Abstract
Objectives:
Most children exhibit preliteracy skills by preschool. Children who are deaf/hard of hearing (DHH) with a language gap are at risk for delayed preliteracy skills. Our study aimed to describe preliteracy skill development in preschool-aged DHH children and investigate associated factors.
Methods:
Children, aged 3 to 5 years, were included in the analysis if enrolled in randomized trials of a language intervention using augmentative and alternative communication, shown to boost language skills. Evaluations using the Clinical Evaluations of Fundamentals-Preschool Preliteracy Rating Scale (PRS) were conducted at baseline, 24 weeks, and 48 weeks. Repeated-measures models assessed changes in total PRS scores and Early Reading and Early Writing subdomains. Results were presented as least square mean values with 95% confidence intervals.
Results:
Forty-five children had completed pre-data and post-data. The mean nonverbal IQ was 99.3 (SD 14.3), and receptive and expressive language were 82.3 (14.9) and 76.8 (17.0), respectively. Significant (p < 0.0001) skill growth was observed with all preliteracy outcomes, ranging from 11 to 15 points in the first 24 weeks. Increasing receptive and expressive language over time was significantly associated with increasing scores. Factors such as aided hearing thresholds, caregiver education level, and hearing device use were not significant in models.
Conclusion:
Language is essential for literacy development. Language-enhancing interventions could facilitate literacy skills. Monitoring preliteracy skills in DHH children is crucial, given their increased risk for language delays. Further research is needed to support early literacy development in this population, ensuring they have the tools they need for future success.
Index terms: deaf and hard of hearing, preliteracy skills, language
By preschool, most children display preliteracy skills (exploring books, recognizing some letters, and retelling stories). Several factors have been associated with strong preliteracy skills in typically developing children. These include early exposure to language and literacy activities, such as reading books and singing songs; frequent caregiver involvement in literacy activities; and a positive and supportive home literacy environment through parent-child shared reading, book availability, and verbal interactions.1 These early literacy activities are designed to support the development of vocabulary; print knowledge, which includes distinguishing letters from pictures; holding a book upright; and developing phonological awareness. This awareness encompasses the ability to recognize and manipulate sounds in language,2 which supports reading acquisition. Furthermore strong language skills, which include vocabulary knowledge and comprehension, support the development of reading and writing skills.2 The interactive aspects of reading3 and the exposure to reading materials are crucial for fostering a love of reading and the development of literacy skills at a young age. Literacy is foundational to cognitive and social development, and early interventions that promote reading skills can have long-term academic and life benefits.
Learning to read has long been challenging for many deaf/hard of hearing (DHH) children, with various theoretical explanations.4,5 Regardless, it is clear that language is essential for literacy development. Language must be made accessible for DHH children. Without adequate adapted approaches for language learning, language delays or gaps between the child’s ability and their language can occur.6 As communication influences literacy, cognitive, social, and emotional development, consequences of these language delays are long-lasting.
Limited literacy skills increase the risk for academic underachievement, unemployment, and other poor social outcomes in the general population. For DHH individuals, limited literacy skills significantly hinder educational and socioeconomic outcomes.7 Low reading levels have subsequent impact on access to learning when curricula become dependent on strong reading skills. This phenomenon has raised concerns about the educational outcomes of DHH students and highlights the need for effective early interventions.8
We conducted a secondary analysis of data collected as part of a randomized control intervention study that was designed to improve language in DHH children. The Technology Assisted Language Intervention (TALI) is an evidence-based speech-language therapy approach using augmentative and alternative communication (AAC) technology as a language teaching tool for DHH children.9 This intervention significantly improved language skills among DHH children compared with receiving the standard treatment as usual (TAU), which involved no change to the therapy or care children received. It enhanced both receptive and expressive language scores, increased the mean length of utterance in morphemes, boosted conversational turn-taking, and expanded the number of new words spoken.9 The objectives of this analysis were to (1) describe changes in preliteracy skills over time in preschool age children who are DHH and (2) investigate factors that may be associated with this change. Since the TALI appeared to improve language skills, we also conducted an exploratory analysis to evaluate its impact on preliteracy skills.
METHODS
TALI Intervention Trials
We conducted 2 randomized trials to evaluate the impact of incorporating AAC into speech-language therapy on spoken language development in DHH children. Both trials (2016–2019 and 2020–2025) had similar eligibility criteria: permanent bilateral hearing loss of any degree, use of spoken English language, nonverbal IQ >60, and a language gap defined by language skills disparate from nonverbal cognitive abilities. Children with significant communication disorders (e.g., autism spectrum disorder), motor disabilities, or vision impairments affecting the ability to complete testing were excluded. The original trial included children aged 3 to 12 years, and the recent trial included children aged 3 to 10 years. Eligible children were randomly assigned to receive either the TALI or the TAU (no change in therapy). Both groups were monitored for 24 weeks, with an additional follow-up visit at 48 weeks to assess outcome sustainability. Details about the intervention delivery have been previously published.9 Both trials are registered with ClinicalTrials.gov (NCT02998164, NCT04857255).
Current Secondary Data Analysis
Participants.
To address our study objectives, we analyzed data from children aged 3 to 5 years with language delays who enrolled in one of two TALI trials between 2016 and 2024. At enrollment, randomization was stratified by age (<5 vs. >5 years) and nonverbal IQ (<100 vs. >100). We included data from children who received a baseline assessment but were found ineligible for randomization based on their language levels (did not have a language gap). Both trials were approved by the institution’s institutional review board, and all families provided informed consent.
Assessments.
All baseline assessments were administered before randomization. Nonverbal IQ was measured using the Leiter International Performance Scale—Revised10 (original trial) or The Leiter International Performance Scale-311 (recent trial). Receptive and expressive language skills were assessed using the CELF-Preschool 2.12,13 Caregivers completed the Behavior Rating Inventory of Executive Function—Preschool Version (BRIEF-P),14 which assesses executive function in preschool-aged children with subscales for inhibition, shifting, emotional control, working memory, and planning/organizing, reported as t-scores. Caregivers provided information on sex, race, parental income, insurance status, and education through a questionnaire. Audiograms and audiologic histories, including hearing-device use, were reviewed from medical records. Language assessments were administered at baseline (study entry), 24 weeks (end of intervention trial), and 48 weeks.
Measurement of Preliteracy.
Children were administered the Preliteracy Rating Scale (PRS) as part of the CELF-P at baseline and 24 weeks. The PRS is a questionnaire in which parents rate items as Always, Often, Sometimes, or Never. This questionnaire allows for a numerical score and comparison with the general population for age-appropriate skill development. Scores are provided for an overall preliteracy score and subdomains of Early Reading and Early Writing. Examples of Early Reading Skills at various ages include: “holds a book right side up,” “can point to a picture when an adult names it,” “can tell what happened first, next, and last in a familiar story,” “recognizes own printed name and familiar printed words” and “joins 3 letters to make a syllable or word.” Examples of Early Writing Skills at various ages include: “writes, draws, and/or scribbles to imitate writing,” “writes and/or scribbles from the left to the right side of a page,” “copies and/or writes own name accurately,” “writes on printed lines when provided,” “copies short words from the board accurately (e.g., “go, “dog”)” and “self-corrects errors if letters or numbers are copied incorrectly.” The CELF-P was updated between the 2 trials from the CELF-P212 to the CELF-P3.13
Coding of PRS Scores.
Because of the differing number of items in the 2 CELF-P versions (P2 with 26 items, P3 with 35 items), raw scores varied between them. To ensure comparability, percentage scores were calculated by dividing the obtained raw score by the total possible score. This method was applied to the PRS, Early Reading, and Early Writing scores. In addition, a sensitivity analysis was conducted on the common items present in both assessment versions.
Statistical Analysis.
We evaluated data distributions using mean values with SDs and frequencies with percentages. Unadjusted comparisons were tested using t-tests, Wilcoxon rank sums tests, and χ2 tests. To address the primary objective, we first evaluated unadjusted relationships between baseline preliteracy measures and participant characteristics using Pearson or point biserial correlations. Generalized estimating equations (GEEs) were used to account for the potential correlation induced by the repeated-measures data. Separate models were constructed for PRS total, Early Reading, and Early Writing scores by using a general linear model with an identity link function and exchangeable correlation matrix structure. Variables possibly associated with the outcomes, selected from the correlations and the literature, were tested individually and retained in the model if they had a p-value <0.10. Variables tested included annual income <$40,000, type of insurance (public vs. private), caregiver education level (college or higher), severe to profound hearing loss, age of hearing loss identification, and BRIEF-P scales. To better understand the relationship between language and preliteracy, we constructed 3 models for each of the PRS outcomes: expressive language, receptive language, and a model for the difference between receptive and expressive language scores. We evaluated the model fit using the Quasi-likelihood under the Independence Model Criterions (QIC). The model with the lowest QIC value was selected as it provided the best balance between goodness of fit and model complexity. For simplicity, if the predictor in 1 of the models (PRS, Early Reading, Early Writing) was retained, we kept that variable in all models. Results from the GEE models were reported as estimated coefficients (β) for each predictor variable, along with standard errors. We also reported least square mean values (adjusted mean values) of the various PRS scores at each time point with 95% confidence intervals (CIs). Since the children who were ineligible for the trial had only 1 timepoint and were not assigned to an intervention group, we used their data as a reference. In addition, we conducted an exploratory analysis to determine if preliteracy growth differed between the TALI and TAU groups. All statistical analyses were performed using SASv9.4 (SAS Institute, Inc, Cary, NC).
RESULTS
Participant Characteristics
Across both trials, 74 children aged 3 to 5 years participated (mean age 4.1 [0.7] years) and had at least 1 preliteracy assessment. Of these, 45 children (24 TALI and 21 TAU) completed both preintervention and postintervention assessments; 16 children had a 48-week assessment. Two children were currently active and had not completed the postintervention visit, 13 did not complete the 24-week visit, and 3 children did not have preliteracy data at the follow-up visit. Eleven additional children completed the baseline visit but were deemed ineligible for randomization because of the absence of language gaps.
Table 1 illustrates characteristics of the overall cohort, children with follow-up data, and children with no language gaps (ineligible for randomization). Although ineligible children had slightly better hearing thresholds, there were no statistical differences in demographics or nonverbal IQ across the groups. For the 45 children with postintervention data, the mean baseline (SD) receptive and expressive language scores were 82.3 (14.9) and 76.8 (17.0), respectively. The nonverbal IQ was 99.3 (14.3).
Table 1.
Characteristics of Participants Who Were DHH Aged 3 to 5 year
| Characteristics | Overall (n = 74) | Has Follow-up (n = 45) | No Language Gap (n = 11) |
|---|---|---|---|
| Age at visit in years, mean (SD) | 4.1 (0.7) | 4.1 (0.8) | 4.0 (0.5) |
| Age of identification in months, median [IQR] | 2.0 [1.0–19.5] | 3.0 [1.0–20.0] | 2.8 [1.0–20.0] |
| Identified by 3 mo of age, n (%) | 44 (59) | 24 (53) | 6 (55) |
| Gender, identified by parent, n (%) | |||
| Female | 32 (43) | 23 (51) | 5 (45) |
| Male | 42 (57) | 22 (49) | 6 (55) |
| Racea, n (%) | |||
| Black/African-American | 11 (15) | 7 (16) | 0 |
| White | 63 (85) | 39 (87) | 11 (100) |
| Ethnicity, Hispanic/Latino, n (%) | 8 (11) | 4 (9) | 1 (9) |
| Receive public insuranceb, n (%) | 25 (34) | 12 (27) | 3 (27) |
| Caregiver education level, n (%) | |||
| College graduate or higher | 47 (64) | 30 (67) | 9 (82) |
| Household income <$40,000, n (%) | 12 (16) | 6 (13) | 0 |
| Severe to profound hearing thresholds, n (%) | 27 (36) | 17 (38) | 1 (9) |
| Uses cochlear implant, n (%) | 14 (19) | 9 (20) | 0 |
| Uses hearing aids, n (%) | 60 (81) | 36 (80) | 9 (82) |
| Aided hearing thresholdsc, mean (SD) | 25.2 (13.2) | 22.8 (9.0) | 33.3 (31.8) |
| Baseline assessments, mean (SD) | |||
| Nonverbal IQ | 98.4 (15.4) | 99.3 (14.3) | 99.6 (15.2) |
| Receptive language standard scores | 83.7 (18.2) | 82.3 (14.9) | 102.3 (24.1) |
| Expressive language standard scores | 78.6 (20.4) | 76.8 (17.0) | 99.2 (27.0) |
| Baseline preliteracy scores, mean (SD)d | |||
| Preliteracy Rating Scale total score | 40.2 (22.9) | 39.5 (22.3) | 51.4 (22.5) |
| Early Reading subdomain | 49.6 (24.9) | 48.1 (23.7) | 63.5 (22.8) |
| Early Writing subdomain | 30.9 (24.3) | 31.1 (24.0) | 38.7 (37.6) |
Allowed to select >1 category.
Either public insurance only or combined with private insurance.
From pure tone averages or speech awareness/reception thresholds if available.
As a percent of total possible raw score.
DHH, deaf/hard of hearing; IQR, interquartile range.
Preliteracy Skills
The PRS scores were reported as a percentage of the total possible score. At baseline, the mean (SD) of the PRS score was 40.2 (22.9), whereas the Early Reading and Early Writing scores were 49.6 (24.9) and 30.9 (24.3), respectively (Table 1). Children with no language delays (n = 11) had slightly higher scores compared with the rest of the cohort regarding mean PRS (51.4 [22.5] vs. 41.2 [24.2], p = 0.19), Early Reading (63.5 [22.8] vs. 49.9 [25.8], p = 0.10), and Early Writing (38.7 [27.6] vs. 32.6 [25.3], p = 0.47). Table 2 illustrates the correlations between the baseline preliteracy scores and participant characteristics. Language scores were moderately correlated (r = 0.47–0.59, p < 0.0001) with the PRS total and Early Reading scores while weakly correlated with Early Writing (r = 0.31 and 0.35, p < 0.05). Executive function skills measured on the BRIEF-P were also weakly correlated with preliteracy skills; higher BRIEF-P scores, indicating more problems, were correlated with lower PRS scores.
Table 2.
Correlations Between Baseline Preliteracy Outcomes of the PRS, Early Reading, and Early Writing Scores With Characteristics Among all DHH Participants (n = 45)
| PRS | Early Reading | Early Writing | |
|---|---|---|---|
| Age of identification in months | −0.004 (0.98) | −0.04 (0.80) | 0.05 (0.77) |
| Severe to profound hearing loss | 0.06 (0.68) | −0.02 (0.87) | 0.14 (0.35) |
| Use hearing aid | 0.09 (0.55) | 0.19 (0.22) | −0.01 (0.97) |
| Use cochlear implant | −0.11 (0.46) | −0.23 (0.12) | 0.03 (0.86) |
| Receipt of public insurance | −0.32 (0.03) | −0.41 (0.005) | −0.17 (0.25) |
| Caregivers with college graduate degree | 0.18 (0.22) | 0.15 (0.33) | 0.19 (0.21) |
| Increasing household income categories | 0.37 (0.01) | 0.39 (0.009) | 0.23 (0.13) |
| Household income <$40,000 annually | −0.36 (0.02) | −0.41 (0.006) | −0.26 (0.09) |
| Nonverbal IQ | 0.38 (0.01) | 0.42 (0.004) | 0.27 (0.07) |
| Receptive language standard score | 0.52 (0.0003) | 0.59 (<0.0001) | 0.35 (0.02) |
| Expressive language standard score | 0.47 (0.002) | 0.53 (0.0003) | 0.31 (0.047) |
| BRIEF-P Global executive Composite | −0.35 (0.018) | −0.37 (0.011) | −0.24 (0.12) |
| BRIEF-P Inhibit subscale | −0.39 (0.008) | −0.40 (0.006) | −0.26 (0.088) |
| BRIEF-P shift subscale | −0.29 (0.056) | −0.32 (0.033) | −0.24 (0.11) |
| BRIEF-P Plan/Organize subscale | −0.20 (0.18) | −0.26 (0.087) | −0.09 (0.57) |
| BRIEF-P emotional control subscale | −0.26 (0.08) | −0.29 (0.06) | −0.20 (0.19) |
| BRIEF-P working memory subscale | −0.39 (0.009) | −0.38 (0.0099) | −0.28 (0.066) |
Pearson correlation coefficient reported for language, nonverbal IQ, age, and income. Point biserial correlation reported for remaining variables. Top number represents correlation coefficient and p-value reported in parentheses.
PRS, Preliteracy Rating Scale.
Table 3 presents the results of GEE models. Over time, children exhibited significant increases in preliteracy skills (p < 0.0001), with an average increase of 12.0 percentage points in the PRS total score every 24 weeks. The mean PRS total score (derived from the LS means of the GEE model) rose from 36.2 at baseline to 48.9 at 24 weeks and 61.2 at 48 weeks. For children with commensurate language, the mean PRS total score was 51.4 at the baseline visit. Similar results were observed in the Early Reading and Early Writing subdomains. Figure 1 shows the adjusted mean scores from the regression models at baseline, 24 weeks, and 48 weeks and includes children with no language gaps as a reference.
Table 3.
Estimated Slopes, With Standard Errors in Parentheses, Reported From GEE Models Indicating Change in Outcomes Occurring at Each 24-Week Interval
| Models | PRS Total Estimate (SE) | p | Early Reading Estimate (SE) | p | Early Writing Estimate (SE) | p |
|---|---|---|---|---|---|---|
| Expressive language | ||||||
| Time (baseline, 24 wk, and 48 wk) | 11.5 (1.9) | <0.0001 | 10.7 (2.0) | <0.0001 | 12.2 (2.2) | <0.0001 |
| Expressive language standard score | 0.39 (0.14) | 0.006 | 0.49 (0.15) | 0.0008 | 0.28 (0.17) | 0.10 |
| Executive function—Shift domain | −0.43 (0.24) | 0.069 | −0.16 (0.25) | 0.53 | −0.71 (0.27) | 0.009 |
| Annual household income <$40,000 | −11.7 (8.0) | 0.15 | −15.8 (8.7) | 0.07 | −6.75 (8.1) | 0.41 |
| Receptive language | ||||||
| Time (baseline, 24 wk, 48 wk) | 13.0 (1.9) | <0.0001 | 11.2 (2.0) | <0.0001 | 14.6 (2.2) | <0.0001 |
| Receptive language standard score | 0.16 (0.16) | 0.33 | 0.43 (0.17) | 0.011 | −0.11 (0.19) | 0.54 |
| Executive function—Shift domain | −0.54 (0.27) | 0.049 | −0.15 (0.30) | 0.62 | −0.93 (0.30) | 0.002 |
| Annual household income < $40,000 | −15.4 (7.6) | 0.042 | −19.0 (8.4) | 0.024 | −10.9 (7.4) | 0.14 |
| Receptive-expressive language gap | ||||||
| Time (baseline, 24 wk, 48 wk) | 13.4 (1.6) | <0.0001 | 12.7 (1.6) | <0.0001 | 13.8 (1.9) | <0.0001 |
| Receptive—expressive difference | −0.30 (0.17) | 0.07 | −0.22 (0.17) | 0.20 | −0.39 (0.18) | 0.034 |
| Executive function—Shift domain | −0.66 (0.25) | 0.009 | −0.42 (0.30) | 0.16 | −0.92 (0.28) | 0.0009 |
| Annual household income <$40,000 | −14.8 (6.9) | 0.034 | −20.7 (8.0) | 0.009 | −7.9 (6.8) | 0.24 |
PRS, Preliteracy Rating Scale.
Figure 1.
Least square means with 95% CIs (error bars) for the total Preliteracy Rating Scale (PRS) and the subdomains of Early Reading and Early Writing at baseline, 24 weeks, and 48 weeks for DHH children with language gaps. Models were adjusted for expressive language levels, Shift subscale of the BRIEF-P, and annual household income. Children with no language gaps are included as a reference (bars with hash marks).
Increasing expressive language over time was significantly associated with increases in PRS total and Early Reading scores (β = 0.39 and 0.49, respectively, p < 0.009). Although the estimates were similar, expressive language was not statistically associated with increasing Early Writing scores (β = 0.28, p = 0.10). The receptive language models had similar results with Early Reading. We also found an association between the variance in receptive and expressive language with Early Writing. As expressive language improved to meet receptive levels (reducing the gap between the 2 language scores), Early Writing significantly improved (Table 3).
Better executive functioning, specifically the Shift subscale on the BRIEF-P, was associated with increasing preliteracy skills while lower annual household income (below $40,000) was linked to lower scores over time. No other BRIEF-P subscales were significant in the PRS model (p ≥ 0.20). Other factors tested, including caregiver education level, receipt of public insurance, using cochlear implants or hearing aids, and aided hearing thresholds, were not significant in the models (p > 0.2 for all). A sensitivity analysis focusing on the PRS items common between the CELF-P2 and the CELF-P3 confirmed the original findings.
Exploratory Analysis of Preliteracy by Intervention Group
No statistically significant (p > 0.05) differences were observed regarding participant characteristics between TALI and TAU groups (Supplemental Digital Content 1, http://links.lww.com/JDBP/A503). In addition, there were no statistical differences regarding the PRS scores between groups (37.4 [21.8] vs. 41.9 [23.2] respectively, p = 0.51), although the TAU Early Reading scores appeared slightly higher at baseline. To explore potential differences in score changes by intervention group, we evaluated the PRS changes between baseline and 24 weeks for each group (TALI and TAU) separately (Supplemental Digital Content 1, http://links.lww.com/JDBP/A502). Both groups showed significant (p < 0.0001) and similar growth over time in mean total PRS (15.4 vs. 12.2), Early Reading (14.9 vs. 13.1), and Early Writing (15.7 vs. 11.3). There were no statistically significant differences in the change scores between groups, although children in the TALI seemed to have slightly higher mean changes compared with those in TAU.
DISCUSSION
Our findings demonstrate that improvements in preliteracy skills among young DHH children are associated with improving language skills, stronger executive functioning, and increased household income. Young DHH children with language delays initially had significantly lower preliteracy skills compared with their peers without delays. However, they showed substantial improvements in these skills, which corresponded with their language development. Remarkably, children with language gaps who received therapy appeared to “catch up” to baseline preliteracy performance of those without gaps within 24 weeks, highlighting the potential impact of language interventions on foundational academic skills. For DHH children, developing reading skills may be challenging because of various barriers. Therefore, understanding early literacy growth is crucial for setting realistic expectations and developing effective strategies for continued improvement.
The Literacy Gap in DHH Children
Improving literacy levels has consistently been recognized as a critical need for DHH children. Longitudinal research indicates that even when early literacy skills in DHH students are age- or grade-appropriate, a literacy gap emerges as they age into older grades.15–17 This widening gap may be because of higher order language and reading comprehension skills required for grade-level material.18 Most studies focused on literacy have not accounted for language growth or the language proficiency of students at the time of literacy assessments, which may be a contributing factor to this observed disparity. Our findings indicate that enhanced language abilities significantly drive the development of preliteracy skills. Children with commensurate language had significantly higher preliteracy levels than their language-delayed peers, further emphasizing the critical role of language in preliteracy development. Therapy targeting language skills has significantly supported preliteracy growth in our cohort (Fig. 1). This underscores the importance of continuously monitoring language as a key contributor to reading proficiency and integrating early literacy skills into language intervention models. Focusing on language as a component of early literacy could help bridge the gap in early reading attainment.
Role of Language in Literacy Development
Our research aligns with existing literature that underscores the critical role of expressive language and vocabulary in the development of literacy in DHH students. Previous studies have established a connection between language proficiency, vocabulary, and phonological awareness, with alphabetic or print knowledge19–21 Our findings reinforce this link and demonstrate that growth in receptive and expressive language (not simply vocabulary) is significantly associated with the advancement of preliteracy skills, specifically early reading. Both receptive and expressive language skills form the foundation for literacy. Receptive language, which involves understanding and processing language, is fundamental for literacy, enabling children to comprehend the content of stories, follow instructions, and engage reciprocally in conversations. Strong expressive language skills enable children to effectively express their understanding and communicate their thoughts about the reading material. We observed a stronger connection between early writing and expressive language over receptive language, which may be because writing and expressive language both support the expression of ideas. In addition, closing the gap between receptive and expressive language seems to play an important role in early writing development, as our analysis has shown. When DHH children have commensurate receptive and expressive language abilities, they have a more holistic understanding and use of language. These foundational language skills are critical for preliteracy skill development and preparing DHH children for later conventional reading instruction. Ultimately, our findings emphasize the importance of establishing a strong language foundation early on, which serves as a critical underpinning for subsequent developmental areas.
Challenges in Literacy Research for DHH Children
Research on literacy among DHH students faces several challenges. The heterogeneity in study populations, including types of amplification, communication strategies, and educational settings,22 hinders comparisons. Variability in predictive variables and literacy measurement tools further make comparisons of results across studies challenging.18 Many studies apply reading theories designed for hearing children, focusing on phonological awareness and reading fluency.23 Other research explores interventions such as visual phonics and cued speech to support phonological development in children with limited acoustic access to phonemes.23 Some studies advocate for whole-word or top-down reading approaches,18,24 noting that proficient DHH readers may not always have strong phonological awareness. Ultimately, robust language skills are essential for literacy, regardless of communication modality,20,25 but these skills alone do not guarantee reading proficiency.3
Correlation Between Executive Function and Preliteracy Skills
We found significant correlations between several executive function subscales on the BRIEF-P (e.g., Working Memory, Inhibit, Shift) and PRS scores, with higher BRIEF-P scores (indicating more challenges) being associated with lower PRS scores. However, only the Shift scale remained in the multivariable models. We believe that working memory’s significant role in language development26 means its relationship with preliteracy is likely mediated through language. The Shift subscale measures a child’s ability to transition between situations or tasks and adapt to changing demands, diverting attentional resources as appropriate.27 Children need to shift their attention and adapt to new information quickly as they read and learn to read. This is important because literacy development often requires problem-solving, such decoding new words or understanding the story context. More research is necessary to better evaluate the role of executive functioning in literacy to better support DHH literacy development.
Impact of Socioeconomic Factors on Preliteracy
We noted a relationship between household income and preliteracy skills, with lower skills associated with lower income. It is possible that income may serve as an indicator of social determinants of health that may affect reading abilities. Social determinants such as parental education, household affluence, or environmental indices of deprivation have all been explored as potentially significant factors for language acquisition.28 For DHH children, socioeconomic status has been linked to language development, although the precise role remains unclear. Future research should prioritize identifying malleable factors and strategies to better support families.
Exploratory Analysis of TALI Versus TAU
Our exploratory analysis did not show statistically significant differences in preliteracy skill growth between children who received TALI and those who received TAU (Supplemental Digital Content 1, http://links.lww.com/JDBP/A502). However, the original trials were not designed to evaluate preliteracy skill development, so we lacked the statistical power to test these differences among 3- to 5-year-old DHH children. Despite this, our results suggest that children in the TALI group may experience greater gains in preliteracy skills, including early reading and writing. The PRS Early Writing skills include tasks like copying shapes, writing their names, writing 5 or more letters, and self-correcting errors. The TALI uses AAC, which can promote literacy by enhancing phonological awareness, supporting visual representation of language, and encouraging recognition of word structures and patterns through multimodal input.29 AAC devices also enable children to systematically practice sequencing, grammar, syntax, print concepts, spelling, and sentence structure systematically, which are foundational for writing skills. In addition, co-constructing written messages with AAC may support the development of written practices.
More research is needed to understand the role of AAC in early literacy development for DHH children. High-tech AAC technology, such as tablets, act as a language-teaching tool, offering stationary and spatially based visual supports with repeated listening opportunities for key aspects of verbal language that are often challenging for DHH children (e.g., low-emphasis language constructs, word endings, verb tense). TALI’s approach may provide a unique advantage in fostering emerging literacy by enhancing language development. Multisensory tools, with both auditory and visual input, may also benefit literacy development. By leveraging auditory, visual, and tactile feedback, TALI may offer a more accessible comprehensive framework for early reading and writing than traditional speech-language therapy strategies.
Limitations
This research had several limitations. Data analyzed for our research question were collected as part of 2 broader trials designed to target language development and not preliteracy. Nonetheless, both contributing trials shared the same participant inclusion and exclusion criteria and had comparable randomization schemes. The assessment approaches were uniform across both studies, incorporating valid measures of preliteracy skills through parent report. Our preliteracy tool was designed for screening, not diagnosing reading difficulties or disorders. However, early literacy screening is crucial for DHH children. Integrating literacy development into language therapy is a key part of a speech-language pathologist’s role, especially for DHH children who are at high risk for delays in both areas.30 We lacked data on parent engagement, which could affect outcomes. The study was not designed to detect pre-post intervention preliteracy differences. Thus, the available sample size limited our power to assess the impact of the intervention groups (TALI vs. TAU). However, our exploratory analysis suggested potential group differences, guiding future research on early literacy skill development in DHH children. Despite these limitations, the study’s insights will inform future research aimed at improving literacy in DHH children.
CONCLUSION
Language serves as a foundation for nurturing the development of preliteracy skills. The TALI program has been shown to foster both expressive and receptive language in young DHH children. There is a likelihood that bolstering language skills lays a solid groundwork for early literacy development. The assessment of preliteracy in young DHH children through objective measures is an important next step. It is essential to track the literacy development of DHH children over time because literacy skills progress and a single assessment may not reflect future achievements or skills. Moreover, reading requires direct teaching and the limited evidence for effective reading interventions that are tailored to DHH children has significant implications for educational practices. Therefore, a thorough evaluation of targeted language-based, preliteracy and reading intervention strategies is needed to enhance the long-term academic trajectory of DHH children.
Supplementary Material
Footnotes
National Institute on Disability, Independent Living, and Rehabilitation Research (90IF0122) and in part by the National Institute on Deafness and Other Communication Disorders (1R01DC018550) and the National Institutes of Health Clinical and Translational Science Award Program (2UL1TR001425-05A).
The authors declare no conflict of interest.
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