High screen time and low child-adult talk associated with poorer language development in early childhood

Abstract

Objectives:

To examine associations between children's and parents' screen time, children's face-to-face talk with adults, and children's language skills.

Design, setting, and participants:

Cross-sectional study based on mother-reported survey data collected from September 2023 to December 2024 in Estonia. Participants were 458 children aged 30–48 months; analyses included 448 children (mean [SD] age, 39.1 [5.0] months) with complete data.

Measures:

Daily child screen time, parental screen time, and children's time spent in face-to-face talk with adults were reported for a typical weekend day. Children's language skills were assessed using the Estonian version of the MacArthur–Bates Communicative Development Inventories III (ECDI-III). Multiple linear regression examined independent and combined associations of screen time and talk with language scores, adjusting for child age and sex. Latent class analysis (LCA) was used to identify family-level patterns of screen use and conversational engagement.

Results:

Among the 448 children [232 girls (51.8%); mean (SD) age, 39.1 (5.0) months], 39.4% had ≤ 60 min of daily screen time, 33.7% had 61-120 min, and 27.0% had >120 min. In regression analyses, higher screen time was negatively (B = −0.081; 95% CI, −0.115 to −0.048; P < 0.001) and child-adult face-to-face talk positively (B = 0.031; 95% CI, 0.015 to 0.047; P < 0.001) associated with ECDI-III scores. The full model, including age and sex, explained 26.1% of the variance in language scores. LCA identified three family profiles: Screen-Saturated, Somewhat Talkative Families (43.2%), Low-Screen, Quiet Families (40.2%), and Parent-Screen, Talk-Rich Families (16.6%). Children in Parent-Screen, Talk-Rich Families showed higher language scores and greater child-adult conversational engagement than children in the other profiles (Welch's F_{(2, 221)} = 6.23; P = 0.002).

Conclusions:

Higher screen time and lower child-adult conversational engagement were associated with poorer language outcomes in early childhood. Family typologies suggested that low screen time alone was not associated with stronger language skills unless accompanied by rich conversational environments. These findings highlight the importance of considering both digital media use and everyday conversational experiences when examining early language development.

Introduction

The impact of screen time on young children's development remains a sensitive and evolving research topic, requiring an open-minded and balanced consideration of its potential benefits and drawbacks. Healthy lifestyle patterns, including screen time practices, are established early in childhood and tend to persist over time (Mallawaarachchi et al., 2025). Longitudinal evidence suggests that these early patterns are relatively stable, with screen use habits established at ages 1-3 years persisting up to age 8 (Trinh et al., 2020). The language environment of children is increasingly shaped by digital media. Most children aged 2 to 5 already exceed the recommendation (American Academy of Pediatrics. Council on Communications Media, 2016) of no more than 1 h of digital media use per day (McArthur et al., 2022b; Tamm and Tulviste, 2024).

Early language skills have long-term consequences for later language outcomes, cognitive and social development, academic achievement, and quality of life (Golinkoff et al., 2019; Rescorla, 2009). Early language development is shaped not only by heritability (Dale et al., 2000), but also by the richness of the language environment in which the child grows up (Brushe et al., 2024; Rowe and Snow, 2020). Numerous studies have shown that both the quantity and the quality of language input play important roles in early language development (Hart and Risley, 1995; Hoff, 2006; Rowe, 2012). Recent research particularly highlights the critical role of interactions-children's active verbal engagement in face-to-face, back-and-forth, one-to-one dyadic conversations with adults (Golinkoff et al., 2019; Rowe and Snow, 2020; Zimmerman et al., 2009; Romeo et al., 2017).

Nevertheless, evidence on the relationship between screen time and early language development remains mixed. The majority of studies report negative associations (Dynia et al., 2021; Karani et al., 2022; Kartushina et al., 2022; Lin et al., 2015; Madigan et al., 2020; Axelsson et al., 2022; Sundqvist et al., 2021). Others suggest that the effects depend on the type and content of programs viewed or the nature of the screen-based activities (Tabullo and Gago-Galvagno, 2022; Roseberry et al., 2014; Linebarger and Walker, 2005; Jing et al., 2023). Research on the home learning environment indicates that analog and digital forms of stimulation represent distinct yet related dimensions of children's everyday experiences, whereby developmental outcomes are associated with configurations of family interaction and engagement rather than with single environmental factors in isolation (Lehrl et al., 2021). Still other studies, including broader reviews where language was assessed as one of multiple outcomes, have reported no significant effects (Alloway et al., 2014; Taylor et al., 2018; Zhang et al., 2022). Importantly, the effects of screen use differ across ages, screen use contexts, and developmental domains (Madigan et al., 2020; McArthur et al., 2022a).

A frequently cited explanation is that screen use displaces face-to-face interaction with parents (Dynia et al., 2021; Alroqi et al., 2023) and adults, more broadly (Christakis et al., 2009). Although few studies have tested this hypothesis directly (Gath et al., 2023; Mutz et al., 1993) in one study using Language ENvironment Analysis (LENA) recordings, higher screen use between 12 and 36 months was linked to fewer adult words, child vocalizations, and conversational turns (Brushe et al., 2024). Another study reported that 3-year-old children who spend more time in silence demonstrate lower language skills (Tulviste and Tamm, 2021). The growing dominance of screen-based activities may also displace other developmentally enriching activities such as joint reading, play, social interactions, and physical activity (Putnick et al., 2023). Family-level patterns are also important: children tend to mimic their parents' digital media habits, and families characterized by high screen use tend to have children with lower vocabulary and grammar skills compared to families with low screen use (Tulviste and Tulviste, 2024). Consistent with this, children acquire language more effectively from in-person verbal exchanges than from media (Kuhl, 2007; Krcmar et al., 2007).

Importantly, most evidence linking screen time to early language development is correlational, and causal interpretations remain uncertain. Reverse developmental pathways are plausible, whereby children with poorer emerging language skills may engage more frequently with screens, and the associations may also reflect unmeasured familial, socioeconomic, or genetic factors. Available evidence from longitudinal and genetically informed studies indicates that higher screen time in early childhood relates to slightly poorer language outcomes, although effect sizes are generally small and substantially attenuated when adjusting for confounding factors. (Madigan et al. 2019) reported a directional association between high screen time and poorer developmental outcomes among very young children, while not observing a reverse association. (Yang et al. 2024) found weak associations of screen use with cognitive development outcomes after controlling for sociodemographic and children's birth factors and lifestyle confounders, suggesting that the context of screen use matters.

The present cross-sectional study aims to clarify family-level behavioral correlates of early language development rather than to establish causal effects. We examined associations between screen time among 2-4-year-old children and their parents, the time children spend talking with adults, and their language skills. First, we examined children's screen time and the amount of time they spent talking with adults, assessing whether higher screen use was associated with lower language skills and lower levels of child-adult conversation. Secondly, we adopted a family-level perspective by including parents' screen time alongside children's. Finally, to complement the independent associations identified in regression analyses, we aimed to identify naturally occurring family-level behavioral profiles that characterize children's everyday developmental environments. Screen use by children and parents, as well as the amount of face-to-face interaction experienced by young children, show substantial individual variability, yet relatively few studies have linked family-level behavioral patterns to language outcomes in early childhood. By applying latent class analysis (LCA) we can examine how specific combinations of family members' screen use and child-adult conversational engagement are associated with language outcomes. This approach allows to verify whether low screen time or high child-parent conversational engagement alone associate with higher language skills.

We hypothesized that:

(1) Higher screen time in children would be associated with lower levels of face-to-face child-adult talk and with poorer language skills.

(2) Child screen time and child-adult conversational engagement would show independent associations with children's language outcomes.

In addition, rather than testing a directional hypothesis, we conducted an exploratory LCA to identify naturally occurring configurations of child and parental screen use together with children's face-to-face conversational engagement with adults, and to examine how these naturally occurring family profiles were associated with language outcomes.

Materials and methods

Study design

This was a cross-sectional study using mother-reported survey data collected from September 2023 to December 2024 in Estonia using a web-based questionnaire. The study formed part of a larger project on young children's language environments. Data were gathered through a secure web-based platform hosted by the University of Tartu. Mothers provided informed electronic consent before participation. The study was approved by the Research Ethics Committee of the University of Tartu, Estonia (protocol No. 376/T-18).

Participants

Mothers of children aged 30-48 months residing in Estonia were eligible. Recruitment occurred via childcare centers, social-media advertisements, and mailing lists. Inclusion criteria were completion of the core survey questions addressing child's screen use and talking time, and the language questionnaire. Exclusion criteria were incomplete data or implausible values on key variables. All eligible and consenting mothers who completed the survey within the study period were included to maximize statistical precision. A total of 458 children [232 (50.7%) female], aged 30-48 months[mean (SD), 39.08 (5.03)] were recruited; analyses included 448 with complete data on all study variables.

Study assessments

Mother-reported screen time and child talking time with adults

Mothers reported (1) the hours and minutes that the child, mother, and father spent using screen-based devices (television, computers, laptops, tablets, mobile phones, game consoles) on a typical weekend day; (2) the estimated time children spent talking face-to-face with adults (eg, chatting, playing, reading together) without screens. Study variables and parental background characteristics were reported by the mother using a questionnaire developed for a previous study (Tulviste and Tulviste, 2024). Mother's educational level was used as a proxy measure of socioeconomic status (SES), as is common in studies of early child development (Rowe, 2012).

Child language skills

Children's language skills were assessed using the Estonian version of the MacArthur-Bates Communicative Development Inventories III (ECDI-III; Tulviste and Schults, 2020), a maternal report-based instrument, adapted from the Swedish version of the CDI-III (Eriksson, 2017). The instrument demonstrates high internal consistency (Cronbach's α = 0.97 for the Vocabulary section and α = 0.92 for the Grammar section) and shows both concurrent and predictive validity (Tulviste and Schults, 2020, 2023). The instrument consists of (a) the level of communication-a general evaluation of a child's language complexity; (b) a 100-item vocabulary checklist, where mothers indicated which words their child actively uses; (c) the grammar section containing two subcomponents: Grammatical constructions and Sentence complexity; (d) the metalinguistic awareness section; and (e) the pronunciation section. The maximum total score is 154.

Data processing

Responses reported in hours and minutes were cleaned for inconsistencies and transformed into continuous minute-based variables. Outlying values (> 12 h/day) were trimmed to 12 h. For descriptive analyses, variables were also categorized for interpretability: child screen time ≤ 60 min, 61-120 min, >120 min/day (based on the AAP guideline of ≤ 1 h); parental screen time ≤ 120, 121-240, >240 min/day; child talk time ≤ 120, 121-240, >240 min/day. Continuous variables were used in regression models; categorical indicators were used for latent class analysis (LCA). Missing data were minimal (< 2 % per variable); analyses used listwise deletion. A sensitivity analysis excluding the top 5 % of screen time outliers yielded comparable results.

Statistical analysis

Hypothesis 1 was evaluated using bivariate correlations and multiple linear regression analyses (Models 1-2) with the ECDI-III total score as the dependent variable. Child screen time (Model 1) and face-to-face talk with adults (Model 2) were entered separately as predictors of language scores.

Hypothesis 2 was evaluated using regression Models 3-4, in which both predictors were entered simultaneously (Model 3) and subsequently adjusted for child age and sex (Model 4). Cases with missing data were excluded listwise. Model fit was evaluated using R² and F statistics. For each model, unstandardized coefficients (B), standard errors (SE), standardized beta coefficients (β), p-values, and 95% confidence intervals are reported.

To identify qualitatively different subgroups within families based on reported screen time of the child, mother, and father as well as the estimated child-adult total face-to-face talk time (in Supplementary Table 2), we applied LCA, which allows the detection of different subgroups (classes) within populations using their responses to categorical indicator variables (Hagenaars and McCutcheon, 2002). We determined the optimal class solution by comparing 2- through 7-class models based on relevant statistical indicators (see Supplementary Table 4 for model fit indices) including Bayesian Information Criterion (BIC), Akaike Information Criterion (AIC), entropy, and interpretability of classes. Based on low AIC (3757) and BIC (3865) values and adequate entropy (0.711) values, a three-class model was selected (Weller et al., 2020). Maternal education was examined descriptively, as covariate in regression models, and in relation to latent class.

Because the assumption of homogeneity of variances was not met (Levene's test p = 0.049), Welch's ANOVA was used to test for mean differences across classes. Effect sizes are reported as eta squared (η²). Statistical analyses were performed in IBM SPSS 30.0. For LCA we used the R-based Jamovi (Sahin and Aybek, 2019), SnowRMM: Rasch mixture (Seol, 2023), and “poLCA” (Linzer and Lewis, 2011) software packages. Statistical significance was set at p < 0.05 (two-tailed).

Results

Descriptive Statistics

Of the participating children (N = 458), 10 (2.2%) were reported as screen non-users with no daily screen time. The analytic sample included 448 children (232 girls [51.8%]; mean [SD] age, 39.1 [5.0] months). Among these, 39.3% (n = 176) had ≤ 60 min of daily screen time, 33.7% had 61 to 120 min, and 27.0% had more than 120 min. Mother-reported child–adult face-to-face talk time was ≤ 120 min for 35.8%, 121 to 240 min for 34.1%, and more than 240 min for 30.1%. When controlling for age, the adjusted mean language score was 92.28 (SD = 31.99).

Correlation between screen time, face-to-face talk, and language skills

Zero-order correlations (presented in Table 1) showed that child screen time was negatively associated with child-adult talk (i.e., the child's total face-to-face talking time with adults). Furthermore, child screen time was negatively associated with children's language scores. By contrast, parent screen time was not significantly associated with children's language scores. Child language scores were positively associated with child-adult talk. Finally, child screen time was positively correlated with both mother's and father's screen time.

As expected, child age correlated with language outcomes, with older children scoring higher on the ECDI-III total score. Age also showed weak correlations with face-to-face interaction with adults with slightly less child-adult talk as children get older. Girls showed higher ECDI-III language scores than boys, consistent with well-established sex differences in early language development. Age-adjusted partial correlations among the primary study variables are provided in Supplementary Table 1.

Predictors of language skills

Regression analysis (Table 2) showed that higher child screen time was significantly associated with lower language scores, accounting for 3.8% of the variance in ECDI-III scores (Model 1). Time spent talking with adults was also significantly associated with language scores, explaining 3.3% of the variance (Model 2).

Including both screen time and face-to-face talk with adults in the same model improved model fit, with the two predictors jointly accounting for 5.6% of the variance and both remaining statistically significant (Model 3). When child age and sex were added as covariates, the full model explained 26.1% of the variance in language scores (Model 4). In Model 5, maternal education was added as an additional covariate but was not significantly associated with language outcomes, and the associations between screen time, child-adult talk, and language scores remained unchanged. Full regression results, including standardized coefficients, are provided in Supplementary Table 3.

Across models, higher screen time and lower child-adult talk were each independently associated with lower language scores, even when included together and after adjusting for child age and sex. When considered jointly, the results indicated a pattern in which higher screen time co-occurs with both lower levels of face-to-face talk and poorer language outcomes, while conversational engagement remains independently related to language skills. Rather than reflecting a single pathway, these findings suggest that child screen time and child-adult face-to-face interaction represent related but distinct correlates of early language development.

Family typologies of screen use and face-to-face interaction patterns of the child and parents

Figure 1 illustrates the response probabilities of family members' (child, mother, and father) screen time and child-adult face-to-face talking time across the three identified latent classes. LCA identified three distinct family types: Screen-Saturated, Somewhat Talkative (43.2%; N = 198), where both parents and children had high screen use and moderate child-adult conversation; Low-Screen, Quiet (40.2%; N = 184), where parents and children had low screen use but also limited child-adult conversation; and Parent-Screen, Talk-Rich (16.6%; N = 76), where children had minimal screen exposure, parents exhibited moderate screen use, and children engaged in frequent face-to-face talk with adults. (Descriptive statistics of the four LCA indicator variables by class are presented in Supplementary Table 6).

Figure 1

Language scores differed significantly across the three latent classes (Welch's F _{(2, 221.07)} = 6.23, p = 0.002, η² = 0.02). Post hoc Games–Howell comparisons indicated that children in the Parent-Screen, Talk-Rich class showed higher ECDI-III total scores (mean = 102.21, SD = 27.96) than children in both the Screen-Saturated, Somewhat Talkative (mean = 88.28, SD = 34.37) and Low-Screen, Quiet classes (mean = 91.10, SD = 31.93), whereas the latter two groups did not differ significantly from each other (see Supplementary Table 5 for pairwise comparisons).

Latent class membership did not differ significantly by parental education (maternal: χ²(2, N = 450) = 2.48, p = 0.290; paternal: χ²(2, N = 445) = 5.10, p = 0.078).

Discussion

The findings supported the first hypothesis, indicating that higher screen time was associated with less child-adult face-to-face interaction and with lower language scores. Notably, more than half of the children (59.4%) in the study exceeded the recommended limit of no more than 1 h of screen time per day, while only 2.2% were non-users of digital devices, underscoring the developmental relevance of these associations.

Higher screen time and reduced face-to-face talk co-occurred with lower language scores, and children characterized by both higher screen time and lower conversational engagement showed poorer language outcomes than those experiencing either factor alone, after controlling for child age and sex.

The second hypothesis was also supported, since screen time and child-adult interaction each showed independent associations with children's language skills, suggesting that they represent related but distinct correlates of early language development. Although higher screen time was associated with lower language scores and with lower child-adult face-to-face talk, conversational engagement did not fully account for the association between screen time and language outcomes.

Several limitations should be considered. First, the cross-sectional design does not permit causal inference, and reverse developmental pathways are plausible, whereby children with poorer language skills may gravitate toward screens. Evidence that parents increase verbal interaction as children's language skills develop further supports the possibility of reverse developmental pathways (Dailey and Bergelson, 2023). Second, all measures relied on maternal report, which may introduce common-method variance, subjective bias, and social desirability bias, but also recall bias since the mother may not be able to accurately report on the screen time and child-adult talk indicators for herself nor family members. Third, the proportion of variance in language scores explained by screen time and child-adult conversational engagement was modest. This is consistent with the multifactorial nature of early language development, which is shaped by a wide range of genetic, familial, and environmental influences not captured in the present study, and with prior meta-analytic findings reporting small effect sizes for associations between screen time and early developmental outcomes (Madigan et al., 2020). Also, SES was assessed only via maternal education.

Nevertheless, the observed small-to-moderate effects were meaningful, indicating that each additional 10 min of daily child-adult talk was associated with an increase of about 0.31 points in ECDI-III scores, whereas each additional 60 min predicted nearly 2 points higher scores. These increments, while modest for an individual child, could accumulate to substantial differences in language trajectories across early childhood.

Reduced child-adult face-to-face talk did not fully account for the association between screen time and language skills, suggesting that additional pathways—such as reduced sleep, fewer opportunities for play and physical activity, or attentional overstimulation—may also contribute (McArthur et al., 2022b; Madigan et al., 2019; Santos et al., 2025). These findings highlight the importance of considering a broader set of mechanisms that may help explain the observed association between screen use and language development.

LCA provided further insight by identifying three distinct family profiles. Importantly, low child screen time alone was not associated with better language outcomes, as children in the Low-Screen, Quiet class did not outperform peers in the Screen-Saturated, Somewhat Talkative class, suggesting that face-to-face conversation—not just low or restricted screen use—is critical for language skills. In contrast, children in Parent-Screen, Talk-Rich class had the highest language scores, suggesting that richer conversational environments co-occur with more favorable language outcomes even in the presence of parental screen use. These findings extend evidence related to the displacement hypothesis (Gath et al., 2023; Mutz et al., 1993) by indicating that screen exposure is associated not only with reduced conversational input but also with variation in broader conversational environments linked to language outcomes.

Conclusions

Guidance on screen time in early childhood should emphasize not only restriction but also the active promotion of daily child-adult and parent-child conversation (eg, shared reading, storytelling, play). Integrating recommendations on screen time limits with explicit goals for verbal interaction may be a more effective strategy to support language development and broader child wellbeing.

Our findings suggest that lower levels of face-to-face talk may partly account for the observed association between higher screen time and poorer language skills, while conversational engagement may buffer these effects. The results reinforce the importance of growing up in a home environment rich in direct face-to-face interaction, where children benefit most from sustained conversation with adults (Hart and Risley, 1995; Hoff, 2006; Rowe, 2012; Romeo et al., 2017; Gilkerson et al., 2018).

The findings highlight the need to address screen time not only by limiting hours of use but also by ensuring that parents deliberately foster rich, daily conversations with their children, both in family settings and in policy guidance.

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