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Use of the Woodcock-Johnson III with preschool age children born prematurely Kozey, Michelle Lynne 2006

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USE OF THE WOODCOCK-JOHNSON III WITH PRESCHOOL AGE CHILDREN BORN PREMATURELY by MICHELLE LYNNE KOZEY B.A.H., Queen's University, 1995 B.Sc.H., Trinity College at University of Toronto, 2001 A THESIS SUBMITTED IN PARTIAL FUFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS in THE FACULTY OF GRADUATE STUDIES (School Psychology) THE UNIVERSITY OF BRITISH COLUMBIA April 2006 © Michelle Lynne Kozey, 2006 ABSTRACT USE OF THE WOODCOCK-JOHNSON III WITH PRESCHOOL AGE CHILDREN BORN PREMATURELY Preterm and low birth-weight children are one of the most common at-risk groups for whom early assessment and long term monitoring is strongly indicated, as they display a significantly higher incidence of developmental impairments such as difficulties in childhood cognitive, motor, academic, behavioural and social functioning, and they require higher levels of special education services (Bhutta, Cleeves, Casey, Craddock & Anand, 2002). Although demand has increased for the early identification of the psycho-educational difficulties of preterm and other clinical populations, the assessment of preschool-aged children has continued to be challenged by issues related to the standardized assessment of young children, and the technical properties and content validity of instruments available for use with this age range. The most recent revision of the Woodcock-Johnson III contains tests that are developmentally and psychometrically appropriate for use with preschool age children, but no published studies are currently available on its use with clinical populations of a preschool age (Ford, Kozey & Merkel, 2006 under review). The purpose of this study was to evaluate the utility of the WJ III with a common clinical population of a preschool age, specifically children aged four and five years born who were born prematurely. Results indicated no significant differences between the score distributions of preschool-aged children born prematurely versus a matched sample from the WJ III Standardization sample in terms of global intelligence, individual Cattell-Horn-Carroll abilities, global achievement or individual academic abilities. Design issues related to the screening of the matched sample limited possible conclusions regarding the relationship between birth status and performance on the WJ III tests administered in this study, and no relationship Ul was found between perinatal complications as measured by the Maternal Perinatal Scale and performance on the WJ III. However, current findings may be a function of the limited size and biased composition of the study sample, rather than the actual function of the WJ III. The application of CHC theory and a cross-battery approach remains as a promising method to understanding the cognitive and academic deficits of preterm children in general, and further investigation is necessary to determine the utility of the WJ III with preschool-aged children born prematurely. iv Table of Contents Abstract ii Table of Contents iii List of Tables v Acknowledgements.. vi Chapter One: Introduction 1 Definition of Key Terms 2 Preterm Children 2 Preschool Children '. 3 Cognitive Abilities 3 Early Academic Abilities 4 Purpose of the Study 5 Significance of the Study '.': 6 Chapter Two: Review of the Literature 7 Issues in the Assessment of Preschool Children 8 Age-Related Test Session Behaviours & Test Administration 9 Technical Properties of Measures Used with Preschool Children 9 Content Validity of Psychoeducational Measures for Preschool Aged 10 Children Use of Cattell-Horn-Carroll Theory with Preschool-Aged Children 10 Cattell-Horn-Carroll Theory of Cognitive & Academic Abilities 10 Cattell-Horn-Carroll Theory & Preschool-Aged Children 11 Validity & Use of the WJ III with Preschool Aged Children 12 Application of Cattell-Horn Carroll Theory to Children Born Prematurely 13 Methodological Issues in the Study of Children Born Prematurely 13 Cognitive Deficits of Children Born Prematurely. 17 Academic Deficits of Children Born Prematurely 28 Research Questions and Anticipated Outcomes 28 Chapter Three: Methodology 32 Participants..... 32 Recruitment of Sample 32 Characteristics of Sample 33 Instrumentation 35 Woodcock-Johnson, Third Edition 35 Maternal Perinatal Scale 39 Study Questionnaire 41 Procedures J 41 Preterm Sample Recruitment 41 Assessment 42 Analysis 43 Descriptive Analyses 43 Research Questions 43 Chapter Four: Results 52 Initial Descriptive Analyses 52 Research Questions #1 & #2 52 General Intellectual Abilities-Early Development Score 52 Individual Woodcock-Johnson III Cognitive & Diagnostic Supplement 53 Tests... Research Questions #3 & #4 54 Pre-Academic Standard Score 54 Individual Woodcock-Johnson III Achievement Tests 54 Research Question #5 55 Descriptive Results for Maternal Perinatal Scale 55 Relationship of Maternal Perinatal Scale Scores to Woodcock-Johnson III Cognitive & Diagnostic Supplement Scores. 55 Relationship of Maternal Perinatal Scale Scores to Woodcock-Johnson III Achievement S cores 56 Post Hoc Gender Analyses 56 Chapter Five: Discussion 75 Individual Research Questions 76 Limitations of Study 80 Contributions to the Field 83 Conclusions 85 References 86 Appendices 102 List of Tables vi Table Title Page 2.1 Broad Cognitive and Academic Abilities in the Catttell-Horn-Carroll Model 31 3.1 Demographics of Study Participants 45 3.2 Chronological Age of Preterm and Matched Sample in Months 46 3.3 Family Characteristics of Study Participants 47-49 3.4 Gestational Age and Birthweight of Preterm Sample 49 3.5 Psychometric Characteristics of Woodcock-Johnson III Cluster Scores & Individual Tests Used in the Present Study 51-52 4.1 Comparison of Distributions of Demographic Variables for Preterm 58 Sample 4.2 Means and Standard Deviations for the Woodcock-Johnson III Cognitive 59 and Diagnostic S Composite and Individual Test Scores 4.3 Comparison of Score Distributions for Woodcock-Johnson III Cognitive 60 Scores & Relationship with Birth Status 4.4 Means and Standard Deviations for Woodcock Johnson III Tests of 61 Academic Achievement Scores 4.5 Comparison of Score Distributions for Woodcock-Johnson III 62 Achievement Scores & Relationship with Birth Status 4.6 Item Level Results from the Material Perinatal Scale for Preterm Sample 63-66 4.7 Correlation between Woodcock Johnson III Cognitive & Diagnostic 67 Supplement Standard Scores with Cumulative Maternal Perinatal Risk Score for Preterm Sample 4.8 Correlation between Woodcock Johnson III Achievement Standard Scores 68 with Cumulative Maternal Perinatal Risk Score for Preterm Sample 4.9 Preterm Sample Means and Standard Deviations for the Woodcock-Johnson 69 III Tests of Cognitive Abilities and Diagnostic Supplement Composite and Individual Test Scores By Gender 4.10 Matched Sample Means and Standard Deviations for the Woodcock-Johnson III Tests of Cognitive Abilities and Diagnostic Supplement Composite and Individual Test Scores By Gender (n=16) 70 vii 4.11 Comparison of Preterm Males Versus Preterm Female Score Distributions for 71 the Woodcock-Johnson III Tests of Cognitive Abilities and Diagnostic Supplement Scores 4.12 Preterm Sample Means and Standard Deviations for the Woodcock-Johnson 72 III Tests of Academic Achievement Composite and Individual Test Score By Gender (n= 16) 4.13 Matched Sample Means and Standard Deviations for the WJ III Achievement 73 Composite and Individual Test Score By Gender (n=16) 4.14 Comparison of Preterm Males Versus Preterm Female Score Distributions for 74 the Woodcock-Johnson III Tests of Academic Achievement Scores Acknowledgements vni I would like to thank the Human Early Learning Partnership and the Woodcock-Munoz Foundation for their financial support of this research project. I would also like to thank my advisor, Dr. Laurie Ford, and the members of my committee, Dr. Linda Siegel and Dr. Shelley Hymel for their feedback and assistance. CHAPTER ONE Introduction Preterm and low birth-weight children are one of the most common at-risk groups for whom early assessment and long term monitoring is strongly indicated. Compared to full term children, they display a significantly higher incidence of developmental impairments (Allen, 2002; Lorenz, 2001; Repka, 2002), special education requirements (Allen, 2002; Cherkes-Julkowski, 1998), and have well documented difficulties in cognitive, motor, academic, behavioural and social functioning during childhood (Aylward, 2002a; Foulder-Hughes & Cooke, 2003; Marlow, 2004). In recent decades, preschool-aged children born prematurely, as well as children with other developmental disabilities such as autism, brain injury, autism, attention problems, or specific learning disorders, have increasingly been referred for early psychoeducational assessment (Bhutta, Cleves, Casey, Cradock & Anand, 2002; McLean, 2004). This trend has been fuelled by increased public awareness about child development between the ages of birth and seven years, the positive impact of early education and preschool programs, and early childhood special education legislation in the United States (Hartlage & Williams, 1997; Nagle, 2000). Formalized assessment of young children is complicated by numerous issues (Ford & Dahinten, 2005; Nagle, 2000). Developmental status changes rapidly between birth and entry into school, and the assessment of young children is challenged by issues related to test administration and test session behaviours, the psychometric properties of available assessment tools, and their related content and ecological validity (Flanagan & Alfonso, 1995; Ford, 2003; Neisworth & Bagnato, 2004). Many of the cognitive and academic measures currently available . 2 for use with young children have been similarly criticized for poor psychometric properties and the limited number of cognitive abilities that they evaluate (Ford, Kozey, Merkel, & Swart, 2005; Tusing & Ford, 2004). A number of studies examining the use of the Woodcock-Johnson - Third Edition Tests of Cognitive Abilities and Tests of Achievement (WJ III; Woodcock, McGrew, and Mather, 2001) with typically developing children have been conducted and suggest that the many of the WJ III tests are developmentally and psychometrically appropriate for use with children of preschool age (Ford, 2003; Ford, Merkel, & Kozey, under review; Ford, Kozey, Merkel, & Swart, 2005; Ford, Merkel, Kozey & Swart, 2005; League, 2000; Merkel, 2005; McCullough, 2001; Teague, 1999; Tusing, Maricle, & Ford, 2003). However, no published studies are currently available on its use with clinical populations of a preschool age (L.A. Ford, personal communication, March 5, 2006; McGrew & Schrank, 2006). Definition of Key Terms Preterm Children Preterm children are those born before 37 weeks of gestation and are typically classified by their gestation age into categories of prematurity. Although variable terminology is used to characterize premature birth in the professional literature, in the context of this study, an attempt was made to be consistent with definitions used by British Columbia Reproductive Care Program (2001). Although the program identifies children born before 28 weeks gestation age as extremely preterm (EPT), those born between 28 and 32 weeks gestation age as moderately preterm (MPT), and children born 33-37 weeks gestation age are described as preterm (PT), for the purposes of the present study all children born before 37 weeks gestation age were referred to as preterm. 3 Preschool Children The terms "infant" or "toddler" are often employed to describe children between zero and three years of age, whereas the term "school-age" is commonly used to describe children between ages of four or five years and seventeen years (McLean, Wolery & Bailey, 2004). In contrast, the term "preschool child" typically refers to children who are between the ages of three years to approximately five years (Ford & Dahinten, 2005; Tideman & Gustafsson, 2003). In the context of the sample for this study, the term "preschool children" is defined as children between the ages of three years, zero months and five years, eleven months. This is consistent with similar assessment studies using preschool age children, and accounts for the age ranges of most psychological and educational tests used with preschool age children. Cognitive Abilities The terms intelligence and cognitive abilities are frequently used interchangeably. Moreover, "there is no broad consensus in the scientific community about the conceptualization of intelligence and measurement methods for intelligence testing" (Wilhelm & Engle, 2005, p. 7). To understand the term, one must typically refer to the theoretical foundations of the test (if provided) and the authors of a given test. However, since the publication of the Human Cognitive Abilities in 1993 (Carroll), the Tri-Stratum Theory and subsequently Cattell-Horn-Carroll (CHC) Theory (McGrew, 2005) is a common theoretical standard by which current measures of cognitive ability are interpreted (Alfonso, Flanagan, & Radwan, 2005). For the purposes of this study, the term "cognitive abilities" is defined consistent with CHC theory as a multiple intelligences approach from the psychometric tradition with general level cognitive ability (g) at Stratum or Level III, and seven of the nine factor-level or broad abilities that differentially load upon g (Fluid Reasoning, Crystallized Intelligence, Visual-Spatial Thinking, Short Term Memory, Long Term Storage and Retrieval, and Processing Speed) at Stratum or 4 Level II and a narrow abilities at Stratum or Level III. Although the theory purports three levels or "stratum", only the first two will be examined in the present study. Early Academic Abilities Academic achievement in preschool-aged children is distinct from the term school readiness, which typically refers to more generic skills and behaviours associated with successful early school learning (Gredler, 2000). In school-age and adult populations, academic achievement is commonly characterized by skill development or success within particular curricular areas, such as reading, writing, or mathematics, and is frequently indicated by performance on standardized tests. Within the context of CHC theory, cognitive and academic skills are structured along the same continuum of mental abilities, with the two academic abilities of Quantitative Knowledge and Reading/Writing found alongside the other seven broad abilities listed above (McGrew, 2005). However, CHC abilities are conceptualized as ranging from those that "develop largely independent of formal education and school-related experiences (cognitive abilities)... to those that "develop largely as a function of formal education and direction learning and instruction;" thus, academic abilities are characterized as those "which develop more as a function of formal, school-related experiences (Flanagan, Ortiz, Alfonzo, & Mascolo, 2002, p. 49). Although limited investigation has been conducted on the specific nature of CHC academic abilities in young children (Merkel, 2005; McCullough, 2001; Tusing, Maricle, & Ford, 2003), specific aspects (narrow abilities) of the broader CHC academic abilities are thought to be particularly relevant and important to early education, and thus are appropriate conceptualizations of academic abilities in preschool-aged children (Schrank, Mather, McGrew & Woodcock, 2003). In the present study, academic abilities will include those CHC abilities measured as a part of the Tests of Achievement on the Woodcock-Johnson Third Edition, notably reading and math abilities. 5 Purpose of the Study The primary purpose of this study was to explore the use of the WJ III with a sample of preschool age children born premature. 1. What was the relationship of global intellectual ability, as measured by the GIA-EDev Standard Score, of children born prematurely compared to a matched sample of children from the standardization sample? 2. What was the relationship of broad cognitive abilities, as measured on WJ III COG, including Auditory Processing (measured by Test 8: Incomplete Words), Crystallized Abilities as measured by Test 1: Verbal Comprehension), Fluid Reasoning (as measured by Test 5: Concept Formation), Visual-Spatial Processing (as measured by the Test 22: Visual Closure), Short-Term Memory (as measured by Test 27: Memory for Words), Long Term Memory & Retrieval ( as measured by Test 22: Memory for Names), and Processing Speed (as measured by Test 5: Visual Matching), of children born prematurely compared to a matched sample of children from the standardization sample? 3. What was the relationship of global pre-academic abilities, as measured by the Woodcock-Johnson III Tests of Achievement Pre-Academic Skills-Standard (Pre-Ach-Std) score, of children born prematurely compared to a matched sample of children from the standardization sample? 4. What was the relationship of specific early academic skills measured by the Woodcock-Johnson III Tests of Achievement, including early reading skills (as measured by Test 1: Letter-Word Identification, and Test 14: Picture Vocabulary), early writing skills (as measured by Test 7: Spelling), early mathematical skills (as measured by Test 10: Applied Problems), of children born prematurely compared to a matched sample of children from the standardization sample? 5. Among children born prematurely, what is the relationship of the Woodcock-Johnson III Tests of Cognitive Abilities General Intellectual Ability-Early Development (GIA-EDev) Standard Score, the individual Woodcock-Johnson III EDev tests (as listed in research question 2), the Woodcock-Johnson III Tests of Achievement Pre-Academic Skills-Standard, and the individual Woodcock-Johnson III Tests of Academic Achievement (as listed in research question 4) with cumulative perinatal risk factors, as measured by overall risk score on the Maternal Perinatal Scale? Significance Due to improvements in medical technology, both the survival rate and incidence of morbidity associated preterm birth have continued to rise in recent decades (Bennet, 2002; Hack & Faranoff, 1999; Lu, Tache, Alexander, Kotelchuck, & Halfon, 2003). The problems associated with preterm birth impose an immense burden on these children, their families, health, education and social services, and society (Petrou, Sach & Davidson, 2001). Exploration of the WJ III as a possible assessment tool with this preterm population may assist with the understanding and identification of their early deficits. CHAPTER TWO Review of the Relevant Literature Preterm and low birth-weight children are one of the most common at-risk groups for whom early assessment and long term monitoring is strongly indicated. Overall, preterm children display a significantly higher incidence of developmental impairments and delays, which include physical deficits, visual impairments, hearing impairments and cerebral palsy (Allen, 2002; Lorenz, 2001; Repka, 2002). Preterm children display a number of deficits upon entering school, including delays in general cognitive, motor, academic, behavioural and social functioning (Aylward, 2002a; Foulder-Hughes & Cooke, 2003; Marlow, 2004). Children born prematurely require more special education than children born at term (Allen, 2002; Aylward, 2002a), with up to 75% of moderately preterm children display learning disabilities, attention deficit disorder, language impairment or a mild neurological impairment by grade five (Cherkes-Julkowski, 1998). Longitudinal studies have shown that developmental deficits and educational disadvantage associated with prematurity not only persist with advancing age, but may also increase in early adolescence (O'Brien et al., 2004). The incidence of preterm birth has increased by almost 20% over the past two decades, partially because of improvements in prenatal care and associated decreases in infant mortality (Lu, Tache, Alexander, Kotelchuck, & Halfon, 2003). On average 7.5% of Canadian infants are born prematurely, with 3,000 children born prematurely annually in British Columbia (BC Reproductive Care Program, 2001). Research and early intervention services for children born prematurely, including those in British Columbia, have traditionally focused on those at greatest risk such as infants of low birth weight (<1500 grams), of extremely low gestational age (born at 27 weeks or less), or those experiencing 8 major medical complications (R.Gruneau, personnel communication, November 3,2004). However, with advances in medical care have resulted in lower levels of mortality, but higher levels of morbidity in children, and there is concern about the adequacy of resources available for follow-up of the health, educational and emotional needs of moderately preterm children (MPT, born 28-32 weeks) and preterm children (born 33-37 weeks), and their families (Allen, 2002). Issues in the Psycho-Educational Assessment of Preschool -Aged Children Interpretation of previous literature regarding the cognitive and academic difficulties of preschool-aged children born prematurely requires consideration of general issues associated with the psychoeducational assessment of young children. Following the passage of US federal legislation that requires states to provide services to preschool children with special needs (1975 Public Law 94-142, 1986 Public Law 99-457, 2004 Public Law 108-446), increased public awareness about child development between the ages of birth and seven years, and the widespread growth of preschool programs, the assessment of preschool children has come to center on the early identification of psychological and educational difficulties (Hartlage & Williams, 1997; Nagle, 2000). In recent decades, preschool-aged children born prematurely, as well as children with other developmental disabilities such as autism, brain injury, autism, attention problems, or specific learning disorders, have been increasingly referred for formal psychoeducational evaluation (Bhutta, Cleves, Casey, Cradock & Anand, 2002; McLean, 2004). Assessment practices have shifted towards more specialized diagnostic services such as cognitive assessment, and assessment methods that inform early intervention and preschool special education instruction (Hooper, 2000). Despite this increased demand for early psychoeducational services, practitioners conducting assessment with preschool-aged populations are challenged by issues related to test administration and test session behaviours, 9 the technical adequacy of assessment tools and the rapidly changing and complex nature of early development, and the test content and ecological validity and treatment utility of available measures (Ford & Dahinten, 2005). Similarly, the implications of these issues for the interpretation of research findings must also take into consideration. Age-Related Test Session Behaviours & Test Administration. Test administration and the reliability of assessment results for young children can be problematic because of developmental issues, including shorter attention spans, high activity levels, separation anxiety, and limited language comprehension and expression (Ford, 2003; Romero, 1992). Many preschool measures have been also criticized for their inclusion of developmentally inappropriate basic concepts or linguistic terms in their tests directions, such as "another, on top of, or beside," etc. (Boehm, 2000; Bracken & Walker, 1997; Flanagan, Alfonso, Kaminer, & Rader, 1995; Merkel, Kozey, Swart & Ford, 2005). Due to these issues, some researchers advocate that norm-referenced, standardized intelligence tests should be abandoned in favor of multidisciplinary, ecological, and curriculum-based approaches to assessment (Bagnato & Neisworth, 1994). Technical Properties of Measures Used with Preschool Children. Until recently, well established technical properties of psychological measures for preschool children have been often limited, if present at all (Bracken, 1987; Flanagan & Alfonso, 1995; Ford & Dahinten, 2005). Measures have been typically most problematic for children below the age of four years (Bracken, 1987; Bradley-Johnson, 2001, Flanagan & Alfonso, 1995; Ford, Kozey, Merkel, & Swart, 2005). Common problems include insufficient test floors (e.g., median subtests scores frequently equaling zero), inadequate item gradients (e.g., item difficulty failing to measure different developmental levels of task requirements), and norm tables with broad age-span layouts (e.g. norms provided for age 10 intervals of six months or greater) (Nagle, 2000). Despite the poor technical quality of earlier measures of cognitive abilities in young children, significant improvements have been noted in recently revised versions of many test batteries for preschool-aged children; the standardization samples and internal consistency of many of these newer measures have been observed to be remarkably improved (Flanagan & Alfonso, 1995; Ford & Dahinten, 2005; Ford et al., 2005). Content Validity of Psychoeducational Measures for Preschool Aged Children. The use of intelligence tests with young children has also been criticized as atheoretical, and the content validity of preschool measures is under considerable debate. This issue is further complicated by the idiographic nature of development and the rapidly changing nature of cognitive abilities in early childhood (Ford, 2003). Historically, the assessment of young children has focused upon one, and in some cases two factor conceptualizations of cognitive ability, such g or general intelligence, or verbal and performance intelligence, respectively (Nagle, 2000), in spite of research that supports more expanded models for interpreting preschool tests (Elliott, 1990; League, 2000; Teague, 1999; Tusing & Ford, 2004). Use of Cattell-Horn-Carroll Theory to Understand the Cognitive and Academic Abilities of Preschool-Aged Children Cattell-Horn-Carroll Theory of Cognitive & Academic Abilities. The Tri-Stratum Theory of Carroll, along with the Gf-Gc model supported by the work of Cattell and Horn, now known as the Cattell-Horn-Carroll (CHC) theory (McGrew, 2005), is a common theoretical standard by which current measures of cognitive and academic abilities are interpreted (Alfonso, Flanagan, & Radwan, 2005). Research supporting CHC theory hypothesizes that cognitive ability is comprised of a general level ability (g), but primarily of 11 seven to ten factor-level or broad abilities (Table 2.1) that differentially load upon g (McGrew, 2005). These broad abilities can be further delineated into more specific, narrow abilities. General CHC research has clearly identified unique developmental trajectories for each of these ten cognitive abilities, with many of the ten abilities emerging by at least five years of age (McGrew, Woodcock, & Ford, 2002). Cattell-Horn-Carroll Theory & Preschool-Aged Children. The original Tri-Stratum Theory was formulated upon data from school-aged children and adults(McGrew, 2005), and few published studies have examined the application of CHC theory to cognitive abilities in children under the age of six years (Tusing et al., 2003). However, findings to date suggest that CHC theory is valid and appropriate approach to understanding the cognitive abilities of preschool-aged children; factor-analytic research indicates that at least a three to five cognitive abilities exist in preschoolers, with crystallized (Gc), auditory (Ga) and visual factors (Gv) present at two years of age, and more factors emerging by five years of age (League, 2001; Teague, 2003; Tusing et al., 2003). Two studies similarly identified least five CHC cognitive abilities in preschoolers: results from Tusing and Ford (2004) identified Gc, Glr, Gsm, Ga, and a Nonverbal Ability, although the results of Teague (1999) identified Gc, Ga, Gv, Gsm, and Glr (but not for Gf and Gs) in young children. Limited published information is available on the application of the CHC theory to the academic abilities of young children. McCullough (2001) and Merkel (2005) both examined the relation between CHC cognitive abilities in preschoolers and found some initial relationships between performance on cognitive measures interpreted from a CHC framework and early academic achievement (Merkel, 2005; Tusing et al., 2003). 12 Validity and Use of the Woodcock-Johnson III with Preschool Aged Children. The Woodcock-Johnson, Third Edition (WJ III) was designed to measure cognitive and academic abilities as outlined in CHC theory. A number of studies examining the use of the Woodcock-Johnson - Third Edition Tests of Cognitive Abilities and Tests of Achievement (WJ III; Woodcock, McGrew, and Mather, 2001) with typically developing children suggest that the many of the WJ III tests are appropriate for use and are a valid measure of cognitive and academic abilities in young children (Ford, 2003; Ford, Merkel, & Kozey, under review; Ford, Kozey, Merkel, & Swart, 2005; Ford, Merkel, Kozey & Swart, 2005; League, 2000; Merkel, 2005; McCullough, 2001; Teague, 1999; Tusing, Maricle, and Ford, 2003). Preliminary investigations with the WJ III on the role of basic concepts suggest that the directions and procedures in the WJ III are linguistically suitable for use with young children (Ford, Merkel, Kozey & Swart, 2006).The WJ III measures cognitive and academic abilities with tests that psychometrically allow for technically appropriate interpretation of factor level scores (McGrew, Flanagan, Keith, & Vanderwood, 1997), and work by Tusing, Maricle, & Ford (2003) indicates that the majority of tests found in the WJ III demonstrate adequate reliability and test floors for this purpose with children of a preschool age. Moreover, the recent application to standardized tests of Rasch-based psychometrics, which employs an equal interval scale centered on a mean of 500, allows for the description of the quality of performance on a test versus the relative status of performance in comparison to age and grade peers. The use of Rasch or W-Difference scores can be used to indicate how difficult young children find tasks to be, regardless of the total number of items that they get correct. On the WJ III COG, the use of Rasch or Relative Proficiency Index (RPI) scores may provide "an interpretive advantage that may be particularly useful for determining the presence and severity of developmental delay in assessment of young children" (Ford & Dahinten, 2005; p. 23). Finally, the WJ III evaluates a wider range of 13 cognitive abilities than other measures available for use with young children (Ford, Kozey, Merkel & Swart, 2005). Two studies were identified as employing the W J III with typically developing preschool aged children; Duncan and Rafter (2005) used the W J III C O G Brief Intellectual Abi l i ty & the W J III A C H to validate the Phelps Kindergarten Readiness Scale, Revised, whereas Gormley, Gayer, Philips, & Dawson (2005) used select tests from the W J III A C H to evaluate the effects of a universal Kindergarten program in Oklahoma. However, no published studies are currently available that investigate its utility with clinical populations of a preschool age ( L . A . Ford, personal communication, March 5, 2006). Application of CHC Theory to Children Born Prematurely To date, no studies were identified as examining the cognitive abilities and academic outcomes of children born prematurely from the Cattell-Horn-Carroll theoretical framework, nor were any studies identified as using instruments based upon C H C theory (e.g., Stanford-Binet Intelligence Scale- Fifth Edition; Woodcock-Johnson Psychoeducational Battery-Revised; W J III C O G ) with children born prematurely. In the context of the current study, literature findings were interpreted from a C H C theoretical perspective, using the cross-battery approach espoused by Flanagan and Ortiz (2001) that allows practitioners and researchers to evaluate a wider range of abilities than represented on a single battery. Methodological Issues in the Study of Preterm Children. A review of the literature (from any theoretical perspective) on the cognitive and academic difficulties of children born prematurely yields some ambiguous and contradictory findings. The study of preterm children is challenged by issues related to changes over time in newborn medicine, conceptual issues, the heterogeneity of preterm populations, study design, and variability in outcome definition and instrumentation. Changes in Perinatal Care and Neonatal Medicine. Medical practice used in newborn care has changed significantly in recent decades, with numerous advances in neonatal 14 pharmacology (e.g., surfactant or steroid therapy) and intensive care technology (e.g., assisted ventilation) occurring in the end of the 1980s and in the early 1990s (Hack & Faranoff, 1999). In dramatic contrast to earlier mortality rates, current survival rates are at least 90 percent for preterm children of gestational ages (GA) as low as 28 weeks and birth weights appropriate to their GA, and approximately 50 percent for infants born at 28 to 24 weeks GA (Bennett, 2002). In terms of both the nature of their medical care and their degrees of biological risk related to increased prematurity, preterm children born prior to and after the early 1990s are considered to be qualitatively different. For these reasons, the comparability of research on different cohorts of children and treated in different centers is also problematic. Low Birth-Weight Versus Gestational Age. Follow-up studies of preterm children have traditionally focused upon outcome related to low birth weight (LBW). The concepts of gestational age and birth weight are positively related; lower gestational ages are associated with shorter periods of intrauterine growth and therefore lower birth weight, and instances of low birth weight typically occur in conjunction with preterm birth (Bennett, 2002). However, LBW is both absolute (in comparison to typical, full term children) and relative (to that expected for a given gestational age). Preterm birth with LBW which is GA-appropriate is medically distinct from LBW with intrauterine growth retardation (IGR), where an LBW-IGR child is typically below the 10th, 5th or 3rd decile for GA, depending upon the definition (Taylor, Klein & Hack, 2000). Due to the limited survival of children born 32 weeks or less (<1,500-1,000 grams) and previous difficulties with accurately estimating gestational age, neonatal medical practice and^  research traditionally has focused upon children with absolute low birth weight (Hack, Klein & Taylor, 1995). The increased survival rates of moderately and extremely preterm children have been accompanied by increased efforts to identify the specific etiology and most useful manner for 15 conceptualizing preterm children. Comprehensive reviews demonstrate that "the maturity of the infant at birth, as measured by gestational age, is the major predictor of outcome" (Hack et al, 1995). Similarly, gestational age, but not birth weight, is frequently found to improve the prediction of preterm outcomes (Fawer et al, 1995). Accordingly, in the past decade the focus of research has shifted from absolute low birth weight to prematurity. Despite this, many studies continue to interchangeably use the terms LBW and preterm birth, and fail to distinguish between the outcomes of preterm children with and without IGR (Wolke & Meyer, 1999), thus complicating interpretation of such findings. Heterogeneity of Preterm Populations. Preterm literature is further challenged by the heterogeneity of preterm populations, and evidence that differential outcomes are linked to factors that vary across preterm populations. The etiology of prematurity variables can include poor maternal health, perinatal nutrition, or prenatal drug/alcohol exposure, and multiple different risk factors have been found to differentially impact cognitive and academic outcomes (Taylor, Burant, Holding, Klein & Hack, 2002). Similarly, inter-child variability exists in terms of perinatal risk factors that are associated with more adverse outcomes, such brain pathology, intraventricular hemorrhage (IVH)/hemorrhagic lesions, periventricular leukomalacia (PVL), chronic lung disease, asphyxia or infection (Fawer et al, 1995; Hack et al, 1995; Vollmer et al, 2003). Findings regarding the difficulties of children born prematurely are also potentially confounded by factors such as gender, family socio-economic status, and environmental stimulation. Findings from Johnson and Breslau (2000) suggest that male, but not female preterm children have early academic deficits. Rates of preterm birth are significantly higher in low income or socially disadvantaged families (Paneth, 1995). Dezoete, MacArthur and Tuck (2003) and Fawer et al (1995) also found that family socio-economic status and background better 16 predicted outcome than birthweight or gestational age, consistent with the established relationship between SES and measured intelligence in the general population. Similarly, Weisglas-Kuperus, Baerts, Smrkovsky et al (1993) concluded that early cognitive delays associated with low birth weight and prematurity dissipated by four years in children who were in positive and stimulating home environments. Siegel (1982) similarly demonstrated that cognitive outcomes of preterm infants were best predicted by consideration of multiple factors, including reproductive, perinatal, demographic, socioeconomic and environmental conditions. Alternatively, Forslund and Bjerre (1990) found that the clear deficits of four-year-old preterm children were uncorrelated with birthweight, gestational age, prenatal/perinatal scores, parental social status or parental education. Preterm Study Design Issues. Interpretation of findings regarding children born prematurely are also complicated by significant methodological problems related to study design, such as a lack of control group, use of single-centered studies, short duration of followup or the number of children lost to follow-up (Aylward, 2002a, 2002b; Siegel, 1994). Contradictions in findings are also attributed to inter-study differences in sample selection procedures and vvariable ages of children at assessment (Wolke & Meyer, 1999). Moreover, in the course of this literature review, no studies that reported effect sizes or strength of association indexes were identified. Variation in Instrumentation and Definition of Outcome. Multiple different measures have been used to evaluate the cognitive and academic outcomes of preterm children (Hack et al, 1995). Developmental and intellectual measures differ significantly in terms of their content and psychometric properties, including the range of CHC abilities that they assess, and the narrow CHC abilities measured; many of the measures used to assess children born prematurely also have limited sensitivity to the particular disorders associated with preterm birth (Taylor et al, 2002). Similarly, the comparability of performance on psychological tests of significantly different publication dates has been questioned due to differences in test content, psychometrics and the age of associated norms (Bracken, 1988) and the variable cutoffs used to define cognitive impairment in children born prematurely have also been characterized as arbitrarily set (Hack, 1995). Due to the dramatic changes in neonatal medical care in the early 1990s, a shift in the past decade in the focus of research from absolute low birth weight to preterm birth, and significant changes in the content of psychological instruments in the past 10-15 years, the following literature review is largely focused on findings published between 1990 and the 2005. In addition, whenever possible, this literature review was restricted to findings that correspond to the ages of the children in the current study sample, namely between four and six years of age. Cognitive Deficits of Children Born Prematurely. Overall Cognitive Abilities. A review of the literature reveals inconsistent findings regarding the overall cognitive abilities (i.e., global intelligence or "g") of children born prematurely. Several studies surveyed found either no or limited differences between the overall cognitive abilities of preterm versus full term children (Lapine, Jackon & Saigal, 1995; Wolke, 1993). Five-year-old children born extremely preterm, moderately preterm and preterm all performed within the normal range on the McCarthy Scales of Children's Abilities, but their scores varied significantly by socioeconomic class (Petersen, Greisen, Kovacs, Munck & Friis-Hansen, 1990). Similarly, Saigal, Szatman and Rosenbaum (1991) also found no significant differences between the overall cognitive abilities of pre- and full-term children at 8 years on the WISC-R, although the global IQ scores of the same preterm children who had BW of less than 1,000 grams was significantly lower. Limited differences in overall cognitive abilities have been found between children born prematurely 18 versus full term on measures such as the Griffiths' Mental Developmental Scale, and the WPPSI-R (Alin-Akerman & Nordberg, 1980; Forslund & Bjerre, 1990; Bohm, Katz-Salamon, Smedler, Lagercrantz & Forssberg, 2002), with children born prematurely more frequently having IQ scores in the lower end of the average range. The literature also indicates a parallel finding where children born prematurely have global intelligence scores which are approximately 6 to 10 points lower than full term children, with significant differences of this magnitude found on several measures (Aylward, 2002a). In contrast to Petersen et al (1990), Siegel (1983) found that the global scores of children born prematurely were significantly lower by six points at age five years, and by at least 10 points on the Stanford-Binet at age three years. Similar results were found for four-year-old children on the Stanford-Binet 4th Edition (SB-IV; Thorndike, Hagen & Sattler, 1986) by Dezoete, MacArthur and Tuck (2003). On the Kaufman Assessment Battery for Children (Kaufman & Kaufman, 1983), the scores of six-year-old children born prematurely were found to be lower by a large magnitude (15 to 13 points; Wolke & Meyer, 1999), with almost half of preschool children born extremely preterm displaying serious impairments (Marlow, Wolke, Bracewell & Samara, 2005). Lower global intelligence in preterm/low birthweight also has been found on the WISC-III at ages 7 to 11 (Kesler et al, 2004). These variable findings may be partially related to some of the methodological issues in the study of children born prematurely that were identified earlier, but the precise reasons for these variable findings is unclear, particularly since there are contradictory patterns across publication dates (and periods of medical care), similar measures, and study samples with similar and different inclusion criteria. Specific Cognitive Deficits in Preterm Children. As noted by Aylward (2002a), "an area IQ/standard score is the average of various subtests and is therefore subject to wide variation among those subtests; a full scale IQ or 19 composite score is an average of averages, and would further mask more subtle findings" (pp. 234). Many of the previous measures used to assess individual cognitive abilities in children born prematurely are those that emphasize global intelligence (or cognitive abilities), and thus may not be sensitive to the unique cognitive deficits of preterm children, especially in infancy and the preschool years when such deficits may be more subtle (Dumont & Willis, 1995; Kalmar, 1996). Children born prematurely with normal intelligence are commonly reported to have specific difficulties with memory, spatial abilities, attention, executive function, and fine/gross motor function (Breslau, Chilcoat, Johnson, Andreski, & Lucia, 2000), with such findings confirmed in a meta-analysis of school-aged children born prematurely (Bhutta, Cleves, Casey, Cradock & Anand, 2002). As no publications using a Cattell-Horn-Carroll approach to the understanding of preterm outcomes were identified, the literature was reviewed using a cross-battery approach (Flanagan & Ortiz, 2001), based on psychological test content; many studies, however, failed to report mean performance on subtests or subscales, which are typically interpreted as more specific measures of individual cognitive abilities. It is for this reason (that most published studies were found to report findings at the global IQ and cluster or composite score levels, rather than at the subtest level) that the focus of this investigation was upon CHC broad abilities, rather than more specific narrow abilities. Auditory Processing Abilities. Limited findings were available regarding the ability of preschool-aged children born prematurely to process and manipulate linguistic sounds (Ga). On a series of unstandardized phonological processing tasks, preterm children demonstrated two to three times the level of significant impairment compared to controls (Wolke & Meyer, 1999). Holdgrafter (1995) also found delayed phonological development in preterm children at age 3-5 years on a series of measures. Phonological processing was also observed to be impaired in 20 children born prematurely at age 5-9 years on several subtests of the NEPSY (Korkman, Liikanen, & Fellman, 1996). Crystallized Abilities. Literature regarding the verbal-comprehension (Gc) or language outcomes of preschool-aged children born prematurely is somewhat unclear. More rudimentary language abilities such as vocabulary, which are often reflective of test content in language measures commonly used with young children, appear to be relatively intact (Dammann et al, 1996; Luoma, Herrgard, Martikainen, & Ahonen, 1998; Taylor, Klein & Hack, 1994). The mean Peabody Picture Vocabulary Test score was non-significantly lower by four points for preterm versus full controls at five years of age in Siegel (1982); in the same study, no differences were found on one measure of grammar, but significant differences were observed on a measure of receptive grammar (Northwestern Syntax Screening Test, 1969) and a general measure of language development (Reynell Developmental Language Scales, 1969). Similarly, the performance of five and a half-year-old preterm children was poorer only on the more complex verbal tasks of the WPPSI-R (Bohm et al, 2002); After accounting for the effects of global IQ scores and socio-economic status, older children born prematurely do display deficits in more complex language abilities, such as mean length of utterance, syntax/verb production and comprehension, verbal reasoning, and extended language comprehension (Aylward, 2002; see also Barksley & Siegel, 1992; Frisk & Whyte, 1994; Robison & Gonzalez, 1999). Fluid Reasoning Abilities. Fluid reasoning abilities (Gf) appear to be consistently problematic for children born prematurely. The Performance Intelligent Quotient (WPPSI-R), which includes non-verbal reasoning and visual-motor reasoning tasks, was 17 points lower on average for preterm children at 5 V2 years in Bohm et al (2002), and similarly lower on the WPPSI and WISC-R for preterm children aged 5-9 years (Korkman et al, 1996; McGrath & Sullivan, 2002). In children with gestational ages of less than 32 weeks at age six years, fluid 21 reasoning deficits were found on the Kaufman Assessment Battery for Children Simultaneous Processing Scale (Wolke & Meyer, 1999), which involves tasks related to visual-spatial recognition, pattern building and memory, and logical reasoning. Forslund and Bjerre (1990) also report deficits in the practical reasoning and performance abilities on the Griffiths Developmental Scale of children < 35 weeks GA at 4 years, but did not specify which tasks were used. Visual-Spatial Abilities. Understanding of the visual-spatial abilities (Gv) of children born prematurely is complex, due to the fact that many studies have employed tasks which use both visual and motor components, or visual and reasoning components, thereby confounding interpretation of the results given the established reasoning and motor deficits of preterm children (Aylward, 2002a). General visual-motor perception has been found to be deficient in children born prematurely on the Performance scales of the Weschler tests (Bohm et al, 2002; Korkman, et al, 1996; McGrath & Sullivan, 2002), which measure fluid reasoning, visual-spatial abilities and visual-motor coordination (Flanagan & Ortiz, 2001). In addition to deficits found on tasks simultaneously measuring coordinated use of visual and motor abilities, preterm children have been found to demonstrate deficits on tasks that measure visual-spatial abilities alone. Preterm children between the ages of three and seven years demonstrated visual-spatial difficulties on the Developmental Test of Visual Perception, 2nd Edition (Hammill, Pearson & Voress, 1992), the visual-spatial tests of the NEPSY (Herrgard, Luoma, Tuppurainen, Karjalainen, & Martikainen, 1993), and on the Bruininks Test of Visual-Perceptual Skills (Bruinicks, 1978; Feder et al, 2005). Kessenich (2003) also found that preterm/LBW children scored lower on tasks involving spatial relations, shape rotation, and line slopes, but that children with a history periventricular lesions performed more poorly than children born prematurely with or without intraventricular cerebral lesions. Waber and 22 McCormick (1995) found the processing of simpler visual-spatial stimuli to be intact in older (7-10-year-old) children born prematurely, but significant deficits on tasks requiring more complex visual-spatial processing (e.g., the Rey-Osterrieth Complex Figure), which also requires coordination between the visual-spatial system and multiple other cognitive functions. In contrast, limited information has been published regarding the visual memory abilities of premature children. Spatial recognition memory was reported to be fairly intact in children born prematurely, but they have been observed to have weaker spatial memory span and spatial working memory difficulties, particularly on tasks involving longer delays between stimuli exposure and response (Lucianna, Lindeke, Georgieff, Mills, and Nelson, 1999) Short-Term Memory Abilities. Results from previous measurements of short term memory (Gsm) in children born prematurely are contradictory. The most commonly reported finding is that children born prematurely do not display any deficits in short term recall or memory span for auditory information, such as simple lists, digits or prose (Hack et al, 1995; Herrgard et al, 1993). Other studies, however, such as Briscoe, Gathercole, and Marlow (1998), suggest that short term verbal memory of children born prematurely is impaired on more naturalistic or everyday tasks, even in children born 28-32 weeks gestational during the preschool years. Lucianna et al (1999) similarly found that preterm children specifically display deficits on memory tasks when the difficulty is increased (e.g., with spans above three or four items). Results from studies with school-age children also indicate that older children born prematurely score lower on very working memory tasks (Anderson & Doyle, 2003; Frisk & Whyte, 1999). Taylor et al (2002) also found lower but non-significant differences in verbal working memory between children born pre and full term at a mean age of 11 years. Long Term Storage and Retrieval Abilities. Limited findings are available regarding the Long Term Storage and Retrieval (Glr) abilities of children born prematurely. Six-year-old . 23 preterm children performed more poorly on the K - A B C Simultaneous versus Sequential Processing subtests, suggesting deficits in Glr abilities during the preschool years (Wolke & Meyer, 1999). School-aged children born preterm/LBW demonstrated significantly lower delayed recall and retrieval scores on the California Verbal Learning Test-Children's Version ( C V L T - C ; Taylor, Kle in , Minish , & Hack, 2000), also indicating possible deficits in Glr abilities. Older children born prematurely (mean age 11 years) were found to perform more poorly on several tasks of learning and longer term memory, but these deficits were also related to overall levels of intelligence (Hack et al, 2002). Processing Speed Abilities. Limited findings are available regarding the processing speed abilities (Gs) of children born prematurely. Processing speed deficits have been observed in children born prematurely at six years on standardized assessment of rapid number naming on the K - A B C , after controlling for global cognitive ability (Wolke & Meyer, 1999; Luoma et al , 1998). Bohm et al (2002) and Korkman et al (1996) also found that five to nine-year-old children born prematurely were significantly slower on several N E P S Y tests that measure processing speed (Verbal Fluency, Naming). Bohm et al also found deficits on the WPPSI-R Animal Pegs test, although eight-year-old children born prematurely scored only 2-3 points lower on the processing speed tests of the WISC-R (Anderson & Doyle, 2003). Rose and Feldman (1996) also found significant deficits in children born prematurely on experimental processing speed tasks, but at age 11 years. Executive Function Abilities. Although executive functioning is not identified as a specific cognitive factor according C H C theory, it is considered in different ways within the C H C model. Given the more recent developments in understanding the role of executive functioning and self-regulation in academic performance (Blair, 2003; Normandeau & Guay, 1998), it is briefly reviewed here as another subheading of the specific cognitive abilities section of this review. Deficits in executive function (EF), including higher-order attention, planning, inhibition, and shifting, are perhaps one of the most consistently documented impairments in preschool-aged children born prematurely. Children born prematurely demonstrated deficits on the Tower of Hanoi and Lurian sequencing tasks (Harvey, O'Callaghan, & Mohay, 1999) at 5 years, on the Tower of London and NEPSY EF tasks, particularly those that tap sustained attention and inhibition, at 5 XA years (Bohm et al, 2002), although Herrgard et al (1993) found equivalent performances on NEPSY attentions tasks in children born pre versus full term. Similar deficits in visual scanning and sustained attention were also found at age 3-4 years on the Leiter-R Sustained Attention tests (Vicari, Caravale, Carlesimo, Casadei & Allemand, 2004), although such tasks also tap motor speed which as mentioned above, is known to be impaired in children born prematurely. Executive function deficits have also been documented in older children born prematurely (Anderson, 2004; Korkman et al, 1996; Lucianna et al, 1999), and on experimental measures of EF (Andrews-Espy, Stalets, McDiarmid, et al, 2002). Academic Deficits of Children Born Prematurely. Global Academic Deficits. No studies were identified as reporting results for global or overall academic outcomes in children born prematurely of or near a preschool age, although poorer overall academic outcomes for older children born prematurely/LBW, even with normal intelligence, are well-established (Grunau, Whitfield & Davis, 2002; Klevanov, Brooks-Gunn & McCormick, 1994). Similarly, most studies of preschool-aged preterm children only reported administering a select number of academic skills tests from one or more standardized batteries. In the areas of reading and spelling, available findings for preschool-aged children contrast with older children born prematurely; it is unclear whether this is due 25 to a true absence of such deficits, the difficulty in defining and measuring early academic achievement, later emergence of academic deficits in children born prematurely, or to the historically poor psychometric properties of academic achievement measures for younger relative to older children. Specific Academic Difficulties of Children Born Prematurely Academic Abilities: Reading. Recent findings do not indicate that preschool-aged children born prematurely have significant impairments in early reading abilities. On a combination measure of basic reading and reading comprehension (averaged performance on the Woodcock-Johnson-Revised Letter-Word Identification test and the Wechsler Individual Achievment Test Reading Comprehension subtest), preschool and kindergarten-aged children born prematurely performed well as full term children (Litt, Taylor, Klen & Hack, 2005). Waber and McCormick (1995) similarly found the performance of children born prematurely/low birth weight to be in the average range on the Woodcock Johnson Psychoeducational Battery Reading cluster at age 5 to 7 years. Kesler et al (2004) found no differences between pre and full term children on the Peabody Individual Achievement-Revised (PIAT-R) reading recognition and comprehension subtests at 7-11 years. These findings for preschool-aged children born prematurely contrast with findings for older children who were born prematurely. At ages 11 and older, children born prematurely performed more poorly on the WJ-R Word Identification test by 10 to 6 points (Taylor et al, 2000), and on the Wide Range Achievement Test-3 (WRAT-3) by 8 to 6 points (Sullivan and McGrath, 2003). Similarly, 8-year-old extremely preterm children scored significantly lower in Basic Reading skills, Reading Comprehension and overall on the Woodcock Reading Mastery Test (Bowen, Gibson & Hand, 2002). 26 Academic Abilities: Spelling and Writing. Research findings on the early writing abilities of children born prematurely should be interpreted in the context of other literature on their fine motor and visual-motor coordination functioning, which strongly indicates related impairments and delays in this area. Motor deficits were found on neurological examination at age 5 (Herrgard et al , 1993), the McCarthy Motor Scale and Ri ley Motor Problem Scale at age 4 (Sullivan and McGrath, 2003), in 65% of the children assessed on Peabody Developmental Motor Scales at age 5 (Goyen & Lu i , 2002), on the Bruinicks-Oseretsky Fine Motor tests at age 6-7 (Feder et al , 2005), on the Movement A B C at various ages (Bracewell and Marlow, 2002), and on various fine motor tasks at age 7 (Samson et al, 2002). Specific eye-hand coordination deficits were found on Griffiths eye hand coordination subscale age 4 (Forslund & Bjerre, 1990), on the N E P S Y at age 5 (Herrgard et al , 1993). Findings consistently indicate that children born prematurely/LBW exhibit deficits related to writing and spelling. Numerous studies demonstrate that children born prematurely perform more poorly on specific tests of drawing, copying and writing, such as on the N E P S Y (Herrgard et al , 1993) or various editions of the Test of Visual Motor Integration (VMI) , with significant impairments on the latter being documented at 4 years (Sullivan & McGrath, 2003), 5 years (Siegel, 1982), 6 years (Jongmans, Mercuri, Dubowitz, & Henderson, 1998). Six- and seven-year-old preterm children were also reported to have significantly slower writing speed, and poorer general handwriting skills on the Evaluation Tool o f Children's Handwriting-Manuscript (Feder et a l , 2005). Only one study was identified as specifically examining the early spelling skills o f preterm children at ages less than 7 years, where preterm/LBW children were reported to be twice as l ikely to perform poorly on WJ -R Revised Dictation test (Taylor, K le in , Schatschneider & Hack, 1998). At ages seven and eight respectively, children born prematurely scored lower than expected by 8 to 4 points on the W R A T - 3 Spelling section (Anderson & Doyle, 2005; McGrath & Sullivan, 2002; Sullivan & McGrath, 2003), and by 9 points on the South Australian Spelling Quotient (Bowen et al, 2002). Academic Abilities: Mathematical Knowledge. Preterm children are consistently reported to have early delays and learning difficulties with both mathematical computation and mathematical reasoning. Significant deficits were found at eight years on the Woodcock Johnson-Revised (WJ-R) Calculation test (6 points below average, Assel et al, 2001), and at 5 to 7 years on the Woodcock Johnson Psychoeducational Battery Mathematics cluster (4 to 8 points for children under l,500grams, Waber & McCormick, 1995). Litt et al (2005) also found that 11 -year-old preterm children born 28 weeks or less had scores lower by 6 points on average on the WJ-R Broad Mathematics score, but that the mathematical skills of preterm/low birth weight children born 28 weeks or later were in the average range. Minimal (2 point) but significant differences were found were found between eight-year-old full and preterm children on the Quantitative Reasoning subtest of the Stanford-Binet, 4th Edition (Assel etal., 2001). In conclusion, preterm children are one of the most common at-risk groups for whom early medical and psychoeducational assessment is indicated, but the early cognitive and learning difficulties of preterm children can be easily overlooked by pediatricians and other practitioners (de Kleine et al, 2003). Although these difficulties are sometimes detectable with highly specialized neuropsychological diagnostic tools, such tools are not practical for routine cognitive, developmental or academic assessments. Research by Wolke, Ratschinski, Ohrt, and Riegel (1994) indicates that the inadequate technical properties of early assessment instruments can lead to large underestimations of cognitive impairments in preterm children, thus indicating need for improved diagnostic instruments. With its inclusion of a wider range of empirically validated cognitive abilities that can be interpreted at the factor level and strong technical 28 properties at younger age ranges, the WJ III holds promise for use with children born prematurely of a preschool age. Further research with the WJ III and clinical populations of a younger age such as preterm birth was warranted, given that 1) standardized psycho-educational measures are often used to identify children for early special education services in both Canada and the United States; 2) any of the currently available cognitive and academic measures for young children have been criticized for their poor psychometric properties and the limited number of cognitive abilities that they evaluate; 3) the current edition of the WJ III includes two subsets of scores deemed specifically appropriate for use with preschool-aged children; and 4) no published studies are available the utility of this tool with a clinical populations of preschool age. Accordingly, the primary purpose of this study was to explore the use of the WJ III with a sample of preschool age children born premature. The following research questions were addressed, and based upon the previous literature findings, the following outcomes were anticipated: 6. What was the relationship of global intellectual ability, as measured by the GIA-EDev Standard Score, of children born prematurely compared to a matched sample of children from the standardization sample? Anticipated Outcome: A difference in the score distributions was expected, and children born prematurely were expected to score lower than matched children from the WJ III COG standardization sample. 7. What was the relationship of broad cognitive abilities, as measured on WJ III COG, including Auditory Processing (measured by Test 8: Incomplete Words), Crystallized Abilities as measured by Test 1: Verbal Comprehension), Fluid Reasoning (as measured by Test 5: Concept Formation), Visual-Spatial Processing (as measured by the Test 22: 29 Visual Closure), Short-Term Memory (as measured by Test 27: Memory for Words), Long Term Memory & Retrieval (as measured by Test 22: Memory for Names), and Processing Speed (as measured by Test 5: Visual Matching), of children born prematurely compared to a matched sample of children from the standardization sample? Anticipated outcomes: No differences were expected between the score distributions of children born prematurely versus the matched sample on the WJ III COG tests of Crystallized Intelligence (Verbal Comprehension) and Short Term Memory (Memory for Sentences). Correlations were expected between birth status and performance on the WJ III COG test of Auditory Processing (Incomplete Words), Fluid Reasoning (Concept Formation), and Processing Speed (Visual Matching), Visual-Spatial Abilities (Visual Closure), and Long-Term Retrieval and Storage (Memory for Names), with children born prematurely scoring lower than matched children from the WJ III COG standardization sample. 8. What was the relationship of global pre-academic abilities, as measured by the Woodcock-Johnson III Tests of Achievement Pre-Academic Skills-Standard (Pre-Ach-Std) score, of children born prematurely compared to a matched sample of children from the standardization sample? Anticipated Outcome: A difference in the score distributions was expected, and children born prematurely were expected to score lower than matched children from the WJ III COG standardization sample. 9. What was the relationship of specific early academic skills measured by the Woodcock-Johnson III Tests of Achievement, including early reading skills (as measured by Test 1: Letter-Word Identification, and Test 14: Picture Vocabulary), early writing skills (as measured by Test 7: Spelling), early mathematical skills (as measured by Test 10: 30 Applied Problems), of children born prematurely compared to a matched sample of children from the standardization sample? Anticipated Outcome: No differences were expected in the score distribution of children born prematurely versus a matched sample on the WJ III A CH Letter- Word Identification and Picture Vocabulary tests. Differences were expected between the score distributions of the WJ III ACH Spelling test and the WJ III Applied Problems test, with children born prematurely scoring lower than the matched sample of children from the WJ III standardization sample. 10. Among children born prematurely, what is the relationship of the Woodcock-Johnson III Tests of Cognitive Abilities General Intellectual Ability-Early Development (GIA-EDev) Standard Score, the individual Woodcock-Johnson III EDev tests (as listed in research question 2), the Woodcock-Johnson III Tests of Achievement Pre-Academic Skills-Standard, and the individual Woodcock-Johnson III Tests of Academic Achievement (as listed in research question 4) with cumulative perinatal risk factors, as measured by overall risk score on the Maternal Perinatal Scale? Anticipated Outcome: An inverse correlation was expected between cumulative perinatal risk factors and performance on the WJ III tests, with children born prematurely with higher levels ofperinatal risk factors scoring lower than children born prematurely with lower levels of perinatal risk. 31 Table 2.1 Broad Cognitive and Academic Abilities in the Catttell-Horn-Carroll Framework Acronym Factor Description Gc Acculturated Knowledge Verbal abilities (e.g. language development), and store of general information and acquired knowledge Gf Fluid Reasoning Reasoning or problems solving abilities, particularly with abstract or novel information Glr Long Term Retrieval Ability to store and later retrieve information in memory Gsm Short Term Memory Memory span and working memory abilities, or ability to hold and use information in immediate awareness Gv Visual-Spatial Processing Ability to perceive, analyze, synthesize and think with visual patterns, including spatial memory Ga Auditory Processing Ability to perceive, analyze, synthesize and discriminate both linguistic and non-linguistic auditory sounds Gs Processing Speed Performance speed and efficiency on automatic tasks Gq Quantitative Reasoning Acquired knowledge to use quantitative information and manipulate numeric symbols. Grw Reading and Writing Acquired knowledge required for the comprehension of written language and expression of thought in written form. 'Adapted from Mather & Jaffe (2005, pp.6). CHAPTER THREE Methodology Participants Recruitment of Sample. Recruitment of Children Born Prematurely. Upon receiving approval from the UBC Behavioural Research Ethics Board (BREB) and the Research Review Board of BC Children's Hospital, participants were recruited from three primary sources: the Special Care Nursery and Neo-Natal Follow-up Unit at BC Children's Hospital, through newspaper advertisement and recruitment posters. The Special Care Nursery and Neo-Natal Follow-up Unit maintain a registry of children born under high risk conditions in the British Columbia mainland since 1983, including premature birth or low birthweight. Clinic staff reviewed the registry, and designated a select number of clinic patients as both meeting the study criteria (gestational age of 37 weeks or less, and no history of congenital abnormalities, e.g., genetic disorders, significant early physical health problems, e.g., grade four cerebral palsy, mental retardation, blindness or substantial hearing loss) and appropriate to solicit for participation. The families of 29 children were identified and mailed a letter of an invitation to participate (Appendix A). If no responses to the letters were received after approximately three weeks, clinic staff contacted the families with several follow-up phone calls. As a result of the phone contacts, the contact information was found to be incorrect for six families, three families were geographically too far away for the assessment (e.g., over 300 kilometers away), three families did not respond and four declined to participate. The child of one family contacted was beyond the study age range at the time that the family responded, and the child of one other family contacted did not speak an adequate level of English to participate. In sum, 11 33 families recruited from the Special Care Nursery and Neo-Natal Follow-Up Unit agreed to participate in the study. A recruitment advertisement (Appendix B) was placed in the local newspaper which resulted in three additional participants. Recruitment posters were also displayed at six health centres, five child development centers, two child development associations, six family centers, four daycares and three other locations (e.g., obstetrics and pediatric clinics) in the Lower Mainland, from which two other participants were identified. Nine other agencies were contacted but declined to display study recruitment posters. Selection of Matched Sample. A matched sample of children was selected from the WJ III standardization sample on the basis of (in order): chronological age in months, highest level of parental education in the home (father or mother), sex and race.1 Four of the preterm participants had multiple possible matches in the standardization sample, from which their specific match for the present study were randomly selected. Perfect matches, using the match criteria (chronological age levels of both maternal and paternal education, sex and race), were available for four cases, ten cases matched on four variables, and two cases matched on three of the four variables (age, parental education and sex, but not race). Characteristics of Sample Sample of Children Born Prematurely. The final sample of children born prematurely for this pilot investigation was 16 children living in the lower mainland of British Columbia. The sample included seven males (43.8%) and nine females (56.3%). Eighty-one percent of the sample was Caucasian, with one instance each of (6.3%) of East Indian, First Nations and black heritage; one child was reported to be part Chinese and part Caucasian (Table 3.1). Two females 1 "Race" was used as a match criterion to represent both race and ethnicity. This was the definition used in the WJ III Standardization sample, consistent with US Census approaches. The most notable difference in this characterization is that Hispanic heritage is treated separately as an ethnic rather than a racial category. The researcher is aware that this approach would not be the most typical way to characterized race or ethnicity within the Canadian context; however, this was the approach used in the WJ 1111 standardization 34 were reported by their families to be functionally bilingual in both French and English. The sample ranged in age from 4 years, 7 months to 5 years, 10 months, with an average age of 61 months (SD= 6 months; Table 3.2). As indicated in Table 3.3, the gross family income of the preterm sample was between $30,000 and $39,999 in 3 families (18.8%), between $40,000 and $49,999 in three families (18.8%), and in the majority of cases (10), exceeded $60,000 (62.6%). Five (31.3%) mothers reported as completing at least some high school, another five (31/3%) reported completion of 1-3 years of college, and 6 (37.5%) reported completion of a bachelors' degree or higher. The majority (n=9) of the mothers of the participants did not work outside the home (56.3%), whereas two worked in professional/ managerial positions (12.5%), four worked in technical, sales or administrative positions (25%) and one worked in the service industry (6.3%). Fathers of the sample participants displayed similarly high levels of education and employment. One father completed less than high school (6.3%), while seven fathers had completed 1-3 years of college (43.8%) and seven had at least a bachelors' degree (43.8%o). The majority (n=7) of fathers were employed in professional or managerial positions (43.8%), with four others in technical, sales and administrative positions (25%), two in trades (12.5%), and one each in the service industry or as a labourer (6.3% each). As indicated in Table 3.4, the sample gestational age ranged from 25 to 36 weeks, with an average gestational age of 28.4 weeks (SD=3.52 weeks), with the majority of the sample (n=T 1) born at 29 weeks or less gestational age. Four out of the 16 children were born small for their gestational age, or with low birth weight (2 males, 2 females). The average birth weight was 1375.56 (SD=791.91) grams. Half of the sample (n=8) had a birthweight under 1,000 grams, with four instances of birthweight between 1,000 and 1,5000 grams, and four instances of birthweight over 1,500 grams. Characteristics of Matched Sample. Children in the WJ III Standardization sample were not screened for prematurity of birth, but were considered to be normally developing. The matched sample included seven males (43.8%) and nine females (56.3%). Eighty-one percent of the matched sample was Caucasian, with one instance of (6.3%) of Native American heritage and two instances of black heritage (Table 3.1). The age of the matched sample ranged from 4 years, 7 months to 5 years, 10 months, with an average age of 61 months (SD= 6 months; Table 3.2). Data on family income of the individuals in the matched sample was not available. Three (18.7%) mothers reported as completing at least some high school, another eight (50%) reported completion of 1-3 years of college, and five (31.3%) reported completion of a bachelors' degree or higher. Five of the mothers of the matched sample did not work outside the home (31.3%), while five worked in professional/ managerial positions (31.3%), four worked in technical, sales or administrative positions (25%) and two worked in the service industry (12.5%). Fathers of the sample participants displayed relatively high levels of education and employment. Two fathers completed at least high school (12.5%), while 3 fathers had completed 1-3 years of college (18.8%) and the majority (n=l 1) had at least a bachelors' degree (68.8%). The majority (n=6) of fathers were employed in professional or managerial positions (37.5%), with 3 others employed in technical, sales and administrative positions (18.8%), two in trades (12.5%), two in the service industry (12.5%), one as laborer (6.3%), and for two cases paternal employment data was not provided. Instrumentation Woodcock-Johnson Third Edition The Woodcock Johnson-Third Edition (WJ III, Woodcock, McGrew & Mather, 2001) was designed for conducting psychological and/or educational assessments with individuals ages 2 through 80+ years of age. The WJ III may be used in its entirety or its individual components may be used independently. The WJ III involves the use of several independent but complementary, individually administered, standardized assessment tools: the Woodcock-Johnson III Tests of Cognitive Abilities (WJ III COG; Woodcock et al., 2000), Woodcock-Johnson III Diagnostic Supplement to the Tests of Cognitive Abilities (WJ III DS; Woodcock, McGrew, Mather, & Schrank, 2003), and the Woodcock-Johnson III Tests of Academic Achievement (WJ III ACH; Woodcock, McGrew, & Mather, 2001). The WJ III COG, the WJ III DS and the WJ III ACH raw scores are converted to a range of scores including standard scores, percentile ranks, grade equivalents, age equivalents, and criterion or Rasch-based W scores. Standard scores were used in this investigation, which have a mean score of 100 and a standard deviation of 15 points on a normal curve distribution. The Woodcock-Johnson III: Tests of Cognitive Abilities and the Diagnostic Supplement to the Woodcock-Johnson III Tests of Cognitive Abilities and Woodcock-Johnson III Tests of Achievement. The WJ III COG, the WJIII DS and the WJIII ACH are individually administered, standardized tests of cognitive functioning and achievement (Schrank, Mather, McGrew, & Woodcock, 2003; Woodcock et al., 2000). The WJ III COG, WJ III DS, and the WJIII ACH contain 20, 11 and 22 tests respectively, with each test measuring a different aspect of cognitive ability based on the Cattell-Horn-Carroll (CHC) model. The WJ III COG provides two primary indices of global cognitive ability, the General Intellectual Ability-Standard and the General Intellectual Ability-Extended, which are derived from a weighted average of tests scores for different broad cognitive abilities or factors: Comprehension-Knowledge, Visual-Spatial Thinking, Auditory Processing, Fluid Reasoning, Processing Speed, Long-Term Retrieval, and Short-Term Memory. 37 The General Intellectual Ability- Early Development (GIA-EDev) is available when the WJ III COG is used in conjunction with select supplemental tests of the WJ III Diagnostic Supplement (DS), and is derived from measures of the six CHC abilities that are thought to be most reflective of the cognitive abilities of young children (Table 3.3). The tests used to calculate the GIA-EDev were designed to be "particularly appropriate for evaluation of developmental delay in the cognitive domain [of preschool children] (Ford, 2003, p. 44). In addition to the six tests used to calculate the GIA-EDev (Test 1: Verbal Comprehension, Test 6: Visual Matching, Test 8: Incomplete Words, Test 21: Memory for Names, Test 22: Visual Closure & Test 27: Memory for Sentences) Test 5: Concept Formation from the WJII COG was also administered as a measure of Fluid Reasoning for younger children. The WJ III ACH assesses achievement in the areas of reading, oral language, mathematics, written language, and academic knowledge. In the present study, an attempt was made to identify the tests most appropriate for use with preschool as children. The three tests from the WJ III ACH (Test 1: Letter-Word Identification, Test 7: Spelling, and Test 10: Applied Problems) that are used to calculate the Pre-Academic-Standard (WJIII Pre-Std) cluster were administered, along with Test 14: Picture Vocabulary and Test 18: Quantitative Concepts. Characteristics of the Pre-Academic-Standard are presented in Table 3.4. Psychometric Characteristics of the WJIII COG, WJIII DS & WJ III ACH. Psychometric data for children in the standardization sample is reported and summarized in Tables 3.5 and 3.6. The reliability of the GIA-EDev for the standardization sample was reported to be .95 and .93 for children df 4 and 5 years of age, respectively (Schrank et al., 2003). Available one to two year test-retest reliabilities ranged from .71 to .82 (McGrew & Woodcock, 2000). The test floors for the Early Development score ranged from three years, two months to four years, eight months, 38 while test floor for Test 5: Concept Formation was reported to be five years, four months (Table 3.3, Ford, Kozey, Merkel & Swart, 2005; Tusing et al., 2003). The internal consistency for the WJIII Pre-Std cluster score was reported to be 0.96 for children of 4 and 5 years of age (McGrew & Woodcock, 2001). Reliabilities for the individual WJ III ACH tests used in this study range from .81 to .99 for children 4 and 5 years of age in the standardization sample. Available one to two year test-retest reliabilities ranged from .84 to .91 (McGrew & Woodcock, 2001). The test floors for the individual achievement tests administered in this study range from two years, eight months to three years, eight months (Table 3.6, Tusing et al., 2003). Psychometric Characteristics of the WJIII COG, DS, ACH with Current Sample of Preterm Children. An attempt was made to determine whether the WJ III COG, DS and ACH scores and tests were psychometrically reliable instrument with the current sample of preterm children by duplicating the reliability procedures used by the test authors (McGrew & Woodcock, 2001). Calculation of the reliability of the GIA-EDev score, two individual cognitive tests (Test 6: Visual Matching, a speeded test; Test 27: Memory for Sentences, a non-dichotomous test with a response format that has a variable value across items) and the Pre-Ach-Std with the current sample was not possible within the context of this study. For these two cluster scores and individual tests, the test authors use a series of specific calculations (McGrew & Woodcock, 2001, pp.33-38) that are not executable with the computer software program used in this study (SPSS); similarly, the current data was not feasibly exportable to the only software in which these calculations are executable (DOS BASIC), which would have required contracting of the a mathematical computer programmer to complete (K. McGrew, personal communication, March 6, 2006). The current study author was able to duplicate the split-half, odd-even with Spearman-Brown correction procedures used by the test authors to calculate the internal consistency values for the other individual WJ III COG, DS and ACH tests administered 39 in this sample.2 However, these results were calculated based on a small sample (N=16) that had limited socio-economic and racial diversity, and demonstrated lower variability in its response patterns to items on the individual tests. As internal consistency calculations are based upon the variability of responses on items within a sample (Cohen, Swerdlik & Phillips, 1996), the current results can be interpreted as reflective of the sample variability itself, rather than a valid estimate of the reliability of the instrument, and thus an accurate estimate of the reliability of the WJ III COG and DS with the current sample was not possible. Maternal Perinatal Scale The Material Perinatal Scale (MPS; Dean & Gray, 1985) is structured, 47 item self-report measure and was used to record information about peri-natal events. Twenty-six items on the MPS elicit information about peri-natal history including pregnancy events, labour and delivery, and the remaining 21 items inquire about maternal medical history. The MPS asks respondents to provide ratings of facts (e.g., as true or false), rather than respond open-ended questions with detailed information. MPS items are rated on either a continuum of 1.0 to 5.0, or a nominal scale (true or false), and can be used to calculate relative risk ratios (Minick-Vanhorn, Titus, & Dean, 2002). The MPS has been reported to have high test-retest stability (Gray, Dean, & Rattan, 1987) and validity, with a high correlation to medical chart information r=.91 (Gray, Dean, Rattan, & Bechtel, 1988). The MPS has been used in studies that examined specific outcomes of premature birth and full term birth with perinatal complications concurrently, but no studies were identified as using the MPS to exclusively examine the general perinatal complications of premature birth or the outcomes children born prematurely. The MPS has been found to distinguish between normal children and those with 2 The Spearman-Brown reliability coefficient with the preterm sample was found to be .96 for Test I: Verbal Comprehension, .68 for Test 8: Incomplete Words, .96 for Test 21: Memory for Names, .85 for Test 22: Visual Closure, and .90 for Test 5: Concept Formation. The Spearman-Brown reliability coefficient with the preterm sample was found to be .96 for Test 1: Letter-Word Identification, .99 for Test 7: Spelling, .95 for Test 10: Applied Problems, and .83 for Test 14: Picture Vocabulary. learning disabilities (Hill, Cawthorne, & Dean, 1998), and to predict developmental disabilities (Gray, Dean, Strom, & Wheeler, 1989), school achievement (Gray, Davis, McCoy, & Dean, 1992), developmental functioning (Gatten, Arceneaux, Dean, & Anderson, 1994), neuropsychological outcome in children with learning disabilities (Ma, 1997), educational placement (Minick-Vanhorn et al., 2002; Vanhorn, 2000), and infantile autism (Wilkerson, Volpe, Dean, & Titus, 2002). Scoring of the Maternal Perinatal Scale. Maternal responses to the MPS have been used in different ways to examine the relationship between reported perinatal risk factors to various outcomes, either by relating the endorsement of specific items to outcomes, or by computing a relative risk ratio based upon a select number of items on the scale.(e.g., Minick-Vanhorn, Titus & Dean, 2002). At an item level, lower scores on the MPS are considered to be indicative of less risk, as outlined in Minick-Vanhorn et al., (2002). In the context of this study, a cumulative perinatal risk score was calculated based upon the sum total of the values associated with responses to the individual items on the MPS, with items 6, 7, 9, 11, 18, 20, 21 and 22 rated either as reversal items (e.g., endorsement of the first choice was awarded a value of three, endorsement of the second choice was awarded a value of two, endorsement of the third choice was awarded a value of one, and endorsement of the fourth choice was awarded a value of zero), or with a weighting alternate to the order on the questionnaire. The latter scoring procedure was used for several reasons. Information regarding scoring at the item level of the MPS was not provided with the MPS itself or in the available publications related to the MPS, and the author of the MPS was asked to but was not able to provide detailed information on the alternative approaches to scoring the MPS. Moreover, the maternal respondents in this study endorsed an extremely limited number of items associated with increased peri-natal risk (see Chapter 4), which did not warrant a 41 factor-based or a multivariate approach to scoring the MPS (e.g., Minick-Vanhorn, Titus & Dean, 2002).3 In the context of this study, the decision to rate individual item choices as indicative of lower versus higher risk (and the decision to score specific items as reverse items) was reviewed with a registered nurse specializing in newborn care services from the BC Children's Hospital. Items 1 to 26 were scored using values that ranged from zero to five (depending upon the number of choices associated with each item), and items 27 through 47 were scored as having values of either 0 or 1. Study Questionnaire Parents were asked to complete a background information questionnaire created by the study investigators (Appendix D). General demographic information on the child and the family, including race/ethnicity, the role of the parent in relation to the child, the composition of the family in the home, family income and parental education was provided. Procedures Preterm Sample Participant Recruitment The study received approval from the British Columbia Behavioural Research Ethics Board and the Hospital Research Review Board at BC Children's Hospital (with Dr. Anne Synnes of the NeoNatal Followup Clinic and Special Care Nursery acting as the site investigator). Using the recruitment procedures detailed earlier, interested families were invited to contact the study coordinator by mail or telephone, or alternatively gave permission for the NFU clinic staff to release contact information directly to the study coordinator. An initial telephone interview screen was conducted with interested parents, to determine the eligibility of the child for the study and to schedule an initial testing appointment if appropriate. 3 An attempt was made to use the data reduction method Principal Component Analysis with the individual MPS items, which would have allowed for the items to be weighted according to their relationship to the other items and a possible total score. However, this procedure was not possible due to zero variance on numerous items. Assessment Informed consent was obtained, and testing was conducted in the homes of the participants (13 participants) or at the Psychological Research and Training Centre at the University of British Columbia (3 participants). Direct assessment of the preschool age children in the preterm sample was conducted by the investigator or a research assistant. The testing was completed in one visit for three of the participants, two visits for 12 of the participants, and three visits for one participant. Each visit took approximately two hours, plus breaks as the children required. A set test administration order was generally used, with the children completing the WJ III COG EDev tests first, then the WJ III A C H tests, followed by Test 5: Concept Formation and other supplemental WJ III COG tests not presented in this study. Exceptions to the set administration order occurred only when a child refused to complete an individual test, whereupon administration of that particular test was temporarily abandoned but returned to as soon as possible. Two children did not complete the WJ III COG Test 5: Concept Formation and the WJ III A C H Test 14: Picture Vocabulary due to fatigue and refusal to continue testing. The mother of one child was unable to complete the Maternal Perinatal Questionnaire, as the child had been adopted with limited perinatal birth information available to the parents. The child was provided with several small toys (e.g., stickers) during participation, and a book at the completion of testing. Parents of the participants were provided with $25.00 as a thank-you, and a brief written summary of findings regarding the performance of their child. The Dean-Woodcock Sensory-Motor Battery was also administered to all participants on a separate visit, but these results are not included in the present study. .43 Analysis In this study, participants' performance was scored using norms for their chronological age.4 Raw data gathered from the preterm sample was compiled and converted to standard scores using the WJ III Compuscore Software Program Version 2.0 (Schrank & Woodcock, 2003). Manual calculations with raw data and conversion to standard scores were then reviewed by another research assistant. Data was then manually entered into and analyzed with SPSS version 12.0 statistical program (SPSS, 2003). Descriptive analysis Initial descriptive data analyses were conducted to determine overall demographics of the clinical sample, including number of weeks of prematurity, gender, age, ethnicity, language, socio-economic status, and parental education, which were used to identify matched cases from the DWNAS standardization sample. Initial analyses included the calculation of means, standard deviations, and ranges for the WJ III EDev and the WJ III Pre-Ach-Std, and the individual COG, ACH, and DS test scores. Detailed results are presented in Chapter Four. Research Questions Due to the limited sample size and potentially non-normal distribution of scores in the preterm sample, the non-parametric Mann-Whitney test was used to examine the relationship between birth status (as indicated by sample membership) and performance on the WJ III variables of interest in Research Questions 1 through 4 (the General Intellectual Ability-Early Development Standard Score, the individual WJII COG and WJII COG DS test Standard Scores that were selected as appropriate measures of specific cognitive Cattell-Horn-Carroll factors in young children [Test 8: Incomplete Words, Test 1: Comprehension-Knowledge, Test 22: Visual Closure, Test 27: Memory for Words, Test 22: Memory for Names, Test 5: Visual Matching, Test 5: Concept Formation], the Pre-Academic Skills-Standard Standard Scores, and the 4 See Siegel (1983) for a discussion of the issues related to correcting age or scores to account for premature birth. 44 individual WJ III ACH test Standard Scores selected as appropriate measures of early academic skills in young children [Test 1: Letter-Word Identification, Test 14: Picture Vocabulary, Test 7: Spelling, and Test 10: Applied Problems]). As scores on the Maternal Perinatal Scale and the Woodcock-Johnson III are both continuous, the Pearson correlation was used to examine the relationship in preterm children between the Maternal Perinatal Risk score and the GIA-EDEv, the Pre-Ach-Std, and the individual cognitive and achievement tests for Research Question 5. Because of the inflated Type I statistical error rate associated with the number of proposed statistical tests to be performed (42), the p values for the above procedures were adjusted to 0.002 using the Bonferroni correction. Due to the limited sample size and use of non-parametric statistics, post-hoc estimates of the relationship between study sample size and effect size was not possible (Bezeau & Graves, 2001). Table 3.1 Demographics of Study Participants Preterm Children Matched Sample3 N Percentage . N Percentage Sex Male 7 43.8% 7 43.8% Female 9 56.3% 9 56.3% Race" White 13 81.0% 13 81.3% East Indian 1 6.3% 0 0% First Nations0 1 6.3% ' 1 6.3% Black 1 6.3% 2 12.5% a From the WJ III standardization sample. b Consistent with WJ III standardization groupings, Hispanic heritage is treated as an ethnic category, which is distinct from race. One child in the preterm sample was reported to be Hispanic. °The child in the preterm sample was identified as First Nations, while the child in the matched sample was identified as Native American. Table 3.2 Chronological Age of Preterm and Matched Sample in Months Range Mean SD Median Preterm Children Males 53.0-69.0 58.9 5.8 56.0 Females 53.0-70.0 63.4 5.7 63.0 Overall 53.0-70.0 61.4 6.0 62 Matched Sample1 Males 53.0-69.00 58.9 5.8 56.0 Females 55.0-70.0 63.4 5.7 63.0 Overall 53.0-70.0 61.4 6.0 62.0 From the WJ III standardization sample. Table 3.3 Family Characteristics of Study Participants Preterm Children Matched Sample3 N Percentage •N Percentage Socio-Economic Status6 30,000 to 39,999 3 18.8% N/A N/A 40,000 to 49,999 3 18.8% N/A N/A 60,000 plus 10 62.6% N/A N/A Maternal Education High School Completed 5 31.3% 3 18.7% 1-3 Years of College 5 31.3% 8 50.0% Bachelors Degree + 6 37.5% 5 31.3% Maternal Occupation Professional/Managerial 2 12.5% 5 31.3% Technical, sales, admin 4 25.0% 4 25.0% Service 1 6.3% 2 12.5% Not Working/At Home 9 56.3% 5 31.3% Paternal Education Less than High School 1 6.3% 0 0 High School Graduate 0 0% 2 12.5% 1-3 Years of College 7 43.8% 3 18.8% Bachelors Degree + 7 43.8% 11 68.8% Not Applicable 1 6.3% 0 0% Table 3.3 Continued Family Characteristics of Study Participants Preterm Children N Percentage Matched Sample3 N Percentage Paternal Occupation Professional/Managerial Technical, sales, admin Service Craft/repair Laborer Not Applicable 7 4 1 2 1 0 43.8% 25.0% 6.3% 12.5% 6.3% 0% 6 3 2 2 1 2 37.5% 18.8% 12.5% 12.5% 6.3% 12.5% From the WJ III standardization sample. b Information on socioeconomic status in terms of family income was not collected as part of the standardization of the WJ III and thus was not available for the matched sample. 49 Table 3.4 Gestational Age and Birthweight of Preterm Sample Range Mean SD Median Mode Gestational Age (weeks) Males (N=7) 27-37 30.3 3.5 29.0 28 Females (N=9) 25-36 28.6 3.5 28 25 Overall (N= 16) 25-37 29.3 3.5 28 28 Birthweight (grams) Males (N=7) 650-3200 1537.14 953.6 1160 650 Females (N=9) 710-2749 1257.7 676.9 945 710 Overall (N=16) 650-3200 1375.6 791 1012.50 650 50 Table 3.5 Psychometric Characteristics of Woodcock-Johnson III Cluster Scores & Individual Tests Used in the Present Study Broad Cattell-Horn- Test/Cluster Score Internal 1-2 Year Carroll Ability Consistency Test-Retest (4 & 5 Reliability years) (2-7 years) Global Cognitive General Intellectual Ability 0.95-0.93 - -Ability -Early Development Score Crystallized Abilities Test 1: Verbal Comprehension .89 - 3:2 Processing Speed Test 6: Visual Matching .95-.93 .80 4:2 Auditory Processing Test 8: Incomplete Words .86-.83 .76 4:8 Long-Term Retrieval Test 21: Memory for Names .84-.86 .71 3:3 Visual-Spatial Test 22: Visual Closure J7-.69 .82 3:3 Processing Short-Term Memory Test 27: Memory for Sentences .86-.87 .80 3:0 Fluid Reasoning Test 5: Concept Formation .94 .82 5:4 Global Achievement Pre-Academic Standard 0.97 - -Reading/Writing Test 1: Letter-Word .98-.99 .91 3:4 Ability Identification Age of Test Floor" Table 3.5 Continued Psychometric Characteristics of Woodcock-Johnson III Cluster Scores & Individual Tests Used in the Present Study Broad Cattell-Horn- Test/Cluster Score Internal 1 -2 Year Age Carroll Ability Consistency Test-Retest of (4 & 5 Reliability Test years) (2-7 years) Floorb Reading/Writing Test 14: Picture Vocabulary .81-.76 - 2:8 Ability Reading/Writing Test 7: Spelling .90 .84 3:8 Ability Quantitative Test 10: Applied Problems .94-.92 .85 3:6 Knowledge "Adapted from McGrew & Woodcock (2001). bAdapted from Tusing et al. (2003), and Ford, Kozey, Merkel & Swart (2005). A test floor is the age at which a raw score of 1 is associated with a score of at least 2 standard deviations below average. 5 2 C H A P T E R F O U R Results The purpose of this chapter is to present the results regarding an investigation of the validity of the W J III with a group of children aged four and five years born who were born prematurely. For each of the research questions posed in Chapter Three, relevant descriptive analyses is presented which is then followed by data specific to each of the research questions. Graphic boxplot displays comparing the performance of the preterm and matched sample are provided in Appendix E through Q. Discussion and implications of the findings are presented in Chapter Five. Initial Analyses. A s indicated in Chapter 3, the mean chronological for males in the preterm sample was lower than the females in the preterm sample, the average gestational age of the male preterm participants was higher than the female preterm participants, and the average birthweight for the male preterm participants was higher than that for the female preterm participants. A s indicated in Table 4.1 though, the distributions of chronological age, gestational age and birthweight did not statistically differ for the male versus female preterm participants. Research Questions #1 & #2 General Intellectual Ability-Early Development Score. The relationship between birth status and global intellectual ability was examined. Children born prematurely were expected to score lower on the G IA -EDev than matched children from the W J III C O G standardization sample, and a small correlation with birth status was expected. A s indicated in Table 4.2, the overall preterm sample demonstrated a mean G IA -EDev within the average range (Standard Score M=105.4), as did the matched sample (M=l 10.0). The overall variability for the GIA-EDev was within the normal range for the 53 preterm sample (SD=16.8), but slightly higher than expected for the matched sample (SD=22.9). The difference between the GIA-EDEV score distributions of the preterm versus the matched sample were not significantly different (Mann Whitney U=104.0, p=.37; Table 4.3). Individual WJ III Cognitive & Diagnostic Supplement Tests. The relationship between birth status and seven broad CHC cognitive abilities measured by WJ III COG was examined, with no score distribution differences expected with Test 1: Verbal Comprehension and Test 27: Memory for Sentences, and differences expected with Test 8: Incomplete Words, Test 7: Concept Formation, and Test 6: Visual Matching, Test 22: Visual Closure, and Test 21: Memory for Names. On the individual WJ III COG & DS tests, the average standard scores for the preterm sample were all within the average range on (103.4 -113.3), as were those for the matched sample (99.8 - 108.4). For all of the individual WJ III COG and DS tests except one, the average preterm sample score was within 5 points of the matched sample scores. On Test 22: Visual Closure, the difference between the preterm and matched sample exceeded 5 points, with the preterm population having an average standard score of 113.3 versus 103.8 for the matched sample. The overall variability for the preterm sample ranged from less (Test 22: Visual Closure, SD=11.1) to more than typically expected on standardized tests (Test 1: Verbal Comprehension, SD=19.8), as did the overall variability for the matched sample (Test 22: Visual Closure, SD=101 versus Test 1: Verbal Comprehension, SD=20.9). On all of the individual WJ III COG and DS tests, the variability of the preterm sample was within five points of the variability of the matched sample except for Test 27: Memory for Sentences (preterm SD=T4.5 versus matched sample SD=22.4). Results from the non-parametric Mann Whitney U test indicated no significant difference between the distribution of the preterm versus matched sample distributions on individual WJ III COG test scores (Table 4.3). 54 Research Questions #3 & #4 Pre-Academic-Standard Score. The relationship between birth status and pre-academic abilities, as measured by the Woodcock-Johnson III Tests o f Achievement, was examined. A score distribution difference was expected between birth status and performance on the W J III Pre-Ach-Std. As indicated in Table 4.4, the overall preterm sample demonstrated a mean Pre-Ach-Std score within the average range (Standard Score M=101.4), but was more than 15 points lower than the average Pre-Ach-Std score for the matched sample (M= l 16.3). The variability for the Pre-Ach-Std score was higher than typically found for both the preterm sample (SD=20.5), and the matched sample (SD=26.1). However, a difference approaching significance was observed between birth status (preterm versus matched sample) and the Pre-Ach-Std (Mann Whitney U=82.50, p=0.09; Table 4.5). Individual WJ III Achievement Tests. The relationship between birth status and specific early academic skil ls measured by the Woodcock-Johnson III Tests of Achievement was examined. No difference was expected with Test 1: Letter-Word Identification test, and score distribution differences were expected with Test 7: Spelling and Test 10: Appl ied Problems. As indicated in Table 4.4, the individual WJ III A C H standard scores for the preterm sample were all within the average range on (91.7 - 112.6), as were those for the matched sample (102.8 -121.2). On all of the individual WJ III A C H tests except one, the average preterm sample score was at least 10 points lower than the average matched sample score. On Test 10: Applied Problems, the difference between the preterm and matched sample exceeded 5 points, with the preterm population having an average standard score of 113.3 versus 103.8 for the matched sample. The variability of the preterm sample was within five points of the variability of the matched sample on Test 10: Applied Problems (SD-16.5 versus 17.6, 55 respectively), but lower than by more than 5 points for Test 1: Letter Word Identification (SD=16.8 versus 29.7) and Test 14: Picture Vocabulary (SD=12.7 versus 19.0). The overall variability of the preterm sample on Test 10: Applied Problems was higher (SD=31.8) than that observed for the matched sample (SD=18.4). Results from the non-parametric Mann Whitney U test (Table 4.5) indicated no significant differences between the distributions of the preterm versus matched sample scores on Test 1: Letter-Word Identification, Test 10: Applied Problems, and Test 14: Picture Vocabulary. Results from the non-parametric Mann Whitney U test (Table 4.5) indicate that the difference between the distributions of the preterm versus matched sample scores for Test 7: Spelling approached statistical significance (Mann Whitney U=72.0, p=.06). Research Question #5 Descriptive Results for Maternal Perinatal Scale. Responses to the Maternal Perinatal Scale yielded cumulative risk scores that ranged from 26 to 47 points, with an average cumulative MPS score of 36 points (SD=6.9 points). Results from items that were positively endorsed within the current sample are listed in Table 4.6. Relatively few perinatal complications were reported by the mothers of the current sample. The most commonly endorsed high risk responses low birthweight (66.7%), lower gestational age (less than eight months, 80%), saddle block anesthesia (66.7%), and prior pregnancies resulting in spontaneous abortion (33.3%). Maternal Perinatal Scale & WJ III Cognitive Scores. The relationship between cumulative perinatal risk factors as measured by the MPS and performance on the Woodcock-Johnson III Tests of Cognitive Abilities General Intellectual Ability-Early Development (GIA-EDev) Standard Score, the individual Woodcock-Johnson III EDev tests (as listed in research question 2), the Woodcock-Johnson III Tests of Achievement 56 Pre-Academic Skills-Standard, and the individual Woodcock-Johnson III Tests of Academic Achievement (as listed in research question 4) was examined. An inverse correlation was expected between cumulative perinatal risk factors and performance on the WJ III tests, with children born with more perinatal risk factors scoring lower than children born with fewer perinatal risk factors. Results indicated no significant relationship between the GIA-EDev score, individual WJ III COG test scores, and cumulative perinatal risk scores (Table 4.7). The correlation between between the overall MPS score and performance on the WJ III COG Test 21: Memory for Names approached significance, with children with a higher MPS score demonstrating lower scores (r=-0.622, p=.013). Maternal Perinatal Scale & WJ III Achievement Scores. No significant relationship was observed between the cumulative perinatal risk score based on responses to the Maternal Perinatal Scale, and the Pre-Ach-Std and the individual WJ III ACH test scores (Table 4.8). Post-Hoc Gender Analyses The means and standard deviations for the WJ III Cognitive and Diagnostic Supplement scores are displayed by gender for the Preterm Sample (Table 4.9) and Matched Sample (Table 4.10). Results from the non-parametric Mann Whitney U test (Table 4.5) indicate no significant difference between the distribution of the preterm versus matched sample distributions of GIA-EDev scores (Mann Whitney U=104.00, p=0.37; Table 4.11). The means and standard deviations for the WJ III Achievement scores are displayed by gender for the Preterm Sample (Table 4.12) and Matched Sample (Table 4.13). Results from the non-parametric Mann Whitney U test indicate no significant difference between the distribution of the preterm versus matched sample distributions of Pre-Ach-Std scores (Mann Whitney U=82.50, p=0.86; Table 4.14). Post-57 hoc analyses of the Pre-Ach-Std and the individual WJ III ACH tests indicate that the score distributions were not statistically different the preterm males versus females (Table 4.14). In summary, results did not identify any significant differences between the score distributions of children born preterm versus the matched sample, and no significant correlations between preterm versus matched sample status, in terms of the WJ III General Intellectual Ability-Early Development Score, individual WJ III cognitive tests, WJ III Pre-Academic Standard Score, and the individual WJ III achievement tests. Similarly, no significant correlations were observed between these scores and perinatal risk, as measured by a cumulative score on the Maternal Perinatal Scale. 58 Table 4.1 Comparison of Demographic Variable Distributions for Preterm Sampk Cluster Score/Test Males Females Mann P N= =7 N= =9 Whitney U-Test Sum of Mean Sum of Mean Ranks Rank Ranks Rank Chronological Age (months) 44.50 6.36 91.50 10.17 16.50 .11 Gestational Age (weeks) 71.50 10.21 64.50 7.17 19.60 .21 Birthweight (grams) 63.0 9.0 73.0 8.11 28.00 .71 59 Table 4.2 Means and Standard Deviations for the WJ III Cognitive and Diagnostic Supplement Composite and Individual Test Scores Cluster/Test Preterm Children Matched Sample N=16 N=16 Minimum-Maximum M SD Minimum-Maximum M SD General Intellectual Ability - 84-137 105.4 16.8 57-157 110.0 22.9 Early Development Test 1: Verbal Comprehension 66-135 105.9 19.8 68-147 106.6 20.9 Test 6: Visual Matching 81-123 103.4 12.6 87-133 108.2 12.8 Test 8: Incomplete Words 84-117 104.0 10.3 88-137 106.0 14.6 Test 21: Memory for Names 84-144 103.5 18.5 59-129 105.1 16.3 Test 22: Visual Closure 100-134 113.3 11.1 82-124 103.8 10.1 Test 27: Memory for Sentences 85-137 103.9 14.5 59-137 108.4 22.4 Test 5: Concept Formation6 83-127 104.4 12.9 77-141 99.8 16.5 From the WJ III standardization sample. bOnly 14 children completed Test 5: Concept Formation 60 Table 4.3 Comparison of Score Distributions for Woodcock-Johnson III Cognitive Scores & Relationship with Birth Status Cluster Score/Test Preterm Matched Mann P Children Sample Whitney U-Test Sum of Mean Sum of Mean Ranks Rank Ranks Rank General Intellectual Ability -Early Development 240 15 288 18 104.000 .37 Test 1: Verbal Comprehension 269.50 16.84 258.50 16.16 122.500 .84 Test 6: Visual Matching 242.60 15.16 285.50 17.84 106.50 .42 Test 8: Incomplete Words 261.50 16.34 266.50 16.66 125.00 .93 Test 21: Memory for Names 232.50 14.53 295.50 18.47 96.60 .24 Test 22: Visual Closure 322.50 20.16. 205.50 12.84 69.50 .27 Test 27: Memory for Sentences 236.00 14.75 292.00 18.25 100.00 .29 Test 5: Concept Formation6 220.50 16.96 214.50 13.41 78.50 .26 bOnly 14 children completed Test 5: Concept Formation. 61 Table 4.4 Means and Standard Deviations for Woodcock Johnson III Tests of Academic Achievement Scores (n=16)a Cluster/Test Preterm Children Matched Sampl Minimum- M SD Minimum- M SD Maximum Maximum Pre-Academic - Standard 61-•148 101.4 20.5 74-178 116.3 26.1 Test 1: Letter-Word 74-•153 109.0 16.8 93-198 121.2 29.7 Identification Test 7: Spelling 0-136 91.7 31.8 74-151 110.3 18.4 Test 10: Applied Problems 61- 117 100.0 16.5 54-138 102.8 17.6 Test 14: Picture Vocabulary 95- 146 112.6 12.7 64-138 110.6 19.0 Only 14 preterm children completed Test 14: Picture Vocabulary 62 Table 4.5 Comparison of Score Distributions for Woodcock-Johnson III Achievement Scores & Relationship with Birth Status Test 1: Letter-Word Identification Test 7: Spelling Test 10: Applied Problems Test 14: Picture Vocabulary Cluster Score/Test Preterm Children Matched Sample Mann P Whitney U-Test Sum of Mean Sum of Mean Ranks Rank Ranks Rank Pre-Academic -Standard 2 1 8 , 5 0 1 1 6 6 3 0 9 - 5 0 1 9 3 4 8 2 - 5 0 0 -09 239.50 14.97 288.50 18.03 103.5 192.00 12.80 304.00 19.00 72.00 267.00 16.69 261.00 16.31 125.0 215.00 15.36 250.00 16.63 110.0 .36 .06 .91 .95 63 Table 4.6 Item Level Results from the Material Perinatal Scale for Preterm Sample (n=15) Maternal Perinatal Scale Frequency % Maternal Perinatal Scale Frequency % Item Item Number of Prior Pregnancies 7 None 6 One 1 Two 1 Three or More Vaginal Bleeding During Pregnancy None 13 Some Near End 1 Some at 1 Beginning/Middle Child Birthweight More than 6 Pounds 2 Five to Six Pounds 1 Four to Five Pounds 1 Three to Four Pounds 1 Three Pounds or Less 10 Medication During 46.7 Pregnancy 40.0 None 6.7 Prescribed Vitamins/Iron 6.7 Other Medications Delivery Position Head First 86.7 Think Head First 6.7 Feet First/Breech 6.7 Side Presentation Child's Colour After Birth 13.3 Not Blue 6.7 Was Reported to Be Blue 6.7 Observed as Blue 6.7 66.7 3 9 3 5 6 2 2 12 1 2 20.0 60.0 20.0 33.3 40.0 13.3 13.3 80.0 6.7 13.3 64 Table 4.6 Continued Maternal Perinatal Scale Item Frequency % Maternal Perinatal Scale Item Frequency % Gestational Age Gynecological Surgery No Prior Surgery 10 66.7 Nine or More Months 1 6.7 More than 2 Years Prior 1 6.7 Eight to Nine Months 2 13.3 Voluntary Prior Abortion 1 6.7 Seven to Eight Months 8 53.3 During Pregnancy 2 13.3 Six to Seven Months 4 26.7 To Correct Infertility 1 6.7 Stress During Pregnancy Previous Pregnancies Very Little 6 40.0 None 6 40.0 Moderate Amount 7 46.7 One or More Resulting in Significant Amount 2 13.3 Normal Birth 3 20.0 One or More Resulting in Spontaneous Abortion 5 33.3 One or More Resulting in Stillbirth/Neonatal 1 6.7 Death Length of Labour Cigarettes Smoked Per Day Less Than 3 Hours 8 53.3 During Pregnancy 3-5 Hours 1 6.7 None 14 93.3 6-10 Hours 3 20.0 1 to 10 Cigarettes 1 6.7 11-16 Hours 3 20.0 65 Table 4.6 Continued Maternal Perinatal Scale Item Frequency % Maternal Perinatal Scale Item Frequency % Maternal Weight Gain 11-15 Pounds 4 16-25 Pounds 5 26-35 Pounds 2 36 to 45 Pounds 2 Less than 10 Pounds 2 Maternal Age 20-29 Years 5 30-34 Years 5 35-40 Years 3 Over 40 Years 2 Maternal Swelling During Pregnancy Minimal 11 Some Near End 2 Good Deal Throughout 2 Labour Medically Induced No 13 Yes 2 Alcohol Per Day During 26.7 1 Pregnancy 33.3 None 13.3 1-2 Drinks 13.3 13.3 High Blood Pressure 33.3 None Experienced 33.3 Experienced 20.0 13.3 Motional Problem None 73.3 Experienced 13.3 13.3 Urinary Tract Infection 86.7 None 13.3 Experienced 14 1 11 4 13 2 1.4 1 93.3 6.7 73.3 26.7 86.7 13.3 93.3 6.7 66 Table 4.6 Continued Maternal Perinatal Scale Item Delivery Method No Forceps Forceps Cesarean Planned Degree of Pregnancy Carefully Planned Not Planned But Pleased Multiple Pregnancy Single Pregnancy Twins Frequency % Maternal Perinatal Scale Item Frequency % Viral Infection 11 73.3 None 3 20.0 Experienced I 6.7 Physical Trauma During II 73.3 Pregnancy 4 26.7 None Experienced Depression During 11 73.3 Pregnancy 4 26.7 None 13 2 14 1 14 1 86.7 13.3 93.3 6.7 93.3 6.7 Experienced 67 Table 4.7: Correlation between Woodcock Johnson III Achievement Standard Scores with Cumulative Maternal Perinatal Risk Score for Preterm Sample (n=15) Cluster Score/Test Pearson Correlation with Cumulative Maternal Perinatal Risk Score P Pre-Academic - Standard -0.011 .97 Test 1: Letter-Word Identification -.016 .96 Test 7: Spelling -.091 .76 Test 10: Appl ied Problems .015 .96 Test 14: Picture Vocabulary b -.042 .89 This correlation was based upon 13 children. 68 Table 4.8: Correlation between Woodcock Johnson III Cognitive Standard Scores and Cumulative Maternal Perinatal Risk Score for Preterm Sample (n=15) Cluster Score/Test Pearson Correlation with Cumulative Maternal Perinatal Risk Score P General Intellectual Ability - Early Development -.14 .62 Test 1: Verbal Comprehension .19 .51 Test 6: Visual Matching .29 .30 Test 8: Incomplete Words -.31 .26 Test 21: Memory for Names -.62 .01 Test 22: Visual Closure .19 .50 Test 27: Memory for Sentences -.14 .63 Test 5: Concept Formation6 .31 . .32 This correlation was based upon 12 children. 69 Table 4.9 Preterm Sample Means and Standard Deviations for the Woodcock-Johnson III Tests of Cognitive Abilities and Diagnostic Supplement Composite and Individual Test Scores By Gender Cluster/Test Males N=7 Females N=9 Minimum- M SD Minimum- M SD Maximum Maximum General Intellectual Ability - 84-142 101.3 17.9 85-137 108.6 16.3 Early Development Test 1: Verbal Comprehension 88-130 108.3 14.3 66-135 104.1 23.9 Test 6: Visual Matching 81-117 98.3 13.2 89-123 107.4 11.2 Test 8: Incomplete Words 84-117 105.9 12.1 88-116 102.6 9.1 Test 21: Memory for Names 89-144 105.9 17.9 84-138 101.7 19.8 Test 22: Visual Closure 100-134 111.3 11.4 100-130 114.9 11.3 Test 27: Memory for Sentences 85-137 101.3 18.7 90-120 105.9 11.0 Test 5: Concept Formation" 91-118 104.4 9.7 83-127 104.4 15.2 bOnly 14 children completed Test 5: Concept Formation. 70 Table 4.10 Matched Sample Means and Standard Deviations for the Woodcock-Johnson III Tests of Cognitive Abilities and Diagnostic Supplement Composite and Individual Test Scores By Gender (n= 16) Cluster/Test Males Females Minimum- M SD Minimum- M SD Maximum Maximum General Intellectual Ability - 107-157 122.7 17.4 57-135 100.1 22.5 Early Development Test 1: Verbal Comprehension 107-157 113.7 17.4 68-147 1.01.0 22.4 Test 6: Visual Matching 98-133 114.6 12.5 87-121 103.2 11.3 Test 8: Incomplete Words 89-137 111.9 17.9 88-119 101.4 10.2 Test 21: Memory for Names 91-120 110.6 10.3 59-129 100.8 19.3 Test 22: Visual Closure 93-124 107.4 11.3 82-112 101.0 8.6 Test 27: Memory for Sentences 105-137 121.7 10.0 59-137 98.1 24.2 . Test 5: Concept Formation6 80-126 100.4 14.7 77-141 99.2 18.6 bOnly 14 children completed Test 5: Concept Formation. 71 Table 4.11 Comparison of Preterm Males Versus Preterm Female Score Distributions for the Woodcock-Johnson III Tests of Cognitive Abilities and Diagnostic Supplement Scores Cluster Score/Test Males Females Mann P N= =7 N= =9 Whitney U-Test Sum of Mean Sum of Mean Ranks Rank Ranks Rank General Intellectual Ability -Early Development 50.0 7.14 86.0 9.56 22.0 .351 Test 1: Verbal Comprehension 62.0 8.86 74.0 8.22 29.0 .837 Test 6: Visual Matching 46.0 6.57 90.0 10.0 18.0 .174 Test 8: Incomplete Words 69.0 9.86 67.0 7.44 22.0 .351 Test 21: Memory for Names 69.0 9.86 67.0 7.44 22.0 .351 Test 22: Visual Closure 53.5 7.64 82.5 9.17 25.5 .536 Test 27: Memory for Sentences 49.60 7.07 86.50 9.61 21.5 .299 Test 5: Concept Formation" 34.50' 6.90 56.50 7.06 19.5 .943 72 Table 4.12 Preterm Sample Means and Standard Deviations for the Woodcock-Johnson III Tests of Academic Achievement Composite and Individual Test Score By Gender (n=16) Cluster/Test Males Females Minimum- M SD Minimum- M SD Maximum Maximum Pre-Academic - Standard 61-124 94.4 21.8 79-148 106.9 18.7 Cluster Test 1: Letter-Word 74-124 104.9 17.1 94-136 112.2 16.9 Identification Test 7: Spelling 0-126 78.5 44.2 66-136 100.6 18.0 Test 10: Applied Problems 73-114 99.0 17.3 61-117 100.8 16.86 Test 14: Picture Vocabulary 98-146 116.17 98 95-118 110.0 9.1 73 Table 4.13 Matched Sample Means and Standard Deviations for the WJ III ACH Composite and Individual Test Score By Gender (n=l 6) Cluster/Test Males Females Minimum- M • SD Minimum- M SD Maximum Maximum Pre-Academic - Standard 79-148 106.9 18.7 74-153 110.9 22.1 Cluster Test 1: Letter-Word 94-153 112.2 16.9 93-175 116.6 24.6 Identification Test 7: Spelling 66-136 100.6 18.0 74-124 106.2 16.6 Test 10: Applied Problems 61-117 100.8 16.9 54-122 97.0 18.7 Test 14: Picture Vocabulary 95-118 110.0 9.1 63-137 107.0 21.2 74 Table 4.14 Comparison of Preterm Males Versus Preterm Female Score Distributions for the Woodcock-Johnson III Tests of Academic Achievement Scores Cluster Score/Test Males Females Mann P N= =7 N= -9 Whitney U-Test Sum of Mean Sum of Mean Ranks Rank Ranks Rank Pre-Academic - Standard Cluster 49.0 7.0 87.0 9.67 21.0 .21 Test 1: Letter-Word Identification 57.0 8.14 79.0 8.78 29.0 .79 Test 7: Spelling 37.0 6.17 83.0 6.17 16.0 .19 Test 10: Applied Problems 61.0 8.71 75.0 8.33 30.0 .87 Test 14: Picture Vocabulary 8 50.50 8.42 5.4.50 6.81 18.50 .48 Only 14 preterm children completed Test 14: Picture Vocabulary 75 CHAPTER FIVE Discussion The purpose of this chapter was to discuss the results presented in Chapter 4 regarding the utility of the WJ III with a population of a, four- and five-year-old preschool age children born prematurely. Implications of findings these conclusions were explored, and contributions to the literature were outlined. Limitations of the current study and directions for future research were also presented. The limited size and demographic composition of the study sample must be taken into consideration throughout the discussion of the study results. Challenges with sample reruitment resulted in a final sample size of only sixteen subjects which was very low. The author acknowledges that a study investigating group differences with a smaller sample size is prone to Type II error (failure to detect a true difference), simply due to a lack of statistical power (Huck, 2004). The likelihood of detecting any statistically significant relationships between birth status and performance on the measures used in this study was even further reduced by the necessary use of non-parametric statistics, which are known to be less sensitive than parametric procedures to significant differences (Huck, 2004). Similarly, the p value for statistical significance was adjusted to reflect the large number of statistical operations conducted in this study, and even with a conservative use of the Bonferroni correction (p=0.0011). None of the findings approaching significance in the current study were robust enough to pass this standard. As well, due to the limited number of subjects and the large numbers of variables under examination (two cluster scores, seven cognitive abilities and performance on four individual achievement tests), it was not possible to utilize more advanced statistical methods such as regression or analysis of covariance, to control for the effects of variables such as gender, socioeconomic class or global intelligence that have been previously shown to be significantly related to outcomes of 76 prematurity. Finally, given that the preterm/LBW literature suggests that the cognitive and academic deficits of children born prematurely (without major mental or physical impairment) are subtle to moderate in magnitude, the use of a smaller sample may be even more problematic in research with children born prematurely, as the detection of such subtle to moderate differences would be more improbable with smaller samples. Research Questions Research Questions #1 and 2: Examining Woodcock-Johnson III General Intellectual Ability-Early Development Score, and Individual Cognitive Abilities The purpose of Research Question #1 was to explore the use of the WJ III COG measure of global intellectual ability, the WJ III GIA-EDev score, with children born prematurely. Based upon the most commonly reported findings in the literature (e.g., Aylward, 2002a), it was expected that the children born prematurely would score significantly lower than matched children from the WJ III standardization sample. Although the overall preterm sample demonstrated a mean GIA-EDev that was four points lower (Standard Score M= 105*4) than the mean score of the matched sample (M=l 10.0), so significant difference in the GIA-EDEV score was identified between birth status (preterm versus matched). The results may be accounted for or interpreted in several possible ways. First, it is possible that there were no significant differences due to a lack of statistical power associated with the small sample size and composition of the current sample. Alternatively, the WJ III EDev score, which is comprised of a weighted combination of five different cognitive abilities represents a wider range of cognitive abilities than those typically included in previous studies (e.g. WPPSI-R, SBIV). It is also possible that the WJ III EDev score is not sensitive to the cognitive deficits of children born prematurely, particularly given that the more robust literature findings suggest that cognitive deficits of preterm children appear to be at the specific factor or ability level. Results for all of the individual cognitive tests suggested no significant difference between the preterm and matched sample, in terms of their mean scores or score distributions. Visual inspection of boxplot graphic displays of the individual WJ III COG & DS score distributions (Appendix E to K) also indicated that the pattern of scores for all six of the individual CHC abilities that contribute to the GIA-EDev was similar across the preterm and matched samples. In contrast to the outcomes anticipated based upon previous findings in the literature, it appears that the current sample of preterm children did not perform any differently on the WJ III GIA-Dev than a matched sample. As with the finding at the global and cluster level in Question #1, no significant differences were identified at the level of the individual WJ III tests, which were used to examine individual CHC abilities. It was hypothesized that there would be no score distribution difference or correlation with Test 1: Verbal Comprehension and Test 27: Memory for Sentences, and these hypotheses were supported. However, based upon previous research findings, it was expected that there would be a 1 score distribution difference and correlation with Test 8: Incomplete Words, Test 7: Concept Formation, and Test 6: Visual Matching, Test 22: Visual Closure, and Test 21: Memory for Names. Results regarding the mean scores, score distributions, correlations and boxplot graphic displays of the individual WJ III COG & DS score distributions (Appendix F to L) failed to support the latter hypotheses. One trend towards differential performance in CHC cognitive abilities was suggested on Test 22: Visual Closure. However, these results are not consistent with the literature that indicates strong support that preterm children routinely demonstrate deficits in visual-spatial processing. In this study, the preterm sample mean for Test 22: Visual Closure (a measure of visual-spatial processing) was approximately 10 points higher than that of the matched sample, and the pattern of the preterm score distribution (Appendix J) also demonstrated a trend towards being higher than that of the 78 matched sample. Given the strong literature evidence discussed that indicates that preterm children demonstrate consistent deficits in visual-spatial processing, the latter finding is unexpected. This unusual finding with Test 22: Visual Closure may be attributable to the pre-requisite abilities required to perform the activities visual-spatial processing on this task, which is knowledge of environmental objects and adequately developed language abilities to name (crystallized abilities) the occluded objected perceived on the stimuli easels. Thus, given the high socio-economic composition of the preterm sample and the known positive relationship between SES and crystallized abilities, Test 22 may in fact have functioned as a measure of Gc and environmental enrichment with the current sample, rather than measure of visual-spatial processing. In summary, results therefore indicate that the current sample of preterm children did not perform any differently than a matched sample on any of the individual measures of CHC cognitive abilities. Research Questions #3 and #4: Examining the relationship of the Woodcock-Johnson III Tests of Academic Achievement Pre-Academic-Standard Score and Individual Academic Abilities The purpose of Research Question #3 was to explore the use of the WJ III ACH global achievement score, the WJ III Pre-Ach-Std score, with children born prematurely. It was expected that children born prematurely would score lower than the matched sample, and a small score distribution difference between the preterm and matched samples would be found. Although the overall preterm sample demonstrated a mean Pre-Ach-Std Score that was approximately 15 points lower (Standard Score M=101.4) than the mean score of the matched sample (M=l 16.3), no significant score distribution difference was observed. Inspection of the Pre-Academic-Std distributions (Boxplot, Appendix N) also suggests that mean Pre-Ach-Std score for the matched sample may have been elevated due to an extremely high score in one 7 9 case. The lower Pre-Ach-Std score mean score of the preterm sample may have been the result of the lower preterm sample mean scores on two of tests contributing to the Ach-Std tests (Test 1: Letter-Word Identification and Test 7: Spelling). However, further inspection of the results for these two tests indicate that the matched sample mean on Test 1: Letter-Word Identification could be higher due to two high scores (case 18 & 26; Appendix O); on Test 7: Spelling, it was unclear whether the preterm mean was lowered by presence of possible outliers (case 5, 8, 16; Appendix P), or whether this was simply variability within this sample. Accordingly, in contrast to the hypothesized outcome, it appeared that the current sample of preterm children did not perform any differently on the WJ III ACH Pre-Ach-Std score than a matched sample. The purpose of Research Question #4 was to investigate individual CHC academic abilities as measured by individual WJ III ACH tests with children born prematurely. It was hypothesized that no there would be no score distribution difference with Test 1: Letter-Word Identification test and Test 14: Picture Vocabulary, and in this instance, the null hypotheses were not refuted. In contrast, score distribution differences were expected respectively with Test 7: Spelling and Test 10: Applied Problems. The mean preterm sample score was similar to the matched sample on Test 10: Applied Problems, with a null finding of differences. The preterm sample mean score for Test 7: Spelling was over 15 points (one standard deviation) lower than that of the matched sample, with a null finding of distribution differences that nonetheless approached significance (Mann-Whitney=72.00, p=.06). However, it is unclear whether the lower preterm mean (and difference approaching significance) on Test 7 Spelling may have been due in part to the presence of several outliers in both the preterm and matched sample on Test 7: Spelling, as noted above (Appendix P). It is also unclear whether this possible trend is reflective of actual delays in the development of spelling skills in the preterm sample or possible visual motor coordination deficits commonly found with children born prematurely, as the initial items 80 on Test 7: Spelling are those that require simple drawing and tracing skills. In summary, results therefore indicated that the current sample of preterm children did not perform any differently than a matched sample on any of the individual measures of CHC cognitive abilities. Research Question #5: Relationship between Scores & Perinatal Risk Factors An inverse relationship was expected between cumulative perinatal risk factors and performance on the WJ III tests, and children born with higher levels of perinatal risk were expected to score lower than children born with lower levels of perinatal risk factors. Pearson correlations between the GIA-EDev, the individual cognitive tests administered in this study, the Pre-Ach-Std, and the individual academic tests administered in this study were non-significant, suggesting no relationship between cumulative perinatal risk, and cognitive and academic outcomes in this sample of preschool-aged children born prematurely. The trend towards an inverse relationship between performance on the WJ III DS Test 21: Memory for Names (a measure of long term storage and retrieval; Mann-Whitney U=-.62, p=0.01) is consistent with expectations, but there is no obvious reason as to why this trend was observed on one but none of the other cognitive scores. The lack of findings regarding the WJ III and MPS scores may be attributable to the limited size or high socioeconomic composition of the preterm sample, which reported relatively low incidence of the perinatal complications reported on the Maternal Perinatal Scale. It may also reflect any limitations regarding the perinatal complications measured by the MPS, such as its lack of measurement of perinatal factors such as cerebral hemorrhage. Limitations of the Study In addition to the issue of small sample size, the current study had several other limitations such as sample composition, study procedures, and the measures used, which severely restrict the scope and the strength of any conclusions drawn from the present results. 81 Due to the difficulties with recruitment, the current study utilized wider inclusion Criteria than originally planned. The majority of studies included in the current literature review focused upon children who are at higher risk due to moderate or extreme prematurity (e.g., 33 weeks gestational age or less). Alternatively, studies including children born between 33 and 37 weeks gestational age typically employed samples that were large in size, thereby allowing for three-way group comparisons of children born preterm, moderately prematurely or extremely prematurely. Given the literature findings that the incidence of cognitive and academic morbidity is more frequent and impaired in children of lower gestational age, the decision to include children with gestational ages between 33 and 37 weeks also may have limited the ability of the current investigation to detect any relationship between birth status and performance on the WJ III. The current study suffered from another similar limitation, where outcome of preterm birth was confounded with low birthweight by the simultaneous inclusion of children who were born both small for gestational age and children born with a birthweight appropriate for gestational age. As noted earlier by Hack et al (1995), the medical risks and outcomes of children born preterm versus with intra-uterine growth retardation may be medically distinct. Similarly, the limited sample size of In terms of sample composition, this study shared several other limitations common to many of the available studies in the literature on the cognitive and academic abilities of children born prematurely. In addition to the inclusion of children who were more heterogeneous in terms of their gestational age and birthweight, the current preterm sample was biased in terms of several factors which are associated with more positive cognitive and academic outcomes. Over 60% of preterm participants came from families with household incomes exceeding $60,000 and high levels of paternal education. In contrast to other published studies, the mothers of the current sample also had access to universal pre and post-natal healthcare, and reported relatively 82 low incidence of perinatal complications. The higher levels of socio-economic status, parental education, and access to healthcare may account for the relatively consistent average performance of the current preterm sample on the WJ III tests. One other aspect of the sample that may have been problematic was the inclusion of two children who were reported to be functionally bilingual in both French and English, which may have affected their performance, as both of these children performed more poorly on Test 1: Verbal Comprehension (a measure of crystallized abilities and language development). The composition of the matched sample from the WJ III Standardization sample as a comparison group to the current sample of children born prematurely was also a significant limitation of this study. The original study design included the use of a matched sample from the standardization sample of the Dean-Woodcock Neuropsychological Assessment System (Dean and Woodcock, 2004), which included children who were screened for premature birth and neuropsychiatric conditions. However, due to circumstances beyond the control of the study investigators, this sample was not available for use and the WJ III Standardization sample was used as an alternative comparison group. Although the children included in the WJ III Standardization sample were screened for major handicaps and were considered to be typically developing, they were not screened specifically for premature birth. Consequently, the current study cannot make any claims regarding the relationship between performance on the WJ III and birth status, as the birth status of the matched sample was not available. Several aspects of the study design and procedures may be considered as possible limitations. An attempt was made to consider the effects of perinatal conditions which have been documented to be related to outcomes of children born prematurely, but the means through which this was done in the current study may have been inadequate in several respects. Due to the low variability and limited reports of perinatal complications on the MPS, an alternative, 83 non-standard scoring procedure had to be used to calculate an overall risk score; this did not allow for differential weighting of related items or items (such as asphyxia at birth) that are more strongly predictive of later adverse outcomes. Similarly, although the Maternal Perinatal Scale evaluated a large number of perinatal complications, it did not evaluate certain conditions known to be predictive of later adverse outcomes, such as cerebral hemorrhage, post-natal lung infections, or medications administered to the child in the post-natal period. Finally, the current study design and the limited sample size did not allow for evaluation of other environmental variables which have been demonstrated to influence cognitive and academic outcomes after premature birth, such as enrollment in preschool or stimulation in the home. Contributions to the Field and Implications for Future Research This study also demonstrated common methodological and design issues that will have to be addressed in future studies with preterm populations. Future study designs will need to account for issues related to the heterogeneity of preterm populations (such as differences gestational age and low birthweight), differential outcomes associated with family socio-economic status, access to perinatal health care, exposure to stimulation in the family home and parenting style, and access to early childhood education and care. Ideally, future investigations would have adequate sample sizes that would allow for isolation of variables confounded with preterm outcomes, and would also include a three-way analysis between extremely premature, moderately premature and preterm status, as well as gender differences and specific perinatal risk factors, such as cerebral hemorrhage or post-natal infection. Moreover, inclusion of measures that can distinguish between confounded cognitive and other developmental abilities would be appropriate, such as tests of visual-motor coordination. Although many of the findings anticipated upon the inception of this study were not found, results from this study highlighted the need to continue to explore utility of C H C theory 84 and the related cross-battery approach in understanding the deficits of children born prematurely. The focus of the present literature review and study was upon the deficits of children born prematurely at the CHC broad or factor level ability level, partially due to the lack of information regarding the specific subtests and related results used in previously published studies. Although it is well-documented that the cognitive and academic deficits of preterm children are primarily at the level of specific (rather than global) cognitive or academic abilities, it was found in the current literature review employing a CHC theoretical framework that the specific ability or factor-level deficits of preterm children varied in consistency and strength across studies, and instrumentation. In conjunction with the recent development of cognitive and academic measures for preschool-aged children that are psychometrically appropriate for interpretation at the subtest or factor level, the use of a CHC-cross battery approach that allows for comparison of results across instruments at both the broad and narrow (task) CHC ability level, which may assist with the explanation of differential findings and allow for greater specification of their cognitive and academic deficits. Replication of the current study with a larger sample may still be informative to understanding the deficits of preterm children. The WJ III attempts to evaluate cognitive and academic functioning using tasks that focus upon individual abilities, rather than the coordinated or simultaneous use of multiple cognitive abilities. Given that the most robust literature findings regarding the deficits of children born prematurely relate to the coordinated use of visual-motor abilities, executive functioning and more complex academic tasks (such as reading comprehension, written composition and mathematical reasoning), replication of the current study findings may help to clarify and confirm whether the deficits of children born prematurely are at the level of broad CHC abilities, specific narrow abilities, or coordinated use of CHC abilities. 85 Future understanding regarding the use of the WJ III with and the CHC abilities of preschool-aged children born prematurely also requires further research on the general development of early CHC cognitive and academic abilities. Establishment of normative developmental trajectories of the broad and narrow CHC abilities across the preschool and early school-aged years will allow for clarification of whether particular cognitive and academic deficits are present in any given preschool-aged clinical population, and if particular morbidities associated with premature birth are detectable during the preschool years, or alternatively are associated with onset at later developmental stages. Conclusions The current study was the first reported investigation of the Woodcock-Johnson III with a clinical sample of preschool-aged children. Results indicated no significant difference between the score distributions of preschool-aged children born prematurely versus a matched sample from the WJ III Standardization sample in terms of global intelligence, individual Cattell-Horn-Carroll abilities, global achievement or individual academic abilities. Sample size design issues related to the screening of the matched sample limited possible conclusions regarding the relationship between birth status and performance on the WJ III tests administered in this study, and no relationship was found between performance on the WJ III and perinatal complications, as measured by the Maternal Perinatal Scale. Current findings were likely a function of the limited size and biased composition of the study sample, rather than the actual function of the WJ III. The application of CHC theory and a cross-battery approach remains a potentially promising theoretical framework for understanding the cognitive and academic deficits of preterm children in general, and further investigation is necessary to determine the utility of the WJ III with preschool-aged children born prematurely. R E F E R E N C E S 86 Alfonso, V . C , Flanagan, D. P., & Radwan, S. (2005). The impact of the Cattell-Horn-Carroll theory on test development and interpretation of cognitive and academic abilities. In D.P.Flanagan (Eds.), Contemporary intellectual assessment: Theories, tests and issues (2nd ed., pp. 185-202). New York, N Y : Guilford Press. Al len, M . C. (2002). Preterm outcomes research: A critical component of neonatal intensive care. Mental Retardation and Developmental Disabilities Research Reviews, 8, HX-llli. Anderson, P. (2004). Executive functioning in school-aged children who were born very preterm or with extremely low birth weight in the 1990s. Pediatrics, 114, 50-57. Anderson, P., & Doyle, L.W. (2005). Neurobehavioral outcomes of school-age children born extremely low birth weight or very preterm in the 1990s. Journal of the American Medical Association, 289, 3264-3272. Andrews-Espy, K., Stalets, M . M . , McDiarmid, M . M . , Senn, T.E. , Cwik, M.F., & Hamby, A . (2002). Executive functions in preschool children born preterm: Application of cognitive neuroscience paradigms. Child Neuropsychology, 8, 83-92. Assel , M.A. , Landry, S .H. , Swank, P., Smith, K .E. , & Steelman, L . M . (2003). Applied Developmental Science, 7, 27-38. Aylward, G. P. (2002a). Cognitive and neuropsychological outcomes: More than IQ scores. Mental Retardation & Developmental Disabilities Research Reviews, 8, 234-240. Aylward, G. P. (2002b). Methodological issues in outcome studies of at-risk infants. Journal of Pediatric Psychology, 27, 37-45. Bagnato, S. J. & Neisworth, J. T. (1994). A national study of the social and treatment "invalidity" of intelligence testing for early intervention. School Psychology Quarterly, 9, 81-102. Barksley, V . E . & Siegel, L.S. (1992). Predicting future cognitive, academic and behavioral outcomes for the very low birthweight (<15000 grams) infants. In S.L. Friedman and M . Sigman (Eds), The psychological development of lower birthweight children: Advances in applied developmental psychology (pp. 275-284). Norwood, N J : Ablex. Beery, K. (1982). Developmental Test of Visual Motor Integration. Cleveland, O H : Modern Curriculum Press. Bennet, F.C. (2002). Low birth weight infants: Accomplishments, risks and interventions. Infants and Young Children, 15 (J), vi-ix. Bezeau, S. & Graves, R. (2001). Statistical power and effect sizes o f clinical neuropsychology research. Journal of Clinical & Experimental Neuropsychology, 23, 399-406. Bhutta, A . T., Cleves, M . A . , Casey, P. H., Cradock, M . M . , & Anand, K. J . (2002). Cognitive and behavioral outcomes of school-aged children who were born preterm: A meta-analysis. Journal of the American Medical Association, 288, 728-737. Blair, C. (2003). Self-regulation and school readiness. Champaign, IL: ERIC Clearinghouse on Elementary and Early Childhood Education. Boehm, A . E. (2000). Assessment of basic relational concepts. In B.Bracken (Ed.), Psychoeducational assessment of preschool children (3rd ed., pp. 186-203). Neeham Heights,MA: A l l yn & Bacon. Bohm, B., Katz-Salamon, M . , Smedler, A . , Lagercrantz, H., & Forssberg, H. (2002). Developmental risks and protective factors for influencing cognitive outcome at five and 88 a half years of age in very low birthweight children. Developmental Medicine & Child Neurology, 44, 508-516. Bowen, J.R., Gibson, F.L., & Hand, P.J. (2002). Educational outcome at 8 years for children who were born extremely prematurely: A controlled study. Journal of Paediatrics and Child Health, 38, 438-444. Bracewell, M. & Marlow, N. (2002). Patterns of motor disability in very preterm children. Mental Retardation and Developmental Disabilities Research Reviews, 8, 241-248. Bracken, B. (1988). Ten psychometric reasons why similar tests produce dissimilar results. Journal of School Psychology, 26, 155-166. Bracken, B. (1987). Limitations of preschool instruments and standards for minimal levels of technical adequacy. Journal of Psychoeducational Assessment, 4, 313-326. Bracken, B. A. & Walker, K. C. (1997). The utility of intelligence tests for preschool children. In D.P.Flanagan, J. L. Genshaft, & P. Harrison (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (pp. 484-502). New York, NY: Guilford Press. Bradley-Johnson, S. (2001). Cognitive assessment for the youngest children: A critical review of tests. Journal of Psychoeducational Assessment, 19, 19-44. Breslau, N., Chilcoat, H.D., Johnson, E.O., Andreski, P. & Lucia, V.C. (2000). Neurologic soft signs and low birthweight: Their association and neuropsychiatric implications. Biological Psychiatry, 47, 71-79. Briscoe, J., Gathercole, S.E., & Marlow, N. (1998). Short-term memory and language outcomes after extreme prematurity at birth. Journal of Speech, Language, and Hearing Research, 41, 654-666. Bruininks, H.(1978). Bruininks-Oseretsky Test of Motor Proficiency. Circle Pines, MN: American Guidance Service. 89 Carroll, J.B. (1993). Human cognitive abilities: A survey of factor analytic studies. Cambridge, UK: Cambridge University Press. Cherkes-Julkowski, M. (1998). Learning disability, attention-deficit disorder, and language impairment as outcomes of prematurity: A longitudinal descriptive study. Journal of Learning Disabilities, 31, 294-306. Clark, C. M. & Ryan, L. (1993). Implications of statistical tests of variance and means. Journal of Clinical & Experimental Neuropsychology, 15, 619-622. Cohen, R. J., Swerdlik, M. E., & Philips, S. M. (1996). Validity. In Psychological testing and assessment: An introduction to tests and measurement (pp. 174-217), 3 r d Edition. Mountain View, CA: Mayfield Publishing Company. Dammann, O., Walther, H„ Allers, B., Schroder, M., Drescher, J., Lutz, D. et al. (1996). Development of a regional cohort of very low-birthweight children at six years: Cognitive abilities are associated with neurological disability and social background. Developmental Medicine and Child Neurology, 38, 97'-108. de Kleine, M. J., den Ouden, A. L., Kollee, L. A., Nijhuis-van der Sanden MW, Sondaar, M., Kessel-Feddema, B. J. et al. (2003). Development and evaluation of a follow up assessment of preterm infants at 5 years of age. Archives of Disease in Childhood, 88, 870-875. Dean, R. & Gray, J. (1985). Maternal Perinatal Scale. Unpublished test. Muncie, Indiana: Ball State University Dezoete, J.A., MacArthur, B.A., & Tuck, B. (2003). Prediction of Bayley and Stanford-Binet scores with a group of very low birthweight children. Child: Care, Health & Development, 29, 367-372. Dumont, R. & Willis, J. O. (1995). Intrasubtest scatter on the WISC-III for various clinical samples vs. the standardization sample: An examination of WISC folklore. Journal of Psychoeducational Assessment, 13, 271-285. Duncan, J. & Rafter, E. (2005). Concurrent and predictive validity of the Phelps Kindergarten Readiness Scale-II. Psychology in the Schools, 42, 355-359. Elliot, C. (1990). Differential Ability Scales. San Antonio, TX: Psychological Corporation. Fawer, C.L., Besnier, S., Forcada, M., Buclin, T., & Calame, A. (1995). Influence of perinatal, developmental and environmental factors on cognitive abilities of preterm children without major impairments at 5 years. Early Human Development, 43, 151-164. Feder, K.P., Majnemer, A., Bourbonnais, D., Piatt, Blayner, M. et al. (2005). Handwriting performance in preterm children compared with term peers at age 6 to 7 years. Developmental Medicine & Child Neurology, 47, 163-170. Flanagan, D. P. & Alfonso, V. C. (1995). A critical review of the technical characteristics of new and recently revised intelligence tests for preschool children. Journal of Psychoeducational Assessment, 13, 66-90. Flanagan, D. P., Alfonso, V. C , Kaminer, T., & Rader, D. (1995). Incidence of basic concepts in the directions of new and recently revised American intelligence tests for preschool children. School Psychology International, 16, 345-364. Flanagan, D.P., & Harrison, P.L. (2005). Contemporary intellectual assessment: Theories, tests and issues. New York, NY: Guilford Press. Flanagan, D.P. & Ortiz., S. (2001). Essentials of Cross-Battery Assessments New York: John Wiley & Sons. 91 ' Ford, L., Merkel, C, & Kozey, M. (under review). Use of the WJIII Tests of Cognitive Abilities and Achievement with Young Children. Assessment Service Bulletin. Itasca, IL: Riverside Publishing. Ford, L. (2003). Assessment of young children. In F.A.Schrank, N. Mather, K. S. McGrew, & R. W. Woodcock (Eds.), Manual for Woodcock-Johnson III Diagnostic Supplement to the Tests of Cognitive Abilities (pp. 37-46). Itasca, IL: Riverside Publishing. Ford, L. & Dahinten, S. (2005). The use of intelligence tests in the assessment of preschoolers. In D.P.Flanagan & P. Harrison (Eds.), Contemporary intellectual assessment: Theories, research, and issues (2nd ed., pp. 487-503). New York: Guilford. Ford, L. Kozey, M, & Merkel, C. (2006). Use of the Woodcock-Johnson III with young children. Poster session presented at the annual meeting of the National Association of School Psychologists conference, Anaheim, CA. Ford, L., Kozey, M., Merkel, C , & Swart, S. (2005). Contemporary perspectives and critical review of cognitive measures for young children. Paper presented at the annual meeting of the National Association of School Psychologists conference, Atlanta, GA. Ford, L., Merkel, C , Ford, L., Kozey, M., Merkel, C , & Swart, S. (2005). Basic concepts & their impact on cognitive measures for young children. Poster session presented at the annual meeting of the National Association of School Psychologists conference, Atlanta, GA. Forslund, M., & Bjerre, I. (1990). Follow-up of preterm children: II. Growth and development at four years of age. Early Human Development, 24, 107-118. Foulder-Hughes, L. A. & Cooke, R. W. I. (2003). Motor, cognitive, and behavioural disorders in children born very preterm. Developmental Medicine & Child Neurology, 45, 97-103. 92 Frisk, V., & Whyte, H. (1994). The long-term consequences of periventricular brain damage on language and verbal memory. Developmental Neuropsychology, 10, 313-333. Gatten, S. L., Arceneaux, J. M., Dean, R. S., & Anderson, J. L. (1994). Perinatal risk factors as predictors of developmental functioning. International Journal ofNeuroscience, 75, 167-174. Gormley, W., Gayer, T., Philips, D., & Dawson, B. (2005). The effects of universal Pre-K on cognitive development. Developmental Psychology, 41, 872-884. Goyen, T.A., & Lui, K. (2002). Longitudinal motor development of "apparently normal" high risk infants at 18 months, 3 and 5 years. Early Human Development, 70, 103-115. Gray, J. W., Davis, B., McCoy, K., & Dean, R. S. (1992). Mothers' self-reports of perinatal information as predictors of school achievement. Journal of School Psychology, 30, 233-243. Gray, J. W., Dean, R. S., & Rattan, G. (1987). Assessment of perinatal risk factors. Psychology in the Schools, 24, 15-21. Gray, J. W., Dean, R. S., Rattan, G., & Bechtel, B. A. (1988). Mothers' self-reports of perinatal complications. Journal of Clinical Child Psychology, 17, 242-247. Gray, J. W., Dean, R. S., Strom, D. A., & Wheeler, T. E. (1989). Perinatal complications as predictors of developmental disabilities. Developmental Neuropsychology, 5, 105-113. Gredler, G.R. (2000). Early childhood screening for developmental and educational problems. In B.Bracken (Ed.), The psychoeducational assessment of preschool children (3rd ed., pp.399-427). Needham Heights, MA: Allyn & Bacon. Grunau, R.E., Whitfield, M.F., & Davis, C. (2002). Pattern of learning disabilities in children with extremely low birth weight and broadly average intelligence. Archives of Pediatric and Adolescent Medicine, 156, 615-620. Hack, M. & Fanaroff, A. A. (1999). Outcomes of children of extremely low birthweight and gestational age in the 1990's. Early Human Development, 53, 193-218. Hack, M., Klein, N., & Taylor, H.G. (1995). Long term developmental outcomes of low birth weight infants. Low Birth Weight, 5, 176-196. Hack, M., Taylor, G., Klein, N., Eiben, R., Schatschneider, C , & Mercuri-Minich, B.S. (1994). School-age outcomes in children with birth weights under 750g. The New England Journal of Medicine, 331, 753-708. Hartlage, L. C. & Williams, B. L. (1997). Pediatric neuropsychology. In A.MacNeill Horton, D. Wedding, & J. Webster (Eds.), The neuro-psychology handbook (2nd ed., pp. 211-235). New York, NY: Springer Publishing Co. Harvey, J.M., O'Callaghan, M.J., and Mohay, H. (1999). Executive function of children with extremely low birthweight: A case control study. Developmental Medicine and Child Neurology, 41, 292-297. Herrgard, E., Luoma, L., Tuppurainen, K., Karjalainen, S., & Martikainen, A. (1993). Neurodevelopmental profile at five years of children born at <32 weeks gestation. Developmental Medicine and Children Neurology, 35, .1083-1096. Hill, S. K. (1998). Maternal perinatal events as predictors of sensory-motor functioning in normal children. Dissertation Abstracts International, 59(06), 3093B. (UMI No. 9838230). . Hill, S. K., Cawthorne, V., & Dean, R. S. (1998). Utility of the Maternal Perinatal Scale (MPS) in distinguishing normal from learning disabled children. International Journal of Neuroscience, 95, 141-154. Holdgrafter, G.U. (1995). Language abilities of neurologically normal and suspect preterm children now in preschool. Perceptual and Motor Skills, 80, 1252-1262. 94 Hooper, S. R. (2000). Neuropsychological assessment of the preschool child. In B.A. Bracken (Ed.), The psychoeducational assessment of preschool children (pp. 383-398). Boston: Allyn & Bacon. Huck, S.W. (2004). Reading statistics and research, 4lh Edition. New York: Pearson Education Inc. Johnson, E.O., & Breslau, N. (2000). Increased risk of learning disabilities in low birth weight boys at age 11 years. Biological Psychiatry, 45, 490-500. Jongmans, M.J., Mercuri, E., Dubowitz, L.M., & Henderson, S.E. (1998). Perceptual-motor difficulties and their concomitants in six-year-old children born prematurely. Human Movement Science, 17, 629-653. Kaufman, A.S., & Kaufman, N.L. (1983). Kaufman Assessment Battery for Children. Circle Pines, MN: American Guidance Service. Kalmar, M. (1996). The course of intellectual development in preterm and fullterm children: An 8-year longitudinal study. International Journal of Behavioral Development, 19, 491-516. Kesler, S.R., Ment, L.R., Vohr, B, Pajot, S.K., Schneider, K.C., Katz, K.H., et al. (2004). Volumetric analysis of cerebral regional development in preterm children. Pediatric Neurology, 31, 318-325. Kessenich, M. (2003). Developmental outcomes of premature, low birth weight and medically fragile infants. Newborn and Infant Nursing Reviews, 3, 80-87. Klebanoy, P.K., Brooks-Gunn, J., & McCormick, M.C. (1994). School achievement and failure in very low birth weight children. Journal of Developmental and Behavioral Pediatrics, 15, 248-256. Korkman, M., Kirk, U., & Kemp, S. (1998). The NEPSY. A developmental neuropsychological . assessment. San Antonio, TX: Psychological Corporation. 95 Korkman, M., Liikanen, A., & Fellman, V. (1996). Neuropsychological consequences of very low birth weight and asphyxia at term: Follow-up until school-age. Journal of Clinical Nueropsychology, 18, 220-233. Kozey, M., Merkel, C. & Ford, L. (2005). A validation of the WJ III Diagnostic Supplement Early Development Cluster Scores. Poster presentation at the August 2005 American . Psychological Association Conference, Washington, D.C. League, S. E. (2001). A joint factor analysis with the Woodcock-Johnson Tests of Cognitive Abilities-Third Edition and the Weschler Preschool and Primary Scales of Intelligence-Revised. Dissertation Abstracts International Section A: Humanities and Social Sciences, 61 (7-A), 2594. Litt, J., Taylor, G., Klein, N., & Hack, M. (2005). Learning disabilities in children with very low birthweight: Prevalence, neuropsychological correlates and educational interventions. Journal of Learning Disabilities, 38, 130-141. Lorenz, J. M. (2001). The outcome of extreme prematurity. Seminars in Perinatology, 25, 348-359. Lu, M. C , Tache, V., Alexander, G. R., Kotelchuck, M., & Halfon, N. (2003). Preventing low birth weight: is prenatal care the answer? Journal of Maternal-Fetal & Neonatal Medicine, 13, 362-380. Lucianna, M., Lindeke, L., Georgieff, M., Mills, M., and Nelson, C. (1999). Neurobehavioural evidence for working-memory deficits in school-aged children with histories of prematurity. Developmental Medicine & Child Neurology, 41, 521-533. Luoma, L., Herrgard, E., Martikainen, A., & Ahonen, T. (1998). Speech and language development of children born at <32 weeks gestation: A 5 year prospective follow-up study. Developmental Medicine & Child Neurology, 40, 380-387. 96 Ma, X. J. (1997). Perinatal complications as predictors of neuropsychological outcome in children with learning disabilities. Dissertations Abstracts International: Section B: The Sciences & Engineering, Vol 58 (7-B), Jan 1998.pp.3962. Marlow, N. (2004). Neurocognitive outcome after very preterm birth. Archives of Disease in Childhood Fetal and Neonatal Edition, 89, 224-228. Marlow, N., Wolke, D., Bracewell, M.A., & Samara, M. (2005). Neurologic and developmental disability at six years of age after extremely preterm birth. The New England Journal of Medicine, 352, 367-372. Mather, N. & Jaffe, L. E. (2005). Woodcock-Johnson HE Reports, recommendations and strategies. New York, NY: Jon Wiley and Sons, Inc. Matula, K., Gyurke, J. S., & Aylward, G. P. (1997). Bayley Scales-II. Journal of Developmental & Behavioral Pediatrics, 18, 112-113. McCarthy, D. (19/2). McCarthy Scales of Children's Abilities. San Antonio, TX: Psychological Corporation.. McLean, M. (2004). Assessment and its importance in early intervention/early childhood special education. In M. MacLean, M. Wolery & D.B. Bailey (Eds.), Assessing Infants and Preschoolers with Special Needs, 3rd Edition (p. 1-21). Columbus, Ohio: Pearson-Merrill Prentice Hall. McCullough, J. M. (2001). Relationship betM'een cognitive abilities and achievement in preschool children. Unpublished masters thesis. University of South Carolina. McGrath, M., & Sullivan, M. (2002). Birth weight, neonatal morbidities, and school age outcomes in full-term and preterm infants. Issues in Comprehensive Pediatric Nursing, 25, 231-254. McGrew, K. S. (2005). The Cattell-Horn-Carroll theory of cognitive abilities: Past, present, and Future. In D.P. Flanagan & P.L. Harrison (Eds.), Contemporary intellectual assessment: Theories, tests and issues (pp. 136-182). New York, NY: Guilford Press. McGrew, K.S., & Schrank, K. (2006). WJ III post-publication empirical research reference list. Posted February 20, 2006. Retrieved April 2, 2006. http://www.iapsych.com/articles/wj3ewokrefs.pdf McGrew, K. S., Flanagan, D. P., Keith, T. Z., & Vanderwood, M. (1997). Beyond g: The impact of Gf-Gc specific cognitive abilities research on the future use and interpretation of intelligence tests in the schools. School Psychology Review, 26, 189-210. McGrew, K. S. & Woodcock, R. W. (2001). Technical Manual. The Woodcock-Johnson III. Itasca, IL: Riverside Publishing Co. McGrew, K. S., Woodcock, R. W., & Ford, L. (2002). The Woodcock-Johnson -Third Edition (WJ III). In A.Kaufman, N. Kaufman, & E. .Lichetenberger (Eds.), Assessing Adolescent and Adult Intelligence (2nd ed., pp. 561-628). New York: John Wiley. Merkel, C. (2005). Relationship between Cattell-Horn-Carroll (CHC) cognitive abilities and early academic abilities in preschool children. Unpublished master's thesis, University of British Columbia, Vancouver, British Columbia, Canada. Minick-Vanhorn, R. E., Titus, J. B., & Dean, R. S. (2002). Maternal perinatal events as predictors of educational placement: Computation of relative risk ratios. International Journal of Neuroscience, 112, 313-333. Nagle, R. (2000). Issues in preschool assessment. In B.Bracken (Ed.), The psychoeducational assessment of preschool children (3rd ed., pp. 19-32). Needham Heights, MA: Allyn & Bacon. Neisworth, J. T. & Bagnato, S. J. (2004). The mismeasure of young children: The authentic assessment alternative. Infants and Young Children, 17, 198-212. Normandeau, S., & Guay, F. (1998). Preschool behavior and first-grade school achievement: The mediational role of cognitive self-control. Journal of Educational Psychology, 90, 111-121. O'Brien, F., Roth, S., Stewart, A., Rifkin, L., Rushe, T., & Wyatt, J. (2004). The neurodevelopmental progress of infants less than 33 weeks into adolescence. Archives of Disease in Childhood, 89, 207-211. Paneth, N. (1995). The problem of low birth weight. The Future of Children, 5, 19-34. Petersen, M.B., Greisen, G., Kovacs, R., Munck, H., & Friis-Hansen, B. (1990). Status at four years of age in 280 children weighing 2,300 g or less at birth. Danish Medical Bulletin, 34, 546-52. Repka, M. X. (2002). Ophthalmological problems of the premature infant. Mental Retardation & Developmental Disabilities Research Reviews, 8, 249-257'. Robison, D., & Gonzalez, L.S. (1999). Children born premature: A review of linguistic and behavioural outcomes. Infant-Toddler Intervention, 9, 373-390. Romero, I. (1992). Individual assessment procedures with preschool children. In E.V.Nuttall, I. Romero, & J. Kalesnick (Eds.), Assessing and screening preschoolers: Psychological and educational dimensions (pp. 55-66). Needham Heights, MA: Allyn & Bacon. Schrank, F.A., & Woodcock, R. W. (2003). WJIII Compuscore and Profiles Program, Version 2.0. Itasca, IL: Riverside Publishing Company. Schrank, F. A., Mather, N., McGrew, K. S., & Woodcock, R. W. (2003). Woodcock-Johnson III Diagnostic Supplement to the Tests of Cognitive Abilities. Itasca, IL: Riverside Publishing. Siegel, L.S. (1994). The long-term prognosis of preterm infants. Human Nature, 5, 103. Siegel, L.S. (1983). Correction for prematurity and its consequences for the assessment of the very low birth weight infant* Child Development, 54, 1176-1188. Siegel, L.S. (1982). Reproductive, perinatal and environmental factors as predictors of the cognitive and language development of preterm and full term infants. Child Development, 53, 963-973. SPSS Inc. (2003). SPSS Base 12.0 for Windows. SPSS Inc., Chicago IL. Taylor, H.G., Burant, C .J . , Holding, P. A . , K le in, N. & Hack, M . (2002). Sources of variability in sequaelae of very low birth weight. Child Neuropsychology, 8, 163-178. Taylor, H .G, K le in , N . , & Hack, M . (2000). School-age consequences of birth weight less than 750g: A review and update. Developmental Neuropsychology, 17, 289-321. Taylor, H.G. , K le in , N . , Min ich , N .M . , & Hack, M . (2000). Verbal memory deficits in children with less than 750 g birth weight. Child Neuropsychology, 6, 49-63. Taylor, H.G., K le in , N. , Schatschneider, C. & Hack, M . (1998) Predictors of early school age outcomes in very low birth weight children. Developmental and Behavioral Pediatrics, 19, 235-243. Teague, T. L. (2003). Joint factor-analytic investigation of the Differential Abi l i t iy Scales and the Woodcock-Johnson Tests of Cognitive Abil it ies-Third Edition with preschool-age children. Dissertation Abstracts International Section A: Humanities & Social Sciences, 62 (7-A), 2338. Thorndike, R., Hagen, W., & Sattler, J . (1986). The Stanford-Binet Intelligence Scale: Fourth Edition. Chicago: Riverside Publishing. Tusing, M . E. & Ford, L. (2004). Understanding measures of preschool cognitive abilities from a C H C framework. International Journal of Testing, 4, 91-114. Tusing, M. E., Maricle, D. E., & Ford, L. (2003). Assessment with the Woodcock-Johnson III and Young Children. In F.Schrank & D. P. Flanagan (Eds.), WJ III Clinical Use and Interpretation: Scientist and Practitioner Perspectives (pp. 243-283). San Diego, CA: Academic Press. Vanhorn, R. E. (2000). Maternal perinatal events as predictors of educational placement: Computation of relative risk ratios. Dissertation Abstracts International, 60 (07), 3598B. (UMI No. 9937195). Vicari, S., Caravale, B., Carlesimo, G., Casadei, A.M., & Allemand, F. (2004). Spatial working memory deficits in children at ages 3-4 who were low birth weigh, preterm infants. Neuropsychology, 18, 673-678. Vollmer, B., Roth, S., Baudin, J., Stewart, A., Neville, B., Wyatt, J.S. (2003). Predictors of long term outcome in very preterm infants: Gestational age versus neonatal cranial ultrasound. Pediatrics, 5, 1108-114. Wechsler, D. (1989). Wechsler Preschool and Primary Scale of Intelligence-Revised. San Antonio: The Psychological Corporation. Weisglas-Kuperus, N., Baerts, W., Smrkovsky, M. & Sauer, P. (1993). Effects of biological and social factors on the cognitive development of very low birth weight children. Pediatrics, 92, 658-665. Wilkerson, D. S., Volpe, A. G., Dean, R. S., & Titus, J. B. (2002). Perinatal complications as predictors of infantile autism. International Journal ofNeuroscience, 112, 1085-1098. Wolke, D., Ratschinski, G., Ohrt, B., & Riegel, K. (1994). The cognitive outcome of very preterm infants may be poorer than often reported: an empirical investigation of how methodological issues make a big difference. European Journal of Pediatrics, 153, 906-915. Woodcock, R. W., McGrew, K. S., & Mather, N. (2001). The Wpodcock-Johnson III. Itasca, IL: Riverside Publishing Co. Woodcock, R. W., McGrew, K. S., & Mather, N. (2001). Woodcock-Johnson III Tests of Achievement. Itasca, IL: Riverside Publishing. Woodcock, R. W., McGrew, K. S., & Mather, N. (2001). Woodcock-Johnson HI Tests of Cognitive Abilities.. Itasca, IL: Riverside Publishing. 102 Appendix A : Recruitment Letter for Children Recruited Through B C Children's NeoNatal Followup Cl in ic T H E U N I V E R S I T Y O F B R I T I S H C O L U M B I A Department of Educational & Counselling ^ Psychology, & Special Education 2125 Main M a l l Vancouver, B . C . Canada V 6 T 2B5 Tel: (604) 822-4602 Fax:(604) 822-3302 Dean-Woodcock Neuropsychological Assessment System Validity Study with Preschool Aged Children Born Premature Dear Parent/Guardian, We are writing to invite you and your child to take part in a research study that we are conducting. This project is funded by the Woodcock-Munoz Foundation, non-profit foundation dedicated to research in the assessment field and the Human Early Learning Partnership (HELP) at U B C . Your name was selected because of you were followed Neonatal Follow-up Programme at the Children's and Women's Health Centre of British Columbia and said you would like to know more about on going research projects. The purpose of this study is to learn more about the developmental tests we use to understand how children learn. Because these tests are often given to children born premature, it is important for us to learn more about how the tests work with children born premature. Your willingness to work with us is very important. It wi l l help us learn more about the test. While our focus is on the test and not your child for our study, we would also be able to give you a brief summary about your child's early learning skills, and areas where he or she may need more help to get ready for school. If you would like to take part in our study, we want you to know that taking part is voluntary (you do not have to take part i f you do not want to). Taking part in the study wi l l not affect any services you receive from the Children's and Women's Health Centre of British Columbia or any other agency. You wi l l also have the right to withdraw (or stop taking part) from the study at any time without any penalty i f you want. Taking part in the study means that you would take part in a 15 minute telephone interview to determine i f your child can take part in the study. If, after you learn more about the study and after we learn a little more about your child, i f the study is right for your child, you and your child wi l l be asked to take part in one or two in-person sessions of about two hours each. Y o u (the caregiver) wi l l be asked to complete a questionnaire about your child's development, learning, and health history and behavior as well as some general background information. This 103 will take about 20 minutes. Your child will take part in a one-on-one assessment of their learning with activities about language, thinking, motor and other learning abilities. The person assessing your child is trained in giving these tests to young children and will not give them unless your child is very comfortable and wants to take part. The assessment will take about two to three hours of your child's time in small settings with a lot of small breaks. Depending on your child, the assessment may take place over two sessions. If you/your child agree to take part in the in-person assessment, it will take place at a location that you agree to (most likely at the University of British Columbia or at your home). We will work with you to find the best place to do the assessment. We will send you a brief summary about the results of your child's assessment. If there are any concerns, study staff (who have all worked with young children born premature) will help you find ways to help your child and/or your family. There are no risks for your child's participation. To thank you for your time and any transportation expense, each family that takes part will receive $25 and your child will get a small book. It is very important to us that your family's right to privacy is respected. Therefore, all information collected as part of this research study will be kept confidential. No individual information will be reported to anyone not working with the study and no parent or child will be identified by name in any reports about the completed study. If you are interested in taking part or would like to learn more about the study, please call our research office at (604) 822-4602 or calling one of the researchers directly at the numbers listed below. After you contact us to learn more about the study, you will be asked if you want you to take part. If you do want to take part, our research team will find a time to conduct the telephone interview at a time works best for you. If you do decide to take part in this study and at any time have any concerns about your treatment or your rights as a research participant you may contact the Research Subject Information Line in the UBC Office of Research Services at the University of British Columbia at(604)822-8598. Sincerely, Laurie Ford, PhD Co-Investigator Department of Educational & Counselling Psychology and Special Education Michelle Kozey, BAH, BSc Co-Investigator Department of Educational & Counselling Psychology and Special Education 604-822-4602 604-822-0091 Appendix B: Newspaper Advertisement Run in Vancouver Sun 104 Was your 4 or 5 year old child b o r n p r e m a t u r e ? Have your child take part in our UBC research study Clinical Utility of the Dean-Woodcock Neuropsychological Assessment System with Preterm Children Participating children will receive a cognitive, early academic and sensory-motor assessment by trained UBC research professionals. You will receive $25 and a written summary of your child's results. Our study team is Dr. Laurie Ford, PhD, and Michelle Kozey, BScH, BAH, of the School Psychology Program in UBC Faculty of Education. PHONE the Study Coordinator Michelle at (604) 822-4602 This project is approved by the UBC Behavioural Research Ethics Board, & is funded by the Woodcock-Munoz Foundation, a non-profit foundation, and the Human Early Learning Partnership (HELP). 105 Appendix C: Consent Form for Children Recruited Through BC Children's NeoNatal Followup Clinic T H E U N I V E R S I T Y O F B R I T I S H C O L U M B I A Department of Educational & Counselling Psychology, & Special Education 2125 Main Mall Vancouver. B.C. Canada V6T 2B5 Tel: (604) 822-4602 Fax:(604) 822-3302 Dean-Woodcock Neuropsychological Assessment System Validity Study with Children Born Premature Consent Form for Child Assessment and Personal Interview Principal Investigator: Laurie A. Ford, PhD Associate Professor Department of Educational & Counseling Psychology & Special Education 604-822-0091 Co-Investigator: Michelle Kozey, BScH, BAH Graduate Student Department of Educational & Counseling Psychology & Special Education 604-822-4602 Project Office: 604-822-4602 Dear Parent/Guardian, Please read the following form carefully. Sign one copy and return. Keep the other for your records. This is a request for you and your child to take part in the study that we are doing. This project is funded by the Woodcock-Munoz Foundation, a non-profit foundation dedicated to research in the assessment field, and the Human Early Learning Partnership (HELP) at UBC, and is being conducted as part of a School Psychology graduate thesis." Purpose: The purpose of this study is to learn more about the developmental tests we use to understand how children learn. Because these tests are often given to children born premature, it is important for us to learn more about how the tests work with children born premature. The study will help us learn more about the test. Our focus is on the test and not your child for our study, By taking 106 part in this project, you may help to improve services for children born premature and their families. Research Study Participation: 1. Taking part in this part of the study means that you are agreeing to complete a questionnaire that asks about your child's your child's development, learning, and health history and behavior as well as some general background information. This will take about 20 minutes. 2. Your child will take part in a one-to-one assessment of their learning with activities about language, thinking, motor and other learning abilities. 3. The person assessing your child is trained in giving these tests to young children and will not give them unless your child is very comfortable and wants to take part. 4. The assessment will take about two to three hours of your child's time in small settings with a lot of small breaks. Depending on your child, the assessment may take place over two sessions. 5. Your taking part is voluntary and will not affect any services that your family or child receives from Children's and Women's Health Centre of British Columbia or any other agency 6. You have the right to withdraw from the study at any time and you have the right to not answer any of the questions. 7. You will receive a very brief summary about the results of your child's assessment if you would like. 8. If for some reason there are any concerns with how your child did on the test, study staff (who have all worked with young children bom premature) will help you find ways to help your child and/or your family. 9. The information you give us is confidential. No individual information will be reported and no parent or child will be identified by name in any reports about the study. The only people who will have access to the information you give us are the researchers working on this project. 10. You will receive $25 to help with any travel, parking or other costs that might occur because of taking part in the study and to thank you for your time. I 11. Your child will receive a small child's book as a thank you for helping us. 12. If at any time you have any concerns about your treatment or rights as a research participant, you may contact the Research Subject Information Line in the UBC Office of Research Services at the University of British Columbia at (604) 822-8598. 107 If you have any questions or concerns regarding study you may contact any of the researchers at the numbers above or leave a message at the project office (604-822-4602). Thank you. Laurie Ford, PhD Michelle Kozey, BScH, BAH Principal Investigator Co-Investigator 108 Dean-Woodcock Neuropsychological Assessment System Validity Study with Children Born Premature Consent Form for Child Assessment and Personal Interview Please check one of the following: Yes, I agree to take part in this part of the project and I agree that my child may take part in this project. No, I do not wish to take part in this part of the project and I do not wish my child to take part. Parent's/Guardian's signature (please sign): Parent's/Guardian's name (please print your name): Date: Child's Name: Child's Birth Date: Your signature indicates that you have received a copy of this consent form (Pages 1-3) for your own records. Appendix- D: Study Background Information Questionnaire 109 Background Information We would like you to tell us more about yourself and your preschool-aged child. Please complete the following questions about you, your preschool aged child, and your family. If you have any questions or concerns about this for, call Michelle Kozey at 604-822-4602. 1. What is your age? 2. What is your child's birth date? Day: Month: Year: 3. What is the sex of your child? • Female • Male 4. What is your child's race/ethnicity? (check one) • White/Caucasian o Asian (Japanese, Chinese, etc.) • East Asian (Pakistan, Sri Lanka, India, etc.) • African • Hispanic • First Nations/Aboriginal • Other (please tell us): 5. You are this child's: • Biological mother • Biological father • Stepmother • Stepfather 6. How do you describe the family living in your home: • Two parent family • One parent family • Blended family • Extended family • Other (please tell us) 7. How many children live in your home (including your child participating in the study)? • One • Two • Three • Four • Five • Six or more 8. What best describes your yearly household income (please check one)? • Les than $14,999 • $30,000 to $39,999 • $ 15,000 to $ 19,999 • $40,000 to $59,999 • $20,000 to $29,999 • $60,000 or more 9. What is the education of the mother of the child? • Some elementary • Some university • Some high school • Bachelors' degree • Completed high school • Some graduate studies • Some college or o Master's degree technical training • PhD • College or technical diploma • Other (Please tell us) 10. What is the mother's employment? 11. What is the education of the father of the child? • Some elementary • Some university • Some high school • Bachelors' degree • Completed high school • Some graduate studies • Some college or • Master's degree technical training • PhD • College or technical diploma • Other (Please tell us) 12. What is the father's employment? ' I l l Appendix E: Boxplot of Woodcock-Johnson III General Intellectual Ability-Early Development Score 160 k . o u 0) 140' TO TJ C 2 W 120-4-1 C V E a o ® 100-a> a 80H ra UJ < O O o 2 60-4 0 -1 _ P Preterm Sample Matched Sample from the W J I Standardization Sample 112 Appendix F: Boxplot of Woodcock-Johnson III Tests of Cognitive Abilities-Verbal Comprehension Score g) 16CH o o CO 26 140H 120H n TJ C 2 co c o '35 c a> JZ 9) k_ o. E o o j§ 100-a> > O O O 80H $ 60H I Preterm Sample I Matched Sample from the WJ Standardization Sample 113 Appendix G: Boxplot of Woodcock-Johnson III Tests of Cognitive Abilities-Visual Matching Score Preterm Sample Matched Sample from the WJ I Standardization Sample 114 Appendix H: Boxplot of Woodcock-Johnson III Tests of Cognitive Abilities-Incomplete Words Preterm Sample Matched Sample from the W J I Standardization Sample 115 Appendix I: Boxplot of Woodcock-Johnson III Tests of Cognitive Abilities-Memory for Names Preterm Sample Matched Sample from the W J I Standardization Sample 116 Appendix J: Boxplot of Woodcock-Johnson III Tests of Cognitive Abilities-Visual Closure Preterm Sample Matched Sample from the WJ III Standardization Sample 117 Appendix K: Boxplot of Woodcock-Johnson III Tests of Cognitive Abilities-Memory for Sentences Preterm Sample Matched Sample from the WJ III Standardization Sample 118 Appendix L: Boxplot of Woodcock-Johnson III Tests of Cognitive Abilities-Memory for Sentences Preterm Sample Matched Sample from the W J III Standardization Sample > 119 Appendix M: Boxplot of Woodcock-Johnson III Tests of Cognitive Abilities-Concept Formation Preterm Sample Matched Sample from the WJ III Standardization Sample 120 Appendix N: Boxplot of Woodcock-Johnson III Tests of Academic Achievement-Pre-Academic-Staridard Score 180H <D O u CO •a 160-m •o S 140H re T J c to 120-H E <D T> (w U <. 100-& Q. X o < 80-60 H 18 13 I Preterm Sample — , Matched Sample from the W J III Standardization Sample 121 Appendix O: Boxplot of Woodcock-Johnson III Tests of Academic Achievement-Letter-Word Identification Score Preterm Sample Matched Sample from the W J II! Standardization Sample 1 2 2 Appendix P: Boxplot of Woodcock-Johnson III Tests of Academic Achievement-Spelling Score Preterm Sample Matched Sample from the WJ I Standardization Sample 123 Appendix Q: Boxplot of Woodcock-Johnson III Tests of Academic Achievement-Applied Problems Score Preterm Sample Matched Sample from the W J Standardization Sample 124 Appendix R: Boxplot of Woodcock-Johnson III Tests of Academic Achievement-Picture Vocabulary Preterm Sample Matched Sample from the WJ Standardization Sample 125 Appendix S: Relationship Between Cumulative Maternal Perinatal Score and Preterm Performance on the Woodcock-Johnson III Test 21: Memory for Names 50.00 H 45.00 - \ 40.00 H (A Q. E 35.00 H 30.00 H 25.00 H 80 1 90 100 110 120 130 140 COG21: Memory for Names SS 

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