Screening and Assessment Tools

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CHAPTER 7 Screening and Assessment Tools

7A. Measurement and Psychometric Considerations

GLEN P. AYLWARD, TERRY. STANCIN

In a general pediatric population, practitioners can expect 8% of their patients to experience significant developmental or behavioral problems between the ages of 24 and 72 months, this rate increasing to 12% to 25% during the first 18 years.1,2 Therefore, consideration and interpretation of tests and rating scales are part of the clinician’s day-to-day experience, regardless of whether the choice is made to administer evaluations or review test or rating scale data obtained by other professionals.

This chapter is an introduction to the section on assessment and tools. It contains topics such as: discussion of descriptive statistics (e.g., mean, median, mode), distributions of scores and standard deviations, transformation of scores (percentiles, z-scores, T-scores), psychometric concerns (sensitivity, specificity, positive and negative predictive values), test characteristics (reliability, validity), and age and grade equivalents. Many of these topics are also elaborated in greater detail in subsequent chapters of this text. A more thorough discussion of psychological assessment methods can be found in Sattler’s text.3

Developmental and psychological evaluations usually include measurement of a child’s development, behavior, cognitive abilities, or levels of achievement. Comprehensive child assessments involve a multistage process that incorporates planning, collecting data, evaluating results, formulating hypotheses, developing recommendations, and conducting follow-up evaluations.3 Test data provide samples of behavior, with scores representing measurements of inferred attributes or skills. These scores are relative and not absolute measures, and rating scales and test instruments are typically used to compare a child to a standardized, reference group of other children. Approximately 5% of the general population obtains scores that fall outside the range of “normal.” However, the range of normal is descriptive, not diagnostic: it describes problem-free individuals, but does not provide a diagnosis for them.3 No test is without error, and scores may fall outside the range of normal simply as a result of chance variation or issues such as refusal to take a test. Three major sources of variation that may affect test data include characteristics of a given test, the range of variation among normal children, and the range of variation among children who have compromised functioning.

Selection of which test to use depends on the referral questions posed, as well as time and cost constraints. Testing results vary in terms of levels of detail, complexity, and definitiveness of findings. The first level of testing is screening, the results of which are suggestive. The second level is administration of more formal tests designed to assess development, cognition, achievement, language, motor, adaptive, or similar functions, the results being indicative. The third tier involves administration of test batteries to assess various areas and abilities; these results are assumed to be definitive. This third tier typically includes a combination of formal tests or test batteries, history, interview, rating scales, and observations. The primary goal of more detailed testing is to delineate patterns of strengths and weaknesses so as to provide a diagnosis and guidance for intervention and placement purposes. Results gain meaning through comparison with norms. A caveat is that tests differ markedly in their degree of accuracy.

In general, regardless of whether a measurement tool is designed to be used as an assessment or a screening instrument, the normative sample on which the test is based is critical. Test norms that are to be applied nationally should be representative of the general population. Demographics must proportionately reflect characteristics of the population as a whole, taking into account factors such as region (e.g., West, Midwest, South, Northeast), ethnicity, socioeconomic status, and urban/rural setting. If a test is developed with a nonrepresentative population, characteristics of that specific sample may bias norms and preclude appropriate application to other populations. Adequate numbers of children need to be included at each age across the age span evaluated by a given test so as to enhance stability of test scores. Equal numbers of boys and girls should be included. Clinical groups should also be included for comparison purposes. Convenience samples, or those obtained from one geographic location are not appropriate for development of test norms.

Tests generally need to be reduced and refined by eliminating psychometrically poor items during the development phase. Conventional item analysis is one such approach and involves evaluation of an item difficulty statistic (percentage of correct responses) and patterns of responses. The use of item discrimination indexes (item-total correlations) and item validity (discrimination between normative and special groups, by T-tests or chi square analyses) is routine. More recent tests such as the Bayley Scales of Infant and Toddler Development—Third Edition (BSID-III)4 or the Stanford-Binet V5 employ inferential norming6 or item response theory.7 Item response theory analyses involve difficulty calibrations for dichotomous items and step differences for polychotomous items, the goal being a smooth progression of difficulty across each subtest (e.g., as in the Rasch probabilistic model8). Item bias and fairness analysis are also components; this procedure is called differential item functioning.9 See Roid5 or Bayley4 for a more detailed description of these procedures.

STANDARDIZED ASSESSMENTS

Standardized normreferenced assessments (SNRAs) are the tests most typically administered to infants, children, and adolescents. The most parsimonious definition of SNRAs is that they compare an individual child’s performance on a set of tasks presented in a specific manner with the performance of children in a reference group. This comparison is typically made on some standard metric or scale (e.g., scaled score).10 Although there may be some allowance for flexibility in rate and order of administration procedures (particularly in the case of infants), administration rules are precisely defined. The basis for comparison of scores is that tasks are presented in the same manner across testings, and there are existing data that represent how similar children have performed on these tasks. However, if this format is modified, additional variability is added, precluding accurate comparison of the child’s data and those of the normative group.

A major issue facing users of SNRAs is identification of the question to be answered from the results of testing. One of two contrasting questions is probably the reason for testing: (1) How does this child compare with his or her referent group? or (2) What are the limits of the child’s abilities, regardless of comparison to a referent group? SNRAs are suited to answer the first question. Examiners can subsequently test limits or alter procedures to clarify clinical issues such as strengths and weaknesses after the standard administration is completed. However, these data, although clinically useful, should not be incorporated into the determination of the test score because of the reasons cited previously. Also, no single SNRA in isolation can provide all the answers regarding a child’s development or cognitive status; rather, it is a component of the overall evaluation.

Use of SNRAs is not universally endorsed, particularly with regard to infant assessment, because of concerns regarding one-time testing in an unfamiliar environment, different objectives for testing, and linkage to intervention, instead of diagnosis. Therefore, emphasis is placed on alternative assessments that rely on criterion-referenced and curriculum-based approaches. In actuality, curriculum-based assessment is a type of a criterion-referenced tool. These assessments can help to answer the second question posed previously and could also better delineate the child’s strengths. Both provide an absolute criterion against which a child’s performance can be evaluated. In criterion-referenced tests, the score a child obtains on a measurement of a specific area of development reflects the proportion of skills the child has mastered in that particular area (e.g., colors, numbers, letters, shapes). For example, in the Bracken Basic Concepts Scale—Revised,11 in addition to normreferenced scores, examiners can also determine the percentage of mastery of skills in the six areas included in the School Readiness Composite. More specifically, in the colors subtest, the child is asked to point to colors named by the examiner. This raw score can be converted to a percentage of mastery, which is computed regardless of age. Similarly, other skills such as knowledge of numbers and counting or letters can be gauged. In curriculum-based evaluations, the emphasis is on specific objectives that are to be achieved, the potential goal being intervention planning.12,13 The Assessment, Evaluation, and Programming System for Infants and Children14 and the Carolina Curricula for Infants and Toddlers with Special Needs15 are examples of curriculum-based assessments. Therefore, SNRAs, criterion-referenced tests, and curriculum-based tests each have a role, depending on the intended purpose of the evaluation.

PRIMER OF TERMINOLOGY USED TO DETECT DYSFUNCTION

The normal range is a statistically defined range of developmental characteristics or test scores measured by a specific method. Figure 7A-1 depicts a normal distribution or bell-shaped curve. This concept is critical in the development of test norms and provides a basis for the following discussion.

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FIGURE 7A-1 The normal distribution.

Descriptive Statistics

The mean (M) is a measure of central tendency and is the average score in a distribution. Because it can be affected by variations caused by extreme scores, the mean can be misleading in scores obtained from a highly variable sample. In Figure 7A-1, the mean score is 100.

The mode, also a measure of central tendency, is the most frequent or common score in a distribution.

The median is defined as the middle score that divides a distribution in half when all the scores have been arranged in order of increasing magnitude. It is the point above and below which 50% of the scores fall. This measure is not affected by extreme scores and therefore is useful in a highly variable sample. In the case of an even number of data points in a distribution, the median is considered to be halfway between two middle scores. Noteworthy is the fact that in the normal distribution depicted in Figure 7A-1, the mean, mode, and median are equal (all scores = 100), and the distribution is unimodal.

The range is a measure of dispersion that reflects the difference between the lowest and highest scores in a distribution (highest score − the lowest score +1). However, the range does not provide information about data found between two extreme values in the test distribution, and it can be misleading when the clinician is dealing with skewed data. In this situation, the interquartile range may be more useful: The distribution of scores is divided into four equal parts, and the difference between the score that marks the 75th percentile (third quartile) and the score that marks the 25th percentile (first quartile) is the interquartile range.16

The standard deviation (SD) is a measure of variability that indicates the extent to which scores deviate from the mean. The standard deviation is the average of individual deviations from the mean in a specified distribution of test scores. The greater the standard deviation, the more variability is found in test scores. In Figure 7A-1, SD = 15 (the typical standard deviation in normreferenced tests). In a normal distribution, the scores of 68% of the children taking a test will fall between +1 and −1 standard deviation (square root of the variance). In general, most intelligence and developmental tests that employ deviation quotients have a mean of 100 and a standard deviation of 15. Scaled scores, such as those found in the Wechsler tests, have a mean of 10 and a standard deviation of 3 (7 to 13 being the average range). If a child’s score falls less than 2 standard deviations below average on an intelligence test (i.e., IQ < 70), he or she may be considered to have a cognitive-adaptive disability (if adaptive behaviors are also impaired).

Skewness refers to test scores that are not normally distributed. If, for example, an IQ test is administered to an indigent population, the likelihood that more children will score below average is increased. This is a positively skewed distribution (the tail of the distribution approaches high or positive scores, i.e. the right portion of the x-axis). Here, the mode is a lower score than the median, which, in turn is lower than the mean. Probabilities based on a normal distribution will yield an underestimate of the scores at the lower end and an overestimate of the scores at the higher end. Conversely, if the test is administered to children of high socioeconomic status, the distribution might be negatively skewed, which means that most children will do well (the tail of the distribution trails toward lower scores or the left portion of the x-axis). In negatively skewed distributions, the value of the median < mean < mode scores at the lower end will be overestimated, and those at the upper end will be underestimated. Skewness has significant ramifications in interpretation of test scores. In fact, the meaning of a score in a distribution depends on the mean, standard deviation, and the shape of the distribution.

Kurtosis reflects the shape of the distribution in terms of height or flatness. A flat distribution, in which more scores are found at the ends of the distribution and fewer in the middle, is platykurtic, in comparison with the normal distribution. Conversely, if the peak is higher than the normal distribution, scores do not spread out and instead are compressed and cluster around the mean. This is called a leptokurtic distribution.

Transformations of Raw Scores

LINEAR TRANSFORMATIONS

Linear transformations provide information regarding a child’s standing in comparison to group means. The z-score is a standard score (standardization being the process of converting each raw score in a distribution into a z-score: raw score − the mean of the distribution, divided by the standard deviation of the distribution) that corresponds to a standard deviation; that is, a z-score of +1 is 1 standard deviation above average and a z-score of −1 is 1 standard deviation below average. The mean equals a z-score of 0; therefore scores between z-scores of −1 and +1 are in the average range. Stated differently, if a child receives a z-score of +1, he or she obtained a score higher than those of 84% of the population (see Fig. 7A-1).

The T-score is another linear transformation and can be considered a z-score × 10 + 50. The mean T-score is 50, and the standard deviation is 10. Therefore a z-score of 1 equals a T-score of 60. T-scores are often found in psychopathology-related test instruments such as the Minnesota Multiphasic Personality Inventory—A, the Conners rating scales, or the Child Behavior Checklist, on which T-scores of 70 or greater are considered to be clinically relevant (approximately the 98th percentile); these cutoffs are depicted in many scoring forms.

AREA TRANSFORMATIONS

A percentile (the technical slang is “centile”) tells the practitioner how an individual child’s performance compares to a specified norm group. If a percentile score is 50, half of the children tested will score above this, and half will score below. A score that is 1 standard deviation below average is at approximately the 16th percentile; a score 1 standard deviation above average is at the 84th percentile. Clinicians must be aware that small differences in scores in the center of the distribution produce substantial differences in percentile ranks, whereas greater raw score differences in outliers do not have as much of an effect on percentile scores. Oftentimes, the third percentile is considered to be a clinical cutoff (e.g., in the case of the infant born small for gestational age). Deciles are bands of percentiles that are 10 percentile ranks in width (each decile contains 10% of the normative group). Quartiles are percentile bands that are 25 percentile ranks in width; each quartile contains 25% of the normative group. Percentiles require the fewest assumptions for accurate interpretation and can be applied to virtually any shape of distribution. This metric is most readily understood by parents and professionals and is recommended as the preferred way to describe how a child’s score compares within a group of scores. For example, a Wechsler Intelligence Scale for Children—Fourth Edition (WISC-IV) Full Scale IQ score of 70 indicates that fewer than 3% of children of a similar age score lower on that measure of intelligence; conversely, more than 97% of children taking the test have a higher score.

The stanine is short for standard nine, and this metric divides a distribution into nine parts. The mean = 5, and the SD = 2, with the third to seventh stanine being considered the average range. Approximately 20% of children score in the fifth stanine, 17% each in the fourth and sixth stanines, and 12% each in the third and seventh stanines (78% in total). Stanines are frequently encountered with group administered tests such as the Iowa Tests of Basic Skills, the Metropolitan Achievement Tests, or the Stanford Achievement Tests. The interrelatedness of these scores is depicted in Figure 7A-1.

PSYCHOMETRIC CONCERNS

Appropriate interpretation of test data necessitates consideration of other important test characteristics. As mentioned previously, when a child’s normreferenced test results are interpreted, the extent to which the child’s characteristics are represented in the normative sample from which scores were derived is a critical concern. Moreover, caution is recommended when test results for children from cultural and ethnic minorities drive academic or clinical decisions, unless there is adequate representation of this diversity in standardization samples and validation studies.

Sensitivity and Specificity

Frequently, interpretation of test results must take into account how well the instrument performs with set cutoff scores. Sensitivity is a measure of the proportion of children with a specific problem who are positively identified by a test, with a specific cutoff score. Children who have a disorder but are not identified by the test are considered to have false-negative scores. In developmental/behavioral pediatrics, the “gold standard” (criterion used to determine the presence of a given problem) often is not definitive but rather is a reference standard. Comparison with an imperfect “gold standard” may lead to erroneous conclusions that a screening test is inaccurate. As a result, sensitivity may be better conceptualized as copositivity. Desired sensitivity rates are 70% to 80%, and sensitivity is the true positive rate of a test.

Specificity is a measure of the proportion of children who actually are normal and who also are correctly determined by a given test to not have a problem. Children who are normal but who are incorrectly determined by a test cutoff score to be delayed or learning disabled are considered to have false-positive scores. Specificity is the true negative rate of a test. Again, in cases such as developmental screening, the presence of a reference (and not “gold”) standard makes the term conegativity more appropriate. A specificity rate of 70% to 80% is desirable. However, in the case of screening, it is better to have a higher sensitivity rate, perhaps at the cost of lowered specificity, so as to enhance identification of infants and children who might be at risk.

Cutoff scores can be adjusted to enhance sensitivity. By making criteria more inclusive, fewer children with true abnormalities will be missed; however, a more restrictive cutoff will also increase the probability of false-positive findings (overidentifying “normal” children as being abnormal). Conversely, if the cutoff score is made more exclusive to enhance specificity, the number of normal children inaccurately identified as abnormal is decreased, but some of those who are truly abnormal will be erroneously called normal (false-negative findings). Sensitivity and specificity are described in Figure 7A-2.

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FIGURE 7A-2 Example highlighting sensitivity and specificity.

Positive predictive value refers to the proportion of children with a positive test result who actually are delayed or learning disabled. This reflects the probability of having a problem when the test result is positive. The lower the prevalence of a disorder, the lower is the positive predictive value. Sensitivity may be a better measure in low-prevalence problems. In developmental screening, positive predictive values often are in the range of 30% to 50%.

Negative predictive value refers to the proportion of children with a negative test result who indeed do not have developmental delays or learning problems. It is the probability of not having the disorder when the test result is negative. This value is influenced by the frequency or prevalence of a problem; in low-prevalence problems, specificity may be a better measure.

Frequency of a Disorder/Problem

Prevalence rate refers to the number of children in the population with a disorder, in relation to the total number of children in the population, measured at a given time. The incidence rate indicates the risk of developing a disorder: namely, new cases of a problem that develop over a period of time. The relationship between incidence and prevalence can best be illustrated by the following: prevalence rate = the incidence rate × the duration of the disorder. In essence, the predictive value of screening takes into account sensitivity and specificity of the screening procedure and the prevalence of the disorder.

Base rate is the naturally occurring rate of a given disorder. For example, the base rate of learning disabilities would be much higher in children referred to a learning and attention disorders clinic than in the general population. If a screening instrument were used to detect learning disabilities for this group, sensitivity and specificity values would differ from those found in the general pediatric population. For example, in the follow-up of low-birth-weight infants, the base rate for major handicaps (moderate to severe mental retardation; cerebral palsy; epilepsy; deafness or blindness) is 15%; therefore, in 85% of this population, the findings would be true negative. Low base rates increase the possibility of false-positive results. High base rates do not leave much room for improvement in terms of locating true-positive scores and result in an increase in false-negative findings. Tests can be most helpful in decision making when the base rate is in the vicinity of 0.50. Therefore, particularly in the case of screening, the relatively low base rates of developmental problems in very young children may increase the probability of false positive findings. However, in such situations, this scenario is more desirable than the converse: false negative findings.

Relative risk provides an alternative strategy for evaluating test accuracy.17,18 This approach involves use of the likelihood ratio, which indicates the increased probability that the child will display a developmental problem, if the results of an earlier screening test were abnormal or suspect. This approach recognizes that not all children at early risk will later manifest a developmental problem, but there is a greater likelihood that they will. If a problem or disorder is rare, relative risk and odds ratios are nearly equal.

Test Characteristics

RELIABILITY

Measurement is the ability to assign numbers to individuals in systematic ways as a means of inferring properties of these individuals. Reliability refers to consistency or accuracy in measurement. Reliability focuses on how much error is involved in measurement or how much an obtained score varies from the “true score.” An observed test score = true score + measurement error. Internal consistency is a measure of whether all components of a test evaluate a cohesive construct or set of constructs (e.g., verbal ability or visual-motor skills). Stated differently, high internal consistency means that all items are highly intercorrelated. This is measured with Cronbach’s alpha, split-half reliability, or the Kuder-Richardson reliability estimate. Cronbach’s alpha is used to evaluate how individual items relate to the test as a whole (intercorrelation among items); split-half reliability relates half of the test items to the remaining half, often by an odd-even split; and the Kuder-Richardson reliability estimate is used for dichotomous (i.e., “yes”/“no”) items. Test-retest reliability is particularly pertinent in developmental and psychological testing because it takes into account the “true score” and error, addressing whether the same score would be obtained if a specific test were readministered. The length of time between the two administrations of the test is critical in regard to this measurement; that is, the sooner the test is readministered, the greater the reliability estimate is. In general, test-retest correlations of 0.70 are considered moderate, 0.80 moderate to high, and 0.90, high (scores >0.85 are desirable, although explicit, evidence-based criteria have not been defined yet). Tests with more items tend to have higher reliability, because of the likelihood of a greater variance in scores. Interrater reliability refers to how well independent examiners agree on results of a test. Alternate forms involve use of parallel tests, so as to prevent carryover (score inflation) if the parallel test is administered soon after the first. For example, the Peabody Picture Vocabulary Test—III has two forms, as does the Wide Range Achievement Test—4.

Reliability is affected by test length (longer tests are more reliable), test-retest interval (longer interval lessens reliability), variability of scores (greater variance increases reliability estimate), guessing (increased guessing decreases reliability), variations in test situation, and practice effects.3

VALIDITY

Validity refers to whether a test measures what it is supposed to measure for a specific purpose. A test may be valid for some uses and not others. For example, the Peabody Picture Vocabulary Test—III may be a valid measure of receptive vocabulary, but it is not a valid measure of overall cognitive ability or even overall language ability. It is important to keep in mind that test validation is context specific. In order to determine whether an assessment method is “psychometrically sound” or “valid,” the clinician must consider how it is being used. For example, an intelligence test may be a valid method for determining a child’s cognitive abilities but may have limited validity for treatment design and planning (see previous discussion of SNRAs). Similarly, a test may have demonstrated evidence as a valid measure of severity of general anxiety but not of phobias; a certain behavior rating scale may be valid as a measure of current clinical symptoms but may not have validity for treatment planning or for predicting outcomes. Thus, the purpose of the assessment needs to be considered in order to properly evaluate the psychometric characteristics of an assessment method.

Content validity determines whether the items in the test are representative of the domain the test purports to measure: that is, whether the test does cover the material it is supposed to cover. Construct validity concerns whether the test measures a particular psychological construct or trait (e.g., intelligence). Criterion-related validity involves the current relationship between test scores and some criterion, such as results of another test. Criterion-related validity can be concurrent (convergent) or predictive. In both instances, the results of a test under consideration are compared to an established reference standard to determine whether findings are comparable. In concurrent validity, the two tests (e.g., a screen such as the Bayley Infant Neurodevelopmental Screener and a “reference standard” such as the BSID-II) are administered at the same time, and the results are correlated. With predictive validity, a screening test might be given at one time, followed by administration of the reference standard at a later date (e.g., the BSID-II is given to children aged 36 months, and the Wechsler Preschool and Primary Scales of Intelligence—III at age 4½ years). Discriminant validity shows how well a screening test detects a specific type of problem. For example, autism might be the condition of concern, and a screening test such as the Modified Checklist for Autism in Toddlers (M-CHAT) is used to distinguish children with this disorder from those with mental retardation without autism. Face validity involves whether the test appears to measure what it is supposed to measure. Test-related factors (examiner-examinee rapport, handicaps, motivation), criterion-related factors, or intervening events could affect validity.

With regard to the interrelatedness among reliability and validity, reliability essentially sets the upper limit of a test’s validity, and reliability is a necessary but not sufficient condition for valid measurement. A specific test can be reliable, but it may be invalid when used to evaluate a function that it was not designed to measure. However, if a test is not reliable, it cannot be valid. Stated differently, all valid tests are reliable, unreliable tests are not valid, and reliable tests may or may not be valid.19

Practitioners should also be cognizant of the fact that testing can involve a speed test, in which items are relatively easy but there is a specific time limit and it is difficult to answer all of the items. The infamous 2-minute math test is an example. A power test involves progressively more difficult items, this difficulty being determined by the limits of a child’s knowledge base.

Age and Grade Equivalents

Age- and grade-equivalent scores are based on raw scores and portray the average age or grade placement of children who obtained a particular raw score. Although these metrics are useful in explaining results to parents and make conceptual sense, age and grade-equivalent scores are uneven units of measurement. For example, a six-month difference in performance at the age of 2 years is much more significant than a 6-month lag at age 8 years. Moreover, a 9-year-old with an age equivalent of 7 years is quite different from a 4-year-old functioning at a 7-year age equivalent, or an average 7-year-old. These measures lack precision, and in some test manuals, the same standard scores can produce somewhat different age/grade equivalents. Both metrics assume that growth is consistent throughout the school year and tend to exaggerate small differences in performance. These measures also vary from test to test. Furthermore, with achievement testing, it is necessary to know whether age or grade norms were used to obtain standard scores. For example, if age norms are used and the child had been retained in grade, he or she would be at a significant disadvantage because he or she would not have been exposed to the more advanced material. Conversely, if a child failed second grade and is being tested in early fall while repeating second grade, he or she may receive inflated scores if grade norms are used.

The IQ/DQ ratio (developmental quotient) is computed as mental age (obtained by the use of a test score) ÷ the child’s chronologic age and then multiplied by 100. Although developmental age refers to a level of functioning, DQ reflects the rate of development.19 IQ/DQ ratio scores are not comparable at different age levels because the standard deviation (variance) of the ratio does not remain constant. As a result, interpretation is difficult, and these scores generally are not used very much in contemporary standardized testing. Instead, the deviation IQ/DQ is employed. The deviation IQ is a method of estimation that allows comparability of scores across ages and is used with most major psychological and developmental test instruments. The deviation IQ/DQ is norm referenced and normally distributed, with the same standard deviation; typically, M = 100 and SD = 15. Therefore, a deviation IQ of 85 obtained at age 6 should have the same meaning as a score of 85 obtained at age 9.

The standard error of measurement (SEM) is an estimate of the error factor in a test that is the result of sampling or test characteristics, taking into account the mean, standard deviation, and size of the sample. The larger the standard error of measurement, the greater the uncertainty associated with a given child’s score. The SEM is produced by multiplying the standard deviation of the test by the square root of (1− the reliability coefficient of the test). In 95% of cases, the interval of approximately two times (1.96) the SEM above or below a child’s score would contain the “true” score: a 95% confidence interval. Stated differently, a 95% confidence interval indicates that if a test is given 100 times with different samples, scores will fall in this interval 95% of the time. In a 90% confidence interval, an interval of 1.64× the SEM above and below a child’s score would contain the “true” score. Such estimates are important in test-retest situations or in the case of a child who does not receive services because of missing a cutoff score by only a few points (e.g., a WISC-IV Full Scale IQ score of 72).

A final concern is the Flynn effect,20 in which test norms increase approximately 0.3 to 0.5 points per year, which is equivalent to a 3- to 5-point increment per decade. This finding has ramifications in comparisons of scores obtained on earlier versions of tests to more contemporary scores (e.g., WISC-Revised to the WISC—Third Edition or WISC-IV; BSID to BSID-II; Stanford-Binet form LM to the 5th edition). Caution is warranted when the practitioner attributes a decline in scores to a loss of cognitive ability, because in actuality this decline may be attributable to the fact that a newer test has mean scores that are considerably lower than those of an earlier version of the test (e.g., 5-8 points).20 This issue would also have ramifications for children whose IQ score on an older version of a test is in the low 70s but decreases to below the cutoff for mild mental retardation on a newer version.

Although some practitioners may administer tests, all have occasion to respond to inquiries from parents about their child’s test performance or diagnosis derived from testing. The physician’s role includes explaining test results to parents, acknowledging parental concerns and advocating for the child, providing additional evaluation, or referring to other professionals.21

REFERENCES

1 Costello EJ, Edelbrock C, Costello AJ, et al. Psychopathology in pediatric primary care: The new hidden morbidity. Pediatrics. 1988;82:415-424.

2 Lavigne JV, Binns HJ, Christoffel KK, et al. Behavioral and emotional problems among preschool children in pediatric primary care: Prevalence and pediatricians’ recognition. Pediatrics. 1993;91:649-657.

3 Sattler JM. Assessment of Children, 4th ed. San Diego: Jerome M. Sattler, 2001.

4 Bayley N. Bayley Scales of Infant and Toddler Development, Third Edition: Technical Manual. San Antonio, TX: PsychCorp, 2005.

5 Roid GH. Stanford-Binet Intelligence Scales for Early Childhood, Fifth Edition: Manual. Itasca, IL: Riverside, 2005.

6 Wilkins C, Rolfhus E, Weiss L, et al: A Simulation Study Comparing Inferential and Traditional Norming with Small Sample Sizes. Paper presented at annual meeting of the American Educational Research Association, Montreal, Canada, 2005.

7 Wright BD, Linacre JM. WINSTEPS: Rasch Analysis for All Two-Facet Models. Chicago: MESA, 1999.

8 Rasch G. Probabilistic Models for Some Intelligence and Attainment Tests. Chicago: University of Chicago Press, 1980.

9 Dorans NJ, Holland PW. DIF detection and description: Mantel-Haenszel and standardization. In: Holland PW, Wainer H, editors. Differential Item Functioning. Mahwah, NJ: Erlbaum; 1993:35-66.

10 Gyurke JS, Aylward GP. Issues in the use of normreferenced assessments with at-risk infants. Child Youth Fam Q. 1992;15:6-8.

11 Bracken BA. Bracken Basic Concepts Scale-Revised. San Antonio, TX: The Psychological Corporation, 1998.

12 Greenspan SI, Meisels SJ. Toward a new vision for the developmental assessment of infants and young children. In: Meisels SJ, Fenichel E, editors. New Visions for the Developmental Assessment of Infants and Young Children. Washington, DC: Zero to Three: National Center for Infants Toddlers and Families; 1996:11-26.

13 Meisels S. Charting the continuum of assessment and intervention. In: Meisels SJ, Fenichel E, editors. New Visions for the Developmental Assessment of Infants and Young Children. Washington, DC: Zero to Three: National Center for Infants Toddlers and Families; 1996:27-52.

14 Bricker D. Assessment, Evaluation and Programming System for Infants and Children, Volume 1: AEPS Measurement for Birth to Three Years. Baltimore: Paul H. Brookes, 1993.

15 Johnson-Martin N, Jens K, Attermeir S, et al. The Carolina Curriculum, 2nd ed. Baltimore: Paul H. Brookes, 1991.

16 Urdan T. Statistics in Plain English. Mahwah, NJ: Erlbaum, 2001.

17 Frankenburg WK, Chen J, Thornton SM. Common pitfalls in the evaluation of developmental screening tests. J Pediatr. 1988;113:1110-1113.

18 Frankenburg WK. Preventing developmental delays: Is developmental screening sufficient? Pediatrics. 1994;93:586-593.

19 Salvia J, Ysseldyke JE. Assessment, 8th ed. New York: Houghton Mifflin, 2001.

20 Flynn JR. Searching for justice. The discovery of IQ gains over time. Am Psychol. 1999;54:5-20.

21 Aylward GP. Practitioner’s Guide to Developmental and Psychological Testing. New York: Plenum Medical, 1994.

7B. Surveillance and Screening for Development and Behavior

FRANCES P. GLASCOE, PAUL H. DWORKIN

More than three decades have elapsed since the identification of developmental, behavior, and psychosocial problems as the so-called “new morbidity” of pediatric practice.1 During the ensuing years, profound societal change, with public policy mandates for deinstitutionalization and mainstreaming, has further influenced the composition of pediatric practice. Studies have documented the high prevalence of developmental and behavioral issues within the practice setting, including disorders of high prevalence and lower severity such as specific learning disability, attention-deficit/hyperactivity disorder, and speech and language impairment, as well as problems of higher severity and lower prevalence such as mental retardation, autism, cerebral palsy, hearing impairment, and serious emotional disturbance.2

The critical influence of the early childhood years on later school success and the well-documented benefits of early intervention provide a strong rational for the early detection of children at risk for adverse developmental and behavioral outcomes. Neurobiological, behavioral, and social science research findings from the 1990s, the so-called decade of the brain, have emphasized the importance of experience on early brain development and on subsequent development and behavior and the extent to which the less differentiated brain of the younger child is particularly amenable to intervention.3

In this chapter, we highlight links between early detection and early intervention. Much has been written on this topic and the American Academy of pediatrics has recently revised its policy statement on developmental screening. The new statement includes expert opinion on how to provide quality developmental surveillance (the process of incorporating medical/developmental history, knowledge of the family, parents’ concerns, screening test results, and clinical observation) in order to make informed decisions about any needed referrals. Thus, this chapter offers a review of evidence and challenges in surveillance and screening, reconciles both approaches, includes a list of quality screening measures, describes effective early identification initiatives, and provides suggestions for enhancing the well-child visits to facilitate early detection of developmental and behavioral problems.

BACKGROUND

Early identification and intervention affords the opportunity to avert the inevitable secondary problems with loss of self-esteem and self-confidence that result from years of struggle with developmental dysfunction. Federal legislation, the Individuals with Disabilities Education Act (IDEA) of 2004, and related state legislation mandate early detection and intervention for children with developmental and behavioral disabilities. Surveys indicate that parents have strong interest in promoting children’s optimal development.4,5

Perhaps the most compelling rationale for early detection is the effectiveness of early intervention. Researchers have documented the benefits of early intervention in children with mental retardation and physical handicaps, particularly when improved family functioning is a measured outcome.6 More recently, the benefits of early intervention for children at environmental risk has also been demonstrated. For example, enrollment and participation of disadvantaged children in Head Start programs contribute to a decreased likelihood of grade repetition, less need for special education services, and fewer school dropouts.7 Detection is also supported by the clearer delineation of adverse influences on children’s development. For example, the effect of such diverse factors as low-level lead exposure and adverse parent-infant interaction on child development has implications for early identification.

By virtue of their access to young children and their families, child health providers are particularly well positioned to participate in early identification of children at risk for adverse outcomes through ongoing monitoring of development and behavior. Clinicians’ knowledge of medical and genetic factors also facilitates early identification of conditions associated with developmental problems. Furthermore, through their relationships with children and their families, pediatricians and other child health providers are familiar with the social and familial factors that place children at environmental risk. Professional guidelines emphasize the importance of early detection by child health providers. The American Academy of Pediatrics’ Committee on Children with Disabilities; Medicaid’s Early Periodic Screening, Diagnosis, and Treatment (EPSDT) program; and Bright Futures (guidelines for health supervision of infants, children, and adolescents developed by the American Academy of Pediatrics and the Maternal and Child Health Bureau) all encourage the effective monitoring of children’s development and behavior and the prompt identification of children at risk for adverse outcomes.8,9 The emphasis on the primary care practice as a comprehensive medical home for all children also supports the office as the ideal medical setting for developmental and behavioral monitoring.10

Despite this strong rationale, results of surveys of parents and child health providers demonstrate that current practices widely vary and suggest the need to strengthen developmental monitoring and early detection. Only about half of parents of children aged between 10 and 35 months recall their children’s ever having received structured developmental assessments from their child health providers.11 Parents also report gaps in the discussion of development and related issues with pediatric providers.12 Most pediatricians employ informal, nonvalidated approaches to developmental screening and assessment. The majority of pediatricians do not incorporate within their practice such tools as those recommended by Bright Futures to aid in early detection.13

Not surprisingly, the early detection of children at risk for adverse developmental and behavioral outcomes has proved elusive. Fewer than 30% of children with such disabilities as mental retardation, speech and language impairments, learning disabilities, and serious emotional/behavioral disturbances are identified before school entry.13 This lack of detection precludes the opportunity and benefits of timely, early intervention. Although nearly half of parents have some concerns for their child’s development or behavior, such concerns are infrequently elicited by child health providers.14

Multiple factors have been cited as barriers to effective developmental monitoring. Child health providers report inadequate time during the office visit to deliver developmental services, including monitoring and early detection. A professionally administered developmental test (e.g., the Denver-II) cannot be adequately performed in a child health supervision visit that lasts, on average, less than 20 minutes and in which other content must be delivered. Other recognized barriers include the inadequate training of child health providers and ineffective administrative and clinical practices, including staffing and record keeping. Despite the assigning of a value to the billing code for developmental screening (96110) by the Centers for Medicare and Medicaid Services, reimbursement for developmental services in general and for developmental monitoring specifically by third-party payers remains inadequate. Health care organizations do not measure or prioritize the developmental content of child health supervision services. Furthermore, even if at-risk children are identified, the linkage of such children and their families to developmentally enhancing programs and services is often inefficient and challenging.

DEVELOPMENTAL SURVEILLANCE

Currently, child health providers employ a variety of techniques to monitor children’s development and behavior. History taking during a health supervision visit typically includes a review of age-appropriate developmental milestones. Unfortunately, recall of such milestones is notoriously unreliable and typically reflects parents’ prior conceptions of children’s development.15 Although the accuracy in determining the age of performing certain tasks is certainly improved by the use of diaries and records, the wide range of normal acquisition for such milestones limits their value in assessing children’s developmental progress. Child health providers may also question parents as to their predictions for their child’s development. Predictions (typically elicited with questions such as “when your child becomes an adult, do you think he or she will be above average, average, or below average?”) are also unhelpful in developmental monitoring, because parents are likely to expect average functioning for children with delays and predict overachievement for children developing at an average pace, a phenomenon dubbed the presidential syndrome.15

During the physical examination, child health providers may interact with children by using an informal collection of age-appropriate tasks. The lack of a standardized approach to measuring developmental progress makes interpretation of children’s performance on such tasks difficult. The reliance of child health providers on “clinical judgment,” based on subjective impressions during the performance of the history and physical examination, are also fraught with hazard. Such impressions are unduly influenced by the extent to which a child is verbal and sociable in a setting that may be frightening, an effect likely to restrict affect and deter spontaneous demonstrations of pragmatic language skills. Studies have documented the poor correlation between provider’s subjective impressions of children’s development and the results of formal assessments. Clinical judgment identifies fewer than 30% of children with developmental disabilities.15 The reliance on subjective impressions undoubtedly contributes to the late identification of children with such developmental issues as mild mental retardation.

According to research findings and expert opinion, surveillance and screening constitute the optimal approach to developmental monitoring.16 As originally described by British investigators, surveillance encompasses all activities relating to the detection of developmental problems and the promotion of development through anticipatory guidance during primary care.17 Developmental surveillance is a flexible, longitudinal, continuous process in which knowledgeable professionals perform skilled observations during child health care.17 Although surveillance is most typically performed during health supervision visits, clinicians may perform opportunistic surveillance during sick visits by exploring the child’s understanding of illness and treatment.18a

The emphasis of developmental surveillance is on skillfully observing children and identifying parental concerns. Components include eliciting and attending to parents’ opinions and concerns, obtaining a relevant developmental history, skillfully and accurately observing children’s development and parent-child interaction, and sharing opinions and soliciting input from other professionals (e.g., visiting nurse, child care provider, preschool and school teacher), particularly when concerns arise. Developmental history should include an exploration of both risk and protective factors, including environmental, genetic, biological, social, and demographic influences, and observations of the child should include a careful physical and neurological examination. Surveillance stresses the importance of viewing the child within the context of overall well-being and circumstance.17

The most critical component of surveillance is eliciting and attending to parents’ opinions and concerns. Research has elucidated the value of information available from parents. Although there are several ways to obtain quality information, research on parents’ concerns is voluminous. Concerns are particularly important indicators of developmental problems, particularly for speech and language function, fine motor skills, and general functioning (e.g., “He’s just slow”).15,18 Although concerns about self-help skills, gross motor skills, and behavior are less sensitive indicators of developmental functioning, such opinions should serve as clinical “red flags,” mandating closer clinical assessment and developmental promotion.15,18 The manner in which parental concerns are elicited is important. Asking parents whether they have worries about their children’s development is unlikely to be useful, because they may be reluctant to acknowledge fears and interpret “development” as merely reflecting physical growth. In contrast, asking parents whether they have any concerns about the way their child is behaving, learning, and developing, followed by more specific inquiry about functioning in specific developmental domains, is more likely to yield valid and clinically useful responses.18,19 Clinicians must be mindful of the complex relationship between concerns and disability (some concerns are predictors of developmental status only at certain ages), the critical importance of eliciting concerns rather than relying on parents to volunteer, and the value of an evidence-based approach to interpreting concerns.18,21

Parents’ estimations are also accurate indicators of developmental status. For example, a study conducted in primary care demonstrated the extent to which parents’ estimates of cognitive, motor, self-help, and academic skills correlate with findings on developmental assessments.22 Parental responses to the question, “Compared with other children, how old would you say your child now acts?” are important indicators of developmental delay, although such questions are more challenging for parents than elicitations of concerns.22

In contrast to the limitations of parents’ recall of developmental milestones, contemporaneous descriptions of children’s current skills and achievements are useful indicators of developmental status. Similar to the solicitation of parental concerns, the format of questions eliciting parental report is important. Recognition questions such as “Does your child use any of the following words?” are more likely to yield helpful information than are such identification questions as “What words does your child say?” that rely on parents’ spontaneous recall and report. Parental report is likely to yield higher estimates of children’s functioning than is professional assessment. This discrepancy is less likely to result from parental inaccuracy or exaggeration than from parents’ reports on newly emerging skills that are inconsistency demonstrated in the familiar and supportive home environment.

Parents’ opinions and concerns must be considered within the context of cultural influences. Parents’ appraisals and descriptions are influenced by expectations for children’s normal development, and such expectations vary among different ethnic groups. For example, in a study of Latino (primarily Puerto Rican), African American, and European American mothers, Puerto Rican mothers expected personal and social milestones to be normally achieved at a later age than did the other groups, whereas first steps and toilet training were expected at an older age by European American mothers.23 Such differences were often explained by underlying cultural beliefs, values, and childrearing practices. For example, the older age for achievement of self-help skills is consistent with the Puerto Rican concept of familismo and its emphasis on caring for children.

USE OF SCREENING TOOLS

The effectiveness of developmental surveillance is enhanced by incorporating valid measures of parents’ appraisals and descriptions of children’s development and skilled professional observations. The process is enhanced by the periodic use of evidence-based screening tools (meaning that measures are repeatedly administered over time), including parent-completed questionnaires and professionally administered tests. Screening tools that elicit information from parents may be used on a routine basis to supplement data gathering during health supervision visits, may be used periodically at select ages (e.g., 9, 18, and 24 months), or may be used in a targeted manner to further explore the significance of parental concerns. Similarly, professionally administered screening tests may be administered periodically to help ensure that children do not elude early identification, or they may be used when concerns arise (so-called second-stage screening) or when parents are not able to provide information.

Table 7B-1 includes descriptions of screening tools that are highly accurate: that is, based on nationally representative samples, fulfilling psychometric criteria (see Chapter 7A), and having both sensitivity and specificity of at least 70% to 80%. Two types of tools are presented: those relying on information from parents and those requiring direct elicitation of children’s skills. The latter are useful in practices with staff (e.g., nurses, pediatric nurse practitioners) who have the time and skill to administer relatively detailed screens. Such measures are also useful in early intervention programs. Information is included on purchasing, cost, time to administer, scores produced, and age ranges of the children tested.

TABLE 7B-1 Developmental, Mental Health/Behavioral and Academic Screens

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COMBINING SCREENING AND SURVEILLANCE

We now present an algorithm for combining surveillance and screening into an effective, evidence-based process for detecting and addressing developmental and behavioral issues. The American Academy of Pediatrics recently revised its policy statement on early detection.8 We include the elements of the statement, as follows.

1. Review the patient’s chart for medical risk factors. Take note of such potentially teratogenic exposures as radiation or medications, infectious illnesses, fever, addictive substances, and trauma, and review results of neonatal screens, including phenylketonuria, hypothyroidism, and other metabolic conditions. Also consider the perinatal history, including birth weight, gestational age, Apgar scores, and any medical complications. In addition, postnatal medical factors to be considered include chronic respiratory or allergic illness, recurrent otitis, head trauma, and sleep problems, including symptoms of obstructive sleep apnea.
2. Identify psychosocial risk factors. Common risk factors for developmental and behavioral problems include parents with less than a high school education, parental mental health or substance abuse problems, four or more children in the home, single-parent family, poverty, frequent household moves, limited social support, parental history of abuse as a child, and ethnic minority status. Four or more risk factors are associated with developmental performance that is well below average, which, in turn, has an adverse effect on future success in school.24 The presence of multiple risk factors suggests the need for enrichment or remedial programs, regardless of screening results. Examples include Head Start, after-school tutoring, parenting training, social work services, mentoring, quality child care, and summer school. A measure such as the Family Psychosocial Screen (available at www.pedstest.com) is often helpful for identifying psychosocial risk factors and can be used as a standard intake form for new patients.
3. Elicit parents’ concerns and observations. Careful attention to wording is essential. Although facilitating conversations with parents can be informally accomplished, several helpful sources suggest well-worded questions. For example, Bright Futures contains useful trigger questions. A parent-completed measure, the Parents’ Evaluation of Developmental Status questionnaire (see Table 7B-1), has empirically tested wording and weighs the types of concerns parents raise, assigns levels of risk, and identifies optimal responses to concerns.
4. Conduct a physical examination. Examination should include attention to growth parameters, head shape and circumference, facial and other body dysmorphology, eye findings (e.g., cataracts in various inborn errors of metabolism), vascular markings, and signs of neurocutaneous disorders (e.g., café-au-lait spots in neurofibromatosis, hypopigmented macules in tuberous sclerosis). Vision and hearing screening are essential.
5. Administer/score developmental screening tests. Use of parent report measures, completed before the visit or in the waiting/examination room, reduces the amount of time needed for screening. Positive results may be followed by additional screening of social-emotional functioning (e.g., Ages & Stages Questionnaires: Social-Emotional and the Modified Checklist for Autism in Toddlers; see Table 7B-1) to better identify the areas of delay and types of services needed. Note that the AAP’s new statement recommends use of an autism specific screen like the M-CHAT at both 18 and 24 months, regardless of performance on broadband tools like PEDS or the ASQ.
6. Provide additional medical screens when developmental-behavioral screens are positive. When indicated, common health-related causes for delays and disorders should include screens for iron deficiency and lead toxicity. Unless suggested by parental report (e.g., seizure activity) or clinical findings (e.g., microcephaly, expanding head circumference), neurophysiological (e.g., electroencephalogram) and neuroimaging (e.g., computed tomographic scan, magnetic resonance imaging) studies are not routinely indicated. Developmental delay may suggest the need for metabolic screening for ammonia, organic, and amino acids (or referral for such screens). A progressive loss of milestones suggests the possible need to screen for human immunodeficiency virus (HIV).
7. Explain results to parents. When parents’ concerns have been elicited, the process of explaining findings can begin with a simple affirmation of parents’ observations. It is important to present results in person and to maintain a positive outlook about available services and their potential to improve outcome. Because screening/surveillance activities are not diagnostic in nature, the clinician should avoid diagnostic labels in favor of euphemisms, such as “developmental delay,” “behind other children,” and “having difficulties with…” When a parent reports conflicting perceptions within the family about the possibility of problems, the clinician should offer to explain findings to other family members. Asking parents whether they know other families with children who have developmental-behavioral differences may be helpful in clarifying discussions.
8. If indicated, make referrals for subspecialty medical services. When medical factors are identified, an appropriate response is referral for further evaluation.
9. Seek nonmedical interventions. Nonmedical interventions need not await a complete diagnosis. All children with apparent delays or disorders should be referred promptly to appropriate programs and services. Public programs, including those mandated by such legislation as the IDEA, should be available through community-based agencies or the public schools without cost to the family and generally provide a range of high-quality therapies and evaluations, including speech-language, physical, and occupational therapy; assistive technology evaluations; and behavioral interventions. Most IDEA programs do not provide a detailed diagnosis but rather define functional skills and deficits. As a consequence, a referral may also need to be made to a multidisciplinary diagnostic service. Because such centers typically have long waiting lists and because a final diagnosis is not necessary for initiating intervention, it is best to make such referrals concurrent with a referral to an IDEA program. Other services should be sought (e.g., Head Start, after school tutoring, quality daycare, parent training) for children with psychosocial risk factors who do not fulfill specific eligibility requirements for early intervention or special education. Referral letters to programs and services should include suggestions for the types of evaluations needed (e.g., speech-language therapy, occupational and physical therapy, social-emotional assessment, intelligence testing, academics). Programs offered through IDEA often require documentation of hearing and vision status. Some programs require the completion of specific referral forms. Parental consent should be obtained for sharing information, including copies of subsequent evaluations.
10. Offer developmental promotion. Regardless of whether a child has developmental problems, parents need advice and encouragement on promoting optimal development, particularly in domains associated with school success: language, academic/preacademic skills, and cognition. Clinicians may provide patient education materials, lists of informative and factual Web sites, lists of parent training services, and contacts for social support programs. Group discussions for parents on developmental topics are another potential strategy but require careful planning and organization. Developmental promotion is assisted by a well-organized system for filing and retrieving parent-focused materials (see www.dbpeds.org for materials and links).
11. Establish a medical home. For children with developmental-behavioral problems and/or complex health care needs, primary care contact and perspectives are of critical importance to promote optimal health and development. The American Academy of Pediatrics National Center of Medical Home Initiatives for Children with Special Needs (www.medicalhomeinfo.org) provides an essential guide for organizing practices to ensure continuity of care, manage multiple referrals and comprehensive records, coordinate appointments, and communicate with various providers.

SYSTEMWIDE APPROACHES TO SURVEILLANCE AND SCREENING

State wide and countywide efforts to enhance collaboration among medical and nonmedical providers offer some of the most promising evidence for the effectiveness of surveillance and screening. Documented outcomes include large increases in screening rates during EPSDT visits;25 a fourfold increase in early intervention enrollment, resulting in a match between the prevalence of disabilities and receipt of services26; a 75% increase in identification of children from birth to age 3 with autism spectrum disorder27; improvement in reimbursement for screening28; and, interestingly, increased attendance at well-child visits when parents’ concerns are elicited and addressed.25

Among the numerous initiatives—national, international, and regional—we selected a few to highlight because they employed varied models and gathered outcome data to support their successes (and challenges).

The Assuring Better Child Health and Development (ABCD) Program

Created by The Commonwealth Fund, the ABCD Program has identified policy strategies for state Medicaid agencies to strengthen the delivery and financing of early childhood services for low-income families. The emphasis is on assisting participating states in developing care models that promote healthy development, including the mental development of young children. Models include developmental screening, referral, service coordination, and educational materials and resources for families and clinical providers. The program has resulted in improvements in screening, surveillance, and assessment. Most notably, work in North Carolina facilitated a 75% increase in screening, increased enrollment rates in early intervention from 2.6% to 8% (in line with the Centers for Disease Control and Prevention’s prevalence projections), while simultaneously lowering referral age26 (http://www.nashp.org; http://www.cdc.gov/ncbdd/child/interventions.htm).

Help Me Grow

A program of the Connecticut Children’s Trust Fund, Help Me Grow links children and families to community programs and services by using a comprehensive statewide network. Components of the program include the training of child health providers in effective developmental surveillance; the creation of a triage, referral, and case management system that facilitates access for children and families to services through Child Development Infoline; the development and maintenance of a computerized inventory of regional services that address developmental and behavioral needs of children and their families; and data gathering to systematically document capacity issues and gaps in services. The program has increased identification rates of at-risk children by child health providers and increased referral rates of such children to programs and services. For example, chart reviews conducted in participating practices noted an increase in documented developmental or behavioral concerns from 9% before training to 18% after training. Furthermore, training resulted in significant differences in referral rates for certain conditions. Behavioral conditions were involved in 4% of referrals from trained practices, in comparison with 1% from untrained practices. Four percent of referrals from trained practices were for parental support and guidance, in comparison with fewer than 1% from untrained practices29 (http://www.infoline.org/Programs/helpmegrow.asp).

Promoting Resources in Developmental Education (PRIDE)

This program is a 3-year project funded by the Duke Endowment through a partnership of the Children’s Hospital, the Center for Developmental Services (a colocation of agencies serving children with developmental disorders), the regional office of the state’s early intervention system (BabyNet), the local school district’s Childfind and Parents-as-Teachers programs, and a parent-to-parent mentoring program for parents of children with special health care needs. The goal of PRIDE is earlier identification and intervention for children in Greenville County, South Carolina with developmental delays and improved support for their parents.

The program has targeted key players in the lives of infants and toddlers as follows: Parents sign up around the time of their child’s birth to receive milestone cards every 3 to 6 months during the first 3 years that describe the key developmental attainments, activities to promote development at that age, and red flags for potential developmental problems. Parents are instructed to discuss any concerns with their physician. Primary care physicians are provided with information and tools (the Parents Evaluation of Developmental Status questionnaire) to improve their system of developmental screening. A nurse practitioner employed by PRIDE as the “physician office liaison” works closely with practices, initially by setting up lunch meetings with physicians and staff that are also attended by the PRIDE developmental-behavioral pediatrician. With the agreement of the physicians, the liaison then assists the office staff in implementing the system and provides a “Resource Guide” with information on local developmental services and forms to facilitate referrals. Child care providers have the opportunity to attend educational sessions (for credit hours) in which they learn about child development, signs of developmental problems, and services that are available for these children. The training sessions are provided in collaboration with local programs that promote higher quality child care and early education (Success By 6 and First Steps), and the attendees receive “toolkits” with information on the topics discussed. Initial results of the program indicate success; 16 of 17 local pediatric practices (which previously had no standardized system of developmental screening) now utilize the Parents Evaluation of Developmental Status questionnaire. Over the first 18 months of the program, referrals to early intervention have increased almost 100% and referrals to the school’s Childfind program by 30%. Other service providers have seen increases in new referrals of up to 30%. The average age at referral to early intervention has also dropped slightly.

Not surprisingly, increasing rates of referral raised the likelihood of even longer waiting lists for tertiary-level developmental-behavioral pediatric evaluations. To address this challenge, the PRIDE staff sought funding from The Commonwealth Fund to study the feasibility and cost effectiveness of a model of “midlevel” developmental-behavioral pediatrics assessment (as a step between telephone triage/record review and comprehensive diagnostic evaluation) for children younger than 6 years.30

First Signs

This national and international training effort is devoted to early detection of children with disabilities, with a particular focus on autism spectrum disorders. This detection is accomplished through a mix of print materials and broadcast press, direct mail, public service announcements, presentations (to medical and nonmedical professionals), a richly informative website (www.firstsigns.org), and detailed program evaluation. Although First Signs initiatives have been conducted in several states, including New Jersey, Alabama, Delaware, and Pennsylvania, the Minnesota campaign is highlighted here because of that state’s assistance in program evaluation. Minnesota is divided into discrete service regions. Centralized train-the-trainers forums were conducted to prepare 130 professionals as outreach trainers. These individuals were from all regions of the state, and most were early interventionists, family therapists, and other nonmedical service providers. They then provided more than 165 workshops to 686 medical providers, to whom they offered individualized training tailored for health care clinics, as well as training for more than 3000 early childhood specialists. First Signs Screening Kits (which include video, information about and in some cases copies of appropriate screening tools, wall charts and parent handouts on warning signs) were distributed to more than 900 practitioners and clinics. In addition, public service announcements were aired across the state in collaboration with the Autism Society of Minnesota. Within 12 months, there was a 75% increase in the number of young children identified in the 0- to 2-year age group and an overall increase of 23% in detection of autism spectrum disorders among all children aged 0 to 21 years in that same period. The state has now expanded the initiative to include childcare providers and is educating them about red flags and warning signs. In addition, physicians with the Minnesota Chapter of the American Academy of Pediatrics Committee for Children with Disabilities have begun incorporating First Signs information into physician training program at the University of Minnesota.27

Blue Cross/Blue Shield of Tennessee

Blue Cross/Blue Shield of Tennessee requested that child health providers use standardized, validated screening at all EPSDT visits. To facilitate compliance, Blue Cross/Blue Shield of Tennessee piloted a program in 34 high-volume, Medicaid-managed care practices. Outreach nurses, called regional clinical network analysts, trained providers on site how to administer, score, interpret, and submit reimbursement for the Parents’ Evaluation of Developmental Status questionnaire (the standardized developmental-behavioral surveillance and screening instrument that elicits parents’ concerns about their children). After training, screening rates increased from 0% to 43.5% during the pilot phase. At the same time, the practices experienced a 16% increase in attendance at scheduled well-child visits, which suggests that focusing on parents’ concerns may increase their adherence to visit schedules. Blue Cross/Blue Shield of Tennessee, together with the Tennessee Chapter of the American Academy of Pediatrics, is now providing training across the state.25 More information can be found through the Center for Health Care Strategies, “Best Clinical and Administrative Practices for Statewide” developmental and behavioral screening initiatives as established by the Center for Health Care Strategies [http://www.chcs.org/]

Healthy Steps for Young Children

This a national initiative improves traditional pediatric care with the assistance of an in-office child development specialist, whose duties include expanded discussions of preventive issues during well-child and home visits, staffing a telephone information line, disseminating patient education materials, and networking with community resources and parent support groups. Now in its 12th year, Healthy Steps followed its original cohort of 3737 intervention and comparison families from 15 pediatric practices in varied settings. In comparison with controls, Healthy Steps families received significantly more preventive and developmental services, were less likely to be dissatisfied with their pediatric primary care, and had improved parenting skills in many areas, including adherence to health visits, nutritional practices, developmental stimulation, appropriate disciplinary techniques, and correct sleeping position. In practices serving families with incomes below $20,000, use of telephone information lines increased from 37% before the intervention to 87% after; office visits with someone who teaches parents about child development increased from 39% to 88%; and home visits increased from 30% to 92%. Low-income families receiving Healthy Steps services were as likely as high-income parents to adhere to age-appropriate well-child visits at 1, 2, 4, 12, 18, and 24 months.31,32 One program evaluation suggests that Healthy Steps offers a benefit comparable with that of Head Start at about one-tenth the cost,33 although this claim is somewhat premature because Head Start data now extend to more than 35 years of follow-up research with a proven return rate of $17.00 for each $1.00 spent on early intervention, with savings realized through reductions in teen pregnancy, increases in high school graduation and employment rates, and decreased adjudication and violent crime.7 Nevertheless, Healthy Steps is extremely promising and inexpensive and includes a strong evaluation component that will answer questions about its long-term effect.

CONCLUSION

In summary, both expert opinion and research evidence support surveillance and screening as the optimal clinical practice for monitoring children’s development and behavior, promoting optimal development, and effectively identifying children at risk for delays. The effectiveness of surveillance is enhanced by incorporating valid measures of parents’ appraisals and descriptions of children’s development and behavior and skilled professional observations. Developmental monitoring should combine surveillance at all health supervision visits with the periodic use of evidence-based screening tools, including parent-completed questionnaires and professionally administered tests.

To be effective, identification must lead to intervention through referral to appropriate programs and services. Surveillance and screening activities must ensure access to medical evaluations, developmental assessments, and intervention programs. Ultimately, collaboration among health care providers, parents, and early intervention and other social service providers is crucial for effectively addressing the challenges of detection and timely enrollment in early intervention programs and services.

Establishing effective surveillance and screening in primary care is nevertheless challenging.13 Effective initiatives consistently offer training to providers, office staff, and nonmedical professionals. Implementation details are numerous (e.g., incorporation into existing office workflow, ordering and managing screening materials, gathering and organizing lists of referral resources and patient education handouts, identifying measures that work well with available personnel, and determining how best to communicate with nonmedical providers).18,18a,26,34 Ultimately, helping health care providers recognize the need to adopt effective detection methods is the critical first step.

DIRECTIONS FOR FURTHER RESEARCH

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