Children’s self-regulation development: Continuity, change, and parenting daily hassles

Abstract

Self-regulation is a foundational marker that supports children’s adaptation across cognitive, social, and emotional domains. The bidirectional psychobiological model conceptualizes self-regulation as comprising interrelated top-down processes (e.g., attentional focusing, inhibitory control) and bottom-up processes (e.g., impulsivity) that jointly shape children’s ability to modulate attention, behavior, and emotion. Early caregiving environments, including parents’ experiences of daily hassles, could play a critical role in shaping self-regulation development. However, few longitudinal studies have examined the continuity and change of these distinct domains from toddlerhood to early adolescence and recognized how early parenting daily hassles influence such development. The present study used data from the Arizona Twin Project (N = 1325 twins, 665 families; 49.1% female) to examine developmental patterns of attentional focusing, inhibitory control, and impulsivity from toddlerhood through early adolescence. Autoregressive simplex models characterized stability as carryover from one wave to the next, whereas common factor models characterized continuity as a stable latent disposition shared across waves, with age-specific deviations captured separately. Results indicated that attentional focusing and inhibitory control demonstrated moderate stability in early childhood that strengthened across middle childhood and early adolescence. Impulsivity showed moderate stability from toddlerhood to early childhood, followed by strong continuity from middle childhood through early adolescence. Parental daily hassles in toddlerhood predicted lower attentional focusing and inhibitory control and higher impulsivity. Findings reflect both trait-like continuity and state-like change in self-regulation domains, underscoring how self-regulatory capacities consolidate over time while remaining sensitive to early contextual stress.

The development of self-regulation is a central marker of long-term adaptive functioning, with well-documented contributions to children’s academic readiness, social competence, and psychological well-being (Eisenberg et al., 2024; Robson et al., 2020). Self-regulation is a multifaceted construct (Nigg, 2017), encompassing both top-down processes (i.e., attentional focusing, inhibitory control) and bottom-up processes (i.e., impulsivity). It reflects both trait-like qualities that are relatively stable across developmental stages (Eisenberg et al., 2024) and state-like processes that remain sensitive to change influenced by contextual factors (Blair, 2010; McClelland et al., 2015). Prior research has documented that top-down processes such as attentional focusing (Petersen & Posner, 2012) and inhibitory control (Petersen et al., 2021; Zelazo & Carlson, 2012) show rapid growth across toddlerhood and the preschool years, followed by increasing consolidation around school entry, whereas bottom-up processes such as impulsivity emerge early and tend to decline gradually from early childhood into adolescence (Duckworth & Steinberg, 2015; Forrest et al., 2019). Yet relatively few studies have examined continuity and change across these three distinct domains of self-regulation from toddlerhood through early adolescence, despite evidence that top-down and bottom-up processes follow different developmental courses. Addressing this gap is critical for clarifying when and for which self-regulation domains exhibit stronger trait-like continuity versus greater developmental plasticity. This distinction can help identify sensitive periods and inform the timing of interventions aimed at promoting adaptive development.

Self-regulation shows increasing continuity with age, with early childhood widely viewed as a period of heightened plasticity in which caregiver contexts can shape emerging trajectories (Blair, 2010), underscoring the importance of considering the role of parenting daily hassles. Daily hassles can undermine parents’ capacity to provide sensitive co-regulation and consistent support (Crnic et al., 2005), thereby shaping the developmental course of children’s self-regulatory skills. Examining how parenting daily hassles contribute to self-regulation development could advance theoretical understanding of developmental processes and identify critical opportunities for time-specific prevention and intervention. Building on this rationale, using a large community-based longitudinal twin cohort, the present study investigates continuity and change across three interrelated yet distinct domains of self-regulation (i.e., attentional focusing, inhibitory control, and impulsivity) and examines whether parenting daily hassles is associated with these developmental patterns from toddlerhood through early adolescence.

Continuity and change in self-regulation across development

Self-regulation encompasses interrelated developmental processes spanning cognitive, emotional, behavioral, physiological, and genetic levels. It has been widely conceptualized as a hierarchical, integrated system that involves both top-down and bottom-up processes, jointly shaping children’s capacity to modulate attention, behavior, and emotion, as suggested by the bidirectional psychobiological model (Blair & Ku, 2022). Top-down processes index effortful self-regulation, using higher-order executive functions to intentionally regulate attention and behavior. In contrast, bottom-up processes reflect reactive self-regulation, characterized by more automatic and unconscious reactions to stimuli. Within this framework, the present study focused on three distinct but interrelated self-regulation domains: attentional focusing and inhibitory control, as top-down processes, and impulsivity, as a bottom-up process. Attentional focusing refers to the voluntary capacity to direct and maintain attention toward relevant stimuli while resisting distractions (Rueda et al., 2004). Inhibitory control is defined as the ability to suppress a dominant response to enact an adaptive, goal-consistent response (Diamond, 2013). Impulsivity is a reactive tendency toward immediate rewards (Nigg, 2017).

In infancy, attention is primarily governed by the orienting network, reflected in duration of orienting, which involves the ability to sustain visual fixation on a stimulus for short periods (Colombo, 2001). This early form of attention is largely reactive and exogenously driven, laying the groundwork for later attentional focusing, which involves endogenously controlled, goal-directed attention (Petersen & Posner, 2012). Attentional focusing emerges in toddlerhood and grows rapidly across the preschool years, reflecting the maturation of the executive attention network and prefrontal cortex (Petersen & Posner, 2012; Rueda et al., 2004). During the preschool years, children show improvements in maintaining attention and flexibly shifting focus to meet goal-directed behaviors, skills that are central to the emergence of broader effortful control (Best & Miller, 2010; Garon et al., 2008; Rothbart & Bates, 2006; Zelazo & Carlson, 2012). As children enter formal schooling, attentional focusing becomes more mature and shows increasing stability (Betts et al., 2006; McKay et al., 2010; Yan et al., 2018; Zhou et al., 2007), supporting adaptation to classroom demands and predicting academic achievement (Robson et al., 2020). During middle childhood and early adolescence, attentional focusing becomes increasingly stable, with continuity showing gradual refinement, reflecting both individual differences and the ongoing maturation of the executive attentional system (Volkmer et al., 2022). Twin studies suggest that attentional focusing in middle childhood is moderately to highly heritable, with some evidence for dominant genetic influences (Rea-Sandin et al., 2023), highlighting its characterization as a trait.

In infancy, rudimentary forms of inhibitory control can be observed in early motor inhibition and response suppression, such as the ability to withhold a prepotent reach or gaze toward a forbidden object (Holmboe et al., 2018). These early, reflexive forms of inhibition gradually develop to more voluntary, goal-directed effortful control during toddlerhood, as the prefrontal cortex and associated executive networks begin to support deliberate behavioral regulation (Diamond, 2013). Inhibitory control then shows rapid gains during the preschool years (Kochanska et al., 2000), such that studies using parent-report surveys and laboratory assessments demonstrate substantial growth of inhibitory control between 3 and 6 years (Geeraerts et al., 2021; Moilanen et al., 2010; Petersen et al., 2021; Simpson & Carroll, 2019). With the transition to school years, inhibitory control becomes more stable, supporting school readiness, classroom behavior, and academic competence (Macdonald et al., 2014; Zelazo & Carlson, 2012). During middle childhood and early adolescence, inhibitory control becomes more efficient and flexible, enabling children to apply it in more context-appropriate ways (Best & Miller, 2010). Neurocognitive evidence attributes these refinements to the protracted maturation of the prefrontal cortex that supports cognitive control (Kang et al., 2022). Twin studies suggest that inhibitory control has moderate heritability in early and middle childhood, with both shared and nonshared environmental contributions, highlighting its dual nature as both trait-like and context-sensitive (Gagne & Saudino, 2010, 2016; Rea-Sandin et al., 2023).

Impulsivity displays a developmental trajectory from toddlerhood to early adolescence that differs from the pattern observed for top-down effortful regulation (Côté et al., 2002; Shulman et al., 2016). In toddlerhood, impulsivity is normatively high, reflecting strong temperament-based reactivity to salient stimuli, with individual differences in emerging self-regulatory capacity (Lelakowska et al., 2019; Shaw et al., 2005). In early childhood, impulsivity remains elevated as children continue to develop the higher-order executive function that enables deliberate behavioral regulation, often acting without thinking or having difficulty inhibiting impulses (Côté et al., 2002; Leblanc et al., 2008; Olson et al., 2002). As children enter the school years, impulsivity gradually declines as top-down self-regulation strengthens, supported by the maturation of the prefrontal cortex. This change also reflects maturational shifts within subcortical reward and motivational systems, particularly in the striatum and limbic circuitry, that reduce reactivity and improve goal-related regulated behaviors (Gilman et al., 2024; Inuggi et al., 2014). These neural changes grow alongside environmental feedback, such that consistent routines, parental scaffolding, and classroom expectations help children learn to anticipate consequences and internalize behavioral standards (McClelland et al., 2015). By middle childhood, impulsivity shows moderate rank-order stability, such that children who are more impulsive than their peers tend to remain relatively higher in impulsivity (Forrest et al., 2019; Gilman et al., 2024; Huang et al., 2024). In early adolescence, impulsivity continues to decline, but increases in sensation-seeking outpace still-maturing impulse control, creating a developmental imbalance that leads to elevated risk behaviors (Duckworth & Steinberg, 2015). Together, these patterns suggest that impulsivity reflects a temperamentally rooted, bottom-up disposition that shows trait-like continuity in rank-order stability by middle childhood, while its mean level and behavioral expression remain developmentally and contextually malleable (Duckworth & Steinberg, 2015; Forrest et al., 2019; McClelland et al., 2015).

To characterize continuity and change in self-regulation across development, we estimated both an autoregressive simplex model and a common factor model because they represent different developmental hypotheses about continuity and change over time. The autoregressive simplex model conceptualizes continuity as wave-to-wave carryover, reflecting whether earlier self-regulation predicts later self-regulation and whether the strength of this carryover changes across developmental transitions. In contrast, the common factor model conceptualizes continuity as a stable trait-like component shared across repeated assessments, with age-specific residual variance reflecting occasion-specific influences, contextual shifts, and instrument-specific variance. Considering both approaches is developmentally informative because they highlight different features of continuity in self-regulation domains. The autoregressive simplex model captures how functioning at one period carries forward to the next, thereby emphasizing developmental sequencing and age-to-age transmission. The common factor model captures the extent to which repeated measures reflect enduring individual differences across childhood, even when self-regulation is expressed in developmentally changing forms, consistent with the idea of heterotypic continuity. Taken together, these complementary approaches provide a broader account of developmental patterns by capturing both sequential continuity and persistent stability across childhood.

Parenting daily hassles and development of self-regulation

Across development, the parent–child relationship undergoes normative shifts that reshape socialization processes. In toddlerhood and early childhood, caregivers function as primary co-regulators, scaffolding emerging self-regulation through routines and contingent responding (Lunkenheimer et al., 2023). By middle childhood and early adolescence, parenting increasingly emphasizes monitoring, autonomy support, and negotiation as children spend more time in peer and school contexts (Farley & Kim-Spoon, 2014). Across this period, children are increasingly active agents whose self-regulatory capacities help evoke parenting responses and shape everyday interactions, consistent with transactional socialization processes (Sameroff, 2009). Yet, the quality and consistency of parenting processes are often influenced by parents’ own experiences of daily stress and hassles (Crnic et al., 2005). Parenting daily hassles describe the day-to-day, recurrent challenges of caring for children, such as managing child misbehavior, navigating logistical demands, and coping with household disruptions (Crnic & Greenberg, 1990). Although daily stressors associated with the parenting process could be minor in isolation, they can accumulate over time to create a persistent source of stress. The accumulation of these minor daily hassles has been shown to undermine parenting quality by depleting emotional resources, reducing sensitivity, and disrupting consistency in caregiver responses (Crnic et al., 2005; Li et al., 2022). In turn, heightened daily hassles could compromise parents’ ability to engage in effective co-regulation, diminishing opportunities to scaffold children’s self-regulatory skills, and potentially straining parental emotional regulation capacities (Bornstein, 2020; Muraven & Baumeister, 2000; Winstone et al., 2021).

Parenting daily hassles influence the development of self-regulation. Toddlerhood represents a particularly sensitive developmental stage, as self-regulation undergoes rapid growth and remains highly malleable to contextual influences (Blair, 2010; McClelland et al., 2015). Exposure to elevated parenting daily hassles may interfere with the development of attentional focusing and inhibitory control by reducing opportunities for scaffolding practice and consistent routines, while also exacerbating impulsive responding through inconsistent parenting responses, elevated family stress, and more reactive parent-child interactions (Coplan et al., 2003; Mathis & Bierman, 2015). Empirical evidence suggests that higher levels of parenting daily hassles are associated with weaker cognitive emotion regulation, lower social competence, poorer psychological adjustment, and greater externalizing behavior (Bridley & Jordan, 2012; Chan et al., 2016; Foster et al., 2007; Gülseven et al., 2018). Taken together, these findings suggest that both top-down effortful processes (e.g., attentional focusing, inhibitory control) and bottom-up reactive processes (e.g., impulsivity) are sensitive to parenting daily hassles, highlighting this stressor as a salient predictor of self-regulation development.

Current study

Despite longitudinal studies documenting the continuity and change of self-regulation (Forrest et al., 2019; Heim & Keil, 2012; Petersen et al., 2021), critical gaps remain. Much prior research has treated self-regulation as a global construct or examined isolated domains within narrow developmental windows. Few studies have simultaneously distinguished between top-down processes and bottom-up processes while tracing their continuity and change across the broad span from toddlerhood through early adolescence. Addressing this gap is essential for identifying domain-specific developmental dynamics, pinpointing sensitive periods when self-regulation is most malleable, and informing the timing and targets of interventions.

The current study examined the development of top-down processes (i.e., attentional focusing, inhibitory control) and bottom-up processes (i.e., impulsivity) from toddlerhood through early adolescence. The first research goal was to characterize continuity and age-specific change in each domain across childhood. We hypothesized all three domains would demonstrate moderate rank-order continuity, with stronger stability emerging in middle childhood and early adolescence. The second research goal was to evaluate two ways in which developmental continuity of self-regulation may be represented: (a) as wave-to-wave carryover across adjacent assessments in autoregressive simplex models, where continuity is reflected in the extent to which earlier functioning predicts subsequent functioning over time while recognizing new wave-specific innovations; and (b) as a stable trait-like common factor, where continuity is reflected in enduring individual differences shared across repeated measures. Thus, the autoregressive simplex model emphasizes sequential transmission of prior levels across development, whereas the common factor model emphasizes an underlying stable liability that accounts for covariance across waves. The third research goal was to test whether parenting daily hassles (PDH) at 30 months prospectively predicts children’s self-regulation across childhood within each modeling framework. In the autoregressive simplex models, we examined whether early PDH predicts later self-regulation at each wave above and beyond prior levels, indicating systematic departures from expected continuity over time. In the common factor models, we examined whether early PDH predicts the stable latent factor, indicating enduring between-family differences in children’s self-regulatory functioning across development. Across both approaches, we hypothesized that higher PDH at 30 months would be associated with lower attentional focusing and inhibitory control and higher impulsivity across childhood.

Methods

Participants and procedure

Families were drawn from the ongoing longitudinal Arizona Twin Project. Before data collection, the study protocol was approved by the Institutional Review Board. Written informed consent from parents/guardians and verbal assent from children were obtained prior to each study wave (as developmentally appropriate). Initially, families were recruited through the Arizona State Department of Health Services using state birth records from 2007 to 2008. Information on recruitment and retention is reported in previous publications (Lemery-Chalfant et al., 2019). During toddlerhood, primary caregivers completed the questionnaire during a phone interview. At subsequent waves in early childhood, middle childhood, and early adolescence, they completed the questionnaires online. The analytic sample included 1325 twins (665 families), who contributed data to at least one assessment spanning toddlerhood through early adolescence. Data were collected across six waves, including toddlerhood (30 months, M_age = 2.57, SD = 0.26), early childhood (5 years, M_age = 5.18, SD = 0.27), middle childhood (8 years M_age = 8.44, SD = 0.68 and 9 years, M_age = 9.72, SD = 0.94), and early adolescence (10 years, M_age = 10.9, SD = 1.17; 11 years, M_age = 11.81, SD = 1.13).

Within the analytic sample, wave-specific data availability, reported as number of families, was N = 552 at 30 months, N = 390 at age 5, and N = 709–795 across ages 8–11 (age 8: N = 709; age 9: N = 795; age 10: N = 784; age 11: N = 721). Because the Arizona Twin Project combines re-contact of the original birth-record cohort with recruitment of additional families from the same birth cohort beginning in middle childhood via parent-of-twins groups and online postings, these wave-specific Ns reflect data availability in a staggered-entry design rather than monotone attrition from a single closed cohort. Attrition analyses compared participants who contributed self-regulation data at only one wave versus those who contributed self-regulation data at two or more waves. There was no difference by child sex, χ²(1) = 0.46, p = .50. In contrast, families that contributed to only one wave of data had significantly lower socioeconomic status than families that contributed to two or more waves (t(139.77) = − 3.62, p < .001). For race and ethnicity, White participants were more likely to contribute to data at two or more waves, compared to non-White participants, χ²(1) = 18.36, p < .001, whereas Hispanic participants were more likely to contribute to self-regulation data at only one wave, χ²(1) = 17.05, p < .001.

Participants were 49.1% female, and the sample was racially and ethnically diverse, including 47.9% non-Hispanic White, 38.2% Latino, 3.5% Black, 2.6% Asian, 1.8% Native American, and 6% multiracial. The majority of primary caregivers were mothers (>93%). Families were socioeconomically diverse, with 6.8% below the poverty line, 21.9% near the poverty line, 18.8% classified as lower middle income, 16% as middle income, and 36.5% as upper middle to upper class based on the calculation of income to needs ratios. On average across waves, 1.2% of caregivers reported less than a high school education, 8.9% high school degree, 23% some college, 29.1% a college degree, and 18.3% a graduate or professional degree. Although participants were twins, the classic twin design that decomposes variance into genetic and environmental components was not needed to address our phenotypic research questions. Importantly, twins are representative of singletons in child and adolescent development (Barnes & Boutwell, 2013). Consistent with common practices in developmental research using twin/sibling cohorts (Howard et al., 2026; Mikhail et al., 2025), when the goal is to estimate population-average developmental patterns and between-person associations, we treated twins as individual observations and accounted for within-family non-independence.

Measures

Self-regulation domains (30 Months - Age 11)

Age-appropriate assessments of self-regulation domains (i.e., attentional focusing, inhibitory control, and impulsivity) were administered using the Child Behavior Questionnaire-Short Form (CBQ-SF; Putnam & Rothbart, 2006), Temperament in Middle Childhood Questionnaire (TMCQ; Simon, 2006), and Early Adolescent Temperament Questionnaire (EATQ; Ellis & Rothbart, 1999). These measurements were grounded in Rothbart’s theoretical framework, with items adapted for each developmental stage. Extensive evidence supports the reliability and validity of parent-reported self-regulation measures (Eisenberg et al., 2013, 2015; Putnam et al., 2008). The primary caregiver completed each questionnaire independently for each twin. For each wave, domain-specific mean scores were calculated, and standardized scores were created. Specifically, items were mean composited within each self-regulation domain to form wave-specific scores.

CBQ-SF.

In toddlerhood (30 months) and early childhood (ages 5), self-regulation was assessed using the CBQ-SF. Primary caregivers rated each item on a 7-point Likert scale ranging from 1 (extremely untrue) to 7 (extremely true), reflecting the child’s typical behavior over the past six months. Attentional focusing was measured by six items; an example item included “My child will move from one task to another without completing any of them.” Inhibitory control was measured by six items; an example item included “My child is good at following instructions.” Impulsivity was assessed by six items; an example item included “My child tends to say the first thing that comes to mind, without stopping to think about it.” Scales demonstrated good reliability with McDonald’s Omega (ω) as 0.79 and 0.87 for attentional focusing, 0.71 and 0.95 for inhibitory control, and 0.75 and 0.68 for impulsivity.

TMCQ.

The TMCQ was administered in middle childhood (ages 8 and 9) and early adolescence (ages 10 and 11). Primary caregivers rated on a 5-point Likert scale ranging from 1 (almost always untrue) to 5 (almost always true), based on the child’s behavior over the past six months. Attentional focusing was assessed with seven items; an example item included “When working on an activity, has a hard time keeping his/her mind on it”. Inhibitory control was measured by eight items; an example item included “Can stop him/herself from doing things too quickly”. Both attentional focusing and inhibitory control were assessed with TMCQ at ages 8 and 9. Impulsivity was measured using 13 items; an example item included “Decides what s/he wants very quickly and then goes after it.” Impulsivity was measured with TMCQ across ages 8 through 11. The scale demonstrated good reliability (ω = 0.93–0.94 for attentional focusing, ω = 0.71–0.73 for inhibitory control, and ω = 0.89–0.90 for impulsivity across waves).

EATQ.

The EATQ was used in early adolescence (ages 10 and 11) to assess both attentional focusing and inhibitory control. Primary caregivers responded to a 5-point Likert scale, ranging from 1 (almost always untrue) to 5 (almost always true) when considering children’s behavior in the past six months. Attentional focusing was measured using six items; an example item included “Pays close attention when someone tells her/him how to do something.” Inhibitory control was assessed with five items; an example item included “Is usually able to stick with his/her plans and goals.” The scale demonstrated good reliability for attentional focusing (ω = 0.80 and 0.82) and acceptable reliability for inhibitory control (ω = 0.65 and 0.62).

Parenting daily hassles (30 Months)

Primary caregivers reported on the frequency of everyday hassles and stressors related to child-rearing and parenting tasks using the Parenting Daily Hassles Questionnaire (Crnic & Greenberg, 1990). The measure consists of 15 items with two subscales: Parenting Tasks (8 items) and Challenging Behavior (7 items). Parents rated items on a 5-point Likert scale for frequency of occurrence, ranging from 1 (rarely) to 4 (constantly). Example items included “Continually cleaning up kids’ messes” (Parenting Task) and “Kids resist or struggle over bedtimes” (Challenging Behavior). Mean scores were calculated, with higher values reflecting greater levels of perceived daily hassles in the caregiving context. The scale demonstrated good reliability (ω = 0.83). PDH was reported once by the primary caregiver for the family rather than separately for each child. Therefore, each twin in a family was assigned the same caregiver reported PDH value, and the measure was treated as a family-level contextual predictor.

Covariates

Child age at each assessment, family socioeconomic status at 30 months, and child sex (0 = male, 1 = female) were included as covariates in all models. Child age was included to account for developmental variability within the waves; child sex was included to adjust for potential differences in self-regulation between boys and girls; and family SES was included to control for socioeconomic differences linked to both parenting daily hassles and children’s self-regulation.

Analytic plan

All data preparation, including the creation of mean composites and standardization of scales, was conducted in R Studio Version 4.2. To examine the longitudinal structure of self-regulation, we estimated two alternative developmental models in Mplus 8.7: the autoregressive simplex model (Curran & Bollen, 2001) and the common factor model (MacCallum & Tucker, 1991) for each domain accordingly. The autoregressive simplex model captures stability and change by estimating the extent to which each construct at a given wave is predicted by the preceding wave, thereby modeling continuity as a chain of lagged associations. The autoregressive simplex models were estimated using standardized scores, allowing for direct comparisons of stability coefficients across time. In contrast, the common factor model represents stability across time as a latent factor underlying the measures at each wave, with unique residuals at each age capturing occasion-specific variance. The common factor models were estimated using wave-specific mean composite scores to preserve the scale’s original metric and facilitate interpretation of the latent factor loadings. Model evaluation was based on standard fit indices and cut-off points (Hu & Bentler, 1999), including the Comparative Fit Index (CFI > 0.90), Tucker–Lewis Index (TLI > 0.90), Root Mean Square Error of Approximation (RMSEA <0.08), and Standardized Root Mean Square Residual (SRMR <0.08).

Parenting daily hassles (PDH) at 30 months was then examined as a time-invariant predictor in both the autoregressive simplex and common factor models for each self-regulation domain. Because PDH was reported once by the primary caregiver for the family rather than separately for each twin, the same PDH value was assigned to both children within a twin pair and modeled as a shared family-level predictor. Thus, PDH varied between families but not within families, and there was no within-family PDH component to decompose in a multilevel framework. All models accounted for the non-independence of twin observations by clustering on family ID using TYPE = COMPLEX, which applies a sandwich (cluster-robust) estimator to adjust standard errors and chi-square model tests for family-level clustering. This approach yields valid statistical inference in the presence of within-family dependence. Because our aims were to estimate population-average developmental patterns and associations (rather than decompose genetic and shared environmental variance), twins were treated as individual observations nested within families. Missing data were addressed using full information maximum likelihood (Enders, 2022).

Results

Descriptive statistics

Descriptive statistics and bivariate correlations for self-regulation domains and early parenting daily hassles are presented in Table 1. Within-domain correlations across adjacent waves were positive and moderate in magnitude. Correlations among attentional focusing and inhibitory control were positive, whereas both dimensions showed negative correlations with impulsivity over time. Parental daily hassles were modestly and negatively associated with attentional focusing and inhibitory control, while positively associated with impulsivity. In addition, none of the self-regulation means at any age exhibited skewness or kurtosis values exceeding the recommended thresholds (±2.00 for skewness and ± 2.00 for kurtosis).

Table 1.

Descriptives and bivariate correlation among focused variables.

	1.	2.	3.	4.	5.	6.	7.	8.	9.	10.	11.	12.	13.	14.	15.	16.	17.	18.	19.
1. AF_2	1.00
2. AF_3	0.46***	1.00
3. AF_4	0.20***	0.40***	1.00
4. AF_5	0.25***	0.39***	0.78***	1.00
5. AF_6	0.33***	0.47***	0.60***	0.62***	1.00
6. AF_7	0.21***	0.41***	0.60***	0.63***	0.69***	1.00
7. IC_2	0.45***	0.34***	0.23***	0.28***	0.28***	0.21***	1.00
8. IC_3	0.49***	0.53***	0.47***	0.52***	0.45***	0.43***	0.52***	1.00
9. IC_4	0.31***	0.42***	0.58***	0.56***	0.50***	0.46***	0.43***	0.52***	1.00
10. IC_5	0.23***	0.29***	0.51***	0.57***	0.49***	0.46***	0.35***	0.50***	0.71***	1.00
11. IC_6	0.27***	0.31***	0.43***	0.46***	0.54***	0.41***	0.30***	0.40***	0.53***	0.54***	1.00
12. IC_7	0.29***	0.33***	0.54***	0.54***	0.52***	0.55***	0.30***	0.50***	0.51***	0.53***	0.57***	1.00
13. IM_2	−0.15***	−0.14*	−0.10	−0.22***	−0.18**	−0.14*	−0.28***	−0.17**	−0.20***	−0.21***	−0.19**	−0.19**	1.00
14. IM_3	−0.16**	−0.25***	−0.23***	−0.27***	−0.15*	−0.10	−0.19***	−0.20***	−0.30***	−0.26***	−0.06	−0.08	0.41***	1.00
15. IM_4	−0.24***	−0.31***	−0.62***	−0.51***	−0.42***	−0.41***	−0.31***	−0.43***	−0.69***	−0.56***	−0.48***	−0.55***	0.23***	0.36***	1.00
16. IM_5	−0.26***	−0.25***	−0.56***	−0.63***	−0.42***	−0.39***	−0.33***	−0.43***	−0.61***	−0.66***	−0.58***	−0.62***	0.23***	0.29***	0.76***	1.00
17. IM_6	−0.23***	−0.38***	−0.55***	−0.54***	−0.60***	−0.43***	−0.32***	−0.43***	−0.57***	−0.55***	−0.67***	−0.59***	0.33***	0.26***	0.67***	0.69***	1.00
18. IM_7	−0.23***	−0.29***	−0.54***	−0.54***	−0.49***	−0.54***	−0.24***	−0.44***	−0.58***	−0.55***	−0.52***	−0.72***	0.24***	0.24***	0.66***	0.73***	0.72***	1.00
19. PDH_2	−0.08	−0.16**	−0.14**	−0.20***	−0.00	−0.14*	−0.21***	−0.26***	−0.24***	−0.25***	−0.12*	−0.12	0.08	0.10	0.16**	0.23***	0.13*	0.06	1.00
Mean	4.77	5.03	3.29	3.29	3.34	3.23	4.51	5.04	3.18	3.23	3.66	4.48	4.36	3.03	2.96	2.72	2.82	2.13	4.48
SD	1.03	1.09	0.93	0.95	0.71	0.72	0.98	1.06	0.59	0.59	0.61	1.06	0.97	0.68	0.69	0.66	0.67	0.41	1.06
Minimum	1.33	1.33	1.00	1.00	1.00	1.00	1.00	1.50	1.25	1.13	1.80	1.20	2.00	1.08	1.23	1.15	1.23	1.13	1.20
Maximum	7.00	7.00	4.86	5.00	5.00	5.00	7.00	7.00	4.63	4.75	5.00	7.00	7.00	5.00	4.92	4.92	4.85	3.71	7.00
Skewness	−0.44	−0.67	−0.35	−0.38	−0.23	−0.17	−0.34	−0.46	−0.26	−0.24	−0.19	−0.09	0.09	0.35	0.36	0.40	0.30	0.50	−0.09
Kurtosis	0.11	0.51	−0.56	−0.49	−0.19	−0.02	0.50	0.22	−0.21	0.39	−0.38	−0.23	−0.02	−0.20	0.05	−0.03	−0.08	0.44	−0.23

Note. AF = Attentional Focusing. IC = Inhibitory Control. IM = Impulsivity. PDH = Parental Daily Hassles. SD = Standard Deviation.

^***p < 0.001.

^**p < 0.01.

^*p < 0.05.

Autoregressive simplex models of self-regulation development

To address our first and part of second research goal (characterizing continuity and change in attentional focusing, inhibitory control, and impulsivity from 30 months through age 11 and testing whether stability strengthens across development), we first estimated autoregressive simplex models controlling for child age, family socioeconomic status, and child sex. Model fit indices indicated that the autoregressive models provided an adequate representation of the data for attentional focusing (χ²(23) = 91.55, CFI = 0.94, TLI = 0.91, RMSEA = 0.05, SRMR = 0.07), inhibitory control (χ²(23) = 93.11, CFI = 0.91, TLI = 0.87, RMSEA = 0.05, SRMR = 0.09), and impulsivity (χ²(18) = 91.41, CFI = 0.93, TLI = 0.90, RMSEA = 0.06, SRMR = 0.07).

In the autoregressive simplex models, stability was indexed by the standardized autoregressive path coefficient (β) linking each domain at one wave to the same domain at the subsequent wave. These coefficients can be interpreted as rank-order stability across adjacent assessments, with larger β values indicating greater consistency in children’s relative standing within the domain over time (controlling for covariates and wave-specific residuals). Standardized path coefficients revealed moderate-to-strong stability across adjacent waves for all three self-regulation domains (Figs. 1–3 Panel A). For attentional focusing, autoregressive paths increased from β = 0.50 in early childhood (30 months to age 5) to β = 0.85 by early adolescence (ages 10–11). Inhibitory control showed a similar pattern, with stability coefficients rising from β = 0.42 during the transition from early to middle childhood (ages 5–8) to β = 0.83 in early adolescence (ages 10–11). Impulsivity showed consistently high stability, increasing from β = 0.56 in early childhood (30 months to age 5) to β = 0.91 in early adolescence (ages 10–11). Across domains, autoregressive paths were moderate to strong, with later adjacent waves showing higher stability estimates. In sum, the autoregressive simplex models indicate moderate-to-strong rank-order stability in all three domains, with stability generally strengthening from early childhood into early adolescence.

Fig. 1.

Autoregressive simplex model (Panel A) and common factor model (Panel B) of attentional focusing.

Note. Reported in standardized coefficients. Child age at each wave, family SES at 30 months, and child sex were included as covariates. Model fit for the autoregressive simplex model: χ² = 91.55, df = 23, CFI = 0.94, TLI = 0.91, RMSEA = 0.05, SRMR = 0.07. Model fit for the common factor model: χ² = 74.13, df = 26, CFI = 0.96, TLI = 0.91, RMSEA = 0.04, SRMR = 0.05.

Fig. 3.

Autoregressive simplex model (Panel A) and common factor model (Panel B) of impulsivity.

Note. Reported in standardized coefficients. Child age at each wave, family SES at 30 months, and child sex were included as covariates. Model fit for the autoregressive simplex model: χ² = 91.41, df = 18, CFI = 0.93, TLI = 0.90, RMSEA = 0.06, SRMR = 0.07. Model fit for the common factor model: χ² = 44.27, df = 30, CFI = 0.99, TLI = 0.99, RMSEA = 0.02, SRMR = 0.02.

Common factor models of self-regulation development

To address our first and part of second research goal, testing whether continuity in self-regulation reflects a stable, trait-like component operating across development, we estimated common factor models for each domain, controlling for child age, family socioeconomic status, and child sex. Model fit indices suggested that the common factor model provided a strong fit for attentional focusing (χ²(26) = 74.13, CFI = 0.96, TLI = 0.91, RMSEA = 0.04, SRMR = 0.05), inhibitory control (χ²(18) = 36.82, CFI = 0.98, TLI = 0.94, RMSEA = 0.03, SRMR = 0.03), and impulsivity (χ²(30) = 44.27, CFI = 0.99, TLI = 0.99, RMSEA = 0.02, SRMR = 0.02).

In the common factor models, stability was indexed by the standardized factor loadings of each wave-specific measure on the latent common factor, with larger loadings indicating that the observed score at that age more strongly reflects the stable trait-like component shared across development. Standardized factor loadings indicated that all domains exhibited significant associations with a common underlying factor, although the strength of the loadings varied by age and construct (Figs. 1–3 Panel B). For attentional focusing, factor loadings increased from 0.28 at 30 months to a peak of 0.92 at age 9, before stabilizing around 0.70 at ages 10 and 11. Inhibitory control demonstrated moderately strong and consistent loadings across development, ranging from 0.52 at 30 months to 0.76 at age 11. Impulsivity showed relatively weak loadings in toddlerhood and early childhood (0.32–0.35), followed by strong and consistent loadings from age 8 onward (0.86–0.91). Together, these results indicated that trait-like stability in self-regulation became more prominent across development, particularly for inhibitory control and impulsivity, whereas attentional focusing showed weaker early contributions and stronger loadings beginning in middle childhood.

Early parenting daily hassles associations with self-regulation

Autoregressive Simplex Models.

Higher parenting daily hassles (PDH) at 30 months was associated with lower attentional focusing at age 5 (β = − 0.14, p = .04), but PDH was not significantly associated with attentional focusing at the other assessment wave. Similarly, higher PDH was associated with lower inhibitory control at 30 months (β = − 0.19, p = .002), age 5 (β = − 0.20, p = .004), age 8 (β = − 0.18, p = .01), and age 9 (β = − 0.25, p = .04), but not significantly associated with inhibitory control at ages 10 or 11. In contrast, higher PDH was associated with greater impulsivity at age 8 (β = 0.35, p = .02) and age 9 (β = 0.14, p = .003) but was not linked with impulsivity in any other wave.

Common Factor Models.

PDH at 30 months was significantly associated with the latent common factors of attentional focusing, inhibitory control, and impulsivity, even after accounting for child age, family socioeconomic status, and child sex. Higher PDH predicted lower levels of attentional focusing (β = − 0.18, p < .001) and inhibitory control (β = − 0.28, p < .001), indicating that children exposed to higher levels of PDH in toddlerhood showed reduced levels of self-regulation domains across development. In contrast, higher PDH were positively associated with impulsivity (β = 0.22, p < .001), suggesting that early PDH may contribute to elevated levels of impulsivity over time. In sum, early PDH were prospectively associated with a less adaptive self-regulation profile across development, including lower stable attentional focusing and inhibitory control, alongside higher stable impulsivity.

Discussion

This study advances developmental research on self-regulation by demonstrating that top-down processes (i.e., attentional focusing, inhibitory control) and bottom-up processes (i.e., impulsivity) follow distinct developmental patterns of continuity and change from toddlerhood through early adolescence. Specifically, attentional focusing and inhibitory control showed moderate stability in early childhood that strengthened into early adolescence, whereas impulsivity demonstrated consistently strong stability from early childhood onward, indicating earlier and more enduring continuity for this bottom-up process. The results provide crucial insights into stability and change, as well as potential susceptibility to contextual influences of parenting daily hassles. Consistent with developmental systems theory (McClelland et al., 2015), the findings highlight that different self-regulation domains may exhibit distinct developmental timing and susceptibility to contextual influences. Moreover, associations between parenting daily hassles and self-regulation domains illustrate both the malleability of self-regulation and its sensitivity to social-ecological contexts.

Continuity and change of self-regulation domains

The developmental patterns of self-regulation differed across top-down processes (attentional focusing and inhibitory control) and bottom-up processes (impulsivity), underscoring the importance of examining these domains separately and recognizing that distinct etiological pathways could shape them.

Attentional Focusing.

Consistent with our hypotheses, the autoregressive simplex model indicated that attentional focusing showed moderate stability in early childhood that strengthened across the school years, culminating in greater stabilization during middle childhood and early adolescence (Rueda et al., 2004; Zhou et al., 2007). This pattern aligns with neurodevelopmental evidence that the protracted maturation of the prefrontal cortex and executive attention networks supports children’s increasing capacity to sustain goal-directed attention and resist competing demands (Betts et al., 2006; Petersen & Posner, 2012). Individual differences in attentional focusing are evident in toddlerhood but are less stable at this stage because attentional control remains highly context-dependent and externally scaffolded (Rueda et al., 2004). As executive attention systems mature and children face sustained demands in formal schooling, attentional focusing becomes increasingly stable and trait-like, with longitudinal work showing modest stability in the preschool years that strengthens across middle childhood as effortful control consolidates (Alessandri et al., 2022; Best & Miller, 2010; Kochanska et al., 2000; Li-Grining, 2007). Complementing these findings, the common factor model supported an enduring latent attentional focusing construct from toddlerhood through early adolescence, with age-varying factor loadings. This pattern supports heterotypic continuity, whereby the same underlying trait shows longitudinal continuity even as its behavioral manifestations and measurement indicators shift with development (Petersen et al., 2021; Putnam et al., 2008). Thus, attentional focusing may be expressed early as managing distractibility during play and routines, and later as sustaining attention to multi-step tasks and classroom goals.

Inhibitory Control.

Consistent with our hypotheses, the autoregressive model indicated modest rank-order stability in inhibitory control from toddlerhood through early childhood, followed by strengthening stability across later childhood. This pattern suggests that early individual differences are still consolidating as underlying self-regulatory capacities mature (Geeraerts et al., 2021; Moilanen et al., 2010), with greater stabilization emerging by middle childhood as prefrontal systems develop (Best & Miller, 2010; Eisenberg et al., 2024). Prior longitudinal work similarly shows that inhibitory control is only modestly stable in the preschool years but becomes more robustly stable by middle childhood(Caughy et al., 2025; Pener-Tessler et al., 2022), while continued maturation of top-down regulatory circuitry into early adolescence (Garon et al., 2008; Kang et al., 2022; Rothbart et al., 2011). Notably, relatively larger residual variance across waves suggests that inhibitory control remains comparatively sensitive to contextual influences and developmental transitions, even as stability increases (Zelazo & Carlson, 2012). Complementing these findings, the common factor model supported a single latent inhibitory control construct spanning toddlerhood to early adolescence. Factor loadings increased from toddlerhood through early childhood and then stabilized at high levels from middle childhood into early adolescence, consistent with inhibitory control becoming increasingly trait-like and aligning with temperament-based accounts that situate inhibitory control as a core component of effortful control (Alessandri et al., 2022; Rothbart & Bates, 2006). At the same time, the age-varying loadings imply heterotypic continuity (Hosch et al., 2022; Petersen et al., 2021), such that the same underlying capacity is expressed through developmentally shifting behaviors. Accordingly, inhibitory control may be evident in toddlerhood through simple compliance or brief waiting, and later through rule-following and behavioral regulation in structured academic settings (Berzenski & Yates, 2021; Morasch & Bell, 2011).

Impulsivity.

Consistent with our hypotheses, the autoregressive model indicated moderate to strong rank-order stability in impulsivity from toddlerhood through early adolescence, with continuity evident as early as the toddlerhood-to-preschool transition and remaining robust across later childhood. This pattern suggests that individual differences in impulsivity emerge early and persist, consistent with evidence for moderate stability in temperamental reactivity from early childhood onward (Gilman et al., 2024; Leblanc et al., 2008). Developmentally, this continuity likely reflects early-emerging bottom-up reactivity rooted in striatum-limbic motivational circuitry that matures earlier than prefrontal regulatory networks, producing a temporary imbalance that gradually resolves as top-down control develops (Inuggi et al., 2014; Shaw et al., 2011). This imbalance could explain relatively stable impulsivity across early and middle childhood, with gradual declines reflecting the increasing influence of top-down effortful control during early adolescence (Duckworth & Steinberg, 2015; Gilman et al., 2024).

Complementing these findings, the common factor model supported a stable latent impulsivity component across development, with weaker loadings in toddlerhood and early childhood and strong loadings from middle childhood to early adolescence. This age-varying pattern supports heterotypic continuity (Putnam et al., 2008), whereby the same underlying impulsivity is expressed through developmentally shifting behaviors and indicators as children’s cognitive and behavioral control capacities mature. Thus, impulsivity may be reflected in early childhood as heightened reactivity and difficulty waiting, and later as more cognitively mediated impulsive decision-making. Together, these patterns underscore partially distinct developmental pathways for bottom-up and top-down components of self-regulation (Blair & Ku, 2022).

Parenting daily hassles and development of self-regulation

The present findings reveal that parenting daily hassles, as an indicator of everyday family stressors, were systematically associated with children’s self-regulation across domains, but with varying direction and magnitude. Consistent with hypotheses, parenting daily hassles negatively predicted the latent factors of attentional focusing and inhibitory control, and positively predicted impulsivity. This pattern suggests that the chronic strain of daily parenting stress may disrupt the development of top-down effortful self-regulation processes while amplifying bottom-up reactive tendencies. These findings align with biological sensitivity to context and ecological stress calibration perspectives, which posit that early environmental stressors shape physiological reactivity and behavioral regulation through HPA-axis functioning, allostatic load, and stress responsivity (Boyce et al., 2021; Evans & Kim, 2013; Miller et al., 2007). Frequent exposure to parental stress may heighten children’s physiological arousal and vigilance, which can undermine their ability to sustain attention and suppress impulses in favor of immediate responding (Blair & Raver, 2012; Mathis & Bierman, 2015). Over time, exposure to daily hassles and family stress may embed stress-linked patterns of attentional disengagement and reactive responding (Liston et al., 2009; Obradovíc et al., 2010), thereby reinforcing stable individual differences in self-regulation development.

Importantly, incorporating parenting daily hassles into both the autoregressive simplex and common factor models clarifies the developmental meaning of these associations. In the common factor models, parenting daily hassles were linked to the stable, trait-like component that underlies repeated assessments, indicating that families experiencing higher parenting hassles tended to show persistently lower top-down regulation and higher impulsivity across childhood. In the autoregressive simplex models, parenting daily hassles were evaluated in relation to continuity indexed by adjacent-wave carryover (and, depending on specification, wave-specific levels), providing complementary evidence about whether early parenting stress is associated with the persistence of individual differences over time rather than solely time-local associations at a single age. Together, findings suggest that early parenting hassles are not merely concurrent correlates, but are associated with longer-term patterns of self-regulation across development.

Mechanistically, parents experiencing elevated daily stress may show reduced consistency, lower emotional sensitivity, and more reactive interaction patterns, thereby limiting opportunities for children to practice sustained attention and inhibitory control within a supportive co-regulatory process (Bornstein, 2020; Crnic et al., 2005; Mathis & Bierman, 2015). When parental scaffolding is inconsistent, children may receive fewer structured opportunities to practice sustained focus and inhibition within co-regulatory exchanges, potentially constraining the development of higher-order self-regulatory skills. Chronic exposure to these stress-related dynamics may, over time, narrow children’s capacity to engage effortful control processes under challenge. In contrast, the positive association between parenting daily hassles and impulsivity may reflect the influence of stressful and unpredictable caregiving environments on children’s motivational and behavioral regulation. Parents experiencing increased daily stress often oscillate between overcontrol and withdrawal, creating inconsistent contingencies that make the environment less predictable for children (Bronte-Tinkew et al., 2010; Skinner & Zimmer-Gembeck, 2016). Such daily stressors might heighten children’s tendency toward reactive responding, particularly when parental feedback is unpredictable or emotionally volatile. As such, elevated impulsivity may represent an adaptive response to demanding or unstable caregiving contexts, favoring rapid, context-sensitive responses over sustained deliberation when regulatory scaffolding is inconsistent (Ellis et al., 2011).

Limitations and future directions

Despite the strengths of the current study, several limitations should be noted. First, self-regulation domains were assessed through the primary caregiver’s report. The primary caregiver’s report provides a valid but partial perspective of children’s self-regulated behavior in everyday contexts. Future research should incorporate multiple informants (e.g., teachers) as well as direct observation (Eberhart et al., 2023) and task-based assessments (Lunkenheimer et al., 2017) to provide a more comprehensive and multi-method evaluation of children’s self-regulation. Second, because our sample was recruited from state birth records, the racial/ethnic composition of the sample (i.e., predominantly White and Latino) reflects the demographics of the state birth cohort at the time of recruitment. Despite substantial socioeconomic diversity, generalizability remains limited by the relatively lower representation of families from other racial or ethnic backgrounds. In addition, participation across waves was differential, with families contributing data at only one wave showing lower socioeconomic status, and non-White and Hispanic participants being less likely to contribute data at multiple waves. Although this pattern reflects the staggered-entry design rather than monotone attrition from a single closed cohort, it may further limit generalizability. Future research should prioritize recruitment and retention strategies that enhance inclusivity across racial and ethnic groups, as broader representation is critical for understanding the developmental pathways of self-regulation in diverse cultural contexts. Third, the interpretability of stability estimates is constrained by unequal intervals between assessments. Because autoregressive coefficients scale with the time lag, some cross-wave differences in stability may reflect both interval length and developmental change. Notably, the overall pattern of continuity is corroborated by the common-factor models, which are less sensitive to lag length. Future work should employ more uniform spacing to better capture continuity and change in self-regulation across childhood. Fourth, we examined early parenting daily hassles as one contextual influence on self-regulation domains, yet development of self-regulation is also shaped by potentially adverse early contexts, such as household chaos (Andrews et al., 2021) and family conflict (Zhang et al., 2025) that we did not assess in the current study. Future research should test how these risk factors intersect with parenting stress to provide a more comprehensive understanding of developmental pathways of self-regulation. Lastly, the same primary caregivers rated self-regulation for both twins, which may introduce shared method variance. Caregivers may perceive and report twins as more similar than they are (assimilation effects) or, conversely, accentuate perceived differences (contrast effects), potentially influencing within-family resemblance and the magnitude of associations. With the detailed measures of self-regulation used in the current study, there is no evidence of either type of bias reported in the literature (Goldsmith et al., 1997; Saudino, 2003). In addition, parenting daily hassles reflect caregiver-level stress in the parenting role and are therefore shared within families; accordingly, associations between parenting daily hassles and children’s self-regulation should be interpreted as reflecting between-family differences in parenting stress rather than child-specific (within-family) processes. Future work should adopt multi-informant measurement and genetically informed twin models that can more directly separate shared familial influences from child-specific processes and test within-family mechanisms.

Implications

Our findings advance theoretical understanding of self-regulation development and inform the design of interventions. By simultaneously applying autoregressive simplex models and common factor models, we recognize that self-regulation reflects both trait-like continuity and state-like change across developmental stages (Bornstein et al., 2019; Petersen et al., 2021). This aligns with developmental systems perspectives, which conceptualize self-regulation as a multifaceted construct that develops greater integration across domains with age while remaining sensitive to early contextual influences (Blair, 2010; McClelland et al., 2015). Furthermore, the distinct developmental patterns observed across top-down (i.e., attentional focusing, inhibitory control) and bottom-up (i.e., impulsivity) processes reinforce the need to operationalize self-regulation as a multi-component constellation rather than a single global dimension (Blair & Ku, 2022; Eisenberg et al., 2024; Zhou et al., 2012). Heterotypic continuity further suggests that interventions may be more effective by using developmentally appropriate activities and contexts. The underlying self-regulation trait could show continuity across development. However, the expressed behaviors often change as children mature. Accordingly, interventions should be calibrated to the age-specific demands through which self-regulation is most visible and most malleable. For example, in early childhood, intervention targets may emphasize managing distractibility and sustaining engagement during play and daily routines. In middle childhood, targets may shift toward maintaining task goals and resisting interference in classroom contexts. By early adolescence, targets may focus more on regulating impulsive decision-making and balancing autonomy with responsibility.

Our longitudinal results also inform the timing of intervention. Across self-regulation domains, stability generally increased from early childhood into early adolescence in the autoregressive simplex models, and the common factor models indicated stronger trait-like coherence beginning in middle childhood for several domains. These patterns suggest that earlier developmental periods may offer greater opportunity to alter developmental trajectories before stability becomes more entrenched, whereas interventions later in childhood may need more context-specific strategies to modify well-established self-regulatory tendencies. Accordingly, early childhood and the transition to formal schooling may represent particularly promising windows for intervention (Blair & Raver, 2012). For example, classrooms can incorporate attention-training practices into daily routines and structured interactions (Diamond & Lee, 2011). Inhibitory control and impulsivity could be effectively targeted through social–emotional learning curricula that integrate emotion coaching, rule-switching activities, and impulse-management strategies (Humphrey et al., 2016).

Lastly, the observed influence of early parenting daily hassles underscores the importance of reducing routine stressors in the family environment. Parenting interventions that both build positive parenting skills and support parents’ coping strategies in managing daily stress could strengthen children’s emerging self-regulatory capacities (Deater-Deckard, 2014). Programs such as Triple P (Sanders, 2012) and the Incredible Years (Webster-Stratton & Reid, 2011) exemplify how interventions can simultaneously address challenging child behavior and alleviate parental stress. By targeting both child-level skills and family-level stressors, interventions are more likely to produce durable gains in self-regulation across diverse developmental stages.

Conclusion

This study contributes to a growing body of research on the developmental course of self-regulation by modeling attentional focusing, inhibitory control, and impulsivity from toddlerhood through early adolescence. By fitting both autoregressive and common factor models, we identified both trait-like continuity and state-like change in self-regulation, highlighting how these domains consolidate over time while remaining sensitive to early contextual influences. Distinct developmental patterns across top-down and bottom-up processes underscore the importance of treating self-regulation as a multidimensional construct rather than a single global construct. The predictive role of early parenting daily hassles emphasizes the salience of family stressors in shaping children’s self-regulatory trajectories. Together, these findings advance theoretical understanding of self-regulation as a system characterized by both continuity and change, while pointing to practical implications for the timing and content of interventions designed to strengthen self-regulatory skills in early family and educational contexts.

Fig. 2.

Autoregressive simplex model (Panel A) and common factor model (Panel B) of inhibitory control.

Note. Reported in standardized coefficients. Child age at each wave, family SES at 30 months, and child sex were included as covariates. Model fit for the autoregressive simplex model: χ² = 93.11, df = 23, CFI = 0.91, TLI = 0.87, RMSEA = 0.05, SRMR = 0.09. Model fit for the common factor model: χ² = 36.82, df = 18, CFI = 0.98, TLI = 0.94, RMSEA = 0.03, SRMR = 0.03.

Data availability

Data will be made available on request.