Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Aug 11.
Published in final edited form as: Child Dev. 2021 Jul 1;92(6):2529–2545. doi: 10.1111/cdev.13621

Temperamental Shyness and Anger/Frustration in Childhood: Normative Development, Individual Differences, and the Impacts of Maternal Intrusiveness and Frontal EEG Asymmetry

Ran Liu 1, Jennifer J Phillips 2, Feng Ji 3, Dexin Shi 4, Martha Ann Bell 5
PMCID: PMC9366420  NIHMSID: NIHMS1827311  PMID: 34196961

Abstract

This study used latent growth curve modeling to identify normative development and individual differences in the developmental patterns of shyness and anger/frustration across childhood. This study also examined the impacts of maternal intrusiveness and frontal EEG asymmetry at age 4 on the developmental patterns of shyness and anger/frustration. 180 children (92 boys, 88 girls; Mage = 4.07 years at baseline; 75.6% White, 18.3% Black, 6.1% multiracial/other) participated in the study. Normative development included significant linear decreases in shyness and anger/frustration. Individual variation existed in the developmental patterns. Children with left frontal EEG asymmetry showed a faster decreasing pattern of shyness. Children who experienced higher maternal intrusiveness and had left frontal EEG asymmetry showed a slower decreasing pattern of anger/frustration.

Keywords: shyness, anger/frustration, maternal intrusiveness, frontal EEG asymmetry

Temperament consists of basic early-emerging dispositions pertaining to an individual’s activity, emotion, attention, and regulation and is arisen from and shaped by the complex interactions among genetic, biological, and environmental factors (Shiner et al., 2012). Among different traits of temperament, shyness and anger/frustration have received considerable empirical attention given their predictive associations with various socioemotional problems. For example, young children with higher levels of temperamental shyness and anger/frustration are at higher risks of internalizing and externalizing behaviors, respectively, during middle-late childhood and adolescence (Booth-LaForce & Oxford, 2008; Liu, Calkins, & Bell, 2020). Shyness refers to wariness or anxiety in the face of social novelty and perceived social evaluation (Rubin, Coplan, & Bowker, 2009). Other constructs that share conceptual similarities with shyness and often used in developmental literature include behavioral inhibition, fear, and social withdrawal (Buss, 2011; Rubin et al., 2009). Anger/frustration is defined as the negative emotionality caused by interruption of ongoing tasks or goal blocking (Rothbart, Ahadi, Hershey, & Fisher, 2001).

Identifying the early predictors of the developmental patterns (i.e., initial levels, rates of changes) of shyness and anger/frustration is a first vital step in advancing timely and effective intervention for children at increased risk for more severe clinical symptoms. Developmental theories suggest that children’s adjustment is the product of complex interactions among biological, behavioral, and social systems (Belsky & Pluess, 2009; Calkins, Perry, & Dollar, 2016). In keeping with this viewpoint, we examined the impacts of maternal behaviors, frontal EEG asymmetry, and their interaction in predicting the developmental patterns of shyness and anger/frustration, allowing for a more comprehensive and informative view of children’s temperament development.

Temperamental Shyness and Anger/Frustration in Childhood

To understand the normative development of shyness and anger/frustration in childhood, previous studies have examined changes in the average levels and ranked-order stabilities of shyness and anger/frustration across development (e.g., Karevold, Tstrom, Coplan, Sanson, & Mathiesen, 2012). Researchers have reported that significant intraindividual changes exist in the mean level of temperament over time, though interindividual stability remains relatively high throughout childhood (Bornstein et al., 2015; Eggum-Wilkens, Reichenberg, Eisenberg, & Spinrad, 2016). Beyond normative or average changes, children differ from one another in the rate of intraindividual changes in temperament (Fox, Henderson, Rubin, Clakins, & Schmidt, 2001b; Rothbart & Bates, 2006), leading to studies examining the factors that affect the developmental patterns of temperamental traits.

The majority of studies examining the normative development of shyness have suggested that shyness exhibits a linear decrease across childhood or an increase in infancy and toddlerhood and a decrease thereafter on average, with individual differences driving the extent to which it declines (e.g., Baardstu, Coplan, Karevold, Laceulle, & von Soest, 2020; but see Karevold et al., 2012). For example, Eggum-Wilkens and colleagues (2016) found a decrease in the average level of shyness from 42 to 84 months and significant individual differences in the rate of decline. Similarly, children decreased in shyness from 24 months to first grade on average, with individual differences in the rate of change (Grady, Karraker, & Metzger, 2012).

Compared with shyness, less research has examined the normative development of temperamental anger/frustration. The average level of anger/frustration decreases in childhood due to better communication skills and emotion regulation capabilities (Denham, Lehman, & Moser, 1995). Individual differences, however, exist in the developmental pattern of anger/frustration (e.g., Eisenberg et al., 1997). For example, a recent study examining individual differences in rank-order levels of anger demonstrated that there were six different trajectories of parent-reported anger from 9 months to 7 years: low and stable, average and stable, average and decreasing, average and increasing, high and decreasing, and high and stable (Liu et al., 2018b).

Taken together, this body of research suggests that although the mean levels of shyness and anger/frustration typically decrease in childhood, there are individual differences in the developmental patterns as some children exhibit a slower decreasing pattern. It is important to study the developmental patterns of shyness and anger/frustration during childhood as the continuity and discontinuity of the two temperamental traits in this developmental period have been closely linked to socioemotional outcomes (e.g., Karevold et al., 2012).

Maternal Intrusiveness and Temperamental Shyness and Anger/Frustration

Parenting has been documented as a significant influence on the developmental patterns of both shyness and anger/frustration (Rothbart & Bates, 2006). Particularly, maternal intrusiveness has been shown to play a critical role in the developmental pattern of shyness and anger (e.g., Rubin et al., 2009). Maternal intrusiveness can be defined as mothers engaging in overly controlling behaviors that focus on the needs and goals of the mother, as opposed to the child, when interacting with the child. Research has long supported the idea that mothers who are intrusive might overstimulate their children, inhibit their children’s goals, and handle their children in a rough manner, with persistent anger and irritation toward the children (e.g., Szabó et al., 2008). Temperamental traits have a strong biological basis in the first two years and become increasingly influenced by social context in early childhood (Baardstu et al., 2020). Therefore, children who experience greater maternal intrusiveness may maintain higher levels of negative temperamental traits, such as shyness and anger/frustration, throughout childhood.

Intrusive, controlling, and overprotective parenting styles have been particularly linked to children’s propensity for shyness and related constructs (Hastings, Nuselovici, Rubin, & Cheah, 2010; Rubin et al., 2009). Children of mothers who are overly intrusive and protective may not develop necessary coping and problem-solving strategies and thus maintain high level of shyness (Rubin et al., 2009). In support, mothers who are intrusive tend to report higher levels of shyness in their 18- and 30-month-old children, with reported shyness being higher in boys than in girls (Eggum et al., 2009), indicating that maternal intrusiveness and child gender might both be important main effects in understanding the developmental pattern of shyness. Further, mothers who were more intrusive and expressed more hostility had children who were highly socially withdrawn throughout childhood (Booth-LaForce & Oxford, 2008).

Children of mothers who are intrusive do not have control over the interactions and thus may not develop necessary regulatory skills and lack the ability to engage in positive relationships with others. The lack of autonomy and control may also generate feelings of anger and frustration (Szabó et al., 2008). In support, maternal intrusiveness was related to more anger expression in the anger-eliciting paradigms among toddlers aged 2 – 3 years (Feldman, Dollberg, & Nadam, 2011). Research regarding the influence of maternal intrusiveness on the developmental pattern of anger/frustration, however, is limited. Most of the existing research does not measure the relationship between maternal intrusiveness and anger/frustration specifically, but rather between maternal intrusiveness and externalizing behaviors (e.g., Eisenberg, Taylor, Widaman, & Spinrad, 2015). Among the existing research that does examine the association between maternal intrusiveness and child anger/frustration, the majority of the studies are cross-sectional and focus on the expression and regulation of state anger rather than dispositional anger or frustration (e.g., Feldman et al., 2011). Given this limited research base, more longitudinal research is needed to fully understand the contribution of maternal intrusiveness to the developmental pattern of temperamental anger/frustration.

Frontal EEG Asymmetry and Temperamental Shyness and Anger/Frustration

The role of biological systems in the developmental course of temperament has received considerable attention (e.g., Fox, Henderson, & Marshall, 2001a). Temperament researchers have identified biomarkers that correlate to individuals’ emotional reactivity and the ability to regulate attention and emotion (e.g., Gatzke-Kopp, Jetha & Segalowitz, 2014). One line of research in this field has specifically focused on frontal electroencephalogram (EEG) asymmetry, which refers to the asymmetrical cortical activity in the anterior regions of the two hemispheres during resting state (Reznik & Allen, 2018).

The study of frontal EEG asymmetry often relies on the framework of motivational processes (Harmon-Jones & Gable, 2018). According to the motivational direction model, left frontal EEG asymmetry is associated with approach motivational tendencies, whereas right frontal EEG asymmetry is associated with withdrawal motivational tendencies. Researchers report that left frontal EEG asymmetry is associated with approach-related traits and behaviors, such as anger/frustration and impulsivity, and increases the risk for externalizing problems, whereas right frontal EEG asymmetry has been related to withdrawal-related traits and behaviors, such as shyness and internalizing problems (Peltola et al., 2014; Poole, Santesso, Van Lieshout, & Schmidt, 2019).

Despite the association between frontal EEG asymmetry and temperament, few studies have examined the impact of frontal EEG asymmetry on the developmental pattern of temperament in children using a longitudinal design. Children with greater right frontal EEG asymmetry at age 6 exhibited a greater increase in shyness from age 6 to age 8 (Poole et al., 2019). To our best knowledge, this is the only study that examined how frontal EEG asymmetry influences the developmental pattern of shyness in childhood. The influence of frontal EEG asymmetry on the developmental pattern of anger/frustration is unknown.

Maternal Intrusiveness, Frontal EEG Asymmetry, and Temperamental Shyness and Anger/Frustration

In addition to directly linking to temperamental traits and behavioral outcomes, frontal EEG asymmetry may perform as a moderator of the influence of environment on child outcomes (Peltola et al., 2014; Reznik & Allen, 2018). In support, previous studies have demonstrated the moderating effect of frontal EEG asymmetry between maternal behaviors and infants’ temperament (Diaz et al., 2019; Swingler, Perry, Calkins, & Bell, 2014). Frontal EEG asymmetry that underlies motivational tendencies might influence the way individuals respond to stressful or adverse environment, therefore moderating the effect of environment on the manifestation of traits and behaviors (Gatzke-Kopp et al., 2014). Particularly, children with right frontal EEG asymmetry may avoid interactions with their intrusive mothers and, therefore, tend to keep feelings inside and become more reticent and timider. On the contrary, children with greater left frontal activity may respond to their mothers’ intrusiveness or overcontrol in a more bold and aggressive way, which may elicit greater anger or frustration (Harmon-Jones & Gable, 2018). Children may also generalize the way that they interact with their mothers who are highly intrusive to teachers, peers, and strangers. As such, depending on their frontal EEG asymmetry, they may either lose opportunities to engage in social interactions and maintain a high level of shyness or tend to deal with potential conflicts in an inconsiderate approach and show greater hostile affectivity (Degnan & Fox, 2007, Liu et al., 2020). We examined the moderating effect of frontal EEG asymmetry between maternal intrusiveness and the developmental patterns of shyness and anger/frustration.

Although frontal EEG asymmetry may be an important biomarker of an environment-temperament association, the current empirical evidence is limited in three important ways. First, previous empirical findings focus on the moderating effect of frontal EEG asymmetry on maternal intrusiveness during infancy (Diaz et al., 2019; Swingler et al., 2014). We know, however, that temperament is continually shaped by biological and environmental factors across time (Shiner et al., 2012), making it critical to examine how maternal behaviors and frontal EEG asymmetry interact to predict children’s temperament across development. Second, the majority of existing research on frontal EEG asymmetry and temperament has used cross-sectional designs, which impedes potential directional inferences and interpretations of the results. Among the few studies that applied a longitudinal design, temperament was either measured only once (Swingler et al., 2014) or spanned a short duration of time (Poole et al., 2019). Third, the existing work mostly examined a broad dimension of temperament (e.g., negative affectivity) that contains several subdomains (Diaz et al., 2019) or one single subdomain of temperament (e.g., shyness, Poole et al., 2019). Although this work has provided invaluable information regarding how context risk factors and frontal EEG asymmetry are associated with temperament, the nuances among different subdimensions of temperament might be masked or undetected. Our study contributes to the field by utilizing a longitudinal design to examine the effect of maternal intrusiveness, frontal EEG asymmetry, and their complex interaction on the developmental patterns of both shyness and anger/frustration.

The Present Study

Our study had four major goals: 1) we identified the normative changes of shyness and anger/frustration across childhood. We expected that shyness and anger/frustration would exhibit linear declines from age 4 to age 9 on average; 2) we examined individual variability in the developmental patterns of shyness and anger/frustration across childhood. We expected to see significant individual differences in the initial levels and rates of changes in shyness and anger/frustration; 3) we examined if maternal intrusiveness and frontal EEG asymmetry at 4 years predicted the developmental patterns of shyness and anger/frustrations across childhood. We expected that shyness and anger/frustration would show slower decreasing patterns in children who experienced higher maternal intrusiveness. We also expected that shyness would show a slower decreasing pattern in children who had greater right frontal EEG asymmetry and anger/frustration would show a slower decreasing pattern in children who had greater left frontal EEG asymmetry; 4) we examined if maternal intrusiveness and frontal EEG asymmetry at 4 years interactively predicted the developmental patterns of shyness and anger/frustrations throughout childhood. We hypothesized that shyness would exhibit the slowest decreasing pattern in children of intrusive mothers who also had greater right frontal EEG asymmetry. We expected anger/frustration to show the slowest decreasing pattern in children of intrusive mothers who also had greater left frontal EEG asymmetry. Finally, because sex has been associated with temperament (e.g., Poole et al., 2020), we included sex as a covariate when predicting the developmental patterns of shyness and anger/frustration. Our study is more confirmatory in nature given we made specific and directional hypotheses based on prior research.

Method

Participants

The data were collected from two cohorts of children (n = 304), or approximately 75%, of the participants of a larger longitudinal study examining cognitive and emotional development from infancy through middle childhood. The remaining 25% of the participants in the larger study represented a third cohort who did not have a research visit at age 6. The cohorts were broadly recruited by two research locations, a rural town and a mid-sized city in the mid-Atlantic region, when the children were infants using mailing lists, media advertisements, flyers, and word of mouth. The Blacksburg research location and the Greensboro research location each recruited half of the participants in the longitudinal study. The demographics of the participants recruited from each location reflected the demographics of the area in which each research laboratory was located. Participants at each research location did not differ with respect to sex, χ2(1, N = 304) = 2.21, p = .14. However, the Blacksburg research location had mothers with higher levels of education on average, χ2(4, N = 296) = 10.43, p = .03, and the Greensboro research location had a greater number of ethnic minority participants, χ2(3, N = 304) = 29.83, p < .001.

There was the potential for 304 children to participate at age 4, based on the number of children who contributed data at the previous assessments in the longitudinal study. Of the 304 potential participants, there were 77 children who did not participate in the study at age 4 and 22 children who participated at age 4 via parent-report questionnaires rather than the lab visit, yielding 205 children with a research lab visit at age 4. Among the 205 children (Mean age = 4.07 years, SD = .07, range = 4.01 – 4.39; 107 boys, 98 girls) and mothers who visited the lab when children were 4 years of age, 19 did not have EEG data and 3 did not have maternal interaction data. Reasons for missing EEG data included children who refused to wear the EEG cap (n = 14), equipment failure (n = 4), and poor-quality EEG recording (n = 1).

Of the remaining 183 children, 166 children (Mean age = 6.55 years, SD = .36, range = 5.79 – 8.84; 84 boys, 82 girls) continued their participation at age 6 and 140 children (Mean age = 9.23 years, SD = .28, range = 8.87 – 10.76; 73 boys, 67 girls) participated at age 9. Families lost to attrition included those who could not be located, moved out of the area, declined participation, or did not respond to phone and letter requests to participate. No significant differences were found between families who did or did not participate at every time point with respect to child sex (χ2(1, N = 183) = .14, p = .70), race (χ2(2, N = 180) = 1.25, p = .54), maternal education (χ2(4, N = 177) = 3.77, p = .44), maternal intrusiveness (t = −.03, p = .98), and frontal EEG asymmetry (t = .97, p = .33) at 4 years.

We included children who had complete measures of maternal intrusiveness and EEG at 4 years and at least one temperament measure. There were 3 children who did not have temperament data at any study points due to parents not returning questionnaires; these children were not included in the analyses. As a result, the final sample included 180 children (Mean age at baseline = 4.07 years, SD = .07, range = 3.99 – 4.35; 92 boys, 88 girls). Among the 180 children who contributed data, 23 are the only children in the family, 81 children have one sibling, 39 children have two siblings, 15 children have three siblings, 5 children have four siblings, 2 children have five siblings, and 1 child has seven siblings. Information for the remaining 14 children is missing. For children who have siblings, 54 are first born, 56 are second born, 30 are third born, 2 are fourth born, and 1 is seventh born. With respect to race, 75.6% were White, 18.3% were Black, and 6.1% were multiracial/other. Regarding maternal education level, 3.6% of the mothers did not finish high school; 8.4% of the mothers graduated from high school; 26.9% had technical degrees; 35.3% had college degrees; 25.8% had postgraduate degrees.

Procedure

Data were collected at both research locations between 2011 and 2017, using identical protocols. Research assistants from each location were trained together by the project’s Principal Investigator (final author) on protocol administration, as well as on data collection and psychophysiological coding. To ensure that identical protocol administration was maintained between the labs, the Blacksburg lab periodically viewed video recordings and raw EEG files collected by the Greensboro lab. To ensure that identical EEG processing criteria were maintained between labs, the Blacksburg lab provided verification of artifact screening of processed EEG data collected by the Greensboro lab. All maternal behavior coding was done by the Blacksburg lab.

Upon arriving at the lab, children and mothers were greeted. Consent and assent were obtained from the mothers and the children. At each lab visit, children performed a series of cognitive and emotional control tasks (not included in this study) wearing the EEG cap. Mothers sat near the child at the age 4 visit and in an adjoining room during the age 6 and 9 visits. Mothers and children also participated in several interactive tasks.

We used EEG data from age 4 visit to calculate frontal EEG asymmetry. Baseline EEG was recorded for 2 minutes while children quietly watched a film clip from Finding Nemo (sea turtles riding the East Australia current). We used maternal-report temperament data collected at ages 4, 6, and 9 and the mother-child interaction data from age 4 visit. Mothers received remuneration at each visit. Children received a small gift at each lab visit and also received remuneration at ages 6 and 9.

Measures

Frontal EEG Asymmetry at Age 4

EEG was recorded from 16 left and right scalp sites: frontal pole (Fp1, Fp2), medial frontal (F3, F4), lateral frontal (F7, F8), central (C3, C4), temporal (T7, T8), medial parietal (P3, P4), lateral parietal (P7, P8), and occipital (O1, O2), all referenced to Cz during the recordings. EEG was recorded using a stretch cap (Electro-Cap Inc., Eaton, OH; E-1 series cap) with electrodes positioned to the International 10–20 system. After the cap was placed on the head, a small amount of abrasive gel was placed into each recording site and the scalp gently rubbed. Then, a small amount of conductive gel was placed into each site. Electrode impedances were measured and accepted if they were below 10 KΩ.

The electrical activity from each electrode was amplified using separate James Long Company Bioamps (James Long Company; Caroga Lake, NY). During data collection, the high pass filter was a single pole RC filter with a 0.1 Hz cut-off (3 dB or half-power point) and 6 dB per octave roll-off. The low pass filter was a two-pole Butterworth type with a 100 Hz cut-off (3 dB or half-power point) and 12 dB octave roll-off. Activity for each lead was displayed on the monitor of an acquisition computer. The EEG was digitized on-line at 512 samples per second for each channel to eliminate the effects of aliasing. The acquisition software was Snapshot-Snapstream (HEM Data Corp.; Southfield, MI) and the raw data were stored for later analyses. Prior to the recording of each subject a 10 Hz, 50 uV peak-to-peak sine wave was input through each amplifier. This calibration signal was digitized for 30 s and stored for subsequent analysis.

Spectral analysis of the calibration signal and computation of power at the 9 to 11 Hz frequency band was accomplished. These power figures were used to calibrate the power derived from the subsequent spectral analysis of the EEG. Next, EEG data were examined and analyzed using EEG Analysis software developed by James Long Company. Data were re-referenced via software to an average reference configuration. This re-referencing eliminates concerns that power values at each active site reflect interelectrode distance as much as they reflect electrical potential (Bell & Cuevas, 2012).

The average reference EEG data were artifact scored for eye movements using electrodes Fp1 and Fp2 to examine peak-to-peak criterion of 100 uV or greater (Myslobodsky et al., 1989). EEG data also were artifact scored for gross motor movements using a peak-to-peak criterion of 200 uV V or greater. Only artifact-free data were used in subsequent analyses. The data were then analyzed with a discrete Fourier transform (DFT) using a Hanning window of 1-second width and 50% overlap. The number of DFT windows (mean = 175) was not correlated with any study variable of interest (rs ranged from −0.14 to 0.04, ps > 0.05) except for age-6 anger (r = −0.16, p = 0.04). EEG power was expressed as mean square microvolts and the data were transformed using the natural log (ln) to normalize the distribution.

Power was computed for the 6–9 Hz alpha frequency band. This frequency band was selected for two reasons. First, previous research examining EEG power distribution across early development suggested that 6–9 Hz is the dominant frequency band from infancy through early childhood, with power at 6–9 Hz showing moderate to high consistency from 10 months to 51 months (Marshall, Bar-Haim, & Fox, 2002). Second, previous studies have used this alpha frequency band at 4 years to examine children’s temperament and socioemotional development (Fox et al., 2001b; Henderson, Marshall, Fox, & Rubin 2004). We focused on frontal EEG asymmetry using electrode locations F3 and F4, which have been consistently associated with emotion, motivation, and behavioral problems (Reznik & Allen, 2018). Frontal EEG asymmetry was calculated by subtracting the natural log transformed power at the left hemisphere (F3) from the natural log transformed power at the right hemisphere (F4). Because cortical activity is inversely related to alpha power (Reznik & Allen, 2018), left frontal EEG asymmetry is indicated by positive asymmetry values, which means greater left relative to right brain activation. Right frontal EEG asymmetry is indicated by negative asymmetry values, which means a greater right relative to left brain activation.

Maternal Intrusiveness at Age 4

Mother’s intrusive behaviors were observed in an interactive puzzle task, during which mothers and their children were asked to work together on two puzzles for a total of 6 minutes. Mother and child were instructed to sit on adjacent sides of a table. The interaction was recorded for off-line coding. Specific intrusive behaviors included the following: failing to modulate behavior that the child turns away from, defending against or expressing negative affect to the child, and offering a continuous barrage of stimulation or toys, over-whelming the child rather than observing his/her reaction. Intrusive behaviors also included not allowing the child to influence the pace or focus of play or interaction by ignoring what the child shows interest in and taking away objects while the child still appears interested. Maternal behaviors were off-line coded by trained research assistants who using a coding scheme adapted from Smith and colleagues (2004). Intrusive behaviors were coded by trained research assistants on a 4-point Likert scale from 1 = none to 4 = high in 30-second epochs, which were then summed across epochs and divided by the number of epochs to get a mean value. For calculating reliability, there was 20% overlap in coding among trained coders. Inter-rater reliability (intraclass correlation) was .97.

Temperament at Age 4 and Age 6

Shyness and anger/frustration at age 4 and age 6 were measured with the Children’s Behavior Questionnaire (CBQ; Rothbart et al., 2001), which is a well-established parent report to test children’s temperament from 3 to 7 years of age. Parents reported on a 7-point Likert scale ranging from 1 (“extremely untrue of your child”) to 7 (“extremely true of your child”). Two scales in the CBQ were used: shyness (6 items; “Acts shy around new people.”) and anger (6 items; “Gets angry when told s/he has to go to bed.”). The Cronbach’s α of shyness and anger at age 4 were .86 and .76, respectively. The Cronbach’s α of shyness and anger at age 6 were .86 and .84, respectively.

Temperament at Age 9

Shyness and anger/frustration at age 9 were measured with the Early Adolescent Temperament Questionnaire (EATQ-R; Ellis, & Rothbart, 2001). EATQ-R is a widely used parent report to assess temperament in adolescents aged 9–15. Parents rated their children on a 5-point Likert scale from 1 (“almost always untrue of your child”) to 5 (“almost always true of your child”). In the current study, two scales in the EATQ-R were used: shyness (5 items; “Is shy.”) and frustration (6 items; “Is annoyed by little things other kids do”). The Cronbach’s α of shyness and frustration subscales were .86 and .78, respectively.

The shyness subscale of CBQ (e.g., “Acts shy around new people”) and the shyness subscale of EATQ (e.g., “Feels shy about meeting new people) both measure the level of behavioral inhibition to novelty and uncertainly, especially in social situations. The anger subscale of CBQ (e.g., “Gets quite frustrated when prevented from doing something s/he wants to do”) and the frustration subscale of EATQ (e.g., “Gets irritated when s/he has to stop doing something s/he is enjoying”) both assess the amount of negative affect as a response to interruption of ongoing tasks or goal blocking (Ellis & Rothbart, 2001; Rothbart et al., 2001). Several considerations demonstrate that similar constructs of shyness and anger/frustration were being measured across time in the current study (Petersen et al., 2018). First, Rothbart’s temperament questionnaires are a series of age-appropriate measures containing construct-valid items at different ages. The measures are highly valid and widely used for assessing temperament across development (Ellis & Rothbart, 2001; Rothbart et al., 2001). Second, the measures of shyness and anger/frustration showed high cross-time consistency in our study (see Table 1). Third, the developmental patterns of shyness and anger/frustration in the current study were similar to previous findings, which demonstrated good construct validity.

Table 1.

Descriptive Statistics and Correlations Among Study Variables

N Mean SD Range 1 2 3 4 5 6 7
1. FA age 4 178 .03 .22 −.51 – 1.01
2. MI age 4 178 1.10 .23 1.00 – 3.00 −.10
3. Shyness age 4 176 3.87 1.32 1.00 – 6.83 .07 .06
4. Shyness age 6 166 3.67 1.26 1.00 – 7.00 .03 .01 .64*
5. Shyness age 9 147 2.90 1.18 1.03 – 6.23 −.11 −.03 .47* .59*
6. Anger age 4 176 4.51 1.10 1.67 – 6.83 .02 .05 .15 .05 −.10
7. Anger age 6 166 4.00 1.25 1.00 – 7.00 .04 .07 .12 .10 −.02 .69*
8. Frustration age 9 147 3.59 1.44 .81 – 6.98 −.10 .01 .08 .18* .18* .36* .37*
Open in a new tab

Note. FA = frontal EEG asymmetry scores, MI = maternal intrusiveness. Scores of shyness and anger/frustration at age 9 are transformed scores after equating.

*

p < .05.

Individual CBQ items are rated on a scale from 1 to 7, whereas EATQ items are rated from 1 to 5. To put CBQ and EATQ scores on the same metric so they are comparable across time, we applied Kernel equating using a non-equivalent groups design with kequate package (Andersson, Bränberg, & Wiberg, 2013) in R. Specifically, we used item 52 (i.e., “Acts shy around new people”) in CBQ and item 62 (i.e., “Feels shy about meeting new people”) in EATQ as anchor items when measuring shyness. We used item 30 (i.e., “Gets quite frustrated when prevented from doing something s/he wants to do”) in CBQ and item 45 (“Gets irritated when s/he has to stop doing something s/he is enjoying”) in EATQ as anchor items when measuring anger/frustration. The selection of anchor items was based on conceptual overlap and agreement among all authors. Anchor items provide a reference point in the two scales and function as the common rules (Kolen & Brennan, 2014). The transformed scores of shyness and frustration on EATQ have the same scale as the scores on CBQ (i.e., same range of possible scores, same score indicates same trait level). The transformed EATQ scores after equating were used in subsequent analyses.

Statistical Analyses

Latent growth curve modeling (LGCM) was conducted using Mplus (Version 8; Muthén & Muthén 1998–2017). Data analyses were performed in two stages. First, two separate unconditional LGCMs were constructed to examine the normative development and individual differences in the developmental patterns of shyness and anger/frustration from age 4 to age 9. Each model included two growth parameters: a latent intercept factor representing the initial level of temperament and a latent slope factor representing the pattern of change. The mean of the intercept factor tells the average initial level of temperament, whereas the variance of the intercept captures the variation across individuals in the initial status. The mean of the slope factor represents the average rate of change. The variance of the slope represents the individual variability in the rate of change. The intercept factor was specified by fixing all the factors loading to 1. The slope factor was estimated by fixing the factor loadings to 0, 2, 5 (corresponding to age 4, 6, and 9, respectively) representing the linear change of temperament.

Second, two conditional LGCM were conducted by including maternal intrusiveness, frontal EEG asymmetry, and their interactive term at age 4 to examine whether individual differences in the initial level and the rate of change in temperament varied as a function of early maternal intrusiveness and frontal EEG asymmetry. We also tested whether the initial levels of shyness and anger/frustration are correlated with their rates of change. Sex was included as a covariate in the conditional LGCM.

Little’s MCAR test failed to reject the hypothesis that the data were missing completely at random (χ2(14, N = 180) = 16.82, p = 0.27). Full information maximum likelihood (FIML) was used to handle missing values on the dependent variables (i.e., temperament). An MLR estimator was used to account for possible non-normal distribution of the study variables. Model fit was assessed using the comparative fix index (CFI) and standardized root mean square residual (SRMR). A CFI value greater than .95 and a SRMR value less than .08 indicated good model fit (Hu & Bentler, 1999).

Results

Descriptive statistics and correlations among the variables of interest are presented in Table 1. Shyness at age 4, age 6, and age 9 were positively correlated. Anger/frustration at age 4, age 6, and age 9 were positively correlated. Shyness at age 6 and age 9 were positively correlated with frustration at age 9. Maternal intrusiveness and frontal EEG asymmetry were not correlated with temperament measures at any age. Mothers of boys tended to be more intrusive compared with mothers of girls (t = 2.18, p = 0.03). In addition, mothers rated boys as having higher levels of anger/frustration at age 4 (t = 2.17, p = .03) and age 9 (t = 2.92, p < .001). Mothers rated girls as having higher levels of shyness at age 9 (t = −2.12, p = .04).

Unconditional Latent Growth Curve Models for Temperament

Visual inspection of spaghetti plots of raw longitudinal data suggested large individual variability in the initial level and the rate of change of temperament over time (see Figure S1 in supplements). Two separate unconditional models were estimated to examine the normative development and individual variation in the developmental patterns of shyness and anger/frustration across childhood. The model of shyness had an acceptable fit (χ2 (1, N = 180) = 7.30, p = .01, CFI = .95, SRMR = .05). Shyness showed a linear decrease from age 4 to age 9 on average (b = −.20, p < .001). There was significant variation across children in the initial level of shyness (b = 1.26, p < .001) and the rate of decrease (b = .03, p = .05).

The model of anger/frustration fit the data well (χ2 (1, N = 180) = 3.77, p = 0.05, CFI = .98, SRMR = .03). Anger/frustration linearly decreased from age 4 to age 9 (b = −.19, p < .001). There were significant individual differences in the initial level of anger/frustration (b = 1.24, p < .001) and the rate of change (b = .04, p = .03).

Conditional Latent Growth Curve Models for Temperament as a Function of Early Maternal Intrusiveness and Frontal EEG Asymmetry

Two conditional models were estimated to examine whether maternal intrusiveness, frontal EEG asymmetry, and their interaction at 4 years predicted the developmental patterns of shyness and anger/frustration across childhood. Sex was included as a covariate in the models. The model of shyness had an acceptable model fit (χ2 (5, N = 180) = 11.87, p = .04, CFI = .96, SRMR = .02). Maternal intrusiveness at 4 years did not predict the initial level of shyness (b = .08, p = .40) or the rate of change (b = −.01, p = .57). Frontal EEG asymmetry at 4 years did not predict the initial level of shyness (b = .15, p = .14); however, it significantly predicted the rate of change of shyness (b = −.04, p = .04; see Figure 1).

Figure 1. Results for the Conditional Latent Growth Curve Model of Shyness.

Figure 1

Open in a new tab

Note. Boys were coded as 0; girls were coded as 1. Significant effects are shown by solid black lines, nonsignificant effects are shown by dashed gray lines. Numbers on the significant paths represented the effect of a predictor on an outcome or the correlation between two variables when they were standardized. S = Shyness, MI = Maternal intrusiveness, FA = Frontal EEG asymmetry.

We classified children based on their frontal EEG asymmetry scores into right frontal EEG asymmetry group (frontal EEG asymmetry < .00; n = 90) and left frontal EEG asymmetry group (frontal EEG asymmetry > .00; n = 90) and plotted the trajectories of shyness from age 4 to age 9. As shown in Figure 2, the mean level of shyness decreased faster in children who showed left frontal EEG asymmetry (b = −.56, p = .01) than in children who showed right frontal EEG asymmetry (b = .02, p = .83), controlling for maternal intrusiveness. The interactive term did not predict the initial level of shyness (b = −.10, p = .33) or the rate of change (b = .04, p = .11). The initial level of shyness was negatively associated with the rate of change (b = −.10, p = .01), indicating that the higher the initial level of shyness, the faster the rate of decrease across the three time points. Finally, child sex did not predict the initial level (b = .26, p = .18) or rate of change of shyness (b = .03, p = .51).

Figure 2. Reults for the Conditional Latent Growth Curve Model of Anger/frustration.

Figure 2

Open in a new tab

Note. Boys were coded as 0; girls were coded as 1. Significant effects are shown by solid black lines, nonsignificant effects are shown by dashed gray lines. Numbers on the significant paths represented the effect of a predictor on an outcome or the correlation between two variables when they were standardized. A = Anger/frustration, MI = Maternal intrusiveness, FA = Frontal EEG asymmetry.

The model of anger/frustration had a good model fit (χ2 (5, N = 180) = 10.87, p = .05, CFI = .96, SRMR = .03). Maternal intrusiveness at 4 years did not predict the initial level of anger/frustration (b = .01, p = .94) or the rate of change (b = .01, p = .47). Frontal EEG asymmetry at 4 years did not predict the initial level of anger/frustration (b = −.03, p = .74) or the rate of change (b = −.03, p = .24). The interactive term did not predict the initial level of anger/frustration (b = −.05, p = .45); however, it significantly predicted the rate of change of anger/frustration (b = .06, p < .001; see Figure 3).

Figure 3. The Developmental pattern of Shyness as a Function of Frontal EEG Asymmetry.

Figure 3

Open in a new tab

Note. FA = Frontal EEG asymmetry. Shyness was maternal reported.

We classified children based on their maternal intrusiveness (median split) and frontal EEG asymmetry scores (right: frontal EEG asymmetry < .00; left: frontal EEG asymmetry > .00) into four groups and plot the trajectories of anger/frustration from age 4 to age 9: high maternal intrusiveness and left frontal EEG asymmetry group (maternal intrusiveness > 1.00, frontal EEG asymmetry > .00; n = 29), high maternal intrusiveness and right frontal EEG asymmetry group (maternal intrusiveness > 1.00, frontal EEG asymmetry < .00; n = 31), low maternal intrusiveness and left frontal EEG asymmetry group (maternal intrusiveness = 1.00, frontal EEG asymmetry > .00; n = 61), and low maternal intrusiveness and right frontal EEG asymmetry group (maternal intrusiveness = 1.00, frontal EEG asymmetry < .00; n = 59). As shown in Figure 4, the mean level of anger/frustration decreased slower in children who experienced high maternal intrusiveness and showed left frontal EEG asymmetry (b = −.07, p = 0.12) compared with children who experienced high maternal intrusiveness and showed right frontal EEG asymmetry (b = −.22, p < .001) as well as those who experienced low maternal intrusiveness and had left (b = −.25, p < .001) and right (b = −.10, p < .001) frontal asymmetry. The initial level of anger/frustration was negatively associated with the rate of change (b = −.15, p < .001), indicating that anger/frustration decreased faster in children who had a higher initial level of it. Finally, child sex predicted the initial level of anger/frustration (b = −.36, p = .03), with boys having higher initial level of anger/frustration than girls (boys coded as 0; girls coded as 1).

Figure 4. The Developmental pattern of Anger/Frustration as a Function of Maternal Intrusiveness and Frontal EEG Asymmetry.

Figure 4

Open in a new tab

Note. Frontal EEG asymmetry predicted the trajectory of anger/frustration when children experienced high (upper) and low (lower) levels of maternal intrusiveness (median split) at age 4. Children exhibited the slowest linear decreasing mean pattern of anger/frustration when experienced high maternal intrusiveness and showed left frontal EEG asymmetry at age 4. MI = Maternal intrusiveness, FA = Frontal EEG asymmetry. Anger/frustration was maternal reported.

Discussion

The present study represents the first step in examining the interactive effect of maternal intrusiveness and frontal EEG asymmetry in predicting the developmental patterns of shyness and anger/frustration across childhood. Normative development included significant linear decreases in shyness and anger/frustration throughout childhood. There was significant variation across children in the initial level of temperament and the rate of change. Children with higher levels of shyness and anger/frustration at age 4 showed faster decreases in these temperament traits from age 4 to age 9. Frontal EEG asymmetry significantly predicted the rate of change in shyness. Specifically, children with left frontal EEG asymmetry at age 4 showed a faster decreasing pattern of shyness across childhood than children with right frontal EEG asymmetry. The interplay of maternal intrusiveness and frontal EEG asymmetry significantly predicted the rate of change in anger/frustration. Particularly, children who experienced higher maternal intrusiveness and had left frontal EEG asymmetry at age 4 showed a slower decreasing pattern of anger/frustration across childhood. Taken together, these findings highlight the influences of biological and environmental factors on the developmental pattern of temperament (Shiner et al., 2012).

The results of our study showed that both shyness and anger/frustration decreased from age 4 to age 9 on average, and there were significant differences among children in this decrease. The results are consistent with previous research indicating that shyness and anger/frustration decrease in childhood (e.g., Eggum-Wilkens et al., 2016; Denham et al., 1995). Developing communication and emotion regulation skills are typically associated with decreases in average anger/frustration levels (Denham et al., 1995). Further, high levels of inhibitory control during childhood are associated with lower levels of both anger/frustration (Gerardi-Caulton, 2000) and shyness (Liu et al., 2018a). Inhibitory control develops early in childhood and tends to get better as a child gets older (e.g., Best & Miller, 2010). Notably, our study highlights that the developmental pattern of temperament is largely driven by individual differences in a community sample. Such individual variation in the developmental pattern of temperament has been linked to later psychopathology risk (Perra, Paine, & Hay, 2020; Tang et al., 2017). For instance, infants who display a consistent high level of anger and aggression from 6 to 36 months have increased risks for behavioral problems and clinical disorders in childhood (Perra et al., 2020). Although children’s shyness and anger/frustration decreased on an average level in the current study, which can be expected because they are at a lower risk of developing behavioral problems as a whole, those who had a slower decreasing pattern of shyness and anger/frustration might be at elevated risks for behavioral problems later in development.

In support of our hypothesis, children with greater left frontal EEG asymmetry at age 4 showed a faster decreasing pattern in shyness than children with greater right frontal EEG asymmetry. This is consistent with a recent study reporting that children exhibiting greater right frontal activity at age 6 showed a faster increasing trajectory of shyness from 6- to 8-year-old (Poole et al., 2019). Right frontal EEG asymmetry is linked with withdrawal motivation (Harmon-Jones & Gable, 2018). Children who had greater right frontal EEG asymmetry lack the motivational tendency to explore novel environments and approach new people (Degnan & Fox, 2007). As such, they lose the opportunities to elevate their threshold for detecting threats and to practice social skills. As a result, these children are more likely to experience higher levels of wariness and anxious feelings in social contexts, compared with children who have greater left frontal activity indicating a tendency to approach (Harmon-Jones & Gable, 2018).

It was surprising to find that maternal intrusiveness did not have any main or interactive effects on temperamental shyness in our sample, as intrusive parenting has been linked to child shyness (Rubin et al., 2009). There are several possible reasons as to why our study did not yield this expected finding. First, the relative occurrence of maternal intrusiveness was low in our sample, which might explain the nonsignificant main and interactive effect of maternal intrusiveness on shyness. Second, because not all children who experience maternal intrusiveness will demonstrate temperamental shyness later in life, due to biological and other environmental factors (e.g., Belsky & Pluess, 2009; Calkins et al., 2016), it is possible that the children in our sample had other protective factors (e.g., peer support) that led to a more optimal developmental pattern of shyness. Third, much of the past research that has studied the relationships between maternal intrusiveness and temperamental shyness has been done on children who had a predisposition to developing disadvantageous patterns of temperamental shyness. For example, children classified with a slow-to-warm-up temperamental style during infancy demonstrated higher levels of childhood temperamental shyness when mothers were intrusive, rather than sensitive, in their parenting (Grady et al., 2012). Instead, we have a community sample of children who were not screened for having predispositions to temperamental shyness, which could help explain why we did not find any main or interactive effects regarding maternal intrusiveness and temperamental shyness. Finally, shyness contains multiple subtypes (e.g., fearful shyness, self-conscious shyness, positive-shyness, non-positive shyness; Poole & Schmidt, 2020; Schmidt & Buss, 2010), which may be differently associated with maternal intrusiveness. Related to this, the impact of maternal intrusiveness on shyness may become different as children grow older and as the nature of shyness changes. Thus, it is important to examine the effect of maternal intrusiveness on the different subtypes of shyness across development.

Our study provided first empirical evidence indicating that children of mothers who demonstrated more intrusiveness and who also showed greater left frontal activity at age 4 exhibited a slower decreasing pattern of anger/frustration across childhood. Left frontal EEG asymmetry has been associated with trait anger in adolescents and adults (Harmon-Jones, 2004). Children with left frontal EEG asymmetry tend to be more approach-oriented and thus might encounter more conflicts in daily interactions with peers (Liu et al., 2020). The high level of maternal intrusiveness prevents the growth of emotion regulation in children (Mortensen & Barnett, 2019), thus making the regulation of anger/frustration even more challenging.

Our study advances understanding of the developmental courses of temperament in several important ways. To begin, we considered both biological and contextual factors in predicting the developmental patterns of shyness and anger/frustration, which provided a more comprehensive and fine-grained view to explain individual differences in the developmental patterns of temperament. Second, we filled the gap of the existing literature by examining the moderating effect of frontal EEG asymmetry on the association between maternal negative behaviors and temperament in childhood, compared with previous research that was mainly interested in infancy (Diaz et al., 2019; Swingler et al., 2014). This is critical as maternal intrusiveness and frontal EEG asymmetry might play different roles in temperament depending on developmental period (Poole et al., 2019). Third, we included both withdrawal- (i.e., shyness) and approach-related (i.e., anger/frustration) aspects of temperament. The finding that maternal intrusiveness has an interactive effect on temperamental anger/frustration and not shyness highlight that the two temperamental dimensions may have different developmental pathways with different predictors and risk factors. Fourth, the majority of previous research studying frontal EEG asymmetry has focused on selected samples, such as those that were selected for extreme temperament profile (e.g., Fox et al., 2001b), maltreatment (e.g., Tang et al., 2018), or maternal depression (e.g., Feng et al., 2012), our study allowed the generalization of the findings to typically developing children.

Despite the many strengths of the present study, our findings should be interpreted in light of several limitations. First, temperament was only measured with maternal reports. Although temperament questionnaires have demonstrated validity and reliability and are widely used in developmental research (Rothbart et al., 2001), future research may consider using multi-informants or observation to reflect children’s temperament from different perspectives. Second, maternal intrusiveness in this study was coded during mother-child interactions in a laboratory. It could be that there are measures of maternal intrusiveness with higher ecological validity than what was used here. For example, assessing maternal intrusiveness in the home might yield results that more accurately reflect mothers’ and children’s daily life and interactions than doing so in the lab. Third, we assessed maternal intrusiveness and frontal EEG asymmetry once at age 4, given our main goal was to examine how early maternal intrusiveness and frontal EEG asymmetry serve as foundations of the developmental patterns of temperament across childhood. It remains an important direction to measure maternal intrusiveness and frontal EEG asymmetry at multiple times to examine the transactional associations among maternal intrusiveness, frontal EEG asymmetry, and temperament across childhood. Fourth, we used 6–9 Hz alpha frequency band for our EEG asymmetry calculation at 4 years based on previous studies that calculated alpha based on peak frequency (e.g., Fox et al., 2001b; Henderson et al., 2004; Marshall et al., 2002). Given recent calls for EEG to include both periodic and aperiodic properties (Donoghue et al., 2020), future EEG research should examine both of these properties to determine whether 6–9 Hz is the optional frequency for frontal alpha asymmetry research at age 4. Fifth, anchor items used in equating are often identical items. However, the anchor items in the current study do not have the exact same wording and were selected based on maximum conceptual similarity. Thus, the equating process is only a good approximation. Finally, children and mothers in our sample were predominantly White. More diverse samples are needed in future research.

In summary, maternal intrusiveness and frontal EEG asymmetry at age 4 predicted the developmental patterns of shyness and anger/frustration from 4- to 9-year-old. Specifically, children who displayed greater left frontal EEG asymmetry at age 4 showed a faster decreasing pattern of shyness across childhood. In addition, children who experienced a high level of maternal intrusiveness and showed greater left frontal asymmetry at age 4 had a slower decreasing pattern of anger/frustration across childhood. The findings are consistent with the motivational directional model suggesting that left frontal EEG asymmetry encourages children to approach whereas right frontal EEG asymmetry fosters children’s tendency to withdrawal (Harmon-Jones & Gable, 2018). Temperament has been well established as a predictor of child psychopathology (e.g., Tang et al., 2017). Although we did not directly measure children’s behavioral problems in the present study, these findings might shed light on certain pathways that portend more severe symptoms later in development and, thus, have important implications for early identification and treatment of children with high risk of subsequent psychopathology.

Supplementary Material

Figure S1

Acknowledgments

This research was supported by grant R01 HD049878 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) awarded to Martha Ann Bell. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the NICHD or the National Institutes of Health. We sincerely thank Susan D. Calkins and her team at the University of North Carolina at Greensboro for their many years of collaboration on the subcontract of this project. We are grateful to the families in Blacksburg VA and Greensboro NC for their long-term commitment to participate in our study.

Contributor Information

Ran Liu, Columbia University.

Jennifer J. Phillips, Virginia Tech

Feng Ji, University of California, Berkeley.

Dexin Shi, University of South Carolina.

Martha Ann Bell, Virginia Tech.

References

  1. Andersson B, Bränberg K, & Wiberg M (2013). Performing the Kernel Method of Test Equating with the Package kequate. Journal of Statistical Software, 55, 1–25. [Google Scholar]
  2. Baardstu S, Coplan RJ, Karevold EB, Laceulle OM, & von Soest T (2020). Longitudinal pathways from shyness in early childhood to personality in adolescence: Do peers matter? Journal of Research on Adolescence, 30, 362–379. 10.1111/jora.12482 [DOI] [PubMed] [Google Scholar]
  3. Bell MA, & Cuevas K (2012). Using EEG to Study Cognitive Development: Issues and Practices. Journal of Cognition and Development: Official Journal of the Cognitive Development Society, 13, 281–294. 10.1080/15248372.2012.691143 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Belsky J, & Pluess M (2009). Beyond diathesis stress: Differential susceptibility to environmental influences. Psychological Bulletin, 135, 885–908. 10.1037/a0017376 [DOI] [PubMed] [Google Scholar]
  5. Best JR, & Miller PH (2010). A developmental perspective on executive function. Child Development, 81, 1641–1660. 10.1111/j.1467-8624.2010.01499.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Booth-LaForce C, & Oxford ML (2008). Trajectories of social withdrawal from grades 1 to 6: Prediction from early parenting, attachment, and temperament. Developmental Psychology, 44, 1298–1313. 10.1037/a0012954 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Bornstein MH, Putnick DL, Gartstein MA, Hahn CS, Auestad N, & O’Connor DL (2015). Infant temperament: Stability by age, gender, birth order, term status, and socioeconomic status. Child Development, 86, 844–863. 10.1111/cdev.12367 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Buss KA (2011). Which fearful toddlers should we worry about? Context, fear regulation, and anxiety risk. Developmental Psychology, 47, 804–819. 10.1037/a0023227 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Calkins SD, Perry NB, & Dollar JM (2016). A biopsychosocial model of the development of self-regulation in infancy. In Balter L & Tamis-LeMonda C (Eds.), Child psychology: A handbook of contemporary issues (Vol. 3, 3rd ed., pp. 3–20). New York, NY: Routledge. [Google Scholar]
  10. Degnan KA, & Fox NA (2007). Behavioral inhibition and anxiety disorders: Multiple levels of a resilience process. Development and Psychopathology, 19, 729–746. 10.1017/S0954579407000363 [DOI] [PubMed] [Google Scholar]
  11. Denham SA, Lehman EB, & Moser MH (1995). Continuity and change in emotional components of infant temperament. Child Study Journal, 25, 289–308. [Google Scholar]
  12. Diaz A, Swingler MM, Tan L, Smith CL, Calkins SD, & Bell MA (2019). Infant frontal EEG asymmetry moderates the association between maternal behavior and toddler negative affectivity. Infant Behavior and Development, 55, 88–99. 10.1016/j.infbeh.2019.03.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Donoghue T, Haller M, Peterson EJ, Varma P, Sebastian P, Gao R, Noto T, Lara AH, Wallis JD, Knight RT, Shestyuk A, & Voytek B (2020). Parameterizing neural power spectra into periodic and aperiodic components. Nature Neuroscience, 23, 1655–1665. 10.1038/s41593-020-00744-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Eggum ND, Eisenberg N, Spinrad TL, Reiser M, Gaertner BM, Sallquist J, & Smith CL (2009). Development of shyness: Relations with children’s fearfulness, sex, and maternal behavior. Infancy, 14, 325–345. 10.1080/15200009028.39971 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Eggum-Wilkens ND, Reichenberg RE, Eisenberg N, & Spinrad TL (2016). Components of effortful control and their relations to children’s shyness. International Journal of Behavioral Development, 40, 544–554. 10.1177/0165025415597792 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Eisenberg N, Fabes RA, Shepard SA, Murphy BC, Guthrie IK, Jones S, Friedman J, Poulin R, & Maszk P (1997). Contemporaneous and longitudinal predictors of children’s social functioning from regulation and emotionality. Child Development, 68, 642–664. 10.1111/j.1467-8624.1997.tb04227.x [DOI] [PubMed] [Google Scholar]
  17. Eisenberg N, Taylor ZE, Widaman K, & Spinrad T (2015). Externalizing symptoms, effortful control, and intrusive parenting: A test of bidirectional longitudinal relations during early childhood. Development and Psychopathology, 27, 953–968. 10.1017/S09545794150000620 [DOI] [PubMed] [Google Scholar]
  18. Ellis LK, & Rothbart MK (2001). Revision of the Early Adolescent Temperament Questionnaire. Paper presented at the 2001 meeting of the Society for Research in Child Development, Minneapolis, Minnesota. [Google Scholar]
  19. Feldman R, Dollberg D, & Nadam R (2011). The expression and regulation of anger in toddlers: Relations to maternal behavior and mental representations. Infant Behavior and Development, 34, 310–320. 10.1016/j.infbeh.2011.02.001 [DOI] [PubMed] [Google Scholar]
  20. Feng X, Forbes EE, Kovacs M, George CJ, Lopez-Duran NL, Fox NA, & Cohn JF (2012). Children’s Depressive Symptoms in Relation to EEG Frontal Asymmetry and Maternal Depression. Journal of Abnormal Child Psychology, 40, 265–276. 10.1007/s10802-011-9564-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Fox NA, Henderson HA, & Marshall PJ (2001a). The biology of temperament: An integrative approach. In Nelson CA & Luciana M (Eds.), The handbook of developmental cognitive neuroscience (pp. 631–645). Cambridge, MA: Springer. [Google Scholar]
  22. Fox NA, Henderson HA, Rubin KH, Clakins SD, & Schmidt LA (2001b). Continuity and discontinuity of behavioral inhibition and exuberance: Psychophysiological and behavioral influences across the first four years of life. Child Development, 72, 1–21. 10.1111/1467-8624.00262 [DOI] [PubMed] [Google Scholar]
  23. Gatzke-Kopp LM, Jetha MK, & Segalowitz SJ (2014). The role of resting frontal EEG asymmetry in psychopathology: Afferent or efferent filter? Developmental Psychobiology, 56, 73–85. 10.1002/dev.21092 [DOI] [PubMed] [Google Scholar]
  24. Gerardi-Caulton (2000). Sensitivity to spatial conflict and the development of self-regulation in children 24–36 months of age. Developmental Science, 3, 397–404. 10.1111/1467-7687.00134 [DOI] [Google Scholar]
  25. Grady JS, Karraker K, & Metzger A (2012). Shyness trajectories in slow-to-warm-up infants: Relations with child sex and maternal parenting. Journal of Applied Developmental Psychology, 33, 91–101. 10.1016/j.appdev.2011.11.002 [DOI] [Google Scholar]
  26. Harmon-Jones E (2004). Contributions from research on anger and cognitive dissonance to understanding the motivational functions of asymmetrical frontal brain activity. Biological Psychology, 67, 51–76. 10.1016/j.biopsycho.2004.03.003 [DOI] [PubMed] [Google Scholar]
  27. Harmon-Jones E, & Gable PA (2018). On the role of asymmetric frontal cortical activity in approach and withdrawal motivation: An updated review of the evidence. Psychophysiology, 55, 42–64. 10.1111/psyp.12879 [DOI] [PubMed] [Google Scholar]
  28. Hastings PD, Nuselovici JN, Rubin KH, & Cheah CSL (2010). Shyness, parenting, and parent-child relationships. In Rubin KH & Coplan RJ (Eds.), The development of shyness and social withdrawal (pp. 107–130). New York, NY: Guilford. [Google Scholar]
  29. Henderson HA, Marshall PJ, Fox NA, & Rubin KH (2004). Psychophysiological and Behavioral Evidence for Varying Forms and Functions of Nonsocial Behavior in Preschoolers. Child Development, 75, 251–263. 10.1111/j.1467-8624.2004.00667.x [DOI] [PubMed] [Google Scholar]
  30. Hu L, & Bentler PM (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6, 1–55. 10.1080/10705519909540118 [DOI] [Google Scholar]
  31. Karevold EB, Tstrom E, Coplan RJ, Sanson AV, & Mathiesen KS (2012). A prospective longitudinal study of shyness from infancy to adolescence: Stability, age-related changes, and prediction of socio-emotional functioning. Journal of Abnormal Child Psychology, 40, 1167–1177. 10.1007/s10802-012-9635-6 [DOI] [PubMed] [Google Scholar]
  32. Kolen MJ, & Brennan RL (2014). Test equating, scaling, and linking: Methods and practices. New York, NY: Springer. [Google Scholar]
  33. Liu R, Calkins SD, & Bell MA (2018a). Fearful Inhibition, Inhibitory Control, and Maternal Negative Behaviors During Toddlerhood Predict Internalizing Problems at Age 6. Journal of Abnormal Child Psychology, 46, 1665–1675. 10.1007/s10802-018-0419-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Liu R, Calkins SD, & Bell MA (2020). Frontal EEG asymmetry moderates the associations between negative temperament and behavioral problems during childhood. Development and Psychopathology, 1–10. 10.1017/S0954579420000309 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Liu C, Moore GA, Beekman C, Pérez-Edgar KE, Leve LD, Shaw DS, Ganiban JM, Natsuaki MN, Reiss D, & Neiderhiser JM (2018b). Developmental patterns of anger from infancy to middle childhood predict problem behaviors at age 8. Developmental Psychology, 54, 2090–2100. 10.1037/dev0000589 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Marshall PJ, Bar-Haim Y, & Fox NA (2002). Development of the EEG from 5 months to 4 years of age. Clinical Neurophysiology, 113, 1199–1208. 10.1016/S1388-2457(02)00163-3 [DOI] [PubMed] [Google Scholar]
  37. Mortensen JA, & Barnett MA (2019). Intrusive parenting, teacher sensitivity, and negative emotionality on the development of emotion regulation in early head start toddlers. Infant Behavior and Development, 55, 10–21. 10.1016/j.infbeh.2019.01.004 [DOI] [PubMed] [Google Scholar]
  38. Muthén LK, & Muthén BO (1998–2017). Mplus user’s guide. Los Angeles: Muthén & Muthén. [Google Scholar]
  39. Myslobodsky MS, Coppola R, Bar-Ziv J, Karson C, Daniel D, van Praag H, & Weinberger DR (1989). EEG asymmetries may be affected by cranial and Brain parenchymal asymmetries. Brain Topography, 1, 221–228. 10.1007/BF01129599 [DOI] [PubMed] [Google Scholar]
  40. Peltola MJ, Bakermans-Kranenburg MJ, Alink LRA, Huffmeijer R, Biro S, & van IJzendoorn MH (2014). Resting frontal EEG asymmetry in children: Meta-analyses of the effects of psychosocial risk factors and associations with internalizing and externalizing behavior. Developmental Psychobiology, 56, 1377–1389. 10.1002/dev.21223 [DOI] [PubMed] [Google Scholar]
  41. Perra O, Paine AL, & Hay DF (2020). Continuity and change in anger and aggressiveness from infancy to childhood: The protective effects of positive parenting. Development and Psychopathology, 1–20. 10.1017/S0954579420000243 [DOI] [PubMed] [Google Scholar]
  42. Petersen IT, Lindhiem O, LeBeau B, Bates JE, Pettit GS, Lansford JE, & Dodge KA (2018). Development of Internalizing Problems from Adolescence to Emerging Adulthood: Accounting for Heterotypic Continuity with Vertical Scaling. Developmental Psychology, 54, 586–599. 10.1037/dev0000449 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Poole KL, Santesso DL, Van Lieshout RJ, & Schmidt LA (2019). Frontal brain asymmetry and the trajectory of shyness across the early school years. Journal of Abnormal Child Psychology, 47, 1253–1263. 10.1007/s10802-019-00513-w [DOI] [PubMed] [Google Scholar]
  44. Poole KL, & Schmidt LA (2020). Positive Shyness in the Brain: Frontal Electroencephalogram Alpha Asymmetry and Delta–Beta Correlation in Children. Child Development, 91, e1030–e1045. 10.1111/cdev.13379 [DOI] [PubMed] [Google Scholar]
  45. Reznik SJ, & Allen JJB (2018). Frontal asymmetry as a mediator and moderator of emotion: An updated review. Psychophysiology, 55, 1–32. 10.1111/psyp.12965 [DOI] [PubMed] [Google Scholar]
  46. Rothbart MK, & Bates JE (2006). Temperament. In Eisenberg N, Damon W, & Lerner RM (Eds.), Handbook of child psychology (6th ed., pp. 99–166). New York, NY: Wiley. [Google Scholar]
  47. Rothbart MK, Ahadi SA, Hershey KL, & Fisher P (2001). Investigations of temperament at three to seven years: The Children’s Behavior Questionnaire. Child Development, 72, 1394–1408. 10.1111/1467-8624.00355 [DOI] [PubMed] [Google Scholar]
  48. Rubin KH, Coplan RJ, & Bowker JC (2009). Social Withdrawal in Childhood. Annual Review of Psychology, 60, 141–171. 10.1146/annurev.psych.60.110707.163642 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Schmidt LA, & Buss AH (2010). Understanding shyness: Four questions and four decades of research. In Rubin KH & Coplan RJ (Eds.), The development of shyness and social withdrawal (p. 23–41). New York, NY: The Guilford Press. [Google Scholar]
  50. Shiner RL, Buss KA, McClowry SG, Putnam SP, Saudino KJ, & Zentner M (2012). What Is Temperament Now? Assessing Progress in Temperament Research on the Twenty-Fifth Anniversary of Goldsmith et al. (). Child Development Perspectives, 6, 436–444. 10.1111/j.1750-8606.2012.00254.x [DOI] [Google Scholar]
  51. Smith CL, Calkins SD, Keane SP, Anastopoulos AD, & Shelton TL (2004). Predicting Stability and Change in Toddler Behavior Problems: Contributions of Maternal Behavior and Child Gender. Developmental Psychology, 40, 29–42. 10.1037/0012-1649.40.1.29 [DOI] [PubMed] [Google Scholar]
  52. Swingler MM, Perry NB, Calkins SD, & Bell MA (2014). Maternal sensitivity and infant response to frustration: The moderating role of EEG asymmetry. Infant Behavior and Development, 37, 523–535. 10.1016/j.infbeh.2014.06.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Szabó N, Deković M, van Aken C, Verhoeven M, van Aken MAG, & Junger M (2008). The relations among child negative interactive behavior, child temperament, and maternal behavior. Early Childhood Research Quarterly, 23, 366–377. 10.1016/j.ecresq.2008.01.004 [DOI] [Google Scholar]
  54. Tang A, Miskovic V, Lahat A, Tanaka M, MacMillan H, Lieshout RJV, & Schmidt LA (2018). Trajectories of resting frontal brain activity and psychopathology in female adolescents exposed to child maltreatment. Developmental Psychobiology, 60, 67–77. 10.1002/dev.21585 [DOI] [PubMed] [Google Scholar]
  55. Tang A, Van Lieshout RJ, Lahat A, Duku E, Boyle MH, Saigal S, & Schmidt LA (2017). Shyness Trajectories across the First Four Decades Predict Mental Health Outcomes. Journal of Abnormal Child Psychology, 45, 1621–1633. 10.1007/s10802-017-0265-x [DOI] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

Figure S1
NIHMS1827311-supplement-Figure_S1.docx (2.7MB, docx)

RESOURCES