Emerging Phonological Awareness Differentiates Children with and without Familial Risk for Dyslexia after Controlling for General Language Skills

Emerging Phonological Awareness Differentiates Children with and without Familial Risk for Dyslexia after Controlling for General Language Skills

Puolakanaho, Anne

Emerging phonological awareness was compared in two groups of 3.5-year-old children belonging to the Jyväskylä Longitudinal Study of Dyslexia (JLD): children with familial risk of dyslexia (at-risk group n = 98) and children without such risk (control group n = 91). Four computer animated tasks were used: Word-level and Syllable-level Segment Identification, Synthesis, and Continuation of Phonological Units. The control group children manifested higher mastery than children in the at-risk group in phonological awareness, and the proportion of children with a low phonological awareness mean score was 2.5 times higher in the at-risk group than in the control group. In both groups, phonological awareness at 3.5 years was predicted by early language skills assessed between 14 and 26 months of age, and it was also associated with concurrent language. The difference between the at-risk and control group at 3.5-year in phonological awareness remained significant, even when the effect of other language skills such as productive and receptive vocabulary, and mastery of inflections, measured both at earlier ages and concurrently were controlled for. Our findings indicate that familial risk for dyslexia is reliably reflected in emerging phonological awareness already at this early age and it can be assessed independently of other language skills.


Deficits affecting the development of skills in the phonological domain, particularly phonological awareness, are widely considered the major causal explanation for the unexpected reading failure of individuals with dyslexia (e.g., Pennington, 1995; Snowling, 2000; Stanovich & Siegel, 1994; Vellutino, et al., 2004). Studies conducted at the reading acquisition phase have shown that learning the alphabetic code leads to a growing awareness of phonological elements of speech, which, in turn, leads to growing alphabetic skills (Morais, 1991; Vellutino, Scanlon, & Chen, 1995; Wagner, Torgesen, & Rashotte, 1994). Because both reading and phonological skills are known to be strongly genetically transmitted (e.g., DeFries, et al., 1991; Pennington, 1995), prospective studies starting at an early age in populations with high incidence of dyslexia have provided a viable way around the problem of reciprocal causation. In a pioneering prospective study of dyslexia, Scarborough (1989, 1990, 1991) showed that children with familial risk of dyslexia who were classified as reading disabled at 8 years manifested deficiencies in utterance length, syntactic complexity, and pronunciation accuracy at 2.5 years, and in object-naming and receptive vocabulary at 3 years of age. Deficiencies in these children’s phonological awareness skills were evident ever since the age when phonological awareness was first assessed at 5 years. More recent follow-up studies (Byrne, Fielding-Barnsley, & Ashley, 2000; Byrne, et al., 1997; Carroll, et al., 2003; Elbro, Borstram, & Petersen, 1998; GaIlagher, Frith, & Snowling, 2000; Lefly & Pennington, 1996; Locke, et al, 1997; Snowling, Gallagher, & Frith, 2003) have added to the pioneering work of Scarborough. However, because of the somewhat inconsistent pattern of findings in these studies and diversity of measures employed to assess phonological awareness, it has not been possible to draw firm conclusions as to whether children with familial risk for reading problems manifest impairments in the very early stage of phonological awareness development, before 4 years of age, and what the early predictors of these skills are.

The earliest age for studying phonological awareness has typically been the kindergarten age. In their follow-up from the beginning of kindergarten (mean age 5 years 4 months) to the first grade, Lefly and Pennington (1996) found that children at high risk for dyslexia and a control group of children at low risk differed at the first grade-but not in kindergarten-on both the rhyming phonological awareness factor and on the blending factor. Elbro, et al. (1998) demonstrated in their study that dyslexia diagnosed at the second grade level was predicted by phoneme identification, letter naming, and distinctness of phonological representations assessed at 6 years of age. Byrne, et al. (1997) found that the performance of at-risk children was slightly poorer than that of control children in an initial phoneme identification task at 4 years 7 months of age, but the groups did not differ from each other in rhyme awareness.

The follow-up study reported in Gallagher, et al. (2000) and Snowling, et al. (2003) extended the age range downward to children below 4 years by studying early phonological awareness (nursery rhyme knowledge assessed by reciting and correcting nursery rhymes) in preschoolers at the mean age of 3 years 9 months. Children at risk for dyslexia who were diagnosed as literacy delayed at 6 years of age were found to manifest poorer nursery rhyme knowledge than control children, and those at-risk children whose reading and spelling scores fell inside the normal range at 6 years (Gallagher, et al., 2000). This precursor of phonological awareness did not, however, prove to be a strong predictor of later literacy development compared to early letter knowledge, vocabulary, and phonological memory. The latter finding is in line with the results by Catts, et al. (1999) who found that contribution of kindergarten oral language abilities (semantic, grammatical, and narrative language skills) can be as great or greater than that of phonological processing abilities (phonological awareness and rapid naming) in predicting later reading achievement. Recently, Snowling, et al. (2003) reported on a new set of analyses from their follow-up that allowed a comparison between those high-risk children who fulfilled the criteria for reading impairment at 8 years and those who did not. Retrospective analyses showed that the impaired high-risk group had performed less well in the nursery rhyme knowledge task at 3.9 years than the unimpaired high-risk group (which in turn performed less well than controls), as well as in phoneme deletion and rhyme oddity tasks at 6 years.

In addition to relying on measures of phonological awareness such as rhyme knowledge, children’s very early phonological skills have also been studied by conducting phonetic analyses of vocalizations. The analyses by Locke, et al. (1997) of children’s vocalizations elicited in parent-child free play between 6 and 18 months, however, did not reveal differences between potentially dyslexic children (n = 13) and the control children (n = 12). A significant group difference was found between the groups in verbal short-term memory at 3 years 7 months of age to the advantage of control children, but this difference was not significant before or after this age. Using measures of phonological awareness, Locke, et al. found that children in the control group performed better in rhyme discrimination than children in the risk group, but again only at a very specific age window (between 3.6 and 4.6 years). Children at risk for dyslexia also had lower scores in rhyme production at 5 and 6 years of age but not in the initial consonant deletion task.

The findings from recent longitudinal studies looking at the early phonological awareness development of children at risk for dyslexia (Gallagher, et al., 2000; Locke, et al., 1997; Snowling, et al., 2003) thus clearly provide support for the phonological deficit hypothesis, but below 4 years of age, the evidence of group differences in phonological awareness is not overly strong. One likely explanation is that designing psychometrically sound measures for assessing PA at this early age is very challenging. In our follow-up of children for dyslexia (Jyväskylä Longitudinal Study of Dyslexia), a battery of four phonological awareness tasks was developed for use with 3.5-year-old children, and embedded in a computer animation context. The tasks were selected to tap the two main dimensions presented in the literature, blending segments into meaningful units and identification of phonological units (Wagner, et al., 1994).

The goal of the present study was to provide a replication of previous group comparisons in a well-controlled and large sample of children with and without risk for dyslexia. We extend the previous studies by using several measures of phonological awareness in assessments of children before 4 years of age. By employing a game-like computer animation context, we hoped to be able to tap and reveal the children’s budding phonological awareness skills (c.f., Gombert, 1992), and thus capture the individual and group differences in phonological processing before the environmental effects in the form of instruction of reading related skills have had an extensive impact on the development of these skills. In addition, measures of the children’s skills in other language domains such as productive and receptive vocabulary and inflectional morphology, obtained at previous ages (14 to 26 months) and concurrently (at 3.5 years), were examined to obtain information on their predictive associations to phonological awareness and to control for the effect of general language proficiency from the group comparisons.



The data were drawn from a developmental follow-up of children at familial risk for dyslexia and their controls, the JLD, focusing on early language development and the predictors of reading skills and reading problems (see H. Lyytinen, et al., 2001). Altogether, 200 families are participating in the followup. For inclusion in the sample of families with dyslexia, we required that, in addition to self-reported incidence of reading problems in one parent and at least one of his or her close relatives, the parent had to score at least 1 SD below the norm (based on a separate sample of the same educational level) in oral reading or in spelling. In addition, he or she was required to show a similar deviation from the norm on at least two other reading measures. Neither the parents nor the relatives of the control families had problems with reading (see selection procedure in more detail in Leinonen, et al., 2001). The children and their families come from the city of Jyväskylä and its surrounding communities in the province of Central Finland. The children are all Caucasian and speak Finnish as their native language. At birth, the JLD at-risk and control group newborns did not differ in gestational age, birth weight, or in Apgar scores (Apgar is a quick test given after birth to determine the physical condition of the newborn).

This paper reports findings concerning 98 at-risk children (50 girls and 48 boys) and 91 controls (41 girls and 50 boys) who had completed phonological awareness tasks at age 3.5 (age at assessment 3.5 years ± 2 weeks). The sample involved all children in the follow-up except those who had not turned 3.5 years at the time of the analyses. Additionally, two children were excluded from the analyses: one child who lived abroad at the time of the 3.5-year assessment, and one child who was diagnosed with autism around 2 years of age. The rare occasions in which data for all tasks are missing were due to test refusal (n = 1), poor general comprehension skills (n = 1), or for such reasons as failure in transferring the computer recorded data into a permanent data file (n = 2). Missing values within a task that emerged toward the end of the testing session (e.g., due to tiredness and inattention) were replaced by linear regression estimates calculated based on correlations between the tasks. The substitution involved less than 6% of the tasks.

The parents’ educational level was representative of the Finnish population. Education level was classified into five categories. All parents had at least 10 years of basic education. Additional professional training among the parents was distributed as follows: 4.6% had no advanced training (i.e., only 9-or 10-year comprehensive school), 3.7% had completed one year vocational schooling, 40.5 % had a two-year vocational or college degree, 35.9% had a vocational institute or college degree, 5.8% had a Bachelor’s degree, and 8.8 % a Master’s degree. Analyses of education levels by group (at risk versus control) indicated that the groups did not differ from each other.


Phonological Awareness. Phonological awareness was assessed at 3.5 years of age with four tasks that represent ageappropriate modifications of task types typically used in the literature (for more details see Puolakanaho, et al., 2003). The tasks were embedded in a computer animation context and they were administered to the child using a computer. The child proceeded in the tasks by pressing touch screen items or by answering questions orally. The responses given by the child by pressing the touch screen items were recorded automatically. Those responses given orally were coded online by the experimenter, but all responses were also recorded in digital sound files for later checking of the codings. The administration of the four tasks analyzed in this paper took approximately 15 minutes.

The task instructions and individual test items were embedded in the context of an interactional story, the Heps-Kups Land. The child was familiarized with the two main animation characters, Maka and Popo, who led her or him through a series of adventures involving other animation characters. Children received visual and auditory rewards (e.g., invisible objects turning visible) for answering questions or responding to requests as they proceeded from one subtest to the next. An animation character called Outo-Orvelo, who was always positioned in one corner of the screen, summarized and clarified the events of the animation to the child, and gave general instructions and corrective feedback when needed. An experimenter sat by the child and monitored the testing situation.

The task instructions and sound stimuli that the children heard consisted of voice recordings made using a high-quality audio recorder, transformed into digital form, and stored as computer sound files. The stimuli were presented to the children via headphones (or for the less than 10% of the children who refused to use the headphones, through loudspeakers). The voice recordings were stabilized so that all the sounds were presented to the child at normal talking level (around 75 dB).

Phonological Awareness Tasks. The subtasks analysed in this paper were completed in the following fixed order: Wordlevel segment identification (WI), Syllable-level segment identification (SI), Synthesis of phonological units (SY), and Continuation of phonological units (CO).

1. Word-level segment identification (eight items). Three pictures depicting tangible objects were shown on the computer screen one after another, and the name of the object was presented immediately after the visual object was seen on the screen. The child’s task was to identify the object that contained the requested part of a compound word. The child responded by touching one of the three pictures on the screen. For example, in Item 2 involving the set “lentokone” (airplane), “soutuvene” (rowing boat), and “polkupyörä” (bicycle), the child was asked, “In which picture can you hear the sound ‘kone’ (plane)?” Two practice items were administered for each child, and a third practice followed automatically if the child failed the first two.

2. Syllable-level segment identification (eight items). The task was similar to the word-level segment identification task in all other aspects except that the target units consisted of subword elements. In two items, a two-syllabic target was used, and in six items, the target unit consisted of one syllable. For example, in Item 6, the set “koira” (dog), “kissa” (cat), “kukko” (cock), the child was asked to identify the syllable “koi.” No practice items were given as the procedure was exactly the same as in the previous task.

In the Word-level and Syllable-level identification tasks, half of the target units were cut artificially from the initial words (e.g., the two-syllabic unit “meli” was cut from the voice recording of the word “kameli”) and half of the target units were naturally produced (e.g., during the audio recording, the speaker had been asked to pronounce both the syllable “su” and the word “possu” separately). The two types of stimuli were used to examine whether the targets including more of the context cues-i.e., the artificially cut target unitswould be easier for the children to identify. However, since no differences emerged in the distributions of correct responses between naturally produced and artificially cut word segments, these two types of stimuli were combined in the analyses.

3. Synthesis of phonological units (12 items). In this task, the child was asked to make “hidden animals” become visible by saying aloud the animal names that could be composed of sound segments that the child heard via the headphones (or the loudspeakers). The child heard segments of varying size (words, syllables, phonemes) that were presented using a 750-msec pause between each segment, and she or he was asked to produce the targeted animal name (e.g., What is “ka-me-li” [camel]?). One test item consisted of a compound word (“virta-hepo” = hippopotamus), eight items required synthesis of syllables (e.g., “per-ho-nen” = butterfly), and three items required synthesis of syllables and phonemes (e.g., “aa-s-i” = donkey). Only a response containing the right assembled form was coded as correct. The principle of assembly was reinforced in the two practice items. To motivate the child and aid in understanding the tasks, the computer screen showed a picture of a landscape with trees and bushes. As the tester coded the child’s response by clicking with the mouse, the program automatically (regardless of the code entered; that is, the correctness of the child’s answer) proceeded to make the picture of the animal in question appear in the landscape (for instance, a tiger jumped from a bush or a monkey appeared on a branch of the tree). The selection of the length of the pause (750 msec) was based on piloting the items. The pause was sufficiently long so that the children would hear the segments as separate units, and the task would be difficult enough in order to reveal variance in the children’s ability for phonological assembly.

4. Continuation of phonological units (eight items). The child was given the beginnings of “secret” words and asked to guess how the words continue (e.g., What could this be: “mu-?”). In some of the items, the syllable easily elicited a word known by most children (e.g., “veit-” [arrow right] “veitsi” (knife) whereas in others the syllable could mark the beginning of a number of words (e.g., “mu-” [arrow right] “muna,” “muki,” “muumi,” “musta”). To motivate the child to go on, a picture of an example of an object starting with the requested phonological segment was shown on the screen after the child gave his or her response. There were two practice items. Items were chosen so that they easily provided the beginning of a meaningful word in the vocabularies of 3.5-year-old children. Only continuations that were meaningful words were coded as correct. In this task, the computer screen showed a picture of staircase, the “secret steps.” The child was asked to “help” the animation characters Maka and Popo climb the stairs by guessing one “secret” word at each step. As the tester coded the child’s response by clicking with the mouse, the program automatically (regardless of the code entered; i.e., the correctness of the child’s answer) proceeded to make a picture of one possible correct response appear on the step in question. For instance, on the item “veit-,” the picture of a knife (in Finnish, “veitsi”) appeared on the step.


Indices of children’s early language development were selected from the measures that had been administered to the children (test data) or their parents (parental ratings on structured questionnaires) when the children were 14, 18, 24, and 26 months of age. The basis for selection was that these measures demonstrated high reliability and predictive value, and they tapped crucial aspects of language development at the age in question.

Vocabulary Comprehension at 14 Months. Parental reports on their children’s developing language skills were obtained using the Finnish adaptation (Lyytinen, 1999) of the infant and toddler forms of the MacArthur Communicative Development Inventory (MCDI), a widely used measure of early language development (Fenson, et al., 1994). The infant MCDI covers the age from 6 months to 16 months, and it provides information on actions and gestures and on vocabulary comprehension and production. Vocabulary comprehension was assessed by means of an item checklist (380 words). A composite score was calculated by summing the number of words that the parent had checked as ones that the child comprehended.

Verbal Comprehension at 18 Months. The Reynell Developmental Language Scales (RDLS) (Reynell & Huntley, 1987) were administered in the laboratory setting when the children were 18 months of age. This RDLS is an individually administered test of verbal comprehension and expressive language skills for children aged 1 year 0 months to 6 years 11 months. In the Verbal Comprehension items, the child is presented with an array of stimulus materials and asked to identify the specified object by pointing or picking it up (e.g., “Which one is carrying something?”) or by responding with specified actions (e.g., “Take two buttons out of the cup.”)· The Expressive Language scale provides three sets of items (Vocabulary, Content, and Structure). Only the index of verbal comprehension at 18 months was used in the current analyses.

The Mental Development Index (MDI) of the Bayley Scales of Infant Development-II (BSID-II) (Bayley, 1993). The BSID-II is a test of infant’s current developmental functioning for ages 1-42 months. It was administered at 2 years of age, and the Mental Development Index (MDI) was included among the early language measures. At this age, a majority of the Mental Scale items critically tap the child’s language comprehension and production skills (e.g., displays verbal comprehension, names three objects, imitates a two-word sentence, uses pronouns, poses questions), and relatively few items are not directly based on comprehension of linguistic concepts (e.g., builds a tower, places pegs, places beads in tube). Our earlier findings also indicate that the MDI correlates highly with expressive language measures derived from parental reports such as correlation of .70 between the two-year Bayley-II MDI and the two-year vocabulary production as reported by parents on the MacArthur Communicative Development Inventory (Lyytinen, 1999). Raw scores on the Mental Scale are converted to standard scores (M = 100, SD = 15).

Global Language at 26 Months. The summated score of global language was based on six language measures: 1) vocabulary production, 2) mastery of inflections, 3) maximum sentence length, 4) verbal comprehension, 5) expressive language, and 6) comprehension of inflections. Three measures-vocabulary production, mastery of inflections, maximum sentence lengthwere derived from parental reports obtained using the toddler form of the MCDI (Fenson, et al., 1994) covering ages from 16 to 30 months. The vocabulary production score consisted of the number of words that the parent had checked as ones that the child both comprehended and produced (maximum 595). Mastery of inflections was based on the 16-item grammar section of the Finnish toddler MCDI in which the parents reported on their child’s use of suffixes (e.g., the child’s uses of suffixes to indicate plural forms of nouns or past tenses of verbs). The maximum sentence length (MSL) was derived by asking parents to write down three of the longest utterances by the child recently. The scoring was based on the mean number of morphemes that the child used in these utterances. For example, the Finnish expression “talo/i/ssa/mme” (“in our houses”) would be counted as four morphemes as it includes a noun /talo/, the plural marker/i/, the indicator of inessive case /ssa/ (corresponding to the prepositional expression of in something), and the possessive suffix /mme/.

Measures of verbal comprehension and expressive language were derived from the administration of the RDLS (Reynell & Huntley, 1987) at 26 months. The sixth measure was a measure of comprehension of inflections derived from a 12-item test administered to the children at 26 months. The test contains four test items and one practice item of each of the following inflectional forms: adjective inflection (comparative), verb inflection (passive past tense), and noun inflection (inessive, i.e., in something). Each item includes a set of three colored pictures: one picture for introducing the target word in its basic form, one picture depicting an object to which the inflected target word applies, and one picture acting as a distractor (e.g., This house is this high. Show me the picture where the house is even higher). The child received one point for each correctly comprehended item.


Productive Vocabulary. The Boston Naming Test (BNT) (Kaplan, Goodglass, & Weintraub, 1983) was used to obtain a measure of productive vocabulary. The BNT is a visual confrontation naming task that taps word retrieval skills and is often used to diagnose word-finding problems (see Kirk, 1992). The Finnish translation of the BNT (Laine, et al., 1997; see also Laine, et al., 1993) contains 60 pictured items that the child is asked to name. The score is based on the number of items that the child names correctly spontaneously plus the number of items that the child names correctly after receiving a semantic stimulus cue.

Receptive Vocabulary. The Peabody Picture Vocabulary Test-Revised (PPVT-R) (Dunn & Dunn, 1981) was used to obtain a measure of receptive vocabulary. In this test, the child hears a word and is asked to point out which picture the word depicts from a set of four alternative pictures. Because the PPVT-R has not yet been standardized in Finland, the raw sum score of correct items (Form L) was employed.

Inflectional Morphology. Mastery of inflectional morphology was assessed using a 20-item Berko-type elicitation test (P. Lyytinen, 1987; P. Lyytinen, et al., 2001; P. Lyytinen & H. Lyytinen, 2004) that covers items of adjective inflection (comparative, superlative), verb inflection (present), and noun inflection (elative; that is, from something). In the test, two- to four-syllabic words are presented orally, together with a colorful drawing, to the child, and the child is instructed to generate the inflection of the target word. The stimuli consist of old Finnish words that are no longer in use and thus are not known by the child. The summated score of correct inflections was used in the current analyses.

Sentence repetition, comprehension of instructions, and productive naming measures were derived from the Developmental Neuropsychological Assessment (NEPSY) (Korkman, Kirk, & Kemp, 1998). This neuropsychological test battery is designed for children aged 3 to 12 years and contains subtests for assessment of attention/executive functions, language, sensorimotor functions, visuospatial processing, and memory and learning. In the sentence repetition subtest, the child repeats verbatim sentences that the examiner reads aloud (17 items). Below the age of 5 years, this type of test is considered to tap verbal knowledge and comprehension along with short-term memory (Sattler, 2001). The Comprehension of Instructions subtest taps the child’s ability to process verbal instructions of increasing complexity. The child is shown a picture sheet of rabbits of difference size, color, and facial expression, and he or she is asked to point to the picture that matches the description given orally by the examiner (13 items; e.g., “Show me a bunny that is big and blue and happy.”). Productive naming was assessed using a task in which the child was shown a picture of a child and asked to name the body parts indicated (11 items; e.g., nose, elbow). In the three tasks, the child was given one point for each correct response. Standard scores were used for all the subtests (M = 10, SD = 3).



There were no statistically significant differences between boys and girls on the phonological awareness skills; thus all subsequent analyses were conducted for both genders combined. Parental educational background did not correlate with children’s phonological awareness skills. Descriptive statistics for phonological awareness skills of the children in the at-risk and control groups are shown in table I. Children in both groups indicated high mastery, especially in word- and syllable-level segment identification and continuation of phonological units, whereas mean level of accuracy was somewhat lower in the syntesis task. As shown in table II, associations among the phonological awareness tasks varied from relatively high to nonsignificant intercorrelations. The correlation pattern suggests particularly strong links between word- and syllable-level segment identification on the one hand, and between synthesis and continuation of phonological units on the other hand.


Comparisons between mean levels of accuracy in phonological awareness of at-risk and control group children were first conducted using the subtest scores (raw sums of correct responses in each task). In these comparisons, one-tailed testing was employed based on the assumption that the potential difference would be in the direction of poorer performance for the at-risk group. As shown in table I, statistically significant differences between the at-risk group and the control group in favor of the control children were found in all tasks. Next, a mean PA score was created by first converting each variable to a z-score and then averaging the z-scores across the four tasks. As shown in table II, intercorrelations between the four tasks are not as high as one would hope; however, averaging over all four tasks produced the strongest composite with internal consistency of .63 as evaluated by Cronbach’s alpha. The groups differed significantly from each other also on the PA mean, £(187) = -3.52, p

An additional analysis was conducted to control for the effect of background variables on this group difference. The background variables selected for this analysis were mother’s and father’s education, and child’s developmental level at 2 years of age. These were selected in order to ascertain whether variance in parental stimulation and richness of home environment as reflected in educational attainment or in child’s general cognitive skills would explain the group difference in phonological awareness. As a measure of earlier developmental level, we used the MDI from the Bayley Scales of Infant Development-II (Bayley, 1993), an individually administered test of infants’ current developmental functioning administered to all children in the follow-up at 2 years of age. The MDI is a standard score (M = 100, SD = 15) based on Mental Scale items tapping various aspects of cognition and language (e.g., language comprehension and production, problem-solving, memory, number concepts, classification, and some aspects of personal-social development). An ANOVA with the phonological awareness mean score as the dependent variable, group as the between factor, mother’s and father’s educational level, and the child’s two-year Bayley MDI as covariates showed that the group difference remained (F[1.179] = 14.73, p

We also conducted a group comparison on those children who were among the lower half of the distribution (scoring below the 50th percentile on the phonological awareness mean score) in each group. The 50th percentile criterion was based on the expectation presented in the literature (see Pennington, 1995) that approximately half of the children with familial risk for dyslexia eventually manifest reading problems. This comparison also produced a significant difference between the groups, f(94) = -4.85, p


The mean score of children in the control group was used as a normative reference for determining the 1.0 and 1.5 standard deviation cutoff points for impaired phonological awareness. When the 1 SD criterion was applied, the scores of 36.7% of the children in the at- risk group and 14.3% of the children in the control group fell below the criterion. When the 1.5 SD criterion was applied, the scores of 16.3% of the children in the at-risk group and 6.6% of the children in the control group fell below the criterion.

Associations between Phonological Awareness and Early and Current Language Development. Score distributions of language variables to be entered into the analyses were found to be close to normal. The few missing values were found to be random in nature, and they were replaced by using the EM algorithm (SPSS 11.0). As shown in table III, the phonological awareness mean (calculated across the four PA tasks administered at 3.5 years) correlated significantly with all of the early and current language variables in the at-risk group and all but one language variable in the control group.

Early Language. A maximum likelihood analysis of the early language scores (table III) found one latent language construct. The resulting early language factor scores correlated significantly with the 3.5-year phonological awareness mean (at-risk group: r = .48, p

Language at 3.5 Years. There also were relatively high correlations among the language variables assessed at 3.5 years of age, and a factor analysis (using the Maximum Likelihood method) confirmed a one-factor solution. When the resulting concurrent language factor scores were partialled out from the correlations between the 3.5 year language variables and phonological awareness, most of the coefficients dropped to a nonsignificant level (for coefficients, see table IV). Those correlations, which remained significant even after partialling, were scattered on mostly different variables in the at-risk and control group, and none of these associations proved to be statistically significantly different in the two groups.

Early and concurrent language correlated highly in both groups (at risk: r = .72, p

Next, an ANCOVA model was constructed with phonological awareness as the dependent variable that included both the early and concurrent language factor scores in addition to group. Because a slightly stronger relationship between phonological awareness and early language was suggested for the atrisk group children than the control group children (.48 versus .31), the interaction effect was tested for group and early language, but only the main effect was tested for concurrent language. The groups were not found to differ in the association between early language and phonological awareness. In this model including both early and concurrent language, a significant relationship emerged between PA and concurrent language (F[.184] = 26.33, p


Phonological awareness was compared in two groups of 3.5-year-old children: children with familial risk for dyslexia and children without such risk. The control group children were found to manifest higher mastery of phonological awareness skills than the at-risk children, and the proportion of children with a low phonological awareness mean score was 2.5 times higher in the at-risk group than in the control group. In both groups, phonological awareness at 3.5 years was predicted by early language skills (e.g., verbal comprehension, vocabulary, and inflectional skills) assessed between 14 and 26 months of age. At least moderately high associations were also found between PA and other language skills assessed at the same age (e.g., receptive and productive vocabulary, and morphological skills). However, the group difference in phonological awareness remained significant even when both early language and concurrently assessed language skills were controlled for. The present study supports the importance of assessing emerging phonological awareness skills in association with risk for dyslexia (Byrne, et al., 1997; Chaney, 1998; Elbro, et al., 1998; Gallagher, et al, 2000; Lefly & Pennington, 1996; Locke, et al., 1997; Scarborough, 1990).

Parental educational background was not associated with children’s phonological awareness skills, nor were there differences between girls and boys. The mean level of performance of the at-risk group children was poorer than that of the control children in all four phonological awareness tasks. The group difference was most pronounced in tasks requiring continuation and synthesis of phonological units. Also, previously, tasks tapping synthesis skills have been reported to show differences between young children of different ages (e.g., Metsala, 1999), and to predict later reading related skills (e.g., Burgess & Lonigan, 1998; Chaney, 1998; Wagner, et al., 1993).

It may be speculated that phonological awareness skills have a different role in highly transparent, orthographically regular languages such as Finnish than in less transparent or irregular languages (see Aro, et al., 1999). In consistent orthographies, exposure to print and letters is believed to be a powerful method for advancing phonemic awareness, and consequently it could be speculated that phonological awareness deficiency as such may not as directly affect acquisition of reading accuracy or reading fluency as in less consistent orthographies (see e.g., Wimmer, Mayringer, & Landerl, 2000). Our finding of differences between children with familial risk for reading problems and those without such risk in their PA skills at 3.5 years of age, however, implies that measures of early phonological awareness also tap features associated with familial risk in an orthographically regular language. A recent Finnish study revealed that phonological awareness assessed before formal reading instruction predicted reading reliably at the first grade (Holopainen, Ahonen, & Lyytinen, submitted; Holopainen, et al., 2000). It should be noted that although approximately onethird of the Finnish children typically spontaneously learn to read by the time they enter the first grade (the year when they turn 7 years of age), very precocious reading is not very common, which may partly be due to the tradition of our early childhood education that does not explicitly include teaching of letter names or the principle of assembly. Among the JLD followup sample, the median of accurately named letters was only one letter at 3.5 years of age (less than 4% could name 16 letters accurately), and none of the children manifested reading skill at 4 years of age (less than 1.5% read four out of six words accurately).

We found that in the at-risk group, the proportion of children with a low phonological awareness mean score was substantially higher than in the control group. This is in line with prior literature, except for the fact that the ratio of low scoring children in familial risk groups has sometimes been reported to be notably higher (e.g., four times higher risk for children in the familial risk group) (Gallagher, et al., 2000). This, of course, is affected by the selected cutoff for and the measures of phonological awareness. Our lower percentage may be due to our intentional decision to employ purely measures of phonological awareness instead of using component scores that also tap other phonological skills (e.g., phonological memory tasks such as nonword repetition). Inclusion of measures that reflect phonological skills more broadly would very likely have increased the proportion of low scoring children in the at-risk group (see H. Lyytinen, et al., 2004). Another reason for our lower ratio may be the very young age of assessment of our subjects, which may bring more measurement error. With age and accumulating environmental effects, the deficiencies are likely to become more evident (see H. Lyytinen, et al., 2001 for a summary of early findings of the follow-up).

Our longitudinal design and its frequent assessment points also provided an opportunity to analyze the early correlates of phonological awareness. The language measures that were employed were comprehensive with respect to domain (e.g., vocabulary, syntax, morphology), and they involved both parental ratings (mainly in the youngest ages between 14 and 26 months) and structured tests. Children’s phonological awareness skills were found to be associated with all earlier language and concurrent language skills, and as expected, when both of them were included in the same model, only the concurrent association remained significant. Among the tasks that shared highest variance with PA was concurrent comprehension of instructions (table IV), a measure that taps the ability to process and respond to verbal instructions of increasing syntactic complexity by pointing to target shapes. Although the correlations suggested a tendency for higher associations between the language measures and phonological awareness in the at-risk group than in the control group, the analyses using the language factor scores indicated no group differences. Of most interest was the finding that the significant difference between the at-risk and control group in 3.5-year phonological awareness remained, even when the effect of other language skills measured both at earlier ages and concurrently were controlled for.

Our findings indicate that phonological awareness can be assessed using age-adapted tasks long before formal reading instruction. Although the tasks can be improved psychometrically by increasing the number and difficulty of the items, it is noteworthy that they discriminated between the control and at-risk groups in their current form. To increase the clinical utility of the tasks and to avoid a great number of false positives, a wide spectrum of measures with careful psychometrical experimentation is needed. In future studies, it will be important to study how emerging phonological awareness skills are related to skills in other linguistic and cognitive domains (cf., Catts, et al., 1999), and finally to emerging reading and writing.


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Manuscript received August 11, 2004.

Final version accepted September 20, 2004.

Anne Puolakanaho, Anna-Maija Poikkeus, Timo Ahonen, Asko Tolvanen, and Heikki Lyytinen1

University of Jyväskylä, Finland

1 This paper was prepared as a part of the project Human Development and Its Risk Factors financed by the Academy of Finland (Finnish Centre of Excellence Programme Nr. 40166 for 1997-1999, and Nr. 44858 for 2000-2002).

Address correspondence to: Anne Puolakanaho, Vaajakoski Social Services Center, 40800 Jyväskylä, Finland, E-mail: Anne. Puolakanaho@jklmlk.fi; or Anna-Maija Poikkeus, Department of Teacher Education, University of Jyväskylä, P. O. Box 35, 40014 Jyväskylä, Finland, E-mail: poikkeus@psyka.jyu.fi.

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