European Journal ofPsvcliolog}' of Education
2004. Vol. XIX, nU, 385-406
'O2004.J.S.P.A,
Pathsways to school achievement in very preterm
and full term children
Wolfgang Schneider
University ofWiirzburg. Germany
Dieter Wolke
Jacobs Foundation, Zurich, Switzerland
Matthias Schlagmiiller
University of Wurzburg, Germany
Renate Meyer
University ofKonstanz. Germany
Individual differences in academic success were investigated in a
geographically defined whole-population sample of very preterm
children with a gestational age of less than 32 weeks or a birth weight
of less than 1500 gm. The sample consisted of 264 verv preterm
children (75.6% of German-speaking survivors) and 264 controls
matched for gender, socioeconomic status, marital status and age of
mother, who were studied from birth. The present analyses focused on
the impact of cognitive skills assessed at ages 6 and 8 on academic
success at the age 13. IQ scores, prereading skills, reading, spelling,
and math performance assessed during the last kindergarten year and
again at the end of Grade 2 were used as predictors of academic
success in early adolescence. Differences between very preterm
children and controls in cognitive abilities already observed in earlier
assessments remained stable over time, with controls on average
performing more than half a standard deviation above the level of
preterm children. Preterm children also performed poorer on the
literacy measures and indicators of math performance. Multivariate
and causal modeling revealed different prediction patterns for the two
groups. Whereas IQ was particularly important for the prediction of
Research on this project was financially supported by a grant of the German Research Foundation (Deutsche
Forschungsgemcinschaft) to Wolfgang Schneider and Dieter Wolke (SCHN 315/15-1), We would like to thank Klaus
Riegel and Barbara Ohrt who sel up the Bavarian Longitudinal Study in the !980s. Furthermore, thanks are due to David
Bjorklund for his valuable comments on an earlier drafi of ihe manuscript and Marco Ennemoser for his assistance in
data analysis.
386
W. SCHNEIDER, D, WOLKE, M. SCHLAGMULLER, & R. MEYER
academic success in the pre-term sample, general IQ was less relevant
for the prediction of academic success in the control group. When
subgroups of at-risk children were formed according to birth weight
categories, we found that school problems were most pronounced for
children with extremely low birth weight (WOO gm and less).
Very preterm delivery is often related to a negative consequences such as brain insults
and pulmonary problems (cf,. Hack, Klein, & Taylor, 1995; Landry, Fletcher, Denson, &
Chapieski, 1993). Further adverse consequences include poorer mental and motor
development relative to term controls during the preschool and kindergarten years (Wolke,
1998; Skuse, 1999), For instance, meta-analyses of studies on the intellectual development of
very preterm and/or very-low-birthweight (VLBW) children have revealed that their IQs are
approximately 0.5 standard deviations below those of temi infants {e.g,, Aylward, Pfeiffer,
Wright, & Verhulst, 1989; Escobar, Littenberg, & Petitti, 1991; Omstein, Ohisson, Edmonds,
& Asztalos, 1991), Other developmental problems such as language delays as well as
articulation problems have also been noted to be more common in VLBW children (ef,,
Friedman & Sigman, 1992; Wolke & Meyer, 1999). It is still unclear whether these deficits
are due to damage and thus inhibition of. normal development in specific areas of the brain,
or related to general IQ deficits.
Most follow up studies of VLBW samples into the school-age years indicate continued
problems in early and middle childhood (cf. Hack et al., 1995; Taylor, Klein, Minich, &
Hack, 2000; Whitfield, Grunau, & Holsti, 1997, Wolke, Schulz, & Meyer, 2001). This
research .suggests that cognitive problems range from global mental impairment to subtle
weaknes.ses in specific neuropsychological domains, such as language, memory, executive
function, and visuo-niotor skills. Although there is some evidence that VLBW children may
have more marked impairments in the areas of visuo-spatial functioning and memory than in
the language domain, the overall pattem is not yet clear. Behavioral problems of VLBW
children include attention deficit hyperactivity disorder (ADHD), as well as deficits in social
competence and adaptive behavior (e.g., Botting, Powls, & Cooke, 1997; Hille, den Ouden,
Saigal, Wolke, Lambert, Whitaker, Pinto-Matrin, Hoult, Meyer, Verloove-Vanhorick, &
Paneth, 2001; Sommerfelt, Ellertsen, & Markestad, 1993). Moreover, deficiencies in acadeniie
achievement sueh as reading skills and mathematics have been reported in several studies
(Hille, den Ouden, Bauer, Brand, & Verloove-Vanhorick, 1994; Ross, Lipper, & Auld, 1991;
Bhutta, Cleves, Casey, Cradock, & Anand, 2002). Given that the cognitive and behavioral
problems of VLBW children interfere with learning, there is reason to believe that their
academic problems accumulate with increasing age. In fact, several cross-sectional studies
have reported higher rates of special education and more pronounced learning difficulties in
older compared to younger samples of VLBW children (e.g., Wolke, 1997; McCormick,
Gortmaker, & Sobol, 1990; Zelkowitz, Papageorgiou, Zelazo, & Weiss, 1995),
The leaming difficulties lead to a relatively high number of VLBW children requiring
special education. For instance, Hille et al, (1994) found that many of their VLBW children
suffered from reading and spelling problems when tested at the age of about eight years, with a
large percentage (more than 20%) of these children located in special education settings.
Evidence from related studies in North America (Saigal, Szatmarl, Rosenbaum, Campbell, &
King, 1991; Whitfield et al, 1997) or across the Westem countries (Saigal, den Ouden, Wolke,
Hoult, Pameth, Streiner, Whitaker, & Pinto-Martin, 2003) suggest that the percentage of at-risk
children receiving some form of special education may be even higher, up to 45%. This is
considerably more than you would expect for the general child population in European countries.
For instance, in Germany, only about 4% of a given school age cohort receive special education.
There is also increasing evidence that the school-related problems of VLBW children
continue to be substantial in adolescence and do not seem to reduce over time (Botting, Powls,
Cooke, & Marlow, 1998; Cohen, Beckwith, Pamielee, Sigman, Asamow, & Espinosa, 1996;
Saigal, Hoult, Streiner, Stoskopf, & Rosenbaum, 2000; Taylor et al., 2000).
SCHOOL ACHIEVEMENT IN PRETERM AND FULL-TERM CHILDREN
387
The achievement problems may be even more pronounced for those preterm children
with extremely low birth weight (ELBW; 1000 g and less) or bom at extreme prematurity
(<28 weeks). Those studies that compared groups at differeut neonatal risk (i.e., ELBW
children and VLBW children whose birth weight ranged between 1000 and 1500 g) found that
ELBW participants were even more disadvantaged than their VLBW counterparts (e.g.,
Klebanov, Brooks-Gunn, & McCormick, 1994; Saigal et al., 2000; Taylor et al., 2000), and
that there was a substantial negative correlation (about -,50) between birth weight and the
number of academic problems identified in adolescence. For instance, Taylor et al. (2000)
reported that about 45% of the less than 750 g group were placed in special education
programs compared to 25% of the 750 g to 1499 g group, and 14% of the term children.
Subsequent comparisons of the three groups at middle school-age suggested that the
consequences of premature delivery and very low birth weight were as apparent at this
measurement point as at early school age. Rates of grade repetition, special school programs,
and severe achievement problems were more prevalent in the less than 750 g group than in the
two other groups. There was also evidence that the less than 750 g group developed at a
slower pace relative to the (wo higher birth weight groups, and that verbal leaming skills were
specifically impaired (see also Taylor, Minich, Klein, & Hack, in press). Most of these studies
also emphasized the importance of social risk factors, indicating that children from low SES
famiiies and/or unfavorable family background were particularly vulnerable (Botting et al.,
1998; Saigal et al., 2000), i,e,, the effects were additive (Wolke, Schutz, & Meyer, 2001).
In contrast, studies of larger or low-risk preterm infants have not reported significant
deterioration in academic behavior over time (e,g,, Schothorst & van Engeland, 1996), or
reported only weak relationships between language problems of at-risk children identified
during the preschool years and subsequent reading and spelling skills (Wcindrich, JennenSteinmetz, Laucht, Esser, & Schmidt, 2000).
The patterns of findings appear to suggest that school achievement is more severely
affected the lower the birth weight or gestational period is, and that these deficits are long
lasting. However, there are several shortcomings of earlier studies. Many previous
longitudinal studies included no control group, employed arbitrary criteria to define cognitive
impairment, were single-centered studies, and generally included only short follow-up periods
(see Wolke, Ratschlnski, Ohrt, & Riegel, 1994; Wolke & Schulz, 1999, for more details
regarding these problems). Unclear is whether writing, reading or mathematical achievement
deficiencies are specific skill deficits or are more often explained by general cognitive
impairment (i.e., low IQ), There is a distinct lack of prospective research on differences or
similarities in the causal pathways between early deficits in pre-reading skills, the acquisition
of literacy and later school outcome in neonatal at-risk children. There is plenty of evidence
that individual differences in phonological information processing skills such as phonological
awareness, verbal memory capacity, and processing speed predict reading and spelling
development in 'normal', that is, randomly selected samples (cf, Bryant, MacLean, &
Bradley, 1990; Schneider & Naslund, 1999; Wagner & Torgesen, 1987), However, it is still
uncertain whether the same mechanisms that produce leaming problems in term children also
cause reading and spelling deficiencies in VLBW children. Thus understanding possible
differences would have immediate implications for educational intervention strategies with
very pretcmi infants.
For instance, if it tums out that VLBW children's reading problems are mainly caused by
poor phonological processing skills and not that much by low [Q, then it would make sense to
use phonological training programs with these children before they enter elementary school.
Such training programs have been shown to be particularly effective during the last year of
kindergarten (for a review, see Bus & van Ijzendoorn, 1999). Given that in most eases
objective data on the risk status of VLBW children are available from birth on, it should be
rather easy to identify these children in kindergarten and select them for specific phonological
treatment. So specific educational intervention programs (and not only different kinds of
medical treatment) could prevent prematurily born children from developing reading and
spelling problems.
388
W. SCHNEIDER, D. WOLKE. M. SCHLAGMULLER, & R. MEYER
The present paper reports on a large longitudinal study that investigated the intellectual
abilities, self-concept, language comprehension and expression, prereading and academic
skills in a population of very preterm children, matched term controls, and a representative
sample of children in the same age cohort living in a geographically defined area in the south
of Germany. These children were followed from hirth and tested at the ages of 5 months, 20
months, 4;8, 6;3, and 8;5 years. Questionnaire information on the cognitive and social
development of the sample and their school performance was obtained when participants were
12 to 13 years old. Results obtained for ihe preschool period have been published elsewhere
(e.g., Wolke, Ratschinski, Ohrt, & Riegel, 1994; Wolke & Meyer, 1999). In this paper, we
explore developmental trends in school achievement focusing on reading and spelling
development and school achievement between the ages of 6 to 13 years.
The aims ofthe present study were:
1)
To investigate the size of differences in cognitive development, achievement and
scholastic outcome between extremely, very low birthweight and low birthweight
children and to estimate the impact of socioecomic factors.
2)
To assess the causal pathways between pre-reading (phonological) skills and the
acquisition of literacy. Specifically, do the same relationships between preschool
measures of phonological skills and early literacy hold for both the VLBW children
and the control sample?
3
To assess the impact of early biological and social risk factors and early school
achievement in explaining scholastic outcome at 13 years of age. Do the same
factors predict later poor school outcome in groups of high- versus low-risk very
pretemi and control children?
Method
The design of the Bavarian Longitudinal Study (BLS) has been described elsewhere in
detail (e.g., Riegel, Ohrt, Wolke, & Osterlund, 1995; Wolke et al., 1994) and will only be
briefly outlined here. Ait infants born alive in a geographically defined area in Southern
Bavaria (Germany) between February 1985 and March 1986 and who required admission to a
children's hospital within the first 10 days after birth comprised the target sample. During the
study period, 70,600 births were registered in the region. The inclusion criterion was met by
7,505 children (10.6% of all births). The at-risk population ranged from very ill preterm
infants to tenn infants who required only brief observation in the special eare units. In addition,
916 healthy infants receiving care in the normal postnatal wards in the same hospital centres
or adjacent to the children's hospital were recruited as control infants during the same period.
Samples
The following samples were included in the subsequent analyses:
Very preterm children. Ofthe 7,505 at-risk children, 560 were very pretenn (<32 weeks
gestation) or very low birthweight children (birthweight<1500 g; referred to as VLBW/VP
subsequently) (see Wolke & Meyer, 1999). This sample comprised virtually all (>99%)
VLBW/PV children boni during thi.s period in this region. Of these VLBW/VP children, 158
died during the initial hospitallsation, and another seven died belween discharge from hospital
and 6;3 years of age. Four parents gave no written informed consent for participation in the study.
Forty-two parents and children were not included in the study because they did not speak
German. The potential sample of survivors thus comprised 349 very pretenn children. Of these,
264 very pretenn children could still be assessed at the ages of 6 to 13 years. A comparison of
those children who dropped out during the course ofthe study with those who participated from 3
years onwards did not show any systematic differences (cf Wolke & Meyer, 1999).
SCHOOL ACHIEVEMENT IN PRETERM AND FULL-TERM CHILDREN
389
For several statistical analyses, the sample of very preterm children was further
subdivided in groups of extremely low birthweight (ELBW; less than 1000 g), very low
birthweight (VLBW; between 1000 and 1500 g) and low birthweight (LBW; between 1500
atid 2500 g and gestational age less than 32 weeks).
Control group. From the 916 term children who received care in the normal postnatal
wards, a comparison group of 264 children was group-matched to the 264 VLBW children
according to sex of child, family SES, marital status ofthe parents, and maternal age.
Normative sample. A normative sample representative ofthe total population of Bavarian
infants was drawn from the complete BLS sample. Five stratification variables for constituting
a representative sample were available from the Statistical Yearbook 1985 for Bavaria and the
Bavarian Perinatal and Neonatal Survey 1985. These were sex distribution of newborn infants
(51% male), size ofthe community the parents were inhabiting (>50,000 inhabitants=27%),
educational level of mothers giving birth in 1985 (basic education: 9 years or iess-14%;
moderate education: 10-12 years with passed final exams: 76%; completed high school or
university education: 10%), gestation at birth (<32 weeks^O.9%; 32-36 weeks=6%), and
whether the infant had been admitted to a children's hospital within the first 10 days of life
(10.6%). There were 311 children in the normative sample. This sample was solely studied to
determine cohort-speeifie and regional norms, such as means, SD's and cut-off points for
determining cognitive impairment.
Medical and psychological foUow-up data around birth and in preschool
Prenatal and neonatal assessments are described in more detail in Wolke, Ratschinski,
Ohrt, and Riegel (1994). Within the group of very pretenn children, the amount of biological
risk was assessed using the 'Duration ofTreatnient Index'. Daily assessments of level of care,
respiratory support, and neurological status such as mobility, muscle tone, and neurological
excitahility were conducted from the first day after birth. The 'Duration ofTreatnient Index'
was computed as the number of days until the infant reached a stable clinical state (Wolke et
al., 1994; Gutbrod, Wolke, Sochne, & Riegel, 2000). SES was computed as a weighted
composite score of maternal highest educational qualification, and occupation ofthe head of
family (Bauer, 1988). For the analyses presented in this article, however, a transformed
categorical measure was used (high, middle, and low SES). As part of a full neurological and
psychological assessment program, children's eognitive development was assessed at 5 and 20
months of age, corrected for prematurity with the Griffiths Scales of Babies Abilities (Brandt,
1983), and the Columbia Mental Maturity Scale (CMM; Burgemeister, Blum, & Lorge, 1972)
at 4 years 8 months chronological age.
The si.x-year assessment
The major aim of this assessment was to test children's cognitive and language skills
before they began elementary school (Wolke & Meyer, 1999). Ninety-four percent ofthe
children were still in kindergarten at the time of testing, and those who had entered school had
less than three months of schooling.
Cognitive status. Children's intelligence was assessed with the German version ofthe
Kauftnan Assessment Battery for Children (K-ABC; Kaufman & Kaufman, 1983; Melchers &
Preuss, 1991). This battery is based on neuropsychological and information-processing
theories of intellectual functioning. Intelligence is measured with the Mental Processing
Composite (MPC; eighl sublests), designed to test basic mental processes. The MPC is
subdivided in two further subscores, the simultaneous information processing score (SGD)
based on the results of five suhtests requiring the processing of several stimuli at the same
time, and the sequential information processing score (SED) based on three subtests that
390
W. SCHNEIDER, D. WOLKE, M. SCHLAGMULLER, & R. MEYER
require Ihe processing of individual stimuli one-by-one. The Achievement Score (AS)
includes three subtests measuring what has been learned by the child.
Language development. Four subtests were used from a German test battery for language
development (the Heidelberger Sprachentwicklungstest HSET; Grimm & Scholer, 199!). These
included the following subscales: plural-singular rules, correction of semantically inconsistent
sentences, sentence production, and understanding of grammatical structures. Standardized
scores (T-scores) are available for each subtest as well as for the total score of the four subtests.
Academic self-concept. The cognitive self-esteem scores of the Harter Pictorial Perceived
Competence Scale (Harter & Pike, 1984; Asendorpf & van Aken, 1993) were chosen to assess
academic self-concept. The cognitive competence subscale emphasized academic performance
(being smart, feeling good about one's performance). Each item was scored on a four-point
scale, where a score of 4 indicated the most competent, and a score of 1 the least competent.
Prereading skills. The ability to recognize and categorize sounds (phonological awareness)
has been found to be particularly predictive of later reading and spelling skills and difficulties
(cf, Bradley & Bryant, 1983; Goswami, 1990; Schneider, 1993; Schneider & Naslund, 1999),
even when controlling for social and environmental factors (Raz & Bryant, 1990). The phoneoddity task involves rhymes in which three of four words share a common phoneme and the child
has to detect the odd word (Bradley & Bryant, 1983), This can be problematic, however, because
children must retain four words in order to make a decision. Given that not all of the six-yearolds have a memory span of four words (see Schneider & Naslund, 1999), a modified phoneoddity measure was adapted for this study that makes fewer requirements on memory
(Skowronck & Marx, 1989), The rhyming task consisted of 18 word pairs, half of which rhymed.
The number of correctly identified rhyming and non-rhyming pairs was counted.
In the sound-to-word matching task, children had to repeat each given word, and then
indicate if a specific phoneme pronounced by the experimenter was included in the presented
word. For example, the experimenter presented the word "Auge" and asked children whether
it contained an "au" phoneme. Again, the number of correct responses was counted. Both the
rhyming and sound-to-word matching task items were presented from a standard prerecorded
tape to all children to control for possible differences in pronunciation by different
experimenters. Intemal consistency was high for both tasks (alpha's>.90).
The naming of numbers and letters assessed children's knowledge of the alphabet and the
number sequence 0 to 9, Children were instructed to read a row of letters (random order) and
to indicate those that they knew. Answers were judged correct if the child could name,
pronounce, or say a word that began with the letter. Similarly, the digits were presented and
the child asked to name them. The total number of correct answers was calculated separately
for the naming of letters and numbers.
The eight-year-assessment
This assessment took place when children were in the fmal period of second grade. Their
average age was 8 years and five months.
Intelligence and language development. Again, children's intelligence was assessed with
the German version of the K-ABC, A total IQ score (Mental Processing Component: MPC) as
well as the various subtest scores described above were used in the statistical analyses. Also,
the test battery for language development (HSET) described above was used at this
measurement point.
School achievement. The Zurich Reading Test (Grissemann, 2000) was used to assess
reading speed and the number of reading errors. In addition to this standardized test assessing
children's word decoding skills, a pseudoword reading test developed by Leon-Villagra and
Wolke (1993) was given. It has been repeatedly shown that poor readers experience particular
SCHOOL ACHIEVEMENT IN PRETERM AND FULL-TERM CHILDREN
391
problems with pseiidowords, whereas normal readers' performance does not differ
significantly as a function of word materials (i.e., meaningful words versus pseudowords; see
Schneider & Naslund, 1999; Winimer, 1996), Internal consistency for the pscudoword reading
test was sufficiently high (alpha=.9t),
A standardized spelling test {Diagnostischer Rechtschreibtest DRT 2; Muller, 1983) was
used to assess children's spelling competencies. This closed test required participants to fill in
single words dictated by the experimenter into sentences depicted on the test materials. The
numbers of orthographic errors served as the dependent variable.
Finally, a measure assessing mathematical competencies was provided which was
developed by Wolke and Leon-Villagra (1993) as a German adaptation of the test package by
Stigler, Lee, and Stevenson (1990), The three subtests Estimation of sizes. Reasoning, and
Visualization were highly correlated (>,40) and summarized in one scale (Math performance;
alpha=.93).
Self-concept. In addition to academic success, self-perceived academic competence was
assessed again using the German version of the Pictorial Scales of Perceived Competence
described above (Barter & Pike, 1984; Asendorpf & van Aken, 1993).
The 13-year assessment
Academic success. When participants were about 13 years of age, a questionnaire was
seni out to them as well as to their parents in order to obtain information on academic success
and changes in self esteem. The response rate was good: 76% of all surviving very preterm
participants and about 95% of the controls (and their parents) answered the questionnaires.
A complex procedure was developed to measure academic success taking into account
level of educational track and performance within each track based on end of school year
grades. This procedure had to acknowledge the fact that in German schools (Bavaria) a
selection procedure (educational tracking) takes place after Grade 4 (the last year of elementary
school). Those children with above average or average achievement scores move on either to
the high or middle educational tracks (Gymnasium or Rcalschule). Those children with belowaverage academic performance continue with the low educational track (Haup(schule), Finally,
children with particularly poor academic achievement may receive special education
(Sonderschule), The ranking scale depicting academic succes.s combined information on the
educational track status and academic performance within the particular educational track (as
indicated by grades in math and German). The highest score of 9 was given to those students
who not only attended the Gymnasium (highest track) but also were at the age-appropriate grade
level (Grade 7) and showed average or above average performance {i.e,, grade mean better than
average), A score of 8 was given to those Gymnasium students who attended the ageappropriate class level but whose performance was below the mean, etc. Finally, a score of 1
was given to students who had received special education throughout their sehool career.
Statistical analysis
In a first step, comparisons were made between the total sample of VLBW/VP children
and matched control groups. Analyses of variance were carried out to assess group differences.
In a second step, multiple regression analyses were run for both groups in order to investigate
the impact of social and cognitive variables assessed over the preschool and kindergarten years
on subsequent reading, spelling, and math performance at the end of second grade. More
comprehensive structural equation modeling was carried out next, with the aim of assessing the
roles of preceding noncognitive and cognitive measures for academic success measured at the
age of 13, Finally, the sample of very preterm children was further subdivided in comparison
groups that differed in birth weight. More specifically, a set of ANOVAs was conducted using
the subsamples of extremely low birthweight eliildren (ELBW; less than lOOOg), very low
birthweight children (VLBW; between 1000 and 1500 g), and low birthweight children (LBW;
392
W. SCHNEIDER. D, WOLKE. M, SCHLAGMULLER, & R. MEYER
more than 1500g and less than 2500g; gestational age less than 32 weeks) to investigate whether
differences in birthweight were associated with educational outcomes.
Results
Preliminary analyses revealed that there were no differences between the control group
and the normative sample for any of the variables under study. For the sake of simplicity, only
the control group data are used in the following analyses.
Table I gives the means and standard deviations for ali of the variables considered in
subsequent analyses, as a function of group membership. The table also indicates the
significance of group differences and their practical importance (effect size), using the eta
statistics. As can be seen from Table 1, group differences for all of the variables under study
were significant. Moreover, the majority of these differences were substantial, as indicated by
the effect sizes (eta scores). With a few exceptions, eta scores ranged between .5 and 1,
indicating that the mean differences between the VLBW children and the controls ranged
between half a standard deviation and a standard deviation for those variables, which reflects
moderate to strong effects.
Table I
Means and standard deviations for all of the variables considered in subsequent analyses, as
a function of group membership
VLBW
Variable
SES
Gri'mih's EQ (20 mths)
CMM7'-scorc(4;8yrs)
Language r-score (6;3 yrs)
Lener Knowledge (6;3 yrs)
Number Knowledge (6;3 yrs)
Phoneme Test (6;3 yrs)
Rhyming Task (6;3 yrs)
K-ABC Scale S1F(6;3 yrs)
K-ABC. Scale SlF(8;5yrsj
Zurich Reading(en-ors;8;5yrs)
Spelling test (errors; 8;5 yrs)
Mathematics lest (8;5 yrs)
Academic success (13 yrs)
Control
M
SD
M
SD
1.89
92,06
40,49
44,97
5.12
5,41
9.15
11,37
86,61
89,28
38,46
14,56
12,45
4.42
0.75
21.60
17.51
8,25
6,67
3,72
4,61
5,10
16,50
17,98
52.64
7.04
5,19
2,94
1.91
106.39
50.46
51,52
8,46
7,98
11,83
13.46
100.16
100.52
13.52
10,59
16,30
6.76
0.75
6,71
10.00
6,77
7,83
2,45
3,17
3,11
11,24
9,92
14,15
5,66
3,39
2,31
P<
n.s.
001
001
001
001
001
001
001
001
001
001
001
001
001
eta
0,03
1,01
0.72
0,47
0,46
0,83
0,69
0,51
0,98
0.81
0.75
0.63
0.90
0.83
The relative impact of biological and social risk factors on academic achievement
To assess the relative impacts of biological and social risk faetors on indicators of
cognitive and academic achievement at the age of 8 years, analyses of variance using group
membership (VLBW vs. control) and SES (low, middle, high) as independent variables were
carried out for IQ (K-ABC-MPC), reading (number of errors, Zurich reading test), spelling
(number of errors, DRT 2), and math (conceptual understanding - see Table 2).
For the IQ variable (MPC) there was a significant group effect, F(l,487)=68.9, p<.(i],
and also a reliable effect of SES, F(2,487)=8.8,/3<,01. As can be seen from Figure 1, effects
of SES were similar for the two group.s. However, the effects of premature birth were stronger
than effects of SES, given that low-SES control children performed better than high-SES
children at risk, /(142)^3.67,/)<.0L The group difference in mean IQ at age 8 was substantial
(about a standard deviation) and comparable to the differences found at earlier assessments
(Caughy, 1996; Landry, Smith, Miller-Loncar, & Swank, 1997; Sameroff, Seifer, Baldwin, &
Baldwin, 1993; Wolke et al., 1994; Wolke & Meyer, 1999). About 21,9% of the VLBW
children but only 2,3% of the controls showed serious intellectual deficiencies, with IQs more
than two standard deviations below the mean.
SCHOOL ACHIEVEMENT IN PRETERM AND FULL-TERM CHILDREN
393
no
105
100
95
- • - S E S high
- • -SES middle
-•-SES low
90
80
VLBW
Control
Group
Figure I. Results of an analysis of variance using group tnembership (VLBW vs. control) and
SES (low, middle, high) as independent variables and IQ (K-ABC total score; at age:
6;3 years) as dependent variable
The analysis of variance using reading errors at age 8 as Ihe dependent tiieasure yielded
significant effects of group, F( 1,485)^54,6, p<.0\, but no effect of SES, /^(2,485)-2.0,/j> 05
(Table 2). Again, control children outperformed VLBW children. The group by SES
interaction was not significant. Overall, the mean reading error difference between VLBW
children and controls was about three quarters of a standard deviation, thus indicating a
moderately strong effect. Fitidings for the spelling error variable were similar. Group membership .showed a main effect (F( 1,483)^46.2, / J < . 0 1 , but there was no effect of SES and no
interaction. The mean perfoniiance difference between the two groups was about two thirds of
a standard deviation, again indicating a moderately strong effect. Finally, an analysis of
variatice with group membership and SES as independent factors and math performance
(conceptual understanding) yielded slightly different results. Both group membership,
F(],490)-97.9,/?<.0l, and SES, f(2,490)-4.2,;?<.05 (Table 2), had a significant effect for the
group and SES variable, respectively. There was no significant interaction. Table 2 shows the
means and standard deviations oflhe three criterion variables as a function of group and SES.
Table 2
Means and standard deviations (in parentheses) of ihe three criterion variables assessed at
8:5 years, as a function of group and SES
VLBW
Control
Variable
SES low
SES tniddie
SES high
SES low
SES middle
SES high
Zurich Reading (errors; 8;5 yrs)
45.82
(55.55)
15,39
(7.01)
12,01
(5.52)
34,05
(48,09)
i4,66
(6,87)
12.62
(4.87)
36.74
(56.43)
13.40
(7.29)
12.75
(5,37)
15.77
(14.72)
11.01
(5.74)
15.31
(3,50)
13,78
(14,22)
10.77
(5.7 i)
16.42
(3.06)
9,97
(12,67)
9,67
(5,44)
17,48
(3.44)
Number of cnrors DRT 2 (8;5 yrs)
Mathematics test (8;5 yrs)
Prediction of school achievement at age 8. Multiple stepwise regression analyses were
run to explore the impact of biological risk, social background, and cognitive abilities assessed
during the preschool and kindergarten years on reading, spelling, and mathematics perfonnance
at the end of Grade 2. Data of both the VLBW and control children were simultaneously
entered in the regression analysis, and group membership was coded as a dummy variable.
Predictors used were SES, language developtnent (total score), intelligence (K-ABC total
score, assessed at age 6), letter and number knowledge at age 6, self-concept at age 6, as well
as rhyming and phoneme discrimination at age 6,
W. SCHNEIDER, D. WOLKE, M. SCHLAGMULLER, & R. MEYER
394
Table 3 shows the outcome of stepwise regression analyses carried out separately for
reading, spelling, and math. When reading errors in the Zurich Reading Test were used as
criterion variable, about 40% ofthe variance could be predicted by the intelligence variable
{K-ABC-MPC at 6 years) alone. In subsequent steps, rhyming skills and number knowledge
accounted for additional variance in the reading variable. Overall, about 50% ofthe variance
in reading errors was explained by this combination of predictor variables. Group membership
did not significantly contribute to the prediction.
Table 3
Results of stepwise regression analyses for age 8 data, separately for the criterion variables
reading, spelling, and math
Predictors
(a) Dependent variable: Reading {R^ coiTected: 0.50)
IQ
Rhyming
Number Knowledge
(b) Dependent variable: Spelling {R- correcled: 0.41)
Letter Knowledge
10
Number Knowledge
Rhyming
(c) Dependent variable: Math {R- corrected: 0.56)
IQ
Phoneme Knowledge
Number Knowledge
Group
Letter Knowledge
Beta
T
P<
.41
8.88
4.97
4.11
0.01
0.01
0.01
.13
5.93
4.80
4.75
2.96
O.OI
O.OI
O.OI
0.03
.52
.13
.11
.08
.08
12.15
3.09
2.80
2.24
2.04
0.01
0.01
0.01
0.05
0.05
.22
.17
.25
.23
.22
Similar findings were obtained for spelling. Here, letter knowledge, IQ, number
knowledge, and rhyming contributed to the prediction, explaining about 4 1 % ofthe variance
in the dependent variable. Again, group membership did not contribute to the prediction.
Finally, the stepwise regression analysis using mathematics performance as dependent
variable yielded different results. Here, IQ turned out to be a very powerful predictor,
accounting for about 45% of the variance. Adding phoneme and number knowledge further
improved model fit. In addition, group membership and letter knowledge contributed to the
prediction of math performance. Overall, 56% ofthe variance in math perfonnance could be
explained by these predictor variables.
Given that group tnembersliip was a significant predictor of math performance, separate
stepwise regression analyses were carried out as a function of this classification variable. Overall,
results for VLBW children were most impressive. IQ turned out to be a powerful predictor,
accounting for about 64% of the variance. Adding number knowledge further improved model
fit. In total, 67% ofthe variance in VLBW children's math performance could be explained by
these two predictor variables. In comparison, only about 23% of the variance in the control
children's math performance could be explained by the regression model, indicating that IQ,
letter knowledge, and SES assessed in kindergarten had the greatest predictive power.
Predietion of academic achievement at age 13. As can be seen from Table 1 {last row),
control children showed higher levels of academic achievement than VLBW children when
the two groups were compared at age 13. This difference was not only statistically significant
but also substantial, yielding a difference close to a standard deviation. Causal modeling using
latent variables (AMOS) was used to explore the importance ofthe kindergarten predictor
variables as well as that of academic achievement assessed in elementary school {i.e., at age 8)
for prediction of academic success at the age of 13.
SCHOOL ACHIEVEMENT IN PRETERM AND FULL-TERM CHILDREN
395
A sequential strategy was used to test the assumption that the same pattem of
interrelationships would hold across the two groups. In a first step of analysis, we explored
whether the same measurement model held across the two groups. This assumption had to be
rejected given that model fit was very poor (;j<.0001). In a second step, we tested a
simultaneous model that allowed for different measurement models across groups but assumed
that the structural relations among constructs (i.e., the path coefficients) should be equivalent
across the two groups. Again, model fit was suboptimal (/?<.OO1), indicating that the
simultaneous model did also not hold using such less strict assumptions. As a consequence, the
simultaneous model was rejected and independent (one sample) models were estimated next.
ln the initial model specified for VLBW children, individual differences in biological risk
and SES were used as exogenous variables, which were assumed to predict IQ and
phonological skills assessed during the last year of kindergarten. In tum, the kindergarten
measures should predict reading, spelling, and math performance assessed at the end of second
grade (i.e., age 8). The model also specified a significant impact ofthe latter variables on the
measure of academic success at the age of 13.
Initial model estimates indicated that the original model did not fit the data. A closer
inspection of modification indices showed that the inclusion ofthe biological risk variable as
exogenous factor caused estimation problems. To improve model fit, the model was re-speeified,
and the biological risk variable was omitted. The resulting causal model is depicted in Figure
2. As can be seen from this figure, SES at birth had a moderate impact on IQ assessed at age
6. In ttu-n, IQ had a substantial effect on phonological awareness in kindergarten and also
strongly predicted math performance at age 8. IQ did not directly influence reading but had a
substantial indirect effect via phonological awareness. In comparison, the IQ effect on spelling
was insignificant and thus was omitted from Figure 2. Interestingly, phonological awareness
in kindergarten had a very strong impact on both reading and spelling assessed at the end of
second grade, explaining considerable amounts of variance in these constructs (67% and 76%
for reading and spelling, respectively). The three school achievement measures assessed at age 8
(i.e., reading, spelling, and math) had moderate but reliable effects on academic success
measured at the age of 13. Overall, about 64% ofthe variance in the academic success
measure could be explained by this model.
76
Figure 2. Structural equation model showing relationships between SES, IQ, phonological
awareness, and academic performance for the at-risk sample
Note. Chi-sqijare=196.21 (48 (//);;J=.OOO; n-t=.98; RMSR= 108.
396
W. SCHNEIDER, D, WOLKE, M, SCHLAGMULLER, & R, MEYER
Model fit was examined using the comparative fit index (CFI; Bentler, 1990) and the root
mean square error of approximation (RMSEA; Steiger, 2000), The CFI has a range from 0 to
1,0, with higher numbers representing better fit. CFI values larger than .95 seem generally
acceptable. The RMSEA index provides a measure of misspecification per degree of freedom.
Values under .06 indicate relatively good fit between a hypothesized model and the observed
data (Hu & Bentler, 1998). The model fit indicators obtained for the preterm sample did not
fulfill each of these threshold values {CFI=,98; RMSREA=.1O) indicating that one should be
somewhat cautious when interpreting the causal model,
A similar model was specified for the matched control children (cf.. Figure 3). Overall,
the structure of path coefficients was similar to that obtained for the VLBW children, SES
assessed at birth had a somewhat stronger effect on IQ assessed at age 6 in this group than it
had for the VLBW children, IQ showed a strong impact on phonological awareness during the
last kindergarten year, and also had a moderately strong effect on math at the end of Grade 2.
IQ also had an indirect effect on reading via the phonological awareness variable. Again, the
effect of IQ on spelling was negligible and insignificant. Although all of the three school
achievement measures showed a significant effect on academic success at the age of 13 years,
spelling had the strongest impact. Overall, 42% of the variance in the academic success variable were explained by this model. The model estimated for the controi children yielded a data
fit similar to that specified for the VLBW children {CFI-.98, RMSREA=. 10).
49
Figure 3. Structural equation model showing relationships among SES, IQ, phonological
awareness, and academic performance for the control group
Note. Chi-square=l92.89
(48df);p=.O00: CFI^,9S:
RMSR^.107.
Comparisons among at-risk subsamples
More recent findings have indicated that children of extremely low birthweight {ELBW;
less than 1000 g) show poorer educational outcomes as compared to VLBW children, preterm
children with low birthweight (LBW; more than 1500 g), and term-born controls (e.g.,
Klebanov et a!,, 1994). A closer inspection of our biological risk sample showed that 57
participants belonged to the ELBW group, another 135 children to the VLBW group, whereas
72 children could be classified as members of the LBW group. The means and standard
SCHOOL ACHIEVEMENT IN PRETERM AND PULL-TERM CHILDREN
397
deviations of IQ and outcomes on various educational test measures are given in Table 4, as a
function of group niemhersliip.
Table 4
Means and standard deviations for relevant variables, as a function of at-risk subsamples and
control group
ELBW(l)
Variable
SES
Griffith's EQ {20 nnhs)
C M M T-score (4;8 yrs)
Language 7-score (6;3 yrs)
[.elter Knowledge (6;3 yrs)
NumlKT Know ledge (6;3 yrs)
I'lioncmi; Tesl (6;3 yrs)
Rhyming Task (6;3 yrs)
K-At3C. Scale S ; F ( 6 ; 3 yrs)
K-ABC. Scale SiF(8;5 yrs)
larter Scale cognition (6;3 yrs)
laner Scale cognition (8;5 yrs)
Zurich Reading (err; 8;5 yrs)
Spelling lest (errors; 8;5 yrs)
Mathematics test (8;5 yrs)
Academic success (13 yrs)
VLBW (2)
LBW (3)
control
M
SD
M
SD
M
SD
M
SD
1.89
82.76
34.29
44.88
4.46
4.94
7.13
9.26
77.46
79.38
3.05
2.88
65.12
17.46
9.38
3.12
0.82
25.72
18.77
8.19
6.57
3.94
4.92
5.67
I6.B1
19.80
.55
.53
66.88
6.87
5.38
2.81
1.85
91.64
39.56
4S.O0
4.59
5.47
9.50
11.81
88.48
89.89
3.07
3.22
35.38
14.71
12.75
4.21
0.72
21.84
17.02
7.70
6.13
3.60
4.40
4.96
15.29
16.76
.51
.45
48.99
6.73
4.93
2.78
1.9
99.93
46.86
50.44
6.67
5.67
10.07
!2.32
90.57
96.67
3,03
3.31
21.59
11.76
14.59
5.85
0.78
13.53
15.55
8.57
7.53
3.79
4.34
4.38
15.90
14.57
.48
.41
34.73
6.76
4.24
2.78
1.91
106.39
50.46
51.52
8.46
7.98
11.83
13.46
100.16
100.52
3.22
3.45
13.52
10.59
16.30
6.76
0.75
6.71
10.00
6.77
7.83
2.45
3.17
3.11
11.24
9.92
.42
.40
14.15
5.66
3.39
2.31
SNK-Test
1-2
1-3
2-3
•
••
*
•
•
•
*
•
•
•
••
•
•
**
•
•
•
•
•
•
*
•
*
Note.
Several analyses of variance were carried out using group membership as independent
factor and IQ measures, language ability, and prereading measures as dependent variables.
Effects of group membership were significant for all ofthe IQ measures depicted in Table 4
(all/3's<.OO5). Subsequent S(udent-Newman-Keuls (SNK) tests revealed that ELBW children
performed significantly poorer than VLBW children on these measures, who in turn were
outperfonned by the LBW children. Although control children tended to perform better than
the LBW children, IQ differences were not significant. A significant main effect of group
membership was also found for the HSET language test, F(3,479)=6.56, /?<.002). Subsequent
SNK tests showed that ELBW children performed significantly worse than all of the other
groups, and that VLBW children were outperformed by both the LBW and the control children,
which did not differ from each other. Furthermore, significant effects of group membership on
results ofthe phoneme test and the rhyming task were found, F(3,479)=6.18,/J<.002, and
F{3,479)=5.99, /X.003, respectively. Again SNK tests showed that the ELBW children
performed poorest on both of these measures. On both tasks, the two other at-risk groups
performed significantly better than the ELBW children, but did not differ from each other.
Control chiidren performed best on these tasks, and significantly better than the three
remaining groups.
Another set of analyses of varianee were carried out for the educational outcome
measures assessed at the ages of 8 and 13 to compare performance of the three at-risk
subgroups with that of the term-born eonfrols. The analysis using group membership as
independent factor and reading (number of errors, Zurich reading test) as dependent measure
yielded a significant group effeet, F{3,479)=34.31, p<.Q I. Subsequent Student-Newman-Keuls
(SNK) tests revealed that the controi children and the LBW group differed significantly from
the VLBW group, which in turn performed significantly better than the ELBW group. A
similar ANOVA carried out for spelling as dependent variable yielded a main effect of group,
f(3,479)=23.65,;?<.01. Post hoc SNK tests showed that all ofthe subgroups differed reliably
from each other: the control children performed best, followed by the LBW, VLBW, and
ELBW groups, respectively. The ANOVA carried out for math performanee at age 8 yielded
comparable results, F(3,479)=48.05,/J<.OI. Again, subsequent SNK tests revealed that the
W, SCHNEIDER, D. WOLKE, M, SCHLAGMULLER, & R, MEYER
398
control group performed best, followed by the LBW, VLBW, and ELBW groups, respectively.
Finally, a similar analysis of variance using group as independent factor and academic success
at the age of 13 as dependent variable indicated that the pattern of findings obtained for the
early elementary school years was replicated. There was a reliable group effect,
F(3,527)=49.41, /X.Ol. Subsequent SNK tests showed that all of the four groups differed
significantly from each other, with the control group and the ELBW children forming the
extremes.
An interesting finding concerned the development of academic self-concept in the
various groups, A repeated measurement analysis of variance using group membership as
independent factor and academic self-concept assessed at the ages of 6 and 8 years as
dependent variable revealed significant effects of group, f(3,453)=16.27,/J<,OOI, and time,
F(i,453)^12,43,p<.00l. Overall, the control children's self-concept was better than that of the
at-risk children, and self-concept generally increased from time 1 to time 2. However, these
findings were qualified by a significant group x lime interaction, F(3,453)=5.72,p<.001 which
is illustrated in Figure 4. Subsequent SNK tests showed that increases over time were found
for all groups except for the ELBW children whose academic self-concept dropped between 6
and 8 years of age.
3.5
;ion
3.3
Harlei
c
oo
o
•
3.1
2.9
•
-•-LBW
• .«... V L B W
--•-ELBW
.4I_ control
2,7
2,5
8;5
6;3
Group
Figure I. Analysis of variance using group membership (ELBW, VLBW, LBW and control)
and age (6;3, 8;5) as independent variables and self-concept (Harter scale;
Cognition) as dependent variable
Discussion
The present study yielded coherent findings over time. First of all, the size of differences
in cognitive ability variables between the VLBW/PV and control children remained stable
over time. In an earlier comparative analysis of the present sample, Wolke and Meyer (1999)
already emphasized the fact that at 6 years of age, very preterm children performed more
poorly on all of the K-ABC subscale composites, with group differences in the simultaneous
infonnation processing component (SGD) heing particularly large (i,e., more than a standard
deviation). In comparison, group differences obtained for the sequential information
processing component (SED) were smaller, with preterm children on average performing half
a standard deviation below the level of the controls. By and large, this pattern of findings was
replicated in the assessment when children were 8 years of age. As can be seen from the last
column of Table 1, effect sizes (eta scores) obtained for the language and phonological
information processing variables assessed at the age of 6 years ranged between .5 and ,8,
indicating that the task-specific differences between preterm and control children were not
SCHOOL ACHIEVEMENT IN PRETERM AND FULL-TERM CHILDREN
399
only significant but also practically important. Similarly, pronounced group differences in
early literacy (i.e., number and letter knowledge) existed before children entered school.
Not surprisingly, these early group differences affected the acquisition of reading and
spelling skills at school. Control children outperformed the VLBW/VP children on all of the
literacy measures, with differences varying between a half to two thirds of a standard deviation.
Again, theses differences reflect substantial effects. They were most pronounced for
mathematics performance requiring visualization and reasoning (eta=.9O), indicating that
VLBW/VP children's school problems were not restricted lo the literacy domain. The present
analyses thus concur with fuidings from other longitudinal studies indicating that children bom
prematurely and with a lower birth weight are at increased risk of school failure (for a review, see
Taylor et al., 2000; Bhutta et al., 2002). They do not confirm findings that effects of early
biological risk on academic performance may not be strong (e.g., Schothorst & van Engeland,
1996; Weindrieh et al., 2000). Being born very pretcrni puts these children, as a group, at
statistically and practically higher risk for cognitive impaimient and schooling difficulties (Bhutta
et al., 2002; Wolke, 1998). Very low birth weight or very preterm birth is strongly predictive of
poor general cognitive abilities (IQ) and specifically, processing of simultaneous information
required in many life tasks such as in solving mathematical problems or dealing with the social
and behavioural demands of peer groups (Hille et al., 2001). Thus, within the VLBW/VP group,
cognitive processing in different domains was the major factor predicting school achievement.
Additional analyses of the impact of socio-economic status (SES) on cognitive abilities
and school perfomiance in the two groups revealed that this variable was infiuential, but that
there was no group by SES interaction. Overall, effects of SES were similar for VLBW/VP
and control children. As previously reviewed, the effects of very premature birth were
stronger than those of SES differences, given Ihat low-SES control children outperformed
high-SHS children at risk (Wolke, 1998). Very preterm children from low SES background are
thus at double jeopardy for poor scholastic outcome.
Another issue of interest that stimulated the present analyses was whether the same
structural relationships between preschool measures of phonological skills and early literacy
would hold for the groups of preterm and control children. Although findings from the various
analyses of variance consistently showed that mean level of group performance differed for
almost all of the variables considered, this does not necessarily imply that structural
relationships follow a different pattern. Indeed, findings from multiple stepwise regression
analyses with school performance measures as criterion variables revealed that prediction
patterns for the reading and spelling variables did not differ across groups. However, whereas
individual differences in IQ level were not that relevant for the prediction of math performance
in the control group, they were much more important for predicting math performance in the
group of VLBW/VP children. To our knowledge, similar analyses and results have not yet
been reported in the relevant literature. The fact that individual differences in biological risk
did not prove similarly important is likely due to the fact that IQ and biological risk were
intercorrelated. Thus neonatal risk and brain injury is refiected in the cognitive function
domain rather than transmitted by a separate route.
Another important research issue tackled in our study concerns the long-term prediction
of academic success in early adolescence based on preschool information and information on
academic performance in elementary school. Results of a sequential testing procedure
indicated that separate causal models had to be specified for the two subgroups.
The resulting model for the VLBW/VP children (depicted in Figure 2) shows a strong
impact of IQ assessed during the last kindergarten year on math performance, thus replicating
the outcome of the stepwise regression analyses. In addition, IQ had a substantial indirect
effect on reading which was mediated by phonological processing assessed at age 6. IQ
differences also predicted individual differences in phonological processing, which in tum had
a strong impact on reading (but not on math). In accord with the findings of the relevant
literature (e.g., Schneider & Naslund, 1999; Wagner & Torgesen, 1987), the literacy and math
variables had a direct effect on academic success in the secondary school system, accounting
for about 64% of the variance in this variable.
400
W. SCHNEIDER, D. WOLKE, M. SCHLAGMULLER, & R. MEYER
Overall, the results for the control group showed a similar causal pattern. For instance, it
seems remarkable that early SES differerence are not only related to IQ differences in both
samples but also have a direct effect on academic success which is not mediated by other
variables in the analyses. This finding suggests that there are other relevant factors not
specified in the model that are responsible for these SES effects e.g., attitudes, home,
environment and aspirations (e.g., Fergusson & Woodward, 1999; Schoon, Bynner, Joshi,
Parsons, Richard, & Sacker, 2002). The main difference between the two causal models
concerned the impact of early IQ on school performance, which was still moderately strong
for the control sample but not as pronounced as in the group of preterm children. In particular,
the impact of IQ differences on math performance was much stronger for the at-risk sample
than for the control children. Related to this, the model specified for the control children
explained less variance in the school performance variables, compared to the findings for the
preterm group. Again, this outcome confirms the findings from the regression analyses
described above, indicating that general cognitive difficulties are pervasive in VLBW/VP
children and less so in healthy full-temi children. Surprisingly, however, IQ differences also
predicted levels of phonological processing in both groups, a finding not in accord with those
reported in the relevant literature (e.g.. Bus & van Ijzendoorn, 1999; Schneider, Roth, &
Ennemoser, 2000).
Another deviation from typical findings concerned the predictor weight of the school
achievement measures. It was true for both groups that spelling performance at age 8
explained more variance in the academic success variable assessed at age 13 than proficiency
levels in reading. The latter finding may be due to idiosyncracies of the German school system,
where spelling performance is particularly important for selection processes taking place after
elementary school, that is, after Grade 4. Given that the VLBW/VP children generally operated
at a lower academic achievement level than the control children, spelling problems could have
been mainly responsible for class repetition and other problems at the secondary school level.
So far, we have only discussed implications of very premature birth and very low
birthweight combined. To remain consistent with earlier publications dealing with the Bavarian
study (e.g., Wolke & Meyer, 1999; Wolke et al., 1994; Hille et al., 2001), our at-risk sample
was further classified according to gestational age and not birth weight (even though we should
note that there is a considerable overlap in these two classification criteria). A final issue of
interest concerned the question whether differences in birth weight have an impact on
educational outcomes. Given that most recent studies on the issue relate levels of birth weight
with educational success, we re-classified our sample according to birth weight categories as
suggested by the WHO. This seemed important because current information on the effect of
birth weight on school function is limited by rather small samples from a single site, hospital, or
school district. Further concerns are raised when very low birth weight children are considered
as a whole and simply compared with normal birth weight groups, without considering heavier
low birth weight (1501 through 2500 g) children (cf., Klebanov et al., 1994). Our findings
indicate that individual differences in birth weight among at risk children do predict later
academic outcomes. School problems were most pronounced for the ELBW children, regardless
of measurement point, even though they also existed for the VLBW group. In comparison,
academic performance of the LBW children was more comparable to that of the control group
children. These findings are in accord with those of other longitudinal assessments (e.g.,
Klebanov et al., 1994; Saiga! et al., 2000), As previously proposed, biological risk does
distinguish children on the group level (i.e., ELBW have lower scores than VLBW or LBW
children). However on an individual level, the functional impairment in general cognitive ability
is the major predictor of school achievement. Thus those children who had severe neonatal
complications but these did not effect general cognitive abilities have a good chance of good
school adjustment. Previous reports of the Bavarian Longitudinal Study suggest that if the
VLBW children had not caught up within the first 20 months in their mental development and
head growth, the chances for adaptive cognitive development by 8.5 years were highly reduced
(Wolke, Schulz, & Meyer, 2001). Very preterm birth is a major reproductive risk that appears to
reduce the expression of genetic potential (Koeppen-Schomerus, Eley, Wolke, Gringras, &
SCHOOL ACHIEVEMENT IN PRETERM AND FULL-TERM CHILDREN
401
Plomin, 2000), Early recovery and intact general cognitive ability (on the functional level)
provides a good prediction of longer temi educational achievement in this group.
The inclusion oflhe academic self-concept variable indicates that the objective academie
differences are also reflected in altered self evaluations. We already knew from the relevant
literature that prematurily born children show lower levels of academic self-concept in
adoleseenee (cf., Cohen et al,, 1996), Our analyses revealed that at-risk children's academic
self concept was already generally lower than that of the matched controls from age 6 on, and
that different developmental trends could be observed as a function of risk subtype. The most
problematic trend was found for the ELBW children, whose academic self-concept deteriorated
significantly from age 6 to age 8. Although the two other at-risk groups tended to score lower
than the control children, the overall developmental trend paralleled that of the controls in that
their self-eoncept improved over time. The divergent pattern detected in case of the ELBW
children indicates that this group is in particular need of specific intervention.
Such a conclusion is substantiated by the findings for the prereading variables. The
ELBW children performed significantly worse than the other groups on both the phoneme and
rhyming tasks. A closer inspection of their scores on these tasks revealed that about 30% of
the ELBW children but only about 4% of the control children ranked below the 5th percentile.
Thus about one third of the ELBW children showed a severe risk regarding subsequent
reading and spelling acquisition in school. Using a more lenient criterion, more than 65% of
the BLBW children was classified into the lowest quartile of the distribution, which again
indicates a substantial risk. Although the situation was comparably better for the two other
at-risk groups, about one quarter of the LBW children and about 45% of the VLBW children
belonged to this at-risk category (i,e,, lowest 25%).
Overall, then, the academie situation appears difficult for prematurely bom children.
Although their lower IQ may limit the chances of cognitive interventions, the findings
nevertheless identify potential levers of where to intervene. As already noted above,
phonological training programs typically carried out during the last year of kindergarten have
been proven successful in groups of normal and at-risk children. Given the generally low
levels of phonological skills found for the VLBW children included in our analyses, these
children bom prematurely qualify as candidates for such educational intervention programs.
There is some evidence that these children may benefit from such programs, A recent training
study by Schneider. Roth, and Ennemoser (2000) revealed that the few prematurely bom
children in that sample (N=5) benelited as much as the rest of the sample from the training
procedure, and, as a consequence, did not develop academic problems in sehool. Thus,
whereas more general intervention programs mainly developed in the medical field had only
limited impact on altering at risk-children's general cognitive abilities (McCarton, BrooksGunn, Wallace, Bauer, Bennett, Bernabaum, Broyles, Casey, McCormick, Scott, Tyson,
Tonascia, & Meinert, 1997; APIP, 1998), it appears that more process-oriented training
programs in the field of edueational psychology couid help these children to overcome some
of their sehool problems, at least as far as reading and spelling is eoncemed.
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405
De.s differences individitelles coiiceniant le siicces academique sont
recherchees en cadre d'une population geogrciphiquement
definie
eiitiere des enfaitls ne.s avant lerme ages de mains de 32 semaines avant
!a naissance et tin puids de naissance moin.s de 1500 gramntes. La
population coneernee se compose de 264 prematures (75.6% des
survivants qui parlent I'allemand) et 264 en/ants pour le groupe de
controle. gemines le sexe. I'etat socio-economiqiie. la situation de
famille et I 'age de la mere, qui sont examines depuis lew naissance. Les
analyses actueltes sont pointees a I'influence des capacites cognitives
revues a I'dge de 6 et 8 ans au succes academique a I'age de 13. Les
scores de t'intelligence, les capacites avant lire, tire, epeler et la
capacite en matbematiques obtenus pendant la derniere annee aujardin
d'enfants et de notiveati a la fin de "Grade 2" sont utilises pour la
prediction du succes academique a I'age adolescent. Les differences
entre les prematures et tes en/ants de controle concernant les capacites
cognitives deja ohservces dans les recherches precedentes restent
stables tout le temps, les cnfants de controle montrent une performance
en moyen une demie deviation miettx que les prematures. Les prematures
sont aussi pire concernant les mesures de la litterature et la performance
en mathematiqiies. Les modeles multivariates et de causalite montrent
des modeles prevoyantes differentes pour les deux groupes. Pendant que
I 'intelligence est particulierement importante pour la prediction du
succes academique dans la population prematuree.
I'intelligence
generate est nioins important pour la prediction du succes academique
dans le groupe de controle. Si des sous-groupes des enfants en risque
sont formes accordes aux categories du poids de naissance, on a montre
que les problemes a I'ecole sont particutieremenl valable pour les
enfants de poids extremement bas (1000 grammes et encore moins).
Key words: Longitudinal study, Preterm children, School achievement.
Received: March 2004
Revision received: August 2004
Wolfgang Schneider. Department of Psychology, University of Wiirzburg, Wittelsbacherplatz 1,
D-97()74 W(ir/burg, Gemiaiiy; E-mail: Schncider@psychologie.uni-wuerzburg.de
Current ihe me of research:
Cognitive development, Prediction of school performance. Prevention of dyslexia, Reading and spelling. Longitudinal
studies.
Most relevant publications in thefteld of Psychology of Education:
Artelt, C , Schiefele, U., & Schneider, W, (2002). Predictors of reading literacy. European Journal of P.sychology of
Education. 16, 363-384.
Schneider, W., & Bjorklund, D.V. (2003). Memory and knowledge develiipmcnt. In J, Valsiner & K. Conoily (Eds.).
Handbook of developmental psychology (pp. 370-403). London: Sage.
Schneider, W., Knopf, M., & Stefanek, J. (2002). The development of verbal memory in childhood and adole,scence:
Findings from the Munich Longitudinal S\ody. Journal of Educational Psychology. 94, 751-761.
Schneider, W., & Pressley, M, (1997). Memory development between 2 and 20. Mahwah, NJ: Erlbaum,
Weinert, F.E., & Schneider, W. (Eds,), (1999). Individual development from 3 to 12: Findings from ihe Munich
Longitudinal Study (LOGIC). Cambridge, MA: Cambridge University Press.
406
W. SCHNEIDER. D, WOLKE, M, SCHLAGMULLER, & R, MEYER
Dieter Wolke. Professor Unit, of Perinatal and Paediatric Epidemiology, Department of Community
based Medicine, University of Bristol. 24 Tyndall Avenue, Bristol, BS8 ITQ, UK. And Scientific
Director Jacobs Foundation, Seefeldquai 17, P.O. Box, C H - 8 0 3 4 Zurich) E-mail:
Dieter-Wolke@jacobsfoundation,org; Web site: www,aispac.bris,ac.uk/welcome/dieter_biog,slitml,
www,jacobsfoundation,org
Current theme of research:
Longitudinal studies of biological at risk children. Longitudinal studies of antisocial behaviour in adolescence. Bullying
behaviour and schooling. Sleeping and Feeding Development.
Mosi relevant publicalionx in ihe field of Psychology of Education:
Wolke. D,, & Samara, M. (2004), Bullied by siblings: Association with peer vicxiimisaiion and behaviour problems in
Israeli lower secondary school children. Journal of Child Psychology- and Psychiatry. 45. 1015-1029,
Woods, S,, & Wolke, D, (2004), Direct and relational bullying among primary school children and academic
\.. Journal of School Psychology. 42. 135-155,
Saigal. S,, den Ouden, L., Woike, I),, Hoult, L,, Paneth. N,, Slreiner, D,L,, Wbitaker, A,. & Pinto-Martin, J, (2003).
School-age outcomes in children who were extremely low birth weight from four internalionai population-based
cohorts. Pediatrics, 4, 943-950,
Woods, S,, & Wolke, D, (2003), Does ihe content of anti-bullying policies inform us about the prevalence of direct and
relational bullying behaviour in primary schools? Educalional Psychology. 23(2), 381-402,
Wotke, D., Woods, S,, Schulz, H,, & Stanford, K, (2001). Bullying and victimisation of primary school children in
South England and South Germany: Prevalence and school factors. British Journal of Psychology. 92, 673-696,
Matthias Schlagmiiller. Department of Psychology, University of WUrzburg, Wittelsbacherplatz 1,
D-97074 Wiirzburg, Germany; E-mail: schlagmu(gpsychologie,uni-wuerzburg,de
Current theme of research:
Memory development. Strategy development.
Most relevant publications in the field of Psychology of Education:
Schneider. W,, SchlagmQIler, M,. & Vise, M, (1998), The impact of metamemory and domain-specific knowledge on
memory performance, European Journal of Psychology of Education, /.?, 91-103,
Schlagmuller. M,, & Schneider. W,(20fl2), The development of organizational strategies in children: Evidence from a
microgenetic longitudinal study. Journal of Experimental Child Psycholog}', 81. 298-319,
Renate Meyer. Am Steinbach 17, D-90559 Burgtbaiin, Germany; E-mail: r.e,meyer@t-onlitie.de
Current iheme of research:
Longitudinal studies of biological at risk children,
Mo5f relevant publications in the field of Psychology of Education:
Wolke, D,,& Meyer, R, (!999), Cognitive status, language aUainment and pre-reading skills of 6-year-old very preterm
children and their peers: The Bavarian Longitudinal Study, Developmental Medicine and Child Neurology: 41(2),
94-109,
Wolke, D,, Meyer. R,, Ohrt, B , & Riegel, K, (1995), The incidence of sleeping problems in preterm and fuUterm infants
discharged from special neonatal care units: An epidemiological longitudinal study. Journal of Child Psychology
and Psychiatry. i6(2), 203-223.
Wolke, D., Gray, P,. & Meyer, R, (1994), Excessive infant crying: A controlled study of mothers helping mothers.
Pediatrics. 94(3), 322-332,