:421-30
20. Guide for the Uniform Data Set for Medical Rehabilitation (Adult FIM), Version 4.0. Buffalo, NY 14214, State University of New York at Buffalo, 1993
21. Sexton D, McLean M, Boyd R, et al: Criterion-related validity of a new standardized developmental measure for use with infants who are handicapped. Meas Eval Couns Dev 1988:21:6-24
22. Glascoe FP, Byrne KE: The usefulness of the Battelle Developmental Inventory Screening Test. Clin Pediatr 1993;32:273-80
23. Feldman AB, Hayley SM, Coryell J: Concurrent and construct validity of the pediatric evaluation of disability inventory. Phys Ther 1990;70:602-10
24. Rosenbaum P, Saigal S, Szatmari P, et al: Vineland Adaptive Behavior Scales as a summary of functional outcome of extremely low-birthweight children. Dev Med Child Neurol 1995;37:577-86
25. Vig S, Jedrysek E: Adaptive behavior of young urban children with developmental disabilities. Ment Retard 1995;33:90-8
26. Raggio DJ, Massingale TW, Bass JD: Comparison of Vineland Adaptive Behavior Scale-survey from age equivalent and standard scores with Bayley Mental Development Index. Percept Mot Skills 1994;79:203-6
27. Msall ME: Functional assessment in neurodevelopmental disabilities, in Capute AJ, Accardo PJ (eds) Developmental Disabilities in Infancy and Children, Vol 1, ed 2. Baltimore, Paul Brookes Publishing, 1996, pp 311-8
28. Msall ME, Braun S, Granger CV: Use of the Functional Independence Measure for Children (WeeFIM): an interdisciplinary training tape (abstract). Dev Med Child Neurol 1990;32(suppl):90
29. Msall ME, DiGaudio KM, Duffy LC: Use of functional assessment in children with developmental disabilities. Phys Med Rehabil Clin N Am 1993;4:517-27
30. Heinemann AW, Linacre JM, Wright BD, et al: Relationship between impairment and physical disability as measured by the Functional Independence Measure. Arch Phys Med Rehabil 1993;74:566-73
31. Granger CV, Hamilton BB, Linacre JM, et al: Performance profiles of the Functional Independence Measure. Am J Phys Med Rehabil 1993;72:84-9
32. Granger CV, Cotter AC, Hamilton BB, et al: Functional assessment scales: a study of persons with multiple sclerosis. Arch Phys Med Rehabil 1990;71:870-5
33. Granger CV, Cotter AC, Hamilton BB, et al: Functional assessment scales: a study of persons after stroke. Arch Phys Med Rehabil 1993;74:133-8
34. Squires J, Nickel RE, Eiser D: Early detection of developmental problems: strategies for monitoring young children in practice settings. J Dev Behav Pediatr 1996;17:420-7
35. Aylward GP: Conceptual issues in developmental screening and assessment. J Dev Behav Pediatr 1997;18:340-9
36. DeNise-Annunziata D, Scharf AA: Functional status as an important predictor of length of stay in a pediatric rehabilitation hospital. J Rehabil Outcome Meas 1998;2:12-21

Letters to the Editor

The American Journal of Physical Medicine & Rehabilitation welcomes letters to the Editor that objectively critique information appearing in the Journal. Letters should be limited to a maximum of 500 words (approximately two double-spaced pages). No unsigned letters will be accepted for publication. If a letter is accepted for publication, a copy will be sent to the principal author of the material being discussed, who will have an opportunity to submit a response for publication. All letters are subject to editing by the Editor.

Keywords:

Evaluation; Measurement; Functional Independence; Pediatric Measurement; Activities of Daily Living

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