BACKGROUND:

Research of adults and school-aged children suggest a neurodevelopmental basis for psychiatric disorders. We examined whether infant neuromotor development predicted internalizing and externalizing problems in young children.

METHODS:

In Generation R, a population-based cohort in the Netherlands (2002–2006), trained research assistants evaluated the neuromotor development of 4006 infants aged 2 to 5 months by using an adapted version of Touwen’s Neurodevelopmental Examination (tone, responses, and senses and other observations). We defined nonoptimal neuromotor development as scores in the highest tertile. Mothers and fathers rated their children’s behavior at ages 1.5, 3, 6, and 10 years with the Child Behavior Checklist (n = 3474, response: 86.7%). The associations were tested with generalized linear mixed models.

RESULTS:

Overall, neuromotor development predicted internalizing scores, but no association was observed with externalizing scores. Nonoptimal muscle tone was associated with higher internalizing scores (mothers’ report: β = .07; 95% confidence interval [CI]: 0.01 to 0.13; fathers’ report: β = .09, 95% CI: 0.00 to 0.16). In particular, nonoptimal low muscle tone was associated with higher internalizing scores (mothers’ report: β = .11; 95% CI: 0.05 to 0.18; fathers’ report: β = .13; 95% CI: 0.04 to 0.22). We also observed an association between senses and other observations with internalizing scores. There was no relationship between high muscle tone or reflexes and internalizing scores.

CONCLUSIONS:

Common emotional problems in childhood have a neurodevelopmental basis in infancy. Neuromotor assessment in infancy may help identify vulnerability to early internalizing symptoms and offer the opportunity for targeted interventions.

What’s Known on This Subject:

Researchers who conducted studies with adults and school-aged children suggest that an association exists between early developmental problems and later diagnosis of psychiatric disorders; however, the prospective association with problem behavior in children, in particular emotional problems, is less understood.

What This Study Adds:

In 3474 children from the general population, infant neuromotor development predicted internalizing problems but not externalizing problems through age 10 years. These findings reveal that internalizing problems in childhood may have a neurodevelopmental basis that is evident early in life.

Childhood psychiatric problems are common and are associated with adverse mental health outcomes, poor school achievements, and delinquent behavior in later ages.1,3 Problem behavior in children often coincides with early developmental problems. In a community-based sample of twins, a modest association was reported between problem behavior and cognitive problems.4 Similarly, in a population-based follow-up study, delays in motor function and deviant language development predicted later psychiatric disorders.5 These observations are in accordance with the notion that an association exists between early developmental problems and later problem behavior. A possible explanation for this link comes from research on developmental disorders.6 For example, children with autism are shown to have problems with muscle tone in infancy.7 Other abnormalities, such as difficulties in motor coordination, were also observed in children at risk for autism.8 Neuromotor abnormalities, including abnormal movement and motor coordination problems, can also be a precursor of schizophrenia.9 Overall, with this line of research, it is suggested that early motor impairment, reflecting diffuse neural dysfunction, represents a vulnerability marker for psychopathology.10,11 Nonetheless, the association with later problem behavior in young children and in particular emotional problems is poorly understood. The association between neuromotor development and later psychopathology could be a potential treatment target for early detection and prevention. If early neuromotor impairment can predict specific patterns of behavioral traits in the general population, we may be able to better influence disease development with early interventions.

In registry studies, researchers using routine assessment of motor milestone have unveiled important findings in psychopathological research, but they have several limitations (eg, appropriate adjustment for confounders).11,12 Also, researchers who conducted studies that assess motor functioning and psychiatric disorders in large samples have relied on parents to report on the age of achieving a motor milestone.10 In contrast, the studies based on full neurologic examinations conducted by professionals to assess neuromotor development as a precursor of psychopathology are typically administered in small or clinical samples.10 

Thus, our goal was to study the prospective association between objective measures of neuromotor development conducted in infancy with repeated measures of children’s internalizing and externalizing problems through age 10 years. On the basis of our previous work, which demonstrated the importance of later executive functioning in infants with suboptimal motor development, we tested children’s shifting and planning as the underlying mechanisms of any potential association.13 Although child behavior was measured by using parental rating, the infant neuromotor development was assessed by research nurses, eliminating common method bias.14 We hypothesized that infants with nonoptimal neuromotor development had an increased risk of internalizing and externalizing problems.

Participants were from the Generation R Study, a population-based cohort in the Netherlands, which follows children and their parents from fetal life onwards.15,16 Pregnant women with an expected delivery date between 2002 and 2006 in Rotterdam were invited to participate in the study.

A flowchart of the study population is shown in Supplemental Fig 3. A total of 4006 infants underwent a neuromotor assessment at corrected ages between 2 and 5 months of age during a home visit. Information on 1 or more assessments of child behavior up to age 10 years was available for 3474 children (86.7% of 4006). Because the random exclusion of siblings did not change our results, they were included in the analyses. The study was approved by the Medical Ethics Committee of the Erasmus University Medical Center. Written informed consent was obtained from adult participants.

We performed a full neurologic age-adequate examination, encompassing assessment of tone, elicited responses, and senses and other observations (such as spontaneous movements) at age 2 to 5 months. There were 2 versions of the neuromotor assessment instrument (for 9–15 weeks and for 15–20 weeks) adapted from Touwen’s Neurodevelopmental Examination.17 All measured items were categorized in the following 3 groups: tone, responses, and senses and other observations. Tone items were scored as normal, low, or high tone; most responses and senses and other observations were scored as present, absent, or excessive. An age-appropriate response was labeled “normal”; a response that indicated delayed development was labeled “not normal.” Senses and other observations comprise strabism, fixation eyes, following movement eyes, hearing, sweating, and startled reactions. Within the subscale measuring tone, a further distinction was made between low tone and high tone, resulting in 2 additional scales for tone: “low tone symptoms” and “high tone symptoms.” As we studied a nonclinical population, the outcome measures were skewed; thus, we categorized the sum scores of the total and the subscales into tertiles, subsequently classifying the lowest and the middle tertiles as optimal neuromotor development and the highest as nonoptimal.18 

We examined the short-interval test-retest intraobserver reliability and the interobserver reliability of the assessment (n = 76). The intraclass correlation coefficient for the interobserver reliability was 0.64.13 

Two versions of the Child Behavior Checklist (CBCL) were used to obtain standardized parent reports of children’s problem behavior: the preschool version (CBCL/l1/2–5) and the school-aged version (CBCL/6–18). By summing the scores of specific questions from the CBCL/l1/2–5, the following syndrome scales were obtained: emotionally reactive, anxious and/or depressed, somatic complaints, withdrawn, sleep problems, attention scores, and aggressive behavior. The CBCL/6–18 includes similar scales as the CBCL/l1/2–5, with the exception of the emotionally reactive and sleep problems scores. There are 2 broadband scales: internalizing comprises the anxious and/or depressed, withdrawn-depressed, and somatic complaints scales, whereas externalizing comprises attention problems and aggressive behavior. According to the taxonomy of the CBCL, internalizing behaviors comprise problems that manifest mainly within the self, such as sad mood or anxiety, somatic complaints without known medical cause, and withdrawal from social contacts. These problems that pertain to emotions are often more difficult to detect than overt behavioral problems. Externalizing problems that are outer-directed generate discomfort and conflict.19,20 Good reliability and validity have been reported for both versions of the CBCL.21 Scale values were used continuously after a square root transformation to approximate normality. Because the CBCL/6–18 scores had different scales compared to the version for younger ages, we standardized all CBCL scale scores by dividing them by the corresponding SD. This method enabled us to compare 2 scores that are from different distributions.

Questionnaires were used to obtain information on parents’ highest level of education completed, age, antenatal psychiatric symptoms, child ethnicity, history of smoking during pregnancy, and household income. Maternal smoking was assessed by using questionnaires at enrollment, in midpregnancy, and in late pregnancy. Family income was defined by the total net monthly income of the household. The Brief Symptom Inventory was used to assess parents’ antenatal psychiatric symptoms.22 Child ethnicity was based on the parents’ countries of birth. Fetal ultrasound examinations were used to establish gestational age at birth. Midwife and hospital registries provided information on the infant’s date of birth, birth weight, and sex. Parents reported on their children’s autistic-like behaviors at age 6 years by using a short form of the Social Responsiveness Scale.21 Parents also rated their children’s executive functioning at age 4 years in domains of shifting and planning by using the Behavior Rating Inventory of Executive Function-Preschool version.23 

Differences in characteristics between children with and without data on problem behavior were compared by χ2 tests and independent samples t tests. We observed that mothers of infants with missing data were lower educated and suffered from more antenatal psychological symptoms compared with those included; this has been observed previously.18,24 There were no differences in other characteristics between the 2 groups. In Table 1, we provide the percentage missing for the covariates.

TABLE 1

Participants’ Characteristics (N = 3474)

Characteristics
Maternal 
 Age at enrollment, y 30.9 (5.0) 
  Missing data 
 Education, n (%)  
  Primary 630 (18.1) 
  Secondary 945 (27.2) 
  High 1674 (48.2) 
  Missing data 225 (6.5) 
 Antenatal psychiatric symptoms 0.15 (0.06 to 0.31) 
  Missing data  
 Smoking during pregnancy, n (%) 672 (20.8) 
  Missing data 250 (7.2) 
 Household income, n (%)  
  Poor 168 (4.8) 
  Low 389 (11.2) 
  Modal and above 2098 (60.4) 
  Missing data 819 (23.6) 
Partner  
 Age at enrollment, y 33.5 (5.4) 
  Missing data 977 
 Education %  
  Primary 395 (11.4) 
  Secondary 594 (17.1) 
  High 1239 (35.7) 
  Missing data 1246 (35.9) 
Child  
 Age at neuromotor assessment, wk 12.6 (2.0) 
  Missing data 
 Sex, boy (%) 1702 (49.0) 
  Missing data 
 Ethnic background, n (%)  
  Dutch 1858 (53.5) 
  Other Western 388 (11.2) 
  Non-Western 1167 (33.6) 
  Missing data 61 (1.8) 
 Gestational age at birth, wk 39.9 (1.7) 
  Missing data 
 Instrument (9–15 wk), % 2802 (80.7) 
 Instrument (15–20 wk), % 672 (19.3) 
  Missing data 
Characteristics
Maternal 
 Age at enrollment, y 30.9 (5.0) 
  Missing data 
 Education, n (%)  
  Primary 630 (18.1) 
  Secondary 945 (27.2) 
  High 1674 (48.2) 
  Missing data 225 (6.5) 
 Antenatal psychiatric symptoms 0.15 (0.06 to 0.31) 
  Missing data  
 Smoking during pregnancy, n (%) 672 (20.8) 
  Missing data 250 (7.2) 
 Household income, n (%)  
  Poor 168 (4.8) 
  Low 389 (11.2) 
  Modal and above 2098 (60.4) 
  Missing data 819 (23.6) 
Partner  
 Age at enrollment, y 33.5 (5.4) 
  Missing data 977 
 Education %  
  Primary 395 (11.4) 
  Secondary 594 (17.1) 
  High 1239 (35.7) 
  Missing data 1246 (35.9) 
Child  
 Age at neuromotor assessment, wk 12.6 (2.0) 
  Missing data 
 Sex, boy (%) 1702 (49.0) 
  Missing data 
 Ethnic background, n (%)  
  Dutch 1858 (53.5) 
  Other Western 388 (11.2) 
  Non-Western 1167 (33.6) 
  Missing data 61 (1.8) 
 Gestational age at birth, wk 39.9 (1.7) 
  Missing data 
 Instrument (9–15 wk), % 2802 (80.7) 
 Instrument (15–20 wk), % 672 (19.3) 
  Missing data 

Numbers are mean (SD) for variables with normal distribution, median (quartile range) for not-normally distributed variables, and percentages for categorical variables.

We used generalized linear mixed models (GLMMs) to estimate the standardized coefficients (β) and 95% confidence intervals (CIs) of the association between neuromotor development measured in infancy and internalizing and externalizing scores up to age 10 years. Subsequently, we examined the associations with the different CBCL syndrome scales. All models included a child-level random intercept and slope to account for repeated measures of child behavior and to model the child-specific variable effect. In these models, we used children’s repeated CBCL scores from age 1.5 years to age 10 years. GLMMs are robust to loss to follow-up under the missing at random assumption.25,26 Testing for missing assumptions27 confirmed that the missingness in externalizing scores but not internalizing was completely at random. All models were rerun with neuromotor development as a continuous variable.

Models were adjusted for confounders, selected on the basis of the change-in-estimate method or the theoretical framework of the study question. We also adjusted the models for the version of the instrument used. In an additional step, we adjusted the models for a child’s autistic-like behaviors to assess whether our results were independent of autistic traits.28 Interaction terms of neuromotor development with the age of each CBCL assessment, sex, ethnicity, and educational level were tested. Because the likelihood ratio tests did not reveal significant differences between nested models, except for the model for low muscle tone and age in relation to externalizing problems, the interaction terms were not included in other final models.

We ran mediation models with 99% bias-corrected bootstrap CIs, applying 5000 bootstrap samples by using an SPSS macro (IBM SPSS Statistics, IBM Corporation, Armonk, NY).29 We explored the indirect effects of infant neuromotor development on child’s internalizing behavior through shifting and planning (scores square-root transformed).

To handle the missing values on covariates, we used multiple imputations. Imputations were based on information on the infant neuromotor development and all covariates measured. Five independent data sets were generated and pooled estimates for those data sets were calculated. Multiple imputations were performed by using SPSS version 22.0. All other analyses were performed by using SAS version 9.3 (SAS Institute, Inc, Cary, NC) and R 3.4.0.30 

Participants’ characteristics are presented in Table 1. Neuromotor development was assessed at an average age of 12.6 weeks (SD = 2 weeks). In Table 2, we show the relationship between infant neuromotor development and internalizing scores through age 10 years. Nonoptimal overall neuromotor development predicted internalizing scores across childhood. Low muscle tone in infancy was associated with higher internalizing scores (mothers’ report: adjusted β = .11; 95% CI: 0.05 to 0.18; fathers’ report: adjusted β = .13; 95% CI: 0.04 to 0.22). In Supplemental Fig 4, we show associations between low muscle tone and internalizing scores at each assessment (adjusted for covariates and also additionally for previous observations). There was also an association between senses and other observations in infancy and internalizing scores (Table 2) but not between high muscle tone or reflexes and internalizing scores.

TABLE 2

Infant Neuromotor Development and Internalizing Scores Across Childhood Within the Generation R Study

Nonoptimal Neuromotor DevelopmentInternalizing Scores
Mother Reporta (1.5, 3, 6, and 10 y)Father Reportb (3 and 10 y)
Nβ (95% CI)PNβ (95% CI)P
Overall neuromotor development       
 Unadjusted 3402 .12 (0.06 to 0.18) <.001 3023 .11 (0.03 to 0.19) .009 
 Adjusted 3402 .08 (0.02 to 0.14) .008 3023 .10 (0.02 to 0.18) .022 
Muscle tone       
 Unadjusted 3321 .09 (0.03 to 0.15) .003 2954 .09 (0.01 to 0.17) .031 
 Adjusted 3321 .07 (0.01 to 0.13) .028 2954 .09 (0.00 to 0.16) .041 
Low tone symptoms       
 Unadjusted 3327 .13 (0.07 to 0.20) <.001 2959 .14 (0.05 to 0.22) .003 
 Adjusted 3327 .11 (0.05 to 0.18) <.001 2959 .13 (0.04 to 0.22) .004 
High tone symptoms       
 Unadjusted 3441 .06 (0.00 to 0.12) .048 3056 .09 (−0.01 to 0.20) .091 
 Adjusted 3441 .06 (−0.02 to 0.14) .114 3056 .07 (−0.04 to 0.18) .211 
Responses       
 Unadjusted 3267 .03 (−0.03 to 0.09) .271 2901 .05 (−0.03 to 0.14) .195 
 Adjusted 3267 .00 (−0.06 to 0.06) .923 2901 .05 (−0.03 to 0.13) .258 
Senses       
 Unadjusted senses 3452 .12 (0.06 to 0.18) <.001 3068 .13 (0.04 to 0.22) .003 
 Adjusted senses 3452 .06 (0.00 to 0.12) .040 3068 .10 (0.02 to 0.19) .019 
Nonoptimal Neuromotor DevelopmentInternalizing Scores
Mother Reporta (1.5, 3, 6, and 10 y)Father Reportb (3 and 10 y)
Nβ (95% CI)PNβ (95% CI)P
Overall neuromotor development       
 Unadjusted 3402 .12 (0.06 to 0.18) <.001 3023 .11 (0.03 to 0.19) .009 
 Adjusted 3402 .08 (0.02 to 0.14) .008 3023 .10 (0.02 to 0.18) .022 
Muscle tone       
 Unadjusted 3321 .09 (0.03 to 0.15) .003 2954 .09 (0.01 to 0.17) .031 
 Adjusted 3321 .07 (0.01 to 0.13) .028 2954 .09 (0.00 to 0.16) .041 
Low tone symptoms       
 Unadjusted 3327 .13 (0.07 to 0.20) <.001 2959 .14 (0.05 to 0.22) .003 
 Adjusted 3327 .11 (0.05 to 0.18) <.001 2959 .13 (0.04 to 0.22) .004 
High tone symptoms       
 Unadjusted 3441 .06 (0.00 to 0.12) .048 3056 .09 (−0.01 to 0.20) .091 
 Adjusted 3441 .06 (−0.02 to 0.14) .114 3056 .07 (−0.04 to 0.18) .211 
Responses       
 Unadjusted 3267 .03 (−0.03 to 0.09) .271 2901 .05 (−0.03 to 0.14) .195 
 Adjusted 3267 .00 (−0.06 to 0.06) .923 2901 .05 (−0.03 to 0.13) .258 
Senses       
 Unadjusted senses 3452 .12 (0.06 to 0.18) <.001 3068 .13 (0.04 to 0.22) .003 
 Adjusted senses 3452 .06 (0.00 to 0.12) .040 3068 .10 (0.02 to 0.19) .019 

The association between nonoptimal neuromotor development and internalizing through age 10 y were estimated with GLMMs to account for repeatedly assessed outcome. All models adjusted for a child’s age, sex and ethnicity, gestational age at birth, antenatal maternal psychiatric symptoms, household income, maternal history of smoking in pregnancy, and the version of neuromotor instrument.

a

In addition, all models are adjusted for age of the mother and education level of the mother.

b

In addition, all models are adjusted for age of the father and educational level of the father.

There was no association between nonoptimal overall neuromotor development in infancy and externalizing scores. Neither low nor high muscle tone was associated with externalizing scores (Table 3). We depict how infants’ low muscle tone relates to internalizing and externalizing scores over time in Figs 1 and 2. When we repeated the analysis with continuous neuromotor variables, the results remained essentially unchanged (Supplemental Table 3).

TABLE 3

Infant Neuromotor Development and Externalizing Scores Across Childhood Within Generation R Study

Nonoptimal Neuromotor DevelopmentExternalizing Scores
Mother Reporta (1.5, 3, 6, and 10 y)Father Reportb (3 and 10 y)
Nβ (95% CI)PNβ (95% CI)P
Overall neuromotor development       
 Unadjusted 3402 .02 (−0.03 to 0.08) .381 3023 .04 (−0.04 to 0.11) .353 
 Adjusted 3402 −.01 (−0.07 to 0.04) .617 3023 .03 (−0.05 to 0.10) .520 
Muscle tone       
 Unadjusted 3321 .01 (−0.05 to 0.06) .832 2954 .01 (−0.08 to 0.10) .704 
 Adjusted 3321 −.02 (−0.08 to 0.03) .466 2954 .02 (−0.06 to 0.09) .737 
Low tone symptoms       
 Unadjusted 3327 c — 2959 .04 (−0.04 to 0.12) .386 
 Adjusted 3327 c — 2959 .03 (−0.05 to 0.11) .446 
High tone symptoms       
 Unadjusted 3441 .04 (−0.01 to 0.10) .136 3056 .02 (−0.10 to 0.15) .764 
 Adjusted 3441 .01 (−0.06 to 0.09) .686 3056 −.02 (−0.12 to 0.09) .765 
Responses       
 Unadjusted 3267 .01 (−0.04 to 0.07) .692 2901 .04 (−0.03 to 0.12) .276 
 Adjusted 3267 −.01 (−0.06 to 0.05) .785 2901 .04 (−0.03 to 0.11) .299 
Senses       
 Unadjusted senses 3452 .03 (−0.02 to 0.09) .242 3068 .03 (−0.05 to 0.11) .445 
 Adjusted senses 3452 −.02 (−0.07 to 0.04) .556 3068 .01 (−0.07 to 0.08) .807 
Nonoptimal Neuromotor DevelopmentExternalizing Scores
Mother Reporta (1.5, 3, 6, and 10 y)Father Reportb (3 and 10 y)
Nβ (95% CI)PNβ (95% CI)P
Overall neuromotor development       
 Unadjusted 3402 .02 (−0.03 to 0.08) .381 3023 .04 (−0.04 to 0.11) .353 
 Adjusted 3402 −.01 (−0.07 to 0.04) .617 3023 .03 (−0.05 to 0.10) .520 
Muscle tone       
 Unadjusted 3321 .01 (−0.05 to 0.06) .832 2954 .01 (−0.08 to 0.10) .704 
 Adjusted 3321 −.02 (−0.08 to 0.03) .466 2954 .02 (−0.06 to 0.09) .737 
Low tone symptoms       
 Unadjusted 3327 c — 2959 .04 (−0.04 to 0.12) .386 
 Adjusted 3327 c — 2959 .03 (−0.05 to 0.11) .446 
High tone symptoms       
 Unadjusted 3441 .04 (−0.01 to 0.10) .136 3056 .02 (−0.10 to 0.15) .764 
 Adjusted 3441 .01 (−0.06 to 0.09) .686 3056 −.02 (−0.12 to 0.09) .765 
Responses       
 Unadjusted 3267 .01 (−0.04 to 0.07) .692 2901 .04 (−0.03 to 0.12) .276 
 Adjusted 3267 −.01 (−0.06 to 0.05) .785 2901 .04 (−0.03 to 0.11) .299 
Senses       
 Unadjusted senses 3452 .03 (−0.02 to 0.09) .242 3068 .03 (−0.05 to 0.11) .445 
 Adjusted senses 3452 −.02 (−0.07 to 0.04) .556 3068 .01 (−0.07 to 0.08) .807 

The association between nonoptimal neuromotor development and externalizing through age 10 y were estimated with GLMMs to account for repeatedly assessed outcome. All models adjusted for a child’s age, sex and ethnicity, gestational age at birth, antenatal maternal psychiatric symptoms, household income, maternal history of smoking in pregnancy, and the version of neuromotor instrument. —, not applicable.

a

In addition, all models are adjusted for age of the mother and education level of the mother.

b

In addition, all models are adjusted for age of the father and educational level of the father.

c

Because of the interaction effect of low muscle tone with age, results cannot be presented here. See Fig 2.

FIGURE 1

Internalizing z scores in children with optimal and nonoptimal neuromotor development in infancy (fitted values from the linear mixed model) with bootstrap CIs from 1000 runs. The mean of the fitted values from the multivariate model on association between infant neuromotor development and mother report of internalizing scores through age 10 years in children with optimal and nonoptimal low muscle tone are shown in the graph. The association was estimated with GLMMs to account for repeatedly assessed internalizing problems. The model is adjusted for a child’s age, sex and ethnicity, gestational age at birth, antenatal maternal psychiatric symptoms, household income, maternal history of smoking in pregnancy, maternal age, maternal education level, and the version of neuromotor instrument. CIs were calculated from 1000 bootstrap runs. SQRT, square root.

FIGURE 1

Internalizing z scores in children with optimal and nonoptimal neuromotor development in infancy (fitted values from the linear mixed model) with bootstrap CIs from 1000 runs. The mean of the fitted values from the multivariate model on association between infant neuromotor development and mother report of internalizing scores through age 10 years in children with optimal and nonoptimal low muscle tone are shown in the graph. The association was estimated with GLMMs to account for repeatedly assessed internalizing problems. The model is adjusted for a child’s age, sex and ethnicity, gestational age at birth, antenatal maternal psychiatric symptoms, household income, maternal history of smoking in pregnancy, maternal age, maternal education level, and the version of neuromotor instrument. CIs were calculated from 1000 bootstrap runs. SQRT, square root.

Close modal
FIGURE 2

Externalizing z scores in children with optimal and nonoptimal neuromotor development in infancy (fitted values from the linear mixed model) with bootstrap CIs from 1000 runs. The mean of the fitted values from the multivariate model on association between infant neuromotor development and mother report of externalizing scores through age 10 years in children with optimal and nonoptimal low muscle tone are shown in the graph. The association was estimated with GLMMs to account for repeatedly assessed externalizing problems. The model is adjusted for a child’s age, sex and ethnicity, gestational age at birth, antenatal maternal psychiatric symptoms, household income, maternal history of smoking in pregnancy, maternal age, maternal education level, and the version of neuromotor instrument. CIs were calculated from 1000 bootstrap runs. SQRT, square root.

FIGURE 2

Externalizing z scores in children with optimal and nonoptimal neuromotor development in infancy (fitted values from the linear mixed model) with bootstrap CIs from 1000 runs. The mean of the fitted values from the multivariate model on association between infant neuromotor development and mother report of externalizing scores through age 10 years in children with optimal and nonoptimal low muscle tone are shown in the graph. The association was estimated with GLMMs to account for repeatedly assessed externalizing problems. The model is adjusted for a child’s age, sex and ethnicity, gestational age at birth, antenatal maternal psychiatric symptoms, household income, maternal history of smoking in pregnancy, maternal age, maternal education level, and the version of neuromotor instrument. CIs were calculated from 1000 bootstrap runs. SQRT, square root.

Close modal

When the interaction of motor development with age at CBCL assessment was tested, we observed that for externalizing scores, the likelihood ratio test revealed model fit improvement compared to the model with no interaction term. There was no constant overall association between infant low muscle tone and externalizing scores through age 10 (Fig 2).

We examined the association between infant neuromotor development and internalizing subscales (mother and father report) and found that children with nonoptimal neuromotor development were more likely to have higher withdrawn, emotionally reactive, and anxious and/or depressed scores (the latter with the father’s report only) (Supplemental Tables 5 and 6). In particular, a low muscle tone was consistently associated with higher withdrawn scores (mothers’ report: adjusted β = .09; 95% CI: 0.05 to 0.14; fathers’ report: adjusted β = .09; 95% CI: 0.03 to 0.16). No association was observed with high muscle tone.

Using a bootstrapping technique, we observed a significant indirect effect of low muscle tone on internalizing and, in particular, withdrawn problems explained by shifting problems (adjusted β = .03; 95% CI for internalizing: 0.00 to 0.06; adjusted β = .02; 95% CI: 0.00 to 0.04 for withdrawn). We did not observe any mediation by planning.

In all analyses, adjustment for autistic traits did not change the results. With exclusion of 21 children with physical impairments, the results remained unchanged. There was no difference in sex in the relation between infant neuromotor development and child behavior (data not shown).

We found that nonoptimal infant neuromotor development and, in particular, low muscle tone and nonoptimal senses were consistently associated with internalizing scores, as repeatedly reported by mothers and fathers through age 10 years. This association was mainly accounted for by withdrawn problems and was partly mediated by problems in the shifting domain. We observed no association between nonoptimal neuromotor development and externalizing scores.

Common genetic and environmental factors might underlie both nonoptimal neurodevelopment and child problem behavior. Subtle genetic variations, represented by single nucleotide polymorphisms or copy number variation, have been associated with subtle abnormalities of brain development.31 In recent genome wide meta-analysis, researchers have shown that internalizing problems are heritable and moderately genetically stable from childhood to adulthood.32 At the same time, teratogens may cause brain abnormalities during prenatal development,33 which in turn lead to neurodevelopmental problems during the course of life. Examples of these adverse influences are nicotine and alcohol exposure during gestation,34,35 viral infections,36,37 as well as maternal stress, nutrition, and age.38,39 In our analysis, we controlled for several environmental factors. We observed that gestational age and birth weight as indicators of insults during pregnancy did not substantially affect the associations under study. Likewise, parental psychiatric symptoms, possible indicators of stress, did not explain our observations.40,41 With adjustment, the relationship between early neuromotor development and problem behavior was attenuated for parental psychopathology but remained. Postnatal factors (eg, a child’s physical health) may also underlie the association between infant neuromotor development and internalizing problems in children.42,43 Although we cannot completely rule out potential influences by a third factor (that underlies both nonoptimal neuromotor and child psychopathology) based on our results, we can conclude that motor skills are at the core of infants’ and children’s everyday actions and interactions and consequently affect perceptual, cognitive, and social development.44,45 Therefore, motor skills may initiate a cascade of events, influencing subsequent development. Since Piaget’s original observations that infants own sensorimotor experiences are critical for their learning about the environment, researchers in several studies have reported evidence for relations between motor skills and development in seemingly unrelated domains, such as object perception, face processing, and language skills.46 For example, early experiences of successful reaching at 3 months have been found to be associated with infants’ attention to faces over objects.47 Similarly, in another study, the onset of sitting independently at 3 to 5 months predicted language development at 10 and 14 months.48 Low muscle tone affects how infants move and develop and may mean that the infants achieve the major developmental milestones late. These infants get upset when confronting new situations on motor tasks and therefore spend less time exploring objects and different ways to do things. This cautious and fearful infant behavior style may have long-term consequences for communications and emotional and cognitive development. As a consequence, infants can become more reactive.

We showed an association between low muscle tone and internalizing and, in particular, withdrawn problems, which was independent of autistic traits. This finding is compatible with Touwen’s theory that describes infants with suboptimal neuromotor development (ie, mild neurologic signs) as typically displaying “clumsy behavior” that worsens between 4 and 9 years.49 Infants with low muscle tone might have difficulties in initiating movement and interacting with the environment and therefore show symptoms of withdrawal behavior during toddlerhood and school age. With our results, we suggest that low muscle tone in infancy might be an independent precursor of withdrawal behavior in these children. It is unclear if children withdraw because they lack the drive for social interaction or because of fear and anxiety. Whatever the origins of minor and mild neurologic signs, their presence plays a role in the development of behavioral and learning problems, most likely in combination with other factors.

To our knowledge, this study is the first to investigate whether executive functioning underlies the path from low muscle tone to internalizing problems. We found that a higher-order cognitive process, such as shifting, is an important factor in children’s vulnerability to psychopathology. Shifting presents a separate domain from other executive function domains.13,50,51 Children with shifting problems are often described as rigid, inflexible, not creative in problem solving, or upset with changes in routines. The specific neurobiological characteristics of shifting, described as the ability to make transition and to change the focus from 1 mindset to another, are less known than those of other aspects of executive function.52 Shifting aspect of executive function builds on other domains of executive function such as inhibition and develops later through development.53 Infants with low muscle tone face more problems when adapting to new circumstances during childhood. These more “rigid” children are at a higher risk of developing internalizing and, in particular, withdrawn behavior.54 The combined cognitive and motor problems may be the result of underlying inhibition problems or a general automation deficit. Researchers suggested that motor development predicts shifting and inhibition.13,55 Shifting particularly addresses the ability to automate behavior.56 Based on our findings, we postulate that the children with low muscle tone are less likely to learn to shift their focus of attention and therefore will experience more difficulties in adapting to changes in the environment.

We did not find an association between infant neuromotor development and externalizing scores. Externalizing problems, like aggression, are highly prevalent in young children57 and probably often reflect a normal developmental stage of children as evident by the decline in externalizing symptoms seen in both the children with optimal and nonoptimal motor development. Developing a sense of autonomy and determination to become independent of caregivers typically involve conflicts with parents and other caregivers. This could explain why in young children, scores in the borderline range of externalizing behavior are less likely to have origins in deviant neuromotor development. In twin studies, researchers have shown that although externalizing behaviors have unique genetic and a shared environmental basis, internalizing behaviors are associated with unique genetic influences only.58 Our findings are compatible with the notion that externalizing behaviors are sensitive to environmental influence as indicated by an early nonnormative development in children with more hypotonus at baseline; although, in theory, such an age-limited difference could also be of genetic origin.

This study has several strengths, including a large sample, considering many potential confounders, and objective assessments of neuromotor development independently of the mother. This is important, as relying on parents’ report for both neurodevelopment and the child’s behavior may introduce shared method bias.14 Also, we used the mother’s and father’s reports of child behavior to test consistency and obtain a more accurate description of the children’s problems.59 But we faced limitations. First, we experienced a loss to follow-up. However, we used GLMMs that are robust to loss to follow-up if the assumption holds that missing outcome happened at random. Second, we had only parental rating data on child behavior. Parents who are aware of their infant’s delay in neuromotor development could have been more attentive to their child’s problem behavior. In addition, parents were blinded to delayed neuromotor development and, therefore, their report was independent of neuromotor development in infancy. We considered many confounders; however, we cannot rule out residual confounding. We performed several rounds of tests. Therefore, chance finding should be considered when interpreting data. Also, the observed betas indicate small effects as expected in the general population.

In a prospective population-based study, we found that infants with nonoptimal neuromotor development and, in particular, low muscle tone, have higher internalizing scores during childhood. With our findings, we suggest that internalizing problems in childhood might have origins in early neurodevelopment. Future studies are needed to examine whether evaluation of early neuromotor development might help in identifying vulnerability to internalizing symptoms and can be used for targeted interventions in young children. For example, scaffolded reaching experiences have been shown to improve developmental parameters in 3-month-old infants at risk for motor delay.60 

     
  • CBCL

    Child Behavior Checklist

  •  
  • CBCL/l1/2–5

    Child Behavior Checklist preschool version

  •  
  • CBCL/6–18

    Child Behavior Checklist school-aged version

  •  
  • CI

    confidence interval

  •  
  • GLMM

    generalized linear mixed model

Dr Serdarevic conceptualized the study, performed the analysis, drafted the manuscript, interpreted the data, and completed all steps of revision until submission; Dr Ghassabian conceptualized the study, performed the analysis, interpreted the data, and completed all steps of revision until submission; Dr van Batenburg-Eddes designed the study, coordinated and supervised neuromotor data collection, interpreted the data, and completed all steps of revision until submission; Dr Tahirovic performed the analysis, interpreted the data, and completed all steps of revision until submission; Drs White and Jaddoe interpreted the data, critically reviewed the manuscript, and completed all steps of revision until submission; Dr Verhulst designed the study, interpreted the data, critically reviewed the manuscript, and completed all steps of revision until submission; Dr Tiemeier conceptualized and designed the study, drafted the manuscript, interpreted the data, and completed all steps of revision until submission; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: Supported by the Erasmus Medical Center (Rotterdam), the Erasmus University Rotterdam, the Netherlands Organization for Health Research and Development (ZonMw “Geestkracht” programme 10.000.1003), the Netherlands Organization for Scientific Research, and the Ministry of Health, Welfare and Sport. The Generation R Study is conducted by the Erasmus Medical Center in close collaboration with the School of Law and the Faculty of Social Sciences of the Erasmus University Rotterdam, the Municipal Health Service Rotterdam area, the Rotterdam Homecare Foundation, and the Stichting Trombosedienst and Artsenlaboratorium Rijnmond. Dr Tiemeier was supported by a grant from the Dutch Ministry of Education, Culture, and Science and the Netherlands Organization for Scientific Research (NWO grant 024.001.003, Consortium on Individual Development). The Erasmus–Western Balkans scholarship grant financed by the European Commission was awarded to Fadila Serdarevic (grant agreement 2013-2548/001-001-EMA2).

We thank participating mothers, general practitioners, hospitals, midwives, and pharmacies in Rotterdam.

1
Skovgaard
AM
,
Houmann
T
,
Christiansen
E
, et al;
CCC 2000 Study Team
.
The prevalence of mental health problems in children 1(1/2) years of age - the Copenhagen child cohort 2000.
J Child Psychol Psychiatry
.
2007
;
48
(
1
):
62
70
[PubMed]
2
Koot
HM
,
Verhulst
FC
.
Prevalence of problem behavior in Dutch children aged 2-3.
Acta Psychiatr Scand Suppl
.
1991
;
367
:
1
37
[PubMed]
3
Sourander
A
.
Emotional and behavioural problems in a sample of Finnish three-year-olds.
Eur Child Adolesc Psychiatry
.
2001
;
10
(
2
):
98
104
[PubMed]
4
Plomin
R
,
Price
TS
,
Eley
TC
,
Dale
PS
,
Stevenson
J
.
Associations between behaviour problems and verbal and nonverbal cognitive abilities and disabilities in early childhood.
J Child Psychol Psychiatry
.
2002
;
43
(
5
):
619
633
[PubMed]
5
Skovgaard
AM
,
Olsen
EM
,
Christiansen
E
,
Houmann
T
,
Landorph
SL
,
Jørgensen
T
;
CCC 2000 Study Group
.
Predictors (0-10 months) of psychopathology at age 11/2 years - a general population study in The Copenhagen Child Cohort CCC 2000.
J Child Psychol Psychiatry
.
2008
;
49
(
5
):
553
562
[PubMed]
6
Rutter
M
,
Kim-Cohen
J
,
Maughan
B
.
Continuities and discontinuities in psychopathology between childhood and adult life.
J Child Psychol Psychiatry
.
2006
;
47
(
3–4
):
276
295
[PubMed]
7
Flanagan
JE
,
Landa
R
,
Bhat
A
,
Bauman
M
.
Head lag in infants at risk for autism: a preliminary study.
Am J Occup Ther
.
2012
;
66
(
5
):
577
585
[PubMed]
8
Fournier
KA
,
Hass
CJ
,
Naik
SK
,
Lodha
N
,
Cauraugh
JH
.
Motor coordination in autism spectrum disorders: a synthesis and meta-analysis.
J Autism Dev Disord
.
2010
;
40
(
10
):
1227
1240
[PubMed]
9
Reiersen
AM
.
Collection of developmental history in the evaluation of schizophrenia spectrum disorders.
Scand J Child Adolesc Psychiatry Psychol
.
2016
;
4
(
1
):
36
43
[PubMed]
10
Ming
X
,
Brimacombe
M
,
Wagner
GC
.
Prevalence of motor impairment in autism spectrum disorders.
Brain Dev
.
2007
;
29
(
9
):
565
570
[PubMed]
11
Rosso
IM
,
Bearden
CE
,
Hollister
JM
, et al
.
Childhood neuromotor dysfunction in schizophrenia patients and their unaffected siblings: a prospective cohort study.
Schizophr Bull
.
2000
;
26
(
2
):
367
378
[PubMed]
12
Susser
E
,
Bresnahan
M
.
Epidemiologic approaches to neurodevelopmental disorders.
Mol Psychiatry
.
2002
;
7
(
suppl 2
):
S2
S3
[PubMed]
13
Serdarevic
F
,
van Batenburg-Eddes
T
,
Mous
SE
, et al
.
Relation of infant motor development with nonverbal intelligence, language comprehension and neuropsychological functioning in childhood: a population-based study.
Dev Sci
.
2016
;
19
(
5
):
790
802
[PubMed]
14
Podsakoff
PM
,
MacKenzie
SB
,
Lee
JY
,
Podsakoff
NP
.
Common method biases in behavioral research: a critical review of the literature and recommended remedies.
J Appl Psychol
.
2003
;
88
(
5
):
879
903
[PubMed]
15
Jaddoe
VW
,
van Duijn
CM
,
Franco
OH
, et al
.
The Generation R Study: design and cohort update 2012.
Eur J Epidemiol
.
2012
;
27
(
9
):
739
756
[PubMed]
16
Tiemeier
H
,
Velders
FP
,
Szekely
E
, et al
The Generation R Study: a review of design, findings to date, and a study of the 5-HTTLPR by environmental interaction from fetal life onward.
J Am Acad Child Adolesc Psychiatry
.
2012
;
51
(
11
):
1119
1135.e7
17
Touwen
BCL
.
Examination of the Child With Minor Neurological Dysfunction: Heinemann Medical
.
London, United Kingdom
:
Spastics International Medical Publications
;
1979
18
van Batenburg-Eddes
T
,
de Groot
L
,
Huizink
AC
, et al
.
Maternal symptoms of anxiety during pregnancy affect infant neuromotor development: the generation R study.
Dev Neuropsychol
.
2009
;
34
(
4
):
476
493
[PubMed]
19
Rescorla
LA
.
Assessment of young children using the Achenbach System of Empirically Based Assessment (ASEBA).
Ment Retard Dev Disabil Res Rev
.
2005
;
11
(
3
):
226
237
[PubMed]
20
Achenbach
T
,
Rescorla
LA
.
Manual for the ASEBA School-Age Forms & Profiles.
Burlington, VT
:
University of Vermont. Research Center for Children, Youth, & Families
;
2001
21
Tick
NT
,
van der Ende
J
,
Verhulst
FC
.
Ten-year increase in service use in the Dutch population.
Eur Child Adolesc Psychiatry
.
2008
;
17
(
6
):
373
380
[PubMed]
22
de Beurs
E
.
Brief Symptom Inventory, Handleiding
.
Leiden, Netherlands
:
PITS
;
2004
23
Gioia
GA
,
Espy
KA
,
Isquith
PK
.
BRIEF-P: Behavior Rating Inventory of Executive Function–Preschool Version: Professional Manual
.
Odessa, FL
:
Psychological Assessment Resources
;
2003
24
Van Batenburg-Eddes
T
,
Brion
MJ
,
Henrichs
J
, et al
.
Parental depressive and anxiety symptoms during pregnancy and attention problems in children: a cross-cohort consistency study.
J Child Psychol Psychiatry
.
2013
;
54
(
5
):
591
600
[PubMed]
25
Molenberghs
G
,
Verbeke
G
.
Models for Discrete Longitudinal Data
.
Berlin, Germany
:
Springer Science & Business Media
;
2006
26
Fitzmaurice
G
,
Laird
N
,
Ware
J
.
Applied Longitudinal Analysis
.
Hoboken, NJ
:
Wiley-Interscience
;
2004
27
Jamshidian
M
,
Jalal
S
.
Tests of homoscedasticity, normality, and missing completely at random for incomplete multivariate data.
Psychometrika
.
2010
;
75
(
4
):
649
674
[PubMed]
28
Serdarevic
F
,
Ghassabian
A
,
Van Batenburg-Eddes
T
, et al
.
Infant muscle tone and childhood autistic traits. A longitudinal study in the general population.
Autism Res
.
2017
;
10
(
5
):
757
768
[PubMed]
29
Hayes
AF
.
PROCESS: A Versatile Computational Tool for Observed Variable Mediation, Moderation, and Conditional Process Modeling
.
Lawrence, KS
:
University of Kansas
;
2012
30
R: A Language and Environment for Statistical Computing
[computer program].
Vienna, Austria
:
R Foundation for Statistical Computing
;
2014
31
Williams
NM
,
Zaharieva
I
,
Martin
A
, et al
.
Rare chromosomal deletions and duplications in attention-deficit hyperactivity disorder: a genome-wide analysis.
Lancet
.
2010
;
376
(
9750
):
1401
1408
[PubMed]
32
Benke
KS
,
Nivard
MG
,
Velders
FP
, et al
.
A genome-wide association meta-analysis of preschool internalizing problems.
J Am Acad Child Adolesc Psychiatry
.
2014
;
53
(
6
):
667
676.e7
33
Altshuler
D
,
Daly
MJ
,
Lander
ES
.
Genetic mapping in human disease.
Science
.
2008
;
322
(
5903
):
881
888
[PubMed]
34
Roza
SJ
,
Verburg
BO
,
Jaddoe
VW
, et al
.
Effects of maternal smoking in pregnancy on prenatal brain development. The Generation R Study.
Eur J Neurosci
.
2007
;
25
(
3
):
611
617
[PubMed]
35
Spadoni
AD
,
McGee
CL
,
Fryer
SL
,
Riley
EP
.
Neuroimaging and fetal alcohol spectrum disorders.
Neurosci Biobehav Rev
.
2007
;
31
(
2
):
239
245
[PubMed]
36
O’Callaghan
E
,
Sham
P
,
Takei
N
,
Glover
G
,
Murray
RM
.
Schizophrenia after prenatal exposure to 1957 A2 influenza epidemic.
Lancet
.
1991
;
337
(
8752
):
1248
1250
[PubMed]
37
Sever
JL
,
Nelson
KB
,
Gilkeson
MR
.
Rubella epidemic, 1964: effect on 6,000 pregnancies.
Am J Dis Child
.
1965
;
110
(
4
):
395
407
[PubMed]
38
Susser
E
,
St Clair
D
,
He
L
.
Latent effects of prenatal malnutrition on adult health: the example of schizophrenia.
Ann N Y Acad Sci
.
2008
;
1136
:
185
192
[PubMed]
39
Brown
AS
,
van Os
J
,
Driessens
C
,
Hoek
HW
,
Susser
ES
.
Further evidence of relation between prenatal famine and major affective disorder.
Am J Psychiatry
.
2000
;
157
(
2
):
190
195
[PubMed]
40
Piallini
G
,
Brunoro
S
,
Fenocchio
C
, et al
.
How do maternal subclinical symptoms influence infant motor development during the first year of life?
Front Psychol
.
2016
;
7
:
1685
[PubMed]
41
Jokiranta
E
,
Brown
AS
,
Heinimaa
M
,
Cheslack-Postava
K
,
Suominen
A
,
Sourander
A
.
Parental psychiatric disorders and autism spectrum disorders.
Psychiatry Res
.
2013
;
207
(
3
):
203
211
[PubMed]
42
Mesman
J
,
Koot
HM
.
Early preschool predictors of preadolescent internalizing and externalizing DSM-IV diagnoses.
J Am Acad Child Adolesc Psychiatry
.
2001
;
40
(
9
):
1029
1036
[PubMed]
43
Allen
NB
,
Lewinsohn
PM
,
Seeley
JR
.
Prenatal and perinatal influences on risk for psychopathology in childhood and adolescence.
Dev Psychopathol
.
1998
;
10
(
3
):
513
529
[PubMed]
44
Bushnell
EW
,
Boudreau
JP
.
Motor development and the mind: the potential role of motor abilities as a determinant of aspects of perceptual development.
Child Dev
.
1993
;
64
(
4
):
1005
1021
[PubMed]
45
Libertus
K
,
Hauf
P
.
Editorial: motor skills and their foundational role for perceptual, social, and cognitive development.
Front Psychol
.
2017
;
8
:
301
[PubMed]
46
Piaget
J
.
The Construction of Reality in the Child
.
Abingdon, United Kingdom
:
Routledge
;
1954
47
Libertus
K
,
Needham
A
.
Reaching experience increases face preference in 3-month-old infants.
Dev Sci
.
2011
;
14
(
6
):
1355
1364
[PubMed]
48
Libertus
K
,
Violi
DA
.
Sit to talk: relation between motor skills and language development in infancy.
Front Psychol
.
2016
;
7
:
475
[PubMed]
49
Touwen
BCL
. Longitudinal studies in motor development: neurodevelopmental neurological considerations. In:
Kalverboer
AF
,
Hopkins
B
,
Geuze
A
, eds.
Motor Development in Early and Later Childhood: Longitudinal Approaches
.
Cambridge, United Kingdom
:
Cambridge University Press
;
1993
:
27
50
Friedman
NP
,
Miyake
A
,
Robinson
JL
,
Hewitt
JK
.
Developmental trajectories in toddlers’ self-restraint predict individual differences in executive functions 14 years later: a behavioral genetic analysis.
Dev Psychol
.
2011
;
47
(
5
):
1410
1430
[PubMed]
51
Miyake
A
,
Friedman
NP
.
The nature and organization of individual differences in executive functions: four general conclusions.
Curr Dir Psychol Sci
.
2012
;
21
(
1
):
8
14
[PubMed]
52
Gioia
GA
,
Andrwes
K
,
Isquith
PK
.
Behavior Rating Inventory of Executive Function-Preschool Version (BRIEF-P)
.
Odessa, FL
:
Psychological Assessment Resources
;
1996
53
Diamond
A
.
Executive functions.
Annu Rev Psychol
.
2013
;
64
:
135
168
[PubMed]
54
Yerys
BE
,
Wallace
GL
,
Harrison
B
,
Celano
MJ
,
Giedd
JN
,
Kenworthy
LE
.
Set-shifting in children with autism spectrum disorders: reversal shifting deficits on the Intradimensional/Extradimensional Shift Test correlate with repetitive behaviors.
Autism
.
2009
;
13
(
5
):
523
538
[PubMed]
55
Michel
E
,
Roethlisberger
M
,
Neuenschwander
R
,
Roebers
CM
.
Development of cognitive skills in children with motor coordination impairments at 12-month follow-up.
Child Neuropsychol
.
2011
;
17
(
2
):
151
172
[PubMed]
56
Koziol
LF
,
Lutz
JT
.
From movement to thought: the development of executive function.
Appl Neuropsychol Child
.
2013
;
2
(
2
):
104
115
[PubMed]
57
Tremblay
RE
,
Nagin
DS
,
Séguin
JR
, et al
.
Physical aggression during early childhood: trajectories and predictors.
Pediatrics
.
2004
;
114
(
1
). Available at: www.pediatrics.org/cgi/content/full/114/1/e43
[PubMed]
58
Mikolajewski
AJ
,
Allan
NP
,
Hart
SA
,
Lonigan
CJ
,
Taylor
J
.
Negative affect shares genetic and environmental influences with symptoms of childhood internalizing and externalizing disorders.
J Abnorm Child Psychol
.
2013
;
41
(
3
):
411
423
[PubMed]
59
Kraemer
HC
,
Measelle
JR
,
Ablow
JC
,
Essex
MJ
,
Boyce
WT
,
Kupfer
DJ
.
A new approach to integrating data from multiple informants in psychiatric assessment and research: mixing and matching contexts and perspectives.
Am J Psychiatry
.
2003
;
160
(
9
):
1566
1577
[PubMed]
60
Libertus
K
,
Landa
RJ
.
Scaffolded reaching experiences encourage grasping activity in infants at high risk for autism.
Front Psychol
.
2014
;
5
:
1071
[PubMed]

Competing Interests

POTENTIAL CONFLICT OF INTEREST: Dr Verhulst is the contributing editor of the Achenbach System of Empirically Based Assessment, from which he receives remuneration; the other authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

Supplementary data