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Journal of Speech, Language, and Hearing Research : JSLHR logoLink to Journal of Speech, Language, and Hearing Research : JSLHR
. 2023 Jul 20;66(8):2766–2782. doi: 10.1044/2023_JSLHR-22-00142

Preliteracy Skills Mediate the Relation Between Early Speech Sound Production and Subsequent Reading Outcomes

Marjolein Mues a, Jennifer Zuk a,b,✉, Elizabeth S Norton c, John D E Gabrieli d, Tiffany P Hogan e, Nadine Gaab a
PMCID: PMC10555467  PMID: 37473736

Abstract

Purpose:

Learning to read is a complex, multifaceted process that relies on several speech and language–related subskills. Individual differences in word reading outcomes are indicated among children with inaccurate speech sound productions, with some of these children developing later reading difficulties. There are inconsistent reports as to whether phonological deficits and/or weaknesses in oral language explain these subsequent reading difficulties. Thus, it remains unclear how variability in speech production accuracy in early childhood may impact reading development. Therefore, the present longitudinal study seeks to clarify the relation between speech sound production accuracy in kindergarten and subsequent reading outcomes with a focus on additional potential mediating factors.

Method:

Speech accuracy, core preliteracy skills (phonological awareness, rapid naming, and letter–name knowledge), and additional potential mediators (phonological memory and oral language abilities) were characterized at the start of formal reading instruction. Word reading, decoding, reading fluency, and comprehension were assessed at the end of second grade. Mediation analyses were conducted to examine factors that mediate the relation between speech accuracy in kindergarten and subsequent reading outcomes.

Results:

Initial associations between early speech sound production accuracy and subsequent reading outcomes were indicated; however, mediation effects of preliteracy skills (phonological awareness and letter–name knowledge) were identified for word reading, decoding, and reading fluency outcomes. For reading comprehension, mediation effects of preliteracy and vocabulary skills were observed.

Conclusions:

The relation between speech sound production accuracy and subsequent word reading, decoding, reading fluency, and comprehension was observed to be mediated by preliteracy skills, specifically phonological awareness and letter–name knowledge. For reading comprehension only, vocabulary knowledge were of additional importance.

Supplemental Material:

https://doi.org/10.23641/asha.23671491

Becoming a proficient reader is of critical importance for academic and societal success, yet approximately two thirds of children in the United States demonstrate below grade-level reading skills in the fourth grade (National Assessment of Educational Progress, 2022). Difficulty learning to read can impact word-level reading, but often also leads to weaknesses in reading fluency and/or comprehension (Nation, 2019; Perfetti et al., 2005), with cascading effects on children's academic trajectory and psychological well-being. Overall, feelings of inadequacy, anxiety, and frustration can be observed in children with reading deficits, hindering long-term academic and vocational potential (Arnold et al., 2005; Guthrie & Wigfield, 2000). Delineation of factors in early childhood that may predict subsequent reading outcomes even before children begin formal reading instruction offers the potential to identify those at risk early on and provide effective targeted remediation.

The Multifactorial Trajectory of Reading Acquisition

Learning to read is a complex, multifaceted process that is dependent on an interaction between multiple factors at cognitive, neural, genetic, and environmental levels (Case et al., 2010; Ozernov-Palchik et al., 2016; Pennington et al., 2012; van Bergen et al., 2014; van Otterloo & van der Leij, 2009). Although the cause(s) of difficulty with learning to read remain elusive, converging evidence points toward the notion that reading difficulties most likely manifest from multiple risk factors rather than a singular explanatory deficit (Catts & Petscher, 2022; Pennington, 2006; Pennington et al., 2012; van Bergen et al., 2014; Yu et al., 2018). It has been suggested that a probabilistic interaction of multiple risk factors increases the liability of developing word reading difficulties, whereas putative “protective” factors may decrease this likelihood (e.g., Pennington, 2006). As a result, the dynamic interaction of these collective factors is thought to give rise to a wide range of outcomes along a continuum from typical to poor word reading abilities (van Bergen et al., 2014).

To date, one potential contributing factor that remains elusive in shaping the trajectory of reading acquisition is the role of early speech sound production. Learning to read is built upon an initial awareness of individual speech sounds (phonemic awareness) within words and how these sounds map to graphemes to decipher the symbolic code. Thus, it is conceivable that the ability to accurately produce individual speech sounds in spoken language (i.e., speech sound production) may contribute to the foundational skills necessary to become a proficient reader (e.g., recent review in Cabbage et al., 2018). However, it remains unclear to what extent speech sound production accuracy uniquely contributes to the prediction of reading abilities. In particular, there is a need to build a better understanding of the role of contributing factors known to influence reading abilities that may also explain putative links between speech production accuracy and subsequent reading outcomes.

Three factors that have been repeatedly shown to predict subsequent reading outcomes at the kindergarten age (i.e., “preliteracy” skills) comprise phonological awareness, alphabet knowledge (letter–sound and letter–name knowledge), and rapid automatized naming (RAN; Bowey, 2005; Caravolas et al., 2012; Lonigan et al., 2000). Phonological and phonemic awareness involve awareness of individual speech sounds and the ability to manipulate speech sounds within words (Melby-Lervåg et al., 2012). Phonological awareness, together with a child's letter name knowledge, is especially instrumental for word reading and decoding. Ultimately, phonological awareness and letter–sound knowledge set a crucial foundation for subsequent reading fluency and comprehension skills (Cardoso-Martins & Pennington, 2004; Foulin, 2005; Leppänen et al., 2008; Melby-Lervåg et al., 2012; Snowling & Melby-Lervåg, 2016). The ability to rapidly name visual symbols (e.g., familiar objects, including letters), known as RAN, has been identified as a robust predictor of particularly word reading and reading fluency skills (Blachman, 1984; Compton, 2003; de Jong & van der Leij, 1999; Landerl et al., 2013; Landerl & Wimmer, 2008; Lepola et al., 2005; Pan et al., 2011; Schatschneider et al., 2004; Snowling & Melby-Lervåg, 2016; Wolff, 2014).

In addition to these “core preliteracy skills,” broad weaknesses in various components of oral language (such as oral sentence comprehension, general listening comprehension, and/or vocabulary knowledge) have been shown to introduce a heightened risk for difficulty learning to read (for recent reviews, see Adlof & Hogan, 2018; Hogan et al., 2014; Snowling & Melby-Lervåg, 2016). Notably, however, these broad language deficits have been predominantly associated with deficits in reading comprehension (Hemphill & Tivnan, 2008) and reading fluency (Durand et al., 2013) rather than word reading or decoding difficulties.

Of the breadth of longitudinal investigations that have sought to predict word-level reading outcomes from kindergarten, surprisingly, few studies have evaluated the role of early speech sound production accuracy (Cabbage et al., 2018; Gallagher et al., 2000; Pennington & Lefly, 2001). Therefore, this study seeks to examine the extent to which associations between early speech sound production accuracy and subsequent word reading, decoding, fluency, and/or comprehension may be present when accounting for a comprehensive set of potential explanatory contributing factors.

Early Speech Sound Production Accuracy in Relation to Reading Acquisition

Varied literacy outcomes have been reported among children with speech sound disorders, a broad diagnostic label used to characterize inaccurate production of individual speech sounds that persist in a child's conversational spoken language beyond the typical age of acquisition (Shriberg, 2003). Some children with speech sound disorders at the preschool/kindergarten age, characterized by articulation and/or phonological errors, present with an early risk for reading difficulties (Gallagher et al., 2000; Pennington & Lefly, 2001; Scarborough, 1990; Tambyraja et al., 2020) and subsequently demonstrate poor word reading abilities (Anthony et al., 2011; Bird et al., 1995; Larrivee & Catts, 1999; Lewis et al., 2000; Peterson et al., 2009; Raitano et al., 2004; Rvachew, 2007) as well as reduced reading fluency performance (Puranik et al., 2008). However, it is important to note that not all children with speech sound disorders subsequently develop reading difficulties (Catts, 1993; Hesketh, 2004; Nathan et al., 2004; Peterson et al., 2009).

To date, it remains unclear why some children with speech sound disorders develop reading difficulties whereas others do not. Emerging evidence suggests that children who produce atypical or unusual speech errors (errors that are not common in typically developing speech, e.g., vowel distortions or initial consonant deletions) are at greater risk for later reading difficulty as compared with children who produce speech errors that are more common in younger, typically developing children (Hayiou-Thomas et al., 2017; Preston et al., 2013). Importantly, one of the most significant risk factors for reading difficulty among children with speech sound disorders is whether or not they are still producing speech production errors at the onset of reading instruction (i.e., in kindergarten; Bird et al., 1995; Hayiou-Thomas et al., 2017; Raitano et al., 2004). Children with speech sound disorders beyond 6 years of age, regardless of initial severity (Hayiou-Thomas et al., 2017), have demonstrated a heightened risk for reading difficulty (Nathan et al., 2004; Raitano et al., 2004).

It is possible that a lack of clarity in our understanding of speech sound disorders and reading is due to co-occurring language difficulties in these children, but the influence of language has not yet been consistently addressed. Some previous studies have included children both with speech sound disorder and language difficulties. For example, 6-year-old children with speech sound disorders who also had co-occurring language difficulties (defined by receptive and/or expressive language performance below the 10th percentile) subsequently showed poorer performance on word-level reading outcomes, whereas children with speech sound disorders without language difficulties did not differ from typically developing controls (Nathan et al., 2004). Four- to 6-year-old children with co-occurring speech sound disorders and broad language deficits demonstrated significantly reduced decoding and reading comprehension abilities relative to those with speech sound disorders and typical language abilities (Lewis et al., 2000). Converging longitudinal evidence identified that while children with speech sound disorders at age 5 years exhibit a greater likelihood of developing word reading, reading fluency, and comprehension difficulties by age 9 years, this estimate became significantly higher among those with co-occurring language difficulties (Peterson et al., 2009).

Learning to read in itself may promote speech sound perception and production abilities, as reading acquisition calls upon and reinforces phonological representations of words and phonemes. This, in turn, scaffolds the encoding of novel phonological forms (e.g., Burnham, 2003; de Jong et al., 2000; Huettig et al., 2018; Konerding et al., 2020), as word reading abilities at the end of second grade have been shown to predict phonological awareness abilities in fourth grade (Hogan et al., 2005). Thus, it remains unclear whether early speech sound production abilities uniquely relate to subsequent reading outcomes or whether these putative links may be explained by closely related contributing factors.

The Need to Clarify the Relation Between Speech Sound Production Accuracy and Multifaceted Reading Skills in the Context of Potential Contributing Factors

Although provisional links between early speech sound production and subsequent word reading have been established (e.g., Anthony et al., 2011; Peterson et al., 2009; Raitano et al., 2004; Rvachew, 2007), it remains unclear whether speech sound production accuracy uniquely contributes to word-level reading, fluency, and comprehension skills in the context of well-established key literacy predictors, namely, core preliteracy predictors (phonological awareness, rapid naming, and alphabet knowledge) and oral language abilities. Mixed research has examined the possibility of core preliteracy skills and oral language as explanatory contributing factors, resulting in the need to build a better understanding of whether and how these putative contributing factors may explain the relation between speech sound production and multifaceted reading skills. These potential contributing factors are considered in the context of extant literature below.

Core Preliteracy Skills as Explanatory Factors Contributing to the Relation Between Speech Sound Production Accuracy and Reading

A growing body of evidence suggests that phonological and phonemic awareness (hereafter referred to collectively as phonological awareness) may explain the relation between speech sound production and reading. Specifically, word reading deficits among children with speech sounds disorders have been linked to weaknesses in phonological awareness (Bird et al., 1995; Nathan et al., 2004; Preston & Edwards, 2010; Raitano et al., 2004). These weaknesses have been implicated even when controlling for poor speech sound production accuracy (Anthony et al., 2011; Rvachew et al., 2003; Sutherland & Gillon, 2005) and after speech sound errors have resolved/been remediated (Raitano et al., 2004). One longitudinal study tracking children with and without speech sound disorders from 4 to 7 years of age found that, although there was a higher prevalence of risk for reading difficulties among children with persistent speech deficits, longitudinal follow-ups revealed no effect of speech perception or production abilities in contributing to the prediction of word-level reading and reading comprehension outcomes when controlling for phonological awareness (Nathan et al., 2004). Thus, phonological awareness is robustly linked to reading outcomes, in children both with and without speech sound disorders.

One study to date reports that phonological awareness mediates the relation between speech sound production accuracy and word reading (Overby et al., 2012). In their retrospective longitudinal analysis examining the relation between speech sound production abilities in kindergarten in relation to subsequent word reading outcomes 1–3 years later, phonological awareness was reported to mediate the relation with first and second grade word reading (with phonological awareness accounting for > 80% of the variance in second grade word reading; Overby et al., 2012). These findings suggest that the relation between speech sound production and word reading is mediated by phonological awareness and that this relation changes over the course of development. However, this study only examined word reading. Thus, it remains unclear how potential mediating associations may vary across additional reading constructs (e.g., decoding, reading fluency, and comprehension) as various constructs may rely on differing subsets of foundational skills (Scarborough, 2001).

Despite emerging evidence suggesting phonological awareness mediates the link between speech sound production and word reading skills, the role of additional core preliteracy skills, specifically RAN and alphabet knowledge, has yet to be systematically addressed. Associations between phonological awareness, RAN, and alphabet knowledge are complex (Ozernov-Palchik et al., 2022) and underspecified in the context of the relation between speech sound production and reading. It is conceivable that RAN could be associated with speech sound production abilities, as weaknesses in RAN have been correlated with difficulty in quickly and efficiently performing phonological encoding tasks, which, based on the aforementioned literature, may in-turn be intricately linked with speech sound production abilities (Byrd, 2018). Given the key role of RAN in the trajectory of literacy acquisition and its unknown relation to speech sound production abilities, the possible role of RAN warrants direct investigation when examining the relation between speech sound production and reading.

As for alphabet knowledge, the third core preliteracy skill highly predictive of multifaceted reading outcomes (Catts et al., 2001; Foulin, 2005; McBride-Chang, 1999), specific associations between speech sound production accuracy and letter naming accuracy have previously been indicated. Early speech production accuracy from infancy/toddlerhood has been linked with subsequent letter–name identification at the preschool age (Farquharson et al., 2018), and children's speech accuracy at the preschool age has been shown to predict letter–name knowledge at age 6 years (Webster et al., 1997). Furthermore, children with speech difficulties have also demonstrated poor letter identification (letter naming) from 4 to 6 years of age (Carroll & Snowling, 2004). These collective findings suggest that speech sound production and letter–name knowledge may be intricately linked, especially at the start of formal reading instruction. However, no study has examined letter-name knowledge as a potential mediator of the relation between speech sound production and reading abilities.

Oral Language Skills as Explanatory Factors Contributing to the Relation Between Speech Sound Production Accuracy and Reading

Another relevant aspect known to impact the trajectory of reading acquisition pertains to broad oral language abilities (e.g., receptive and/or expressive vocabulary, grammar/syntax, sentence comprehension), as studies have shown that children with co-occurring speech and language deficits are at a heightened risk for difficulty learning to read words and comprehend text (Apel & Lawrence, 2011; Hayiou-Thomas et al., 2017; Lewis et al., 2000; Nathan et al., 2004; Peterson et al., 2009). Two studies to date have additionally examined whether general oral language abilities, particularly expressive vocabulary, mediate the relation between speech sound production abilities and reading, yielding mixed reports (Jin et al., 2020; Overby et al., 2012). Although one recent study observed a significant mediation effect of expressive language abilities at age 5 years explaining the relation between speech and overall estimates of reading proficiency at age 8 years (Jin et al., 2020), all speech, language, and reading estimates were solely determined by rudimentary parent report. No effect of vocabulary knowledge was observed in previous mediation models from Overby and colleagues, although it is important to note that this sample involved children with predominantly typical vocabulary skills and a lack of variation in language abilities within the sample may have impacted this finding (Overby et al., 2012). Therefore, further evidence needs to examine the extent to which variation in broad oral language abilities may mediate the relation between speech sound production and reading abilities.

Overall, some converging evidence suggests that putative contributing factors may explain the relation between speech sound production and reading; however, there is a lack of consensus as to what these factors are and lack of understanding what the role of these factors may be in this context. Emerging literature suggests that the relation between speech sound production and reading is mediated by phonological awareness (Overby et al., 2012), yet additional core preliteracy skills and broad oral language abilities have scarcely been examined in this context (Nathan et al., 2004). Moreover, this limited evidence solely focused on word reading (e.g., Overby et al., 2012). Thus, the role of speech sound production accuracy in contributing to multifaceted reading skills has yet to be fully addressed, particularly (a) decoding, which would be of interest to understand in relation to speech sound production given the emphasis on “sounding out” unfamiliar words, and (b) reading fluency and comprehension, essential indicators of reading achievement that ultimately involve integrating printed text to extract meaning (Soden et al., 2015).

Purpose of This Study

Determination of factors in early childhood that influence the likelihood of developing subsequent word reading difficulties offers great potential to inform educational and clinical approaches to facilitating successful reading acquisition (Case et al., 2010; Fielding-Barnsley & Purdie, 2003; Schneider et al., 2000; van Otterloo & van der Leij, 2009) and ultimately, to minimize the long-term negative consequences associated with difficulty learning to read. This study therefore seeks to determine whether early speech sound production accuracy uniquely contributes to the prediction of subsequent word reading, decoding, fluency, and comprehension beyond core preliteracy and broad oral language skills. The present investigation is undertaken as part of a comprehensive longitudinal study from the start of formal reading instruction (i.e., kindergarten) to the end of second grade in a sample with diverse socioeconomic representation. Utilizing a retrospective approach to obtain a detailed characterization of speech sound production accuracy in kindergarten (via Percent Consonants Correct–Revised [PCC-R]), we evaluated speech sound production in conjunction with core preliteracy skills (phonological awareness, RAN, and letter–name knowledge), and oral language abilities at the start of formal reading instruction in relation to subsequent reading outcomes at the end of second grade.

To date, the only mediation analysis to employ overt characterization of children's longitudinal abilities rather than relying solely on parent report (Jin et al., 2020) has exclusively focused on word reading (Overby et al., 2012). Therefore, this study will extend beyond previous research through comprehensive investigation of the longitudinal relation between speech sound production and reading by examining not only word reading but also decoding, reading fluency, and comprehension while accounting for core preliteracy and broad oral language skills. Therefore, this study contributes a necessary next step to clarify the role of early speech sound production accuracy in explaining unique variance in subsequent reading abilities. Ultimately, this research holds the potential to illuminate key factors in conjunction with early speech sound production that contribute to children's reading outcomes from the start of formal reading instruction.

Method

Participants

One hundred fourteen children (60 female/54 male, age range: 4;8–6;7 [years;months], M age = 5;6, SD = 3 months) were included in this study as part of a larger longitudinal investigation of children at behavioral risk for dyslexia: Researching Early Attributes of Dyslexia (i.e., the READ study). Participants were initially enrolled through initial screening conducted within 20 prekindergarten (i.e., a classroom-based kindergarten readiness program in the United States for children who are generally from 4 to 5 years of age) and kindergarten classrooms within varied types of schools (public district, public charter, private, and religious) across diverse areas (e.g., urban and suburban) across New England. Initial screening involved completion of a brief battery of key preliteracy skills to identify children at risk for reading difficulties (see also Centanni et al., 2018; Ozernov-Palchik et al., 2016; Saygin et al., 2013; Zuk et al., 2021). Screening took place in the spring of prekindergarten or early fall of the kindergarten year to ensure that the child had received minimal formal reading instruction at the time of assessment.

In total, initial classroom screening involved 1,433 English-speaking children. A subset of 186 children were then enrolled for multimodal longitudinal follow-up, which involved only a subset of children in order to employ neuroimaging (EEG and MRI) methods and comprehensive behavioral assessment during the kindergarten year as well as subsequent longitudinal follow-up until the end of second grade as part of the larger longitudinal investigation. Following the initial screening, children identified as at risk for dyslexia were oversampled in the selection of longitudinal enrollment in an effort to capture variance in reading outcomes over time. Among the 186 children longitudinally enrolled, only those who met the eligibility criteria (outlined below) and for whom primary factors of interest (speech and at least one reading measure) were acquired and usable at both the kindergarten and second grade time points were included in the present analysis, which led to a sample of 114 children (with data missing at random due to a combination of whether quality audio recordings obtained at the first time for speech analysis and whether reading measures were successfully completed at longitudinal follow-up). Children with partial completion of subsequent reading measures were included, resulting in some missing data for untimed word reading (n = 2), untimed decoding (n = 3), reading fluency (n = 3), and reading comprehension (n = 4). Due to this subtest-specific missing data, final analyses ranged from n = 110 to n = 114, depending on the reading outcome variable employed in each analysis. This study focused on key behavioral factors at the kindergarten time point in relation to subsequent reading outcomes at the end of second grade.

All children included in this study were native American-English speakers with no vision or hearing difficulties and no history of neurological or psychiatric disorders, per parent report. An overview of the diversity of the sample is provided in Table 1. Additionally, all children demonstrated typical nonverbal cognitive abilities as indicated by a standard score of at least 80 on the Kaufman Brief Intelligence Test–Second Edition (KBIT-2; Kaufman & Kaufman, 2004). Most children were right-handed, with four left-handed children included in the present sample. Out of the 114 children in this sample, 49 children were retrospectively flagged with a suspected speech sound disorder in kindergarten (per methods for retrospective characterization of speech sound production accuracy described below, with further details provided in Supplemental Material S1). As for potential language difficulties, six out of the 114 children demonstrated standard scores below 70 on the Sentence Comprehension subtest of the Clinical Evaluation of Language Fundamentals–Fourth Edition (CELF-4; Semel et al., 2003), but no children in the present sample demonstrated standard scores below 70 in receptive vocabulary (as indicated by the Peabody Picture Vocabulary Test–Fourth Edition [PPVT-4]; Dunn & Dunn, 2007). Informed consent was obtained by all participants, in which verbal assent was obtained from each child and written consent from each legal guardian, respectively. All experimental protocols and procedures were approved by the institutional review boards at Boston Children's Hospital and Massachusetts Institute of Technology.

Table 1.

Participant characteristics.

Variable Demographic details
Gender (boy, girls) n = 54 (47%), n = 60 (53%)
Nonverbal cognition x¯ = 99.6, σ = 9.49
min = 81, max = 131
Socioeconomic status x¯ = 49, σ = 11.5
min = 17, max = 66
Race/ethnicity Black or African American: n = 17 (15%)
Hispanic: n = 15 (13%)
White: n = 73 (63%)
Indicated more than one of the above: 10 (9%)
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Note. Socioeconomic status measured by the Barratt Simplified Measure of Social Status, in which the overall index reported presently is the sum of total education and total occupation, known as the Total Parent Education and Occupation Index, which ranges from 8 to 66.

Measures

Speech Sound Production Accuracy at the Start of Reading Instruction

Speech sound production accuracy at the start of formal reading instruction (prekindergarten/kindergarten) was retrospectively determined through audio-recorded connected speech samples that capture verbal responses during standardized assessments at the time of initial screening. Specifically, audio recordings of measures with the most consistent verbal output and phonetic variation were reviewed and transcribed using the Computer-Readable “Klattese” Transcription Equivalents to the International Phonetic Alphabet (IPA) by researchers with training in speech-language pathology and/or linguistics (Shriberg et al., 1997). Specifically, audio-recorded measures included the Sentence Repetition subtest from the Grammar and Phonology Screening (GAPS; Gardner et al., 2006) and words initially repeated during the Elision subtest from the Comprehensive Test of Phonological Processing (CTOPP; Wagner et al., 1999). Sentence and word-level contexts were taken together to compute percent consonants correct (PCC). These samples yielded several opportunities for production of consonants representative of the developmental sequence for speech sounds (56 “Early 8” speech sounds [/m, b, j, n, w, d, p, h/], 48 “Middle 8” speech sounds [/t, ŋ, k, g, f, v, tʃ, dʒ/], and 44 “Late 8” speech sounds [/ʃ, θ, s, z, ð, l, r, ʒ/]) in initial, medial, and final positions within words. Transcribed samples were then analyzed for phonetic accuracy using the PCC-R analysis.

The PCC-R is a standard approach for classification of speech sound production accuracy (for consonants) with this age range and population (Shriberg et al., 1997; Shriberg & Kwiatkowski, 1982) and has been used for retrospective characterization of production accuracy in recent studies (Preston et al., 2013). Specifically, production accuracy is determined by percentage of the number of correct consonants divided by the total number of correct and incorrect consonants produced within the speech sample (Shriberg & Kwiatkowski, 1982). Per PCC-R procedure, distortions (i.e., imprecise productions of speech sounds) were not counted as errors, and in addition, neither were productions characteristic of the New England regional dialect or those characteristic of African American English (in accordance with ASHA guidelines; American Speech-Language-Hearing Association, 1983, 1993). Interrater reliability was conducted between two raters with 15% of the sample to verify consistent identification across raters, and an intraclass correlation coefficient > .9 was achieved.

Reading Outcomes at the End of Second Grade

Multiple aspects of reading abilities were characterized at the final longitudinal time point at the end of second grade as follows: word reading and decoding (timed and untimed conditions for each construct), reading fluency, and reading comprehension. Specific measures were as follows:

Word-level reading (word reading and decoding). Two assessments were employed to characterize timed and untimed conditions for word reading and decoding. The Test of Word Reading Efficiency–Second Edition (TOWRE-2; Torgesen et al., 2012) measured (a) word reading, that is, the ability to read aloud single words and (b) decoding, the ability to read aloud pronounceable nonwords from lists as rapidly and accurately as possible within 45 s (timed conditions). Average reliability and test–retest coefficients for the TOWRE-2 exceed 0.90 (Torgesen et al., 2012). The Woodcock Reading Mastery Test–Revised (WRMT-R; Woodcock, 1998) required children to read aloud increasingly complex words (word reading) and pronounceable nonwords (decoding) at their own pace (untimed conditions). The WRMT-R has an average reliability coefficient of .97 (Woodcock, 1998). Composite scores were made by summing standardized timed and untimed word reading scores and standardized timed and untimed decoding scores and dividing the results by two, thus giving both tests equal weight in the composite scores.

Reading fluency and reading comprehension. Reading fluency, comprehension, and overall accuracy were characterized utilizing the Gray Oral Reading Test–Fifth Edition (GORT-5; Bryant & Wiederholt, 2011). This test consists of 16 possible reading passages, each of which five open-ended comprehension questions. Reading fluency was a combination of the child's accuracy (the number of words the child pronounced correctly when reading the passage) and the amount of time, in seconds, it took the child to read the story out loud and comprehension was characterized by the number of open-ended questions the child answered correctly. The GORT-5 has an average internal consistency reliability coefficient of .90 (Bryant & Wiederholt, 2011).

Potential Mediators

Building on closely related evidence to date, the following factors were evaluated as potential mediators: Core preliteracy skills were shown to be key predictors of word-level reading (phonological awareness, letter–name knowledge, RAN; Foulin, 2005; Melby-Lervåg et al., 2012; Pennington & Lefly, 2001; Snowling & Melby-Lervåg, 2016), phonological memory, and core language constructs (sentence comprehension and vocabulary knowledge; for comprehensive reviews, please see Adlof & Hogan, 2018; Hogan et al., 2014; Snowling & Melby-Lervåg, 2016). Specific protocols were established during administration and scoring to ensure that children were not penalized for articulation error patterns such that any potential speech sound disorders would not impact performance on these measures. Potential mediators of interest were all characterized at the first time point (start of kindergarten) as part of a larger battery of standardized assessments. Specific measures of interest were as follows:

Phonological awareness. A composite of phonological and phonemic awareness abilities was established from the Elision and Blending Words subtests of the CTOPP (Wagner et al., 1999). Elision measures the ability to omit one or more phonemes from a word. Blending Words require children to combine a string of individually presented speech sounds to form a word. The CTOPP has an average internal consistency coefficient between subtests above .80 (Wagner et al., 1999).

Phonological memory. The Nonword Repetition subtest from the CTOPP was used to measure phonological memory (Wagner et al., 1999), which measures a child's ability to repeat orally presented nonwords, word like in phonological form and pronunciation but containing no meaning.

RAN. For RAN, the Colors and Objects of the RAN/rapid alternating stimulus (RAS) tests were used (Wolf & Denckla, 2005). For each category, the child saw a picture with either a color or an object that he or she had to name accurately and as quickly as possible. All colors and objects shown on the pictures were familiar to the child. The mean of the Colors and Objects standard scores made up a RAN composite score. Test–retest reliability coefficients for RAN/RAS range from .84 to .92 (Wolf & Denckla, 2005).

Letter–name knowledge. Letter–name knowledge was characterized by the Letter Identification subtest from the WRMT-R. In this subtest, the child was asked to name letters of the alphabet in different fonts, such as bold and cursive and in uppercase and lowercase. The WRMT-R has an average reliability coefficient of .97 (Woodcock, 1998).

Sentence comprehension. Sentence comprehension was assessed with the Sentence Structure subtest of the CELF-4. During this task, children were asked to select which of four pictures best represented the sentence read by the researcher. The average Cronbach's alpha of subtests of the CELF-4 is .80 (Semel et al., 2003).

Receptive vocabulary. Receptive vocabulary was measured using the PPVT-4 (Dunn & Dunn, 2007). The child was asked to choose which of four pictures best depicted the word said by the researcher. The PPVT-4 has a split-half internal consistency reliability coefficient of .94 (Dunn & Dunn, 2007).

Sample Characteristics

Nonverbal cognitive abilities. Nonverbal cognitive abilities to characterize the sample were measured using the subtest Matrices of the KBIT-2 (Kaufman & Kaufman, 2004). During this test, the child was asked to decide which of a series of pictures presented to them completes a pattern. Split-half reliability coefficients for the KBIT-2 range from .80 to .90, and test–retest coefficients range from .88 to .93 (Kaufman & Kaufman, 2004).

Socioeconomic status. Socioeconomic status (SES) was characterized by parent report utilizing the Barratt Simplified Measure of Social Status (BSMSS; Barratt, 2006). This questionnaire documents mother and father education levels and derives the average to provide a total education index (reported based on seven levels, resulting in a score from 3 to 21). Occupation is also then documented by parent and in total (reported based on nine levels, resulting in a score from 5 to 45). The sum of total education and total occupation is utilized to determine the Total Parent Education and Occupation Index (which ranges from 8 to 66).

Data Analysis

All analyses were performed in R (R Core Team, 2022). In a first step, outlier analysis revealed a limited number of outliers (seven outliers across all variables of interest), defined by values 3 times the standard deviation above or below the mean of each variable (Dixon, 1960). To preserve sample size and sample characteristics, outliers were addressed by winsorizing, replacing outlier values with those precisely 3 times the standard deviation above or below the mean for each variable (Dixon, 1960). Next, to assess possible collinearity between variables of interest, variance inflation factor (VIF) analyses were employed. Resultant VIF values ranged from 1.26 to 1.85 between all variables of interest, suggesting no presence of collinearity among these variables (Vittinghoff et al., 2012).

Mediation analyses were conducted to investigate mediating variables on the relation between early speech sound production abilities and later reading outcome using the mediation package in R (Tingley et al., 2014). Mediation analyses were conducted on the whole sample following the approach outlined by MacKinnon (2008; see also MacKinnon et al., 2002). First, a regression was performed to assess the relation of speech production abilities on each of the four reading outcome variables (word reading, decoding, reading fluency, and reading comprehension [Path c]). Then, the effect of speech on each of the mediators was assessed (Path a), after which the effect of each independent mediator on the reading outcome measures was assessed (Path b). Last, a regression was conducted to assess the effects of both the mediator and speech simultaneously (Path c'). Speech as an independent variable was centered around its mean to make for an interpretable intercept in the mediation analyses for each outcome variable and potential mediator evaluated. The residuals of the regression models were all normally distributed.

A mediation effect was indicated when bootstrapping analysis with 1,000 iterations, using the mediation package in R (Tingley et al., 2014), showed a significant decrease of the influence of speech on reading following the addition of a mediator in the model. This procedure was implemented to assess each mediator individually. Bonferroni corrections were then employed to adjust for multiple comparisons for multiple mediators (Abdi, 2007). As mediation analysis as it was conducted here cannot deal with missing values, a new data frame per reading variable was created in which the rows containing missing data were deleted.

Results

Initial Associations Between Early Speech Sound Production Accuracy and Reading Outcomes

An overview of the means and standard deviations of the sample for all measures of interest is provided in Table 2. Note that the majority of children in the present sample demonstrated typical reading outcomes. For a full summary of distribution of variables split by speech-status, see Supplemental Material S1.

Table 2.

Descriptive overview of measures of interest.

Measures of interest M SD Range
Percentage consonant correct (PCC-R) 91.20 6.81 70.4–100
Phonological awareness 98.19 9.69 80–128
Phonological memory 9.04 2.58 4–17
Rapid automatized naming 97.61 13.05 68.3–122.3
Letter–name knowledge 103.60 10.42 78–124.5
Nonverbal cognitive abilities 99.60 9.49 81–131
Sentence comprehension 11.62 0.93 1–23
Receptive vocabulary 115.58 13.41 81–160
Socioeconomic status 48.96 11.15 17–66
Word reading 103.59 14.28 40–128.5
Decoding 98.06 15.38 40–129.5
Reading fluency* 10.02 2.49 2–15
Reading comprehension* 9.69 2.15 2–16
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*

N = 111 for these measures due to time constraints at longitudinal follow-up.

Following Bonferroni correction for multiple comparisons, Spearman correlation analyses with the whole sample revealed significant associations between early speech sound production accuracy and decoding (r = .27, p < .01), word reading (r = .33, p < .01), reading fluency (r = .35, p < .01), and reading comprehension (r = .35, p < .01). Significant associations between speech sound production and potential mediating factors were observed for phonological awareness (r = .38, p < .05), letter–name knowledge (r = .38, p < .05), sentence comprehension (r = .32, p < .05), and receptive vocabulary (r = .35, p < .01), with no significant effects indicated for RAN nor nonverbal cognitive abilities. Furthermore, reading outcome measures were highly correlated with one another, with correlation coefficients ranging from r = .48 (p < .001) to r = .82 (p < .001). A correlation matrix summarizing these effects is provided in Table 3. Asterisks indicate the corresponding p values (for a full summary of distribution for all variables of interest; see Supplemental Material S1).

Table 3.

Intercorrelations between variables.

Key measures of interest 1. 2 3 4 5 6 7 8 9 10 11 12 13
1. PCC-R 1
2. Phonological awareness .38*** 1
3. Phonological memory .21* .37*** 1
4. RAN .27** .32** .59*** 1
5. Letter–name knowledge .38*** .62*** .49*** .37*** 1
6. Nonverbal cognitive abilities .23* .18 .14 .22* .21* 1
7. Sentence comprehension .33** .33** .33** .17 .34** .25* 1
8. Receptive vocabulary .35** .39*** .34** .22* .38*** .30* .56*** 1
9. SES .36** .40*** .20 .08 .35*** .15 .21* .35** 1
10.Word reading .33** .46*** .22* .36** .44*** .16 .28* .30* .29* 1
11. Decoding .27** .32* .21* .30* .30* .14 .17 .18 .29* .84*** 1
12. Reading fluency .35** .41** .38** .43*** .41*** .14 .25* .28* .29* .84*** .75*** 1
13. Reading comprehension .35** .44*** .34** .32** .49*** .21* .29* .47*** .38** .64*** .58*** .72*** 1
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Note. PCC-R = Percent Consonants Correct–Revised; RAN = rapid automatized naming; SES = socioeconomic status.

*

p ≤ .05.

**

p ≤ .01.

***

p ≤ .001.

Mediation Analyses

Mediation analyses were conducted with the whole sample for each of the four reading constructs. Analyses were conducted for word-level and reading fluency and comprehension outcomes, as follows.

Word-Level Reading

Word reading. Although the initial relation between speech sound production accuracy and word reading was significant, b = .50, F(1, 112) = 6.64, p < .05, significant mediation effects were observed for phonological awareness (ACME = .25, 95% CI [.12, .42], proportion mediated = .54, p < .001) and letter–name knowledge (ACME = .33; 95% CI [.13, .58], proportion mediated = .66, p < .001). Bootstrapping analyses with 1,000 iterations confirmed this mediation effect.

Both mediators significantly contributed to word reading, phonological awareness: b = .46, F(1, 108) = 13.87, p < .001; letter–name knowledge: b = .60, F(1, 112) = 26.87, p < .001. No mediation effects were observed for phonological memory, RAN, sentence comprehension, or receptive vocabulary.

Decoding. Early speech sound production accuracy initially did significantly contribute to the prediction of subsequent decoding abilities, b = .42, F(1, 112) = 4.00, p < .05. A significant mediation effect was however observed for phonological awareness (ACME = .25, 95% CI [.09, .44], p < .001). Bootstrapping analyses with 1,000 iterations confirmed this mediation effect. Phonological awareness significantly contributed to decoding, phonological awareness: b = .44, F(1, 108) = 10.61, p < .001. No mediation effects were observed for phonological memory, letter–name knowledge, RAN, sentence comprehension, or receptive vocabulary. For an overview of the results of the mediation analyses for word-level reading, see Figure 1.

Figure 1.

2 block diagrams. The first block diagram illustrates the parameters relating to speech sound production accuracy and word reading. The block on the left is labeled Speech sound production accuracy. The block on the right is labeled Word reading. The block at the top center is labeled Phonological Awareness. The block at the bottom center is labeled Letter name knowledge. An arrow from the Speech sound production accuracy block to the word reading block is marked b = 0.50. Another arrow from the Speech sound production accuracy block to the Phonological awareness block is marked b = 0.60, 3 asterisks. A third arrow from the Speech sound production accuracy block to the Letter name knowledge block is marked b = 0.58, 3 asterisks. An arrow from the Phonological awareness block to the Word reading block is marked b = 0.46, 3 asterisks. An arrow from the Letter name knowledge block to the Word reading block is marked b = 0.60, 3 asterisks. The second block diagram illustrates the parameters relating the Speech sound production accuracy to Decoding. The block on the left is labeled Speech sound production accuracy. The block on the right is labeled Decoding. The block at the top center is labeled Phonological Awareness. The block at the bottom center is labeled Letter name knowledge. An arrow from the Speech sound production accuracy block to the Decoding block is marked b = 0.42. Another arrow from the Speech sound production accuracy block to the Phonological awareness block is marked b = 0.60, 3 asterisks. A third arrow from the Speech sound production accuracy block to the Letter name knowledge block is marked b = 0.58, 3 asterisks. An arrow from the Phonological awareness block to the Decoding block is marked b = 0.44, 3 asterisks. An arrow from the Letter name knowledge block to the Decoding block is marked b = 0.48, 3 asterisks.

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Factors that mediate the relation between early speech sound production accuracy and subsequent word-level reading. *p < 0.05. **p ≤ .01.***p ≤ .001.

Reading Fluency and Comprehension

Mediation analyses were separately conducted for reading fluency and reading comprehension (as indicated by standardized performance on the GORT-5). In a first step, early speech sound production accuracy was found to significantly contribute to the prediction of both subsequent reading fluency, b = .13, F(1, 109) = 15.09, p < .01, and reading comprehension, b = .11, F(1, 108) = 15.11, p < .01, abilities. For reading fluency, this relation with early speech sound production accuracy was found to be mediated by phonological awareness (ACME = .05, 95% CI [.02, .08], proportion mediated = .36, p < .001) and letter–name knowledge (ACME = .04, 95% CI [.01, .09], proportion mediated = .34, p < .001). Phonological awareness contributed significantly to the prediction of reading fluency outcomes, b = .10, F(1, 105) = 20.71, p < .001, as did letter-name knowledge, b = .10, F(1, 109) = 22.17, p < .001. Bootstrapping analyses with 1,000 iterations confirmed this mediation effect. No mediation effects were observed for phonological memory, RAN, sentence comprehension, or receptive vocabulary.

As for reading comprehension, the relation between early speech sound production abilities and subsequent reading comprehension was found to be mediated by phonological awareness (ACME = .04, 95% CI [.02, .08], proportion mediated = .28, p < .001), letter–name knowledge (ACME = .05, 95% CI [.02, .08], proportion mediated = .44, p < .001), and receptive vocabulary (ACME = .04, 95% CI [.01, .08], proportion mediated = .37, p < .001. These effects were confirmed using bootstrapping analysis with 1,000 iterations. Each mediator was found to be significantly associated with reading comprehension, phonological awareness, b = .09, F(104) = 17.15, p < .001; letter–name knowledge, b = .10, F(1, 108) = 35.11, p < .001; receptive vocabulary, b = .08, F(1, 108) = 30.76, p < .001. No mediation effects were observed for phonological memory, RAN, or sentence comprehension. For an overview of the results of the mediation analyses for reading fluency and comprehension, see Figure 2.

Figure 2.

2 block diagrams. The first block diagram illustrates the parameters relating Speech sound production accuracy to Reading fluency. The block on the left is labeled Speech sound production accuracy. The block on the right is labeled Reading Fluency. The block at the top center is labeled Phonological Awareness. An arrow from the Speech sound production accuracy block to the Reading accuracy block is marked b = 0.13, 2 asterisks. Another arrow from the Speech sound production accuracy block to the Phonological awareness block is marked b = 0.60, 2 asterisks. An arrow from the Phonological awareness block to the Reading fluency block is marked b = 0.10, 3 asterisks. The second block diagram illustrates the parameters relating Speech sound production accuracy to Reading comprehension. The block on the left is labeled Speech sound production accuracy. The block on the right is labeled Reading Comprehension. The 3 blocks in the middle are labeled Phonological awareness, Letter name knowledge, and Receptive vocabulary. An arrow from the Speech sound production accuracy block to the Reading comprehension block is marked b = 0.11, 2 asterisks. A second arrow from the Speech sound production accuracy block to the Phonological awareness block is marked b = 0.60, 3 asterisks. A third arrow from the Speech sound production accuracy block to the Letter name knowledge block is marked b = 0.58, 2 asterisks. A fourth arrow from the Speech sound production accuracy block to the Receptive vocabulary block is marked b = 0.68, 3 asterisks. An arrow from the Phonological awareness block to the Reading comprehension block is marked b = 0.09, 3 asterisks. An arrow from the Letter name knowledge block to the Reading comprehension block is marked b = 0.10, 3 asterisks. An arrow from the Receptive vocabulary block to the Reading comprehension block is marked b = 0.08, 3 asterisks.

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Factors that mediate the relation between early speech sound production accuracy and subsequent reading fluency and comprehension. *p ≤ .01. **p ≤ .001.

Discussion

In an effort to clarify how speech production accuracy in early childhood may impact reading development, the present investigation focused on the extent to which early speech sound production, retrospectively characterized by consonant production accuracy in simple sentence repetition contexts, uniquely contributes to subsequent reading outcomes. Simple regression analyses established initial significant associations between speech sound production accuracy and subsequent word reading, decoding, reading fluency, and comprehension. For word-level measures, mediation analyses implicated phonological awareness and letter–name knowledge as mediators in the relation between early speech sound production abilities and word reading and decoding. For sentence-level measures, phonological awareness and letter–name knowledge mediated the relationship between early speech sound production abilities and reading fluency, and phonological awareness, letter–name knowledge, and receptive vocabulary were identified as mediators in the relation between speech sound production and reading comprehension.

Overall, these results align with previous work (Overby et al., 2012) in illuminating the mediating role of phonological awareness in the context of reading abilities. Furthermore, our results extend beyond previous research in specifying the respective roles of additional factors in contributing to the prediction of multifaceted reading outcomes at the end of second grade. These results indicate that although children with speech sound disorders may have an enhanced likelihood of developing reading difficulties as per previous findings (e.g., Anthony et al., 2011; Peterson et al., 2009; Puranik et al., 2008; Raitano et al., 2004; Rvachew, 2007), speech production abilities in itself are not the only determining factor in shaping later reading outcomes.

The Role of Core Preliteracy Skills in Mediating the Relation Between Speech Sound Production and Reading

Phonological (and phonemic) awareness has previously been shown to mediate the relation between early speech sound production abilities and subsequent word reading abilities (Overby et al., 2012). However, this relation has only previously been investigated in the context of word reading skills and, further, did not account for additional possible mediating factors (Overby et al., 2012). The present findings align with those of Overby et al. (2012) in that the mediating role of phonological awareness was identified in the context of the relation between early speech sound production and subsequent word reading and extend beyond in identifying phonological awareness as a mediator in relation to decoding, fluency, and comprehension as well.

Our results suggest that phonological awareness is the predominant link between speech sound production abilities and reading outcome as phonological awareness was the only mediator that was significant in all of the investigated reading outcomes. This implies that children that show early speech sound production deficiencies, or speech sounds disorders, may be at risk for deficiencies in phonological awareness, which in turn may negatively impact their reading development across different facets of reading.

Moreover, the incorporation of additional potential key mediators, namely, letter–name knowledge and RAN, offer a crucial next step to further specify the nature of the relation between speech sound production accuracy and subsequent reading outcomes. RAN did not show any mediating effects for associations between speech accuracy and any reading outcomes. Thus, although RAN is known to be an important predictor of word reading and fluency outcomes (e.g., Schatschneider et al., 2004; Snowling & Melby-Lervåg, 2016; Wolff, 2014), the role that RAN contributes to literacy acquisition seems to be independent of possible contributions of speech sound production abilities.

Letter–name knowledge as a mediator underlying the relation between speech sound production and word reading, fluency, and comprehension outcomes is a novel contribution of this study to further suggest significant links between the production of speech sounds and letters, particularly at the onset of learning to read. The robust role of letter–name knowledge as an explanatory mediator for word reading, fluency, and comprehension in the current findings aligns with prior research implicating letter–name knowledge as an important kindergarten-age predictor of early emerging reading outcomes (Catts et al., 2001; Foulin, 2005; McBride-Chang, 1999).

Although reduced letter–name knowledge has been indicated among children with speech sound disorders when compared with typical peers (Bird et al., 1995; Scarborough, 1990), this effect has not been observed across studies, suggesting that letter–name knowledge likely does not solely explain literacy risk status for children with speech sound disorders (Anthony et al., 2011; Benway et al., 2021; Rvachew et al., 2003).

Relatedly, letter–name knowledge as a mediator for the relation between speech sound production and word reading may be, at least partly, explained by the role of orthographic facilitation, in which more accurate production of a spoken word is observed when the corresponding written word is simultaneously presented during spoken word learning (Ehri & Wilce, 1979). Typically developing children and even children with dyslexia have been shown to benefit from orthographic facilitation during word learning (Baron et al., 2018; Ricketts et al., 2009; Rosenthal & Ehri, 2008), which suggests that orthographic facilitation is another factor that may contribute to/underlie reported links between speech sound production, letter–name knowledge, and ultimate word reading outcomes. Some children with (persistent) speech sound production errors may even benefit from such an approach when learning speech sounds (i.e., to simultaneously present the corresponding letter), as is shown in a recent paper by Jevtović et al. (2022). However, additional research is needed to uncover the potential role of orthographic facilitation in the context of associations between speech sound production accuracy and reading.

The present findings support the notion that letter–name knowledge is a key contributing factor that accounts for unique variance in the context of the relation between speech and subsequent reading abilities and illuminate the importance of accounting for additional contributing factors beyond phonological awareness when investigating links between speech sound production abilities and reading.

The Role of Early Language Skills in Shaping Reading Comprehension

Extant findings have outlined the importance of early language skills, especially vocabulary knowledge, grammar use, and oral comprehension for reading comprehension (e.g., Hemphill & Tivnan, 2008; Petscher et al., 2018; Thompson et al., 2015). However, mixed findings prevail regarding the role of early language skills in the context of the relation between early speech sound production and subsequent reading skills. Although some studies have linked early language skills with difficulties in decoding and reading comprehension among children with speech sound disorders (e.g., Lewis et al., 2000; Peterson et al., 2009), others, examining specifically vocabulary knowledge, found no such effect (Overby et al., 2012). In this study, vocabulary knowledge was specifically linked with subsequent reading comprehension, such that kindergarten-age vocabulary knowledge together with phonological awareness and letter–name knowledge mediated the relation between speech sound production and later reading comprehension abilities.

The present findings align with steady evidence in support of the theory that successful reading comprehension is achieved through the integration of our ability to comprehend and decode written text (Gough & Tunmer, 1986). In line with previous evidence illuminating the importance of language abilities for successful reading comprehension (e.g., Catts et al., 2006; Lervåg et al., 2018; Muter et al., 2004), present findings further affirm the independent contribution of early language abilities, specifically vocabulary knowledge, in shaping subsequent reading comprehension abilities, although future research is necessary to examine the predictive contributions of additional language components in this context (i.e., listening comprehension).

Considerations and Limitations

The present findings are to be interpreted in the context of several considerations. Firstly, speech sound production accuracy has been measured via retrospective analysis of PCC in simple word and sentence repetition contexts. Future work is needed to examine the respective contributions of more varying and complex speech production contexts in relation to contributing factors and subsequent reading outcomes. In addition, the present battery, unfortunately, did not include a receptive measure of phonological awareness (i.e., the child is presented with three pictures of objects, the examiner aurally presents each word with the pictures and asks the child which two words start with the same first sound, e.g., map, mat, and pan). Therefore, present findings implicating phonological awareness must be interpreted in the context of expressive measures. However, these measures did not discredit children for speech sound production errors, as noted in methods. Second, the present longitudinal sample reflects an oversampling of children at risk for dyslexia following initial screening in kindergarten. Thus, it is possible that the variation in speech sound production accuracy observed may be at least partly attributed to oversampling of dyslexia risk. High prevalence rates of speech sound disorders in kindergarten have been observed among children with subsequent reading difficulties (e.g., Tambyraja et al., 2020). However, the majority of children (n = 85 out of 114) in the present sample demonstrated typical reading outcomes at longitudinal follow-up. Therefore, these findings reflect associations in a sample of children with primarily typical reading outcomes, calling into question how these associations may present in the context of a wider range of reading outcomes, particularly among those with subsequent reading difficulties. Future work is also warranted to address how these associations manifest specifically among children with speech sound disorders, as well as those with primary language difficulties, that is, developmental language disorder. In this context, fine-grained assessment of speech errors and error patterns (e.g., articulation vs. phonological errors) is needed to determine whether the relation between speech sound production and subsequent reading outcomes may differ based on severity level and/or profiles of error patterns. Lastly, given the longitudinal design of this study, it is important to acknowledge that selective attrition may be an additional factor impacting the sample presently investigated. This is to be noted particularly with respect to potential bias in studying families who were willing and able to enroll their children in a longitudinal study. That said, the present sample reflects a diverse representation with respect to socioeconomic variation, race, and ethnicity (as outlined in Table 1).

Conclusions

The present investigation sought to clarify the relation between speech sound production accuracy in kindergarten and subsequent reading outcomes at the end of second grade through a comprehensive battery of reading measures while accounting for key contributing factors, including phonological awareness, letter–name knowledge, and early oral language abilities. In this context, the relation between speech sound production accuracy and subsequent word reading abilities was observed to be mediated by preliteracy skills (i.e., phonological awareness and letter–name knowledge), in line with previous work (Overby et al., 2012). Extending beyond previous literature, we showed that preliteracy skills not only mediate the relation between speech sound production and word reading abilities but also decoding skills as well as reading fluency and comprehension. The inclusion of key preliteracy factors in the context of examining associations between speech and various reading constructs, specifically word reading, decoding, reading fluency, and comprehension has further clarified the specific role of early speech sound production abilities in contributing to the prediction of subsequent reading outcomes. Although the present investigation provides further insight into the complexities of these associations, findings also uncover the path for much needed future work to extend beyond the present retrospective approach. Future work should include prospective investigations with detailed assessment of speech production abilities to delineate motor versus articulation-based speech sound deficits. In-depth error analyses should be focused on children with speech sound disorders in the context of the multifactorial approach to reading development to provide a more detailed description of speech sound production accuracy.

Ultimately, incorporation of multiple facets of reading and contributing factors led to specification of speech sound production accuracy in kindergarten as a factor that is highly correlated with key preliteracy skills yet does not explain unique variance in reading outcomes. Nonetheless, the substantial body of work indicating contributions of speech production to reading development and heightened rates of reading difficulty among children with speech sound disorders suggest that it is important to closely monitor emerging literacy abilities among children with speech sound disorders and account for speech sound production abilities when screening children for risk of reading difficulties. Taken together, the present findings further support the view of reading development as a complex and multifaceted process that is dependent on multiple factors and their interactions (Case et al., 2010; Pennington, 2006; van Bergen et al., 2014; van Otterloo & van der Leij, 2009), illuminating multiple mediators beyond solely phonological awareness that contribute to multifaceted associations between speech sound production and reading abilities.

Data Availability Statement

The data sets generated during and/or analyzed during this study are available from the senior author, Nadine Gaab, on reasonable request.

Supplementary Material

Supplemental Material S1. Supplemental information.
Click here for additional data file. (354KB, pdf)

Acknowledgments

This research was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01 HD067312). Funding was also provided for Jennifer Zuk by the National Institutes of Health National Research Service Award (F31 DC015919-01) and the American Speech-Language-Hearing Foundation. We thank Willa van Dijk for statistical consultation and assistance. We are especially thankful to all participating families for their long-term dedication to this study and school coordinators and principals who made screening possible. We thank all additional members of the READ team who contributed to data collection and initial processing, especially Ola Ozernov-Palchik, Sara Beach, Bryce Becker, Abigail Cyr, and Kelly Halverson. Marjolein Mues and Jennifer Zuk contributed equally to this work.

Funding Statement

This research was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01 HD067312). Funding was also provided for Jennifer Zuk by the National Institutes of Health National Research Service Award (F31 DC015919-01) and the American Speech-Language-Hearing Foundation.

References

  1. Abdi, H. (2007). Bonferroni and Šidák corrections for multiple comparisons. [Google Scholar]
  2. Adlof, S. M. , & Hogan, T. P. (2018). Understanding dyslexia in the context of developmental language disorders. Language, Speech, and Hearing Services in Schools, 49(4), 762–773. 10.1044/2018_LSHSS-DYSLC-18-0049 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. American Speech-Language-Hearing Association. (1983). Position paper: Social dialects and implications of the position on social dialects. Asha, 25(9), 23–27. [Google Scholar]
  4. American Speech-Language-Hearing Association. (1993). Definitions of communication disorders and variations. https://www.asha.org/policy/rp1993-00208/
  5. Anthony, J. L. , Aghara, R. G. , Dunkelberger, M. J. , Anthony, T. I. , Williams, J. M. , & Zhang, Z. (2011). What factors place children with speech sound disorders at risk for reading problems? American Journal of Speech-Language Pathology, 20(2), 146–160. 10.1044/1058-0360(2011/10-0053) [DOI] [PubMed] [Google Scholar]
  6. Apel, K. , & Lawrence, J. (2011). Contributions of morphological awareness skills to word-level reading and spelling in first-grade children with and without speech sound disorder. Journal of Speech, Language, and Hearing Research, 54(5), 1312–1327. 10.1044/1092-4388(2011/10-0115) [DOI] [PubMed] [Google Scholar]
  7. Arnold, E. M. , Goldston, D. B. , Walsh, A. K. , Reboussin, B. A. , Daniel, S. S. , Hickman, E. , & Wood, F. B. (2005). Severity of emotional and behavioral problems among poor and typical readers. Journal of Abnormal Child Psychology, 33(2), 205–217. 10.1007/s10802-005-1828-9 [DOI] [PubMed] [Google Scholar]
  8. Baron, L. S. , Hogan, T. P. , Alt, M. , Gray, S. , Cabbage, K. L. , Green, S. , & Cowan, N. (2018). Children with dyslexia benefit from orthographic facilitation during spoken word learning. Journal of Speech, Language, and Hearing Research, 61(8), 2002–2014. 10.1044/2018_jslhr-l-17-0336 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Barratt, W. (2006). The Barratt Simplified Measure of Social Status (BSMSS): Measuring SES [Unpublished manuscript] . Indiana State University. [Google Scholar]
  10. Benway, N. R. , Garcia, K. , Hitchcock, E. , McAllister, T. , Leece, M. C. , Wang, Q. , & Preston, J. L. (2021). Associations between speech perception, vocabulary, and phonological awareness skill in school-aged children with speech sound disorders. Journal of Speech, Language, and Hearing Research, 64(2), 452–463. 10.1044/2020_jslhr-20-00356 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Bird, J. , Bishop, D. V. M. , & Freeman, N. H. (1995). Phonological awareness and literacy development in children with expressive phonological impairments. Journal of Speech and Hearing Research, 38(2), 446–462. 10.1044/jshr.3802.446 [DOI] [PubMed] [Google Scholar]
  12. Blachman, B. A. (1984). Relationship of rapid naming ability and language analysis skills to kindergarten and first-grade reading achievement. Journal of Educational Psychology, 76(4), 610–622. 10.1037/0022-0663.76.4.610 [DOI] [Google Scholar]
  13. Bowey, J. A. (2005). Predicting individual differences in learning to read. In M. J. Snowling & C. Hulme (Eds.), The science of reading: A handbook (pp. 155–172). Blackwell Publishing. 10.1002/9780470757642.ch9 [DOI] [Google Scholar]
  14. Bryant, B. R. , & Wiederholt, J. L. (2011). Gray Oral Reading Tests (GORT-5)–Fifth Edition. Pro-Ed. [Google Scholar]
  15. Burnham, D. (2003). Language specific speech perception and the onset of reading. Reading and Writing, 16, 573–609. 10.1023/A:1025593911070 [DOI] [Google Scholar]
  16. Byrd, C. T. (2018). Assessing bilingual children: Are their disfluencies indicative of stuttering or the by-product of navigating two languages? Seminars in Speech and Language, 39(4), 324–332. 10.1055/s-0038-1667161 [DOI] [PubMed] [Google Scholar]
  17. Cabbage, K. L. , Farquharson, K. , Iuzzini-Seigel, J. , Zuk, J. , & Hogan, T. P. (2018). Exploring the overlap between dyslexia and speech sound production deficits. Language, Speech, and Hearing Services in Schools, 49(4), 774–786. 10.1044/2018_LSHSS-DYSLC-18-0008 [DOI] [PubMed] [Google Scholar]
  18. Caravolas, M. , Lervåg, A. , Mousikou, P. , Efrim, C. , Litavsky, M. , Onochie-Quintanilla, E. , Salas, N. , Schöffelová, M. , Defior, S. , Mikulajová, M. , Seidlová-Málková, G. , & Hulme, C. (2012). Common patterns of prediction of literacy development in different alphabetic orthographies. Psychological Science, 23(6), 678–686. 10.1177/0956797611434536 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Cardoso-Martins, C. , & Pennington, B. F. (2004). The relationship between phoneme awareness and rapid serial naming skills and literacy acquisition: The role of developmental period and reading ability. Scientific Studies of Reading, 8(1), 27–52. 10.1207/s1532799xssr0801_3 [DOI] [Google Scholar]
  20. Carroll, J. M. , & Snowling, M. J. (2004). Language and phonological skills in children at high risk of reading difficulties. The Journal of Child Psychology and Psychiatry, 45(3), 631–640. 10.1111/j.1469-7610.2004.00252.x [DOI] [PubMed] [Google Scholar]
  21. Case, L. P. , Speece, D. L. , Silverman, R. , Ritchey, K. D. , Schatschneider, C. , Cooper, D. H. , Montanaro, E. , & Jacobs, D. (2010). Validation of a supplemental reading intervention for first-grade children. Journal of Learning Disabilities, 43(5), 402–417. 10.1177/0022219409355475 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Catts, H. W. (1993). The relationship between speech-language impairments and reading disabilities. Journal of Speech and Hearing Research, 36(5), 948–958. 10.1044/jshr.3605.948 [DOI] [PubMed] [Google Scholar]
  23. Catts, H. W. , Adlof, S. M. , & Ellis Weismer, S. (2006). Language deficits in poor comprehenders: A case for the simple view of reading. Journal of Speech, Language, and Hearing Research, 49(2), 278–293. 10.1044/1092-4388(2006/023) [DOI] [PubMed] [Google Scholar]
  24. Catts, H. W. , Fey, M. E. , Zhang, X. , & Tomblin, J. B. (2001). Estimating the risk of future reading difficulties in kindergarten children: A research-based model and its clinical implementation. Language, Speech, and Hearing Services in Schools, 32(1), 38–50. 10.1044/0161-1461(2001/004) [DOI] [PubMed] [Google Scholar]
  25. Catts, H. W. , & Petscher, Y. (2022). A cumulative risk and resilience model of dyslexia. Journal of Learning Disabilities, 55(3), 171–184. 10.1177/00222194211037062 [DOI] [PubMed] [Google Scholar]
  26. Centanni, T. M. , Norton, E. S. , Park, A. , Beach, S. D. , Halverson, K. , Ozernov-Palchik, O. , Gaab, N. , & Gabrieli, J. D. (2018). Early development of letter specialization in left fusiform is associated with better word reading and smaller fusiform face area. Developmental Science, 21(5), e12658. 10.1111/desc.12658 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Compton, D. L. (2003). Modeling the relationship between growth in rapid naming speed and growth in decoding skill in first-grade children. Journal of Educational Psychology, 95(2), 225–239. 10.1037/0022-0663.95.2.225 [DOI] [Google Scholar]
  28. de Jong, P. F. , Seveke, M. J. , & van Veen, M. (2000). Phonological sensitivity and the acquisition of new words in children. Journal of Experimental Child Psychology, 76(4), 275–301. 10.1006/jecp.1999.2549 [DOI] [PubMed] [Google Scholar]
  29. de Jong, P. F. , & van der Leij, A. (1999). Specific contributions of phonological abilities to early reading acquisition: Results from a Dutch latent variable longitudinal study. Journal of Educational Psychology, 91(3), 450–476. 10.1037/0022-0663.91.3.450 [DOI] [Google Scholar]
  30. Dixon, W. J. (1960). Simplified estimation from censored normal samples. The Annals of Mathematical Statistics, 31(2), 385–391. 10.1214/aoms/1177705900 [DOI] [Google Scholar]
  31. Dunn, L. M. , & Dunn, D. M. (2007). PPVT-4: Peabody Picture Vocabulary Test. Pearson Assessments. [Google Scholar]
  32. Durand, V. , Loe, I. , Yeatman, J. , & Feldman, H. (2013). Effects of early language, speech, and cognition on later reading: A mediation analysis. Frontiers in Psychology, 4, 586. 10.3389/fpsyg.2013.00586 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Ehri, L. C. , & Wilce, L. S. (1979). The mnemonic value of orthography among beginning readers. American Psychological Association. 10.1037/0022-0663.71.1.26 [DOI] [Google Scholar]
  34. Farquharson, K. , Hogan, T. P. , Hoffman, L. , Wang, J. , Green, K. F. , & Green, J. R. (2018). A longitudinal study of infants' early speech production and later letter identification. PLOS ONE, 13(10), Article e0204006. 10.1371/journal.pone.0204006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Fielding-Barnsley, R. , & Purdie, N. (2003). Early intervention in the home for children at risk of reading failure. Support for Learning, 18(2), 77–82. 10.1111/1467-9604.00284 [DOI] [Google Scholar]
  36. Foulin, N. (2005). Why is letter-name knowledge such a good predictor of learning to read? Reading and Writing, 18(2), 129–155. 10.1007/s11145-004-5892-2 [DOI] [Google Scholar]
  37. Gallagher, A. , Frith, U. , & Snowling, M. J. (2000). Precursors of literacy delay among children at genetic risk of dyslexia. The Journal of Child Psychology and Psychiatry, 41(2), 203–213. 10.1017/S0021963099005284 [DOI] [PubMed] [Google Scholar]
  38. Gardner, H. , Froud, K. , McClelland, A. , & van der Lely, H. K. J. (2006). Development of the Grammar and Phonology Screening (GAPS) test to assess key markers of specific language and literacy difficulties in young children. International Journal of Language & Communication Disorders, 41(5), 513–540. 10.1080/13682820500442644 [DOI] [PubMed] [Google Scholar]
  39. Gough, P. B. , & Tunmer, W. E. (1986). Decoding, reading, and reading disability. Remedial and Special Education, 7(1), 6–10. 10.1177/074193258600700104 [DOI] [Google Scholar]
  40. Guthrie, J. T. , & Wigfield, A. (2000). Engagement and motivation in reading. In M. L. Kamil, P. B. Mosenthal, P. D. Pearson, & R. Barr (Eds.), Handbook of reading research (Vol. III, pp. 403–422). Erlbaum. [Google Scholar]
  41. Hayiou-Thomas, M. E. , Carroll, J. M. , Leavett, R. , Hulme, C. , & Snowling, M. J. (2017). When does speech sound disorder matter for literacy? The role of disordered speech errors, co-occurring language impairment and family risk of dyslexia. The Journal of Child Psychology and Psychiatry, 58(2), 197–205. 10.1111/jcpp.12648 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Hemphill, L. , & Tivnan, T. (2008). The importance of early vocabulary for literacy achievement in high-poverty schools. Journal of Education for Students Placed at Risk, 13(4), 426–451. 10.1080/10824660802427710 [DOI] [Google Scholar]
  43. Hesketh, A. (2004). Early literacy achievement of children with a history of speech problems. International Journal of Language & Communication Disorders, 39(4), 453–468. 10.1080/13682820410001686013 [DOI] [PubMed] [Google Scholar]
  44. Hogan, T. P. , Adlof, S. M. , & Alonzo, C. N. (2014). On the importance of listening comprehension. International Journal of Speech-Language Pathology, 16(3), 199–207. 10.3109/17549507.2014.904441 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Hogan, T. P. , Catts, H. W. , & Little, T. D. (2005). The relationship between phonological awareness and reading: Implications for the assessment of phonological awareness. Language, Speech, and Hearing Services in Schools, 36(4), 285–293. 10.1044/0161-1461(2005/029) [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Huettig, F. , Lachmann, T. , Reis, A. , & Petersson, K. M. (2018). Distinguishing cause from effect—Many deficits associated with developmental dyslexia may be a consequence of reduced and suboptimal reading experience. Language, Cognition and Neuroscience, 33(3), 333–350. 10.1080/23273798.2017.1348528 [DOI] [Google Scholar]
  47. Jevtović, M. , Stoehr, A. , Klimovich-Gray, A. , Antzaka, A. , & Martin, C. D. (2022). One-to-one or one too many? Linking sound-to-letter mappings to speech sound perception and production in early readers. Journal of Speech, Language, and Hearing Research, 65(12), 4507–4519. 10.1044/2022_JSLHR-22-00131 [DOI] [PubMed] [Google Scholar]
  48. Jin, F. , Schjølberg, S. , Eadie, P. , Nes, R. B. , & Røysamb, E. (2020). Preschool speech intelligibility and 8-year literacy: A moderated mediation analysis. Journal of Speech, Language, and Hearing Research, 63(10), 3380–3391. 10.1044/2020_jslhr-19-00394 [DOI] [PubMed] [Google Scholar]
  49. Kaufman, A. S. , & Kaufman, N. L. (2004). Kaufman Brief Intelligence Test–Second Edition (KBIT-2). AGS. [Google Scholar]
  50. Konerding, M. , Bergström, K. , Lachmann, T. , & Klatte, M. (2020). Effects of computerized grapho-phonological training on literacy acquisition and vocabulary knowledge in children with an immigrant background learning German as L2. Journal of Cultural Cognitive Science, 4(3), 367–383. 10.1007/s41809-020-00064-3 [DOI] [Google Scholar]
  51. Landerl, K. , Ramus, F. , Moll, K. , Lyytinen, H. , Leppänen, P. H. T. , Lohvansuu, K. , O'Donovan, M. , Williams, J. , Bartling, J. , Bruder, J. , Kunze, S. , Neuhoff, N. , Tóth, D. , Honbolygó, F. , Csépe, V. , Bogliotti, C. , Iannuzzi, S. , Chaix, Y. , Démonet, J. F. , … Schulte-Körne, G. (2013). Predictors of developmental dyslexia in European orthographies with varying complexity. The Journal of Child Psychology and Psychiatry, 54(6), 686–694. 10.1111/jcpp.12029 [DOI] [PubMed] [Google Scholar]
  52. Landerl, K. , & Wimmer, H. (2008). Development of word reading fluency and spelling in a consistent orthography: An 8-year follow-up. Journal of Educational Psychology, 100(1), 150–161. 10.1037/0022-0663.100.1.150 [DOI] [Google Scholar]
  53. Larrivee, L. S. , & Catts, H. W. (1999). Early reading achievement in children with expressive phonological disorders. American Journal of Speech-Language Pathology, 8(2), 118–128. 10.1044/1058-0360.0802.118 [DOI] [Google Scholar]
  54. Lepola, J. , Poskiparta, E. , Laakkonen, E. , & Niemi, P. (2005). Development of and relationship between phonological and motivational processes and naming speed in predicting word recognition in grade 1. Scientific Studies of Reading, 9(4), 367–399. 10.1207/s1532799xssr0904_3 [DOI] [Google Scholar]
  55. Leppänen, U. , Aunola, K. , Niemi, P. , & Nurmi, J.-E. (2008). Letter knowledge predicts grade 4 reading fluency and reading comprehension. Learning and Instruction, 18(6), 548–564. 10.1016/j.learninstruc.2007.11.004 [DOI] [Google Scholar]
  56. Lervåg, A. , Hulme, C. , & Melby-Lervåg, M. (2018). Unpicking the developmental relationship between oral language skills and reading comprehension: It's simple, but complex. Child Development, 89(5), 1821–1838. 10.1111/cdev.12861 [DOI] [PubMed] [Google Scholar]
  57. Lewis, B. A. , Freebairn, L. A. , & Taylor, H. G. (2000). Follow-up of children with early expressive phonology disorders. Journal of Learning Disabilities, 33(5), 433–444. 10.1177/002221940003300504 [DOI] [PubMed] [Google Scholar]
  58. Lonigan, C. J. , Burgess, S. R. , & Anthony, J. L. (2000). Development of emergent literacy and early reading skills in preschool children: Evidence from a latent-variable longitudinal study. Developmental Psychology, 36(5), 596–613. 10.1037/0012-1649.36.5.596 [DOI] [PubMed] [Google Scholar]
  59. MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. Taylor & Francis Group/Lawrence Erlbaum Associates. [Google Scholar]
  60. MacKinnon, D. P. , Lockwood, C. M. , Hoffman, J. M. , West, S. G. , & Sheets, V. (2002). A comparison of methods to test mediation and other intervening variable effects. Psychological Methods, 7(1), 83–104. 10.1037/1082-989x.7.1.83 [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. McBride-Chang, C. (1999). The ABCs of the ABCs: The development of letter-name and letter-sound knowledge. Merrill-Palmer Quarterly, 45, 285–308. [Google Scholar]
  62. Melby-Lervåg, M. , Lyster, S. A. , & Hulme, C. (2012). Phonological skills and their role in learning to read: A meta-analytic review. Psychology Bulletin, 138(2), 322–352. 10.1037/a0026744 [DOI] [PubMed] [Google Scholar]
  63. Muter, V. , Hulme, C. , Snowling, M. J. , & Stevenson, J. (2004). Phonemes, rimes, vocabulary, and grammatical skills as foundations of early reading development: Evidence from a longitudinal study. Developmental Psychology, 40(5), 665–681. 10.1037/0012-1649.40.5.665 [DOI] [PubMed] [Google Scholar]
  64. Nathan, L. , Stackhouse, J. , Goulandris, N. , & Snowling, M. J. (2004). The development of early literacy skills among children with speech difficulties: A test of the “critical age hypothesis.” Journal of Speech, Language, and Hearing Research, 47(2), 377–391. 10.1044/1092-4388(2004/031) [DOI] [PubMed] [Google Scholar]
  65. Nation, K. (2019). Children's reading difficulties, language, and reflections on the simple view of reading. Australian Journal of Learning Difficulties, 24(1), 47–73. 10.1080/19404158.2019.1609272 [DOI] [Google Scholar]
  66. National Assessment of Educational Progress. (2022). NAEP Report Card: Reading. https://www.nationsreportcard.gov/reading
  67. Overby, M. S. , Trainin, G. , Smit, A. B. , Bernthal, J. E. , & Nelson, R. (2012). Preliteracy speech sound production skill and later literacy outcomes: A study using the Templin archive. Language, Speech, and Hearing Services in Schools, 43(1), 97–115. 10.1044/0161-1461(2011/10-0064) [DOI] [PubMed] [Google Scholar]
  68. Ozernov-Palchik, O. , Sideridis, G. D. , Norton, E. S. , Beach, S. D. , Wolf, M. , Gabrieli, J. D. E. , & Gaab, N. (2022). On the cusp of predictability: Disruption in the typical association between letter and word identification at critical thresholds of RAN and phonological skills. Learning and Individual Differences, 97, 102166. 10.1016/j.lindif.2022.102166 [DOI] [Google Scholar]
  69. Ozernov-Palchik, O. , Yu, X. , Wang, Y. , & Gaab, N. (2016). Lessons to be learned: How a comprehensive neurobiological framework of atypical reading development can inform educational practice. Current Opinion in Behavioral Sciences, 10, 45–58. 10.1016/j.cobeha.2016.05.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Pan, J. , McBride-Chang, C. , Shu, H. , Liu, H. , Zhang, Y. , & Li, H. (2011). What is in the naming? A 5-year longitudinal study of early rapid naming and phonological sensitivity in relation to subsequent reading skills in both native Chinese and English as a second language. Journal of Educational Psychology, 103(4), 897–908. 10.1037/a0024344 [DOI] [Google Scholar]
  71. Pennington, B. F. (2006). From single to multiple deficit models of developmental disorders. Cognition, 101(2), 385–413. 10.1016/j.cognition.2006.04.008 [DOI] [PubMed] [Google Scholar]
  72. Pennington, B. F. , & Lefly, D. L. (2001). Early reading development in children at family risk for dyslexia. Child Development, 72(3), 816–833. 10.1111/1467-8624.00317 [DOI] [PubMed] [Google Scholar]
  73. Pennington, B. F. , Santerre-Lemmon, L. , Rosenberg, J. , MacDonald, B. , Boada, R. , Friend, A. , Leopold, D. R. , Samuelsson, S. , Byrne, B. , Willcutt, E. G. , & Olson, R. K. (2012). Individual prediction of dyslexia by single versus multiple deficit models. Journal of Abnormal Psychology, 121(1), 212–224. 10.1037/a0025823 [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Perfetti, C. A. , Landi, N. , & Oakhill, J. (2005). The acquisition of reading comprehension skill. In M. J. Snowling & C. Hulme (Eds.), The science of reading: A handbook (pp. 227–247) Blackwell Publishing. 10.1002/9780470757642.ch13 [DOI] [Google Scholar]
  75. Peterson, R. L. , Pennington, B. F. , Shriberg, L. D. , & Boada, R. (2009). What influences literacy outcome in children with speech sound disorder? Journal of Speech, Language, and Hearing Research, 52(5), 1175–1188. 10.1044/1092-4388(2009/08-0024) [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Petscher, Y. , Justice, L. M. , & Hogan, T. (2018). Modeling the early language trajectory of language development when the measures change and its relation to poor reading comprehension. Child Development, 89(6), 2136–2156. 10.1111/cdev.12880 [DOI] [PubMed] [Google Scholar]
  77. Preston, J. , & Edwards, M. L. (2010). Phonological awareness and types of sound errors in preschoolers with speech sound disorders. Journal of Speech, Language, and Hearing Research, 53(1), 44–60. 10.1044/1092-4388(2009/09-0021) [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Preston, J. L. , Hull, M. , & Edwards, M. L. (2013). Preschool speech error patterns predict articulation and phonological awareness outcomes in children with histories of speech sound disorders. American Journal of Speech-Language Pathology, 22(2), 173–184. 10.1044/1058-0360(2012/12-0022) [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. Puranik, C. S. , Petscher, Y. , Al Otaiba, S. , Catts, H. W. , & Lonigan, C. J. (2008). Development of oral reading fluency in children with speech or language impairments: A growth curve analysis. Journal of Learning Disabilities, 41(6), 545–560. 10.1177/0022219408317858 [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. R Core Team. (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing. http://www.r-project.org [Google Scholar]
  81. Raitano, N. A. , Pennington, B. F. , Tunick, R. A. , Boada, R. , & Shriberg, L. D. (2004). Pre-literacy skills of subgroups of children with speech sound disorders. The Journal of Child Psychology and Psychiatry, 45(4), 821–835. 10.1111/j.1469-7610.2004.00275.x [DOI] [PubMed] [Google Scholar]
  82. Ricketts, J. , Bishop, D. V. M. , & Nation, K. (2009). Orthographic facilitation in oral vocabulary acquisition. The Quarterly Journal of Experimental Psychology, 62(10), 1948–1966. 10.1080/17470210802696104 [DOI] [PubMed] [Google Scholar]
  83. Rosenthal, J. , & Ehri, L. C. (2008). The mnemonic value of orthography for vocabulary learning. Journal of Educational Psychology, 100(1), 175–191. 10.1037/0022-0663.100.1.175 [DOI] [Google Scholar]
  84. Rvachew, S. (2007). Phonological processing and reading in children with speech sound disorders. American Journal of Speech-Language Pathology, 16(3), 260–270. 10.1044/1058-0360(2007/030) [DOI] [PubMed] [Google Scholar]
  85. Rvachew, S. , Ohberg, A. , Grawburg, M. , & Heyding, J. (2003). Phonological awareness and phonemic perception in 4-year-old children with delayed expressive phonology skills. American Journal of Speech-Language Pathology, 12(4), 463–471. 10.1044/1058-0360(2003/092) [DOI] [PubMed] [Google Scholar]
  86. Saygin, Z. M. , Norton, E. S. , Osher, D. E. , Beach, S. D. , Cyr, A. B. , Ozernov-Palchik, O. , Yendiki, A. , Fischl, B. , Gaab, N. , & Gabrieli, J. D. (2013). Tracking the roots of reading ability: White matter volume and integrity correlate with phonological awareness in prereading and early-reading kindergarten children. Journal of Neuroscience, 33(33), 13251–13258. 10.1523/jneurosci.4383-12.2013 [DOI] [PMC free article] [PubMed] [Google Scholar]
  87. Scarborough, H. S. (1990). Very early language deficits in dyslexic children. Child Development, 61(6), 1728–1743. 10.2307/1130834 [DOI] [PubMed] [Google Scholar]
  88. Scarborough, H. S. (2001). Connecting early language and literacy to later reading (dis)abilities: Evidence, theory and practice. In Neuman S. & Dickinson D. (Eds.), Handbook for research in early literacy. Guilford. [Google Scholar]
  89. Schatschneider, C. , Fletcher, J. M. , Francis, D. J. , Carlson, C. D. , & Foorman, B. R. (2004). Kindergarten prediction of Reading skills: A longitudinal comparative analysis. Journal of Educational Psychology, 96(2), 265–282. 10.1037/0022-0663.96.2.265 [DOI] [Google Scholar]
  90. Schneider, W. , Roth, E. , & Ennemoser, M. (2000). Training phonological skills and letter knowledge in children at risk for dyslexia: A comparison of three kindergarten intervention programs. Journal of Educational Psychology, 92(2), 284–295. 10.1037/0022-0663.92.2.284 [DOI] [Google Scholar]
  91. Semel, E. , Wiig, E. , & Secord, W. (2003). CELF-4: Clinical Evaluation of Language Fundamentals–Fourth Edition. Harcourt Assessment, Inc. [Google Scholar]
  92. Shriberg, L. D. (2003). Diagnostic markers for child speech-sound disorders: Introductory comments. Clinical Linguistics & Phonetics, 17(7), 501–505. 10.1080/0269920031000138150 [DOI] [PubMed] [Google Scholar]
  93. Shriberg, L. D. , Austin, D. , Lewis, B. A. , McSweeny, J. L. , & Wilson, D. L. (1997). The percentage of consonants correct (PCC) metric: Extensions and reliability data. Journal of Speech, Language, and Hearing Research, 40(4), 708–722. 10.1044/jslhr.4004.708 [DOI] [PubMed] [Google Scholar]
  94. Shriberg, L. D. , & Kwiatkowski, J. (1982). Phonological disorders III: A procedure for assessing severity of involvement. Journal of Speech & Hearing Disorders, 47(3), 256–270. 10.1044/jshd.4703.256 [DOI] [PubMed] [Google Scholar]
  95. Snowling, M. J. , & Melby-Lervåg, M. (2016). Oral language deficits in familial dyslexia: A meta-analysis and review. Psychology Bulletin, 142(5), 498–545. 10.1037/bul0000037 [DOI] [PMC free article] [PubMed] [Google Scholar]
  96. Soden, B. , Christopher, M. E. , Hulslander, J. , Olson, R. K. , Cutting, L. , Keenan, J. M. , Thompson, L. A. , Wadsworth, S. J. , Willcutt, E. G. , & Petrill, S. A. (2015). Longitudinal stability in reading comprehension is largely heritable from grades 1 to 6. PLOS ONE, 10(1), Article e0113807. 10.1371/journal.pone.0113807 [DOI] [PMC free article] [PubMed] [Google Scholar]
  97. Sutherland, D. , & Gillon, G. T. (2005). Assessment of phonological representations in children with speech impairment. Language, Speech, and Hearing Services in Schools, 36(4), 294–307. 10.1044/0161-1461(2005/030) [DOI] [PubMed] [Google Scholar]
  98. Tambyraja, S. R. , Farquharson, K. , & Justice, L. (2020). Reading risk in children with speech sound disorder: Prevalence, persistence, and predictors. Journal of Speech, Language, and Hearing Research, 63(11), 3714–3726. 10.1044/2020_jslhr-20-00108 [DOI] [PubMed] [Google Scholar]
  99. Thompson, P. A. , Hulme, C. , Nash, H. M. , Gooch, D. , Hayiou-Thomas, E. , & Snowling, M. J. (2015). Developmental dyslexia: Predicting individual risk. The Journal of Child Psychology and Psychiatry, 56(9), 976–987. 10.1111/jcpp.12412 [DOI] [PMC free article] [PubMed] [Google Scholar]
  100. Tingley, D. , Yamamoto, T. , Hirose, K. , Keele, L. , & Imai, K. (2014). Mediation: R package for causal mediation analysis. Journal of Statistical Software, 59(5), 1–38. 10.18637/jss.v059.i05 26917999 [DOI] [Google Scholar]
  101. Torgesen, J. K. , Wagner, R. K. , & Rashotte, C. A. (2012). Test of Word Reading Efficiency–Second Edition (TOWRE-2). Pro-Ed. [Google Scholar]
  102. van Bergen, E. , van der Leij, A. , & de Jong, P. F. (2014). The intergenerational multiple deficit model and the case of dyslexia. Frontiers in Human Neuroscience, 8, 346–346. 10.3389/fnhum.2014.00346 [DOI] [PMC free article] [PubMed] [Google Scholar]
  103. van Otterloo, S. G. , & van der Leij, A. (2009). Dutch home-based pre-reading intervention with children at familial risk of dyslexia. Annals of Dyslexia, 59(2), 169–195. 10.1007/s11881-009-0030-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  104. Vittinghoff, E. , Glidden, D. V. , Shiboski, S. C. , & McCulloch, C. E. (2012). Regression methods in biostatistics: Linear, logistic, survival, and repeated measures models. Springer. 10.1007/978-1-4614-1353-0 [DOI] [Google Scholar]
  105. Wagner, R. K. , Torgesen, J. K. , & Rashotte, C. A. (1999). Comprehensive Test of Phonological Processes. Pro-Ed. [Google Scholar]
  106. Webster, P. E. , Plante, A. S. , & Couvillion, L. M. (1997). Phonologic impairment and prereading: Update on a longitudinal study. Journal of Learning Disabilities, 30(4), 365–375. 10.1177/002221949703000402 [DOI] [PubMed] [Google Scholar]
  107. Wolf, M. , & Denckla, M. B. (2005). RAN/RAS: Rapid automatized naming and rapid alternating stimulus tests. Pro-Ed. [Google Scholar]
  108. Wolff, U. (2014). RAN as a predictor of reading skills, and vice versa: Results from a randomised reading intervention. Annals of Dyslexia, 64(2), 151–165. 10.1007/s11881-014-0091-6 [DOI] [PubMed] [Google Scholar]
  109. Woodcock, R. (1998). Woodcock Reading Mastery Tests–Revised (WRMT-R). AGS. [Google Scholar]
  110. Yu, X. , Zuk, J. , & Gaab, N. (2018). What factors facilitate resilience in developmental dyslexia? Examining protective and compensatory mechanisms across the neurodevelopmental trajectory. Child Development Perspectives, 12(24), 240–246. 10.1111/cdep.12293 [DOI] [PMC free article] [PubMed] [Google Scholar]
  111. Zuk, J. , Dunstan, J. , Norton, E. , Yu, X. , Ozernov‐Palchik, O. , Wang, Y. , Hogan, T. P. Gabrieli, J. D. E. Gaab, N. (2021). Multifactorial pathways facilitate resilience among kindergarteners at risk for dyslexia: A longitudinal behavioral and neuroimaging study. Developmental Science, 24(1), e12983. 10.1111/desc.12983 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Material S1. Supplemental information.
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Data Availability Statement

The data sets generated during and/or analyzed during this study are available from the senior author, Nadine Gaab, on reasonable request.

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