Investigating Morphosyntactic Patterns and Phonological Memory in Children With ASD and DLD

Abstract

Purpose

This study explored the morphosyntactic characteristics of Hebrew-speaking children with autism spectrum disorder (ASD) and developmental language disorder (DLD) as well as the associations between morphosyntactic skills and phonological memory.

Methods

Eighty Hebrew-speaking preschool children aged 5-to-6 years were assessed. All participants had nonverbal intelligence within average range IQ > 85. Language abilities were assessed using the Hebrew Goralnik test, which evaluates naming, articulation, comprehension, sentence imitation, expressive language, and storytelling skills. Morphosyntactic skills were assessed using the Katzenberger Hebrew Language Assessment test (KHLA). This test assessed the following language skills: (a) inflecting verbs for the past and future tense; (b) using the same verb in two verb-derivation patterns; (c) inflecting plural forms with changing stems and/or irregular suffixes; (d) deriving singular forms from nouns with irregular plural suffixes; (e) inflecting the plural adjectives of irregular inflected nouns; and (f) deriving consequential adjectives from a verb. In addition, phonological memory for nonsense words and syllables was assessed using the Shatil test.

Results

Typically developing (TD) children achieved the highest KHLA and Shatil scores. One-way ANCOVAs controlling for nonverbal intelligence revealed significant group differences. Pairwise comparisons demonstrated that TD outperformed ASD-Language- normal (ASD-LN), ASD-Language-Impaired (ASD-LI), and DLD on the KHLA and phonological memory tasks. Associations were found between KHLA and Shatil scores in ASD-LI and DLD, suggesting that morphosyntactic skills are linked to phonological memory in these groups. Hierarchical regression analysis across all groups (n = 80) revealed that phonological memory contributes an additional 11% to the variance of morphosyntactic skills (KHLA) beyond the effects of language abilities.

Conclusion

These results highlight differences in morphosyntactic skills among subgroups of children with TD, ASD-LN, ASD-LI, and DLD that are associated with difficulties in phonological memory, especially in children with ASD-LI and DLD.

Keywords

ASD-LN ASD-LI DLD morphology

Introduction

Two well-known neurodevelopmental disorders that affect language are developmental language disorder (DLD) and autism spectrum disorder (ASD). Both conditions impact academic, social, and emotional development, but differ in their primary characteristics: DLD involves persistent language difficulties without hearing, neurological, or motor deficits (Bishop, 2017; Bishop et al., 2016; Norbury et al., 2024), while ASD is defined by challenges in social communication and restricted or repetitive behaviors (American Psychiatric Association, 2022; Bottema-Beutel et al., 2021). Within ASD, there is substantial heterogeneity, with some children presenting with language impairments (ASD-LI) and others exhibiting language within the typical range (ASD-LN) (Grzadzinski et al., 2013; Kjelgaard & Tager-Flusberg, 2001; Lord & Jones, 2012; Roberts et al., 2004; Schaeffer et al., 2023).

Morphosyntactic Abilities in DLD and ASD

Children with DLD consistently demonstrate morphosyntactic difficulties, such as omission or simplification of morphemes, tense and agreement errors, and challenges with pluralization and pronoun use (Calder et al., 2022; Castilla-Earls et al., 2020; Güven & Leonard, 2023; Leonard, 2014; Moraleda-Sepúlveda & López-Resa, 2022; Restrepo & Gutierrez-Clellen, 2001; Rice & Wexler, 1996). These difficulties have been documented across languages: in English (Calder et al., 2021, 2023; Leonard, 2014; Rice & Wexler, 1996), Spanish (Castilla-Earls et al., 2020; Restrepo & Gutierrez-Clellen, 2001), Swedish (Reuterskiöld et al., 2021), Turkish (Güven & Leonard, 2023), and Arabic (Alharbi et al., 2025). This body of evidence suggests that morphosyntactic deficits may serve as a cross-linguistic clinical marker of DLD.

Similarly, children with ASD-LI often show comparable morphosyntactic difficulties, while ASD-LN generally perform closer to typically developing (TD) peers (Huang & Finestack, 2020; Kjelgaard & Tager-Flusberg, 2001; Roberts et al., 2004). For example, children with ASD-LI may omit tense marking, struggle with auxiliary and copular forms, and simplify complex syntactic structures (Bartolucci et al., 1980; Brynskov et al., 2017; Meir & Novogrodsky, 2020; Roberts et al., 2004; Sukenik & Friedmann, 2018; Tuller et al., 2017). Cross-linguistic research indicates that ASD-LI and DLD share some difficulties. In English, these include sentence repetition (Lloyd et al., 2006), receptive and expressive language abilities (Loucas et al., 2008), grammatical development in toddlers (Ellis Weismer et al., 2011), limited use of prepositional clauses, passive constructions, relative clauses, reflexive pronouns, Wh-clauses, and infinitives (Huang & Finestack, 2020). Similar patterns have also been observed in French, where both groups demonstrate comparable challenges in producing Wh-questions (Prévost et al., 2017). However, to the best of our knowledge, no study to date has directly compared the morphosyntactic abilities of children with DLD, ASD-LI, and ASD-LN in Semitic languages. This gap is particularly important, as Semitic languages are characterized by a root-and-pattern morphology and non-linear inflectional and derivational processes that pose challenges that differ from those of Indo-European languages. Addressing this gap in Hebrew therefore offers a unique opportunity to evaluate whether the similarities and differences reported for other languages extend to a typologically distinct system.

The Case of Hebrew

As a Semitic language, Hebrew has a rich morphological system, including root-and-pattern derivation (e.g., the root k-t-v yielding katáv “he wrote,” ktiváh “writing,” mikhtáv “letter”), extensive verb inflection for person, gender, number, and tense (e.g., hu rats “he runs” vs. hi rátsa “she ran”), and productive noun and adjective formation (e.g., gadól “big” → gdolím “big [plural],” simlá “dress” → smalót “dresses”) (Berman, 1981; Schwarzwald, 1998). These derivations are organized within systematic morphological templates, namely, the verb patterns (binyanim), such as paál (the basic or simple active pattern), piél (an intensive or causative pattern), hitpaél (a reflexive pattern), and the nominal patterns (mishkalim) that determine the structure of nouns and adjectives (e.g., the template miCCáC yields mikhtáv “letter/” and CaCóC, which yields gadól “big”). These patterns provide regular means for word formation and have semantic as well as syntactic functions. Such characteristics render Hebrew a particularly valuable testing ground for investigating morphosyntactic acquisition in children. The interplay of roots with verb and nominal patterns creates a complex system that requires children to simultaneously acquire lexical items, internalize abstract morphological templates, and apply them productively across the lexicon (Berman, 1981; Ravid & Schiff, 2006). The rich inflection paradigm, with distinctions in person, gender, number, and tense, further challenges learners to master agreement relations and verb conjugations at an early age (Berman, 1981, 1985).

Prior studies of Hebrew-speaking children with DLD aged 4 to 6 years have demonstrated significant challenges with verb inflections (Dromi et al., 1993, 1999; Leonard et al., 2000; Leonard & Dromi, 1994). Consistent with this, Hebrew-speaking children with ASD and co-occurring language impairment aged 4;6–9;2 years simplify complex syntactic structures and show difficulty with embedded clauses (Meir & Novogrodsky, 2020). Among adolescents aged 9;0–18;0 years, those with ASD and those with DLD perform comparably on syntactic tasks but exhibit different error patterns, suggesting distinct underlying mechanisms (Sukenik & Friedmann, 2018). However, despite these insights into morphology and syntax, no previous study has systematically examined both inflectional and derivational processes in nouns and verbs among Hebrew-speaking preschool children with DLD and ASD. Given that these skills may be linked to phonological memory, it is important to consider this domain as well.

Phonological Memory in Children With DLD and ASD

In their seminal study, Baddeley and Hitch (1974) proposed the working-memory model, which consists of a central control system, the central executive component—responsible for managing attention—and two supporting subsystems, namely, the phonological loop, which stores verbal and phonological information, and the visuospatial sketchpad, which stores visual and spatial information. Phonological memory refers to the ability to temporarily store and recall the phonological (sound-based) aspects of language, such as words or syllables. Difficulties with phonological memory are considered a core factor contributing to challenges in language acquisition (Baddeley, 2003; Gathercole, 2006).

The capacity of the phonological loop is most accurately assessed by storage of verbal information, that is, forward digit span, word and non-word repetition (NWR) (Barrouillet et al., 2007). Unlike forward digit span and word repetition, NWR and pseudoword repetition does not involve retrieving familiar words from long-term memory, which could support storage in the phonological loop (Hulme et al., 1991). NWR is considered an important clinical marker for DLD across different languages, including English (e.g., Bishop et al., 1996), Cantonese (Fu et al., 2024), Italian (Bortolini et al., 2006; Dispaldro et al., 2013), and Swedish (Kalnak et al., 2014). NWR effectively distinguishes children with DLD from TD peers (Kalnak et al., 2014; Poll et al., 2010).

Previous studies have suggested that phonological memory plays a crucial role in the language acquisition of children with DLD and is closely linked to grammar acquisition (Delage & Frauenfelder, 2020; Delcenserie et al., 2021; Dispaldro et al., 2013; Torrens & Yagüe, 2018). However, less is known about phonological memory in children with ASD-LI. Some studies indicate that children with ASD-LI exhibit reduced NWR performance, similar to findings in children with DLD (Abd El-Raziq et al., 2025; Jokel et al., 2021; Kjelgaard & Tager-Flusberg, 2001; Roberts et al., 2004). This suggests a possible shared impairment for ASD-LI and DLD. For instance, one study comparing children with ASD-LI, DLD, and TD peers on an NWR task found that children with ASD-LI performed similarly to those with DLD, differing from both ASD children without language impairment and TD controls (Tager-Flusberg, 2015). These findings support the idea that a subgroup of children with ASD also has DLD (Harper-Hill et al., 2013; Tager-Flusberg, 2015).

In contrast, other studies challenge this hypothesis, reporting that children with ASD-LI outperform those with DLD on NWR tasks, particularly in multisyllabic words. These findings suggest that phonological memory deficits may be more pronounced in DLD than in ASD-LI (Riches et al., 2011; Whitehouse et al., 2008; Williams et al., 2013). Given these mixed findings, further research is needed. In Hebrew-speaking children with DLD, the role of NWR remains underexplored. Investigating NWR in Hebrew-speaking children with DLD and ASD-LI and the association with morphosyntactic abilities could provide valuable insights into the nature of language impairment in these populations, contributing to a deeper understanding of cross-linguistic diagnostic markers.

The Present Study

The aims of the current study are to assess morphosyntactic characteristics and phonological memory across the following four groups: children with DLD, children with ASD with language impairment (ASD-LI), children with ASD with normal language development (ASD-LN), and TD children. By comparing these groups, we aim to determine whether deficits in these domains are shared across clinical categories or are specific to certain populations, thus contributing to a more precise characterization of language impairment in ASD and DLD.

An additional key objective of this study is to investigate the extent to which phonological memory is associated with morphosyntactic performance in each group. Given that phonological memory is known to support language acquisition, we hypothesize that children with weaker phonological memory skills will struggle more with morphosyntactic tasks. However, differences between groups may reveal distinct underlying impairment mechanisms. For instance, if phonological memory is related to morphosyntactic performance in both DLD and ASD-LI, this would suggest a shared cognitive basis for their language deficits. Conversely, if ASD-LI exhibits a pattern that differs from that of DLD, this may indicate that language difficulties in ASD arise from broader neurodevelopmental differences rather than limitations in phonological memory.

We hypothesized that (a) children with DLD and ASD-LI would demonstrate reduced morphosyntactic abilities compared to TD children and children with ASD-LN, (b) children with DLD and ASD-LI would demonstrate reduced phonological memory compared to TD children and children with ASD-LN, and (c) phonological memory would be positively correlated with morphosyntactic abilities across all groups, with weaker phonological memory predicting greater difficulties in morphosyntax. We predicted that this relationship would be strongest in the DLD and ASD-LI groups, suggesting a shared cognitive basis for language deficits in these populations.

Importantly, although morphosyntactic and phonological memory deficits in DLD and ASD-LI have been reported for other languages, the present study offers a novel empirical and theoretical contribution in several ways. First, it is the first systematic comparison of morphosyntactic abilities and phonological memory across DLD, ASD-LI, ASD-LN, and TD groups in Hebrew, a morphologically complex Semitic language. Second, by examining both inflectional morphology (morphosyntactic) and derivational morphology (lexical), the study captures a broader range of linguistic vulnerabilities than has been addressed in most prior work. Finally, by linking phonological memory performance to morphosyntactic outcomes, the study provides new evidence on the cognitive aspects related to morphosyntactic difficulties as well as supporting cross-linguistic diagnostic markers for distinguishing subgroups of children with neurodevelopmental disorders.

Method

Participants

This study included 80 monolingual Hebrew-speaking children (ages 63.6–72 months), divided into four groups of 20: ASD-LN, ASD-LI, DLD, and TD children as shown in Table 1. Gender distribution was comparable across groups (χ²(3) = 5.27, p = .15). No significant age differences were observed between groups [F(3, 76) = 2.16, p = .09].

Table 1.

Participants’ Characteristics.

Group	N	Girls	Boys	Age Range (Months)	Mean age (Months)	SD
ASD-LN	20	7	13	63.6–72	68.65	1.49
ASD-LI	20	3	17	63.6–72	66.55	3.43
DLD	20	9	11	63.6–72	67.25	3.14
TD	20	9	11	63.6–72	66.60	3.39

Note. TD = typically developing children; ASD-LN = children with ASD and normal language development; ASD-LI = children with ASD and language impairment; DLD = children with developmental language disorder.

Participants with ASD and DLD were recruited through special education programs and referrals by speech-language pathologists (SLPs) upon obtaining parental consent. ASD diagnoses were confirmed by psychiatric specialists using DSM-5 criteria (American Psychiatric Association, 2022). DLD diagnoses were established jointly by a pediatrician and a licensed SLP following standard clinical guidelines. As part of the diagnostic process, all children in the DLD group underwent evaluations to rule out ASD, ensuring that the DLD group did not include children with ASD. All children had normal vision, hearing, and nonverbal intelligence, and no history of neurological difficulties, as reported by parents. In addition, children's articulation was typical of their age according to their SLPs and the only speech impairment observed by the clinicians was related to sigmatism. TD children were recruited by means of social media advertisements targeted at SLPs and the public and word-of-mouth referrals. The TD children were verified to be free of neurodevelopmental issues through parental reports obtained via a developmental questionnaire, language assessments, and non-verbal intelligence tests.

Following recruitment, the children referred underwent a comprehensive reassessment involving two one-hour sessions. The first session focused on clinical diagnostic procedures, while standardized background tests were administered in the second session, providing detailed nonverbal intelligence and language ability data. This research was approved by Tel Aviv University's Research Ethics Committee (No. 0006493-2) and adhered to the Declaration of Helsinki. Parental consent was obtained for all participants.

Clinical Diagnostic Procedure

Test Materials and Procedure

The Katzenberger Hebrew Language Assessment for Preschool Children (KHLA).

The KHLA. It is a standardized test developed to assess the language development of Hebrew-speaking preschoolers (Katzenberger & Meilijson, 2014). For the present study, we used the morphosyntactic subtest, which comprises six tasks assessing verb inflection (tense, person, number, gender), verb derivation patterns (binyanim), noun morphology (singular/plural, including irregular forms), noun–adjective agreement, and derivational morphology (e.g., forming adjectives from verbs). Scoring reflects both grammatical accuracy and appropriateness relative to typical adult usage in Hebrew. Further details of the test design and validation are provided in Katzenberger and Meilijson (2014).

Short-Term Memory Assessment. The phonological memory assessment was conducted using two subtests from the Shatil test specifically designed to evaluate short-term memory capabilities, namely, syllable span and pseudoword repetition (Shatil, 2002). The syllables and pseudowords were constructed in accordance with the rules of the Hebrew phonological system.

Syllable Span. This subtest assesses the participant's ability to retain and reproduce sequences of syllables. It includes strings of nonsense CVC (consonant-vowel-consonant) syllables, with string lengths varying from one to five syllables (e.g., /doz-mel-pen/). Two consecutive trials are presented for each length. The child is asked to repeat the strings of words. Testing was discontinued if the participant failed both trials at a given length. One point is awarded for each correctly recalled string, with a total of 20 strings provided for the task.

Pseudoword repetition. This subtest evaluates the participant's ability to accurately repeat pseudowords, following the framework developed by Gathercole and colleagues (Gathercole et al., 1994). The subtest comprises 40 individually presented pseudowords featuring various phonological patterns, each consisting of two to three syllables (e.g., shnila, pikayon, tislofet). Each pseudoword adheres to the rules of Hebrew phonology. One point is assigned for each precise repetition by the participant.

Background Tests

Cognitive Assessment. Nonverbal intelligence was assessed using Raven's Colored Progressive Matrices (Raven et al., 1995), a standardized measure of nonverbal reasoning and fluid intelligence. The task requires children to identify the missing element in visual patterns, which renders it suitable for evaluating children with language difficulties. Only children with IQ scores within the average range (>85) were included in this study.

Language Assessment. To identify participants and determine group classification (language impaired vs. unimpaired), we used the standardized Goralnik screening test (Goralnik, 1995).

Data Analysis

All analyses were performed using the Statistical Package for the Social Sciences (SPSS) version 29. The variables of the Goralnik, KHLA, and the Shatil memory subtests for syllable span and pseudoword repetition were normally distributed with Z-scores of skewness and kurtosis values between −2.58 and 2.58 for the four groups. The Raven scores were not normally distributed; therefore, Spearman's correlations were calculated between Raven and the other variables. Significant correlations were found between Raven and KHLA (r_s = .48, p < .001) and between Raven and pseudoword repetition (r_s = .54, p < .001) and syllable span (r_s = .42, p < .001).

An independent samples Kruskal-Wallis test was performed on the Raven scores across groups. A one-way analysis of variance (ANOVA) was conducted on language scores (Goralnik) across groups. A one-way ANCOVA was performed to assess the differences between the groups in the KHLA. A one-way MANCOVA was performed to examine the differences between groups in the subtests of the KHLA and memory tasks, with the Raven standard scores as a covariate. The following pairwise comparisons were adjusted using the Bonferroni correction (p = .05). A hierarchical linear regression standardized for Raven was performed to assess the contribution of the language (Goralnik) and memory tests on the variance of KHLA.

Results

Background Measures

A summary of nonverbal intelligence, and language abilities of children with ASD-LN, ASD-LI, DLD, and TD is presented in Table 2.

Table 2.

Descriptive Statistics of Participant Age, RAVEN's Progressive Matrices Scores, and Goralnik Language Scores.

	Group
	ALN	ALI	DLD	TD
	M (SD)	M (SD)	M (SD)	M (SD)	χ²(3)/ F (3, 76)	p	η²
RAVEN (Standard scores)^a	124.4(1.85)	113 (7.55)	110.40 (8.78)	122.95(4.71)	41.49	<.001	.51
GORALNIK (Z scores)^b	0.62 (0.74)	−2.57 (1.04)	−2.23 (0.89)	0.54 (0.68)	82.56	<.001	.77

Note. N = 80 (n = 20 for each group). TD = typically developing children; ASD-LN = children with ASD and normal language development; ASD-LI = children with ASD and language impairment; DLD = children with developmental language disorder.

An independent samples Kruskal-Wallis test was performed on the RAVEN scores.

A one-way analysis of variance (ANOVA) was conducted on the Goralnik scores.

Nonverbal intelligence. An independent samples Kruskal-Wallis test performed on the Raven scores revealed significant differences across the four groups, χ² (3)= 41.49, p < .001, η² = 0.51. Post-hoc tests with Bonferroni correction (p = .05) revealed that the DLD and ASD-LI scores were significantly lower than those of the children with ASD-LN and TD (p < .001). No significant differences were found between DLD and ASD-LI and between TD and ASD-LN.

Language measure. A one-way ANOVA conducted on language scores (Goralnik) revealed significant differences across the four groups, F(3, 76) = 82.56, p < .001, η² = 0.77. Post-hoc tests with Bonferroni correction (p = .05) revealed that the DLD and ASD-LI scores were significantly lower than those of the children with ASD-LN and TD (p < .001). No significant differences were found between DLD and ASD-LI and between TD and ASD-LN.

Test Results

KHLA

The mean scores of the KHLA-adjusted and unadjusted for nonverbal intelligence are presented in Table 3. The highest unadjusted scores were found for the TD group (M = 33.20), followed by the ASD-LN (M = 29.55), DLD (M = 23.95), and ASD-LI groups (M = 21.55) with the lowest scores.

Table 3.

Summary of Test Results. Mean and Standard Deviation for the KHLA Grammar Test and Subtests are Presented for Each Group, As Well As Adjusted Means and Standard Errors for Non-verbal Intelligence (RAVEN).

	Group
	TD		ASD-LN		ASD-LI		DLD
	M(SD)	M(SE)^a	M(SD)	M(SE)^a	M(SD)	M(SE)^a	M(SD)	M(SE)^a	F (3, 75), p, η²	p	η²
KHLA	33.20 (2.68)	32.56(1.17)	29.55 (3.73)	28.74 (1.23)	21.55 (6.40)	22.12 (1.15)	23.95 (5.65)	24.83 (1.25)	11.85, <.001, .32
Subtest 1	2.88 (0.36)	2.85 (0.22)	2.48 (0.68)	2.44 (0.23)	1.48 (1.19)	1.50 (0.21)	1.92 (1.05)	1.97 (0.23)	5.79, .001, .19
Subtest 2	9.75 (1.12)	9.55 (0.34)	8.52 (1.23)	8.26 (0.36)	6.40 (1.47)	6.58 (0.34)	6.83 (1.80)	7.11 (0.37)	11.40, <.001, .31
Subtest 3	4.75 (0.64)	4.73 (0.22)	4.27 (0.60)	4.25 (0.23)	3.33 (1.25)	3.34 (0.22)	3.67 (1.00)	3.70 (0.24)	5.79, .001, .19
Subtest 4	3.88 (0.28)	3.83 (0.20)	3.95 (0.22)	3.89 (0.21)	3.03 (1.42)	3.07 (0.20)	3.52 (0.82)	3.59 (0.22)	2.92, .039, .11
Subtest 5	7.55 (0.76)	7.43 (0.42)	6.67 (1.58)	6.53 (0.44)	5.03 (2.58)	5.13 (0.41)	6.00 (1.38)	6.16 (0.44)	4.74, .004, .16
Subtest 6	4.40 (0.75)	4.15 (0.32)	3.65 (1.46)	3.33 (0.33)	2.30 (1.34)	2.52 (0.31)	1.90 (1.63)	2.25 (0.34)	5.24, .002, .17

Note. ^aAdjusted for RAVEN, Subtest 1 = verb inflection, Subtest 2 = verb derivation, Subtest 3 = inflection of plural forms, Subtest 4 = deriving singular forms from nouns with irregular plural suffixes, Subtest 5 = inflecting the plural adjectives of irregular inflected nouns, Subtest 6 = derivation of consequential adjectives from a verb.

A one-way ANCOVA was conducted to examine the effect of group on KHLA while controlling for nonverbal intelligence (Raven standard scores). The analysis revealed a statistically significant group effect, F(3, 75) = 11.85, p < .001, η² = .32. Post-hoc analysis with Bonferroni adjustment revealed that the TD group scored higher than the ASD-LI and DLD groups (p < .001). The scores of the ASD-LN group were higher than those of the ASD-LI (p = .003). No significant differences were found between TD and ASD-LN, and between ASD-LI and DLD or between ASD-LN and DLD.

The mean scores for the six KHLA tasks across participant groups are shown in Table 3. A one-way MANCOVA was performed to examine group differences, revealing a significant main effect in the simultaneous test, Wilks’ λ = 0.56, F(18, 198) = 2.51, p < .001, η² = 0.18. The main effects for each task are presented in Table 3. Main effects for group were found for all the subtests. For Task 1 (verb inflection), the TD children scored significantly higher than the ASD-LI group (p < .001), and the ASD-LN group also outperformed the ASD-LI group (p = .04). In Task 2 (verb derivation), TD children again had significantly higher scores than the ASD-LI group (p < .001), and the DLD group (p < .001). In addition, the ASD-LN group had higher scores than the ASD-LI group (p = .014).

In Task 3 (plural inflection), TD children scored significantly higher than the ASD-LI group (p < .001) and the DLD group (p = 0.03). For Task 4 (deriving singular forms), all comparisons were not significant. In Task 5 (inflecting plural adjectives of irregular nouns), TD children scored significantly higher than the ASD-LI group (p = .002). Finally, for Task 6 (deriving consequential adjectives from a verb), TD children achieved significantly higher scores than those with ASD-LI (p = .007) and those with DLD (p = .002). Additional comparisons were not significant.

Shatil

The mean scores for the Shatil subtests, including pseudoword repetition and syllable span, both adjusted and unadjusted for nonverbal intelligence, are presented in Table 4. For non-word repetition, the TD group achieved the highest unadjusted mean score (M = 37.45), followed by the ASD-LN group (M = 36.85), the ASD-LI group (M = 28.30), and the DLD group, which had the lowest score (M = 25.65). For syllable span, the TD group again had the highest unadjusted mean score (M = 12.80), followed by the ASD-LN group (M = 9.70), the DLD group (M = 8.50), and the ASD-LI group, which had the lowest score (M = 7.70).

Table 4.

Summary of Test Results. Mean and Standard Deviation for the Shatil Pseudoword Repetition and Syllable Span Subtests are Presented for Each Group, As Well As Adjusted Means and Standard Errors for Non-verbal Intelligence (RAVEN).

	Group
	TD		ASD-LN		ASD-LI		DLD
	M(SD)	M(SE)^a	M(SD)	M(SE)^a	M(SD)	M(SE)^a	M(SD)	M(SE)^a	F (3, 75),p, η²
Non-word	37.45 (2.46)	35.61 (1.84)	36.85 (3.12)	34.50 (1.93)	28.30 (10.61)	29.94 (1.82)	25.65 (10.88))	28.20 (1.97)	2.33, 08, . 09
Syllables	12.80 (1.99)	12.37 (0.65)	9.70 (2.83)	9.15 (0.68)	7.45 (2.70)	7.83 (0.64)	7.70 (3.11)	8.29 (0.69)	9.13, . < .001, .27

Adjusted for RAVEN.

A one-way MANCOVA was performed to examine group differences while controlling for nonverbal intelligence (Raven standard scores), revealing a significant main effect in the simultaneous test, Wilks’ λ = 0.69, F(6, 148) = 4.90, p < .001, η² = 0.17. The univariate analysis did not show a statistically significant difference between groups in the pseudoword repetition task, F(3, 75) = 2.33, p = .08, η² = .09. However, the univariate analysis revealed group effects on syllable span, resulting in a statistically significant difference between groups, F(3, 75) = 9.13, p < .001, η² = .27. The post-hoc analysis with Bonferroni adjustment indicated that the TD group scored significantly higher compared to the ASD-LN group (p = .001), the DLD group (p = .001), and the ASD-LI group (p < .001). No significant difference was found for the other groups.

Associations Between Shatil and KHLA

In order to examine the associations between phonological memory and morphosyntactic skills, we looked for correlations between the Shatil memory subtests for pseudoword repetition, syllable span, and the KHLA for each group as summarized in Figures 1 and 2.

Figure 1.

Associations between Pseudoword Repetition and KHLA Morphosyntax test.

Figure 2.

Associations between Syllable Span and KHLA Morphosyntax test.

The results demonstrated medium to strong correlations only in the groups of DLD (r_s = .78, .71, p < .001, for pseudoword repetition and syllable span, respectively) and ASD-LI (r_s = .39, p = .04, and r_s = .65, p = .001 for pseudoword repetition and syllable span, respectively)

Hierarchical Regression Analysis

A hierarchical multiple regression model was applied to the sample of the four groups of participants. The hierarchical model was run to determine whether adding the pseudoword repetition and syllable span improved the prediction of KHLA beyond nonverbal intelligence (Raven) and language abilities (the Goralnik test). The results are summarized in Table 5.

Table 5.

Regression Analysis for Predicting KHLA Performance Standardized for RAVEN.

Variable	KHLA
	Model 1				Model 2
	B (SE)	β	t	p	B (SE)	β	t	p
Constant	−9.11		−1.28	.20	0.71		−0.11	.92
Language scores (Goralnik test)	.24	.71	6.72	<.001	.16	.47	4.49	<.001
Pseudoword Repetition Syllable Span					.21.43	.29.22	3.072.36	.001>.02
R²	.53				.64
F	43.85***				33.90***
ΔR²	.53				.11
ΔF	45.11***				11.77 ***

Standardized for RAVEN.

***p < .001.

In Model 1, overall language scores on the Goralnik test significantly predicted morphosyntactic scores of the KHLA (β = .71, t = 6.72, p < .001), indicating that stronger language abilities were associated with higher KHLA scores. This model explained 53% of the variance in KHLA scores (R² = .53, F(2, 77) = 43.85, p < .001), suggesting that language proficiency is a key determinant of KHLA outcomes. Notably, these effects were observed after accounting for nonverbal cognitive abilities, as performance was standardized using Raven percentile scores.

In Model 2, the addition of pseudoword repetition and syllable span significantly improved the model's explanatory power. While language scores remained a significant predictor (β = .47, t = 4.49, p < .001), both pseudoword repetition (β = .29, t = 3.07, p = .001) and syllable span (β = .29, t = 2.36, p = .02) also significantly contributed to KHLA performance. These findings indicate that phonological memory, as measured by both pseudoword repetition and syllable span, plays an important role in the morphosyntactic task of KHLA, independent of general language abilities and nonverbal intelligence.

The inclusion of pseudoword repetition and syllable span led to a statistically significant increase in explained variance (ΔR² = .11, ΔF = 11.77, p < .001), meaning that phonological memory accounted for an additional 11% of the variance in the KHLA morphosyntactic scores beyond language abilities (Goralnik). The final model explained 64% of the variance in KHLA morphosyntactic scores (R² = .64, F(4, 75) = 33.90, p < .001), reinforcing the combined importance of language and phonological memory in morphosyntactic performance on the KHLA.

These findings suggest that while language abilities remain the strongest predictor of morphosyntactic performance on the KHLA, phonological memory, provides additional explanatory power. The results highlight the significance of phonological processing skills in language development and suggest that deficits in phonological memory may contribute to lower morphosyntactic scores. Importantly, these effects were found after controlling for nonverbal cognitive abilities, confirming that the observed associations between language, phonological memory, and KHLA are not merely a reflection of broader cognitive factors.

Discussion

The present study investigated morphosyntactic abilities and phonological memory in four groups of Hebrew-speaking preschoolers: children with DLD, children with ASD-LI, children with ASD-LN, and TD peers. Our objectives were to compare these groups to clarify whether deficits are shared across conditions or are group-specific, and to determine the extent to which phonological memory contributes to morphosyntactic performance.

Morphosyntactic Abilities

In line with our first hypothesis, both the DLD and ASD-LI groups demonstrated reduced morphosyntactic abilities compared to TD children, while the ASD-LN group performed closer to TD peers. Children with ASD-LI did not differ significantly from children with DLD, but they scored significantly lower than those with ASD-LN. This pattern is consistent with earlier work showing that morphosyntactic abilities in ASD-LI resemble those of DLD (Huang & Finestack, 2020; Kjelgaard & Tager-Flusberg, 2001).

The analysis of KHLA subtests revealed that children with ASD-LI and DLD encountered difficulties across multiple domains, including verb inflection and derivation, plural inflection, and noun morphology, particularly irregular forms, as well as noun–adjective agreement and the derivation of consequential adjectives from verbs. These findings extend prior research showing that children with ASD-LI struggle with various aspects of morphosyntax (Alhassan & Marinis, 2023; Durrleman & Delage, 2016; Meir & Novogrodsky, 2023; Modyanova et al., 2017; Riches et al., 2011). Importantly, this is the first study to systematically compare Hebrew-speaking children with ASD-LN, ASD-LI, and DLD on both inflectional and derivational morphology.

Phonological Memory

Consistent with our second hypothesis, children with ASD-LI and DLD showed reduced raw scores on both pseudoword repetition and syllable repetition relative to their TD peers. These findings align with prior work linking phonological memory weaknesses to language difficulties in both DLD and ASD-LI (Delcenserie et al., 2021; Dispaldro et al., 2013; Jokel et al., 2021; Kjelgaard & Tager-Flusberg, 2001; Tager-Flusberg, 2015). Importantly, when nonverbal intelligence (Raven scores) was included as a covariate, group differences in pseudoword repetition were no longer statistically significant. This suggests that performance on the pseudoword task may rely partly on general cognitive ability rather than reflecting a strictly language-specific deficit. In contrast, significant group differences in syllable span persisted after controlling for Raven, indicating that limitations in phonological memory represent a robust, domain-specific vulnerability in ASD-LI and DLD. Notably, even the ASD-LN group performed below TD peers on syllable span, echoing previous reports that some children with ASD may exhibit subtle phonological memory weaknesses despite otherwise typical language development (Bishop et al., 1996; Jokel et al., 2021). Future longitudinal research is needed to determine whether these phonological memory vulnerabilities in ASD-LN reflect transient developmental delays or precursors of later language challenges.

The Association Between Phonological Memory and Morphosyntax

Our third hypothesis predicted a positive association between phonological memory and morphosyntactic abilities, particularly in the DLD and ASD-LI groups. This prediction was confirmed: Significant associations were observed for both pseudoword and syllable span with morphosyntactic performance, but only in DLD and ASD-LI. This finding supports models that emphasize the phonological loop as a crucial resource for grammatical learning (Baddeley, 2003; Delage & Frauenfelder, 2020; Durrleman & Delage, 2016; Tager-Flusberg, 2015). Regression analyses further showed that phonological memory accounted for variance in morphosyntactic performance beyond general language abilities, underscoring its importance as an independent predictor of morphosyntactic skills.

While our findings are consistent with prior research documenting morphosyntactic and phonological memory deficits in children with DLD and ASD-LI, the present study offers several novel contributions. First, by examining Hebrew, a Semitic language characterized by a uniquely rich system of inflectional and derivational morphology, our results extend existing evidence beyond Indo-European languages. This cross-linguistic perspective strengthens the view that morphosyntactic and phonological memory deficits represent robust cross-linguistic clinical markers rather than language-specific vulnerabilities. Second, our direct comparison of ASD subgroups revealed that children with ASD-LI performed similarly to children with DLD, whereas children with ASD-LN performed comparably to TD peers with only subtle weaknesses in syllable span. These findings refine our understanding of the heterogeneity in ASD and support theoretical distinctions between ASD with language impairment versus ASD without language impairment. Third, our regression analysis demonstrated that phonological memory explained an additional 11% of the variance in morphosyntactic performance beyond nonverbal intelligence and general language ability, underscoring the independent contribution of phonological processing to morphosyntactic development. Taken together, these findings provide important empirical support for both comorbidity models (ASD-LI as a co-occurrence of ASD and DLD-like language difficulties) and multidimensional models (language abilities distributed along continua across diagnostic groups), thereby contributing new evidence to ongoing theoretical debates (Ogundele & Ayyash, 2024; Ramírez-Santana et al., 2019; Willcutt, 2019).

Limitations

This study presents several limitations that warrant consideration. Firstly, the cross-sectional design limits our ability to establish causal relationships between phonological memory and morphosyntactic development. A longitudinal study would track these abilities over time to determine the direction of influence. In other words, although our results revealed significant associations between phonological memory and morphosyntactic performance, these findings cannot be interpreted as evidence of causality. Secondly, the reliance on standardized assessments may not fully capture the nuances of individual language profiles. Further research should incorporate measures of executive functions, such as cognitive flexibility, to account for their potential contribution to morphosyntactic abilities. Additionally, although the current findings indicate that children with ASD-LN had higher scores on the morphosyntactic abilities measure (KHLA) compared to children with DLD, this difference did not reach statistical significance. It is possible that larger sample sizes are needed to detect a significant difference.

Clinical Implications

This study reveals significant clinical implications for the assessment of children exhibiting ASD-LI and DLD as well as for efficacious interventions for these children. The overlapping cognitive profile, characterized by challenges in both morphosyntax and phonological memory, requires interventions addressing both areas. The strong correlations between these skills in preschoolers, coupled with the rapid development of language during these early years, emphasize the critical importance of early identification and intervention in both morphosyntax and phonological memory for optimal language outcomes (e.g., Roberts & Kaiser, 2015).

Footnotes

ORCID iD

Osnat Segal

Author Contributions

The first author was responsible for data collection and authored the initial draft. The second author conceived the original idea and supervised the project. She also played a key role in analyzing the results and writing the manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability

Research data supporting this publication are available upon request from the first and second author.

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