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Neuropsychology. Author manuscript; available in PMC 2017 May 1.
Published in final edited form as:
Published online 2015 November 16. doi:  10.1037/neu0000247
PMCID: PMC4840051

Early Language Mediates the Relations between Preschool Inattention and School-Age Reading Achievement



Early inattention is associated with later reading problems in children, but the mechanism by which this occurs is unclear. We investigated whether the negative relation between preschoolers' ADHD symptoms and 8-year-old reading achievement is directly related to the severity of inattention or is mediated by early language skills.


Children (n=150; 76% boys) were evaluated at three time points: preschool [T1; mean (SD) age=4.24 (.49) years]; 1-year later [T2; mean (SD) age=5.28 (.50) years]; and during school-age [T3; mean (SD) age=8.61 (.31) years]. At T1, parents' Kiddie-SADS responses were dimensionalized to reflect ADHD severity. Children completed the Language domain of the NEPSY at T1 and again at T2. At T3, children completed the WIAT-II Word Reading, Pseudoword Decoding, Reading Comprehension, and Spelling subtests, and their teachers completed ratings of Reading and Written Expression performance in school. The mediating effect of T2 Language on the relation between preschool Inattention and age 8 Reading was examined using the non-parametric bootstrapping procedure, while controlling for T1 Language.


Language ability at T2 mediated the path from preschool inattention (but not hyperactivity/impulsivity) to 8-year-old reading achievement (both test scores and ratings) after controlling for preschoolers' language ability.


Early attentional deficits may negatively impact school-age reading outcomes by compromising the development of language skills, which in turn, imperils later reading achievement. Screening children with attentional problems for language impairment, as well as implementing early intervention for both attentional and language problems may be critical to promote reading achievement during school years.

Keywords: ADHD, preschoolers, reading, language, longitudinal

Attention-Deficit/Hyperactivity Disorder (ADHD) is characterized by elevated inattention and/or hyperactivity/impulsivity that leads to impairment in multiple settings (American Psychiatric Association, 2013). Children with a Specific Learning Disorder in the domain of reading (RD) have significant difficulties for their age in decoding, fluent reading, and/or reading comprehension, which cannot be explained by low intelligence or inadequate educational opportunities (American Psychiatric Association, 2013). Additionally, individuals with RD commonly exhibit poor spelling (Bental & Tirosh, 2007; Willcutt, Pennington, Olson, Chhabildas, & Hulslander, 2005). The high frequency with which ADHD and RD co-occur is notable, with comorbidity rates ranging from 15-40% in clinical (August & Garfinkel, 1990; Semrud-Clikeman et al. 1992) and community samples (Willcutt & Pennington, 2000). For many individuals, both ADHD and RD follow a chronic course (Fischer, Barkley, Edelbrock, & Smallish, 1990; Bruck, 1990; Riddle et al., 2013; Shaywitz et al., 1999), placing children at risk for poor educational outcomes (e.g., Fischer et al., 1990; Frick et al., 1991; Hinshaw, 1992). Given the significant implications for children's learning, understanding the relations among inattention, hyperactivity/impulsivity, and reading achievement is critical.

The dual-cascade model of reading proposes both direct (lexical) and indirect (sub-lexical) routes for reading (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001) with beginning readers generally favoring the more effortful and attention-demanding sub-lexical route. First, children must identify visually-presented letters and decode them into their respective sounds. These sounds are temporarily stored until they can be blended to form a word, which can then be read (Coltheart et al., 2001). From this perspective, it is not surprising that children with attentional problems have difficulty learning to read.

In contrast, reading requires minimal conscious effort for proficient readers. However, information processing accounts of reading automaticity highlight the importance of attention at each stage of reading development (LaBerge & Samuels, 1974; Reynolds & Besner, 2006). Based on these models, Shaywitz and Shaywitz (2008) proposed that the development of reading skills is attention-dependent and that disruption of attentional mechanisms may represent a causal pathway in the emergence of reading problems. This could, in part, account for high rates of comorbidity between ADHD and RD. Evidence linking attentional difficulties with reading problems come from cross-sectional studies indicating stronger relations between reading/spelling problems and inattention than hyperactivity/impulsivity (Cain & Bignell, 2014; Snowling, 2008; Willcutt & Pennington, 2000; Willcutt, Pennington, Olson, & DeFries, 2007).

Although inattention and reading appear related, the mechanisms that underlie this association remain somewhat elusive. A recent study of preschoolers showed bivariate negative relations of teacher-rated inattention and Continuous Performance Test omission errors to pre-reading skills, print knowledge and phonological awareness (Sims & Lonigan, 2013). Using a longitudinal design, Walcott, Scheemaker, and Bielski (2010) found that teachers' reports of preschoolers' inattention predicted phonemic awareness and letter naming 1-year later, over and above baseline language ability and performance on the literacy tasks. These studies suggest that inattention is a correlate of early language skills and may interfere with literacy skill development.

Most research has categorized individuals according to diagnostic status (i.e., ADHD and/or RD). Yet, inattention and hyperactivity/impulsivity (Willcutt et al., 2012; see Frick & Nigg, 2012 for a review), as well as reading ability (Rogers, 1983; Shaywitz Escobar, Shaywitz, Fletcher, & Makuch, 1992; Snowling, 2008), are dimensional constructs, with children who meet diagnostic criteria for disorders falling at the severe end of the continuum (Rogers, 1983; Shaywitz et al., 1992; Willcutt et al., 2012). Using a categorical approach may mask our ability to determine relations because sensitivity is reduced when an arbitrary cut-off is placed along a dimension. Of note, evidence suggests that when ADHD and reading difficulties are analyzed dimensionally, a clear positive relation between the two emerges (Gooch, Snowling & Hulme, 2011; Willcutt et al., 2005).

Furthermore, both ADHD and RD emerge relatively early in development (Lahey et al., 2004; Scarborough, 1990). Thus, assessment of their relations at school-age or adolescence may obscure our ability to elucidate the mechanisms linking them during the acquisition of pre-reading skills, which is critical for the development of early interventions (Bradley & Bryant, 1983; Torgesen et al., 1999). With few exceptions (Sims & Lonigan, 2013; Walcott et al. 2010) the literature largely centers on older youth.

This longitudinal study tested whether ADHD symptom severity in preschoolers predicts 8-year-old reading achievement, and the extent to which this relation is mediated by early language skills. Given that inattention shows a stronger relation than hyperactivity/impulsivity to reading (Cain & Bignell, 2014; Greven, Rijsdijk, Anderson, & Plomin, 2012; Willcutt & Pennington, 2000; Willcutt et al., 2005), we examined inattention and hyperactivity/impulsivity separately. We predicted that later reading achievement would be related to early inattention, but not hyperactivity/impulsivity, and that the relation between inattention during preschool and reading achievement at age 8 years would be mediated by early language ability.



Preschoolers were recruited into a longitudinal study via local preschools and direct clinical referrals. Entry was based on parent and teacher reports on the Attention-Deficit/Hyperactivity Disorder Rating Scale, Fourth Edition (ADHD-RS-IV; DuPaul, Power, Anastopoulus, & Reid, 1998). Children who received fewer than 3 symptoms rated as Often or Very Often on the Hyperactivity/Impulsivity and Inattention subscale(s) by both parent and teacher were considered “Typically-developing” (TD). Children who received 6 or more symptoms rated as Often or Very Often on the Hyperactivity/Impulsivity and/or Inattention subscale(s) by either parent or teacher were considered to be Hyperactive/Inattentive. Entry into the study was set to oversample hyperactive/inattentive children at approximately a 2:1 ratio. Children were excluded if they had a Pervasive Developmental Disorder; Post-Traumatic Stress Disorder; a neurological disorder; a Full-Scale IQ less than 80 as measured by the Wechsler Preschool and Primary Scale of Intelligence, 3rd Edition (WPPSI-III; Wechsler, 2002); were taking systemic medication for a chronic medical or psychiatric disorder, including ADHD; did not attend a preschool/daycare facility; or were not fluent in English. This study was approved by the university's Institutional Review Board (IRB). Following a full description of the study, all parents signed IRB-approved informed consent forms.

Among the 216 (140 hyperactive/inattentive; 76 TD) children originally recruited, 150 (90 hyperactive/inattentive; 60 TD) were evaluated at three time-points and served at the participants for this study. At Time 1 (T1) they had a mean age of 4.24 (SD = .49) years. The children returned for a follow-up (T2) evaluation 1 year later at mean age = 5.28 (SD = .50) years. Their third assessment (T3) took place, on average, 4.37 (SD=.48) years after their T1 assessment when they were a mean age of 8.61 (SD = .31) years.

The majority of the 150 children were boys [n=114 (76%)] and the sample was racially and ethnically diverse: 90 (60%) White, 15 (10%) Black, 19 (12.7%) Asian, and 26 (17.3%) identified as multi-racial; 44 (29.3%) had at least one parent of Hispanic descent. Children's WPPSI-III FSIQ fell in the Average range [mean (SD)=107.29 (13.59)]. The Nakao-Treas Socioeconomic Prestige Index (Nakao & Treas, 1994) was used to measure socioeconomic status. The mean SES of children's families at baseline was 64.13 (SD = 17.96) consistent with, on average, a moderate-level SES.


ADHD Ratings

Attention-Deficit/Hyperactivity Disorder Rating Scale, Fourth Edition (ADHD-RS-IV; DuPaul et al., 1998)

This 18-item rating scale comprises the DSM-IV symptoms of ADHD. Parents and teachers indicate the frequency with which children engage in each behavior on a 4-point scale (0 = Never or Rarely; 3 = Very Often). Within our sample, coefficient alpha for parent and teacher reports were .95 and .96, respectively.

The Kiddie SADS Present and Lifetime Version (KSADS; Kaufman, Birmaher, Brent, Rao, & Ryan, 1996)

The KSADS is a semi-structured psychiatric interview that assesses the presence of psychiatric disorders in children according to DSM-IV criteria. At T1, the ADHD module was administered to each child's parent(s) by well-trained graduate students or Ph.D.-level psychologists who were blind to children's ADHD-RS-IV scores. Following the parent interview, teachers' ADHD-RS-IV ratings were integrated with parent-reported information to determine the KSADS summary score for each item using an “and/or” rule (MTA Cooperative Group, 1999). KSADS scores were re-coded from their original scale (1=not present; 2=sub-threshold; 3=threshold) to a 0-2 scale. Dimensional measures of Inattention and Hyperactivity/Impulsivity were calculated using scores for the nine KSADS ADHD items for each domain. Within our sample, coefficient alpha for Inattention and Hyperactivity/Impulsivity domains were .93 and .94, respectively

Early Language Measures

A Developmental Neuropsychological Assessment (NEPSY; Korkman, Kirk, & Kemp, 1998)

The NEPSY is a standardized neuropsychological test battery for children aged 3-12 years. At T1 (3-4 years of age) and T2 (4-6 years of age), well-trained graduate students administered the core subtests from the Language domain to children. In accordance with NEPSY instructions, the exact composition of subtests administered differed depending on the age of the child. Three- and 4-year-old children only were administered Body Part Naming, in which they were asked to name particular parts on a drawing of a child (this measures children's access to the semantic label for a stimulus). Both 3-4 and 5-6 years olds were administered Comprehension of Instructions, a measure of receptive language, in which they had to process and respond to increasingly complex verbal instructions, and Phonological Processing. At 3-4 years, Phonological Processing requires children to listen to a segment of a word and then identify the whole word (by pointing to its pictorial representation). Children aged 5 years and older were extended even further in this subtest by also having to manipulate sound patterns to produce new words. In addition to Phonological Processing and Comprehension of Instructions, children aged 5 years and older were administered Speeded Naming, which measures speed and accuracy of access to alternating language labels. In the normative sample, internal consistency coefficients for 3-4 and 5-12 year-old children for the Language domain were ≥ .80. Language domain standard scores were used in the present analyses.

Academic Achievement

Wechsler Individual Achievement Test, Second Edition (WIAT-II; Wechsler, 2001)

The WIAT-II is a standardized individually-administered test for individuals aged 4 through adulthood. Four WIAT-II subtests were administered to children at T3; Word Reading, Pseudoword Decoding (reading of nonsense words), Reading Comprehension, and Spelling. Reliability coefficients for these subtests range from .93-.98.

The NICHQ Vanderbilt Assessment Scale – Teacher Informant (Vanderbilt; Wolraich, Feurer, Hannah, Baumgaertel, & Pinnock, 1998)

Teacher-rated reading (n = 112) and written expression performance (n = 113) was obtained for a sub-sample of children at T3 using the Vanderbilt. Teachers rated children's ability on a 5-point scale ranging from 1 (Excellent) to 5 (Problematic).

Medication Status

Although all children were medication naïve at T1, at T2 and T3, 9 (6%) and 33 (22%) children, respectively, were prescribed medication for behavioral/emotional difficulties. Of the 9 children taking medicine at T2, 6 were prescribed a stimulant, 2 were taking risperidone and 1 child was taking methylphenidate and risperidone. Of the 33 children taking medicine at T3, 20 were taking a stimulant, 3 were taking atomoxetine, and 1 was taking an SSRI. The remaining 9 children were taking multiple medications to manage their difficulties. Parents of children taking stimulants or atomoxetine for ADHD were asked to withhold the medicine on the day of the evaluation. On the rare occasion that children arrived for their evaluation having been given their medicine, the evaluation was rescheduled at a time convenient for the family. Parents were not asked to withhold other medicines.

Data Analysis

A mediation model was tested (see Figure 1) whereby T1 Inattention served as the predictor (X), T2 Language as the mediator (M), and T3 academic achievement as the criterion variable (Y). All pathways were controlled for T1 Language. As recommended by Hayes (2009), when samples are small, the non-parametric bootstrapping procedure offers a more robust test of mediation. This method also offers the advantage in that it makes no assumptions about the underlying distribution of variables and does not require a significant path between the independent and dependent variables (Preacher & Hayes, 2008). Bootstrapping draws multiple random samples from the data set and measures the unstandardized path coefficients for each sample (B). The bootstrapped estimate of the indirect effect is the mean across all of the samples, with the true indirect effect considered to fall within the 95% confidence interval (CI). A CI that does not include zero can be taken as evidence that the indirect effect is different from zero at p < .05. As recommended by Hayes (2009), 5000 bootstrap samples were taken to estimate the indirect effect. Secondary analyses were conducted to test the mediation model using teachers' subjective ratings of children's performance, which were collected in a subsample, as the outcome variables.

Fig. 1
Mediation design where: c is the total effect of X on Y; a is the effect of X on the mediator (M); b is the effect of M on Y after controlling for the effect of X; c′ is the direct effect of X on Y through M; ab is the indirect effect (i.e., the ...

Missing Data

Sixteen TD and 50 hyperactive/inattentive children of the 216 originally recruited to the study did not return for their T2 and/or T3 assessment(s). For TD and hyperactive/inattentive children we looked to see if there were differences between those who did and did not complete all three evaluations for the following demographic/T1 variables: gender, SES, race, ethnicity, age, FSIQ, and language ability; parent-rated inattention and hyperactivity/impulsivity; and teacher-rated inattention and hyperactivity/impulsivity. Thus, 11 comparisons were conducted for each of the TD and hyperactive/inattentive groups (22 comparisons). To correct for multiple testing, we utilized an alpha of .01 to decrease the likelihood of chance findings, while still being liberal enough to detect potentially important differences. Among TD children who did and not complete all three evaluations, no differences were observed. Among hyperactive/inattentive children, those who completed all three evaluations had stronger Language skills than those who completed one or two evaluations [mean (SD) 100.19 (11.87) vs. 94.21 (12.71), p=.007].


Descriptive statistics of key variables are presented in Table 1. Partial correlation analyses showed that when controlling for T1 Language, T1 Hyperactivity/Impulsivity was not significantly associated with T2 Language (r=-.04, p=.62). As such, mediation analyses were not conducted for this independent variable.

Table 1
Descriptive characteristics of the key measures

In contrast, after controlling for T1 Language, preschool Inattention was significantly related to T2 Language (r=-.19, p=.02) and therefore mediation analyses were conducted.1 When reading achievement was assessed using standardized psychometric tests, bootstrapping analyses showed that after controlling for Language at T1, Language at T2 significantly mediated the relations between T1 Inattention and T3 Word Reading (B = -.14, bias-corrected 95% CI = -.32 - -.02); T3 Pseudoword Decoding (B = -.13, bias-corrected 95% CI = -.29 - -.02); and T3 Spelling (B = -.08, bias-corrected 95% CI = -.17 - -.01). In each of these models, neither the direct effect of T1 Inattention on T3 reading outcomes, nor the partial effect of T1 Language on T3 reading outcomes were significant after the inclusion of T2 Language in the model (all p > .05) (see Table 2). Regarding children's reading comprehension skills at age 8 years, after T1 Language was controlled, Language at T2 partially mediated the relations between T1 Inattention and T3 Reading Comprehension, (B = -.16, bias-corrected 95% CI = -.38 - -.03). Both the direct effect of T1 Inattention (B = -.81) and the partial effect of T1 Language (B=.34) on T3 Reading Comprehension remained significant (p < .05) (see Table 2).

Table 2
Bootstrapa results showing unstandardized path coefficients (B) for mediation model testing whether the negative relation between T1 Inattention severity and T3 academic achievement outcomes is mediated through T2 Language, controlling for T1 Language ...

These findings largely held when bootstrapping analyses were carried out for the subsample of children for whom we received teacher ratings of reading and written expression performance at age 8 years (see Table 2). After controlling for Language at T1, Language at T2 mediated the relation between T1 Inattention and T3 teacher-rated Reading (B = .02, bias-corrected 95% CI = .005 - .03). The direct effect of T1 Inattention on 8-year-old Reading was marginally significant (B = .03, p <.10) and the partial effect of T1 Language on Reading was significant (B = -.02, p < .05). Finally, after controlling for Language at T1, Language at T2 partially mediated the relation between T1 Inattention and T3 teacher-rated Written Expression (B = .01, bias-corrected 95% CI = .004 - .03). The direct effect of T1 Inattention on age 8 Written Expression remained significant (B = .04, p < .05), but this was not so for the partial effect of T1 Language on 8-year-old Written Expression (B = -.01, p ≥ .10).


This study examined mechanisms by which early ADHD symptoms are linked to later reading difficulties. Early attentional deficits seem to negatively impact the development of language-related reading precursors, which in turn, compromises school-age reading outcomes. In addition to this indirect path to poorer reading achievement, preschool inattention was shown to directly impact children's reading comprehension and teacher-rated written expression at age 8 years. In contrast, there was no significant association between severity of preschoolers' hyperactivity/impulsivity and their language ability at 4-6 years when T1 Language ability was controlled. This pattern was expected given that several studies have highlighted the importance of inattention, but not hyperactivity/impulsivity, in predicting learning outcomes (Sims & Lonigan, 2013; Willcutt & Pennington, 2000; Willcutt et al., 2007).

This study has several notable strengths. The longitudinal data allowed us to show relations among ADHD behaviors, language skills, and reading achievement that previously have been posited, but never tested. In addition, we employed multiple measures of reading outcomes to show the breadth of the relations with early inattention, with convergence of findings across teacher-rated and objectively-measured achievement. Furthermore, the use of objective measures of language and reading reduced the risk of halo effects that may have influenced teacher ratings of hyperactive and inattentive children's performance. The use of dimensional measures of inattention, hyperactivity/impulsivity, and reading achievement also allowed greater sensitivity for assessing associations among variables. Finally, importantly, we were able to show that preschoolers' inattention is associated with later language and reading problems over and above language skills at baseline. Given that language difficulties are also early emerging, it was necessary to rule-out the possibility that children presenting with poorer language at 4-5 years old also had language problems at study entry.

The study's findings must also be considered in light of its limitations. Most importantly, many children missed their T2 and/or T3 evaluation, and for hyperactive/inattentive children, those who completed all evaluations showed stronger language skills at baseline than those who did not. Although not ideal, selective attrition is common in longitudinal studies, such that families experiencing greater disadvantage (e.g., lower SES, more psychosocial stress, greater disharmony, less stable job history) are more likely to be lost to follow-up (Campbell, Ewing, Breaux, & Szumowski, 1986). Recent work by Wolke and colleagues (2009) showed that although such differential attrition may result in fewer children meeting criteria for a particular psychiatric disorder at follow-up, the relations among modeled variables is largely unaffected. Thus, our findings are likely valid.

A second issue to consider is that many children in this study were prescribed medication to help manage their behavioral and emotional difficulties. Although parents were asked to withhold children's stimulant medications and/or atomoxetine the morning of testing, it is possible that children's cognitive performance was affected by medication use.

The mediation model supported by the findings of the current study adds to a body of literature attempting to delineate why inattention (in particular) and reading difficulties so commonly co-occur. However, utilizing samples of older children and/or adolescents in cross-sectional designs, other researchers have identified neuropsychological risk factors for comorbid inattention and reading problems other than language, including auditory-verbal working memory (Rogers, Hwang, Toplak, Weiss, & Tannock, 2011) and processing speed (McGrath et al., 2011). It is possible that one, or both, of these constructs may be able to explain the findings in the current study, or would account for additional variance in children's reading skills above and beyond language skills. Alternatively, different neuropsychological constructs may exert greater risk at different times in development. These are empirical questions that need to be answered.

Our findings suggest possible avenues for early intervention. First, monitoring of inattentive preschoolers for emerging language difficulties may identify those at greater risk for poorer reading during school-age. Second, addressing attentional deficits during the preschool period may help to reduce the risk of delays in language development, and in turn, later reading problems. Finally, early intervention to target language skills will be critical. Bradley and Bryant (1983) showed that sound categorization training over a 2-year period improved performance on standardized reading and spelling tests for 5- and 6-year-old children with low sound categorization skills. Spelling performance was improved even further if, in addition to sound categorization training, children were also taught to map sounds to letters. More recently, Fricke, Bowyer-Crane, Haley, Hulme and Snowling (2013) investigated the efficacy of an intensive oral language intervention for 4-year-olds, which aimed to improve vocabulary, narrative skills, listening skills, phoneme awareness and letter-sound knowledge, and self-confidence in speaking. Compared to a wait-list control group, those who completed the intervention showed improvements in vocabulary, phoneme awareness and narrative skills at the completion of the training program and at 6-months follow-up, and achieved higher reading comprehension scores. Thus early interventions targeting language development hold promise.

Overall, the findings from this longitudinal study identify one potential mechanism by which early ADHD symptoms increase risk for RD during the school-age years. Specifically, preschoolers' inattention appears to negatively affect development of language skills, which in turn impacts reading skills at age 8 years. Acting early to mitigate risk is critical given the chronic trajectories of both disorders and their associated impact on daily functioning.


This study was supported by a National Institute of Mental Health grant R01 MH068286 (PI. Jeffrey M. Halperin) and a NIH NIGMS (MARC-USTAR) grant T 34, GM070387 (PI. Zahra Zakeri, Fellowship awarded to Veronica Thornton). The content is solely the responsibility of the authors and does not necessarily represent the official view of the National Institutes of Health.


1When examining the alternative scenario, that T1 Language is associated with T2 Inattention after controlling for T1 Inattention, the pathway was not significant, r = -.08, p = .33.

Conflict of Interest: All authors report no financial relationships with commercial interests.

Contributor Information

Sarah O'Neill, The City College and The Graduate Center, City University of New York.

Veronica Thornton, Regent University.

David J. Marks, New York University.

Khushmand Rajendran, Ohio University, Zanesville.

Jeffrey M. Halperin, Queens College and The Graduate Center, City University of New York.


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