Age-Related Trajectories in Symptom Manifestation in Preschoolers with Autism and Developmental Delay

Nasledov, A.D. Saint Petersburg State University, Russia

Tkacheva, L.O. Saint Petersburg State University, Russia

Miroshnikov, S.A. Saint Petersburg State University, Russia

Introduction 

Given the high prevalence of autism (Isaac et al., 2025), understanding the age-related manifestation of autism symptoms in early childhood has become a priority in contemporary research for several compelling reasons. First, early childhood is a critical window of opportunity due to significant neurodevelopmental plasticity (Mualem et al., 2024). Identifying autism symptoms during this period enables timely interventions, thereby maximizing developmental outcomes, as demonstrated in multiple studies (Maksimović et al., 2023). Second, specific early intervention, such as applied behavior analysis (ABA) and speech therapy, have been shown to significantly improve cognitive, social, and communication skills in children with autism spectrum disorder (ASD) (Gitimoghaddam et al., 2022). Characterizing how symptoms manifest across different ages helps refine diagnostic criteria and facilitate the identification of children most likely to benefit from such interventions. Third, early identification and intervention may prevent or mitigate the emergence of secondary emotional and behavioral difficulties that often arise when autism goes unrecognized or inadequately supported (Esposito et al., 2024). 

Another motivation for this study stems from the well-recognized heterogeneity of ASD. It is widely accepted that autism is a highly heterogeneous condition, and this diversity is particularly pronounced in early childhood (Masi et al., 2017). Understanding how symptoms evolve with age can therefore inform the identification of subtypes and the tailoring of interventions to individual profiles. Research into age-related symptom dynamics is essential, as the severity of autistic symptoms is known to change over time (Waizbard-Bartov & Miller, 2023). Tracking these patterns allows researchers to examine how specific symptom domains, such as repetitive behaviors or social communication difficulties, manifest across the child’s development, particularly as environmental and social demands shift with age. Furthermore, characterizing symptom manifestation in early childhood may enable the detection of subtle, earlier markers of autism, thereby supporting earlier and more precise diagnosis. Another benefit of this line of research lies in its potential to refine diagnostic criteria for ASD. By illuminating how symptoms manifest across different developmental stages, such work can make diagnostic criteria more accurate and sensitive to the developmental nuances of the condition. 

The findings of this study address age-specific challenges in assessment. Diagnostic tools and procedures can be adapted to better suit the unique context of evaluating very young children. This, in turn, may facilitate the identification of age-appropriate assessment methods, while minimizing false positives, false negatives, and the high variability in sensitivity and specificity that often accompany traditional instruments. Such variability is known to arise from multiple factors, including floor effects, which have been documented in widely used tools such as the Modified Checklist for Autism in Toddlers, Revised with Follow-Up M-CHAT-R/F; Communication and Symbolic Behavior Scales Developmental Profile CSBS DP; Autism Diagnostic Observation Schedule, Second Edition ADOS-2 (Fulceri et al., 2025; Saldaris et al., 2024; Thurman et al., 2024; Zheng et al., 2024). Understanding how autism symptoms manifest at different ages is also crucial for differentiating ASD from other developmental conditions that may present with overlapping features in early childhood. These include speech and language delays, intellectual disabilities, global developmental delay, attention-deficit/hyperactivity disorder (ADHD), sensory processing disorder and separation anxiety. The importance of such differentiation is underscored by the high rates of comorbidity between ASD and other conditions in early childhood (Al-Beltagi, 2021). 

The objectives of this study were twofold. First, we aimed to identify age-specific patterns of autism symptom manifestation in younger (1–2 years), middle (3–5 years), and older (6–7 years) preschoolers with ASD. Second, we sought to compare these age-related trajectories with those observed in preschoolers with DD. By doing so, this study intended to support early identification and intervention, deepen understanding of developmental trajectories in ASD, inform diagnostic practices, and optimize intervention strategies, ultimately contributing to improved outcomes for individuals with autism and their families.

Methods

Participants

Data from the youngest age group (1–2 years) were combined with data from the middle (3–5 years) and oldest (6–7 years) age groups. Table 1 presents the sample composition by age, sex, and diagnosis.

Table 1

Composition of the Combined Sample

		Diagnosis		Total
		ASD	DD
Age	1–2-year-olds	130 (89 male)	27 (22 male)	157 (111 male)
	3–5-year-olds	487 (345 male)	218 (148 male)	705 (493 male)
	6–7-year-olds	300 (217 male)	77 (44 male)	377 (261 male)
Total		917 (651 male)	322 (214 male)	1,239 (865 male)

Sample size was determined followed the recommendations of S.B. Green (1991). Given that confirmatory factor analysis (CFA) was planned with no more than 10 observed variables per factor, applying the rule of at least 10 observations per independent variable yielded a minimum required sample size of 100. Applying Green’s alternative rule, based on a power of 0.80 (α = 0.05) and up to 10 predictors per factor, a minimum of 119 observations was required to detect an average effect size. Consistent with this assumption, factor loadings exceeded |0.5|, suggesting an effect size at or above average. Thus, the sample of 1–2-year-olds with ASD (N = 130) is sufficient for the study’s objectives.

Materials

For this stage of the study, we developed an online questionnaire assessing autism markers in 1–2-year-olds, modeled after instruments previously developed for 3–4- and 5–6-year-old children (Nasledov et al., 2021; Nasledov et al., 2024a). The questionnaire comprises 274 markers of ASD, organized into tasks based on the situational contexts in which these markers typically manifest (e.g., play, dressing, communication). Each marker (item) is rated on a binary scale (0 = no – marker not present, 1 = yes – marker present). Consistent with our previous approach, the item bank represents a deliberately extensive collection of descriptions of autism signs and their situational contexts. Items were derived from survey responses of professionals working in medical, psychological, and educational commissions, who reported the markers they rely on during diagnostic assessments. The interface of the questionnaire mirrors the versions used for 3–4- and 5–7-year-old children, but includes only markers applicable for the assessment of 1–2-year-olds. Alongside new tasks developed specifically for this youngest age group, the questionnaire incorporates 36 items that were also included in the instruments for 3–7-year-olds. Of the 40 ASD screening items originally used for 3–4-year-old children (Nasledov et al., 2021; Table 4), 36 were retained for analysis in this study. Four items were excluded from the current analysis due to their inapplicability to 1–2-year-old children: B2501, C3304, L1304, and S5301.

Procedure

The data collection procedure was consistent with that previously employed for 3–4- and 5–6-year-old children (Nasledov et al., 2021; Nasledov et al., 2024a). Data were collected between November 2024 and March 2025 by 23 experienced specialists (psychologists, speech pathologists), who worked regularly with the children. Data collection was conducted via an online questionnaire and did not require tests or other assessments beyond routine inquiries. Specialists were asked to respond to items based on their routine observations and checkups regarding autism markers detectable in each child. Parents were interviewed through face-to-face conversations. To ensure objectivity and minimize bias, specialists completed the questionnaire only for children with whom they had already held multiple meetings and parent consultations—typically at least five sessions. The team of specialists consisted of professionals who had participated in previous studies.

Group assignment (ASD vs. DD) was determined by the same specialists working directly with the children, based on their prior experience and current expert opinion derived from practical work with each child. Parents of 1–2-year-olds sought correctional support rather than a formal diagnosis, which is typical for this age group. At approximately two years of age, children undergo rapid development and exhibit a wide variation in behavior, communication, and social skills. Some typical developmental delays or differences may resemble early signs of autism, but may resolve naturally or follow different developmental trajectories. Consequently, distinguishing between typical variation and a neurodevelopmental disorder at this age is challenging, particularly when a child is assessed by unfamiliar individuals in novel situations, which may elicit uncharacteristic behaviors. Thus, data were collected on children without a pre-existing formal diagnosis. Children were classified by specialists into ASD or DD groups based on observations during scheduled classes and consultations, conducted at the request and with the consent of parents. A detailed description of the online survey and parent interview procedures is provided in previous articles (Nasledov et al., 2021; Nasledov et al., 2023; Nasledov et al., 2024a). In total, 157 1–2-year-old children participated in the study (130 with ASD, 27 with DD). 

Data Analysis

The data analysis was carried out in two stages: first, a factor structure with factor validity and invariance in different parts of the sample was identified, and then the calculated factors were used to identify the features of ASD symptoms in children of different age groups, and depending on the diagnosis (ASD or DD). At the first stage, exploratory factor analysis (EFA) was used first, followed by confirmatory factor analysis (CFA), including intergroup analysis. EFA was used on tetrachoric correlations using the minimum remainder method, with parallel analysis to estimate the number of factors. The “diagonally weighted least squares (DWLS) method using a polychoric correlation matrix” was used for CFA, which does not require multidimensional normality (Li, 2016). Confirmatory factor models were evaluated using recommended consent indices and their thresholds (Byrne, 2010; Chen, 2007; Kline, 2011). At the second stage, the obtained factors were calculated as the average values of the items included in them, and samples differing in age and diagnosis were compared according to the calculated factors. To analyze the differences in symptoms depending on age (1–2, 3–5, and 6–7 years), One-Way Multivariate ANOVA was used: factor – Age; dependent variables – calculated factors. To analyze the differences in age-related changes depending on the diagnosis (ASD, DD), Two Way Multivariate ANOVA was used: factors – Age, Diagnosis; dependent variables – calculated factors. In both cases, Post Hoc Comparisons and Contrasts within the framework of one-dimensional ANOVA were used to clarify the statistically significant multidimensional effects of factors and their interactions. The entire analysis was performed using JASP 0.18.3 and Jamovi 2.4.14.0 software.

Results

Exploratory factor analysis (EFA) was performed on the full sample of children with ASD (N = 917) using 36 binary items to identify the underlying factor structure and group items into subscales. The analysis employed the minimum residual extraction method, a tetrachoric correlation matrix and oblimin rotation. Following the removal of 10 items and reduction to three factors, a parsimonious three-factor structure was obtained comprising 26 items (8–9 per factor). Each item loaded at ≥ .531 on its primary factor and ≤ .301 on all other factors. Each factor demonstrated adequate internal consistency, with Cronbach’s alpha coefficients ranging from .781 to .863. The factor composition is shown in Table 2.

Table 2

Main Results of Factor Analysis and Verification of Reliability of Scales

Factorization of 26 items (N = 917): α = .891; 59.3% of Variance	FL*
Factor 1: “Communication” (Com**; 28.4 % of Variance), α = .863 (9 items)
L8201. The child is practically unable to communicate	.988
M7205**. The child easily talks about their needs. Uses words, phrases, gestures, and facial expressions.	.855
L8303. The child does not respond to questions addressed to him/her.	.847
M1601. The child does not attempt to communicate with other people. He/she does not communicate his/her needs, tries to take everything on his/her own, or uses strategies typical to young children (crying). What the child was “asking” for becomes clear when the crying stops.	.753
G2101. The child plays by him/herself, is aloof, does not allow others to join his play, neither adults nor children.	.747
L0903**. The child immediately looks at the person who is addressing him/her.	.741
L1003**. Showing something to another person, the child places the object so that it can be viewed and checks whether the person sees what he/she is being shown.	.731
L1501. The child does not imitate the actions of other people: he/she is busy with his/her own business, and does not pay attention to others.	.715
C3201. It seems that the child does not pay attention to the surroundings, but wanders around, takes objects aimlessly, does not focus on them, and immediately throws them, sometimes behind his back.	.677
Factor 2: “Hyperactivity” (Hyp***; 17.8% of Variance), α = .795 (8 items)
N6901. There are too many unnecessary movements in the child’s activity; the child is fussy, hyperactive.	.798
B2502. Can’t play quietly.	.787
B2901. The child is aggressive, pugnacious, and prone to physical aggression against animals and other people.	.743
B6202. When something blocks the child from getting what they want, the child “loses control” (e.g., meltdown, aggression, prolonged crying) beyond what is expected for the child’s age.	.740
P3905. The child can’t sit still, leaves his seat in the classroom or elsewhere, jumps up, and wanders around.	.731
B6201. Loses self-control, is prone to emotional outbursts.	.718
B2603. The child is often angry and irritable.	.693
B2503. The child is challenging to control. His/her behavior depends on external stimuli - “I run everywhere I look” (chaotic behavior).	.598
Factor 3: “Sensory Disintegration” (SD***; 16.6% of Variance), α = .782; (9 items)
B2804. The child prefers rituals (goes to bed under a certain scenario, drinks only from his/her favorite cup, dresses only in a specific order, walks only along a certain route).	.763
B6501. The child is overly attached to certain objects (blanket, toy, and clothing). If a favorite item is lost, he/she is worried, may get hysterical.	.759
F2303. The child is rebellious, demanding to get changed into the clothes that he/she prefers.	.736
B2805. The child is very picky about food, has a limited range of favorite dishes, constantly demands to be given the same food, and has requirements for food shape, color, consistency, design.	.615
N4205. The child likes to watch lights turn on and off, doors open and close, wheels turn, fan spinning, blinds open and close, shiny objects, pages flickering when flipping through, etc.	.594
I0103. The child retains an unusually long interest in certain objects toys, ropes, balls, stones, plugs and lids, car wheels, toy parts, etc.	.575
N4601. The child is picky/sensitive to certain food textures (for example, pieces in mashed potatoes or porridge). Such foods are perceived by the child as disgusting or intolerable, leading to active avoidance.	.575
N4602. The child’s mouth and the space around the mouth are hypersensitive (difficulties in teeth brushing, speech therapy massage, visiting a dentist).	.534
B2707. The child has unusual fears, such as fear of elevators, stairs, toilets, balconies, vacuum cleaners, etc.	.531

Note. FL = Factor Loads. ** = Inverted Items. *** = the Factors’ (Subscales’) Designation Used Below in the Text. 

Confirmatory factor analysis (CFA) conducted on the sample of children with ASD demonstrates good fit for the three-factor structure, particularly after allowing a residual correlation between items B2805 and N4601. Fit indices indicated acceptable model fit: χ² (295) = 656.203; CFI = .948; TLI = .943; RMSEA = .037 (p = 1.000); SRMR = .047. The positive residual correlation between these two items is explained by their shared reference to the child’s food preferences, in addition to both belonging to Factor 3. Discriminant validity was supported by the Fornell-Larcker criterion (Fornell & Larcker, 1981). The minimum average variance extracted (AVE) was .217 (for Factor 3), while the highest inter-factor correlation was r = .31. The squared correlation (r² = .096) was lower than the minimum AVE, confirming discriminant validity. Internal consistency, assessed by Cronbach’s α, was acceptable. Reliability coefficients ranged from .713 (for the Sensory Disintegration scale) to .783 (for the total 26-item scale).

Checking 3-Factor Structure Equivalence for Different Ages of the ASD Sample

Multigroup confirmatory factor analysis (MGCFA) was conducted to assess the equivalence of the three-factor structure across different subsamples. The results of the comparison between autistic boys and girls aged 1–7 years are presented in Table 3.

Table 3

Model Fit Indexes for 1–7-Year-Old Boys and Girls

Invariance testing	χ2	df	CFI	TLI	RMSEA
Configural	881.035	592	.958	.954	.033
Metric	923.686	615	.955	.953	.033
Scalar	946.704	638	.955	.955	.033
Strict	1011.689	664	.950	.951	.034

The unconstrained model demonstrates configurational equivalence of the factor structure across boys and girls, with excellent model fit: χ2/df < 2; CFI > .95; TLI > .95; RMSEA < .05. Differences in CFL, TLI, and RMSEA between the unconstrained model and subsequent constrained models did not exceed .01, indicating that measurement invariance held across all levels of constraint. Specifically, invariance was supported for: (a) metric invariance (equal factor loadings), (b) scalar invariance (equal intercepts), and (c) strict invariance (equal residual variances). These results confirm that the three-factor structure is equivalent across autistic boys and girls aged 1–7 years.

The results of the structures comparison for 1–2- and 3–7-year-old children are shown in Table 4.

Table 4

Model Fit Indexes for 1–2- and 3–7-Year-Olds

Invariance testing	χ2	df	CFI	TLI	RMSEA
Configural	119.434	590	.983	.982	.034
Metric	1465.855	613	.976	.975	.040
Scalar	1579.329	636	.974	.973	.041
Strict	1826.472	663	.968	.968	.045

The configurational equivalence of the structure for 1–2- and 3–7-year-old children is confirmed: χ2/df < 2; CFI > .95; TLI > .95; RMSEA < .05. The differences between CFI, TLI, and RMSEA for the previous and subsequent limited models do not reach .01. Thus, the equivalence of models for 1–2- and 3–7-year-olds is also certainly confirmed for all levels of restriction. 

Age Differences on Scales for ASD Sample

Table 5 shows descriptive statistics for the compared groups, and Figure 1 shows a graphical illustration.

Table 5

Descriptive Statistics of Scales for Groups Compared by Age and Diagnosis

Diagnosis		Age
		1–2-year-olds			3–5-year-olds			6–7-year-olds
		Hyp	Com	SD	Hyp	Com	SD	Hyp	Com	SD
ASD	Mean	.359	.589	.385	.294	.564	.427	.330	.477	.393
	N	130	130	130	487	487	487	300	300	300
	Std. Dev.	.280	.251	.255	.271	.256	.297	.273	.223	.224
DD	Mean	.418	.424	.350	.228	.269	.162	.231	.117	.136
	N	27	27	27	218	218	218	77	77	77
	Std. Dev.	.363	.292	.211	.255	.226	.165	.261	.150	.164
Total	Mean	.369	.561	.379	.273	.473	.345	.310	.404	.340
	N	157	157	157	705	705	705	377	377	377
	Std. Dev.	.295	.265	.248	.267	.282	.291	.273	.256	.237

Figure 1. Age differences in the scales depending on the diagnosis (Y-axis is proportion of positive responses).

According to the multidimensional Pillai Test, the effect of the Age factor is statistically significant (p < .001). According to one-dimensional ANOVA, the effects of the Age factor on Hyperactivity (Hyp) (p = .027; η² = .008) and Communication Disorders (Com) (p < .001; η² = .031) are statistically significant; the effects of the Age factor on Sensory Disintegration (SD) is not statistically significant (p = .240; η² = .002).

Hyperactivity (Hyp). According to the results of Post Hoc Comparisons, there are statistically significant differences only in the pair of 1–2- and 3–5-year-olds (p = .04; Cohen’s d = .238): Hyperactivity in 1–2-year-old children is higher than in 3–5-year-olds. According to the contrast criterion, Hyperactivity in 1–2-year-old children is also higher than in 3–7-year-olds, but the differences do not reach statistical significance (t (914) = 1.806; p = .071).

Communication Disorders (Com). According to the results of Post Hoc Comparisons, there are statistically significant differences in the pair of 1–2- and 6–7-year-olds (p < .001; Cohen’s d = .455), and in the pair of 3–5- and 6–7-year-olds (p < .001; Cohen’s d = .355): the highest Communication Disorders are in 1–2-year-olds, the lowest are in 6–7-year-olds.

Differences in Scales Between Samples (ASD and DD) Depending on Age

Descriptive statistics are shown in Table 6. According to the multidimensional Pillai Test, the main effects of Age and Diagnosis factors, as well as the effect of their interaction, are statistically significant (p < .001). The primary focus of this study is the interaction between age and diagnosis (ASD vs. DD). While main effects would indicate overall group differences or general age-related changes, a significant interaction is required to determine whether the developmental trajectories of autistic symptoms differ between children with ASD and those with DD. Specifically, an interaction would suggest that the rate, direction, or pattern of change in symptoms across early childhood is not uniform across diagnostic groups—a finding with important implications for understanding the divergence of developmental pathways in the first years of life.

Hyperactivity (Hyp). The main effect of the Diagnosis factor is not statistically significant (F (1, 1233) = 2.232; p = .135; η² = .014). The effect of the interaction of Age and Diagnosis factors only slightly falls short of statistical significance (F(2, 1233) = 2.844; p = .059; η² = .005). Table 6 shows the results of paired comparisons of averages.

Table 6

Post Hoc Comparisons - Age ✻ Diagnosis (Hyperactivity, Hyp)

		df	t	Cohen’s d	ptukey
(1–2 ASD)	(1–2 DD)	1233	-1.039	-.22	.905
	(3–5 DD)	1233	4.345	.481	< .001
	(6–7 DD)	1233	3.286	.473	.013
(3–5 ASD)	(3–5 DD)	1233	2.966	.242	.036
(6–7 ASD)	(6–7 DD)	1233	2.872	.367	.048

Note. P-value adjusted for comparing a family of six estimates

Hyperactivity rates were similarly elevated in 1–2-year-old children with ASD and DD, with no statistically significant differences between the two diagnostic groups. Across the entire age range, overall group differences in hyperactivity did not reach statistical significance. However, among children aged 3–5 years and 6–7 years, hyperactivity levels were significantly lower in the ASD group than in the DD group. This finding reflects a more pronounced age-related decline in hyperactivity among children with DD compared to those with ASD.

Communication Disorders (COM). The main effect of the Diagnosis factor is statistically significant (F (1, 1233) = 5.602; p < .001; η² = .118). The effect of the interaction of Age and Diagnosis factors is statistically significant (F (2, 1233) = 5.602; p = .004; η² = .008). Table 7 shows the results of paired comparisons of averages.

Table 7

Post Hoc Comparisons - Age ✻ Diagnosis (Communication Disorders, COM)

		df	t	Cohen’s d	ptukey
(ASD 1–2)	(DD 1–2)	1233	3.276	.693	.014
(ASD 3–5)	(DD 3–5)	1233	15.204	1.239	< .001
(ASD 6–7)	(DD 6–7)	1233	11.85	1.514	< .001
(DD 1–2)	(DD 3–5)	1233	3.18	.649	.019
	(DD 6–7)	1233	5.764	1.289	< .001
(DD 3–5)	(DD 6–7)	1233	4.83	.64	< .001

Note. P-value adjusted for comparing a family of six estimates.

Across all three age ranges, Communication Disorders were significantly more pronounced in children with ASD than in those with DD. While Communication Disorders decreased with age in both diagnostic groups, the decline was significantly steeper among children with DD.

Sensory Disintegration (SD). The main effects of the Diagnosis factor (F (1, 1233) = 75.062; p < .001 η² = .056) and the Age factor (F (2, 1233) = 5.680; p = .004; η² = .008) are statistically significant. The effect of the interaction of Age and Diagnosis factors is statistically significant (F (2, 1233) = 8.634; p < .001; η² = .013). Table 8 shows the results of paired comparisons of averages.

Table 8

Post Hoc Comparisons - Age ✻ Diagnosis (Sensory Disintegration, SD)

		df	t	Cohen’s d	ptukey
(ASD 1–2)	(DD 1–2)	1233	.666	.141	.986
(DD 1–2)	(DD 3–5)	1233	3.73	.761	.003
	(DD 6–7)	1233	3.871	.866	.002
(ASD 3–5)	(DD 3–5)	1233	13.168	1.073	< .001
(DD 3–5)	(DD 6–7)	1233	.791	.105	.969
(ASD 6–7)	(DD 6–7)	1233	8.143	1.04	< .001

Note. P-value adjusted for comparing a family of six estimates.

Sensory Disintegration was equally pronounced in 1–2-year-olds with ASD and DD. In contrast, among children aged 3–5 and 6–7 years, Sensory Disintegration declined significantly in the DD group, while no significant decline was observed in the ASD group. The main effect of diagnosis was twice as large for Communication Disorders as for Sensory Disintegration and approximately ten times as large for Communication Disorders as for Hyperactivity. Accordingly, Communication Disorders showed the largest differences between children with ASD and DD.

Discussion

The objectives of this study were twofold: first, to identify age-specific patterns of autism symptoms manifestation in younger, middle, and older preschoolers with ASD; and second, to compare these age-related trajectories with those observed in preschoolers with DD. Additionally, we tested the hypothesis that the three-factor structure would be equivalent across the samples of 1–2-year-olds and 3–7-year-olds with ASD. 

The discussion proceeds as follows. First, we explain and provide theoretical substantiation for the three-factor structure, in which each factor formed a scale with adequate internal consistency (see Table 2). Second, we discuss age-related differences on these scales within the full ASD sample (Table 5 and Figure 1). Finally, we examine the trajectories of symptom manifestation by comparing the ASD and DD samples across three age groups (Tables 6–8).

Interpretation of 3-Factor Structure of Autistic Symptoms in 1–2-Year-Olds

Exploratory factor analysis yielded a parsimonious three-factor structure comprising 26 items (8–9 per factor). The factors were interpreted as Communication Disorders (Com), Hyperactivity (Hyp) and Sensory Disintegration (SD). The first factor (Com) was named based on the items pertaining to the child’s interaction with others. These items include: lack of interaction with others; non-use of communicative gestures; non-response to spoken speech; preference for solitary play; impaired joint attention within the context of interaction; and lack of imitation. The second factor was designated Hyperactivity (Hyp), as it comprises items related to excessive movements, noisiness, a tendency toward arousal and hyper-excitation with aggressive tendencies, difficulties in behavioral and motor control, and impulsivity. The third factor was labeled Sensory Disintegration (SD), as the items concern ritualistic behavior, altered sensory sensitivity, and insistence on sameness. Specific tasks include: preference of ritualism; excessive attachment to certain objects; and seeking or avoidance of particular sensory stimuli.

Previous research has demonstrated that markers and symptoms of ASD begin to emerge within the first year of life and can be detected as early as 6 to 18 months of age (Tanner & Dounavi, 2021). In light of the three-factor structure obtained in the present study, it is noteworthy that both communication difficulties and sensory disintegration (or sensory processing difficulties) are core symptoms of autism. According to the DSM-5 (American Psychiatric Association, 2013), these symptoms typically emerge in early childhood and often persist across the lifespan (American Psychiatric Association, 2013). A recent meta-analysis revealed that communication differences in children on the autism spectrum may already be apparent by the age of one year (Collins et al., 2025). Researchers have identified several key indicators of communication difficulties at this age, including: absent or limited eye contact; failure to respond to one’s name; absence of pointing gestures; difficulties with imitation (Frye et al., 2019); and very limited interest in playing with peers (McGlade et al., 2023). Additional characteristics include delayed speech onset, lack of gestural communication; difficulty understanding spoken language and atypical prosody (Lund et al., 2025). The classic autistic symptom of sensory disintegration can also manifest as early as 1–2 years of age. Affected children may exhibit repetitive movements, motor stereotypes, intense preoccupation with specific objects; unusual play with objects; and adherence to routine or insistence on sameness (Canu et al., 2021). Sensory disintegration is frequently associated with rituals and repetitive behaviors in autism (Boyd et al., 2010). Although repetitive behaviors in early childhood typically serve as a foundation for learning and exploration, in autism these behaviors may persist or intensify in response to ongoing sensory challenges. Rituals tied to sensory needs may become reinforcing because they provide consistent sensory input that the child craves or requires to feel comfortable (Donnellan, Hill & Leary, 2012). Given this established theoretical and empirical framework, the emergence of these two factors—Communication Disorders and Sensory Disintegration—within the factor structure of autism symptoms in 1–2-year-olds was not unexpected.

Unlike Communication Disorders and Sensory Disintegration, hyperactivity is not a core symptom of autism according to the DSM-5. Nevertheless, it represents a common and important feature to understand, as its presentation in autistic children often differs from that observed in typically developing children, children with developmental delay (DD), or those with attention-deficit/hyperactivity disorder (ADHD) alone. Research indicates that autistic children may exhibit constant movement such as running, climbing, jumping, or fidgeting, that can appear relentless and difficult to control (Al Ghamdi & AlMusailhi, 2024). They often shift focus rapidly between objects or activities, which impedes sustained engagement in play or learning. Additionally, sleep difficulties, including problems falling asleep or frequent night awakenings, may exacerbate daytime hyperactivity (Berenguer et al., 2024). Several potential mechanisms have been proposed to explain hyperactivity in this age group. First, hyperactivity may serve as a means of seeking sensory input or coping with sensory overload (Huang et al., 2024). Second, differences in brain maturation trajectories may affect activity levels and behavior regulation (O’Hearn & Lynn, 2023). Third, limited communication skills, particularly restricted verbal abilities, may lead children to express their needs or frustrations through increased activity or behavioral outbursts (Theodoratou, 2024). Finally, both over-stimulating and under-stimulating environments have been shown to exacerbate hyperactive behaviors (Gentil-Gutiérrez et al., 2021). 

Thus, two of the three factors identified in the symptom structure for 1–2-year-olds with autism correspond to classic core symptoms of the condition. The third factor, Hyperactivity, represents a non-specific symptom that may nonetheless play a crucial role at this age, given its multifaceted nature and its susceptibility to influences such as sensory needs, neurological differences, and communication abilities.

When interpreting the three-factor structure of autism symptoms in preschoolers, it is essential to consider social and environmental factors. As autistic children grow, social interactions and environmental demands become increasingly complex, often rendering communication and sensory challenges more apparent. In the absence of early intervention and consistent support, these symptoms may remain stable or even intensify—a challenge that underscores the consequences of delayed autism diagnosis and its associated costs. It is noteworthy that our previous models of autistic symptoms in preschoolers yielded different factor structures when analyzed using structural equation modeling (SEM) on large samples of children, with the number of factors ranging from seven to eight, depending on age (Nasledov et al., 2023; Nasledov et al., 2024b). However, when we specifically examined age-related changes in autistic symptoms, we identified three clusters of correlated symptoms that closely resemble those described in the present manuscript (Nasledov et al., 2024a). Such variation in symptom combinations may be explained by differences in approaches and therapeutic strategies. Some children may develop compensatory strategies over time, even as core difficulties often persist. This pattern of stability in core symptom domains, coupled with variability in their surface-level expression, provides a basis for substantiating the equivalence of the three-factor structure across samples of 1–2-year-olds and 3–7-year-old boys and girls with ASD. 

Age- and Diagnosis-Related Differences in Scales between ASD and DD Samples

Differences on the symptom scales between the ASD, DD, and normative sample were examined as a function of age and diagnosis (see Tables 5–8 and Figure 1). The factor Age had a significant effect on Hyperactivity (Hyp) (p = .027; η² = .008) and Communication Disorders (p < .001; η² = .031). Hyperactivity was higher in 1–2-year-old children than in 3–5-year-olds, regardless of diagnosis. However, among 1–2-year-olds, hyperactivity was higher in children with DD than in their peers with ASD. Overall, hyperactivity in 1–2-year-old children was also higher than in 3–7-year-olds irrespective of diagnosis, though this difference did not reach statistical significance. As illustrated in Figure 1, the pattern of hyperactivity prevalence differs between diagnostic groups: children with DD show a distinct trajectory of declining hyperactivity with age, whereas children with ASD do not. Several factors may explain why hyperactivity is a common symptom shared by 1–2-year-olds with both ASD and DD. Overlapping neurodevelopmental and behavioral factors likely contribute (Martelli et al., 2025). Hyperactivity may serve as a means of seeking additional sensory input or as a reaction to sensory discomfort or overload. Although sensory issues are more characteristic of autism, children with DD may also experience difficulties processing sensory stimuli, which can contribute to hyperactive behaviors (Delgado-Lobete et al., 2020). Additionally, lower cognitive control in 1–2-year-olds may affect their ability to understand and follow instructions, resulting in hyperactive or impulsive actions (Peisch & Arnett, 2024). More broadly, at this age, the brain systems underlying attention and behavioral regulation are still maturing across all neurodevelopmental pathways; thus, hyperactivity may represent an exaggerated expression of a normative developmental feature in both ASD and DD. However, our results show that children with DD exhibit a distinct trajectory of declining hyperactivity across the preschool years, in contrast to the ASD sample. It is possible that children with temporary delays, whether due to environmental factors or responsive to targeted interventions, may “catch up,” with hyperactivity diminish as they develop (Wootton et al., 2022). In contrast, among preschoolers with ASD, hyperactivity remains highly prevalent, with both overlaps and distinctions in executive function impairment (Christoforou et al., 2023; Esposito et al., 2024).

Communication Disorders emerged as the most prominent symptom group in the ASD sample across all ages. Although a gradual decline in communication difficulties was observed over time in autistic children, this symptom domain remained the most distinguishing feature between the ASD and DD samples. In the DD sample, communication problems in 1–2-year-olds were nearly as pronounced as in children with ASD of the same age, but tended to resolve over time. This finding aligns with previous research. It is well known that autistic children struggle with developing communication skills throughout the preschool years (Kauley et al., 2024), whereas children with DD may overcome problems in communication due to brain maturation and the acquisition of behavioral control by older preschool age (Sheridan et al., 2019).

Sensory Disintegration was significantly more pronounced in children with ASD aged 3–5 years and 6–7 years compared to their peers with DD. However, at 1–2 years of age, the difference between the two diagnostic groups was less pronounced. A clear developmental dynamic was observed: sensory issues declined over time in children with DD, whereas they remained prevalent across the entire preschool period in children with ASD. These findings align with previous research. Sensory issues are considered a core symptom of autism and are consistently reported in children with ASD (Khawer et al., 2025). While young children with DD are also known to experience distinct sensory challenges across different sensory systems (Rodríguez-Armendariz, Vela-Romero & Galiana, 2024), this group appears to benefit from timely targeted intervention, with positive outcomes in overcoming sensory difficulties (Liu et al., 2025).

Overall, when comparing both samples, the main effect of the diagnosis was most pronounced for Communication Disorders. This symptom domain appears to be the key differentiator between children with ASD and those with DD. However, it should be noted that while Communication Disorders represent a highly salient and often early-presenting feature that helps distinguish ASD from DD in preschoolers, it is the specific nature of these communication difficulties, particularly deficits in social communication, combined with restricted and repetitive behaviors and interests that ultimately leads to a diagnosis of ASD. A holistic approach that considers the comprehensive clinical picture, rather than any single symptom in isolation, is essential to guiding the diagnostic process.

Conclusion

The findings of this study demonstrate that symptoms of Communication Disorders, Sensory Disintegration, and Hyperactivity persist throughout the preschool years in children with autism spectrum disorder (ASD). We interpret this persistence as reflecting fundamental and stable neurodevelopmental differences that affect brain function, sensory processing, and self-regulation. Although early intervention can improve functioning and reduce symptom severity, these challenges often continue across the preschool period due to the complexity and stability of the underlying neurological mechanisms. Two of the three factors identified in the symptom structure for 1–2-year-olds with autism correspond to classic core symptoms of the condition. The third factor, hyperactivity, represents a non-specific symptom that may nevertheless play a crucial role at this age, given its multifaceted nature and its susceptibility to influences such as sensory needs, neurological differences, and communication abilities. Hyperactivity emerged as a shared symptom for 1–2-year-olds with both ASD and DD. This overlap likely arises from shared neurodevelopmental delays affecting brain regions responsible for attention, motor control, and sensory processing. Difficulties in self-regulation, communication, and sensory integration contribute to increased motor activity and impulsivity in both groups. Although the underlying mechanisms may differ in detail, the behavioral manifestation of hyperactivity is common due to overlapping developmental challenges at this age. However, a key divergence was observed: children with DD tend to overcome hyperactivity over preschool age, whereas in children with ASD it remains pronounced. A similar pattern was observed for Sensory Disintegration. This symptom was also shared between diagnostic groups at age 1–2 years, with a distinct developmental trajectory toward resolution in children with DD, while remaining prevalent in children with ASD across the preschool period. Notably, Communication Disorders emerged as the most distinct symptom for differentiating children with ASD from those with DD, regardless of age. This finding underscores the centrality of social communication deficits in autism and highlights their diagnostic utility, particularly when considered alongside other core and associated symptoms.

Limitations

Several limitations of this study should be acknowledged. The sample size of children with ASD and DD was limited. This constraint stems from the fact that 1–2-year-olds do not yet attend preschool educational institutions, and are assessed much less frequently than older children, making recruitment for this age group inherently challenging. A second limitation concerns the number of symptom groups identified. While the present study yielded a three-factor structure, our previous research has demonstrated that the number of relatively independent symptom groups in preschoolers with ASD can reach seven (for 3–4-year-olds) and even eight (for 5–7-year-olds). The identification of only three symptom groups in this study can be attributed to two factors. First, at 1–2 years of age, ASD symptoms are not yet as differentiated as they are in older preschoolers—a finding that is developmentally expected. Second, to identify age- and sex-related specifics of symptom manifestation in 1–2-year-olds, it was necessary to establish a structure that could be meaningfully compared with that of older preschoolers. Importantly, the three symptom groups identified—Communication Disorders, Hyperactivity, and Sensory Disintegration—are indeed common across the entire age range from 1 to 7 years.

Another limitation, consistent with our previous studies, is that the symptoms identified were those detected and noted by specialists working directly with each child. Although these specialists were familiar with the children’s typical behavior due to regular interactions, the full range of objective manifestations of ASD may be considerably broader than captured in the present assessment.

Practical Implications

Understanding age-related changes in autistic symptoms during the preschool years carries important practical implications for clinical, educational, and caregiving settings. Recognizing that autistic symptoms may manifest differently depending on the child’s age can help practitioners identify autism more accurately and at an earlier stage. Revealing developmental trajectories of symptom manifestation is crucial for differentiating children with ASD from those with DD, as understanding how these symptoms typically evolve over time is key to accurate diagnosis. Knowledge of typical developmental trajectory allows professionals to determine whether a child is simply lagging behind in certain areas or is exhibiting a deviant pattern of development characteristic of ASD. The earlier a child receives an ASD diagnosis, the sooner appropriate interventions can be initiated, and the better the prognosis for long-term development. Practitioners should therefore be particularly attentive to Communication Disorders in 1–2-year-olds as the most salient early sign that may indicate underlying neurological differences associated with autism. In contrast, Hyperactivity and Sensory Disintegration at this age are shared symptoms that may be present regardless of diagnosis and should be interpreted within the broader clinical context. 

Ethics Statement

This study was approved by the St. Petersburg State University Ethics Committee (Approval No. 02-285, RK No. 115-03-27, dated October 10, 2024). Prior to participation, parents provided written informed consent for both their own participation in the survey and their children’s involvement in the online assessment. The consent forms provided clear and comprehensive information regarding the study’s objectives, procedures, and potential benefits. Considering that 1- and 2-year-old autistic children are particularly sensitive to environmental changes, the study was designed to minimize all physical and psychological risks. To ensure a comfortable environment and prevent distress, pain, or sensory overload, data were collected via online questionnaires completed by specialists who work with the children on a permanent basis. This approach ensured that no unfamiliar procedures were introduced, thereby maintaining the children’s routine and emotional well-being. The research group guarantees that data is collected in an anonymized form, with a unique code assigned to each participant. The group also assumes responsibility for the confidentiality of the collected data and its secure storage in protected databases accessible only to the research team. Only anonymized data will be used in publications and reports. To encourage participation, investigators offered direct benefits to the children through enhanced interventions tailored to the results of their data collection. Additionally, the study contributed to the broader autistic community by providing free, open access to practical research findings via the project’s electronic portal. Parents were explicitly informed of their right to withdraw their child or themselves from the study at any time without negative consequences. Although the procedures posed no risk of distress, the voluntary nature of participation was strictly maintained to ensure ethical compliance. During parental surveys, researchers remained highly sensitive to family privacy, ensuring that questioning was non-intrusive. The data collection was conducted by experts with extensive experience in working with young autistic children. This specialized expertise was critical in avoiding common errors associated with standardized tools like the ADOS-2. In typical clinical settings, lack of prior rapport between an observer and a child can cause frustration, leading to atypical behavior and subsequent data bias. By utilizing researchers familiar with the participants, the study ensured a low-pressure environment that captured more accurate behavioral observations.

Informed Consent from the Participants’ Legal Guardians (if the participants were minors)

Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.

Authors’ Contributions

Conceptualization and methodology, A.N.; software, S.M.; validation and formal analysis, A.N.; investigation and resources, S.M.; data curation, A.N.; writing and original draft preparation, L.T.; writing review and editing, L.T.; visualization, A.N.; supervision, A.N.; project administration, A.N.; funding acquisition, A.N. All authors discussed the results and contributed to the final manuscript.

Conflict of Interest

The authors declare no conflict of interest.

Funding

The reported study was funded by the Russian Science Foundation, project No. 23-18-00155-P. “Study of predictive indicators of autism spectrum disorders in preschool children” (https://rscf.ru/en/project/23-18-00155-П/).

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