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. 2023 Sep 24;59(1):396–412. doi: 10.1111/1460-6984.12950

Do parent‐reported early indicators predict later developmental language disorder? A Raine Study investigation

Samuel D Calder 1,✉, Mark Boyes 2,3, Christopher G Brennan‐Jones 4,5, Andrew J O Whitehouse 4, Monique Robinson 4, Elizabeth Hill 3,5
PMCID: PMC10952803  PMID: 37743609

Abstract

Background

Developmental language disorder (DLD) is one of the most common neurodevelopmental conditions. Due to variable rates of language growth in children under 5 years, the early identification of children with DLD is challenging. Early indicators are often outlined by speech pathology regulatory bodies and other developmental services as evidence to empower caregivers in the early identification of DLD.

Aims

To test the predictive relationship between parent‐reported early indicators and the likelihood of children meeting diagnostic criteria for DLD at 10 years of age as determined by standardized assessment measures in a population‐based sample.

Methods

Data were leveraged from the prospective Raine Study (n = 1626 second‐generation children: n = 104 with DLD; n = 1522 without DLD). These data were transformed into 11 predictor variables that reflect well‐established early indicators of DLD from birth to 3 years, including if the child does not smile or interact with others, does not babble, makes only a few sounds, does not understand what others say, says only a few words, says words that are not easily understood, and does not combine words or put words together to make sentences. Family history (mother and father) of speech and language difficulties were also included as variables. Regression analyses were planned to explore the predictive relationship between this set of early indicator variables and likelihood of meeting DLD diagnostic criteria at 10 years.

Results

No single parent‐reported indicator uniquely accounted for a significant proportion of children with DLD at 10 years of age. Further analyses, including bivariate analyses testing the predictive power of a cumulative risk index of combined predictors (odds ratio (OR) = 0.95, confidence interval (CI) = 0.85–1.09, p = 0.447) and the moderating effect of sex (OR = 0.89, CI = 0.59–1.32, p = 0.563) were also non‐significant.

Conclusions

Parent reports of early indicators of DLD are well‐intentioned and widely used. However, data from the Raine Study cohort suggest potential retrospective reporting bias in previous studies. We note that missing data for some indicators may have influenced the results. Implications for the impact of using early indicators as evidence to inform early identification of DLD are discussed.

WHAT THIS PAPER ADDS

What is already known on the subject

  • DLD is a relatively common childhood condition; however, children with DLD are under‐identified and under‐served. Individual variability in early childhood makes identification of children at risk of DLD challenging. A range of ‘red flags’ in communication development are promoted through speech pathology regulatory bodies and developmental services to assist parents to identify if their child should access services.

What this paper adds to the existing knowledge

  • No one parent‐reported early indicator, family history or a cumulation of indicators predicted DLD at 10 years in the Raine study. Sex (specifically, being male) did not moderate an increased risk of DLD at 10 years in the Raine study. Previous studies reporting on clinical samples may be at risk of retrospective reporting bias.

What are the potential or actual clinical implications of this work?

  • The broad dissemination and use of ‘red flags’ is well‐intentioned; however, demonstrating ‘red flags’ alone may not reliably identify those who are at later risk of DLD. Findings from the literature suggest that parent concern may be complemented with assessment of linguistic behaviours to increase the likelihood of identifying those who at risk of DLD. Approaches to identification and assessment should be considered alongside evaluation of functional impact to inform participation‐based interventions.

Keywords: developmental language disorder, early identification, the Raine study

INTRODUCTION

Developmental language disorder (DLD) is one of the most common neurodevelopmental disorders. Prevalence estimates indicate DLD affects roughly 7% of the population in English‐speaking countries between the ages of 5 and 10 years (Calder et al., 2022; Norbury et al., 2016; Tomblin et al., 1997, 2003). This rate of occurrence is greater than other well‐known neurodevelopmental disorders, such as autism spectrum disorder, attention deficit/hyperactivity disorder, intellectual disability and dyslexia (McGregor, 2020). Although the recency of widespread international advocacy efforts to raise awareness of DLD is promising for increased support of those affected the condition, children with DLD have historically been under‐identified for such support (e.g., Skeat et al., 2010; Zhang & Tomblin, 2000).

The under‐identification of children with DLD poses a risk to public health, economic viability and individual well‐being, with the long‐term impacts of language disorder to educational, vocational and societal outcomes well documented. In a UK follow‐up study of 17 men in their 30s with a history severe receptive DLD in childhood, Clegg et al. (2005) found a history of DLD was associated with an increased risk of psychiatric disorder and social adaptation difficulties, including academic outcomes and educational provision, employment, independent living, relationships, family life, and receipt of state benefits and housing. Also in the UK, Conti‐Ramsden et al. (2018) found that in a study of 84 twenty‐four‐year‐olds with a history of DLD and 88 age‐matched controls, those with DLD were at increased risk of obtaining lower academic and vocational qualifications despite few differences between groups engaging with educational opportunities in adulthood. Whitehouse et al. (2009a, 2009) followed up adults who had participated in previous studies of children and found language and literacy difficulties persisted into adulthood (early 20s) where a history of language disorder was associated with pursuing vocational training for professions that do not require high levels of language and literacy proficiency. Whitehouse et al. also stressed the high level of within‐group variation which encourages individualized evaluations of those living with language disorder. In a Canadian longitudinal study of 142 individuals with DLD and 142 controls followed up at 5, 12 and 19 years, males with a history of language disorder were four times more likely to engage in delinquent and aggressive behaviour compared to controls (Brownlie et al., 2004), and females with a history of DLD were three times more likely to experience sexual assault when compared to controls (Brownlie et al., 2007). From an economic standpoint, the cost to society of language disorders in Australia is estimated to be between A$1.362 billion and A$3.308 billion per year, with most of the burden attributed to productivity losses of caring for children with language difficulties (Cronin, 2017).

There are alarming patterns of inequity to service access for children with DLD. Although there does not appear to be a significant difference in the sex distribution of children with DLD in population‐based studies (Calder et al., 2022; Norbury et al., 2016; Tomblin et al., 1997), Whitehouse (2010) conducted a meta‐analysis of sex ratio differences in family aggregation studies of DLD (then referred to as specific language impairment—SLI), and found that more males than females were identified to have DLD via direct assessment methods; however, there were no sex differences observed through indirect assessment of language. There also appears to be a referral bias favouring males in receipt of clinical services for language difficulties. Lindsay and Strand (2016) found that males with language disorder are more than twice as likely to be referred for clinical services in the UK, and Morgan et al. (2017) found males are almost twice as likely to be referred in the United States. The reasons for the disparities in service access between males and females is unclear; however, there is some evidence to suggest that language difficulties in young children are more likely to resolve in females than males (Dale et al., 2003), and males demonstrate more externalized behaviours compared to females, who may be more prone to internalize difficulties (Toseeb et al., 2017).

Early identification of DLD is critical to alleviate the potential socio‐emotional and economic burden of language difficulties and maximizes the benefits of intervention (Fan et al., 2022). An investigation of the Longitudinal Study of Australian Children identified child, parent and family factors may influence language development (Harrison & McLeod, 2010). The same study reported risk factors for speech and language impairment in 4–5‐year‐old children including being male, having ongoing hearing problems, having a more reactive temperament, having an older sibling, parents speaking a language other than English, and support for the child's learning at home. Rudolph (2017) conducted a review of epidemiological studies and found 11 case history risk factors for DLD (then SLI), specifically, which included a range of biological, prenatal, perinatal, and family history factors. Once analysed for clinical significance, however, the odds of developing DLD among children whose mothers has low maternal education, who had a low 5‐min APGAR score, were born later or male was as high as the odds as late talking predicting DLD. Prospective cohort studies published since Rudolph's review have identified perinatal and/or environmental risk factors for low language ability beyond the preschool years. These include parental education (Christensen et al., 2014; Reilly et al., 2018), socio‐economic disadvantage (Christensen et al., 2014), non‐English speaking background (Reilly et al., 2018), family history of speech/language difficulties (Christensen et al., 2014; Reilly et al., 2018), and mothers smoking while pregnant (Armstrong et al., 2017; Calder et al., 2022). Notably, most of these epidemiological studies do not find differences between males and females with language difficulties, suggesting being a male may not be identified as a risk factor in unselected samples (cf. Rudolph, 2017; Whitehouse, 2010).

Certainly, there is a need for recognizing the biological, perinatal and environmental risk factors associated with DLD services to identify vulnerable individuals who may be prioritized for clinical services. However, these factors alone cannot be leveraged to identify children with, or at risk of, language disorder. Direct assessment of language development in the early years is necessary. Yet, predicting the trajectory of language development is complex. In the large‐scale Twins Early Development Study in the UK, Dale et al. (2003) found that 44.1% of children who were identified to have language delay at 2 years of age has persistent language difficulties at 3 years, and 40.2% had persistent difficulties at 4 years. In a subsequent analysis, Bishop et al. (2003) reported that parental concern at 3 years and accessing professional support at 4 years was associated with greater heritability of language difficulties, whereas language delay at 2 years appeared to be associated with environmental influences when parents do not express concern or access professional support. The Early Language in Victoria Study has taken a programmatic approach to tracking the development of language in an Australian population sample. Findings from this longitudinal study indicated at 2 years, 19% of the sample were classified at late talkers; however, 14% (73.7% of late talkers at 2 years) spontaneously caught up to their peers at 4 years, while the remaining 5% of late talkers plus 6% of the typical talkers (7.4% at 2 years) went on to have low language at 4 years, totalling 11% of the entire sample (Reilly et al., 2018). These findings emphasize the complexity and individual variability of language development in early childhood, and stress that late talking is not necessarily a reliable indicator of later language difficulties.

Recent literature has highlighted approaches to addressing the nuances of early identification of language difficulties. A scoping review of 37 studies evaluated early predictors, age for diagnosis and diagnostic tools to inform evidence‐based practice in the assessment of DLD (Sansavini et al., 2021). Delays in gesture production, low receptive and/or expressive vocabulary, and limited word combinations up to 30 months were found to be early indicators of later DLD. Family history of language difficulties was a significant risk factor while low socio‐economic status and communication environments were risk factors with lower predictive power. Recommendations from the review included screening for language ability at 2–3 years and applying a diagnosis if relevant at 4 years using standardized tests and psycholinguistic measures assessing morpheme use and mean length of utterances. Another recent study harmonized variables from two datasets (Early Identification of Risk for Language Impairment and Language Acquisition and Semantic Relations) (Borovsky et al., 2021). Variables included demographic and linguistics measures from the MacArthur Bates Communicative Development Inventory. Machine learning techniques identified grammatical and lexico‐semantic markers as predictive of language delay in the early years, with demographic variables having lower predictive power.

Such complex analyses reveal the nuanced nature of language development and the difficulty associated with early identification of children at risk of DLD. Thankfully, previous authors have elucidated ‘red flags’ by combining findings from previous literature. Unsurprisingly, communicating in shorter sentences, difficulty with rule formation around sounds, words, and sentences, as well as poorly developed social use of language and overall vocabulary as red flags for DLD (Prelock et al., 2008). In the international CATALISE study for consensus on identifying DLD, Bishop et al. (2016) outlined the following consensus statements relating to early identification of children at‐risk of DLD:

  • Between 1 and 2 years of age, the following features are indicative of atypical development in speech, language or communication: (a) no babbling; (b) not responding to speech and/or sounds; and (c) minimal or no attempts to communicate (p. 9).

  • Between 2 and 3 years of age, any of the following features is indicative of atypical development in speech, language or communication: (a) minimal interaction; (b) does not display intention to communicate; (c) no words; (d) minimal reaction to spoken language; and (e) regression or stalling of language development (p. 10).

  • Between 3 and 4 years of age, any of the following features is indicative of atypical development in speech, language or communication: (a) at most two‐word utterances; (b) child does not understand simple commands; and (c) close relatives cannot understand much of child's speech. (p. 10).

  • Children's language can change dramatically, especially in the preschool/early school years (aged 4–5 years), even if there is no intervention. However, severe language impairment involving both comprehension and expression is more likely to be persistent (p. 10).

The final statement reiterates the individual variability in the acquisition of early communication milestones/displaying red flags for later language disorder. The individual differences in language appear to become more stable after the onset of formal schooling, although, this also means that the rate of language learning remains stable (Norbury, 2019). Therefore, if children begin school below their peers in terms of their language skills, they may not be able to develop their language learning at a rate that catches up to those with average language. The stability in the rate of language growth after the onset of schooling persists despite variation in child, parent and family factors (Norbury, 2019). That is, child, parent and family factors may not fully explain individual differences in language ability: some children are born with low language abilities despite good caregiver–child interactions in the early years. The challenge is to reliably identify these children to provide services to ameliorate communication and functional outcomes as soon as possible.

Improved identification of DLD in the early years may serve to mitigate the persistent and pervasive impacts from childhood into adulthood. In efforts to inform the wider public, online developmental resources (e.g., UpToDate, 2023), including speech pathology regulatory bodies publish early language milestones (e.g., American Speech & Hearing Association, n.d.; Royal College of Speech–Language Therapists, n.d.; Speech Pathology Australia, n.d.), which may note red flags. These useful and freely available resources can empower caregivers to identify whether their child may be at risk of DLD. Interestingly, when one follows these links, empirical evidence to support these red flags is typically implied, suggesting that failure to meet milestones is indeed the red flag. Non‐for‐profit organizations also provide easily accessible information for the public (e.g., Boys Town Hospital, 2021; The Hanen Centre, n.d.). Again, evidence of empirical support on these pages is implied. Finally, private organizations provide publicly available information in efforts to empower caregivers to make referrals when appropriate (e.g., Banter Speech, n.d.; Lee Slew, n.d.; North Shore Pediatric Speech Therapy, n.d.). These again usually highlight communication milestones and failure to meet them as red flags for later language disorder.

Although these resources serve as valuable information to the wider public, it is not clear that the use of these red flags to identify children at risk of DLD is empirically supported. Large, unselected samples from population‐based studies allow for investigation of prevalence of conditions, as well as the evaluation of relationships between disorders and exposures, such as the potential risk factors described above.

The Raine Study

The Raine Study is longitudinal cohort study that enrolled roughly 2900 pregnant women in Western Australia (Newnham et al., 1993). Between 1989 and 1992, 2730 mothers (Gen1) gave birth to 2868 offspring (Gen2) (Dontje et al., 2019), and the offspring of Gen2 are currently being followed up. Mothers and children of the Raine Study have found to be representative of the general population at study follow‐ups (see Dontje et al., 2019; Straker et al., 2017; White et al., 2017 for summaries). The rich datasets available within the Raine Study have been studied to estimate the prevalence of many childhood conditions, such as otitis media and hearing loss (Brennan‐Jones et al., 2020a), attention deficit hyperactivity disorder (Middledorp et al., 2016), and conduct and behavioural disorders (Ayano et al., 2021). Studies have also used Raine study data to evaluate the relationships between childhood language abilities and other conditions and/or exposures, such as otitis media (Brennan‐Jones et al., 2020b), maternal stress (Whitehouse, 2010), testosterone (Whitehouse et al., 2012) and anaesthesia (Ing et al., 2012).

Recently, the prevalence of and potential perinatal and environmental risk factors for DLD at 10 years were estimated in the Raine Study (Calder et al., 2022). Participants included 1626 children with available language data. Prevalence of DLD was indicated by scores on standardized measures of language (Clinical Evaluation of Language Fundamentals—3 (CELF‐3); Semel et al., 1995) and non‐verbal intelligence (Raven's Coloured Progressive Matrices (RCPM); Raven, 1977). Of the total sample, n = 104 cases scored 1.50 SD (standard deviations) or below the population mean on the CELF‐3 and within −2.00 SD on the RCPM, suggesting a prevalence rate of 6.4%, which is similar to prevalence estimates in younger children in other English‐speaking countries (Norbury et al., 2016; Tomblin et al., 1997). Notably, only two cases that met criteria for DLD based on standardized assessment were identified to have a language disorder by a health professional at the 10‐year follow‐up. This highlights a potential discrepancy between children who are likely to meet criteria for DLD based on test performance and those who accessed services for clinically significant language difficulties.

The strongest predictor for later DLD at 10 years was children who were exposed to tobacco smoke in utero at 18 weeks. Again, this finding was similar to Tomblin et al. (1998) who found smoking during and after pregnancy was associated with language disorder at 6 years. However, Tomblin et al. found that once parental education was controlled for, the association was washed out, leading the authors to conclude that smoking is more likely a determinant of disadvantaged parenting environment than a causal risk factor for language disorder. Indeed, Calder et al. (2022) highlighted that there was a significantly higher proportion of families who had household incomes < A$27,000 per year who did not provide language data, which made it difficult to rule out social determinants of DLD at 10 years. Another limitation noted in this study was that two important criteria for determining DLD diagnosis could not be obtained from the Raine Study dataset: (1) early onset of language difficulties; and (2) the functional impact of the condition. While the current study attempts to elucidate the limitation of not addressing the first criterion, the measurement of functional impact presents a persisting challenge to epidemiological research in this space (see Calder et al., 2023 for a discussion).

The current study

The aim of this study was to inform the predictive power of early signs of DLD in an unselected and representative longitudinal Australian birth cohort (Raine Study) at 10 years. Our objectives were as follows:

  • To leverage Raine Study data to create variables representing clinically relevant parent‐reported early indicators of DLD.

  • To test associations between parent‐reported indicators and children meeting diagnostic criteria for DLD at 10 years.

A systematic analysis of the predictive power of parent‐reported early indicators of DLD will inform the utility in using such indicators for the early identification of this at‐risk population.

METHODS

Participants

This study included variables from n = 1626 live births at King Edward Memorial Hospital in Perth, Western Australia, between 1989 and 1991. Data were analysed from 1‐year (1990−93), 2‐year (1991−94), 3‐year (1992−95) and 10‐year (1999−2002) follow‐ups. Each follow‐up was approved by the institutional ethics committee and written informed consent from the participants was obtained for each follow‐up. Recruitment and follow‐up for the Raine Study were approved by the Human Ethics Committee at King Edward Memorial Hospital. Analysis of existing data was approved by the Raine Study and Curtin Human Research Ethics Committee (HREC approval number HRE2021‐0117). Demographic information and the frequencies of children with (n = 104) and without (n = 1522) DLD are presented in Table 1, which is rereported from Calder et al. (2022, tab. 2, p. 2047).

TABLE 1.

Demographic information and frequencies of children with and without developmental language disorder in the Raine Study

DLD, n (%) No DLD, n (%)
Total number 104 (6.4%) 1506 (92.6%)
16 (1.0%)a
Socio‐economic status
< A$27 000 56 (53.8%) 835 (54.9%)
≥ A$27 000 40 (38.5%) 604 (39.7%)
Not stated 8 (7.7%) 83 (5.4%)
Ethnicity
Caucasian 95 (91.4%) 1345 (88.4%)
Aboriginal 2 (1.9%) 29 (1.9%)
Polynesian 2 (1.9%) 13 (0.8%)
Vietnamese 0 7 (0.5%)
Chinese 2 (1.9%) 68 (4.5%)
Indian 3 (2.9%) 41 (2.7%)
Other 0 19 (1.2%)
Language spoken most at home
English 101 (97.1%) 1439 (94.5%)
Vietnamese 0 10 (0.7%)
Chinese 0 18 (1.2%)
Italian 0 1 (0.1%)
Greek 0 3 (0.2%)
Spanish 0 5 (0.3%)
Other 3 (2.9%) 46 (3.0%)
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Note: Language disorder associated with intellectual disability, that is, NVIQ ≥ 2.0 SD below the mean.

Variables

The primary outcome variable for this study was children meeting diagnostic criteria for DLD at 10 years. Participants were classified at meeting criteria for DLD if z‐scores on the CELF‐3 Total Language Score was at or below 1.50 the population sample mean and z‐scores on the RCPM were ≥ −2.00 within the sample population mean. Z‐scores were used to determine the thresholds for diagnostic criteria primarily since the CELF‐3 was not normed on an Australian population; and second, to align with previous population‐based studies which used SD cut‐offs to determine prevalence estimates. Specifically, a threshold of −1.50 SD below the population mean on a language composite and within −2.00 SD on a measure of non‐verbal intelligence was applied by Norbury et al. (2016), and a cut‐off of −1.25 SD below the mean on a language composite and within −1.00 SD on a measure of non‐verbal intelligence was applied by Tomblin et al. (1997). We chose to apply the thresholds applied by Norbury et al. (2016) in keeping with the most recent prevalence estimate that corresponds to updates to diagnostic terminology of DLD (Bishop et al., 2017) and international classification systems such as the Diagnostic and Statistical Manual—5 (American Psychological Association (APA), 2013) and International Classification of Diseases—11 (ICD‐11) (World Health Organization (WHO), 2019). Sensitivity and specificity values of the z‐score thresholds were determined using receiver operating characteristic curves and are reported in Supplemental Material 1, indicating at or above acceptable discrimination on all metrics (Hosmer & Lemeshow, 2000). All cases that met z‐score thresholds for DLD were individually checked for ICD codes (parent report) for other biomedical conditions (e.g., autism, intellectual disability, hearing loss) that may better explain language difficulties. Of the total sample of 1626, n = 16 cases were considered to have language disorder associated with intellectual disability as indicated non‐verbal intelligence more than −2.00 SD below the population mean (i.e., no corresponding ICD code provided). No cases from the no‐DLD group were excluded based on an ICD code or parent report of a biomedical condition to maintain the representativeness of the population sample.

Early parent‐reported indicator variables were selected based on their alignment with existing research literature, early milestones, and communication red flags that are frequently reported through public and/or speech pathology advocacy forums outlined earlier and their availability within the Raine Study repository. A total of 11 parent‐reported early indicators of DLD were leveraged into dichotomous variables from parent questionnaires at 1‐, 2‐ and 3‐year follow ups. At the 1‐year follow‐up, concern on parent‐reported early indicators included a ‘no’ response to the following: (1) smiling at or before 6 weeks old, (2) babbling at or before 6 months old, (3) first words at or before 12 months old, (4) following one simple command at 12 months old and (5) pointing or looking at objects when asked. At the 2‐year follow‐up, concern on parent‐reported indicators included a ‘no’ response to the following: (6) speech clear at or more than 50% of the time, (7) combining words and (8) speaking in sentences. At the 3‐year follow‐up, concern on parent‐reported early indicators included a ‘no’ response to the following: (9) speech clear at or more than 50% of the time, (10) speaking in sentences and (11) combining sentences. Positive family history of speech and/or language difficulties from either the (12) mother or (13) father were also leveraged as predictor variables. See Supplemental Material 2 for a visual synthesis of how communication milestones, red flags and risk factors in the research literatures map on to clinically relevant parent‐reported early indicators. Specific wording of questions in relation to the transformed variables are presented in Supplemental Material 3.

Statistical analysis

Frequency distributions of parent‐reported early indicators and family history of speech and/or language difficulties were analysed with χ 2‐tests based on whether or not children met diagnostic criteria for DLD at 10 years. We also converted the parent‐reported early indicators into a cumulative risk index by summing ‘no’ responses (i.e., concern) across each dichotomous variable across 1–3‐year follow‐ups into a continuous variable to determine if such a variable would generate a profile that predicted later DLD. That is, do multiple independent parent‐reported indicators predict DLD at 10 years? Bivariate analyses were planned to evaluate the moderating effect of sex on DLD as a predictive outcome. Data were analysed using SPSS version 28.

RESULTS

Frequency distributions of parent‐reported early indicators from birth to 3‐year follow‐ups and family history of speech and/or language difficulties are reported in Table 2. The only significant difference in the proportion of children with or without DLD and responding ‘no’ to early indicators on any parent‐reported variables was babbling at or earlier than 6 months, where fewer females with DLD at 10 years were reported to have concerns by their parents than females without DLD. We note here, that descriptively, some indicators represented roughly equivalent proportions of concern across both groups, including smiling ≤ 6 weeks (no DLD = 22.0%; DLD = 21.7%), pointing/looking at objects when asked ≤ 12 months (no DLD = 15.0%; DLD = 16.5%), and speaking in sentences at 2 years (no DLD = 20.4%; DLD = 21.3%). We also note that the proportion of concern appeared to decrease across 1–3‐year follow‐ups, with 21.7–51.8% of concern for all indicators before the 1‐year follow‐up and ≤ 5.0% for all indicators at the 3‐year follow‐up.

TABLE 2.

Frequency distributions and results of χ 2 tests of parent‐reported early indicators from birth to 3‐year follow‐ups and family history of speech and/or language difficulties

Parent‐reported early indicators No concern Concern (%) Total Missing cases χ 2‐statistic p‐value
Smile ≤ 6 weeks Male No DLD 476 136 (22.2%) 612 158 0.119 0.730
DLD 34 11 (24.4%) 45 10
Total 510 147 (22.4%) 657 168
Female No DLD 446 124 (21.8%) 570 182 0.234 0.628
DLD 31 7 (18.4%) 38 11
Total 477 131 (21.5) 608 193
Total No DLD 922 260 (22.0%) 1182 338 0.004 0.947
DLD 65 18 (21.7%) 83 21
Babble ≤ 6 months Male No DLD 259 283 (52.2%) 542 228 0.176 0.674
DLD 19 18 (48.6%) 37 18
Total 278 301 (51.9%) 579 246
Female No DLD 267 243 (47.6%) 510 242 5.173 0.023 a
DLD 24 9 (27.3%) 33 16
Total 291 252 (46.4%) 543 258
Total No DLD 526 526 (50.0%) 1052 468 3.430 0.064
DLD 43 27 (38.6%) 70 34
First word ≤ 12 months Male No DLD 326 298 (47.7%) 624 146 3.516 0.061
DLD 17 28 (62.2%) 45 10
Total 343 326 (48.7%) 669 156
Female No DLD 347 233 (40.2%) 580 172 0.007 0.932
DLD 23 15 (39.5%) 38 11
Total 370 248 (40.1%) 618 183
Total No DLD 673 531 (44.1%) 1204 316 1.865 0.172
DLD 40 43 (51.8%) 83 21
Follows one simple command ≤ 12 months Male No DLD 601 41 (6.3%) 642 128 0.374 0.541
DLD 42 4 (8.7%) 46 9
Total 643 45 (6.5%) 688 137
Female No DLD 593 24 (3.9%) 617 135 0.176 0.675
DLD 38 1 (2.6%) 39 10
Total 631 25 (3.8%) 656 145
Total No DLD 1194 65 (2.8%) 1259 261 0.083 0.773
DLD 80 5 (5.9%) 85 19
Pointing/looking at objects when asked ≤ 12 months Male No DLD 527 108 (17%) 635 135 0.197 0.657
DLD 37 9 (19.6%) 46 9
Total 564 117 (17.2%) 681 144
Female No DLD 535 79 (12.9%) 614 138 0.000 0.993
DLD 34 5 (12.8%) 39 10
Total 569 84 (12.9%) 653 148 0.140 0.709
Total No DLD 1062 187 (15%) 1249 271
DLD 71 14 (16.5%) 85 19
Speech clear ≥ 50% of the time at 2 years Male No DLD 372 45 (10.8%) 417 353 0.006 0.940
DLD 26 3 (10.3%) 29 26
Total 398 48 (10.8%) 446 379
Female No DLD 357 12 (3.3%) 369 383 0.772 0.380
DLD 23 0 (0.0%) 23 26
Total 380 12 (3.1%) 392 409
Total No DLD 729 57 (7.3%) 786 734 0.161 0.688
DLD 49 3 (5.8%) 52 52
Combines words at 2 years Male No DLD 450 58 (11.4%) 508 262 2.243 0.134
DLD 32 1 (3.0%) 33 22
Total 482 59 (10.9%) 541 284
Female No DLD 443 18 (3.3%) 461 291 1.256 0.262
DLD 31 0 (0.0%) 31 18
Total 474 18 (3.7%) 492 309
Total No DLD 893 76 (7.8%) 969 551 3.433 0.064
DLD 63 1 (1.6%) 64 40

Speaks in sentences at

2 years

 Male No DLD 365 138 (27.4%) 503 267 0.000 0.984
DLD 24 9 (27.3%) 33 22
Total 389 147 (27.4%) 536 289
Female No DLD 392 56 (12.5%) 448 304 0.076 0.782
DLD 24 4 (14.3%) 28 21
Total 416 60 (12.6%) 476 325
Total No DLD 757 194 (20.4%) 951 569 0.029 0.864
DLD 48 13 (21.3%) 61 43
Speech clear ≥ 50% of the time at 3 years Male No DLD 565 24 (4.1%) 589 181 0.269 0.604
DLD 40 1 (2.4%) 41 14
Total 605 25 (4.0%) 630 195
Female No DLD 553 9 (1.6%) 562 190 0.602 0.438
DLD 37 0 (0.0%) 37 12
Total 590 9 (1.5%) 599 202
Total No DLD 1118 33 (2.9%) 1151 369 0.682 0.409
DLD 77 1 (1.3%) 78 26

Speaks in sentences at

3 years

 Male No DLD 549 11 (2.0%) 560 210 0.800 0.371
DLD 40 0 (0.0%) 40 15
Total 589 11 (1.8%) 600 225
Female No DLD 519 6 (1.1%) 525 227 0.416 0.519
DLD 36 0 (0%) 36 13
Total 555 6 (1.1%) 561 240
Total No DLD 1068 17 (1.6%) 1085 435 1.208 0.272
DLD 76 0 (0.0%) 76 28

Combines sentences at

3 years

 Male No DLD 570 12 (2.1%) 582 188 0.045 0.832
DLD 38 1 (2.6%) 39 16
Total 608 13 (2.1%) 621 204
Female No DLD 540 7 (1.3%) 547 205 0.466 0.495
DLD 36 0 (0.0%) 36 13
Total 576 7 (1.2%) 583 218
Total No DLD 1110 19 (1.7%) 1129 391 0.053 0.819
DLD 74 1 (1.3%) 75 29
Maternal history of speech and/or language problems Male No DLD 483 31 (6.0%) 514 256 0.013 0.908
DLD 34 2 (5.6%) 36 19
Total 517 33 (6.0%) 550 275
Female No DLD 449 20 (4.3%) 469 293 1.244 0.265
DLD 28 0 (0.0%) 28 21
Total 477 20 (4.3%) 497 314
Total No DLD 932 51 (5.2%) 983 537 0.532 0.466
DLD 62 2 (3.1%) 64 40
Paternal history of speech and/or language problems Male No DLD 381 42 (9.9%) 423 347 1.419 0.234
DLD 29 1 (3.3%) 30 25
Total 410 43 (9.5%) 453 372
Female No DLD 359 22 (5.8%) 381 371 0.170 0.680
DLD 25 1 (3.8%) 26 23
Total 384 23 (5.7%) 407 394
Total No DLD 740 64 (8.0%) 804 716 1.423 0.233
DLD 54 2 (3.6%) 56 48
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Note: a χ 2 test significant at p < 0.05.

Since no parent‐reported early indicator independently predicted DLD at 10 years, a cumulative risk index was created by summing ‘no’ responses to parent‐reported indicators into a continuous variable to determine of a combination of independent parent‐reported indicators predicted later DLD. The model was non‐significant, χ 2 (3) = 0.351, p = 0.950, explaining 0.1% of the variance and correctly identified 93.6% of the cases, odds ratio (OR) = 0.95, confidence interval (CI) = 0.85–1.09, p = 0.447. A second model was run to test for the moderating effect of sex with the likelihood of presenting with a combination of risk factors, which was also non‐significant, χ 2 (6) = 7.617, p = 0.268, explaining 0.2% of the variance, OR = 0.89, CI = 0.59–1.32, p = 0.563.

DISCUSSION

The aim of the current study was to systematically test the predictive power of parent‐reported early indicators in determining whether a child met criteria for DLD at 10 years in the Raine Study. It is important to note that identification of DLD in the current study could not include early onset and functional impact as diagnostic criteria, and identification was determined by performance on standardized tests. This study is an attempt to elucidate the utility of indicators of early onset to inform diagnosis while the lack of data on functional impact is acknowledged as a limitation discussed as future directions. From birth to 3‐year follow‐ups, 11 parent‐reported early indicators were leveraged from Raine Study data to align with those reported in the literature (e.g., Bishop et al., 2016), including: if the child does not smile or interact with others, does not babble, makes only a few sounds, does not understand what others say, says only a few words, says words that are not easily understood, and does not combine words or put words together to make sentences. Family history of speech and/or language difficulties from either the child's mother or father were also included. No one variable indicated a significant proportion of children with or without DLD; however, fewer females with DLD at 10 years were reported to babble late compared to females without DLD.

Some indicators demonstrated proportionate concern across groups (i.e., smiling ≤ 6 weeks, pointing/looking at objects when asked ≤ 12 months, and speaking in sentences at 2 years), and there was an overall decrease in the proportion of concern from the 1‐year follow‐up (21.7–51.8%) to 3‐year follow‐up (≤ 5.0%). This adds weight to the finding that variability in language performance is more pronounced in the early years and begins to stabilize towards early school age. Of particular interest is the overall lack of difference between groups across follow‐ups, suggesting parental concern may be present for children who go on to have typical language development, and children who go on to meet criteria for DLD may not raise parental concern in the early years.

We also transformed the parent‐reported early indicators into a cumulative risk index by summing ‘no’ responses across dichotomous variables into a continuous variable to determine if a profile that predicted later DLD could be generated. Results were analysed using the two‐step approach described above to test for the moderating effects of sex. Findings were also non‐significant.

Although the non‐significant findings from our analysis of an unselected population‐based study is somewhat surprising, our results may highlight that previous literature which has reported significant risk factors for DLD may be subject to retrospective reporting bias. For example, Rudolph's (2017) review was of case history factors, not exclusively epidemiological population‐based studies. Once Rudolph analysed 11 risk factors for clinical significance, the odds of developing DLD (then SLI) with four risk factors (low maternal education, low 5‐min APGAR, later born sibling and male sex) was as high as the odds as late talking predicting DLD. Importantly, late talking is not necessarily a reliable predictor of later DLD (e.g., Reilly et al., 2018). Indeed, population‐based studies have found there are no significant sex differences in those with and without DLD (e.g., Calder et al., 2022; Norbury et al., 2016; Tomblin et al., 1997), which suggests that being male is not a risk factor for DLD—rather, the observed differences in sex in the current study is likely the result of referral bias, which is well documented (e.g., Lindsay & Strand, 2016; Morgan et al., 2017). Therefore, the narrative that males are more likely to have language disorder must be challenged based on the overwhelming evidence that may in fact be false. Such challenges to this narrative will serve only to encourage approaches to identify females who are more likely to go undetected for essential services.

We must also consider that the parent‐reported early indicators leveraged from the Raine Study dataset may reflect variables that are subject to great variability within the birth to 3‐year span of early development. Therefore, using parent report as early indicators for later DLD in isolation may be unreliable through the current methods of analyses. Recent research has shown promise in more nuanced approaches to early identification which utilize standardized assessment and psycholinguistic measures to complement other risk factors, such as family history in the early identification of language disorder (e.g., Borovsky et al., 2021; Sansavini et al., 2021). Therefore, future epidemiological research should consider the use of such measures to complement a measure of overall parental concern in population‐based studies, such as the Gen3 Raine Study follow‐ups.

Other considerations for discrepancies between our findings and those previously reported in the literature are methodological. Even population‐based studies of unselected samples apply different diagnostic criteria to identify cases of individuals with below expected language abilities (e.g., Armstrong et al., 2017; Christensen et al., 2014; Harrison & McLeod, 2010; Norbury et al., 2016; Reilly et al., 2018; Tomblin et al., 1997) to determine prevalence and risk factors which may ultimately explain the significant variation in the combined samples. Of particular interest in the current study was the lack of family history predicting later DLD at 10 years. Christensen et al. (2014) and Reilly et al. (2018) have found that a positive family history of language problems may be considered a risk factor for language problems; however, Bishop et al. (2017) highlighted that the predictive power of family history may not be independently predictive of DLD once other risk factors have been accounted for (e.g., Botting et al., 2001). The low predictive power of positive family history problems has been mirrored in Sansavini et al.’s (2021) recent review and Borovsky et al.’s (2021) harmonization of large datasets. Altogether, while the heritability of language disorders has been demonstrated (e.g., Dale et al., 2003, 2018), the predictive value of family history as an independent predictor of DLD is likely still debatable.

Clinical implications and future directions

We stress here that red flags should not be ignored as a standard part of clinical practice and promotion and prevention strategies in the identification of young children who may experience language difficulties in later childhood. Specifically, parental concern should be considered foremostly as an indicator for further assessment and monitoring in clinical practice. We also stress that the parent‐reported indicators included in this study of children with DLD may be applicable as indicators for children with language disorders associated with another condition, so results should not be generalized to other populations. Conversely, we highlight that the lack of significant findings in a large, representative, and unselected population‐based prospective birth cohort suggests an increased likelihood that DLD may go undetected until children reach formal schooling. Given the likely referral bias for males (e.g., Lindsay & Strand, 2016; Morgan et al., 2017), females may be at particular risk for going undetected. Equivalent proportions of those with and without DLD were identified to have showed red flags at 0–3 years (with the exception of late babbling where fewer parents of females with later DLD expressed concern), which also means that an equivalent proportion did not show red flags. DLD may therefore be more insidious in its presentation until children meet formal schooling. Consequently, parents and carers must be vigilant when considering referral, and clinicians should consider the use of robust and objective measures of language functioning to complement the evaluation of parental concern.

This study may also run the risk of parent‐reporting bias, in which parents may not have been informed enough to respond to the probe questions reliably. Indeed, the crosstabulation of parent‐reported concerns in the DLD sample indicated as few as one case in some instances (e.g., combining words at 2 years, clear speech at 3 years, combining sentences at 3 years). Therefore, speech pathologists and researchers should continue to campaign for greater advocacy in detecting behavioural determinants of language difficulties that may manifest as DLD to identify children as early as possible. Another issue relating to parent report may be that mothers and fathers of children may not be aware if they had speech and language difficulties as a child, especially given the propensity for DLD to be under‐identified in childhood (Skeat et al., 2010; Zhang & Tomblin, 2000). Regardless, we must continue exploring new methods of detecting DLD and perhaps increase stringency in how speech pathologists and researchers identify behaviours, both linguistic and non‐linguistic, in how we identify DLD early on.

Calder et al. (2023) presented a range of measures that map to contemporary diagnostic criteria for the identification of DLD. The reliability of screening tools that use measures of sentence recall (e.g., Redmond et al., 2019) and grammaticality judgement (e.g., Rice et al., 1999) should be considered as an approach to detect young children efficiently for further assessment which quantifies language functioning as well as functional impact through a range of sources. A multidimensional approach to describe functional impact associated with DLD may serve to improve participation‐based outcomes following identification (e.g., Cunningham et al., 2017; Washington, 2007). A tool such as the Focus on Outcomes of Communication Under Six (FOCUS) (Thomas‐Stonell et al., 2010) may therefore be useful for use in the identification and measurement of outcomes for children with DLD in the early years. Functional impact may also be confirmed through measures of parental concern, again highlighting the need for continued attention in this area.

Limitations

Although the Raine Study is a large and representative prospective pregnancy cohort study (Dontje et al., 2019; Straker et al., 2017; White et al., 2017), there are limitations to note regarding the current investigation. Firstly, a lack of measures of functional impact in the current Raine Study dataset limits the application of contemporary diagnostic criteria to the cohort, since the children identified to meet criteria for DLD in the current study was determined by scores on standardized assessment in the absence of additional criteria, including evidence of functional impact and early onset (APA, 2013; Bishop et al., 2017; WHO, 2019). This is of particular relevance since fewer females are identified for clinical services despite comprising equivalent proportions to males meeting diagnostic criteria in population‐based studies. That is, do functional impacts manifest in ways that are different and less observable compared to males? Second, there were cases of missing data for many of the parent‐reported early indicators, which may have resulted in the small number of cases that indicated concern in the DLD sample. Indeed, the small number of cases for these variables limited the ability to reliably test the predictive power of individual variables indicating DLD at 10 years. Relatedly, the relatively small sample of children identified with DLD in this study may increase the risk of type II error for some parent‐reported early indicators, such as word combinations at 2 years. This also highlights the need to develop robust data collection methods to evaluate the early onset of language difficulties in research and clinical practice. Finally, mothers of children in the Raine Study were recruited for one hospital in Western Australia, which may contribute to increased risk of selection bias in the sample.

CONCLUSIONS

This study systematically tested the predictive utility of widely used parent‐reported early indicators of DLD. These included if the child did not smile or interact with others, did not babble, makes only a few sounds, did not understand what others say, said only a few words, said words that are not easily understood, and did not put words together to make sentences between birth and 3 years. Even when considered alongside a family history of speech and/or language difficulties, data from a large and representative population‐based study indicated that no one indicator or combination of indicators predicted DLD at 10 years. Further analyses indicated findings remained non‐significant when testing for the moderating effects of sex, again reinforcing the utility in being male as a risk factor for later language disorder is limited. Previous studies that indicate potential risk factors (such as being male or family history) in non‐epidemiological studies may be subject to retrospective reporting bias, and future research and clinical practice should be informed by recent evidence that highlights promise in the use of standardized tests and psycholinguistic measures to evaluate and complement parental concern in the early identification of DLD. Such approaches to identification and assessment should be considered alongside evaluation of functional impact to inform participation‐based interventions.

CONFLICT OF INTEREST STATEMENT

The authors declare there are no relevant conflicts of interest.

Supporting information

Supporting Information

JLCD-59-396-s002.docx (42.1KB, docx)

Supporting Information

JLCD-59-396-s003.docx (15.1KB, docx)

Supporting Information

JLCD-59-396-s001.docx (18.1KB, docx)

ACKNOWLEDGEMENTS

We would like to acknowledge the Raine Study participants and their families for their ongoing participation and the Raine Study team for study coordination and data collection.

Open access publishing facilitated by University of Tasmania, as part of the Wiley ‐ University of Tasmania agreement via the Council of Australian University Librarians.

Calder, S.D. , Boyes, M. , Brennan‐Jones, C.G. , Whitehouse, A.J.O. , Robinson, M. & Hill, E. (2024) Do parent‐reported early indicators predict later developmental language disorder? A Raine Study investigation. International Journal of Language & Communication Disorders, 59, 396–412. 10.1111/1460-6984.12950

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are openly available via application in Raine Study at https://rainestudy.org.au/information-for-researchers/available-data/.

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Associated Data

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

Supplementary Materials

Supporting Information

JLCD-59-396-s002.docx (42.1KB, docx)

Supporting Information

JLCD-59-396-s003.docx (15.1KB, docx)

Supporting Information

JLCD-59-396-s001.docx (18.1KB, docx)

Data Availability Statement

The data that support the findings of this study are openly available via application in Raine Study at https://rainestudy.org.au/information-for-researchers/available-data/.

Articles from International Journal of Language & Communication Disorders are provided here courtesy of Wiley

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