By executive functions (EF) we follow the concept of Friedman and Miyake (2017), understanding them as high-level cognitive processes that control lower-level processes. According to this model, EF include cognitive flexibility, inhibitory control, and working memory. Research shows that EF regulate a wide range of mental functions in children and make a significant contribution to their development in preschool age. The relationship between pragmatic competence and the development of EF has primarily been studied in samples of children with autism spectrum disorders (ASD) (Filipe et al., 2020). These studies found that well-developed EF mitigate the negative impact of ASD on the pragmatic aspect of language in children from 8 to 18 years (Cardillo et al., 2021). In particular, a strong positive influence of well-developed working memory and attention on pragmatic skills in children aged 2–8 years with autism has been noted (Howard et al., 2023). Studies on this relationship in normatively developing populations remain relatively rare, and the available findings are often inconsistent (Blain-Brière et al., 2014). Nevertheless, several studies have emphasized the leading contribution of working memory to higher levels of pragmatic competence in adults and children aged 5–9 years (Bambini et al., 2021; Filippova and Astington, 2008). Also noted is the contribution of inhibitory control (Chen et al., 2025) to the comprehension of non-literal language and irony, as well as the role of cognitive flexibility (Hung and Loh, 2020) in meaning interpretation, which also pertains to pragmatic competence. Thus, despite numerous studies and the general conclusion about the contribution of EF to socio-communicative skills, their contribution to the development of pragmatics and its individual aspects in preschoolers remains insufficiently studied.

By emotion comprehension (EC) we follow the concept of Pons and Harris (2005). EC is the ability to understand “the nature, causes, and consequences of the emotional experience in the self and others” (Pons and Harris, 2019, p. 431). Children’s EC development passes through several stages or levels (Pons and Harris, 2005; Pons et al., 2004). These levels are: (1) the first “External” level at 3–5 years old. This level is associated with the formation of ideas about the external causes of emotions, that is, recognition of others’ emotions from facial expressions and understanding the influence of external circumstances on emotions. (2) The second is the “Mental” level between the ages of 4–5 and 6–7. Children begin to understand that personal beliefs, desires, and memories can trigger different emotions and that certain emotions can be hidden. (3) The third or” Reflective” level occurs at 6–7 to 9–10 years. Children learn to regulate their emotions, begin to better understand ambivalent (mixed) and hidden emotions, and discover the influence of moral norms on emotions (Pons and Harris, 2005; Pons et al., 2003). Pragmatic competence includes communicative skills, that is, the ability and willingness to engage in communication and interaction with others. It would be logical to assume that understanding the interlocutor’s emotions makes a significant contribution to the pragmatic competence. However, there are relatively few studies directly investigating the relationship between EC and pragmatic skills. In particular, Veraksa et al. (2019) provides clear evidence of a positive relationship between pragmatic narrative ability and EC in typical preschoolers. Curenton’s (2015) work shows how an emotion-focused task can reveal pragmatic competence. Pronina et al. (2021) suggest that these skills can be dissociated in intervention. In sum, pragmatic skill appears intertwined with EC during preschool (Spackman et al., 2006): children who are better at social language tend to understand emotions better, whereas those with pragmatic impairments (from ASD, ADHD, or DLD) often show social–emotional weaknesses as well (Carruthers et al., 2022; Wong et al., 2022). Several studies have shown that pragmatic skills contribute to EC, but not vice versa (Farina et al., 2007; Giménez-Dasí et al., 2013). It has also been shown that work with 3- to 4-year-old children focused on expanding their vocabulary with terms related to mental states and emotion labels significantly improved their emotion understanding, as well as their false-belief understanding (Ornaghi et al., 2011). As for precise studies of contribution of EC in children in their pragmatic skills, they are missing.

Thus, the impact of EF and EC on pragmatic skills in children remains understudied. This research question is very important not only for designing intervention programs for children with ASD and communication disorders but also for enhancing the social-communicative and pragmatic skills of typically developing children. The aim of the present study is to assess the contribution of EF and EC to key aspects of pragmatic competence in children aged 5–8 years.

The sample included typically developing children aged 5–8 years from middle-class families, encompassing both monolingual Russian speakers and Russian-dominant bilinguals. Children who did not complete both testing sessions, as well as those whose parents did not provide written informed consent, were excluded from the study. Initially the sample included more than 2000 children from six regions of the Russian Federation. However, after excluding irrelevant teacher responses to the PCQCh, valid assessments remained for 1,842 children, including 910 boys and 932 girls. The children were aged between 59 and 96 months (M = 73.51, SD = 9.0).

To assess the pragmatic competence of children, the Pragmatic Competence Questionnaire for Children aged 5–8 years (PCQCh) (Oshchepkova et al., 2024) was used. This questionnaire was completed by the educators of the children attending their classes. It includes 20 items grouped into four scales: Scale 1. The ability to understand language in context (e.g., “The child understands from your intonation and facial expression that you are dissatisfied, demanding something, or, conversely, that you are pleased,” 6–30 points, Cronbach’s α = 0.811); Scale 2. Communication skills (e.g., “When communicating with relatives and familiar adults, the child shows interest and friendliness,” 5–25 points, Cronbach’s α = 0.795); Scale 3. Use of nonverbal means of communication (e.g., “The child uses gestures appropriate to the situation,” 3–15 points, Cronbach’s α = 0.845); Scale 4. Narrative skills in different genres (e.g., “The child invents his/her own coherent stories, with a beginning, a sequence of events, and an ending,” 3–15 points, Cronbach’s α = 0.856). Teachers evaluate how characteristic this behavior is for the child, from 1 (this behavior is not characteristic at all) to 5 (this behavior is always characteristic of the child).

To assess the level of EC, the TEC (Test of Emotion Comprehension) (Pons and Harris, 2004) was used. TEC is a tool that allows to capture child emotion understanding and measure nine components of EC: (1) emotion recognition, (2) external cause, (3) desire, (4) belief, (5) reminder, (6) regulation, (7) hidden, (8) mixed, and (9) morally based emotions. At the same time, it enables the distinction of three levels of emotion understanding: the external level, the mental level, and the reflective level. The test consists of 22 tasks. An accurate answer receives 1 point, and a wrong answer receives a zero point. The scores obtained for individual tasks are combined into four main indicators: three of them (External, Mental, and Reflective) correspond to the three levels of EC per the authors’ (Pons et al., 2004) theory, and the fourth indicator (Total score) is the sum of the points obtained from the first three indicators. The score can range from 0 to 3 for each of the three indicators. Accordingly, the total score for EC can range between 0 and 9. The total raw score is the sum of points for all 22 tasks, ranging from 0 to 22 points. The reliability of this instrument for Russian-speaking samples has been demonstrated previously (Bukhalenkova et al., 2024).

To assess EF, the NEPSY-II assessment battery was used (Korkman et al., 2007). Using this instrument, the following components were assessed in children: cognitive flexibility, inhibitory control, and working memory (both visual and verbal). To assess inhibitory control and cognitive flexibility, the Inhibition subtest (NEPSY-II) was used: in the task, the child first had to correctly name circles and squares, as well as upward and downward arrows, and then, following the rule, name them in reverse—circles as squares, squares as circles, and arrows in the opposite direction. Tasks performance correctness and time were assessed. Working memory was assessed through Sentence repetition (verbal working memory, maximum score—34) and Memory for designs (visual working memory, maximum score—120). The test had been translated into Russian, adapted for use with Russian-speaking children aged 5–8 years and showed high reliability (Veraksa et al., 2020).

The assessment was conducted individually with each child in a quiet and bright room of the kindergarten attended by the children. Two sessions were organized with each child, lasting 15–20 min. Children were free to stop the test at any time. All methods were presented to children in the same established order: at the first session, the TEC, and Memory for Designs subtest; at the second session, the Inhibition and the Sentence repetition subtests were carried out. Prior to the study, the testers completed specialized training sessions on the administration and scoring procedures of the specified methods. Subsequently, they were required to pass a certification exam, which involved submitting a video recording of themselves conducting and processing the tests. Their scores were compared against those assigned by experienced experts. Only testers who achieved an inter-rater reliability score of at least Cronbach’s α = 0.81 were certified to conduct further testing.

All the parents were informed about the study goals and gave written consent for their children’s participation in the research. The study was carried out in those educational institutions with which cooperation agreements were concluded, and parental consent was collected with the help of teachers working in the groups attended by the children.

Preliminary analyses included simple Pearson and Spearman correlation analyses for main study variables. Additional Mann–Whitney test was then conducted to assess the significance of differences in pragmatic competence scales between boys and girls.

To identify the most significant predictors of pragmatic competence, we adopted a block-wise regression approach, ensuring that all necessary assumptions for linear regression were met. In our analysis, each of the four pragmatic competence scales was, in turn, used as the dependent variable. The predictors were organized into three distinct blocks: one for sex and age, one for EF components, and one for EC variables. In the first stage, we constructed a baseline Model 1 that included only the demographic predictors (sex and age). In the second stage, we developed two alternative extended models: in Model 2.1, the baseline model was supplemented with EF components, while in Model 2.2, predictors for EC were added. In the final stage, we built Model 3 by integrating both the EF and EC blocks along with the original demographic predictors.

After constructing all models for each of the four pragmatic competence scales, Model 2 (in two versions, Model 2.1 and Model 2.2) was compared with the baseline model using R², and Model 3 was compared with Model 2. Based on these comparisons, the best-fitting model was selected. All analyses were conducted in Jamovi (version 2.3.16).

Supplementary Table 1 displays Pearson and Spearman correlations among study variables. The correlational analysis revealed significant (at the p < 0.05 level) associations between the pragmatic competence and age, sex (except for “Narrative skills”), Mental level, External level and Reflective levels of EC (except for “Use of nonverbal means of communication”), Cognitive flexibility, Inhibition (except for “Narrative skills”), Verbal working memory, and Visual working memory.

The Mann–Whitney test for identifying sex differences in the pragmatic competence scales revealed significant differences for three of the scales. Differences were significant in favor of girls for “Ability to understand language in context” (U = 379,769, p < 0.001, Rank biserial correlation = 0.1044), “Communication skills” (U = 379,024, p < 0.001, Rank biserial correlation = 0.1062), and “Use of nonverbal means” (U = 380,505, p < 0.001, Rank biserial correlation = 0.1027). For “Narrative skills,” no significant differences were found (U = 404,272, p = 0.081, Rank biserial correlation = 0.0467).

Preliminary checks of the predictors did not reveal any multicollinearity issues (VIF statistics ranged from 1.01 to 1.60). We conducted separate block-wise linear regression models for each of the four scales of pragmatic competence. The models provide standardized estimates.