Skip to Content

Office of the Vice President for Research

  • banner showing faces made of crumped paper in gray with one in color

Examining Biobehavioral Indicators of ADHD in Children with FXS

Authors
Hannah Pressler, B.S., Kayla Smith, B.S., Ramsey Coyle, B.S., Elizabeth Will, Ph.D., and Jane Roberts, Ph.D. 

 

Abstract

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by inattention and hyperactivity/impulsivity behaviors that are inconsistent with developmental age. Children with fragile X syndrome (FXS), a genetic neurodevelopmental disorder, are often diagnosed with comorbid ADHD (53–59% of males with FXS). Despite the prevalence of ADHD in FXS, little is known about the early manifestation of ADHD. The current project aims to explore group differences in play behaviors between children with FXS and typically developing (TD) children as well as the relationship between infant play behavior and heart activity to future ADHD attention outcomes. Participants included male children with FXS and male TD children assessed at 12 months of age and again during preschool years. During infancy, play behavior and heart activity were measured during a free play task. Cognitive ability was determined using the Mullen Scales of Early Learning (MSEL). The Child Behavior Checklist (CBCL) was used to assess attention problems during preschool years. Groups did not significantly differ in play behavior between infants with FXS and TD infants, F(1,40) = 0.40, p = 0.533. Although groups significantly differed in attention problems, F(1,41) = 34.53, p < 0.001, results indicate that play behavior during infancy was not correlated to future attention problems for infants with FXS, r = -.32, p = .217. Heart activity was also not correlated to future attention problems for infants with FXS, r = -.32, p = .489. These findings suggest that play behavior and heart activity may not be adequate indicators of ADHD in infants with FXS at 12 months of age.

 

Introduction

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder (NDD) characterized by inattention and hyperactivity/impulsivity behaviors that interfere with functioning and development and are inconsistent with developmental age (American Psychiatric Association, 2013). ADHD is one of the most common psychiatric disorders, with an estimated prevalence of 2–5.7% in young children and a male to female ratio of 5:1 (Chronis-Tuscano et al., 2014; Lange et al., 2016). ADHD has been shown to impair social, academic, familial, and occupational areas of life (Barkley, 2003). Furthermore, children with ADHD are at a higher risk for social rejection from their peers (Milich & Landau, 1982; Pelham & Bender, 1982).

The Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM–5) classifies ADHD into three subtypes: predominantly hyperactive-impulsive type, predominantly inattentive type, and combined type (American Psychiatric Association, 2013). The DSM–5 states that a child’s inattention and/or hyperactivity-impulsivity must be frequent, severe, persistent, and incomparable with developmental level to be considered a symptom of ADHD (American Psychiatric Association, 2013; Egger & Angold, 2006). These parameters pose a challenge for clinically diagnosing preschoolers with ADHD as it is difficult to differentiate between developmentally appropriate and clinically significant inattention and impulsivity at this age (Egger & Angold, 2006). The challenges faced by children with ADHD are exacerbated by overlapping symptoms between ADHD and the other neurodevelopmental disorders.

Fragile X syndrome (FXS) is an X-linked dominant genetic disorder and is the most common inherited cause of intellectual disability (ID). Due to sex-linkage, 1 in 4,000 males have FXS and often express a more severe phenotype, while only 1 in 8,000 females have FXS (Crawford et al., 2001). Clinical manifestations of FXS include cognitive, physical, and behavioral abnormalities; however, the most clinically relevant phenotypes are global developmental delay, ID, psychomotor delays, and learning disabilities (Alanay et al., 2007; Mazzocco, 2000). The neuropsychological profile of FXS is complex, with 73% of affected individuals exhibiting at least one comorbid disorder, such as ADHD (Alanay et al., 2007). Children with FXS are at a high risk for ADHD due to intellectual and cognitive deficits. An estimated 53–59% of males with FXS exhibit clinical symptoms of ADHD, a rate that is significantly higher than what is seen in the general population (Sullivan et al., 2006). The National Survey of Children’s Health estimated that 9.4% of typically developing (TD) adolescents have received a clinical ADHD diagnosis (Danielson et al., 2018). Approximately 84% of males and 67% of females with FXS exhibit clinically significant inattention and impulsivity, and 66% of males and 30% of females exhibit increased hyperactivity (Bailey et al., 2008; Sullivan et al., 2006). ADHD symptoms in children with FXS predict social problems and affect social functioning (Chromik et al., 2015). Early diagnosis of ADHD in children with FXS is clinically imperative to help mitigate the adverse effects of the comorbid disorders, as behavioral treatment and medication intervention can be utilized promptly.

Play behavior in children may be a valuable measure of development that can be used as an early marker of hyperactivity, impulsivity, and inattention in children with ADHD. Uninterrupted, exploratory play facilitates problem-solving skills and cognitive development in children as they use these interactions as a platform for social learning (Pierce-Jordan & Lifter, 2005; Sutton-Smith, 1997). TD children sequentially progress from indiscriminate toy manipulation during infancy to symbolic play later in childhood (Ungerer & Sigman, 1984). The Piaget approach to play analysis, a tenet of developmental psychology, describes infant play patterns as indiscriminate, or random, due to their limited knowledge of various schemes, or cognitive thought processes. As actions become more coordinated, toy play also becomes more symbolic as it reflects the child’s conceptual understanding of the outside world (Belsky & Most, 1981). The cognitive challenges experienced by children with FXS impair their engagement in free play, and inhibit them from experiencing the same emergence of play patterns as seen in TD children (McDuffie et al., 2015). When compared at the same chronological age, developmentally delayed children produce fewer toy interactions, engage in simpler play patterns, and show less interest in toys compared to TD children (Lifter et al., 2011; Thiemann- Bourque et al., 2012). The cognitive and behavioral deficits found in children with FXS, namely hyperactivity, impulsivity, inattention, and repetitive behaviors, are thought to impact play skills more than other developmental disabilities found in children (McDuffie et al., 2015). Furthermore, children with comorbid FXS and ADHD have greater difficulty with developmentally age-appropriate play patterns, due to cognitive and psychomotor delays, resulting in fewer toy interactions and increased repetitive or incoherent play patterns (McDuffie et al., 2015; Smith et al., 2012).

In addition to play behavior, physiological markers, such as heart activity, may also serve as a promising early marker of ADHD in children with FXS. ADHD is characterized by emotional lability stemming from autonomic nervous system (ANS) dysfunction (McQuade & Breaux, 2017; Porges et al., 1994). ANS function can be examined via heart rate variability (HRV) measured with an electrocardiogram (ECG). HRV depicts parasympathetic activity and is indexed by respiratory sinus arrhythmia (RSA). More specifically, RSA measures vagal nerve input, commonly called vagal tone (Kuo et al., 1999; Porges et al., 1994). RSA is determined by the beat-to-beat variability per respiration cycle. Using an ECG to determine heart beats, this breath-by-breath analysis is calculated by the difference between maximum inter beat interval (IBI) during inspiration and minimum IBI during expiration. Greater differences in IBI results in a higher RSA, meaning a more appropriate response to an environmental stimulus (Porges et al., 1994). People with ADHD exhibit autonomic hypoarousal and decreased sympathetic and parasympathetic cardiac activity, quantified by decreased RSA. In an analysis of cardiac activity by Wang et al. (2013), males displayed more externalizing expressions, such as hyperactivity and impulsiveness, and showed a significant correlation between behaviors associated with ADHD and HRV (Hermens et al., 2004). Taken together, these results suggest that hypoarousal, as indexed by vagal tone, likely contributes to disruptive behavioral tendencies seen in ADHD (Wang et al., 2013). Heart rate activity is a promising potential early indicator of ADHD as it is not influenced by rater bias as seen in other subjective diagnostic measures (McQuade & Breaux, 2017).

There is an interesting interaction between ADHD and FXS in terms of heart activity. ADHD is characterized by hypoarousal, while FXS is characterized by hyperarousal, yet there are high rates of comorbidity of the two conditions (Bailey et al., 2008; Heilman et al., 2012; Roberts et al., 2001; Roberts et al., 2012; Sullivan et al., 2006; Wang et al., 2013). Due to the contradictory physiological profile present in children with FXS and children with ADHD, further research is needed to understand the underlying biobehavioral mechanisms in children with these two comorbid disorders.

The present study aims to explore the association of play behaviors and heart activity in young males with FXS to later ADHD-associated attention problems. A more complete understanding of biobehavioral markers and their potential use as early indictors of ADHD symptoms is important in the development of intervention strategies for ADHD in young males 7 with FXS and ADHD. The present study examines these relationships through the following research questions:

  1.  Does play behavior, measured by the total number of toy switches and the total number of novel toy switches, during a free play task differ among 12-month-old males with FXS in comparison to 12-month-old TD males?
  2. Does play behavior, measured by the total number of toy switches and the total number of novel toy switches, during a free play task correlate with later ADHD-associated attention problems in 12-month-old males with FXS or TD males?
  3. Do variations in heart activity, as indexed by RSA, during a free play task at 12 months of age correlate with later ADHD-associated attention problems in either males with FXS or TD males?

It was hypothesized that there will be an increased number of the total toy switches and a decreased number of novel toy switches, in males with FXS compared to TD males at 12 months of age, demonstrating developmentally inappropriate play patterns. It was also hypothesized that a decreased vagal tone quantified by decreased RSA during play would be present in 12-monthold males with FXS. It was also predicted that children with decreased RSA and decreased number of novel toy switches during uninterrupted play would exhibit increased ADHDassociated attention problems at school age.

 

Method

Participants

Participants included 17 males with FXS and 26 TD males, serving as a chronologically age-matched control group. The presence of FXS was confirmed through genetic testing. Participants were drawn from a larger longitudinal study on the early development of infants 8 with FXS (Roberts et al., 2020). The current study excluded female participants because of significant sex differences in both ADHD and FXS phenotypes. Participants were included if they had free play observational data, a parent-reported assessment of behavior, and a developmental assessment (2 TD children did not have the developmental assessment at the later time point due to loss to follow-up). Data from a subset of 7 males with FXS and 17 TD males with heart activity data during the play behavior task was analyzed to address the third research question. TD infants were excluded from the study if they had a family history (i.e., first-degree relative) of autism spectrum disorder (ASD) or if they were later diagnosed with ASD through the larger study. Detailed participant characteristics are included in Table 1.

Measures

Play Behavior. Play-based behaviors were coded during the Arc of Toys task during the Laboratory Temperament Assessment Battery (Lab-TAB). The Lab-TAB is a tool used in developmental psychology to evaluate overall temperament via various measures, with one of the measures being the Arc of Toys task to specifically assess behavior and attention during free play (Dougherty et al., 2011; Goldsmith & Rothbart, 1999). During the Arc of Toys task, the child is allowed to engage in uninterrupted play with a standardized set of toys for five minutes. The child-driven task allows observers to record and assess intrinsic play behavior void of parent interaction or external stimuli and provides a valid observational measure of inherent play behavior. The Arc of Toys task was administered by trained research specialists in either the child’s home or in the Neurodevelopmental Disorders (NDD) lab at the University of South Carolina, Columbia in accordance with the Lab-TAB manual developed by Goldsmith (Goldsmith et al., 1999). During the task, the child was allowed to play with a preset group of toys in whatever manner he or she chose. The toys consisted of an airplane, an alligator, a xylophone, a ball, a basket of plastic food items, a small bowling set, a dinosaur, a fire truck, pounding balls, and a rainmaker arranged in a semicircle around the child. The child wore a heart rate monitor during the task to collect heart activity data. The Arc of Toys task was video recorded and coded offline by a trained research assistant. The Arc of Toys task has exhibited rank order stability in the structure and temperament of adolescents with convergence of parent reports (Dyson et al., 2015; Dyson et al., 2011).

The child’s play behavior was coded in Noldus Observer XT (version 10.5, Noldus Information Technology, Leesburg, VA, USA) software using frequency codes. Once the examiner cued the beginning of the task, behavior was coded by toy name each time the child interacted with a toy or any combination of the toys. Each toy interaction was added to the total number of toy switches. When a child interacted with a toy that he had not previously engaged with, it was added to the total number of novel toy switches. If the child was unengaged with the toys when the examiner began the task, the behavior was coded as “latency”. Additionally, if the child exited the camera view the behavior was coded as “obscured”, and if the child was not interacting with any toys the behavior was coded as “unengaged”. Redirections were also coded as “first redirection”, “second redirection”, and “third redirection”. Once all of the video assessments were coded, the data was extracted from Observer XT and analyzed. Behavioral coding was completed by a trained research assistant who established initial reliability with a master coder by obtaining 80% on three consecutive videos. In order to maintain reliability, 20% of the videos were coded by the master coder, with a Cohen’s kappa coefficient of .91.

ADHD Symptom Severity. The Child Behavior Checklist (CBCL) is a parent-reported assessment of child behaviors that screens for emotional, behavioral, and social problems (Achenbach & Rescorla, 2001). The CBCL assesses emotional and behavioral problems in children and adolescents across seven syndrome scale scores, a DSM-orientated scale with five categories consistent with DSM-5 ADHD diagnostics categories, and three summary scores (Achenbach & Rescorla, 2001). The attention-based scale raw scores were used in the present study to assess ADHD-associated attention problems.

The parents of the study participants rated descriptions of their child’s behavior on a Likert scale (0= “Not True,” 1= “Somewhat or Sometimes True,” or 2= “Very True or Often True”) and the scores were totaled for one cumulative score. The CBCL attention-based score reflects the number of items endorsed in that particular section. Accordingly, a higher score was more indicative of severe attention problems (Achenbach & Rescorla, 2001). The CBCL has shown high reliability and validity among symptom rating and psychological diagnoses (van der Veen-Mulders et al., 2017; Warnick et al., 2008).

Developmental Level. The Mullen Scales of Early Learning (MSEL) is a standardized assessment that measures cognitive and motor development in children between 0 and 68 months of age across five subscales (Gross Motor, Visual Reception, Fine Motor, Expressive Language, and Repetitive Language; Mullen, 1995). The Early Learning Composite (ELC) score was derived from all domains except the Gross Motor domain at both time points in this study and was used as a measure of developmental level. Previous research has shown the MSEL’s validity in the evaluation of developmentally delayed children’s engagement and motor skills (Akshoomoff, 2006).

Heart Activity. Heart activity was recorded during the Arc of Toys free play in 12- month-old males with FXS and TD 12-month-old males. ECG data from the Arc of Toys free play task were recorded with an Alive Wireless Heart Monitor (Alive Technologies, Copyright 2005–2009) at a 300 Hz sampling rate. The raw heart activity data was visually processed with CardioEdit software to correct false heart periods or artifacts (Brain-Body Canter, 2007). The data was then bandpass filtered to account for variation associated with spontaneous breathing patterns, and then transformed to its natural logarithm to extract an estimate of RSA using CardioBatch software (Brain-Body Canter, 2007). The average RSA for the Arc of Toys free play task, averaged over 30 second epochs, was used for analyses.

Procedures

As a part of a larger longitudinal study conducted by the NDD Lab (PI: Roberts) examining children with FXS and their TD counterparts, participants were followed from infancy to early childhood with regular, annual assessments. At each visit, the participants underwent a battery of assessments administered to lab standards by trained research staff. For the current study, two time points were examined based on available data. Time point 1 (T1) included play behavior and heart activity data from the Arc of Toys task at 12 months of age as well as MSEL ELC scores at 12 months of age. Time point 2 (T2) included CBCL ADHDassociated attention and MSEL ELC scores at 60 months of age. If data for T2 was not available at the 60-month assessment, data from the next closest assessment (36, 48, or 72 months) was used. The Arc of Toys task was conducted by a trained examiner. The examiner began the task by placing the child in front of the toys and saying “Look at all these neat toys. You can play with them all by yourself however you want.”, while simultaneously turning over the rainmaker. The child was left to play with the toys for five minutes. If the child went off task or remained unengaged for an extended period of time, the examiner said, “Let’s play with these toys now” and turned over the rainmaker. The examiner was allowed to redirect the child a maximum of three times during the five-minute assessment. All data was collected in coordination with International Review Board (IRB) approval and Collaborative Institutional Training Initiative (CITI) training on ethics and responsible conduct.

 

Results

Analytic Approach

The statistical software SPSS 25 was used for all analyses. An analysis of variance (ANOVA) was used to ensure that the FXS and TD groups were chronologically age matched. Groups did not differ on chronological age between children with FXS and TD children at T1, F(1, 41) = 3.00, p = 0.772, or at T2, F(1,41) = 0.45, p = 0.505. There were significant differences in cognitive level at T1, F(1,41) = 55.85, p < 0.001, and T2, F(1,39) = 83.33, p < 0.001, and in ADHD-associated attention problems, F(1,41) = 34.53, p < 0.001, between males with FXS and TD males.

In order to evaluate question 1, an Analysis of Covariance (ANCOVA), with MSEL ELC scores as a covariate to account for the differences in cognitive ability, was performed to examine group differences in the total number of toy switches and the total number of novel toy switches. For question 2, a Pearson correlation was used to examine the relationship between play behavior at T1 and ADHD-associated attention problems at T2. Lastly, for question 3, a Pearson correlation was used to examine the relationship between heart activity (i.e., RSA) and ADHD-associated attention problems at T2.

Group Differences in Play Behavior. An ANCOVA was used to determine group differences in the total number of toy switches and the total number of novel toy switches between infants with FXS and TD infants. Developmental level was included as a covariate for both analyses. There were no significant differences in the total number of novel toy switches between infants with FXS and TD infants, F(1,40) = 0.40, p = 0.533 (see Table 1 for details). Secondly, there were no significant differences in the total number of toy switches between infants with FXS and TD infants, F(1,40) = 0.22, p = 0.63 (see Table 1 for details).

Correlation between Play Behavior and Attention Problems. A Pearson correlation was used to examine the relationship between play behavior at T1 and ADHD-associated attention problems at T2. There was not a significant relationship between the total number of novel toy switches and ADHD-associated attention problems in either children with FXS, r = - .32, p = .217, or TD children, r = .12, p = .557 (see Figure 1). Furthermore, there was not a significant relationship between the total number of toy switches and ADHD-associated attention problems in either children with FXS, r = -.28, p = .275, or TD children, r = -.15, p = .479 (see Figure 2).

Correlation between RSA and Attention Problems. A Pearson correlation was used to determine the relationship between heart activity at T1 and ADHD-associated attention problems at T2. There was not a significant relationship between RSA and ADHD-associated attention problems for children with FXS, r = -.32, p = .489, or TD children, r = -.28, p = .280 (see Figure 3).

 

Discussion

The present study sought to identify early indicators of ADHD symptoms, particularly inattention, in children with FXS by examining play behaviors and heart activity. In order to assess the research aims, toy interactions and heart activity data were examined to gain a better understanding of the external and internal emergence of hyperactivity, impulsivity, and inattention in infants with FXS. Toy interactions were quantified by the total number of toy switches and the total number of novel toy switches. Total toy switches indexed each time a child engaged and disengaged in play, regardless of toy, and novel toy switches indexed each new toy interaction. The differentiation sheds light on the possible external indicators of ADHD associated behaviors during free play. Data were collected at two time points, infancy (i.e., 12 months of age) and school age (i.e., 36, 48, 60, or 72 months of age, depending on available assessment data), in order to understand the relationship between play behavior and heart activity data and later ADHD-associated attention problems.

The results show that both groups, males with FXS and TD males, differed significantly in cognitive level and ADHD-associated attention problems, but not in chronological age. These findings confirm that the groups were appropriately age matched, yet the males with FXS exhibited more severe cognitive deficits compared to the TD group. The first hypothesis, there will be an increased number of total toy switches and a decreased number of novel toy switches in males with FXS compared to TD males at 12 months of age, was not supported. There were no significant differences in the total number of novel toy switches or the total number of toy switches during the Arc of Toys task between infants with FXS and TD infants. Nevertheless, infants with FXS interacted with a greater number of total toys but showed less diverse toy play, thus fewer novel toy switches, than TD infants at 12 months of age during the free play task. These interactions can also be described as repetitive because the child engaged with a limited set of toys multiple times. The findings are in accordance with other studies that emphasize play diversity is a more robust assessment of play behavior in developmentally delayed populations because it expresses flexible and varied play (Lifter et al., 2011; McDuffie et al., 2015; Thiemann-Bourque et al., 2012). Further studies should evaluate delayed development of play behaviors and whether developmentally delayed children even possess the prerequisite skill set to produce developmentally appropriate play behaviors (Kasari et al., 2013). The nonsignificant nuances in play behavior between the groups might suggest that at 12 months of age, infants have not yet gained the coordination and motor skills to exhibit full expressions of play behavior.

The second hypothesis, decreased number of both total and novel toy switches in male infants with FXS compared to TD males at 12 months of age will be correlated to later ADHD attention symptom severity, was also not supported. There was not a significant relationship between the total number of novel toy switches or the total number of toy switches and ADHDassociated attention problems in either children with FXS or TD children. However, children with ADHD engage in more frequent toy switches compared to their non-ADHD peers suggesting hyperactivity and inattentive behaviors influence play activity (Handen et al.,1998). While the results suggest differences between the groups, their nonsignificance might indicate that simply quantifying play interactions is not an adequate evaluation of ADHD inattention associated behaviors. Furthermore, ADHD subtype could not be controlled for, potentially leading to null findings. Future research should examine more comprehensive and robust measures of play behavior, such as functional play or emotional response to play, which may provide more insight into the emergence of ADHD-associated behaviors. Lastly, this study examined ADHD inattentive type problems on the CBCL assessment but examining combined ADHD or hyperactive-impulsive type ADHD might provide more insight into the external expressions of ADHD in children with FXS. Impulsivity, a core temperamental tenet of ADHD, is a stable predictor of ADHD in school-aged children and can lead to poor social functioning without intervention. Temperament emerges early and is relatively stable throughout childhood; therefore, examining hyperactivity or inattention may give more reliable insight into the early emergence of ADHD (Grefer et al., 2016).

The third hypothesis, decreased RSA values during a free play task in 12-month-old males with FXS will correlate to later ADHD attention symptom severity, was also not supported. There was not a significant relationship between RSA and ADHD inattention problems for children with FXS or TD children. The results did suggest, however, that the FXS group did have a lower mean RSA compared to the TD group during the free play task, but these differences were nonsignificant. The general findings follow evidence in other studies that children with FXS are characterized by a decreased vagal tone from decreased parasympathetic activity (Heilman et al., 2012; Roberts et al., 2000).

The autonomic dysregulation found in children with FXS contributes to decreased social functioning due to hyperactivity, reactivity, and defensive behaviors (Hall et al., 2009; Heilman et al., 2012; Roberts et al., 2000). Examining RSA during a neutral task is important in determining baseline autonomic function, and thus can be predictive of how these children might physiologically react in various situations. Parasympathetic activity in children with ADHD and FXS, separately, show interesting patterns. Children with ADHD in a neutral task condition, similar to the Arc of Toys free play task in the present study, exhibit greater RSA when compared to their TD counterparts (Tenenbaum et al., 2019). These findings are contradictory to other studies, which revealed that children with clinical and at-risk diagnoses of ADHD had significantly lower absolute levels of baseline RSA compared to their TD counterparts (Beauchaine et al., 2013; Beauchaine et al., 2001; Graziano & Derefinko, 2013; Morris et al., 2019). For children with FXS, studies show they have less vagal input, or decreased RSA, during a baseline state, meaning the child is physiologically ready to mobilize (Heilman et al., 2012; Roberts et al., 2000). Taken together, research from previous studies and the nonsignificant results from the present study illustrate an intricate and variable function of vagal tone (indexed by RSA) in both ADHD and FXS.

This study is one of the first to examine biobehavioral manifestations of ADHD in infants with FXS. Research has shown that early diagnosis of ADHD is important in the development of school-aged children (Tandon et al., 2011). In this study, neither play behaviors nor heart activity proved significant in correlating later ADHD-associated attention problems, suggesting that these measures in infants may not be predictive biomarkers of inattentive type ADHD in children with FXS. The largest limitation of this study is the small sample size. Larger sample sizes would provide more statistical power to better assess the project aims. Another limitation is the wide range of ages evaluated at T2, which may act as a confounding factor. If the age range at T2 was more restricted, but included more participants, there would be more power to assess the possible associations at hand. On the other hand, this study’s participant group was unique because the general population does not have access to varied and extensive data on a specific cohort. Future studies should also evaluate RSA withdrawal, the difference between RSA at baseline and during an emotion eliciting task, to assess dynamic parasympathetic nervous system function in children with FXS. Additionally, assessing children with FXS alongside children with other NDDs that exhibit ID, such as ASD, will help determine if the behaviors are due to the specific disorder or a general phenotype, such as global developmental delay, seen in NDDs. Lastly, when evaluating play behaviors, older participants might exhibit more informative and dynamic behaviors, and thus would be more appropriate when assessing attention problems. Studies have also shown younger children are still developing their ability to sustain attention over time, meaning that infants might not yet have the attentional skills needed to determine attention associated problems (Egger & Angold, 2006). 

 

About the Author

Hannah Pressler Hannah Pressler

 

References

Achenbach, T. M., & Rescorla, L. (2001). Manual for the ASEBA school-age forms & profiles: An integrated system of multi-informant assessment.

Aseba. Akshoomoff, N. (2006). Use of the Mullen Scales of Early Learning for the assessment of young children with Autism Spectrum Disorders. Child Neuropsychology, 12(4–5), 269–277. https://doi.org/10.1080/09297040500473714

Alanay, Y., Ünal, F., Turanlı, G., Alikaşifoğlu, M., Alehan, D., Akyol, U., Belgin, E., Şener, C., Aktaş, D., Boduroğlu, K., Utine, E., Volkan-Salanci, B., Özusta, Ş., Genç, A., Başar, F., Sevinç, Ş., & Tunçbilek, E. (2007). A multidisciplinary approach to the management of individuals with fragile X syndrome. Journal of Intellectual Disability Research, 51(2), 151–161. https://doi.org/10.1111/j.1365-2788.2006.00942.x

American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders (Fifth Edit). Washington, DC: American Psychiatric Association.

Bailey, D. B., Raspa, M., Olmsted, M., & Holiday, D. B. (2008). Co-occurring conditions associated with FMR1 gene variations: Findings from a national parent survey. American Journal of Medical Genetics, Part A, 146(16), 2060–2069. https://doi.org/10.1002/ajmg.a.32439

Barkley, R. A. (2003). Child Psychopathology. (E. J. Mash & R. A. Barkley, Eds.) (Second Edi). New York, NY: Guilford Press.

Beauchaine, T. P., Gatzke-Kopp, L., Neuhaus, E., Chipman, J., Reid, M. J., & Webster-Stratton, C. (2013). Sympathetic- and parasympathetic-linked cardiac function and prediction of externalizing behavior, emotion regulation, and prosocial behavior among preschoolers treated for ADHD. Journal of Consulting and Clinical Psychology, 81(3), 481–493. 19 https://doi.org/10.1037/a0032302

Beauchaine, T. P., Katkin, E. S., Strassberg, Z., & Snarr, J. (2001). Disinhibitory psychopathology in male adolescents: discriminating conduct disorder from attentiondeficit/ hyperactivity disorder through concurrent assessment of multiple autonomic states. Journal of Abnormal Psychology, 110(4), 610–624. https://doi.org/10.1037//0021- 843x.110.4.610

Belsky, J., & Most, R. K. (1981). From exploration to play: A cross-sectional study of infant free play behavior. Developmental Psychology, 17(5), 630–639. https://doi.org/10.1037/0012- 1649.17.5.630 Brain-Body Canter. (2007). CardioEdit/CardioBatch [Computer software]. Chicago, IL: University of Illinois.

Chromik, L. C., Quintin, E.-M., Lepage, J.-F., Hustyi, K. M., Lightbody, A. A., & Reiss, A. L. (2015). The influence of hyperactivity, impulsivity, and attention problems on social functioning in adolescents and young adults with fragile X syndrome. Journal of Attention Disorders. https://doi.org/10.1177/1087054715571739

Chronis-Tuscano, A., Lewis-Morrarty, E., Woods, K. E., O’brien, K. A., Mazursky-Horowitz, H., & Thomas, S. R. (2014). Parent-Child Interaction Therapy With Emotion Coaching for Preschoolers With Attention-Deficit/Hyperactivity Disorder. Retrieved from www.elsevier.com/locate/cabp

Crawford, D. C., Acuña, J. M., Sherman, S. L., & Med, G. (2001). FMR1 and the Fragile X Syndrome: Human Genome Epidemiology Review HHS Public Access Author manuscript. Genet Med (Vol. 3). Retrieved from https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC4493892&blobtype=pdf 20

Danielson, M. L., Bitsko, R. H., Ghandour, R. M., Holbrook, J. R., Kogan, M. D., Health Bureau, C., & Blumberg, S. J. (2018). Prevalence of parent-reported ADHD diagnosis and associated treatment among U.S. children and adolescents, 2016 HHS Public Access. Journal of Clinical Child and Adolescent Psychology, 47(2), 199–212. https://doi.org/10.1080/15374416.2017.1417860

Dougherty, L. R., Bufferd, S. J., Carlson, G. A., Dyson, M., Olino, T. M., Emily Durbin, C., & Klein, D. N. (2011). Preschoolers’ observed temperament and psychiatric disorders assessed with a parent diagnostic interview. Journal of Clinical Child and Adolescent Psychology, 40(2), 295–306. https://doi.org/10.1080/15374416.2011.546046

Dyson, M. W., Olino, T. M., Durbin, C. E., Goldsmith, H. H., Bufferd, S. J., Miller, A. R., & Klein, D. N. (2015). The structural and rank-order stability of temperament in young children based on a laboratory-observational measure HHS Public Access. Psychological Assessment, 27(4), 1388–1401. https://doi.org/10.1037/pas0000104

Dyson, M. W., Olino, T. M., Durbin, C. E., Goldsmith, H. H., & Klein, D. N. (2011). The structure of temperament in preschoolers: A two-stage factor analytic approach. https://doi.org/10.1037/a0025023

Egger, H., & Angold, A. (2006). Common emotional and behavioral disorders in preschool children: presentation, nosology, and epidemiology. Journal of Child Psychology and Psychiatry, 313–337. https://doi.org/10.1111/j.1469-7610.2006.01618.x

Goldsmith, H. H., Reilly, J., Lemery, K. S., Longley, S., & Prescott, A. (1999). The Laboratory Temperament Assessment Battery: Preschool Version Description of Procedures. Goldsmith, H. H., & Rothbart, M. K. (1999). The Laboratory Temperament Assessment Battery (LAB-TAB): Locomotor Version 3.1. 21

Graziano, P., & Derefinko, K. (2013, September). Cardiac vagal control and children’s adaptive functioning: A meta-analysis. Biological Psychology. NIH Public Access. https://doi.org/10.1016/j.biopsycho.2013.04.011

Grefer, M., Flory, K., Cornish, K., Hatton, D., & Roberts, J. (2016). The emergence and stability of attention deficit hyperactivity disorder in boys with fragile X syndrome. Journal of Intellectual Disability Research, 60(2), 167–178. https://doi.org/10.1111/jir.12226

Hall, S. S., Lightbody, A. A., Huffman, L. C., Lazzeroni, L. C., & Reiss, A. L. (2009). Physiological correlates of social avoidance behavior in children and adolescents with fragile X syndrome. Journal of the American Academy of Child & Adolescent Psychiatry, 48(3), 320–329. https://doi.org/10.1097/CHI.0b013e318195bd15

Handen, B. L., McAuliffe, S., Janosky, J., Feldman, H., & Breaux, A. M. (1998). A playroom observation procedure to assess children with mental retardation and ADHD. Journal of Abnormal Child Psychology, 26(4), 269–277.

Heilman, K. J., Harden, E. R., Zageris, D. M., Berry-Kravis, E., & Porges, S. W. (2012). Autonomic regulation in fragile X syndrome. Developmental Psychobiology, 53(8), 785– 795. https://doi.org/10.1002/dev.20551

Hermens, D. F., Williams, L. M., Lazzaro, I., Whitmont, S., Melkonian, D., & Gordon, E. (2004). Sex differences in adult ADHD: a double dissociation in brain activity and autonomic arousal. Biological Psychology, 66, 221–233. https://doi.org/10.1016/j.biopsycho.2003.10.006

Kasari, C., Chang, Y.-C., & Patterson, S. (2013). Pretending to Play or Playing to Pretend: The Case of Autism Autism Speaks. Am J Play (Vol. 6).

Kuo, T. B. J., Lin, T., Yang, C. C. H., Li, C. L., Chen, C. F., & Chou, P. (1999). Effect of aging 22 on gender differences in neural control of heart rate. American Journal of Physiology - Heart and Circulatory Physiology, 277(6 46-6). https://doi.org/10.1152/ajpheart.1999.277.6.h2233

Lange, A.-M., Daley, D., Frydenberg, M., Rask, C. U., Sonuga-Barke, E., & Thomsen, P. H. (2016). The effectiveness of parent training as a treatment for preschool attentiondeficit/ hyperactivity disorder: study protocol for a randomized controlled, multicenter trial of the new forest parenting program in everyday clinical practice. JMIR Research Protocols, 5(2), e51. https://doi.org/10.2196/resprot.5319

Lifter, K., Foster-Sanda, S., Arzamarski, C., Briesch, J., & McClure, E. (2011). Overview of Play: Its uses and importance in early intervention/early childhood special education. Infants & Young Children, 24(3), 225–245. https://doi.org/10.1097/IYC.0b013e31821e995c Mazzocco, M. M. (2000). Advances in research on the fragile X syndrome. Mental Retardation and Developmental Disabilities Research Reviews, 6(2), 96–106. https://doi.org/10.1002/1098-2779(2000)6:2<96::AID-MRDD3>3.0.CO;2-H

McDuffie, A., Oakes, A., Machalicek, W., Thurman, A., Summers, S., Stewart, A., & Abbeduto, L. (2015). Play with objects in young males with fragile X syndrome: A preliminary study. Journal of Communication Disorders, 53, 17–29. https://doi.org/10.1016/j.jcomdis.2014.10.002

McQuade, J. D., & Breaux, R. P. (2017). Are elevations in ADHD symptoms associated with physiological reactivity and emotion dysregulation in children? Journal of Abnormal Child Psychology, 45(6), 1091–1103. https://doi.org/10.1007/s10802-016-0227-8

Milich, R., & Landau, S. (1982). Socialization and peer relations in hyperactive children. Advances in Learning & Behavioral Disabilities, 1, 283–339. Retrieved from 23 http://web.b.ebscohost.com.pallas2.tcl.sc.edu/ehost/detail/detail?vid=13&sid=7056aa7c- 0604-40a6-8c01-0db65509c07d%40pdc-vsessmgr04& bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3D%3D#AN=1983-06002- 001&db=psyh

Morris, S. S. J., Musser, E. D., Tenenbaum, R. B., Ward, A. R., Martinez, J., Raiker, J. S., … Riopelle, C. (2019). Emotion Regulation via the autonomic nervous system in children with attention-deficit/hyperactivity disorder (ADHD): Replication and extension. Journal of Abnormal Child Psychology, 48, 361–373. https://doi.org/10.1007/s10802-019-00593-8

Mullen, E. (1995). Mullen Scales of Early Learning. Circle Pines, NM: American Guidance Service.

Pelham, W. E., & Bender, M. E. (1982). Peer relationships in hyperactive children: Description and treatment. Advances in Learning & Behavioral Disabilities, 1, 365–436. Retrieved from http://web.b.ebscohost.com.pallas2.tcl.sc.edu/ehost/detail/detail?vid=11&sid=7056aa7c- 0604-40a6-8c01-0db65509c07d%40pdc-vsessmgr04& bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3D%3D#AN=1983-06085- 001&db=psyh

Pierce-Jordan, S., & Lifter, K. (2005). Interaction of social and play behaviors in preschoolers with and without pervasive developmental disorder. Topics in Early Childhood Special Education, 25(1), 34–47. https://doi.org/10.1177/02711214050250010401

Porges, S. W., Doussard-Roosevelt, J. A., & Maiti, A. K. (1994). Vagal tone and the physiological regulation of emotion. Monographs of the Society for Research in Child Development, 59(2/3), 167. https://doi.org/10.2307/1166144

Roberts, J. E., Boccia, M. L., Bailey, D. B., & Skinner, M. (2000). Cardiovascular indices of 24 physiological arousal in boys with fragile x syndrome. Developmental Psychobiology, 39, 107–123.

Roberts, J. E., Hatton, D. D., & Bailey, D. B. (2001). Development and behavior of male toddlers with fragile X syndrome. Journal of Early Intervention, 24(3), 207–223. https://doi.org/10.1177/10538151010240030601

Roberts, J. E., Tonnsen, B., Robinson, A., & Shinkareva, S. V. (2012). Heart activity and autistic behavior in infants and toddlers with fragile X syndrome. American Journal on Intellectual and Developmental Disabilities, 117(2), 90–102. https://doi.org/10.1352/1944-7558- 117.2.90

Roberts, Jane E, Bradshaw, J., Will, E., Hogan, A., McQuillin, S., & Hills, K. (2020). Emergence and rate of autism in fragile X syndrome across the first years of life. Development and Psychopathology, 32(4), 1335–1352. https://doi.org/10.1017/S0954579420000942

Smith, L. E., Barker, E. T., Seltzer, M. M., Abbeduto, L., & Greenberg, J. S. (2012). Behavioral phenotype of fragile X syndrome in adolescence and adulthood. American Journal on Intellectual and Developmental Disabilities, 117(1), 1–17. https://doi.org/10.1352/1944- 7558-117.1.1

Sullivan, K., Hatton, D., Hammer, J., Sideris, J., Hooper, S., Ornstein, P., & Bailey, D. (2006). ADHD symptoms in children with FXS. American Journal of Medical Genetics, Part A, 140(21), 2275–2288. https://doi.org/10.1002/ajmg.a.31388

Sutton-Smith, B. (1997). The Ambiguity of Play. Harvard University Press. Cambridge, MA: Harvard University Press. Retrieved from https://books.google.com/books?hl=en&lr=&id=AgA8q0TCKeIC&oi=fnd&pg=PR5&ots= Cpe3B0x2bX&sig=r3W4wzHceyvJP9-OetcD6eKFqrY#v=onepage&q&f=false 25

Tandon, M., Si, X., & Luby, J. (2011). Preschool onset attention-deficit/hyperactivity disorder: Course and predictors of stability over 24 months. Journal of Child and Adolescent Psychopharmacology, 21(4), 321–330. https://doi.org/10.1089/cap.2010.0045

Tenenbaum, R. B., Musser, E. D., Morris, S., Ward, A. R., Raiker, J. S., Coles, E. K., & Pelham, W. E. (2019). Response inhibition, response execution, and emotion regulation among children with attention-deficit/hyperactivity disorder. Journal of Abnormal Child Psychology, 47(4), 589–603. https://doi.org/10.1007/s10802-018-0466-y

Thiemann-Bourque, K. S., Brady, N. C., & Fleming, K. K. (2012). Symbolic play of preschoolers with severe communication impairments with autism and other developmental delays: More similarities than differences. Journal of Autism and Developmental Disorders, 42(5), 863–873. https://doi.org/10.1007/s10803-011-1317-7

Ungerer, J. A., & Sigman, M. (1984). The relation of play and sensorimotor behavior to language in the second year. Child Development, 55(4), 1448–1455. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/6207995

van der Veen-Mulders, L., Nauta, M. H., Timmerman, M. E., van den Hoofdakker, B. J., & Hoekstra, P. J. (2017). Predictors of discrepancies between fathers and mothers in rating behaviors of preschool children with and without ADHD. European Child and Adolescent Psychiatry, 26(3), 365–376. https://doi.org/10.1007/s00787-016-0897-3

Wang, T. S., Huang, W. L., Kuo, T. B. J., Lee, G. S., & Yang, C. C. H. (2013). Inattentive and hyperactive preschool-age boys have lower sympathetic and higher parasympathetic activity. Journal of Physiological Sciences, 63(2), 87–94. https://doi.org/10.1007/s12576- 012-0238-3

Warnick, E. M., Bracken, M. B., & Kasl, S. (2008). Screening efficiency of the Child Behavior 26 Checklist and Strengths and Difficulties Questionnaire: A systematic review. Child and Adolescent Mental Health, 13(3), 140–147. https://doi.org/10.1111/j.1475- 3588.2007.00461.x


Challenge the conventional. Create the exceptional. No Limits.

©