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. Author manuscript; available in PMC: 2016 Feb 9.
Published in final edited form as: Neuropsychology. 2013 Jan;27(1):13–18. doi: 10.1037/a0031299

Impairments in Real World Executive Function Increase from Childhood to Adolescence in Autism Spectrum Disorders

Michael Rosenthal 1, Gregory L Wallace 2, Rachel Lawson 3, Meagan C Wills 1, Eunice Dixon 2, Benjamin E Yerys 1,4, Lauren Kenworthy 1
PMCID: PMC4747021  NIHMSID: NIHMS725337  PMID: 23356593

Abstract

Objective

While several studies have investigated developmental trajectories of executive functioning (EF) in autism spectrum disorders (ASD) using lab-based tasks, no study to date has directly measured how EF skills in everyday settings vary at different ages. The current study seeks to extend prior work by evaluating age-related differences in parent reported EF problems during childhood and adolescence in a large cross-sectional cohort of children with ASD.

Methods

185 children with an ASD without intellectual disability participated in the study. Subjects were divided into four groups based on age (5–7; 8–10; 11–13; and 14–18 year olds). The four age groups did not differ in IQ, sex ratio, or autism symptoms.

Results

There were significant age effects (i.e., worsening scores with increasing age) in three BRIEF scale scores: Initiate (p=.007), Working Memory (p=.003), and Organization of Materials (p=.023). In addition, analysis of the BRIEF scale profile revealed that, although multiple scales were elevated, the Shift scale showed the greatest problems in both the youngest and oldest age cohorts.

Conclusions

Older children with ASD show greater EF problems compared to the normative sample than younger children with ASD. Specifically, there is a widening divergence from the normative sample in metacognitive executive abilities in children with ASD as they age. This, in combination with significant, albeit more stable, impairments in flexibility, has implications for the challenges faced by high functioning individuals with ASD as they attempt to enter mainstream work and social environments.

Keywords: Autism, Executive Function, BRIEF, Development, Age-related

Introduction

Executive dysfunction is frequently associated with autism spectrum disorders (ASDs; for review, see: Hill, 2004; Kenworthy, Yerys, Anthony, & Wallace, 2008) and has been linked to reduced adaptive functioning (Gilotty, Kenworthy, Sirian, Black, & Wagner, 2002) and greater autism symptoms in ASD (Yerys et al., 2009; Kenworthy, Black, Harrison, Della Rosa, & Wallace, 2009). Executive dysfunction in children with ASDs is not universal, and there is evidence that executive function (EF) impairments occur in older children with ASD but not younger ones (e.g., Hill, 2004; Yerys, Hepburn, Pennington, & Rogers, 2007). This literature is difficult to interpret however, because EF is a complex construct, with multiple processes that mature at different times in typical children and have not been consistently measured across ASD studies (Kenworthy et al., 2008).

The maturation of EF during typical development follows a protracted course, which varies by the process under scrutiny and level of complexity of the task. For example, a recent review by Best and Miller (2010) argues that the ability to control or prevent an automatic behavioral response (i.e., inhibition) develops earlier than other executive processes in typically-developing children. Specifically, inhibition improves rapidly during early childhood (e.g., Gerstadt, Hong, & Diamond, 1994) followed by slower improvements through adolescence (Best & Miller, 2010). In contrast, maintaining information in mind in the face of interference (i.e., working memory) appears to improve in a more linear, gradual fashion from preschool through childhood and adolescence (e.g., Conklin, Luciana, Hooper, & Yarger, 2007). The ability to shift between task sets (i.e., flexibility) also follows a more protracted developmental course, with successful switching on complex tasks occurring by middle adolescence (e.g., Huizinga, Dolan, & van der Molen, 2006). In reviewing this literature, Best and Miller note the importance of measuring multiple EF processes across development in order to capture the emergence of these interdependent, but distinguishable abilities. They also emphasize that future studies should distinguish EF development beyond the preschool years, and that the complexity of tasks tapping specific executive processes is a key factor in determining the age at which a task is mastered. Furthermore, self-monitoring, inferencing, error detection, and integration of multiple functions all make a particular EF task “higher-level” and extend age of mastery into early adulthood (O’Hearn, Asato, Ordaz, & Luna, 2008).

Most of the studies cited above rely on highly-controlled lab-based tasks to determine EF development. Huizinga and Smidts (2011) augmented this data by examining age-related EF differences in a large normative sample using the Behavior Rating Inventory of Executive Function (BRIEF; Gioia, Isquith, Guy, & Kenworthy, 2000), an informant report questionnaire developed to identify everyday EF abilities in children aged 5–18 years. The BRIEF measures two broad areas of EF: behavioral regulation, the ability to shift, and modulate emotions and behavior via appropriate inhibitory control; and metacognition, the ability to cognitively self-manage tasks and monitor performance. Parent-reported EF problems generally decreased with increasing age in typically-developing children, with much of these differences driven by behavioral regulation rather than metacognitive processes. Specifically, 5–8 year olds showed significantly more problems than 9–11 year olds in emotional control, inhibition, shifting, and working memory, and 12–14 year olds were more impaired than their 15–18 year old counterparts on scales of inhibition and emotional control. These findings may appear to contradict those of Best and Miller (2010) (i.e., improvement in metacognitive skills, such as working memory, with increasing age), however, unlike lab tasks, the BRIEF measures parent-report of problem behavior in the context of everyday demands. In other words, limited raw score change on the BRIEF over time reflects an individual’s ability to keep pace with real-world behavioral expectations. Everyday metacognitive demands for organization, planning and working memory increase dramatically as children become adolescents and enter secondary school settings with multiple teachers, longer term assignments, and more cumulative testing. Thus, these findings can be understood as complementing those of lab-based studies, and reflecting how typically-developing children successfully adapt to increased EF demands in their environment.

Understanding the trajectory of EF development in ASD can offer insight into the dynamic nature of the disorder and inform treatment options. Additionally, it can inform research findings of abnormal neuroanatomical growth across childhood (e.g., Courchesne, Campbell, & Solso, 2011; Wallace, Dankner, Kenworthy, Giedd, & Martin, 2010) and its relation to EF in ASD. Moreover, exploration of developmental trajectories of EF in ASD could be helpful in reconciling apparently contradictory findings of impaired and preserved EF functioning stemming from studies of children of different ages.

In a comprehensive review of EF development in school-aged children with ASD, O’Hearn and colleagues (2008) suggested overall age-related improvement on lab-based measures, yet an inability to attain normal performance levels. Similarly, Luna and colleagues (2007) found that in school-aged children with ASD, inhibition and working memory skills improved over time yet were slower to mature and lagged behind skills in same-age typical peers. Several studies of school-aged children, both cross-sectional (Happé, Booth, Charlton, & Hughes, 2006) and longitudinal (Pellicano, 2010) have also suggested age-related gains in EF skills, while others have reported no improvement (Ozonoff & McEvoy, 1994). In general, the literature supports the notion that EF skills improve through childhood and adolescence in ASDs, but they mature at a slower pace and often remain impaired into adulthood.

The aforementioned studies rely on lab-based measures of EF. It is useful to supplement these findings with data collected on everyday EF measures, such as the BRIEF. The BRIEF offers the further advantage of sampling multiple EF processes (inhibition, shifting, emotional control, initiation, working memory, planning and organization, organization of materials, self-monitoring) across a wide age range (5–18 years of age). The purpose of the current investigation is to extend prior studies by evaluating age-related differences in everyday EF during childhood and adolescence in a large ASD cohort. While some prior research using lab-based tasks reports modest EF improvements in ASD during school-age, the greatly increased real-world expectations for EF skills in older adolescents versus young children may create a greater divergence in the severity of parent-reported EF problems between children with ASD and their peers as they progress through adolescence. We therefore hypothesize that children with ASD will show greater EF impairments across age compared to normative samples as indicated by increasing scores (which indicate greater problems) on the BRIEF scales with age.

Methods

Participants

A total of 185 children with an ASD participated in the study. The study received institutional ethics approval from the Institutional Review Board of Children’s National Medical Center, and written informed consent was obtained from all participants. Children were recruited through a hospital clinic in Maryland specializing in ASD and neuropsychological assessment. All individuals were diagnosed by trained, experienced, research reliable clinicians (i.e., ADOS kappa ≥ .80) with a high-functioning ASD using DSM-IV criteria (APA, 2000) and qualified for a “broad ASD” on the Autism Diagnostic Interview/Autism Diagnostic Interview-Revised (ADI/ADI-R; Le Couteur et al., 1989; Lord, Rutter, & Le Couteur, 1994) and/or the Autism Diagnostic Observation Schedule (ADOS; Lord et al., 2000) following the criteria established by the NICHD/NIDCD Collaborative Programs for Excellence in Autism (Lainhart et al., 2006). The “broad ASD” criteria included meeting the ADI-R cutoff for autism in the social domain and at least one other domain or meeting the ADOS ASD cutoff for the combined social and communication score. All but 18 participants had a FSIQ ≥70; IQ for the remaining 18 participants was estimated from a Verbal IQ composite score. IQ was measured by the: Wechsler Intelligence Scale for Children, 3rd Edition (n=2) or 4th Edition (n=59), Wechsler Abbreviated Scale of Intelligence (n=114), Differential Abilities Scale, 2nd Edition (n=5), Wechsler Adult Intelligence Scale, 3rd Edition (n=3), or the Wechsler Preschool and Primary Scales of Intelligence, 3rd Edition (n=2). We excluded participants if they had any reported history of co-morbid genetic or neurological disorders (e.g., Fragile X syndrome, Tourette’s syndrome). Diagnostic and neurobehavioral data were sometimes collected at different time points; therefore, those children who had more than two years between data collection points were excluded from the study.

Participants were divided into four groups based on age (5–7; 8–10; 11–13; 14–18 year olds), consistent with the age subdivisions described in the BRIEF normative sample (Gioia, Isquith, Guy, & Kenworthy, 2000). The number of participants at each age was as follows: 5 years=6, 6 years=10, 7 years=18, 8 years=31, 9 years=19, 10 years=15, 11 years=15, 12 years=18, 13 years=17, 14 years=8, 15 years=9, 16 years=9, 17 years=4, 18 years=6. Analyses confirmed that these age groups did not differ in our sample in terms of socio-economic status (SES), sex ratio, or IQ. Furthermore, to ensure that ASD symptoms were not different across the age groups and therefore would not impact any age-related effects in EF, we divided subjects into three categories based on their ADOS scores: mild ASD (defined as children who met clinical DSM-IV criteria for an ASD and the ADI cut-off for Autism, but the ADOS Social + Communication score was below the ASD cut-off), ASD (defined as children who met clinical DSM-IV and ADOS cut-offs for an ASD and the ADI cut-off for Autism), and Autism (defined as children who met DSM-IV criteria for an ASD, and ADI and ADOS cut-offs for Autism). Comparison of the ratio of diagnostic categories between the four different age bins revealed no significant differences. See Table 1 for complete demographic information.

Table 1.

Participant Demographics by Age Group.

Total Sample

(n=185)		 5–7
Years
(n=34)		 8–10
Years
(n=65)		 11–13
Years
(n=50)		 14–18
Years
(n=36)		 F/Chi-
square		 p
Sex (%M %F) 83%M 17%F 85%M 15%F 85%M 15%F 76%M 24%F 86%M 14%F 2.19a .534
SES Mean** 1.89 1.91 1.93 1.94 1.74 8.9 .712
Full Scale IQ Mean (SD) 105.75 (18.91) 100.35 (16.45) 106.42 (20.55) 109.38 (19.07) 104.58 (17.16) 1.63b .185
ADOS Classification (Mild ASD/ASD/AD)* 25/40/116 9/9/16 8/15/42 5/8/35 3/8/23 7.88a .247
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*

See Methods for explanation of ADOS Classifications; 6 children are not categorized due to insufficient ADOS data

**

Mother’s occupational level used to estimate socio-economic status (SES). Values are as follows: 1=Graduate degree; 2=College graduate; 3=Partial college; 4=High school plus technical school 5=High school

a

Chi-square

b

F-value

ADOS=Autism Diagnostic Observation Schedule; ASD=Autism Spectrum Disorder; AD=Autistic Disorder

Measures

The ADI/ADI-R (Le Couteur et al., 1989; Lord et al., 1994) is a detailed parent/primary caregiver interview of developmental history/autism symptoms. Scores are aggregated into symptom clusters that correspond to DSM-IV criteria for a diagnosis of autism. The ADOS (Lord et al., 2000) is a structured play and conversational interview that includes a series of social presses and other opportunities to elicit symptoms of an ASD.

The parent form of the BRIEF (Gioia, Isquith, Guy, & Kenworthy, 2000) assesses EF in everyday situations and is comprised of eight scales (Initiate, Emotional Control, Shift, Inhibit, Organize/Plan, Organization of Materials, Working Memory, Monitor) which are collapsed into two broad indices: the Behavioral Regulation Index (BRI) and the Metacognition Index (MCI). Results are reported as T-scores. Higher scores indicate greater impairment; T-scores ≥65 (i.e., 1.5+ SDs above the mean) indicate clinically significant ratings. Dependent variables were the eight scales.

Results

Inspection of BRIEF variables revealed a total of nine outliers (i.e., scores beyond 2.5 SDs of the mean of the constituent age group), which were adjusted by moving the outlier score to 2.5 SDs beyond the age group mean and adding one T-score point. None of the BRIEF data presented with significant kurtosis or skew after adjustment of T-scores. A series of eight one-sample t-tests confirmed that mean scale values for the ASD group as a whole were significantly elevated on all scales relative to the normative sample (ts>9.14, ps <.001). A mixed-model ANOVA with age group as the between subjects factor and BRIEF scale as the within subjects factor revealed a main effect for scale (F(1,181)=34.33, p<.001, η2p =.16) and an interaction between scale and age group (F(3,181)=1.82, p=.022, η2p =.03) (see Table 2), but no significant main effect of age group (F(3,181)=2.20, p=.09, η2p =.03). Subsequent one-way ANOVAs revealed age effects for the following scales: Initiate (F(3,181)=4.21, p=.007, η2p =.06), Working Memory (F(3,181)=4.88, p=.003, η2p =.07), and Organization of Materials (F(3,181)=3.25, p=.023, η2p =.05). Post-hoc analyses revealed significantly higher (more impaired) Initiate (Tukey’s corrected p=.003) and Working Memory (Tukey’s corrected p=.001) scale scores in the 14–18 year olds compared to the 5–7 year olds. Finally, repeated measures ANOVAs (with BRIEF scale as the within subjects factor) were run in order to identify the BRIEF scales showing the greatest EF problems in the youngest and oldest groups (since those were the groups driving the age by BRIEF scale interaction). Significant within-group BRIEF scale score differences (F(1,33)=4.97, p=.001, η2p =.13 and F(1,35)=11.52, p<.001, η2p =.25, respectively) were found in both groups. In the youngest group, the Shift scale was the highest T-score and was significantly higher than three of the other scales. The Monitor scale was also significantly higher than three other scales. In the oldest group, the Shift scale was significantly higher than six other scales whereas the next highest T-score (Working Memory) was significantly higher than five other scales. Exploration of possible IQ score influences on age-related differences in the BRIEF revealed that the findings from the ANOVAs presented above were not altered after adding IQ as a covariate.

Table 2.

Age Group Differences in BRIEF Scale Scores.

BRIEF Scalesa Total 5–7 Years 8–10 Years 11–13 Years 14–18 Years F-value p Post-hoc
Testingb
(n=185) (n=34) (n=65) (n=50) (n=36)
Behavioral Regulation Index 66.48 (12.15) 64.24 (10.84) 66.20 (10.74) 67.68 (14.16) 67.42 (12.86) -- -- --
  Emotional 61.42 (12.06) 59.47 (11.34) 61.63 (10.58) 62.94 (14.35) 60.75 (11.94) .60 .615 ns
  Inhibit 63.63 (12.59) 63.35 (11.10) 62.77 (11.66) 64.54 (12.43) 64.19 (15.77) .22 .886 ns
  Shift 69.38 (12.93) 66.06 (13.59) 69.37 (12.34) 68.74 (13.61) 73.44 (11.76) 2.00 .115 ns
Metacognition Index 66.34 (11.15) 62.59 (12.16) 66.20 (10.74) 65.88 (10.84) 69.36 (9.31) -- -- --
  Initiate 64.21 (11.50) 59.65 (11.05) 64.11 (11.51) 63.90 (11.56) 69.14 (10.25) 4.21 .007* 14–18>5–7
  Working Memory 67.33 (11.61) 62.47 (12.27) 67.35 (10.17) 66.74 (11.60) 72.69 (11.69) 4.88 .003* 14–18>5–7
  Planning and Organization 64.86 (12.05) 62.62 (14.03) 64.77 (12.86) 64.44 (11.04) 67.72 (9.50) 1.09 .353 ns
  Organization of Materials 57.49 (11.14) 54.32 (11.96) 59.69 (10.61) 55.04 (11.18) 59.92 (10.16) 3.25 .023* ns
  Monitor 65.56 (11.29) 63.74 (11.91) 64.60 (11.08) 66.8 (12.13) 67.31 (9.77) .94 .423 ns
Global Executive Composite 67.74 (11.07) 64.41 (10.52) 67.85 (11.05) 67.84 (12.04) 70.56 (9.71) -- -- --
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a

All scores reported as T-scores; Mean=50; SD=10; T-scores ≥65 are considered clinically significant

b

Tukey’s

Discussion

This is the first study to evaluate age-related differences in everyday EF in a large group of children with ASD. Findings generally confirmed the hypothesis that children with ASD show increasing EF impairments with age, compared to the normative sample. Specifically, parents of older children with ASD reported more severe problems on several of the Metacognitive scales of the BRIEF. These age-related findings in EF were not due to differences in IQ, sex ratio, or autism symptomatology as the four age groups were matched on these variables. Additionally, all analyses survived IQ covariation, and were generally of medium effect size. Although some (e.g., Dennis et al, 2009) argue that covarying IQ can remove variance relevant to the experimental question, in this case it did not change the findings.

The current finding of increased parent-reported problems with metacognitive abilities in older children and adolescents with ASD is in contrast to a report of general improvement in everyday EF in typically-developing children (Huizinga & Smidts, 2011). Specifically, parents of older children with ASD report greater problems compared to the normative sample in the domains of self- and task-initiation, working memory, and organization of materials. Our findings are consistent with the results of Luna and colleagues (2007; 2008) of slower-to-mature working memory and EF skills in ASD on laboratory measures; unlike their typically-developing peers, metacognitive abilities in ASD may not be improving rapidly enough in late childhood and adolescence to keep pace with increased environmental demands. This pattern confirms what is often observed clinically: the gap between environmental expectations and the actual ability of a child with ASD to follow multi-step directions, keep school materials organized, and be a “self-starter” widens over time.

Although the Shift scale score does not significantly change across the four age groups we investigated, it is the peak area of weakness in both the youngest and oldest age groups. Moreover, not only is the Shift scale the highest mean score in the total sample, but it is also the only mean score that is consistently above the clinical cut-off of T=65 across all of the age groups. This converges with EF studies of ASD using lab-based measures of flexibility, such as the Wisconsin Card Sorting Test and the Intradimensional/Extradimensional Shift Test (e.g., Geurts, Verté, Oosterlaan, Roeyers, & Sergeant, 2004; Lopez, Lincoln, Ozonoff, & Lai, 2005; Yerys et al., 2009).

To our knowledge, the present study is the largest to date to evaluate EF development in ASD, but it examines cross-sectional age effects, rather than using a more powerful longitudinal design. It also relies on standardized scores rather than raw data and it lacks a control group, which limits interpretation of findings to relative differences compared to typically developing children. Future areas for study include longitudinal analyses of raw EF data, which could address questions about whether EF abilities of children with ASD are progressing slowly, not progressing at all, or worsening. Another potential limitation of using T-scores rather than raw data is the presence of artificial basal or ceiling effects. Analysis of the BRIEF psychometric properties confirmed no ceiling or basal effects influencing findings; however, relatively lower scores on the Organization of Materials scale may reflect the limited range of scores one can achieve in this scale (Gioia et al., 2000). We also excluded children with intellectual disability from the study, and therefore findings may not generalize to the entire ASD population. In addition, IQ estimates were drawn from different assessment tools which may not be entirely comparable. Despite being the largest study to date assessing EF development, replication using larger samples especially in the youngest and oldest groups would strengthen the findings. Finally, this study lacks lab-based measures and other informant report (i.e., teacher), which would complement the parent-report of EF skills.

Conclusion

This study examined age-related differences in everyday EF within a large sample of children and adolescents with ASD utilizing a parent rating measure. Findings support previous literature that EF (particularly metacognitive abilities) in ASD matures at a slower rate than it does in typically-developing children and thus shows greater divergence from normative samples with increasing age. While flexibility remains particularly impaired across ages in ASDs, working memory, initiation and organization, become increasingly problematic over time by parent report. The implications of these findings for people with ASD emphasize the need for continuing EF intervention and support throughout later adolescence, a time when school and clinical resources may not be as readily available.

Acknowledgements

We would like to thank the families of the participants and the diagnostic team that characterized the participants for their efforts over the years. This research was supported by the Intramural Research Program of the NIH, National Institute of Mental Health. BEY was supported by the National Institute of Mental Health 5K23MH86111. LK was supported by the Isadore and Bertha Gudelsky Foundation.

Footnotes

Conflicts of Interest

Lauren Kenworthy receives financial compensation for use of the BRIEF. The other authors have no conflicts of interest.

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