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Cited by 126Attention Deficit Hyperactivity DisorderDevelopmental and Educational NeuropsychologyAutism Spectrum Disorder Research

Data‐driven identification of subtypes of executive function across typical development, attention deficit hyperactivity disorder, and autism spectrum disorders

Open access
Vaidya, Chandan J., You, Xiaozhen, Mostofsky, Stewart, Pereira, Francisco, Berl, Madison M., Kenworthy, Lauren·2020·Journal of Child Psychology and Psychiatry
DOI 10.1111/jcpp.13114PMC PMC6906253
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Abstract

BACKGROUND: Impairment of executive function (EF), the goal-directed regulation of thoughts, actions, and emotions, drives negative outcomes and is common across neurodevelopmental disorders including attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). A primary challenge to its amelioration is heterogeneity in symptom expression within and across disorders. Parsing this heterogeneity is necessary to attain diagnostic precision, a goal of the NIMH Research Domain Criteria Initiative. We aimed to identify transdiagnostic subtypes of EF that span the normal to impaired spectrum and establish their predictive and neurobiological validity. METHODS: Community detection was applied to clinical parent-report measures in 8-14-year-old children with and without ADHD and ASD from two independent cohorts (discovery N = 320; replication N = 692) to identify subgroups with distinct behavioral profiles. Support vector machine (SVM) classification was used to predict subgroup membership of unseen cases. Preliminary neurobiological validation was obtained with existing functional magnetic resonance imaging (fMRI) data on a subsample (N = 84) by testing hypotheses about sensitivity of EF subgroups versus DSM categories. RESULTS: We observed three transdiagnostic EF subtypes characterized by behavioral profiles that were defined by relative weakness in: (a) flexibility and emotion regulation; (b) inhibition; and (c) working memory, organization, and planning. The same tripartite structure was also present in the typically developing children. SVM trained on the discovery sample and tested on the replication sample classified subgroup membership with 77.0% accuracy. Split-half SVM classification on the combined sample (N = 1,012) yielded 88.9% accuracy (this SVM is available for public use). As hypothesized, frontal-parietal engagement was better distinguished by EF subtype than DSM diagnosis and the subgroup characterized with inflexibility failed to modulate right IPL activation in response to increased executive demands. CONCLUSIONS: The observed transdiagnostic subtypes refine current diagnostic nosology and augment clinical decision-making for personalizing treatment of executive dysfunction in children.

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Crossref · 10.1111/jcpp.13114

Cites

53 of 53 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

17 of 48 cited sources checked · 7 supported · 0 flagged · accuracy not yet measured

  • Premisecitation

    Impairment in ASD is progressive and increases from childhood to adolescence.

    “impairment is progressive, increasing from childhood to adolescence (Rosenthal et al., 2013)”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Rosenthal et al., 2013 source

      The Discussion reports greater parent-reported executive-function impairment in older children and adolescents with ASD relative to a normative sample. The claim is broader than that finding: it does not specify executive function, and “progressive” implies change over time in individuals, whereas the study compared different age groups in a cross-sectional cohort. (LLM, conf=0.87)

      Experimental — accuracy not yet measured
  • Premisecitation

    Laboratory tasks discriminate between ASD and ADHD with modest and variable effect sizes (k = .38 to .40).

    “and ASD and ADHD (k=.38-.40) (Geurts, Verte, Oosterlaan, Roeyers, & Sergeant, 2004).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Geurts, Verte, Oosterlaan, Roeyers, & Sergeant, 2004 source

      The available indexed passages are bibliographic metadata, not findings from the paper. Searches for the .38–.40 values and for task-based differences between ASD and ADHD returned no results passage, so our copy cannot verify the claimed effect sizes. (LLM, conf=0.73)

      Experimental — accuracy not yet measured
  • Premisecitation

    Comorbid ADHD is associated with worse adaptive function in ASD.

    “relates to worse adaptive function (Yerys et al., 2009)”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Yerys et al., 2009 source
  • Premisecitation

    The right inferior parietal lobule is especially sensitive to shifting visual attention when task relevance is involved.

    “The rIPL, in particular, is sensitive to shifting of visual attention in the context of task-relevance (Krall et al., 2015)”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Krall et al., 2015 source

      The Results (page unavailable) report inferior parietal lobule activation during attentional reorienting, with stronger convergence for reorienting than for false-belief tasks. But the finding is bilateral, and the Methods include auditory, haptic, and cross-sensory as well as visual studies. The paper therefore does not establish that the right inferior parietal lobule is especially sensitive to visual shifts specifically when task relevance is involved. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • Rests on an assumption: The two fMRI runs differ in their demands on executive function.
  • Premisecitation

    Deficits across all parent-reported domains have been reported for both ADHD and ASD.

    “deficits across all parent-reported domains have been reported for both disorders (Kenworthy, Yerys, Anthony, & Wallace, 2008; Lai et al., 2017; Pennington & Ozonoff, 1996)”
    Quote in the paperSubstantial claim1 of 3 sources checked
    • cites Kenworthy, Yerys, Anthony, & Wallace, 2008 source

      In “Autism performance on new tasks claiming verisimilitude” (page unavailable), the review reports executive-control deficits on caretaker questionnaires in children and adolescents with ASD, including comparisons with children with ADHD. It does not establish deficits across all parent-reported domains in both disorders; it instead highlights a distinctive flexibility deficit in ASD. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites Lai et al., 2017 source
    • cites Pennington & Ozonoff, 1996 source
  • Classified as probably not a substantial claim. 22
  • May combine two claims. 34
  • Borderline: one of the tests for a substantial claim is unclear. 1

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Discovery methods applied to temperamental traits identified ADHD subtypes marked by high positive and negative emotionality.

    “discovery methods applied to temperamental traits distinguished ADHD subtypes defined by high positive and negative emotionality (Karalunas et al., 2014).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Karalunas et al., 2014 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Childhood executive function has a strong effect on adult outcomes such as socioeconomic status and criminal conviction, even after accounting for socioeconomic status and IQ.

    “childhood EF profoundly impacts adult outcomes, including socioeconomic status (SES) and likelihood of criminal conviction, even after controlling for SES and IQ (Moffitt et al., 2011).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Moffitt et al., 2011 source

      The Results (Predicting Wealth and Predicting Crime; page unavailable) report that childhood self-control predicted adult socioeconomic position and criminal conviction after accounting for social class origins and IQ. The paper treats self-control as related to executive function, but measured self-control rather than executive function broadly. Its longitudinal findings support prediction, not the claim that executive function profoundly causes those outcomes. (LLM, conf=0.86)

      Experimental — accuracy not yet measured

  • Classified as probably not a substantial claim.

    Premisecitation

    Comparing the two runs permits testing an anatomical hypothesis about flexibility of attentional modulation derived from attention network theory.

    “contrasting the two runs allows for testing anatomical hypothesis about flexibility of attentional modulation from attention network theory”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites Corbetta & Shulman, 2002 source
    • cites Geng & Vossel, 2013 source
    • Rests on an assumption: The two fMRI runs differ in their demands on executive function.

  • May combine two claims.

    Premisecitation

    Changing the task relevance of salient information between runs engages attentional reorienting or task-context updating, which involves ventral attention network regions including right inferior parietal lobule and right inferior frontal gyrus.

    “manipulation of task-relevance of salient information between the two runs taps attentional reorienting (Corbetta & Shulman, 2002) or updating of task context (Geng & Vossel, 2013), which engages ventral attention network regions of right inferior parietal lobule (rIPL) and right inferior frontal gyrus (rIFG).”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites Corbetta & Shulman, 2002 source
    • cites Geng & Vossel, 2013 source

      Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

      Experimental — accuracy not yet measured
    • Rests on an assumption: The two fMRI runs differ in their demands on executive function.

  • May combine two claims.

    Premisecitation

    These measurement modes differ in goals: ratings assess behavior that generalizes across contexts and time, while performance assesses optimal behavior in a controlled context.

    “These modes of measurement differ in goals (Toplak, West, & Stanovich, 2013), with ratings assessing behavior that generalizes over contexts and time, whereas performance assesses optimal behavior in a controlled context.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Toplak, West, & Stanovich, 2013 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    There is extensive evidence that EF is a fractionated construct as measured by both informant report and laboratory tasks.

    “There is extensive evidence that EF is a fractionated construct both as measured by informant report and laboratory tasks (Friedman & Miyake, 2017; Gioia et al., 2002; Miyake et al., 2000; Teuber, 1972).”
    Quote in the paperNot a substantial claim1 of 3 sources checked
    • cites Friedman & Miyake, 2017 source

      Section 2.2 reports extensive evidence that laboratory EF tasks cluster into separable but correlated factors, supporting a fractionated construct. The passages found do not establish the same pattern for EF measured by informant report; Section 3.2 discusses teacher-rated attention problems as a correlate of task-based EFs, not as an informant-report measure of EF structure. Page numbers were not available in our copy. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites Gioia et al., 2002 source
    • cites Miyake et al., 2000 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Community detection on temperamental traits in ADHD revealed segregation by positive and negative emotion regulation problems.

    “Interestingly, community detection applied to temperamental traits in ADHD, revealed segregation by positive and negative emotion regulation problems (Karalunas et al., 2014)”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Karalunas et al., 2014 source

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Many evidence-based treatments for EF in children with developmental disabilities target specific EF deficit subtypes; for example, central stimulants are evidence-based for inhibition, working memory, and attention deficits, Cogmed improves working memory specifically, and Unstuck and On Target improves flexibility.

    “Many evidence-based treatments for EF in children with developmental disabilities target specific “subtypes” of EF deficit, for example central stimulants are evidence-based for inhibition, working memory and attention deficits, while the computer-based treatment Cogmed improves working memory specifically (Diamond & Ling, 2016) and the cognitive-behavioral treatment Unstuck and On Target improves”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites Diamond & Ling, 2016 source

      Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

      Experimental — accuracy not yet measured
    • cites Kenworthy et al., 2014 source

      Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

      Experimental — accuracy not yet measured

  • Borderline on S4 (based): unclear from the text.

    Findingnone given

    The same three-part structure was also found in typically developing children.

    “The same tripartite structure was also present in the typically developing children.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Executive function processes form a spectrum that ranges from normal dispositional traits to maladaptive psychopathology.
    • The authors state this as an assumption: The chosen behavioral measures sufficiently capture the regulation of attention, action, and emotion.

  • May combine two claims.

    Findingown data

    Three transdiagnostic executive function subtypes were found, each marked by relative weakness in one of three areas: flexibility and emotion regulation; inhibition; or working memory, organization, and planning.

    “We observed three transdiagnostic EF subtypes characterized by behavioral profiles that were defined by relative weakness in: 1) flexibility and emotion regulation; 2) inhibition; and 3) working memory, organization, and planning.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The chosen behavioral measures sufficiently capture the regulation of attention, action, and emotion.

  • May combine two claims.

    Findingown data

    In each sample, the subgroups were mostly male and did not differ in age or IQ.

    “For each sample, subgroups were predominantly male and did not differ in age, and IQ (ps>.5).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Community detection on common clinical parent-report measures from two large independent cohorts produced three subgroups with distinct EF profiles: relative weakness in behavioral flexibility and emotion regulation (FLEX-EMOT), hyperactivity/impulsivity and inhibition (INHIBIT), and working memory, organizing, and planning (METACOG).

    “Community detection applied to common clinical parent-report measures from two large independent cohorts revealed three subgroups with distinct EF-profiles defined by relative weakness in 1) behavioral flexibility and emotion regulation (FLEX-EMOT); 2) hyperactivity/impulsivity and inhibition (INHIBIT); and 3) working memory, organizing, and planning (METACOG).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The tripartite community structure also appeared in the combined TD sample, and the three EF profiles were very similar to each full sample.

    “The observed tripartite community structure also characterized the combined TD sample (Q=.46) and the 3 EF profiles were highly similar to each full sample (rs=0.81-0.97, ps<0.005; Figure 3, Figure S4).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Separate models showed a significant main effect of EF-group but not DSM-group.

    “Separate models indicated a significant main effect of EF-group (Model 1:F(24, 142) =1.74, p=.025; etâ2=.23) but not DSM-group (Model 2:p=.58; etâ2=.13)”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    These two profiles did not cover all ADHD cases; 19% were defined by FLEX-EMOT.

    “Most importantly, however, these two profiles did not account for all of the ADHD cases, with 19% defined by the FLEX-EMOT profile”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    After training on CNHS/GU, subgroup classification for KKI was 77.0% accurate: FLEX-EMOT 71.6%, INHIBIT 88.0%, METACOG 76.2%.

    “Subgroup-classification for the KKI sample following training on the CNHS/GU sample was 77.0% (FLEX-EMOT:71.6%; INHIBIT:88.0%; METACOG:76.2%).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The behavioral profiles crossed diagnostic categories: each EF subgroup included ASD, ADHD, and TD participants, and ASD children with comorbid ADHD also appeared across EF subgroups.

    “These behavioral profiles cut across diagnostic categories, as the distribution of participants in each EF subgroup spans ASD, ADHD, and TD participants (Table 1); the distribution of ASD children with comorbid ADHD also cut across EF subgroups.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    EF profiles ranged from normal to impaired, and their distributions crossed ADHD, ASD, and TD samples.

    “EF profiles spanned the normal to impaired spectrum and distributions cut across ADHD, ASD, and TD samples.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    INHIBIT maps to Hyperactivity/Impulsivity; however, INHIBIT and METACOG included elevated Inattention variably between cohorts, suggesting limited utility as a distinguishing feature.

    “INHIBIT maps to Hyperactivity/Impulsivity; however, INHIBIT and METACOG included elevated Inattention variably between cohorts suggesting limited utility as a distinguishing feature.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In each sample, TD children were spread fairly evenly across the three EF subgroups, while ASD and ADHD children were overrepresented in FLEX-EMOT and INHIBIT, with more ASD children in FLEX-EMOT and more ADHD children in INHIBIT.

    “For each sample, TD children are relatively evenly distributed across the three EF subgroups, whereas children with ASD and ADHD are disproportionally represented in the FLEX-EMOT and INHIBIT subgroups with more ASD children having the FLEX-EMOT profile and more ADHD children having the INHIBIT profile (X(2)>50, ps<.001).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Random split-half validation on the combined sample reached 88.9% accuracy: FLEX-EMOT 88.3%, INHIBIT 89.3%, METACOG 89.3%.

    “Random split-half validation conducted on the combined sample had 88.9% accuracy (FLEX-EMOT:88.3%; INHIBIT:89.3%; METACOG:89.3%)”
    • Also stated in: § Translational Implications · plain
      “SVM results based on the large combined sample (N=1012) attained 88.9% accuracy”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Tables S1-S2 show cohort differences such as the ASD:ADHD ratio and elevated inattention symptoms in the KKI ADHD sample relative to CNHS/GU.

    “Tables S1–S2 show cohort differences such as the ratio of ASD:ADHD samples and elevated inattention symptoms in the ADHD sample in the KKI relative to CNHS/GU cohort.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Segregation strength (Qs=.42-.43) was similar across sample sizes (N=320-1012) and was replicated in two independent cohorts.

    “The strength of segregation (Qs=.42-.43) was similar across sample sizes (N=320-1012) and was replicated in two independent cohorts.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    For ASD, only half of the samples in each cohort showed FLEX-EMOT, challenging the often held notion that cognitive inflexibility is the hallmark EF comorbidity in ASD.

    “For ASD, only half of the samples in each cohort showed the FLEX-EMOT profile, which challenges the often held notion of cognitive inflexibility as the hallmark EF comorbidity in ASD (Leung & Zakzanis, 2014).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Leung & Zakzanis, 2014 source

  • May combine two claims.

    Findingown data

    For AUC, TD participants were mostly in the first quartile, indicating lower impairment as expected, while ASD and ADHD children covered the rest of the range, indicating that impairment level was not tied to a specific diagnosis.

    “For AUC (Figure 2A), TD participants are primarily represented in the first quartile, indicating lower impairment as expected; and ASD and ADHD children span the remainder of the range, indicating that degree of impairment is not associated with a specific diagnosis.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Nested Model #2 was significant, meaning that EF-group significantly increased explained variance beyond DSM-groups.

    “Nested Model #2 was significant, F(24, 138)=1.8, p=.017), indicating that the EF-group factor significantly increased the amount of variance explained beyond that accounted for by DSM-groups.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The INHIBIT subgroup mainly showed greater inhibition problems, with peaks on ADHD-RS Hyperactivity/Impulsivity and BRIEF Inhibit.

    ““INHIBIT” reflects primarily greater problems with inhibition, as suggested by peaks for Hyperactivity/Impulsivity on the ADHD-RS and BRIEF Inhibit.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    A model containing both grouping factors showed a significant EF-group effect but not a DSM-group effect.

    “a model with both Group factors (Model 3) showed a significant effect of EF-group (F(24, 138)=1.7, p=.03) but not DSM-Group, p=.46).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Main effects of run, with higher activation in top-down than bottom-up, appeared for rIFG with EF-Group and for both ROIs with DSM-Groups, indicating that task instructions produced the expected shift in attentional state between runs.

    “Main effects of run, higher activation during the top-down than bottom-up run, were observed for rIFG with EF-Group and for both ROIs with DSM-Groups (F(1, 162)>17.6, ps<.0001), indicating that task-instructions evoked the expected change in attentional state between fMRI runs (behavioral results in SI).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    A significant Group X Run interaction appeared in rIPL: activation rose during the Top-down run for INHIBIT and METACOG, but not for FLEX-EMOT.

    “This was observed in rIPL (F(2, 162)=5.57, p =.005) such that activation increased during the Top-down run for INHIBIT (t(23)=5.56, p<.001) and METACOG (t(34)=4.06, p<.001) groups, but not for FLEX-EMOT (t(24)=.47, p=.64) (Figure 4B).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Some cohort differences are apparent: externalizing symptoms distinguished subgroups in CNHS/GU (higher mean in FLEX-EMOT than the other two) but not in KKI, and inattention symptoms differed between subgroups in KKI but less so in CNHS/GU.

    “Some differences are apparent between cohorts – externalizing symptoms distinguished the subgroups in the CNHS/GU (higher mean in FLEX-EMOT than other two subgroups) but not in the KKI cohort and inattention symptoms differed between the subgroups in the KKI cohort but less so in the CNHS/GU cohort.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Community structure was unrelated to age, intelligence, or gender, and did not depend on impairment level because it also characterized the TD-only sample.

    “Community structure was not associated with age, intelligence, or gender, and not dependent on level of impairment as it also characterized the TD-only sample.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Premisenone given

    Heterogeneity in symptom expression within and across disorders is a main obstacle to improving executive function impairment.

    “A primary challenge to its amelioration is heterogeneity in symptom expression within and across disorders.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Premisenone given

    Resolving heterogeneity is required for diagnostic precision, which is an aim of the NIMH Research Domain Criteria Initiative.

    “Parsing this heterogeneity is necessary to attain diagnostic precision, a goal of the NIMH Research Domain Criteria Initiative.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Generalization was tested by split-half validation on the combined sample of 1012 participants, randomly split into halves of 506 matched for site, age, sex, and IQ.

    “generalization was tested with split-half validation on the combined sample (N=1012), by randomly splitting into halves (N=506 each) matched for site, age, sex, and IQ”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Premisenone given

    Modulation by task context should reflect individual differences in cognitive flexibility.

    “Such modulation by task-context ought to be sensitive to individual differences in cognitive flexibility.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The two fMRI runs differ in their demands on executive function.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Parent reports show selectively greater deficits in set-shifting in ASD.

    “and set-shifting for ASD (Gioia, Isquith, Kenworthy, & Barton, 2002).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Gioia, Isquith, Kenworthy, & Barton, 2002 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Neuropsychological models describe executive function as cognitive control, a latent construct reflecting prefrontal-cortex-mediated processes including working memory, response inhibition, shifting, response selection, planning, and fluency.

    “neuropsychological models cast EF as “cognitive control”, a latent construct reflecting prefrontal cortex mediated processes such as working memory, response inhibition, shifting, and response selection (Miyake et al., 2000), in addition to planning and fluency (Pennington, 1997).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Miyake et al., 2000 source
    • cites Pennington, 1997

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Only children with complete data were included in the study.

    “only children with complete data were included in the study.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    A large proportion of autistic children, between 41% and 78%, meet criteria for ADHD.

    “A large proportion of autistic children meet criteria for ADHD (41%-78% (Murray, 2010).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Murray, 2010 source

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    ADHD and ASD diagnoses were based on DSM-IV-TR or DSM-5 criteria.

    “ADHD and ASD diagnoses were based on DSM-IV-TR or DSM-5 criteria”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    The discovered subtypes were validated by independent replication, machine learning, and association with neural biomarkers.

    “Discovered subtypes were validated through independent replication, machine learning techniques, and association with neural biomarkers.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The chosen behavioral measures sufficiently capture the regulation of attention, action, and emotion.

  • May combine two claims.

    Premisecitation

    Comorbidity increases symptom heterogeneity and confounds treatment efficacy, creating a major clinical challenge.

    “poses a major clinical challenge as it enhances symptom heterogeneity and confounds treatment efficacy (Jensen et al., 2001).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Jensen et al., 2001 source

  • Classified as probably not a substantial claim.

    Study design and conductcitation

    ASD diagnosis was confirmed with the ADI-R and/or ADOS-G following NICHD/NIDCD Collaborative Programs for Excellence in Autism criteria.

    “ASD diagnosis was confirmed with the Autism Diagnostic Interview—Revised (ADI-R)(Lord, Rutter, & Le Couteur, 1994) and/or the Autism Diagnostic Observation Schedule—Generic (ADOS-G)(Lord et al., 2000) following the criteria established by the NICHD/NIDCD Collaborative Programs for Excellence in Autism (Lainhart et al., 2006).”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Lord, Rutter, & Le Couteur, 1994 source
    • cites Lord et al., 2000 source
    • cites Lainhart et al., 2006 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Comorbid ADHD is associated with worse quality of life in ASD.

    “quality of life (Sikora, Vora, Coury, & Rosenberg, 2012)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Sikora, Vora, Coury, & Rosenberg, 2012 source

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    Using easy-to-administer and commonly used clinical measures increases the clinical usefulness of the discovered community structure.

    “Use of easy-to-administer and common clinical measures enhances the clinical utility of the discovered community structure”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: The chosen behavioral measures sufficiently capture the regulation of attention, action, and emotion.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    One in five children diagnosed with ASD has a pre-existing ADHD diagnosis.

    “1 in 5 children diagnosed with ASD have a pre-existing ADHD diagnosis (Miodovnik, Harstad, Sideridis, & Huntington, 2015).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Miodovnik, Harstad, Sideridis, & Huntington, 2015 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Of the fMRI subsample, 84 participants met the head motion criteria.

    “of these N=84 met head motion criteria”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductown data

    For the bottom-up run analysis, age and mean FD were covariates, and the threshold was p < .05 FDR corrected.

    “a one-sample t-test (age, mean FD as covariates) for Salient vs. Familiar distractor trials in the Bottom-up run identified regions sensitive to the quality of distracting information (p < .05 FDR corrected: p<.0014, k>10 voxels).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductreasoning

    Both fMRI runs had identical stimulus presentation and differed only in EF demands, which were low in the bottom-up run and high in the top-down run.

    “Thus, both fMRI runs were identical in stimulus presentation differing only in EF demands, low in bottom-up run and high in the top-down run.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    SVM classification of new cases was more than 77% accurate, establishing predictive validity for the observed community structure.

    “Support vector machine based classification of new cases was >77% accurate, establishing predictive validity of the observed community structure.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    Run order was not counterbalanced, to preserve the unexpectedness of distraction in the first, bottom-up run.

    “Run order was not counterbalanced in order to preserve the unexpectedness of the distraction in the first, bottom-up run.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    The tripartite community structure also appeared in TD children alone, suggesting that heterogeneity in disordered EF is nested within normal variability.

    “This tripartite community structure also characterized TD children alone, suggesting that heterogeneity in disordered EF is nested within normal variability.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Preliminary neurobiological validity came from available fMRI data, which showed greater sensitivity of EF than DSM groups to variance in ventral/dorsal attention network regions and supported the predicted ventral attention attenuation selectively in FLEX-EMOT.

    “Preliminary neurobiological validity was obtained with available fMRI data that showed higher sensitivity of EF than DSM groups to variance in ventral/dorsal attention network regions and support for predicted ventral attention attenuation selectively in the FLEX-EMOT subgroup.”
    Quote in the paperSubstantial claim
54 of 54

  • The paper relies on this without support.

    Executive function processes form a spectrum that ranges from normal dispositional traits to maladaptive psychopathology.

    “Processes comprising EF reflect a spectrum, manifested as dispositional traits at the normative end and psychopathology at the maladaptive end.”

  • The authors state this as an assumption.

    The chosen behavioral measures sufficiently capture the regulation of attention, action, and emotion.

    “To the extent that the selected behavioral feature-set adequately captures regulation of attention, action, and emotion, the observed community structure reveals subtypes of EF that are distinguished by behavioral profiles.”

  • The paper relies on this without support.

    The two fMRI runs differ in their demands on executive function.

    “each participant completed two fMRI runs differing in EF demands”

  • The paper relies on this without support.

    The parent-report measures chosen are valid indicators of EF and emotion regulation across the studied populations.

    “With the goal of maximizing clinical utility and access, we selected measures commonly used to assess EF and emotion regulation in most pediatric clinical settings.”

  • The paper relies on this without support.

    Identifying EF subtype membership is clinically useful for guiding diagnosis and treatment, tracking treatment outcomes, and probing neural correlates.

    “These results support the existence of three subtypes of EF, useful clinically for guiding diagnosis and treatment, tracking treatment outcomes, and probing neural correlates.”
5 of 5

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Not all children with ADHD show executive function deficits, and such deficits can also be seen in typically developing children.

    “not all children with ADHD show EF deficits (Willcutt et al., 2005), which can also be seen in typically-developing (TD) children (Vaidya et al., 2020)”

    From Executive Functions in Neurodevelopmental Disorders: Comorbidity Overlaps Between Attention Deficit and Hyperactivity Disorder and Specific Learning Disorders (2021) · cites this paper as Vaidya et al., 2020

  • Transdiagnostic executive function subtypes have been identified using community detection algorithms, and children in an inflexibility subtype failed to modulate parietal activation with increasing executive task demands.

    “For example, transdiagnostic executive function subtypes have been identified with use of community detection algorithms, and children within the subtype characterized by inflexibility showed a failure to modulate parietal lobe activation in response to increasing executive task demands82.”

    From Cognitive and behavioural flexibility: Neural mechanisms and clinical considerations (2021) · cites this paper as [82]

  • A community detection approach combined with support vector machines identified three transdiagnostic subtypes of EF across ASD, ADHD, and TD participants.

    “In doing so, they found three transdiagnostic subtypes with specific relevance to the engagement of different brain regions involved in EF.”

    From Heterogeneity of executive function revealed by a functional random forest approach across ADHD and ASD (2020) · cites this paper as Vaidya et al., 2020

  • Newer machine learning techniques may offer assistance by parsing out non-linear patterns in data that are missed with general linear model-based statistical tests and predictive modeling.

    “Newer machine learning techniques may offer an assistance by parsing out non-linear patterns in data that are missed with general linear model-based statistical tests and predictive modeling (Duda et al., 2016; Uluyagmur-Ozturk et al., 2017; Vaidya et al., 2020).”

    From Heterogeneity of executive function revealed by a functional random forest approach across ADHD and ASD (2020) · cites this paper as Vaidya et al., 2020

  • There may be more than one sole cause of any given phenotype, and such causes may be shared and distinct both between and within the disorders.

    “These results indicate that while ASD and ADHD share some etiological basis, there may be more than one sole “cause” of any given phenotype (Musser et al., 2014; Reiersen & Todd, 2008) and such causes may also be shared and distinct, both between and within the disorders (Karalunas et al., 2018; Rommelse et al., 2017; Vaidya et al., 2020).”

    From Heterogeneity of executive function revealed by a functional random forest approach across ADHD and ASD (2020) · cites this paper as Vaidya et al., 2020

Statistics recomputed

Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.

  • ConsistentF(24, 142) = 1.74reported p = .025 · recomputed p = .025

    “F(24, 142) =1.74, p = .025”

  • ConsistentF(24, 138) = 1.7reported p = .03 · recomputed p = .031

    “F(24, 138)=1.7, p = .03”

  • ConsistentF(24, 138) = 1.8reported p = .017 · recomputed p = .019

    “F(24, 138)=1.8, p = .017”

  • ConsistentF(2, 162) = 5.57reported p = .005 · recomputed p = .005

    “F(2, 162)=5.57, p = .005”

  • Consistentt(23) = 5.56reported p < .001 · recomputed p < .001

    “t(23)=5.56, p < .001”

  • Consistentt(34) = 4.06reported p < .001 · recomputed p < .001

    “t(34)=4.06, p < .001”

  • Consistentt(24) = 0.47reported p = .64 · recomputed p = .643

    “t(24)=.47, p = .64”

7 of 7

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • INHIBIT fMRI test implies more participants than the subgroup contains

    Major

    The fMRI analysis lists 21 participants in INHIBIT, but its within-group comparison between runs reports t(23), which implies 24 paired observations. That test cannot have been calculated from the stated INHIBIT subgroup.

  • KKI externalizing results conflict with the claim that every measure differed

    Minor

    The results say all three subgroups differed significantly on every EF measure in each sample. The discussion instead says externalizing symptoms did not distinguish the subgroups in the KKI cohort.

  • Impairment-severity figure is cited inconsistently

    Minor

    The results identify Figure 2 as showing the AUC distributions used for impairment severity, while the clinical guidance directs readers to Figure 3 for that comparison.

3 of 3

Cited works that were retracted

Works this paper cites that were later retracted, from the retraction notices publishers deposit. Major when the notice came out before this paper was published.

  • Cites a retracted work: 10.1001/jamapsychiatry.2014.763

    Major

    The cited work was retracted on 2018-03-07 (notice 10.1001/jamapsychiatry.2018.0013), before this paper was published (2019-09-11). Its authors could have known.

    Cited work 10.1001/jamapsychiatry.2014.763 · retracted 2018-03-07 · notice 10.1001/jamapsychiatry.2018.0013 · this paper published 2019-09-11

1 of 1

Cites

1 retracted

Flagged first, then by citations

Research works printed but not linked: 1

  1. Achenbach T.M., 2009, The Achenbach system of empirically based assessment (ASEBA): Development, findings, theory, and applications

Cited by

Sorted by citations

Related

Authors
Vaidya, C. J., You, X., Mostofsky, S., Pereira, F., Berl, M. M., & Kenworthy, L.
Affiliations
  • Children's National (US)
  • Kennedy Krieger Institute (US)
  • National Institute of Mental Health (US)
Corresponding author
Vaidya, Chandan J.
ORCID
Venue
Journal of Child Psychology and Psychiatry
Publisher
Wiley
Published
2019-09-11
Volume
61
Issue
1
Pages
51-61
ISSN
  • 0021-9630 (ISSN-L)
  • 1469-7610
DOI
10.1111/jcpp.13114
PMC
PMC6906253
OpenAlex
W2972944145
Cited by
126
References
53
Citations by year
2026: 9 · 2025: 15 · 2024: 16 · 2023: 38 · 2022: 22 · 2021: 15 · 2020: 9 · 2019: 1 · 2013: 1
FWCI
9.34
Type
journal article
Language
en
Open access
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
  • Journal of Child Psychology and Psychiatry (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institute of Mental Health (R01MH110512, R01MH085328, R01MH078160, R01MH084961, R01MH065395, R01MH100028)
  • National Institute of Neurological Disorders and Stroke (R01NS048527)
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (U54HD090257, P30HD040677)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Attention Deficit Hyperactivity Disorder
  • Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Developmental and Educational Neuropsychology
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
Keywords
executive function, attention deficit hyperactivity disorder, autism spectrum disorder, symptom heterogeneity, cognitive flexibility, emotion regulation, inhibition, working memory, planning and organization, children, parent-report measures, support vector machine classification, community detection, Research Domain Criteria, personalized treatment
MeSH terms
Autism Spectrum Disorder, Machine Learning, Emotional Regulation, Adolescent, Attention Deficit Disorder with Hyperactivity, Child, Child Development, Female, Humans, Individuality, Inhibition, Psychological, Magnetic Resonance Imaging, Male, Memory, Short-Term, Reproducibility of Results, Cohort Studies, Adolescent Development, Executive Function, Functional Neuroimaging, Cognitive Dysfunction

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read under definition version 3 (extract-v3) on 2026-09-28.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-09-28.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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