Prediction of childhood cognitive abilities from a set of early indicators of information processing capabilities

Infant Behavior & Development 32 (2009) 91–102

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Infant Behavior and Development

Prediction of childhood cognitive abilities from a set of early indicators of information processing capabilities Holger Domsch a,∗ , Arnold Lohaus a , Hoben Thomas b a b

Bielefeld University, Germany Pennsylvania State University, USA

a r t i c l e

i n f o

Article history: Received 11 June 2008 Received in revised form 2 September 2008 Accepted 24 October 2008 Keywords: Infancy Childhood Information processing Prediction Intelligence Cognitive development

a b s t r a c t Childhood tests of intelligence are often composed of several different tasks or scales. In contrast to this, many studies assessing early indicators of cognitive ability include only one or two different infant paradigms. The present study employs an extended set of infant paradigms for the prediction of childhood development and intelligence. Two groups of infants (64 three- and 63 six-months olds) were tested. Subjects were retested at 24- and 32-months of age with several indicators related to developmental state, verbal skills and intelligence. Especially in the group of 6-month-olds, the analysis demonstrated that significant R2 contributions were yielded by a set of different predictor variables. The results show that a set of predictors in contrast to single predictors leads to a substantial increase of the variance accounted for. © 2008 Elsevier Inc. All rights reserved.

1. Introduction Early studies on the stability of intelligence have shown generally low correlations when scores on standardized infant tests were related to later intelligence scores (Kopp & McCall, 1982). The situation changes, however, when tasks thought to reflect the infants’ information processing skills replace the early intelligence tests as predictor variables. A recent metaanalysis (Kavˇsek, 2004a) based on 25 studies showed an average correlation of r = .37 for early measures of habituation and dishabituation in infancy and later intelligence in childhood. The early measures were obtained between 1.5 and 12 months of age, while later intelligence was assessed when the children were between 1.5 and 11 years of age. The predictive power does not appear to vary systematically with the age of predictor or outcome measurements. This finding supports the results of an earlier meta-analysis by McCall and Carriger (1993), which considered not only habituation, but also recognition memory (novelty preference). Thus, habituation speed and recognition memory can be used, to some degree, to predict intelligence later in childhood or even adulthood (Fagan, Holland, & Wheeler, 2007). Other infant paradigms have also proved to be useful in the prediction of later developmental outcome. Fagen and Ohr (1990) showed an association between performance on the mobile conjugate reinforcement paradigm (Rovee & Rovee, 1969) and preschool intelligence. Furthermore, some longitudinal studies (Haith, Hazan, & Goodman, 1988; Haith & McCarty, 1990) show that reaction time measures from the visual expectation paradigm (VExP) are significant predictors of developmental outcome (DiLalla et al., 1990; Dougherty & Haith, 1997). The conceptual mechanisms that are responsible for the relation between these early measurements and later outcomes may be found in information processing components (McCall & Carriger, 1993). A number of models have been proposed

∗ Corresponding author at: Bielefeld University, Universitaetsstr. 21, 33615 Bielefeld, Germany. Tel.: +49 521 106 4514; fax: +49 521 106 6016. E-mail address: [email protected] (H. Domsch). 0163-6383/$ – see front matter © 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.infbeh.2008.10.006

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with the goal of explaining and identifying the fundamental processes of infant visual performance. Colombo (1993, 1995) and Rose and Feldman (1997), for example, propose two main factors: speed of processing and memory. These two factors were also identified in two studies using factor analysis as basic dimensions of cognitive development in early infancy (Jacobson, Jacobson, O’Neill, & Padgett, 1992; Rose, Feldman, & Jankowski, 2004). These components may reflect information processing capabilities that are also involved in solving intelligence tasks and thus, may be early predictors for later intelligence measures (Bornstein, 1985; Bornstein & Sigman, 1986; Colombo, Mitchell, & Horowitz, 1988; Fagan, 1988; Fagan & Singer, 1983). This link is less clear for the earlier-used standardized infant tests which require, for example, sensory-motor or imitation skills which are not well represented in later intelligence tasks. In addition, the two basic cognitive components, memory and processing speed, have been found to have significant correlations with intelligence in older children as well (Kail & Salthouse, 1994). A closer look at standard intelligence tests shows these measures are typically composed of a set of tasks measuring different facets of intelligence (e.g., Kaufman & Kaufman, 1983). This may also contribute to the increased reliability of intelligence measures. To obtain a comparable situation in the case of the predictor, it seems to be necessary to define a set of tasks that are related to information processing capabilities of infants and consider how well they jointly predict later intelligence. Although, there are several infant paradigms, all assumed to measure information processing capabilities, many studies focus on only one infant task. Studies including several tasks simultaneously are apparently rare (Colombo, Shaddy, Richman, Maikranz, & Blaga, 2004; DiLalla et al., 1990; Laucht, Esser, & Schmidt, 1994). DiLalla et al. (1990), for example, included measures from different paradigms and tasks as infant predictors of later IQ: the Fagan’s Test of Infant Intelligence (Fagan & Detterman, 1992), the VExP, and the Bayley Scales of Infant Development (BSID; Bayley, 1969). Infants were tested at 7 and 9 months of age and again at 1, 2 and 3 years of age. Using stepwise regression, a combination of reaction time (derived from the VExP) and a subscale from the BSID (Activity) accounted for 32% of the variance of childhood IQ with 3 years of age. These results were, however, somewhat inconsistent. Only single predictors explained significant proportions of variance of the BSID at 1 and 2 years of age, while the combination did not lead to significant improvements. Using multiple predictors, Laucht et al. (1994) accounted for significant proportions of variance with regard to developmental outcome in a large sample of low- and high-risk infants. The regression included looking time in the habituation paradigm and a subscale of the BSID in addition to parental education. The inclusion of parental education as a significant predictor in the regression shows that besides infant variables, predictors related to the home environment are also associated with later intelligence (see also Smith, Fagan, & Ulvund, 2002). To summarize, these studies show that the inclusion of several variables as predictors for later intelligence can improve predictability. This is in line with a statement of Colombo and Frick (1999) who postulated that researchers should “use multiple measures of infant cognition in order to raise the likelihood that various cognitive components are being assessed” (p. 65). The present study has two major aims: the first is to broaden the range of tasks in a single study to better predict childhood developmental and cognitive abilities. The second is to determine if the predictive value of the predictors is similar for infants of different ages. Thus, the study includes several tasks assessing infants’ early information processing capabilities at 3 and 6 months of age. In addition, parental education was included as a predictor variable. Several outcome measures were assessed at 24 and 32 months. It was expected that early indicators of information processing would be related to later childhood cognitive abilities and that an increase in incremental validity can be observed by a combination of these predictors. Performance in the infant paradigms is expected to contribute to the prediction of the outcome measures independently of the parental education (Laucht et al., 1994; Smith et al., 2002). It was assumed that the expectations outlined above would hold for both 3- and 6-month-old infants. 2. Methods 2.1. Participants The sample consisted of 64 three-month-old (M = 90.6 days, S.D. = 2.8 days) and 63 six-month-old (M = 180.2 days, S.D. = 8.2 days) full-term infants. There were 32 female and 32 male infants in the 3-month-old group and 30 female and 33 male infants in the 6-month-old group. Parents and their infants were recruited by local newspaper notices. An additional 31 infants were recruited at the age of 3 or 6 months, but were not tested longitudinally because they had missing data on more than two infant paradigms. The cohorts of 3-month as well as the 6-month-old children were tested again on two occasions during toddlerhood. 123 infants visited the laboratory again at 24 months and 122 infants at 32 months reflecting a drop out rate of 3% and 4%, respectively. In most cases, these families had moved to another city. The infants were healthy and alert at time of testing. Informed consent was obtained from all parents prior to their participation. Parents were motivated to participate in the repeated assessments by a payment of about $145.00. 2.2. Procedure At 3 and 6 months of age respectively, infants underwent several assessment procedures: habituation/dishabituation, visual expectation, novelty preference, conjugate reinforcement and the Bayley Mental Scale (Bayley, 1993). To avoid the

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effects of fatigue, the tasks were administered on 3 different days within 1 week. The sequence of the tasks was varied across the sample. At 24 months, all children were tested on 2 days with the Bayley Scales of Infant Development II (BSID II; Bayley, 1993) on 1 day and a German speech test (SETK-2; Grimm, Aktas, & Frevert, 2000) on the other. The assessment at 32 months required one additional date on which a subtest of the German speech test was administered together with the Kaufmann Assessment Battery (K-ABC; Kaufman & Kaufman, 1983; Melchers & Preuss, 1994). The number of infants providing usable data for each task varied. Illness, experimenter error, fussiness, refusal, or equipment errors produced missing data in some assessments. 2.3. Measures 2.3.1. The 3- and 6-months assessments 2.3.1.1. Parental education. Parents were asked for information about their highest level of education in school. In Germany, there are four different levels of graduation in the school system. The mother’s and father’s graduation levels were requested and coded by a number (1–4), respectively. The mean of the mother’s and the father’s educational level was computed to indicate the parents’ level of education. 2.3.1.2. Habituation/dishabituation paradigm. Infants were seated in the middle of a black booth in a dimly lit room. A 120 cm by 90 cm screen was located about 95 cm in front of the infant. The mother and the experimenter were seated behind the booth outside the infant’s field of view. Stimuli were displayed on the screen by a video projector (Liesegang dv 455). The infant’s visual behavior was recorded by a digital video camera and displayed on a monitor for online assessment of looking behavior. A 6 × 6 red and yellow checkerboard served as habituation stimulus. The checkerboard appeared stationary with four central dynamic squares. The four squares in the center of the checkerboard synchronously and slowly disappeared creating a pattern of small fragments that zoomed out to black. The result was a black area in the center of the checkerboard. Immediately afterwards, the original pattern slowly zoomed in again and the black area returned to the original yellow and red checkerboard pattern. The four squares remained for 0.5 s as part of the complete checkerboard. Then the process to create a black area started again. This sequence recurred during the entire trial. The dishabituation stimulus, also a checkerboard, differed from the habituation stimulus only in the color and shape of the elements which were purple and green circles. These stimuli were comparable in their attractiveness for infants. To attract the infant’s attention, a small blue dot appeared in the center of the screen before each trial as an attention getter. The dot gradually grew in size; from an adult perspective this created the impression of an approaching stimulus. During the presentation of the attention getter an auditory stimulus recorded from the sound of a baby toy (about 65 dB) was also presented. Infants received 11 habituation trials. Periodic glances away from the stimulus were recorded and if the infant looked away for more then 2 s within one single look the trial was terminated. Afterwards the attention getter was started again to redirect the infant’s attention back to the center of the screen. As soon as the infant looked back to the center of the screen, the experimenter initiated the habituation stimulus and a new habituation trial began. For the analysis of the habituation paradigm, the total looking time across the 11 habituation trials was computed. After the 11 habituation trials, three additional trials appeared. At trials 12 and 14 the dishabituation novel stimulus appeared with the habituation stimulus again appearing at trial 13. Dishabituation performance was assessed by calculating the total looking times at trial 12 and 14 (dishabituation trials) divided by the total looking times at trials 11 through 14. A ratio below .5 would reflect no dishabituation, while a ratio above .5 would indicate dishabituation. This variable was used as a measure of dishabituation performance. Inter-observer agreements regarding the looking behavior ranged from r = .96 (average duration of views per trial) to .98 (total looking time across 11 trials). 2.3.1.3. Visual expectation task. The infants were shown simple stimuli in a randomized sequence (rectangles, triangles, circles and smileys). The equipment used to present the stimuli was the same as in the habitation task. The stimuli were each shown for 1 s and then disappeared. They were presented one by one in a randomized sequence on one side of the screen. Each appearance of a smiley was accompanied by the presentation of an auditory signal (54–58 dB). Two seconds after each presentation of a smiley, a more complex rotating drawing, for example, an animal or a flower appeared on the other side of the screen. The more complex drawing appeared for about 1.5 s, and then disappeared. After the presentation of the complex stimulus, the series of simple stimuli restarted until the next smiley appeared. A smiley was presented after every two to five presentations of simple stimuli. The task contained 18 smileys with a subsequent complex stimulus on the other side of the screen. The infant’s reaction time to look to the other side of the screen when the smiley appeared was used to indicate the information processing speed of the infant. The infant’s reaction time was determined from a video tape by a picture-by-picture analysis of the looking behavior of the infants. The mean reaction time across the trials defined VExP-reaction time. A random sample of 20% of the video tapes was analyzed by a second examiner and revealed an inter-rater reliability of .91.

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2.3.1.4. Novelty preference task. A paired-comparison procedure was used. The equipment used to present the stimuli was the same as in the habitation task. At the beginning of each trial, an attention getter was presented to catch the infant’s attention. The attention getters included moving pictures or objects (e.g., six dots). In order to enhance the attractiveness of these stimuli, an auditory signal (54–62 dB) appeared simultaneously from a location behind the screen. Subsequently the familiarization stimulus appeared on the left and on the right side of the screen. The cue was presented until the accumulated looking time had exceeded a defined criterion; 35 s for 3-month-old infants and 20 s for 6-month-old infants. Durations of familiarization time were determined by a pretest with additional infants. The experimenter scored the looking time by pressing a key that was interfaced with a computer. When the time criterion was exceeded, a tone sounded in a headphone of the experimenter who then initiated the next presentation. In the retention phase the familiar and a novel stimulus were presented simultaneously with the left–right positions of the familiar and novel stimuli reversed on the subsequent trial. Each of the retention trials persisted across a period of 5 s, regardless of how long the infant looked at the stimuli. Faces and dynamic abstract patterns were used as two types of stimuli in different series of trials. The faces consisted of two black and white cartoons of female faces. Two rotating colored shapes (a circle and a cross) were used in the second series of trials. The looking behavior of the infants was recorded and the videos were analyzed in a reduced speed rate by a computer-based video analysis system. The score assessing novelty preference was calculated from the proportional looking time at the novel stimulus divided by the total looking time at the novel and the familiar stimulus. Data of infants who looked to only one lateral position across the retention trials were excluded, as this does not reflect attention to both stimuli. A random sample of 20% of the video tapes was analyzed by a second examiner and revealed an inter-rater reliability of .97. 2.3.1.5. Mobile conjugate reinforcement paradigm (mobile task). Infants lay on their back on a soft blanket under a mobile. The mobile consisted of five colored wooden elements (three figures and two clouds) and three little jingle bells. One of two different ribbons was tied to the infant’s ankle, depending on the experimental phase. In one case, an elastic ribbon was used, which was connected with a second stand but not with the mobile. In the other case, an inelastic ribbon was connected with the mobile. The paradigm consisted of three different phases. The first phase started with a 2-min non-reinforcement baseline during which the infant’s spontaneous kick rate was measured. The infant was connected with the elastic ribbon and therefore not able to move the mobile. During the following 6-min training phase, the mobile was connected with the second (inelastic) ribbon to the infant’s ankle. A movement of the infant’s leg therefore resulted in a motion of the mobile. The infant’s kick rate should increase if the infant had detected and learned the contingency between his own action and the following movement of the mobile. Thus, the motion of the mobile served as reinforcement for the body action. During a subsequent 2-min test phase (immediate retention test), the mobile was disconnected from the infant’s ankle and the elastic ribbon was used again. During each phase, the rate of the infant’s leg movements was recorded by a video camera and analyzed offline. The kick-rate during the immediate retention test was divided by the kick-rate during the baseline phase. This quotient served as the variable defining immediate retention. If the infant learned the relation between his own kicks and the subsequent motion of the mobile, a quotient larger than one would be expected. Several 6-month-old infants tried repeatedly to turn their body to a face-down position. Useable data could not be derived from these infants. As a consequence, only data from the 3-month group was included. The inter-rater reliability for the kick-rates in the different phases ranged from .89 to .92 based on 20% of the data. 2.3.1.6. Bayley scales of infant development II. The BSID II (Bayley, 1993) yields two development indexes. The Mental Development Index (BS-MDI) is an index for cognitive development, and the Psychomotor Development Index (BS-PDI) is an index for psychomotor development. At 3- or 6-months, only the Bayley Mental Scale was administered to the infants from which the BS-MDI was computed. The respective subsets of test items were used for 3- and 6-month-old infants. 2.3.2. The 24 months assessments 2.3.2.1. Bayley scales of infant development II and language test. The infants were seen again at 24 months of age and administered both Bayley Scales. The BS-MDI and the BS-PDI were computed as the sum of the correct item responses. In addition, a German speech test (SETK-2; Grimm et al., 2000) was used to assess the linguistic competencies of the children. The test includes four sets of items related to (a) the comprehension of words, (b) the comprehension of sentences, (c) the production of words, and (d) the production of sentences. In the context of this study, two scales were constructed related to verbal comprehension (comprising subscales a and b) and verbal production (comprising subscales c and d) by taking the means of the respective T-values (M = 50, S.D. = 10) from the test norm tables. 2.3.3. The 32 months assessments 2.3.3.1. K-ABC and language test. At 32 months of age, the German version of the K-ABC (Kaufman & Kaufman, 1983; Melchers & Preuss, 1994) was used to assess the children’s intelligence. The main intelligence measure of this test battery is the Mental Processing Composite (K-ABC-MPC), which assesses fundamental mental processes related to simultaneous and sequential information processing and is composed of five subtests. In addition, the Achievement Scale (K-ABC-AS) was used to assess the children’s mental processing skills. At 32 months the K-ABC-AS is composed of two subtests. The K-ABC can be used from 30 months upwards.

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In addition, one subscale (production of sentences) of the German speech test by Grimm et al. (2000) was again administered to the children. There were two reasons for using only one subscale. First, the test is similar to parts of the K-ABC. In pre-tests, some children became bored by the repetition of similar items and thus, the assessments had to be terminated. Second, those who were 32-month-old were at the upper limit of the target group of the speech test (35 months). Thus, it was decided to restrict the administration of the test to the subscale with the highest item difficulties (production of sentences). 2.4. Statistical analyses Correlations were computed between predictors and outcome and tested for significance by using t-tests. Afterwards, a series of multiple linear regressions were employed with infancy measures significantly related to later outcome as predictors. Missing values in the outcome variables were not replaced (for example with imputation algorithms) at this point of data analysis because the predictive power of the infant tasks should be examined for each outcome variable independently. In a subsequent step, a principal component analysis was computed to combine the outcome measurements. For this purpose, missing values in the outcome measurements were replaced using the EM-function in SPSS (SPSS 14.0, Chicago, IL, USA). This procedure allowed the inclusion of all subjects in the factor analysis. Because the hypotheses are directional, one-tailed significance tests were calculated. In some cases negative and in other cases positive unstandardized beta weights (B; SE B: standard error of B) and standardized beta weights (ˇ) are expected. For example, shorter looking time in the habituation task (negative correlation with outcome measures), but higher dishabituation (positive correlation with outcome measures) should reflect better information processing. All procedures used standard default SPSS (SPSS 14.0, Chicago, IL, USA) routines. 3. Results Before reporting the associations between early predictors and outcome measures, the initial paragraph will focus on the relations between the parameters assessed with 3 and 6 months of age as well as the intercorrelations between the outcome measures. 3.1. Intercorrelations of predictive and outcome measures Pearson product-moment correlation matrices were generated among all variables of interest: parental education, looking time in the habituation, dishabituation performance, VExP-reaction time, novelty preference, immediate retention and Bayley-MDI. In general, the measures seem to be mostly independent of each other. Only few exceptions exist among the 36 computed correlations. Some of these correlations may be significant by chance because of the multiple comparison problem. As only low effects were expected and sample sizes were not large, it was decided to abstain from using, for example, a Bonferroni correction. The correlation based on sample size n is denoted as r (n). In the group of 3-month infants, the Bayley-MDI was related to habituation rate, r (51) = −.29, p < .05, and VExP-reaction time, r (46) = −.32, p < .05. VExP-reaction time was also correlated with immediate retention, r (41) = −.30, p < .05. In the group of 6-month-old infants, the Bayley-MDI was associated with novelty preference, r (53) = .35, p < .05, and VExP-reaction time, r (53) = −.35, p < .05. In addition, novelty preference and VExP-reaction time were correlated, r (49) = .25, p < .05. The intercorrelations of the outcome measures at 24 and 32 months of age are provided in Table 1. The associations between the scores were clearly higher in these age groups. Even if the time interval is as long as 8 months (between the measurements at 24 and 32 months of age), all correlations proved to be significant. This, however, is not surprising because there are clear overlaps between the included test items. For example, all tests (and not only the language test) include items related to speech production and comprehension. Table 1 Intercorrelations between the outcome measures assessed at 24 and 32 months of age.

Age of 24 months (a) Bayley-MDI (b) Bayley-PDI (c) Verbal comprehension (d) Verbal production

(b)

(c)

(d)

(e)

.48** (123)

.58** (112) .24** (113)

.71** (103) .30** (104) .48** (103)

.50** .34** .38** .48**

Age of 32 months (e) MPC (K-ABC) (f) AS (K-ABC) Note: sample size n is in parentheses; (g): verbal production. ** p < .01.

(f) (117) (118) (111) (104)

.52** .23** .43** .52**

(g) (117) (118) (111) (103)

.59** (121)

.58** .23** .45** .65**

(113) (114) (107) (100)

.53** (115) .51** (115)

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Table 2 Correlations between the predictor measures at 3 months of age and the outcome measures. 24 months

32 months

Bayley

Looking time (habituation) Dishabituation performance Novelty preference VExP-reaction time Immediate retention Bayley-MDI (3 months)

Verbal

K-ABC

Verbal

Mental

Motor

Comprehension

Production

MPC

AS

Production

−.36** (52) −.20 (50) −.10 (46) −.02 (47) −.37** (47) −.18 (59)

−.05 (53) −.14 (51) −.12 (47) −.01 (48) −.47** (50) −.05 (60)

−.32* (49) −.16 (47) −.01 (43) −.30* (43) −.25* (46) −.20 (55)

−.24 (44) −.18 (42) −.06 (39) −.17 (41) −.30* (42) −.12 (49)

−.18 (51) −.31* (48) −.23 (46) −.20 (46) −.36** (48) −.19 (58)

−.29* (51) −.16 (49) −.06 (46) −.22 (46) −.31* (48) −.19 (58)

−.28* (49) −.02 (47) −.11 (43) −.29* (44) −.38** (46) −.03 (57)

Note: sample size n is in parentheses. * p < .05. ** p < .01.

3.2. Bivariate associations between predictor variables and developmental outcomes Associations between parental education and outcome variables were small. Parental education was correlated with Bayley-MDI, r (120) = .19, p < .05, K-ABC-MPC, r (119) = .18, p < .05, and verbal production at 32 months of age, r (115) = .19, p < .05. To determine if the early measures of cognitive ability are important for later developmental outcomes, the predictor variables were correlated with the outcome measurements. These correlations are reported in Tables 2 and 3. In the group of 3-month-old infants, there are four predictors showing significant correlations with several outcome measures. First, faster habituation (shorter looking time) at 3 months of age was associated with higher developmental outcome assessed by the Bayley-MDI and better verbal comprehension at 24 months of age. In addition, faster habituating 3-month-old infants showed better performance in the K-ABC-AS and better verbal production with 32 months of age. Second, dishabituation performance was related to K-ABC-MPC. Third, infants with faster reaction times in the VExP showed better verbal comprehension with 24 months and better verbal production with 32 months of age. Finally, immediate retention (mobile task) was positively related to all outcome measures. Neither performance in the Bayley-MDI, assessed with 3 months, nor performance in the novelty preference task showed significant correlations with the outcome measures. Table 3 provides the associations between assessments at 6 months of age and developmental outcome. The table reveals that looking time in the habituation paradigm was related to all outcome variables. In addition, the results show a relation between dishabituation performance and both Bayley Scales, verbal production with 24 months of age as well as K-ABC-MPC. Novelty preference was related to Bayley-MDI. There were two additional patterns of significant correlations between early and later outcome measures: faster VExP-reaction time was related to better verbal comprehension and production with 24 months of age and to both K-ABC Scales. The early assessment of the Bayley-MDI was associated with both Bayley Scales as well as K-ABC-MPC. In summary, there were several meaningful relations between parental education as well as early indicators of cognitive processes and later developmental outcome. 3.3. Predicting later developmental outcome from sets of indicators A number of simultaneous regression analyses were carried out to test the hypothesis that an increase in incremental validity can be observed by a combination of early predictors of cognitive abilities. Regression analysis was computed in turn for each outcome variable. Those predictors were included in the respective analysis, which had been shown to be significantly correlated with the outcome. Linear multivariate regression analyses and quadratic multivariate regression analyses were Table 3 Correlations between the predictor measures at 6 months of age and the outcome measures. 24 months

32 months

Bayley MDI Looking time (habituation) Dishabituation performance Novelty preference VExP-reaction time Bayley- MDI (6 months)

−.43** (57) −.27** (53) .27* (51) −.15** (50) − .30** (60)

Note: sample size n is in parentheses. * p < .05. ** p < .01.

Verbal

K-ABC

Verbal

PDI

Comprehension

Production

MPC

AS

Production

−.39** (57) −.36** (53) −.17* (51) −21* (50) −.21* (60)

−.40** (51) .19 (49) −.06 (46) −.28* (47) −.04 (55)

−.33** (48) −.30* (46) −.22* (43) −.27* (44) −.10* (52)

−.32** (56) −.26* (54) −.10* (51) −.28* (52) −.22* (59)

−.25* (56) −.18 (54) −.16 (51) −.33* (52) −.05 (60)

−.31* (53) −.18 (51) −.09 (48) −.05 (48) −.21 (57)

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Table 4 Summary of multiple regression analysis for variables prediction the scores of the different outcome variables in the group of 3-month-old infants. Variable

B

SE B

ˇ

sr2

Criterion: Bayley-MDI (24 months) Looking time (habituation) Immediate retention Parental education

−.01 2.67 .98

.01 1.14 1.61

−.28* .32* .06

.08 .10 .01

Criterion: verbal comprehension (24 months) Looking time (habituation) VExP-reaction time Immediate retention

−.01 −.43 1.28

.01 .28 1.63

−.28* −.24 .12

.08 .05 .01

10.19 2.39 1.40

5.00 .99 1.39

.29* .34* .14

.08 .12 .02

−.01 5.57

.01 2.98

−.24* .27*

.06 .07

−.01 −.75 6.25 −1.24

.01 .60 3.48 4.79

−.22 −.20 .28* −.04

.05 .03 .07 .001

Criterion: K-ABC-MPS (32 months) Dishabituation performance Immediate retention Parental education Criterion: K-ABC-AS (32 months) Looking time (habituation) Immediate retention Criterion: verbal production (32 months) Looking time (habituation) VExP-reaction time Immediate retention Parental education Note: sr2 : unique contribution of the predictor. * p < .05.

computed. Quadratic multivariate regression analyses revealed nonsignificant results in most cases. Therefore, results from the linear regression analyses will be reported below. Table 4 summarizes the results for the 3-month age group. In the case of the Bayley-MDI assessed with 24 months, the combination of looking time in the habituation paradigm and immediate retention revealed a significant multiple regression model, R2 = .22, F (3, 42) = 4.20, p < .01. As indicated by Table 4, looking time in the habituation paradigm, ˇ = −.28, p < .05, and immediate retention, ˇ = .32, p < .05, were significantly and independently related to the Bayley-MDI. In order to determine the overall magnitude of association between the significant predictors and verbal comprehension assessed with 24 months as criterion, looking time in the habituation paradigm, VExP-reaction time and immediate retention were entered simultaneously as predictors. This equation was significant, R2 = .19, F (3, 37) = 2.96, p < .05. Nonetheless, only looking time in the habituation paradigm provided a unique contribution, ˇ = −.28, p < .05. In the case of the K-ABC-MPC assessed with 32 months as criterion, dishabituation performance, ˇ = .29, p < .05, and immediate retention, ˇ = .34, p < .05, were significant and positive independent predictors. The regression model explained 47% of the variance, F (3, 39) = 3.84, p < .001. In the fourth multiple regression, the criterion variable was K-ABC-AS assessed with 32 months and the predictors were looking time in the habituation paradigm and immediate retention resulting in a significant model, R2 = .15, F (2, 43) = 3.86, p < .05. Both predictors explaining unique proportions of variance, ˇ = −.24, p < .05 and ˇ = .27, p < .05, respectively. In addition, the regression model with verbal production assessed with 32 months as criterion was significant, F (4, 36) = 2.60, p < .05, indicating that looking time in the habituation paradigm, VExP-reaction time, immediate retention and parental education together accounted for about 22% of the variance in verbal production. Immediate retention was the only predictor that made a unique contribution, ˇ = .28, p < .05. Multiple regression analyses were again computed for the group of 6-month old infants (see Table 5). Most notably, looking time in the habituation paradigm was included as significant predictor in all multiple regressions. The analysis revealed a significant equation with Bayley-MDI assessed with 24 months as criterion, R2 = .38, F (5, 44) = 5.31, p < .001. Of the five predictors, which had been significantly correlated with Bayley-MDI, only looking time in the habituation paradigm, ˇ = −.37, p < .01, and dishabituation performance, ˇ = .26, p < .05, explained unique variance. When using the Bayley-PDI assessed with 24 months as the criterion variable, looking time in the habituation task, ˇ = −.34, p < .01, and dishabituation, ˇ = .30, p < .01, were again included in the model equation, R2 = .24, F (2, 50) = 7.87, p < .001. Verbal comprehension assessed at 24 months is predicted by looking time in the habituation task, ˇ = −.41, p < .01, and VExP-reaction time, ˇ = −.29, p < .05. The two predictors accounted for 25% of the variance, F (2, 44) = 7.14, p < .01. Similar results were obtained for 24-month verbal production, R2 = .26, F (3, 40) = 4.57, p < .01. Again, looking time in the habituation paradigm, ˇ = −.29, p < .05, and VExPreaction time, ˇ = −.29, p < .05, were included in the regression equation. Dishabituation performance explained additional variance, ˇ = .27, p < .05. Using K-ABC-MPS assessed with 32 months as criterion, looking time in the habituation paradigm, ˇ = −.24, p < .05, dishabituation performance, ˇ = .23, p < .05, VExP-reaction time, ˇ = −.35, p < .01, and parental education, ˇ = .27, p < .05, accounted for 30% of the variance, F (4, 43) = 4.55, p < .01. Shorter looking times in the habituation task, ˇ = −.25, p < .05, and shorter reaction times in the VExP task, ˇ = −.33, p < .01, predicted better performance in the K-ABC-AS at 32-month of age, R2 = .17, F (2, 47) = 4.87, p < .01 (see also Table 3).

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Table 5 Summary of multiple regression analysis for variables prediction the scores of the different outcome variables in the group of 6-month-old infants. Variable

B

SE B

ˇ

sr2

Criterion: Bayley-MDI (24 months) Looking time (habituation) Dishabituation performance Novelty preference Bayley-MDI (6-month) Parental education

−.03 12.16 13.29 .49 2.03

.01 7.24 8.68 .30 1.48

−.37** .26* .20 .21 .17

.12 .04* .03* .04 .03

Criterion: Bayley-PDI (24 months) Looking time (habituation) Dishabituation performance

−.01 10.25

.01 4.22

−.34** .30**

.11 .09

−.04 −.85

.01 .39

−.41** −.29*

.17 .08

Criterion: verbal production (24 months) Looking time (habituation) Dishabituation performance VExP-reaction time

−.03 15.82 −.70

.01 8.11 .33

−.29* .27* −.29*

.08 .08 .07

Criterion: K-ABC-MPS (32 months) Looking time (habituation) Dishabituation performance VExP-reaction time Parental education

−.02 13.39 −.85 3.11

.01 7.54 .31 1.55

−.24* .23* .35** .27*

.05 .05 .12 .07

Criterion: K-ABC-AS (32 months) Looking time (habituation) VExP-reaction time

−.05 −2.31

.01 .92

−.25* −.33**

.06 .11

−.05 9.83

.01 4.24

−.25* .30*

.06 .09

Criterion: verbal comprehension (24 months) Looking time (habituation) VExP-reaction time

Criterion: verbal production (32 months) Looking time (habituation) Parental education Note: sr2 : unique contribution of the predictor. * p < .05. ** p < .01.

Higher parental education, ˇ = .30, p < .05, as well as shorter looking time in the habituation paradigm, ˇ = −.25, p < .05, was significantly associated with better verbal production with 32 months of age, resulting in a R2 of .18, F (2, 50) = 5.60, p < .01. In summary, the combination of predictor variables led to increases of the explained variance for some outcome variables in the 3-month-old group and for all outcome variables in the 6-month-old group. Up to this point, the multiple linear regression analysis was computed separately for each outcome variable. In the next step, the outcome variables, namely Bayley-MDI and -PDI, verbal comprehension and production, K-ABC-MPC and -AS and verbal production (at 32 months), were reduced by a principal component analysis which resulted in a single factor accounting for 49% of the variance. Factor loadings ranged between .54 (Bayley-PDI) and .88 (Bayley-MDI). We interpret this factor to indicate cognitive ability. Factor scores on this dimension were used in the subsequent analyses as dependent variable. For the 3-month-old sample, looking time in the habituation paradigm, r (54) = −.31, p < .05, and immediate retention, r (51) = .47, p < .001, were correlated with the factor scores and therefore included as predictors in the multiple regression Table 6 Summary of multiple regression analysis for variables predicting the factor scores (outcome measures) in the samples of 3- and 6-month-old infants. sr2

B

Age of 3 months Looking time (habituation) Immediate retention

−.01 .53

.01 .19

−.23* .44**

.05* .18

Age of 6 months Looking time (habituation) Dishabituation performance VExP-reaction time Bayley-MDI (6-month) Parental education

−.01 2.62 −.13 .02 .48

.01 1.03 .05 .04 .22

−.37** .30** −.36** .06 .27*

.13 .08 .10 <.01 .06*

Note: sr2 : unique contribution of the predictor. * p < .05. ** p < .01.

SE B

ˇ

Variable

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equation. They accounted for 28% of the variance, F (2, 45) = 8.23, p < .001. As Table 6 indicates, looking time, ˇ = −.23, p < .05, as well as immediate retention, ˇ = .44, p < .01, accounted for unique variance, respectively. For the group of 6-month-old infants looking time, r (59) = −.46, p < .001, dishabituation, r (56) = .35, p < .001, VExP-reaction time, r (53) = −.29, p < .05, Bayley-MDI at 6-month of age, r (63) = .22, p < .05, and parental education, r (63) = .28, p < .05, were significantly related with childhood cognitive ability indexed by the factor scores. The analysis resulted in a multiple regression equation that explained substantial variance (46%), F (5, 42) = 7.24, p < .001. Looking time, ˇ = −.37, p < .01, dishabituation performance, ˇ = .30, p < .01, VExP-reaction time, ˇ = −.36, p < .01, and parental education, ˇ = .27, p < .05, accounted for unique variance, respectively. To give an indication of the uncertainty of the estimations, confidence intervals (CIs) were computed for the abovementioned R2 (Cohen, Cohen, West, & Aiken, 2003). The 95% CI for R2 = .30 (3-month-olds) was .07–.49, and for R2 = .46 (6-month-olds) it was .28–.61. The analysis was computed again, this time without a previous replacement of missing values. The same predictors as in the previous analysis explained 22% (3-month age group) and 44% (6-month age group) of the variance.

4. Discussion The results of the present study confirm that several early indicators of later cognitive developmental outcome can be identified. In the present study, looking time in the habituation paradigm, dishabituation performance, novelty preference, VExP-reaction time, immediate retention and the Bayley-MDI were measured during infancy in a sample of 3- and 6-monthold infants. Patterns of correlations are of special interest because of the many correlations that were computed. Most notably, looking time during the habituation paradigm, assessed at 3 or 6 months of age, was predictive for several variables during childhood: mental and motor development, verbal skills and intelligence. Shorter looking times were consistently correlated with better developmental outcomes. These results are in line with previous studies (e.g., Bornstein et al., 2006; Bornstein & Sigman, 1986; Colombo, 1993). The magnitudes of the observed correlations between habituation time and childhood cognitive performance in the present study are in the range of Kavˇsek’s meta-analysis (2004a). In addition, the results are in line with Kavˇsek’s observation that the predictive validity is higher for habituation then for dishabituation performance. This was especially the case when measured at 3 months of age, as will be discussed below. Another variable that related to childhood cognitive performance came from the VExP. As expected from previous studies (e.g., DiLalla et al., 1990), faster reaction time was associated with better developmental outcome in childhood. Furthermore, immediate retention, measured with the mobile conjugate reinforcement paradigm at 3 months, was related to childhood mental and motor development, verbal skills and intelligence. The present results, therefore, support and extend findings from Fagen and Ohr (1990), who reported significant associations between immediate retention and preschool intelligence tests. Conversely and surprisingly, novelty preference showed nearly no predictive validity in the present study. Tables 2 and 3 show that only one correlation reached significance: in the group of 6-month-old infants, novelty preference was significantly correlated with the Bayley-MDI. Although the majority of published studies report meaningful associations between novelty preference during infancy and later developmental outcome, other studies, nevertheless, reported insignificant correlations (Andersson, 1996; Colombo et al., 2004; Tasbihsazan, Nettelbeck, & Kirby, 2003). For example, in Colombo et al. (2004) infancy novelty preference was not significantly correlated with preschool Bayley-MDI and Bayley-PDI. Methodological features (e.g., stimuli or familiarization time) differed among the studies, which could explain the discrepancies. For example, in the present study, only two trials (faces and abstract patterns) were used and measured only once at 3 or 6 months of age. Other studies (e.g., Colombo et al., 2004; DiLalla et al., 1990; Fagan et al., 2007; Rose, Feldman, Futterweit, & Jankowski, 1997; Thompson, Fagan, & Fulker, 1991) used aggregates over more than two trials and, in addition, over several measurement occasions. Such a procedure might result in more reliable measurements and therefore yield a better prediction. Colombo et al. (1988) showed that an increase in the number of trials resulted in an increase of reliability. The Bayley-MDI assessed with 6 months of age was significantly correlated with both 24-month Bayley-Scales as well as childhood intelligence. No significant relation was found when assessed with 3 months of age as Table 2 shows. The low or absent correlations are in line with the majority of the existing literature (e.g., Kopp & McCall, 1982). In addition, the regression analysis revealed that the 6-month Bayley-MDI did not account for unique variance when it was combined with other infant tasks. Finally, parental education was associated with some outcome measures at 24 and 32 months of age, in agreement with previous studies (Roberts, Bornstein, Slater, & Barrett, 1999; Smith et al., 2002). There are several possible explanations for the relation between parental education and childhood intelligence. First, parental education and childhood intelligence could share common variance as a result of genetic influences. Second, children from more highly educated parents may receive increased beneficial stimulation (Landry, Smith, Miller-Loncar, & Swank, 1997; Sigman, Cohen, & Beckwith, 1997; Smith et al., 2002). Regardless, the rs’ magnitudes are relatively small, although they may increase in later childhood (Thompson, 1993). It should, however, be noted that the parents of the present sample were typically better educated. Thus, the restricted variance of the parents’ educational level might be responsible for the relatively small correlations. Nonetheless, even if parental education was included in the regression equation, infants’ performances predicted childhood abilities independently of parental education. As Table 6 shows, for example, infant variables and parental education both contribute to the child’s

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later intellectual status and this result replicates previous findings (Bornstein et al., 2006; Fagan et al., 2007; Laucht et al., 1994; Smith et al., 2002). The results of the analyses support our strategy to include multiple measures of infant cognition. It would appear that when predicting childhood cognitive performance from an age of 3 months, more than one predictor explained unique variance for three out of seven outcome variables (see Table 4). In the group of 6-month-old infants, multiple predictors explained unique variance for each criterion (see Table 5). The variance accounted for was substantially increased when sets of predictors were included in comparison to the correlations reported in Tables 2 and 3. In addition, using factor scores of the combined outcomes, 28% of the variance was accounted when the predictors were assessed at 3 months of age and 46% of the variance when the predictors were assessed at 6 months of age (see Table 6). The CIs are relatively large owing to the small sample sizes. Nonetheless, even the lower bounds of the CIs support the assumption of some continuity of cognitive abilities from infancy to childhood. A reasonable prediction for a single individual, however, is not possible even with multiple predictors as reported here. There are several explanations for the incremental validity based on multiple infant paradigms. At first glance, all infant paradigms may assess different and distinct processes which are each related to later cognitive functioning. This interpretation arises from the observation of relative low or negligible intercorrelations between the predictors. Some studies show, however, that even within the same infant paradigm different tasks may be unrelated to each other. Rose, Feldman, and Wallace (1988), for example, included three sets of paired-comparison tasks in a novelty preference paradigm. As their results show, the average correlations between the tasks were not meaningful (−.16 < r < .13). Although the paired-comparison tasks, all obtained from the novelty preference paradigm, were unrelated to each other, they accounted for significant variance of childhood intelligence. Similar results are reported in other studies as well (Andersson, 1996; Fagan & Detterman, 1992; Tasbihsazan et al., 2003). As a result of these findings, one’s point of view might change when interpreting the results of the present study. Reliability sets an upper limit to a measurement’s power to correlate with other measurements. It is, therefore, possible that the low interrelations of the different infant paradigms primarily result from the low reliability of infant measurements rather than indicating different processes. Several studies yielded psychometrically low to moderate test–retest reliability estimates (Bornstein & Benasich, 1986; Bornstein & Sigman, 1986; Canfield, Wilken, Schmerl, & Smith, 1995; DiLalla et al., 1990; Malcuit, Pomerleau, & Beauregard, 1991; Pêcheux & Lécuyer, 1983). Results from studies examining the reliability of infant paradigms have been mixed. For example, correlations ranged from .20 to .60 for the majority of quantitative habituation measurements (Colombo, 1993; Kavˇsek, 2004b). The magnitudes are close to the predictive power of the measures. Obtaining sufficient predictive power despite a low reliability is possible if the reliability of the outcome measure (childhood development) is high. Therefore, the significant correlations between predictors and criteria are probably a result of the relatively high reliabilities of the outcomes; Cronbach’s alphas of the outcome measures ranged between .65 (verbal comprehension) and .93 (verbal production) in the present study. The different infant paradigms may, therefore, reflect the same or at least-related processes, but in contrast to the criterion, their reliabilities may be low. As noted above, the most prominent candidates for these underlying processes are processing speed and memory. In fact, all infant paradigms implemented in the present study are interpreted as measuring, to some extent, processing speed (Benson, Cherny, Haith, & Fulker, 1993; Colombo, 1993). Novelty preference, dishabituation performance and immediate retention are associated, in addition, with memory performance (Colombo & Frick, 1999; Rose & Feldman, 1997; Rose et al., 1997). When comparing the results for the 3- and for the 6-month-old infants, similarities as well as differences emerge. As noted earlier, looking time in the habituation task was predictive for both age groups and therefore showed some consistency. In addition, in both groups multiple correlations could be derived from the data. Therefore, in two different age groups an increase in explained variance was demonstrated using multiple tasks, although this observation was more obvious in the group of 6-month old infants. In contrast to these similarities, prediction from dishabituation performance was better when assessed at 6 months of age. It is possible that those infants who were 3 months old showed higher variability in attention and task performance because volitional control over attention (endogenous attention) is less developed in younger infants (Colombo, 2001; Colombo & Cheatham, 2006). However, this is only speculative and previous results are heterogeneous. For example, whereas Lewis and Brooks-Gunn (1981) did find a significant relation between dishabituation assessed with 3 months of age and childhood developmental outcome, Laucht et al. (1994) did not. Both studies used a fixed trial procedure as well. In addition, prediction from VExP-reaction time was better when measured at 6 months. This result replicates a previous longitudinal study using the same VExP-task (Lißmann, Korntheuer, & Lohaus, 2007). Differences between the two age groups in the predictability of the VExP-task might be attributed to differences in reliability. Domsch, Lohaus and Thomas (in press) tested 3- and 6-month-old infants with the VExP-task on two occasions 14 days apart. Retest reliability was low but significant in the 6-month age group, r = .32, p < .05, and insignificant in the 3-month age group, r = .16, ns. Nonetheless, our findings should be interpreted with caution in regards to differences between the two age groups. First, the sample size varies between the two groups as a result of missing values. Second, the mobile paradigm failed with 6-month-old infants and therefore a comparison between the two age groups for this task is not possible. Third, 3- and 6-month-old infants were recruited cross-sectionally and thus, the samples are not directly comparable. The results reported here support the existing literature by demonstrating that information processing capabilities are continuous over age. As mentioned above, the present study extends previous findings as it employed a broad range of

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