Young Adult Outcomes for Children With 22q11 Deletion Syndrome and Comorbid ADHD

Young Adult Outcomes for Children With 22q11 Deletion Syndrome and Comorbid ADHD Abstract Background 22q11.2 deletion syndrome (22q11DS) is a common microdeletion syndrome associated with a variety of negative health, cognitive, emotional, and behavioral outcomes. 22q11DS is comorbid with many psychiatric disorders including attention-deficit/hyperactivity disorder (ADHD). The current study aimed to investigate the cognitive, behavioral, and functional outcomes that a childhood ADHD diagnosis predicts to in adulthood. Methods This longitudinal study followed 52 individuals with 22q11DS over 9 years. Childhood ADHD was operationalized both categorically (Diagnostic and statistical manual - 4th edition (DSM-IV) ADHD diagnoses) and dimensionally (inattentive and hyperactive–impulsive symptoms) and was tested as predictors of young adult outcomes. Results As young adults, children with 22q11DS + baseline ADHD had more parent-reported executive dysfunction and lower levels of clinician-rated overall functioning than those with 22q11DS yet without ADHD. Dimensional symptoms of ADHD in childhood did not predict young adult outcomes. No self-report differences emerged between those with and without baseline ADHD. The majority (82.4%) of individuals with 22q11DS + baseline ADHD were never treated with an ADHD medication. Conclusions A categorical diagnosis of ADHD in childhood predicted a greater variety of worse outcomes than dimensional levels of ADHD symptoms. Despite the significant impact of comorbid ADHD in 22q11DS, evidence-based treatment rates were low. 22q11.2 deletion syndrome, ADHD, developmental delay, longitudinal 22q11.2 deletion syndrome (22q11DS), also known as velo-cardio-facial syndrome, is the most common identified microdeletion syndrome and is caused by an interstitial deletion from chromosome at the 22q11.2 band. In most cases, 22q11DS is caused by a deletion of 3 million base pairs of DNA encompassing 40–50 genes. The majority (90%) of 22q11.2 deletions are de novo (Shprintzen et al., 2005). 22q11DS is relatively common, occurring in ∼1:5,950 births (Botto et al., 2003). Heart malformations and cleft palate are common characteristics of 22q11DS; yet, not all individuals demonstrate either (Shprintzen, 2000). Many individuals with 22q11DS have cognitive impairments, with IQs generally 1–2 SDs below the mean for age (Antshel et al., 2007). While a specific mechanism has not been definitively identified, several of the genes that are deleted on one copy of chromosome 22q11.2 are thought to contribute to cognitive impairments observed in 22q11DS (Philip & Bassett, 2011). In addition to cognitive impairments, 22q11DS is associated with a variety of psychiatric comorbidities. Attention-deficit/hyperactivity disorder (ADHD), major depressive disorder, anxiety disorders, oppositional defiant disorder, and autism spectrum disorder are all comorbid with 22q11DS (Schneider et al., 2014). Further, individuals with 22q11DS are at increased risk for psychiatric comorbidities in adulthood, in particular schizophrenia (Schneider et al., 2014). These psychiatric comorbidities likely present challenges for individuals with 22q11DS and their families beyond what is imparted by 22q11DS, although this research question has not been systematically studied (Schneider et al., 2014). Attention-Deficit/Hyperactivity Disorder ADHD is one of the most prevalent comorbid disorders in individuals with 22q11DS (Schneider et al., 2014). Approximately 4–12% of children without 22q11DS are diagnosed with ADHD (Spencer, Biederman, & Mick, 2007). The prevalence rate of ADHD in 22q11DS is roughly 5-fold higher (30–40%) than the prevalence rate of ADHD in the general population (Schneider et al., 2014). In non-22q11DS cross-sectional samples, ADHD negatively affects academic, occupational, social, and emotional functioning (de Schipper et al., 2015). Longitudinally, children with ADHD are at greater risk for difficulties in late adolescence and early adulthood, including school failure, emotional difficulties, dysfunctional relationships, legal problems, substance abuse, and occupational difficulties (Spencer et al., 2007). Thus, an ADHD diagnosis is a concern both in childhood and young adulthood. In the only longitudinal study to date that has investigated ADHD in 22q11DS, Antshel and colleagues (2013) followed children with 22q11DS both with and without ADHD into adolescence. The developmental trajectories of those with 22q11DS were compared with control children with ADHD. Results indicated that children with 22q11DS and ADHD (22q11DS + ADHD) experienced largely similar longitudinal trajectories to control children with ADHD. Hyperactivity–impulsivity symptoms in the 22q11DS + ADHD group, however, increased over time, a finding contrary to the literature on idiopathic ADHD (Spencer et al., 2007). The developmental delays in the 22q11DS and ADHD group and the low pharmacotherapy use in the 22q11DS population may explain this finding (Tang et al., 2014). Individuals with 22q11DS + ADHD were at increased risk for oppositional defiant disorder, at similar rates to those with idiopathic ADHD, both of which are higher than individuals with 22q11DS only (Antshel et al., 2013). However, mood and anxiety disorders were no more prevalent in 22q11DS + ADHD than in individuals with 22q11DS only (Antshel et al., 2013), contrary to idiopathic ADHD research (Spencer et al., 2007). Similar to idiopathic ADHD (Hurtig et al., 2007), major depression predicted ADHD persistence in the 22q11DS population (Antshel et al., 2013). Overall, this study provided evidence that childhood factors that predict ADHD persistence in non-22q11DS populations predict persistence in individuals with 22q11DS, with few exceptions. Presently, the Antshel and colleagues study is the only study that has considered the longitudinal course of children with 22q11DS + ADHD. This study is limited principally by the short follow-up period (3 years). Need for Current Study The persistence of ADHD into adulthood has been empirically supported, both dimensionally along a continuum representing elevated symptoms and as a categorical diagnosis (ADHD vs. non-ADHD) (Faraone et al., 2015). Nevertheless, the developmental trajectories for children with ADHD are heterogeneous (Spencer et al., 2007). Efforts to understand developmental trajectories are needed, especially in populations of children with ADHD and an additional childhood developmental disorder (like 22q11DS). ADHD is frequently comorbid with other childhood developmental disorders besides 22q11DS (Spencer et al., 2007). Investigating adult outcomes of childhood ADHD in developmentally delayed populations is important for several reasons. First, this information can be clinically useful and provide guidance about longitudinal outcomes for clinicians and parents. For example, ADHD is comorbid with a variety of other genetic, medical, and neurodevelopmental conditions, including fragile X syndrome, Williams syndrome, and Klinefelter syndrome (Lo-Castro, D'Agati, & Curatolo, 2011). However, we know little about the longitudinal course of ADHD in 22q11DS. Second, lower intelligence predicts ADHD persistence and impairments in adulthood (Faraone et al., 2015); yet, most studies on ADHD exclude those with an IQ <80 (Mackenzie & Wonders, 2016). Thus, we do not know the longitudinal outcomes of individuals with ADHD who have IQs <80. Third, given that many youth with developmental delays are inattentive and restless (Lo-Castro et al. 2011), there is risk for both overdiagnosis and underdiagnosis of ADHD in these children (Antshel, Phillips, Gordon, Barkley, & Faraone, 2006). Following children with ADHD and developmental delays longitudinally would ultimately inform clinical practice by elucidating the extent to which a childhood ADHD diagnosis is a meaningful predictor of adult outcomes. Antshel and colleagues’ (2013) examination of the longitudinal course of ADHD in the 22q11DS population suggests that childhood ADHD in 22q11DS is of concern into adolescence, but the functional consequences of childhood ADHD into young adulthood are, as of yet, unknown. Rather than focus on ADHD diagnostic continuity from childhood into adulthood, this study investigated whether behavioral and functional outcomes would worsen over time for children with 22q11DS and ADHD. Based on the idiopathic ADHD literature, we hypothesized that a childhood ADHD diagnosis in 22q11DS (22q11DS + baseline ADHD) would predict to poorer behavioral and functional outcomes in young adulthood compared with those with 22q11DS, yet no ADHD (22q11DS only) even after controlling for childhood levels of these variables. Aim 1 tested this hypothesis by examining whether a categorical diagnosis of childhood ADHD predicted behavioral and functional outcomes in adulthood for children with 22q11DS. Given the controversies about ADHD diagnoses in individuals with developmental disorders (Antshel et al., 2006), Aim 2 tested this hypothesis by examining whether continuous, dimensional measures of childhood ADHD symptoms (i.e., inattentive, hyperactive–impulsive symptoms) predicted behavioral and functional outcomes in adulthood. Others (Neely, Green, Sciberras, Hazell, & Anderson, 2016) have suggested that using both categorical and dimensional approaches is particularly important for youth with neurodevelopmental disorders. Method Participants This 9-year longitudinal study followed individuals with 22q11DS every 3 years; thus, four time points (baseline, Year 3, Year 6, and Year 9) were included in the larger study. Children with 22q11DS were initially recruited from a large academic medical center in the northeastern United States during the years 2002–2005. All families that met inclusion criteria agreed to participate. Only those children with a fluorescence in situ hybridization-confirmed deletion of 22q11.2 were included. Children with an identifiable genetic disorder (other than 22q11DS) or children with an identifiable neurological condition (e.g., traumatic brain injury, preterm birth) that is known to affect cognitive or psychiatric function were excluded from participation. For the current project, only participants who had Time 4 (young adult) data and who also had baseline data were included. Our total sample consisted of 52 children with 22q11DS (28 males). At baseline, the average age of individuals with 22q11DS was 12.2 years (SD = 2.3), and at Time 4, the average age of 22q11DS participants was 21.3 years (SD = 2.2). Sample Representativeness Given that we imposed strict participation criteria (requiring both baseline and Time 4 data), not all participants in the larger study are included in our analyses. Thus, we compared our study subsample with all individuals who participated at baseline: participants in the current study did not differ on any relevant Time 1 sociodemographic measures, including participant age F(1, 78) = .003, p = .963, gender X2 (1) = .061, p = .831 or socioeconomic status F(1, 78) = 2.01, p = .165. Likewise, participants in the current project did not differ from those from the larger project on any relevant social and cognitive measures, including baseline adaptive functioning F(1, 78) = .531, p = .792 or IQ F(1, 78) = .316, p = .664. Thus, the current study participants appear to be representative of the larger project sample. ADHD Status At baseline (childhood), 23 of the 52 individuals with 22q11DS met formal Diagnostic and statistical manual - 4th edition (DSM-IV) diagnostic criteria for ADHD based on a structured psychiatric interview with the participants’ parents. This prevalence rate (44%) is similar to what others have reported in the literature (Schneider et al., 2014). Sex differences between the two 22q11DS groups approached significance, X2 (1) = 3.68, p = .055 in that more males were diagnosed with ADHD. Age differences existed between the two 22q11DS groups at both baseline, F(1, 51) = 4.00, p = .050, and young adulthood, F(1, 51) = 4.13, p = .047. At both periods, participants with 22q11DS + baseline ADHD were slightly younger than those with 22q11DS only. Given the age differences between the two 22q11DS groups, analyses comparing the two 22q11DS groups will control for the effects of age. Please see Table I for descriptive data. Table I. Baseline and Young Adulthood Data 22q11DS + ADHD 22q11DS only N 23 29 Time 1 Time 1 Age 11.67 (2.01)* 12.79 (2.46) Gender (% female) 8 (34.8) 16 (55.2) Time 1 BASC Hyperactivity 62.80 (15.62)* 54.80 (12.96) Time 1 BASC Attention Problems 67.24 (10.61)** 59.28 (9.42) Time 4 Time 4 Age 20.5 (1.5)* 21.7 (2.1) Self-report  Time 4 Self-Report BRIEF-A GEC 58.44 (13.05) 55.00 (13.06)  Time 4 ASR Internalizing Composite 56.40 (10.76) 58.71 (16.19)  Time 4 ASR Externalizing Composite 55.83 (14.35) 54.57 (10.31)  Time 4 SAS-SR Total Composite 59.82 (11.10) 62.75 (14.79) Parent report  Time 4 VABS-II Composite 65.85 (11.64) 67.00 (12.77)  Time 4 Parent Report BRIEF-A GEC 64.43 (10.66)** 55.51 (12.58) Clinician rated  Time 4 Current GAF 60.81 (18.85) 61.82 (14.61)  PAS total composite 3.11 (1.32)* 2.24 (1.22) 22q11DS + ADHD 22q11DS only N 23 29 Time 1 Time 1 Age 11.67 (2.01)* 12.79 (2.46) Gender (% female) 8 (34.8) 16 (55.2) Time 1 BASC Hyperactivity 62.80 (15.62)* 54.80 (12.96) Time 1 BASC Attention Problems 67.24 (10.61)** 59.28 (9.42) Time 4 Time 4 Age 20.5 (1.5)* 21.7 (2.1) Self-report  Time 4 Self-Report BRIEF-A GEC 58.44 (13.05) 55.00 (13.06)  Time 4 ASR Internalizing Composite 56.40 (10.76) 58.71 (16.19)  Time 4 ASR Externalizing Composite 55.83 (14.35) 54.57 (10.31)  Time 4 SAS-SR Total Composite 59.82 (11.10) 62.75 (14.79) Parent report  Time 4 VABS-II Composite 65.85 (11.64) 67.00 (12.77)  Time 4 Parent Report BRIEF-A GEC 64.43 (10.66)** 55.51 (12.58) Clinician rated  Time 4 Current GAF 60.81 (18.85) 61.82 (14.61)  PAS total composite 3.11 (1.32)* 2.24 (1.22) Note. ADHD = attention-deficit/hyperactivity disorder; ASR = Adult Self-Report; BASC = Behavior Assessment System for Children; BRIEF-A = Behavioral Rating Inventory for Executive Functioning-Adult version; GAF = Global Assessment of Functioning; GEC = Global Executive Composite; PAS = Premorbid Adjustment Scale; SAS-SR = Social Adjustment Scale-Self-Report; VABS-II = Vineland Adaptive Behavior Scales, Second Edition. * p < .05; ** p < .01. Table I. Baseline and Young Adulthood Data 22q11DS + ADHD 22q11DS only N 23 29 Time 1 Time 1 Age 11.67 (2.01)* 12.79 (2.46) Gender (% female) 8 (34.8) 16 (55.2) Time 1 BASC Hyperactivity 62.80 (15.62)* 54.80 (12.96) Time 1 BASC Attention Problems 67.24 (10.61)** 59.28 (9.42) Time 4 Time 4 Age 20.5 (1.5)* 21.7 (2.1) Self-report  Time 4 Self-Report BRIEF-A GEC 58.44 (13.05) 55.00 (13.06)  Time 4 ASR Internalizing Composite 56.40 (10.76) 58.71 (16.19)  Time 4 ASR Externalizing Composite 55.83 (14.35) 54.57 (10.31)  Time 4 SAS-SR Total Composite 59.82 (11.10) 62.75 (14.79) Parent report  Time 4 VABS-II Composite 65.85 (11.64) 67.00 (12.77)  Time 4 Parent Report BRIEF-A GEC 64.43 (10.66)** 55.51 (12.58) Clinician rated  Time 4 Current GAF 60.81 (18.85) 61.82 (14.61)  PAS total composite 3.11 (1.32)* 2.24 (1.22) 22q11DS + ADHD 22q11DS only N 23 29 Time 1 Time 1 Age 11.67 (2.01)* 12.79 (2.46) Gender (% female) 8 (34.8) 16 (55.2) Time 1 BASC Hyperactivity 62.80 (15.62)* 54.80 (12.96) Time 1 BASC Attention Problems 67.24 (10.61)** 59.28 (9.42) Time 4 Time 4 Age 20.5 (1.5)* 21.7 (2.1) Self-report  Time 4 Self-Report BRIEF-A GEC 58.44 (13.05) 55.00 (13.06)  Time 4 ASR Internalizing Composite 56.40 (10.76) 58.71 (16.19)  Time 4 ASR Externalizing Composite 55.83 (14.35) 54.57 (10.31)  Time 4 SAS-SR Total Composite 59.82 (11.10) 62.75 (14.79) Parent report  Time 4 VABS-II Composite 65.85 (11.64) 67.00 (12.77)  Time 4 Parent Report BRIEF-A GEC 64.43 (10.66)** 55.51 (12.58) Clinician rated  Time 4 Current GAF 60.81 (18.85) 61.82 (14.61)  PAS total composite 3.11 (1.32)* 2.24 (1.22) Note. ADHD = attention-deficit/hyperactivity disorder; ASR = Adult Self-Report; BASC = Behavior Assessment System for Children; BRIEF-A = Behavioral Rating Inventory for Executive Functioning-Adult version; GAF = Global Assessment of Functioning; GEC = Global Executive Composite; PAS = Premorbid Adjustment Scale; SAS-SR = Social Adjustment Scale-Self-Report; VABS-II = Vineland Adaptive Behavior Scales, Second Edition. * p < .05; ** p < .01. For the purposes of this study, we considered ADHD treatment status as positive if, at any point during the 9-year study, a parent reported that the individual with 22q11DS was prescribed an FDA-approved ADHD medication. The majority (82.4%) of individuals with 22q11DS + baseline ADHD were never treated with an FDA-approved ADHD medication. ADHD Status and Attrition Longitudinal retention rates are presented in Supplementary Figure S1 for both the 22q11DS-only and 22q11DS + baseline ADHD groups. A chi-square analysis indicated that there was not differential rates of attrition between the two groups, X2 (1) = .89, p = .345. Measures ADHD was assessed categorically via the childhood Schedule for Affective Disorders and Schizophrenia for School-Age Children—Present and Lifetime Version (K-SADS-PL) (Kaufman et al., 1997). A child and adolescent psychiatrist or clinical child psychologist administered the KSADS. Based on 12 videotaped interviews that were rated by both administrators, the kappa coefficient was .91, signifying good interrater reliability. ADHD symptoms were assessed dimensionally in childhood using the Behavior Assessment System for Children-Parent Rating Scale (BASC-PRS) (Reynolds & Kamphaus, 1992). Our young adult outcome variables were chosen a priori based on the idiopathic ADHD literature, which emphasizes that children with ADHD often lose their diagnosis in adulthood, yet remain symptomatic and impaired (Faraone, Biederman, & Mick, 2005). Parent Report Measures Time 1 BASC-PRS The BASC-PRS (Reynolds & Kamphaus, 1992) is a measure of parent-reported behaviors of children and adolescents rated on a four-point frequency scale from “Never” to “Almost always.” Responses are organized into nine clinical scales (Aggression, Anxiety, Attention Problems, Atypicality, Conduct Problems, Depression, Hyperactivity, Somatization, and Withdrawal), five adaptive behavior scales, and seven content scales. For the current study, only the Hyperactivity and Attention Problems scales were used. Item raw scores are transformed into T-scores (M = 50, SD = 10), with higher scores indicating more maladaptive behaviors. Time 4 Vineland Adaptive Behavior Scales, Second Edition, Composite Score The Vineland Adaptive Behavior Scales-2nd edition (VABS-II) (Sparrow, Cicchetti, & Balla, 2005) Parent/Caregiver Rating Form is a 297-item questionnaire rated on a three-point scale: 2 (usually), 1 (sometimes or partially), 0 (never), for which parents were asked to rate their adult child’s ability to independently perform behaviors across three skill domains: Communication, Daily Living, and Socialization. Standard scores (M = 100, SD = 15) are provided for each domain and a Total Composite, with higher scores indicating better functioning. For the current study, only the VABS-II Total Composite was used. Time 4 Behavior Rating Inventory of Executive Functioning-Adult Version The Behavior Rating Inventory of Executive Functioning-Adult (BRIEF-A) informant version (Roth, Isquith, & Gioia, 2006) is an standardized parent-report measure that assesses a collateral reporters’ view of an adults’ executive functioning in their everyday environment. The BRIEF-A contains 75 equivalently items that load onto nine subdomains. The Global Executive Composite (GEC) index represents the overall EF score and was used in this study. The GEC comprises items for emotional control, shifting, inhibition, self- and task monitoring, planning/organization, working memory, and initiation scales. Higher scores indicate less well-developed executive functioning skills. Clinician-Rated Measures Time 4 Global Assessment of Functioning The Global Assessment of Functioning (GAF) (APA, 2000) is a clinician-rated global measure of functioning ranging from 0 to 100. Clinicians use the GAF to subjectively rate patients on their social, academic, occupational, and psychological functioning, with higher scores representing better functioning. Time 4 Premorbid Adjustment Scale, Total Score The Premorbid Adjustment Scale (PAS) (Cannon-Spoor, Potkin, & Wyatt, 1982) is an interview-based, clinician-rated instrument used to assess functioning. The Total PAS score incorporates items pertaining to sociability, withdrawal, peer relationships, education, employment, establishment of independence, social–personal adjustment, degree of interest in life, and global assessment of highest level of functioning achieved thus far. These items contribute to the adulthood PAS Total score. Clinician ratings on PAS are scored on a 0–6 Likert scale, with 0 indicating typical adjustment and 6 indicating severe impairment. For the current study, only the adulthood PAS Total score was used. Self-Report Measures Time 4 BRIEF-A The BRIEF-A self-report version (Roth et al., 2006) was used to assess self-report of executive functioning in his/her everyday environment. Please see above for description of the BRIEF-A. The decision to administer both parent and self-report versions of the BRIEF-A is supported by the moderate association noted between parent- and self-report of global executive functioning (r = .34) and the stronger associations in the 22q11DS-only group (r = .52) relative to the 22q11DS + baseline ADHD group (r = .16). For the current study, only the BRIEF-A self-report GEC index was used. Time 4 Adult Self-Report The Adult Self-Report (ASR) (Achenbach & Rescorla, 2003) scale was used to assess the young adults with 22q11DSs’ opinions of their symptoms and functioning. The ASR consists of 123 statements that the adult indicates whether the behavior is not true, somewhat or sometimes true, or very or often true. These statements then load onto eight scales. Raw scores are transformed into T-scores for results interpretation. For the current study, only the Internalizing and Externalizing Composite T-scores were used. Time 4 Social Adjustment Scale-Self-Report The Social Adjustment Scale-Self-Report (SAS-SR) (Weissman, 1999) is a 54-item self-report scale that measures adjustment in social role areas: work, social, and leisure activities; relationships with extended family; and role as a spouse or partner, parental role, and role within the family unit. Mean scores are transformed into T-scores, whereby higher scores indicate more social impairment. For the current study, only the SAS-SR Total was used. Procedures Informed consent and assent were attained from parents and participants. At all four periods, a doctoral-level examiner administered all psychological tests to participants in a quiet room. Parents completed all parent-report rating scales in a separate room. The same measures were administered to all participants and their parents. Planned Analyses To investigate Aim 1 (categorical childhood ADHD diagnoses predict poorer young adult outcomes), and reduce Type 1 error rates, two omnibus multivariate analyses of covariance (MANCOVA) of young adult variables were used with ADHD as the independent variable. One MANCOVA used self-reports (SAS-SR, BRIEF-A, ASR) of young adult outcomes as dependent variables, and age as a covariate. A second MANCOVA used parent/clinician reports (BRIEF-A, VABS-II, PAS, GAF) of young adult outcomes as dependent variables, and age and available baseline parent/clinician reports as covariates. To investigate Aim 2 (dimensional ADHD symptoms predict to poorer outcomes in adulthood), stepwise regression analyses were computed entering baseline levels of the self and parent/clinician-report outcome variables in Step 1. In Step 2, parent report of child hyperactivity–impulsivity and inattention were entered simultaneously. Statistical Power Based on previous research on 22q11DS and ADHD (Antshel et al., 2013), we predicted moderate effect size differences for young adult outcomes between individuals with 22q11DS with and without childhood ADHD (Aim 1). Assuming 80% power to detect differences, two groups, two repetitions of the four repeated measures, a correlation across repeated measures of .3, and an alpha level of .05, a sample size of 46 was needed to attain adequate statistical power for our self-report MANCOVA. For the parent/clinician-report MANCOVA, a sample size of 59 was needed, because of the two repetitions of the six repeated measures. Thus, our Aim 1 self-report report analyses are adequately powered, whereas our parent/clinician analyses are slightly underpowered. Based on the extant ADHD research, which indicates childhood ADHD symptom severity levels are a predictor of adult outcomes with large effect sizes (Lara et al., 2009), we predicted a large effect size for our Aim 2 analyses. Assuming 80% power to detect differences, two predictors, and an alpha level of .05, a sample size of 42 was needed to attain adequate statistical power. Thus, our Aim 2 analyses are adequately powered. Results Aim 1—Categorical ADHD Diagnoses in Childhood Young Adult ASR On the ASR, SAS-SR, and BRIEF-A, after controlling for age, no differences emerged between the young adults with 22q11DS + baseline ADHD and those with 22q11DS only, Wilks λ = 0.81, F(6, 44) = 1.77, p = .126, η2 = .195. As noted in Table I, no differences emerged as a function of ADHD status. Parent/Clinician Reports After controlling for age and Time 1 variables as covariates, differences emerged between the two groups on parent/clinician report variables, Wilks λ = .75, F(4, 46) = 2.90, p = .036, η2 = .249. As noted in Table I, the BRIEF-A GEC parent report and PAS Total clinician report variables differed as a function of ADHD status. In both the parent and clinician report variables, those with 22q11DS + baseline ADHD were rated as functioning less well in young adulthood. Participants with 22q11DS + baseline ADHD did not differ at follow-up from those without baseline ADHD in adaptive functioning based on the parent report VABS-II or the clinician-rated GAF. See Table I for complete parent- or clinician-rated results. Aim 2—Dimensional ADHD Symptoms in Childhood Young Adult ASR Parent report of childhood hyperactivity–impulsivity and inattention did not predict young ASR BRIEF-A GEC, F(2, 49) = 2.82, p = .068, R2 = .114, ASR Internalizing ratings, F(2, 49) = 2.80, p = .071, R2 = .111, ASR Externalizing ratings, F(2, 49) = 2.52, p = .121, R2 = .107, or SAS-SR Total, F(2, 49) = 0.11, p = .900, R2 = .005. Parent/Clinician Reports Baseline VABS Composite positively predicted young adult VABS-II Composite, F(1, 47) = 23.48, p < .001, R2 = .353. After controlling for baseline VABS scores, BASC parent report of childhood hyperactivity–impulsivity and inattention did not predict parent report of adaptive behavioral abilities in young adults with 22q11DS, F(2, 45) = 2.66, p = .082, R2 change = .074. Baseline BRIEF GEC predicted young adult BRIEF-A GEC, F(1, 47) = 34.82, p < .001, R2 = .582. After controlling for baseline BRIEF GEC scores, BASC parent report of hyperactivity–impulsivity and inattention did not predict BRIEF-A GEC ratings in young adults with 22q11DS, F(2, 45) = 1.59, p = .225, R2 change = .051. Clinician-rated childhood GAF ratings predicted young adult GAF ratings, F(1, 47) = 5.13, p = .028, R2 = .100. After controlling for baseline GAF scores, parent report of childhood hyperactivity–impulsivity and inattention did not predict young adult GAF scores, F(2, 45) = .22, p = .801, R2 change = .009. Finally, childhood PAS Total ratings predicted young adult PAS Total ratings, F(1, 47) = 3.40, p = .047, R2 = .091. After controlling for baseline PAS Total scores, parent report of childhood hyperactivity–impulsivity and inattention did not predict young adult PAS Total scores, F(2, 45) = 1.55, p = .353, R2 change = .015. See Table II for relationships between parent, clinicians, and self-report of young adult outcome variables and parent-rated childhood hyperactivity–impulsivity and inattention. Table II. Associations Between Time 1 Parent Ratings of ADHD Symptoms and Time 4 Data Time 1 BASC Attention Problems Time 1 BASC Hyperactivity Parent report  Time 1 BASC  attention problems 1 .60**  Time 1 BASC hyperactivity .60** 1  Time 4 BRIEF-A GEC .55** .49**  Time 4 VABS-II Composite −.28 −.37 Clinician ratings  Time 4 Current GAF −.16 −.18  Time 4 PAS Total Composite .29 .32 Self-report  Time 4 BRIEF-A GEC .41** .41**  Time 4 SAS-SR Composite .04 .07  Time 4 ASR Internalizing .28 .31*  Time 4 ASR Externalizing .38** .42** Time 1 BASC Attention Problems Time 1 BASC Hyperactivity Parent report  Time 1 BASC  attention problems 1 .60**  Time 1 BASC hyperactivity .60** 1  Time 4 BRIEF-A GEC .55** .49**  Time 4 VABS-II Composite −.28 −.37 Clinician ratings  Time 4 Current GAF −.16 −.18  Time 4 PAS Total Composite .29 .32 Self-report  Time 4 BRIEF-A GEC .41** .41**  Time 4 SAS-SR Composite .04 .07  Time 4 ASR Internalizing .28 .31*  Time 4 ASR Externalizing .38** .42** Note. ADHA = attention-deficit/hyperactivity disorder; ASR = Adult Self-Report; BASC = Behavior Assessment System for Children; BRIEF-A = Behavioral Rating Inventory for Executive Functioning-Adult version; GAF = Global Assessment of Functioning; GEC = Global Executive Composite; PAS = Premorbid Adjustment Scale; SAS-SR = Social Adjustment; VABS-II = Vineland Adaptive Behavior Scales, Second Edition. * p < .05; ** p < .01. Table II. Associations Between Time 1 Parent Ratings of ADHD Symptoms and Time 4 Data Time 1 BASC Attention Problems Time 1 BASC Hyperactivity Parent report  Time 1 BASC  attention problems 1 .60**  Time 1 BASC hyperactivity .60** 1  Time 4 BRIEF-A GEC .55** .49**  Time 4 VABS-II Composite −.28 −.37 Clinician ratings  Time 4 Current GAF −.16 −.18  Time 4 PAS Total Composite .29 .32 Self-report  Time 4 BRIEF-A GEC .41** .41**  Time 4 SAS-SR Composite .04 .07  Time 4 ASR Internalizing .28 .31*  Time 4 ASR Externalizing .38** .42** Time 1 BASC Attention Problems Time 1 BASC Hyperactivity Parent report  Time 1 BASC  attention problems 1 .60**  Time 1 BASC hyperactivity .60** 1  Time 4 BRIEF-A GEC .55** .49**  Time 4 VABS-II Composite −.28 −.37 Clinician ratings  Time 4 Current GAF −.16 −.18  Time 4 PAS Total Composite .29 .32 Self-report  Time 4 BRIEF-A GEC .41** .41**  Time 4 SAS-SR Composite .04 .07  Time 4 ASR Internalizing .28 .31*  Time 4 ASR Externalizing .38** .42** Note. ADHA = attention-deficit/hyperactivity disorder; ASR = Adult Self-Report; BASC = Behavior Assessment System for Children; BRIEF-A = Behavioral Rating Inventory for Executive Functioning-Adult version; GAF = Global Assessment of Functioning; GEC = Global Executive Composite; PAS = Premorbid Adjustment Scale; SAS-SR = Social Adjustment; VABS-II = Vineland Adaptive Behavior Scales, Second Edition. * p < .05; ** p < .01. Discussion To our knowledge, this is the first study to use a longitudinal design to predict young adult outcomes in children with 22q11DS + baseline ADHD. Our childhood ADHD prevalence rate (44%) is consistent with what others have reported in 22q11DS (Schneider et al., 2014). Categorical and Dimensional ADHD After controlling for baseline parent report of executive dysfunction, parents of youth with 22q11DS + baseline ADHD reported that their young adult child had more executive dysfunction than did parents of young adults with 22q11DS only. Likewise, clinicians rated young adults with 22q11DS + baseline ADHD as having lower levels of overall functioning in young adulthood after controlling for baseline functioning. In this way, differences between the two 22q11DS groups became more pronounced over time. No group differences emerged on any self-report data. When considering ADHD symptoms dimensionally, after controlling for baseline levels of variables, parent report of childhood ADHD symptoms did not predict any clinician or parent report variables of adult functioning. Similarly, parent report of childhood ADHD symptoms did not predict young ASR. Others (Neely et al., 2016) have suggested that using both categorical and dimensional approaches to psychopathology is particularly important for youth with neurodevelopmental disorders. For predicting to young adult functional outcomes in 22q11DS, considering childhood ADHD as a categorical condition was a better predictor of young adult outcomes than a dimensional perspective. This finding argues against the notion that symptoms of inattention and hyperactivity–impulsivity are intrinsic to 22q11DS and therefore not worthy of further assessment or treatment. Our data suggest that such elevated symptoms, although common in individuals with 22q11DS (Ousley, Rockers, Dell, Coleman, & Cubells, 2007), may reflect a diagnosis of ADHD. Moreover, impairment secondary to ADHD symptoms is a criterion in the Diagnostic and statistical manual - 5th edition (DSM-5) (APA, 2013), and our data suggest that assigning a childhood ADHD diagnosis is meaningful and prognostic in youth with 22q11DS. If ADHD diagnoses were simply assigned to those with more severe ADHD symptoms, results in the dimensional analyses would have mirrored the categorical analyses. In contrast, a childhood diagnosis of ADHD (and not simply levels of ADHD symptoms in this population) was predictive of outcomes in 22q11DS. Our data are also consistent with longitudinal research on idiopathic ADHD that suggests that childhood ADHD is associated with young adult outcomes including executive dysfunction (Biederman et al., 2007) and lower levels of functional independence (Barkley, Fischer, Smallish, & Fletcher, 2006). Thus, our results of ADHD in the context of developmental delays mirror the idiopathic ADHD research results (which often exclude those with IQs < 80 from participation). While two group differences emerged between the two 22q11DS groups in young adulthood, multiple young adult measures were not different between the two groups. Likewise, no self-report differences on any young adult variable emerged between the 22q11DS groups. Although some young adult outcomes are negatively affected by the presence of childhood ADHD, multiple other outcomes are not impacted significantly by ADHD. Rather, having developmental delays, as is common in 22q11DS (Antshel et al., 2007), appears to be more impactful toward predicting young adult outcomes in some domains. Parent and Young Adult Perceptions Parent report and self-report of functioning were moderately associated with each other, yet were more strongly related in the 22q11DS-only group. Parents report more concerns about functioning than young adults with 22q11DS, both with and without ADHD. While parent and child reports of child functioning often differ (Kolko & Kazdin, 1993), young adults with 22q11DS do not perceive themselves as experiencing difficulties when compared with their same aged peers. One possible explanation for this finding may be related to cognitive immaturity (Milich, 1994). Cognitive immaturity has been forwarded as a hypothesis to explain the positive self-perceptions that exist in ADHD (Owens, Goldfine, Evangelista, Hoza, & Kaiser, 2007). Our 22q11DS sample, both with and without ADHD, had mean IQs in the Borderline range for age. Thus, it is possible that developmental delays led to poor self-monitoring, which led to parents reporting lower functioning than self-report. However, others (Swanson, Owens, & Hinshaw, 2012) have encouraged researchers not to assume that parents are correct (and children are incorrect). ADHD Treatment in 22q11DS The majority of individuals with 22q11DS + baseline ADHD were never treated with an FDA-approved ADHD medication. Our low ADHD treatment rates are consistent with previous evidence that suggests low treatment rates (between 60 and 80% are not treated) for 22q11DS and comorbid psychiatric disorders (not specific to ADHD) (Tang et al., 2014). In 22q11DS, parents made decisions to not pursue an FDA-approved ADHD medication for their child with ADHD. There are likely a variety of reasons for these decisions. Future research, using a qualitative design, should investigate the pharmacotherapy decision-making processes for parents of youth with 22q11DS + baseline ADHD. In conjunction with previous research that stimulant medication is safe and effective for use in individuals with 22q11DS (Gothelf et al., 2003), these results indicate that the low rate of treatment in this population merits further consideration. Comorbid ADHD affects clinician and parent-report variables of adult functioning above and beyond the effects of developmental delays inherent to 22q11DS, yet may still be undertreated. Limitations While many of our analyses would not have survived a Bonferroni correction, our effect sizes are uniformly large, and we used MANCOVA designs (reducing the chance of type I error). Thus, we believe that these results likely represent the most robust differences between 22q11DS groups. Other real differences (with small to medium effect sizes) may exist, yet did not reach the p < .05 criterion. The lack of an IQ-matched control group is an additional limitation. Thus, the specificity of these results to 22q11DS + baseline ADHD is not presently known. Future Directions and Conclusion Comorbid childhood ADHD as a categorical diagnosis is a significant predictor of parent report of executive dysfunction and clinician ratings of functioning 9-years later and predicted more young adult outcomes than considering childhood ADHD symptoms dimensionally. This suggests that DSM-5 Criterion D (impairment secondary to ADHD symptoms) is particularly important to consider in youth with developmental delays. Further research is needed to understand the mechanisms that may be responsible for these concerning long-term trajectories. Considering environmental factors (e.g., family, peer group) and the interaction of these factors with biological variables will likely prove most informative. Despite several significant negative long-term outcomes, most individuals with 22q11DS + baseline ADHD were never treated with an FDA-approved medication. Given the low rate of pharmacological treatment for this population, despite some evidence for the efficacy (Gothelf et al., 2003), future research should consider how best to increase the use of ADHD evidence-based interventions, both pharmacological and nonpharmacological, in 22q11DS. In the idiopathic ADHD literature, parental lack of knowledge and misconceptions about ADHD and poor symptom recognition are barriers to treatment for children with ADHD (Bussing, Zima, Gary, & Garvan, 2003). These barriers may also affect children with 22q11DS + baseline ADHD. For example, low knowledge of ADHD and poor symptom recognition may exist in 22q11DS via diagnostic overshadowing. In diagnostic overshadowing, symptoms of one condition (ADHD) are ascribed to a secondary condition (22q11DS) (Jopp & Keys, 2001). If a condition is not believed to exist or be valid, that condition is less likely to be treated (O'Brien, Kifuji, & Summergrad, 2006). Further, parents of individuals with 22q11DS report concerns about cardiac effects and fear increased risk of psychosis as a function of stimulant use (Green et al., 2011), despite some evidence to suggest that stimulant medication is safe and effective for use in this population (Gothelf et al., 2003). Future research should consider the barriers for ADHD treatment in the 22q11DS population as well as how to address these barriers. In summary, ADHD predicts several poor outcomes above and beyond the negative outcomes associated with 22q11DS. To the extent that ADHD remains undertreated and underresearched in 22q11DS, a significant portion of individuals with 22q11DS may endure several negative long-term outcomes that may be potentially modifiable with treatment. Supplementary Data Supplementary data can be found at: http://www.jpepsy.oxfordjournals.org/. Funding This work was supported by the National Institutes of Health (grant number R01MH064824). Conflicts of interest: None declared. References Achenbach T. M. , Rescorla L. A. ( 2003 ). Manual for the ASEBA adult forms and profiles . Burlington, VT : University of Vermont . Antshel K. M. , Faraone S. V. , Fremont W. , Monuteaux M. C. , Kates W. R. , Doyle A. , Mick E. , Biederman J. ( 2007 ). Comparing ADHD in velocardiofacial syndrome to idiopathic ADHD. A preliminary study . Journal of Attention Disorders , 11 , 64 – 73 . doi: 10.1177/1087054707299397 Google Scholar CrossRef Search ADS PubMed Antshel K. M. , Hendricks K. , Shprintzen R. , Fremont W. , Higgins A. M. , Faraone S. V. , Kates W. R. ( 2013 ). The longitudinal course of attention deficit/hyperactivity disorder in velo-cardio-facial syndrome . Journal of Pediatrics , 163 , 187 – 193 . doi: 10.1016/j.jpeds.2012.12.026 Google Scholar CrossRef Search ADS PubMed Antshel K. M. , Phillips M. H. , Gordon M. , Barkley R. , Faraone S. V. ( 2006 ). Is ADHD a valid disorder in children with intellectual delays? Clinical Psychology Review , 26 , 555 – 572 . Google Scholar CrossRef Search ADS PubMed APA . ( 2000 ). Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) ( 4th ed. ). Washington, DC : American Psychiatric Association . APA . ( 2013 ). Diagnostic and Statistical Manual of Mental Disorders ( 5th ed. ). Washington, DC : American Psychiatric Publishing . Barkley R. , Fischer M. , Smallish L. , Fletcher K. ( 2006 ). Young adult outcome of hyperactive children: Adaptive functioning in major life activities . Journal of the American Academy of Child and Adolescent Psychiatry , 45 , 192 – 202 . Google Scholar CrossRef Search ADS PubMed Biederman J. , Petty C. R. , Fried R. , Doyle A. E. , Spencer T. , Seidman L. J. , Gross L. , Poetzl K. , Faraone S. V. ( 2007 ). Stability of executive function deficits into young adult years: A prospective longitudinal follow-up study of grown up males with ADHD . Acta Psychiatrica Scandinavica , 116 , 129 – 136 . doi: 10.1111/j.1600-0447.2007.01008.x Google Scholar CrossRef Search ADS PubMed Botto L. D. , May K. , Fernhoff P. M. , Correa A. , Coleman K. , Rasmussen S. A. , Merritt R. K. , O'Leary L. A. , Wong L. Y. , Elixson E. M. , Mahle W. T. , Campbell R. M. ( 2003 ). A population-based study of the 22q11.2 deletion: Phenotype, incidence, and contribution to major birth defects in the population . Pediatrics , 112 , 101 – 107 . Google Scholar CrossRef Search ADS PubMed Bussing R. , Zima B. T. , Gary F. A. , Garvan C. W. ( 2003 ). Barriers to detection, help-seeking, and service use for children wit ADHD symptoms . The Journal of Behavioral Health Services and Research , 30 , 176 – 189 . Google Scholar CrossRef Search ADS PubMed Cannon-Spoor H. E. , Potkin S. G. , Wyatt R. J. ( 1982 ). Measurement of premorbid adjustment in chronic schizophrenia . Schizophrenia Bulletin , 8 , 470 – 484 . http://dx.doi.org/10.1093/schbul/8.3.470 Google Scholar CrossRef Search ADS PubMed de Schipper E. , Lundequist A. , Wilteus A. L. , Coghill D. , de Vries P. J. , Granlund M. , Holtmann M. , Jonsson U. , Karande S. , Levy F. , Al-Modayfer O. , Rohde L. , Tannock R. , Tonge B. , Bölte S. ( 2015 ). A comprehensive scoping review of ability and disability in ADHD using the International Clssification of Functioning, Disability, and Health-Children and Youth Version (ICF-CY) . European Child and Adolscent Psychiatry , 24 , 859 – 871 . doi: 10.1007/s00787-015-0727-z Google Scholar CrossRef Search ADS Faraone S. V. , Asherson P. , Banaschewski T. , Biederman J. , Buitelaar J. K. , Ramos-Quiroga J. A. , Rohde L. A. , Sonuga-Barke E. J. , Tannock R. , Franke B. ( 2015 ). Attention-deficit/hyperactivity disorder . Nature Reviews Disease Primers , 1 , 15 – 20 . doi: 10.1038/nrdp.2015.20 Faraone S. V. , Biederman J. , Mick E. ( 2005 ). The age-dependent decline of attention deficit hyperactivity disorder: A meta-analysis of follow-up studies . Psychological Medicine , 36 , 159 – 165 . http://dx.doi.org/10.1017/S003329170500471X Google Scholar CrossRef Search ADS Gothelf D. , Gruber R. , Presburger G. , Dotan I. , Brand-Gothelf A. , Burg M. , Inbar D. , Steinberg T. , Frisch A. , Apter A. , Weizman A. ( 2003 ). Methylphenidate treatment for attention-deficit/hyperactivity disorder in children and adolescents with velocardiofacial syndrome: An open-label study . Journal of Clinical Psychiatry , 64 , 1163 – 1169 . Google Scholar CrossRef Search ADS PubMed Green T. , Weinberger R. , Diamond A. , Berant M. , Hirschfeld L. , Frisch A. , Zarchi O. , Weizman A. , Gothelf D. ( 2011 ). The effect of methylphenidate on prefrontal cognitive functioning, inattention, and hyperactivity in velocardiofacial syndrome . Journal of Child and Adolescent Psychopharmacology , 21 , 589 – 595 . doi: 10.1089/cap.2011.0042 Google Scholar CrossRef Search ADS PubMed Hurtig T. , Ebeling H. , Taanila A. , Miettunen J. , Smalley S. , McGough J. , Loo S. K. , Järvelin M. R. , Moilanen I. ( 2007 ). ADHD symptoms and subtypes: Relationship between childhood and adolescent symptoms . Journal of the American Academy of Child and Adolescent Psychiatry , 46 , 1605 – 1613 . Google Scholar CrossRef Search ADS PubMed Jopp D. A. , Keys C. B. ( 2001 ). Diagnostic overshadowing reviewed and reconsidered . American Journal of Mental Retardation , 106 , 416 – 433 . doi: 10.1352/0895-80172001 Google Scholar CrossRef Search ADS PubMed Kaufman J. , Birmaher B. , Brent D. , Rao U. M. A. , Flynn C. , Moreci P. , Williamson D. , Ryan N. ( 1997 ). Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): Initial reliability and validity data . Journal of the American Academy of Child & Adolescent Psychiatry , 36 , 980 – 989 . Google Scholar CrossRef Search ADS Kolko D. J. , Kazdin A. E. ( 1993 ). Emotional/behavioral problems in clinic and nonclinic children: Correspondence among child, parent and teacher reports . Journal of Child Psychology and Psychiatry and Allied Disciplines , 34 , 991 – 1006 . Google Scholar CrossRef Search ADS Lara C. , Fayyad J. , de Graaf R. , Kessler R. C. , Aguilar-Gaxiola S. , Angermeyer M. , Demytteneare K. , de Girolamo G. , Haro J. M. , Jin R. , Karam E. G. , Lépine J. P. , Mora M. E. , Ormel J. , Posada-Villa J. , Sampson N. ( 2009 ). Childhood predictors of adult attention-deficit/hyperactivity disorder: Results from the World Health Organization World Mental Health Survey Initiative . Biological Psychiatry , 65 , 46 – 54 . Google Scholar CrossRef Search ADS PubMed Lo-Castro A. , D'Agati E. , Curatolo P. ( 2011 ). ADHD and genetic syndromes . Brain and Development , 33 , 456 – 461 . doi: 10.1016/j.braindev.2010.05.011 Google Scholar CrossRef Search ADS PubMed Mackenzie G. B. , Wonders E. ( 2016 ). Rethinking intelligence quotient exclusion criteria practices in the study of attention deficit hyperactivity disorder . Frontiers in Psychology , 7 , 794. doi: 10.3389/fpsyg.2016.00794 Google Scholar CrossRef Search ADS PubMed Milich R. ( 1994 ). The response of children with ADHD to failure: If at first you don't succeed, do you try, try again? School Psychology Review , 23 , 11 – 28 . Neely R. J. , Green J. L. , Sciberras E. , Hazell P. , Anderson V. ( 2016 ). Relationship between executive functioning and symptoms of attention-deficit/hyperactivity disorder and Autism spectrum disorder in 6-8 year old children . Journal of Autism and Developmental Disorders , 46 , 3270 – 3280 . doi: 10.1007/s10803-016-2874-6. Google Scholar CrossRef Search ADS PubMed O'Brien R. F. , Kifuji K. , Summergrad P. ( 2006 ). Medical conditions with psychiatric manifestations . Adolescent Medicine Clinics , 17 , 49 – 77 . doi: 10.1016/j.admecli.2005.10.007 Google Scholar PubMed Ousley O. , Rockers K. , Dell M. , Coleman K. , Cubells J. F. ( 2007 ). A review of neurocognitive and behavioral profiles associated with 22q11 deletion syndrome: Implications for clinical evaluation and treatment . Current Psychiatry Reports , 9 , 148 – 158 . doi: 10.1007/s11920-007-0085-8 Google Scholar CrossRef Search ADS PubMed Owens J. S. , Goldfine M. E. , Evangelista N. M. , Hoza B. , Kaiser N. M. ( 2007 ). A critical review of self-perceptions and the positive illusory bias in children with ADHD . Clinical Child and Family Psychology Review , 10 , 335 – 351 . Google Scholar CrossRef Search ADS PubMed Philip N. , Bassett A. ( 2011 ). Cognitive, behavioural and psychiatric phenotype in 22q11.2 deletion syndrome . Behavavioral Genetics , 41 , 403 – 412 . doi: 10.1007/s10519-011-9468-z Google Scholar CrossRef Search ADS Reynolds C. R. , Kamphaus R. W. ( 1992 ). Behavior Assessment Scales for Children (BASC) . Circle Pines, MN : American Guidance Service . Roth R. M. , Isquith P. K. , Gioia G. ( 2006 ). Behavior Rating Inventory of Executive Function®–Adult Version (BRIEF-A) . Lutz, FL : Psychological Assessment Resources . Schneider M. , Debbané M. , Bassett A. S. , Chow E. W. C. , Fung W. L. A. , van den Bree M. B. M. , Murphy K. C. , Niarchou M. , Kates W. R. , Antshel K. M. , Fremont W. , McDonald-McGinn D. M. , Gur R. E. , Zackai E. H. , Vorstman J. , Duijff S. N. , Klaassen P. W. , Swillen A. , Gothelf D. , Green T. , Weizman A. , Van Amelsvoort T. , Evers L. , Boot E. , Shashi V. , Hooper S. R. , Bearden C. E. , Jalbrzikowski M. , Armando M. , Vicari S. , Murphy D. G. , Ousley O. , Campbell L. E. , Simon T. J. , Eliez S. ( 2014 ). Psychiatric disorders from childhood to adulthood in 22q11.2 deletion syndrome: Results from the International Consortium on Brain and Behavior in 22q11.2 Deletion Syndrome . American Journal of Psychiatry , 171 , 627 – 639 . doi: 10.1176/appi.ajp. Google Scholar CrossRef Search ADS PubMed Shprintzen R. J. , Higgins A. M. , Antshel K. , Fremont W. , Roizen N. , Kates W. ( 2005 ). Velo-cardio-facial syndrome . Current Opinion in Pediatrics , 17 , 725 – 730 . Google Scholar CrossRef Search ADS PubMed Shprintzen R. J. ( 2000 ). Velo-cardio-facial syndrome: A distinctive behavioral phenotype . Mental Retardation and Developmental Disabilities Research Reviews , 6 , 142 – 2779 . http://dx.doi.org/10.1002/1098-2779(2000)6:2<142::AID-MRDD9>3.0.CO;2-H Google Scholar CrossRef Search ADS PubMed Sparrow S. , Cicchetti D. , Balla D. ( 2005 ). Vineland Adaptive Behavior Scales (Vineland-II) ( 2nd ed. ). San Antonio, TX : Pearson Education . Spencer T. , Biederman J. , Mick E. ( 2007 ). Attention-deficit/hyperactivity disorder: Diagnosis, lifespan, comorbidities, and neurobiology . Journal of Pediatric Psychology , 32 , 631 – 642 . doi: 10.1093/jpepsy/jsm005 Google Scholar CrossRef Search ADS PubMed Swanson E. N. , Owens E. B. , Hinshaw S. P. ( 2012 ). Is the positive illusory bias illusory? Examining discrepant self-perceptions of competence in girls with ADHD . Journal of Abnormal Child Psychology , 40 , 987 – 998 . doi: 10.1007/s10802-012-9615-x Google Scholar CrossRef Search ADS PubMed Tang S. X. , Yi J. J. , Calkins M. E. , Whinna D. A. , Kohler C. G. , Souders M. C. , McDonald-McGinn D. M. , Zackai E. H. , Emanuel B. S. , Gur R. C. , Gur R. E. ( 2014 ). Psychiatric disorders in 22q11.2 deletion syndrome are prevalent but undertreated . Psychological Medicine , 44 , 1267 – 1277 . doi: 10.1017/S0033291713001669 Google Scholar CrossRef Search ADS PubMed Weissman M. M. ( 1999 ). Social Adjustment Scale- Self-report (SAS-SR) User’s Manual . North Tonawanda, NY : Multi-Health Systems, Inc . © The Author(s) 2018. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Pediatric Psychology Oxford University Press

Young Adult Outcomes for Children With 22q11 Deletion Syndrome and Comorbid ADHD

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Abstract

Abstract Background 22q11.2 deletion syndrome (22q11DS) is a common microdeletion syndrome associated with a variety of negative health, cognitive, emotional, and behavioral outcomes. 22q11DS is comorbid with many psychiatric disorders including attention-deficit/hyperactivity disorder (ADHD). The current study aimed to investigate the cognitive, behavioral, and functional outcomes that a childhood ADHD diagnosis predicts to in adulthood. Methods This longitudinal study followed 52 individuals with 22q11DS over 9 years. Childhood ADHD was operationalized both categorically (Diagnostic and statistical manual - 4th edition (DSM-IV) ADHD diagnoses) and dimensionally (inattentive and hyperactive–impulsive symptoms) and was tested as predictors of young adult outcomes. Results As young adults, children with 22q11DS + baseline ADHD had more parent-reported executive dysfunction and lower levels of clinician-rated overall functioning than those with 22q11DS yet without ADHD. Dimensional symptoms of ADHD in childhood did not predict young adult outcomes. No self-report differences emerged between those with and without baseline ADHD. The majority (82.4%) of individuals with 22q11DS + baseline ADHD were never treated with an ADHD medication. Conclusions A categorical diagnosis of ADHD in childhood predicted a greater variety of worse outcomes than dimensional levels of ADHD symptoms. Despite the significant impact of comorbid ADHD in 22q11DS, evidence-based treatment rates were low. 22q11.2 deletion syndrome, ADHD, developmental delay, longitudinal 22q11.2 deletion syndrome (22q11DS), also known as velo-cardio-facial syndrome, is the most common identified microdeletion syndrome and is caused by an interstitial deletion from chromosome at the 22q11.2 band. In most cases, 22q11DS is caused by a deletion of 3 million base pairs of DNA encompassing 40–50 genes. The majority (90%) of 22q11.2 deletions are de novo (Shprintzen et al., 2005). 22q11DS is relatively common, occurring in ∼1:5,950 births (Botto et al., 2003). Heart malformations and cleft palate are common characteristics of 22q11DS; yet, not all individuals demonstrate either (Shprintzen, 2000). Many individuals with 22q11DS have cognitive impairments, with IQs generally 1–2 SDs below the mean for age (Antshel et al., 2007). While a specific mechanism has not been definitively identified, several of the genes that are deleted on one copy of chromosome 22q11.2 are thought to contribute to cognitive impairments observed in 22q11DS (Philip & Bassett, 2011). In addition to cognitive impairments, 22q11DS is associated with a variety of psychiatric comorbidities. Attention-deficit/hyperactivity disorder (ADHD), major depressive disorder, anxiety disorders, oppositional defiant disorder, and autism spectrum disorder are all comorbid with 22q11DS (Schneider et al., 2014). Further, individuals with 22q11DS are at increased risk for psychiatric comorbidities in adulthood, in particular schizophrenia (Schneider et al., 2014). These psychiatric comorbidities likely present challenges for individuals with 22q11DS and their families beyond what is imparted by 22q11DS, although this research question has not been systematically studied (Schneider et al., 2014). Attention-Deficit/Hyperactivity Disorder ADHD is one of the most prevalent comorbid disorders in individuals with 22q11DS (Schneider et al., 2014). Approximately 4–12% of children without 22q11DS are diagnosed with ADHD (Spencer, Biederman, & Mick, 2007). The prevalence rate of ADHD in 22q11DS is roughly 5-fold higher (30–40%) than the prevalence rate of ADHD in the general population (Schneider et al., 2014). In non-22q11DS cross-sectional samples, ADHD negatively affects academic, occupational, social, and emotional functioning (de Schipper et al., 2015). Longitudinally, children with ADHD are at greater risk for difficulties in late adolescence and early adulthood, including school failure, emotional difficulties, dysfunctional relationships, legal problems, substance abuse, and occupational difficulties (Spencer et al., 2007). Thus, an ADHD diagnosis is a concern both in childhood and young adulthood. In the only longitudinal study to date that has investigated ADHD in 22q11DS, Antshel and colleagues (2013) followed children with 22q11DS both with and without ADHD into adolescence. The developmental trajectories of those with 22q11DS were compared with control children with ADHD. Results indicated that children with 22q11DS and ADHD (22q11DS + ADHD) experienced largely similar longitudinal trajectories to control children with ADHD. Hyperactivity–impulsivity symptoms in the 22q11DS + ADHD group, however, increased over time, a finding contrary to the literature on idiopathic ADHD (Spencer et al., 2007). The developmental delays in the 22q11DS and ADHD group and the low pharmacotherapy use in the 22q11DS population may explain this finding (Tang et al., 2014). Individuals with 22q11DS + ADHD were at increased risk for oppositional defiant disorder, at similar rates to those with idiopathic ADHD, both of which are higher than individuals with 22q11DS only (Antshel et al., 2013). However, mood and anxiety disorders were no more prevalent in 22q11DS + ADHD than in individuals with 22q11DS only (Antshel et al., 2013), contrary to idiopathic ADHD research (Spencer et al., 2007). Similar to idiopathic ADHD (Hurtig et al., 2007), major depression predicted ADHD persistence in the 22q11DS population (Antshel et al., 2013). Overall, this study provided evidence that childhood factors that predict ADHD persistence in non-22q11DS populations predict persistence in individuals with 22q11DS, with few exceptions. Presently, the Antshel and colleagues study is the only study that has considered the longitudinal course of children with 22q11DS + ADHD. This study is limited principally by the short follow-up period (3 years). Need for Current Study The persistence of ADHD into adulthood has been empirically supported, both dimensionally along a continuum representing elevated symptoms and as a categorical diagnosis (ADHD vs. non-ADHD) (Faraone et al., 2015). Nevertheless, the developmental trajectories for children with ADHD are heterogeneous (Spencer et al., 2007). Efforts to understand developmental trajectories are needed, especially in populations of children with ADHD and an additional childhood developmental disorder (like 22q11DS). ADHD is frequently comorbid with other childhood developmental disorders besides 22q11DS (Spencer et al., 2007). Investigating adult outcomes of childhood ADHD in developmentally delayed populations is important for several reasons. First, this information can be clinically useful and provide guidance about longitudinal outcomes for clinicians and parents. For example, ADHD is comorbid with a variety of other genetic, medical, and neurodevelopmental conditions, including fragile X syndrome, Williams syndrome, and Klinefelter syndrome (Lo-Castro, D'Agati, & Curatolo, 2011). However, we know little about the longitudinal course of ADHD in 22q11DS. Second, lower intelligence predicts ADHD persistence and impairments in adulthood (Faraone et al., 2015); yet, most studies on ADHD exclude those with an IQ <80 (Mackenzie & Wonders, 2016). Thus, we do not know the longitudinal outcomes of individuals with ADHD who have IQs <80. Third, given that many youth with developmental delays are inattentive and restless (Lo-Castro et al. 2011), there is risk for both overdiagnosis and underdiagnosis of ADHD in these children (Antshel, Phillips, Gordon, Barkley, & Faraone, 2006). Following children with ADHD and developmental delays longitudinally would ultimately inform clinical practice by elucidating the extent to which a childhood ADHD diagnosis is a meaningful predictor of adult outcomes. Antshel and colleagues’ (2013) examination of the longitudinal course of ADHD in the 22q11DS population suggests that childhood ADHD in 22q11DS is of concern into adolescence, but the functional consequences of childhood ADHD into young adulthood are, as of yet, unknown. Rather than focus on ADHD diagnostic continuity from childhood into adulthood, this study investigated whether behavioral and functional outcomes would worsen over time for children with 22q11DS and ADHD. Based on the idiopathic ADHD literature, we hypothesized that a childhood ADHD diagnosis in 22q11DS (22q11DS + baseline ADHD) would predict to poorer behavioral and functional outcomes in young adulthood compared with those with 22q11DS, yet no ADHD (22q11DS only) even after controlling for childhood levels of these variables. Aim 1 tested this hypothesis by examining whether a categorical diagnosis of childhood ADHD predicted behavioral and functional outcomes in adulthood for children with 22q11DS. Given the controversies about ADHD diagnoses in individuals with developmental disorders (Antshel et al., 2006), Aim 2 tested this hypothesis by examining whether continuous, dimensional measures of childhood ADHD symptoms (i.e., inattentive, hyperactive–impulsive symptoms) predicted behavioral and functional outcomes in adulthood. Others (Neely, Green, Sciberras, Hazell, & Anderson, 2016) have suggested that using both categorical and dimensional approaches is particularly important for youth with neurodevelopmental disorders. Method Participants This 9-year longitudinal study followed individuals with 22q11DS every 3 years; thus, four time points (baseline, Year 3, Year 6, and Year 9) were included in the larger study. Children with 22q11DS were initially recruited from a large academic medical center in the northeastern United States during the years 2002–2005. All families that met inclusion criteria agreed to participate. Only those children with a fluorescence in situ hybridization-confirmed deletion of 22q11.2 were included. Children with an identifiable genetic disorder (other than 22q11DS) or children with an identifiable neurological condition (e.g., traumatic brain injury, preterm birth) that is known to affect cognitive or psychiatric function were excluded from participation. For the current project, only participants who had Time 4 (young adult) data and who also had baseline data were included. Our total sample consisted of 52 children with 22q11DS (28 males). At baseline, the average age of individuals with 22q11DS was 12.2 years (SD = 2.3), and at Time 4, the average age of 22q11DS participants was 21.3 years (SD = 2.2). Sample Representativeness Given that we imposed strict participation criteria (requiring both baseline and Time 4 data), not all participants in the larger study are included in our analyses. Thus, we compared our study subsample with all individuals who participated at baseline: participants in the current study did not differ on any relevant Time 1 sociodemographic measures, including participant age F(1, 78) = .003, p = .963, gender X2 (1) = .061, p = .831 or socioeconomic status F(1, 78) = 2.01, p = .165. Likewise, participants in the current project did not differ from those from the larger project on any relevant social and cognitive measures, including baseline adaptive functioning F(1, 78) = .531, p = .792 or IQ F(1, 78) = .316, p = .664. Thus, the current study participants appear to be representative of the larger project sample. ADHD Status At baseline (childhood), 23 of the 52 individuals with 22q11DS met formal Diagnostic and statistical manual - 4th edition (DSM-IV) diagnostic criteria for ADHD based on a structured psychiatric interview with the participants’ parents. This prevalence rate (44%) is similar to what others have reported in the literature (Schneider et al., 2014). Sex differences between the two 22q11DS groups approached significance, X2 (1) = 3.68, p = .055 in that more males were diagnosed with ADHD. Age differences existed between the two 22q11DS groups at both baseline, F(1, 51) = 4.00, p = .050, and young adulthood, F(1, 51) = 4.13, p = .047. At both periods, participants with 22q11DS + baseline ADHD were slightly younger than those with 22q11DS only. Given the age differences between the two 22q11DS groups, analyses comparing the two 22q11DS groups will control for the effects of age. Please see Table I for descriptive data. Table I. Baseline and Young Adulthood Data 22q11DS + ADHD 22q11DS only N 23 29 Time 1 Time 1 Age 11.67 (2.01)* 12.79 (2.46) Gender (% female) 8 (34.8) 16 (55.2) Time 1 BASC Hyperactivity 62.80 (15.62)* 54.80 (12.96) Time 1 BASC Attention Problems 67.24 (10.61)** 59.28 (9.42) Time 4 Time 4 Age 20.5 (1.5)* 21.7 (2.1) Self-report  Time 4 Self-Report BRIEF-A GEC 58.44 (13.05) 55.00 (13.06)  Time 4 ASR Internalizing Composite 56.40 (10.76) 58.71 (16.19)  Time 4 ASR Externalizing Composite 55.83 (14.35) 54.57 (10.31)  Time 4 SAS-SR Total Composite 59.82 (11.10) 62.75 (14.79) Parent report  Time 4 VABS-II Composite 65.85 (11.64) 67.00 (12.77)  Time 4 Parent Report BRIEF-A GEC 64.43 (10.66)** 55.51 (12.58) Clinician rated  Time 4 Current GAF 60.81 (18.85) 61.82 (14.61)  PAS total composite 3.11 (1.32)* 2.24 (1.22) 22q11DS + ADHD 22q11DS only N 23 29 Time 1 Time 1 Age 11.67 (2.01)* 12.79 (2.46) Gender (% female) 8 (34.8) 16 (55.2) Time 1 BASC Hyperactivity 62.80 (15.62)* 54.80 (12.96) Time 1 BASC Attention Problems 67.24 (10.61)** 59.28 (9.42) Time 4 Time 4 Age 20.5 (1.5)* 21.7 (2.1) Self-report  Time 4 Self-Report BRIEF-A GEC 58.44 (13.05) 55.00 (13.06)  Time 4 ASR Internalizing Composite 56.40 (10.76) 58.71 (16.19)  Time 4 ASR Externalizing Composite 55.83 (14.35) 54.57 (10.31)  Time 4 SAS-SR Total Composite 59.82 (11.10) 62.75 (14.79) Parent report  Time 4 VABS-II Composite 65.85 (11.64) 67.00 (12.77)  Time 4 Parent Report BRIEF-A GEC 64.43 (10.66)** 55.51 (12.58) Clinician rated  Time 4 Current GAF 60.81 (18.85) 61.82 (14.61)  PAS total composite 3.11 (1.32)* 2.24 (1.22) Note. ADHD = attention-deficit/hyperactivity disorder; ASR = Adult Self-Report; BASC = Behavior Assessment System for Children; BRIEF-A = Behavioral Rating Inventory for Executive Functioning-Adult version; GAF = Global Assessment of Functioning; GEC = Global Executive Composite; PAS = Premorbid Adjustment Scale; SAS-SR = Social Adjustment Scale-Self-Report; VABS-II = Vineland Adaptive Behavior Scales, Second Edition. * p < .05; ** p < .01. Table I. Baseline and Young Adulthood Data 22q11DS + ADHD 22q11DS only N 23 29 Time 1 Time 1 Age 11.67 (2.01)* 12.79 (2.46) Gender (% female) 8 (34.8) 16 (55.2) Time 1 BASC Hyperactivity 62.80 (15.62)* 54.80 (12.96) Time 1 BASC Attention Problems 67.24 (10.61)** 59.28 (9.42) Time 4 Time 4 Age 20.5 (1.5)* 21.7 (2.1) Self-report  Time 4 Self-Report BRIEF-A GEC 58.44 (13.05) 55.00 (13.06)  Time 4 ASR Internalizing Composite 56.40 (10.76) 58.71 (16.19)  Time 4 ASR Externalizing Composite 55.83 (14.35) 54.57 (10.31)  Time 4 SAS-SR Total Composite 59.82 (11.10) 62.75 (14.79) Parent report  Time 4 VABS-II Composite 65.85 (11.64) 67.00 (12.77)  Time 4 Parent Report BRIEF-A GEC 64.43 (10.66)** 55.51 (12.58) Clinician rated  Time 4 Current GAF 60.81 (18.85) 61.82 (14.61)  PAS total composite 3.11 (1.32)* 2.24 (1.22) 22q11DS + ADHD 22q11DS only N 23 29 Time 1 Time 1 Age 11.67 (2.01)* 12.79 (2.46) Gender (% female) 8 (34.8) 16 (55.2) Time 1 BASC Hyperactivity 62.80 (15.62)* 54.80 (12.96) Time 1 BASC Attention Problems 67.24 (10.61)** 59.28 (9.42) Time 4 Time 4 Age 20.5 (1.5)* 21.7 (2.1) Self-report  Time 4 Self-Report BRIEF-A GEC 58.44 (13.05) 55.00 (13.06)  Time 4 ASR Internalizing Composite 56.40 (10.76) 58.71 (16.19)  Time 4 ASR Externalizing Composite 55.83 (14.35) 54.57 (10.31)  Time 4 SAS-SR Total Composite 59.82 (11.10) 62.75 (14.79) Parent report  Time 4 VABS-II Composite 65.85 (11.64) 67.00 (12.77)  Time 4 Parent Report BRIEF-A GEC 64.43 (10.66)** 55.51 (12.58) Clinician rated  Time 4 Current GAF 60.81 (18.85) 61.82 (14.61)  PAS total composite 3.11 (1.32)* 2.24 (1.22) Note. ADHD = attention-deficit/hyperactivity disorder; ASR = Adult Self-Report; BASC = Behavior Assessment System for Children; BRIEF-A = Behavioral Rating Inventory for Executive Functioning-Adult version; GAF = Global Assessment of Functioning; GEC = Global Executive Composite; PAS = Premorbid Adjustment Scale; SAS-SR = Social Adjustment Scale-Self-Report; VABS-II = Vineland Adaptive Behavior Scales, Second Edition. * p < .05; ** p < .01. For the purposes of this study, we considered ADHD treatment status as positive if, at any point during the 9-year study, a parent reported that the individual with 22q11DS was prescribed an FDA-approved ADHD medication. The majority (82.4%) of individuals with 22q11DS + baseline ADHD were never treated with an FDA-approved ADHD medication. ADHD Status and Attrition Longitudinal retention rates are presented in Supplementary Figure S1 for both the 22q11DS-only and 22q11DS + baseline ADHD groups. A chi-square analysis indicated that there was not differential rates of attrition between the two groups, X2 (1) = .89, p = .345. Measures ADHD was assessed categorically via the childhood Schedule for Affective Disorders and Schizophrenia for School-Age Children—Present and Lifetime Version (K-SADS-PL) (Kaufman et al., 1997). A child and adolescent psychiatrist or clinical child psychologist administered the KSADS. Based on 12 videotaped interviews that were rated by both administrators, the kappa coefficient was .91, signifying good interrater reliability. ADHD symptoms were assessed dimensionally in childhood using the Behavior Assessment System for Children-Parent Rating Scale (BASC-PRS) (Reynolds & Kamphaus, 1992). Our young adult outcome variables were chosen a priori based on the idiopathic ADHD literature, which emphasizes that children with ADHD often lose their diagnosis in adulthood, yet remain symptomatic and impaired (Faraone, Biederman, & Mick, 2005). Parent Report Measures Time 1 BASC-PRS The BASC-PRS (Reynolds & Kamphaus, 1992) is a measure of parent-reported behaviors of children and adolescents rated on a four-point frequency scale from “Never” to “Almost always.” Responses are organized into nine clinical scales (Aggression, Anxiety, Attention Problems, Atypicality, Conduct Problems, Depression, Hyperactivity, Somatization, and Withdrawal), five adaptive behavior scales, and seven content scales. For the current study, only the Hyperactivity and Attention Problems scales were used. Item raw scores are transformed into T-scores (M = 50, SD = 10), with higher scores indicating more maladaptive behaviors. Time 4 Vineland Adaptive Behavior Scales, Second Edition, Composite Score The Vineland Adaptive Behavior Scales-2nd edition (VABS-II) (Sparrow, Cicchetti, & Balla, 2005) Parent/Caregiver Rating Form is a 297-item questionnaire rated on a three-point scale: 2 (usually), 1 (sometimes or partially), 0 (never), for which parents were asked to rate their adult child’s ability to independently perform behaviors across three skill domains: Communication, Daily Living, and Socialization. Standard scores (M = 100, SD = 15) are provided for each domain and a Total Composite, with higher scores indicating better functioning. For the current study, only the VABS-II Total Composite was used. Time 4 Behavior Rating Inventory of Executive Functioning-Adult Version The Behavior Rating Inventory of Executive Functioning-Adult (BRIEF-A) informant version (Roth, Isquith, & Gioia, 2006) is an standardized parent-report measure that assesses a collateral reporters’ view of an adults’ executive functioning in their everyday environment. The BRIEF-A contains 75 equivalently items that load onto nine subdomains. The Global Executive Composite (GEC) index represents the overall EF score and was used in this study. The GEC comprises items for emotional control, shifting, inhibition, self- and task monitoring, planning/organization, working memory, and initiation scales. Higher scores indicate less well-developed executive functioning skills. Clinician-Rated Measures Time 4 Global Assessment of Functioning The Global Assessment of Functioning (GAF) (APA, 2000) is a clinician-rated global measure of functioning ranging from 0 to 100. Clinicians use the GAF to subjectively rate patients on their social, academic, occupational, and psychological functioning, with higher scores representing better functioning. Time 4 Premorbid Adjustment Scale, Total Score The Premorbid Adjustment Scale (PAS) (Cannon-Spoor, Potkin, & Wyatt, 1982) is an interview-based, clinician-rated instrument used to assess functioning. The Total PAS score incorporates items pertaining to sociability, withdrawal, peer relationships, education, employment, establishment of independence, social–personal adjustment, degree of interest in life, and global assessment of highest level of functioning achieved thus far. These items contribute to the adulthood PAS Total score. Clinician ratings on PAS are scored on a 0–6 Likert scale, with 0 indicating typical adjustment and 6 indicating severe impairment. For the current study, only the adulthood PAS Total score was used. Self-Report Measures Time 4 BRIEF-A The BRIEF-A self-report version (Roth et al., 2006) was used to assess self-report of executive functioning in his/her everyday environment. Please see above for description of the BRIEF-A. The decision to administer both parent and self-report versions of the BRIEF-A is supported by the moderate association noted between parent- and self-report of global executive functioning (r = .34) and the stronger associations in the 22q11DS-only group (r = .52) relative to the 22q11DS + baseline ADHD group (r = .16). For the current study, only the BRIEF-A self-report GEC index was used. Time 4 Adult Self-Report The Adult Self-Report (ASR) (Achenbach & Rescorla, 2003) scale was used to assess the young adults with 22q11DSs’ opinions of their symptoms and functioning. The ASR consists of 123 statements that the adult indicates whether the behavior is not true, somewhat or sometimes true, or very or often true. These statements then load onto eight scales. Raw scores are transformed into T-scores for results interpretation. For the current study, only the Internalizing and Externalizing Composite T-scores were used. Time 4 Social Adjustment Scale-Self-Report The Social Adjustment Scale-Self-Report (SAS-SR) (Weissman, 1999) is a 54-item self-report scale that measures adjustment in social role areas: work, social, and leisure activities; relationships with extended family; and role as a spouse or partner, parental role, and role within the family unit. Mean scores are transformed into T-scores, whereby higher scores indicate more social impairment. For the current study, only the SAS-SR Total was used. Procedures Informed consent and assent were attained from parents and participants. At all four periods, a doctoral-level examiner administered all psychological tests to participants in a quiet room. Parents completed all parent-report rating scales in a separate room. The same measures were administered to all participants and their parents. Planned Analyses To investigate Aim 1 (categorical childhood ADHD diagnoses predict poorer young adult outcomes), and reduce Type 1 error rates, two omnibus multivariate analyses of covariance (MANCOVA) of young adult variables were used with ADHD as the independent variable. One MANCOVA used self-reports (SAS-SR, BRIEF-A, ASR) of young adult outcomes as dependent variables, and age as a covariate. A second MANCOVA used parent/clinician reports (BRIEF-A, VABS-II, PAS, GAF) of young adult outcomes as dependent variables, and age and available baseline parent/clinician reports as covariates. To investigate Aim 2 (dimensional ADHD symptoms predict to poorer outcomes in adulthood), stepwise regression analyses were computed entering baseline levels of the self and parent/clinician-report outcome variables in Step 1. In Step 2, parent report of child hyperactivity–impulsivity and inattention were entered simultaneously. Statistical Power Based on previous research on 22q11DS and ADHD (Antshel et al., 2013), we predicted moderate effect size differences for young adult outcomes between individuals with 22q11DS with and without childhood ADHD (Aim 1). Assuming 80% power to detect differences, two groups, two repetitions of the four repeated measures, a correlation across repeated measures of .3, and an alpha level of .05, a sample size of 46 was needed to attain adequate statistical power for our self-report MANCOVA. For the parent/clinician-report MANCOVA, a sample size of 59 was needed, because of the two repetitions of the six repeated measures. Thus, our Aim 1 self-report report analyses are adequately powered, whereas our parent/clinician analyses are slightly underpowered. Based on the extant ADHD research, which indicates childhood ADHD symptom severity levels are a predictor of adult outcomes with large effect sizes (Lara et al., 2009), we predicted a large effect size for our Aim 2 analyses. Assuming 80% power to detect differences, two predictors, and an alpha level of .05, a sample size of 42 was needed to attain adequate statistical power. Thus, our Aim 2 analyses are adequately powered. Results Aim 1—Categorical ADHD Diagnoses in Childhood Young Adult ASR On the ASR, SAS-SR, and BRIEF-A, after controlling for age, no differences emerged between the young adults with 22q11DS + baseline ADHD and those with 22q11DS only, Wilks λ = 0.81, F(6, 44) = 1.77, p = .126, η2 = .195. As noted in Table I, no differences emerged as a function of ADHD status. Parent/Clinician Reports After controlling for age and Time 1 variables as covariates, differences emerged between the two groups on parent/clinician report variables, Wilks λ = .75, F(4, 46) = 2.90, p = .036, η2 = .249. As noted in Table I, the BRIEF-A GEC parent report and PAS Total clinician report variables differed as a function of ADHD status. In both the parent and clinician report variables, those with 22q11DS + baseline ADHD were rated as functioning less well in young adulthood. Participants with 22q11DS + baseline ADHD did not differ at follow-up from those without baseline ADHD in adaptive functioning based on the parent report VABS-II or the clinician-rated GAF. See Table I for complete parent- or clinician-rated results. Aim 2—Dimensional ADHD Symptoms in Childhood Young Adult ASR Parent report of childhood hyperactivity–impulsivity and inattention did not predict young ASR BRIEF-A GEC, F(2, 49) = 2.82, p = .068, R2 = .114, ASR Internalizing ratings, F(2, 49) = 2.80, p = .071, R2 = .111, ASR Externalizing ratings, F(2, 49) = 2.52, p = .121, R2 = .107, or SAS-SR Total, F(2, 49) = 0.11, p = .900, R2 = .005. Parent/Clinician Reports Baseline VABS Composite positively predicted young adult VABS-II Composite, F(1, 47) = 23.48, p < .001, R2 = .353. After controlling for baseline VABS scores, BASC parent report of childhood hyperactivity–impulsivity and inattention did not predict parent report of adaptive behavioral abilities in young adults with 22q11DS, F(2, 45) = 2.66, p = .082, R2 change = .074. Baseline BRIEF GEC predicted young adult BRIEF-A GEC, F(1, 47) = 34.82, p < .001, R2 = .582. After controlling for baseline BRIEF GEC scores, BASC parent report of hyperactivity–impulsivity and inattention did not predict BRIEF-A GEC ratings in young adults with 22q11DS, F(2, 45) = 1.59, p = .225, R2 change = .051. Clinician-rated childhood GAF ratings predicted young adult GAF ratings, F(1, 47) = 5.13, p = .028, R2 = .100. After controlling for baseline GAF scores, parent report of childhood hyperactivity–impulsivity and inattention did not predict young adult GAF scores, F(2, 45) = .22, p = .801, R2 change = .009. Finally, childhood PAS Total ratings predicted young adult PAS Total ratings, F(1, 47) = 3.40, p = .047, R2 = .091. After controlling for baseline PAS Total scores, parent report of childhood hyperactivity–impulsivity and inattention did not predict young adult PAS Total scores, F(2, 45) = 1.55, p = .353, R2 change = .015. See Table II for relationships between parent, clinicians, and self-report of young adult outcome variables and parent-rated childhood hyperactivity–impulsivity and inattention. Table II. Associations Between Time 1 Parent Ratings of ADHD Symptoms and Time 4 Data Time 1 BASC Attention Problems Time 1 BASC Hyperactivity Parent report  Time 1 BASC  attention problems 1 .60**  Time 1 BASC hyperactivity .60** 1  Time 4 BRIEF-A GEC .55** .49**  Time 4 VABS-II Composite −.28 −.37 Clinician ratings  Time 4 Current GAF −.16 −.18  Time 4 PAS Total Composite .29 .32 Self-report  Time 4 BRIEF-A GEC .41** .41**  Time 4 SAS-SR Composite .04 .07  Time 4 ASR Internalizing .28 .31*  Time 4 ASR Externalizing .38** .42** Time 1 BASC Attention Problems Time 1 BASC Hyperactivity Parent report  Time 1 BASC  attention problems 1 .60**  Time 1 BASC hyperactivity .60** 1  Time 4 BRIEF-A GEC .55** .49**  Time 4 VABS-II Composite −.28 −.37 Clinician ratings  Time 4 Current GAF −.16 −.18  Time 4 PAS Total Composite .29 .32 Self-report  Time 4 BRIEF-A GEC .41** .41**  Time 4 SAS-SR Composite .04 .07  Time 4 ASR Internalizing .28 .31*  Time 4 ASR Externalizing .38** .42** Note. ADHA = attention-deficit/hyperactivity disorder; ASR = Adult Self-Report; BASC = Behavior Assessment System for Children; BRIEF-A = Behavioral Rating Inventory for Executive Functioning-Adult version; GAF = Global Assessment of Functioning; GEC = Global Executive Composite; PAS = Premorbid Adjustment Scale; SAS-SR = Social Adjustment; VABS-II = Vineland Adaptive Behavior Scales, Second Edition. * p < .05; ** p < .01. Table II. Associations Between Time 1 Parent Ratings of ADHD Symptoms and Time 4 Data Time 1 BASC Attention Problems Time 1 BASC Hyperactivity Parent report  Time 1 BASC  attention problems 1 .60**  Time 1 BASC hyperactivity .60** 1  Time 4 BRIEF-A GEC .55** .49**  Time 4 VABS-II Composite −.28 −.37 Clinician ratings  Time 4 Current GAF −.16 −.18  Time 4 PAS Total Composite .29 .32 Self-report  Time 4 BRIEF-A GEC .41** .41**  Time 4 SAS-SR Composite .04 .07  Time 4 ASR Internalizing .28 .31*  Time 4 ASR Externalizing .38** .42** Time 1 BASC Attention Problems Time 1 BASC Hyperactivity Parent report  Time 1 BASC  attention problems 1 .60**  Time 1 BASC hyperactivity .60** 1  Time 4 BRIEF-A GEC .55** .49**  Time 4 VABS-II Composite −.28 −.37 Clinician ratings  Time 4 Current GAF −.16 −.18  Time 4 PAS Total Composite .29 .32 Self-report  Time 4 BRIEF-A GEC .41** .41**  Time 4 SAS-SR Composite .04 .07  Time 4 ASR Internalizing .28 .31*  Time 4 ASR Externalizing .38** .42** Note. ADHA = attention-deficit/hyperactivity disorder; ASR = Adult Self-Report; BASC = Behavior Assessment System for Children; BRIEF-A = Behavioral Rating Inventory for Executive Functioning-Adult version; GAF = Global Assessment of Functioning; GEC = Global Executive Composite; PAS = Premorbid Adjustment Scale; SAS-SR = Social Adjustment; VABS-II = Vineland Adaptive Behavior Scales, Second Edition. * p < .05; ** p < .01. Discussion To our knowledge, this is the first study to use a longitudinal design to predict young adult outcomes in children with 22q11DS + baseline ADHD. Our childhood ADHD prevalence rate (44%) is consistent with what others have reported in 22q11DS (Schneider et al., 2014). Categorical and Dimensional ADHD After controlling for baseline parent report of executive dysfunction, parents of youth with 22q11DS + baseline ADHD reported that their young adult child had more executive dysfunction than did parents of young adults with 22q11DS only. Likewise, clinicians rated young adults with 22q11DS + baseline ADHD as having lower levels of overall functioning in young adulthood after controlling for baseline functioning. In this way, differences between the two 22q11DS groups became more pronounced over time. No group differences emerged on any self-report data. When considering ADHD symptoms dimensionally, after controlling for baseline levels of variables, parent report of childhood ADHD symptoms did not predict any clinician or parent report variables of adult functioning. Similarly, parent report of childhood ADHD symptoms did not predict young ASR. Others (Neely et al., 2016) have suggested that using both categorical and dimensional approaches to psychopathology is particularly important for youth with neurodevelopmental disorders. For predicting to young adult functional outcomes in 22q11DS, considering childhood ADHD as a categorical condition was a better predictor of young adult outcomes than a dimensional perspective. This finding argues against the notion that symptoms of inattention and hyperactivity–impulsivity are intrinsic to 22q11DS and therefore not worthy of further assessment or treatment. Our data suggest that such elevated symptoms, although common in individuals with 22q11DS (Ousley, Rockers, Dell, Coleman, & Cubells, 2007), may reflect a diagnosis of ADHD. Moreover, impairment secondary to ADHD symptoms is a criterion in the Diagnostic and statistical manual - 5th edition (DSM-5) (APA, 2013), and our data suggest that assigning a childhood ADHD diagnosis is meaningful and prognostic in youth with 22q11DS. If ADHD diagnoses were simply assigned to those with more severe ADHD symptoms, results in the dimensional analyses would have mirrored the categorical analyses. In contrast, a childhood diagnosis of ADHD (and not simply levels of ADHD symptoms in this population) was predictive of outcomes in 22q11DS. Our data are also consistent with longitudinal research on idiopathic ADHD that suggests that childhood ADHD is associated with young adult outcomes including executive dysfunction (Biederman et al., 2007) and lower levels of functional independence (Barkley, Fischer, Smallish, & Fletcher, 2006). Thus, our results of ADHD in the context of developmental delays mirror the idiopathic ADHD research results (which often exclude those with IQs < 80 from participation). While two group differences emerged between the two 22q11DS groups in young adulthood, multiple young adult measures were not different between the two groups. Likewise, no self-report differences on any young adult variable emerged between the 22q11DS groups. Although some young adult outcomes are negatively affected by the presence of childhood ADHD, multiple other outcomes are not impacted significantly by ADHD. Rather, having developmental delays, as is common in 22q11DS (Antshel et al., 2007), appears to be more impactful toward predicting young adult outcomes in some domains. Parent and Young Adult Perceptions Parent report and self-report of functioning were moderately associated with each other, yet were more strongly related in the 22q11DS-only group. Parents report more concerns about functioning than young adults with 22q11DS, both with and without ADHD. While parent and child reports of child functioning often differ (Kolko & Kazdin, 1993), young adults with 22q11DS do not perceive themselves as experiencing difficulties when compared with their same aged peers. One possible explanation for this finding may be related to cognitive immaturity (Milich, 1994). Cognitive immaturity has been forwarded as a hypothesis to explain the positive self-perceptions that exist in ADHD (Owens, Goldfine, Evangelista, Hoza, & Kaiser, 2007). Our 22q11DS sample, both with and without ADHD, had mean IQs in the Borderline range for age. Thus, it is possible that developmental delays led to poor self-monitoring, which led to parents reporting lower functioning than self-report. However, others (Swanson, Owens, & Hinshaw, 2012) have encouraged researchers not to assume that parents are correct (and children are incorrect). ADHD Treatment in 22q11DS The majority of individuals with 22q11DS + baseline ADHD were never treated with an FDA-approved ADHD medication. Our low ADHD treatment rates are consistent with previous evidence that suggests low treatment rates (between 60 and 80% are not treated) for 22q11DS and comorbid psychiatric disorders (not specific to ADHD) (Tang et al., 2014). In 22q11DS, parents made decisions to not pursue an FDA-approved ADHD medication for their child with ADHD. There are likely a variety of reasons for these decisions. Future research, using a qualitative design, should investigate the pharmacotherapy decision-making processes for parents of youth with 22q11DS + baseline ADHD. In conjunction with previous research that stimulant medication is safe and effective for use in individuals with 22q11DS (Gothelf et al., 2003), these results indicate that the low rate of treatment in this population merits further consideration. Comorbid ADHD affects clinician and parent-report variables of adult functioning above and beyond the effects of developmental delays inherent to 22q11DS, yet may still be undertreated. Limitations While many of our analyses would not have survived a Bonferroni correction, our effect sizes are uniformly large, and we used MANCOVA designs (reducing the chance of type I error). Thus, we believe that these results likely represent the most robust differences between 22q11DS groups. Other real differences (with small to medium effect sizes) may exist, yet did not reach the p < .05 criterion. The lack of an IQ-matched control group is an additional limitation. Thus, the specificity of these results to 22q11DS + baseline ADHD is not presently known. Future Directions and Conclusion Comorbid childhood ADHD as a categorical diagnosis is a significant predictor of parent report of executive dysfunction and clinician ratings of functioning 9-years later and predicted more young adult outcomes than considering childhood ADHD symptoms dimensionally. This suggests that DSM-5 Criterion D (impairment secondary to ADHD symptoms) is particularly important to consider in youth with developmental delays. Further research is needed to understand the mechanisms that may be responsible for these concerning long-term trajectories. Considering environmental factors (e.g., family, peer group) and the interaction of these factors with biological variables will likely prove most informative. Despite several significant negative long-term outcomes, most individuals with 22q11DS + baseline ADHD were never treated with an FDA-approved medication. Given the low rate of pharmacological treatment for this population, despite some evidence for the efficacy (Gothelf et al., 2003), future research should consider how best to increase the use of ADHD evidence-based interventions, both pharmacological and nonpharmacological, in 22q11DS. In the idiopathic ADHD literature, parental lack of knowledge and misconceptions about ADHD and poor symptom recognition are barriers to treatment for children with ADHD (Bussing, Zima, Gary, & Garvan, 2003). These barriers may also affect children with 22q11DS + baseline ADHD. For example, low knowledge of ADHD and poor symptom recognition may exist in 22q11DS via diagnostic overshadowing. In diagnostic overshadowing, symptoms of one condition (ADHD) are ascribed to a secondary condition (22q11DS) (Jopp & Keys, 2001). If a condition is not believed to exist or be valid, that condition is less likely to be treated (O'Brien, Kifuji, & Summergrad, 2006). Further, parents of individuals with 22q11DS report concerns about cardiac effects and fear increased risk of psychosis as a function of stimulant use (Green et al., 2011), despite some evidence to suggest that stimulant medication is safe and effective for use in this population (Gothelf et al., 2003). Future research should consider the barriers for ADHD treatment in the 22q11DS population as well as how to address these barriers. In summary, ADHD predicts several poor outcomes above and beyond the negative outcomes associated with 22q11DS. To the extent that ADHD remains undertreated and underresearched in 22q11DS, a significant portion of individuals with 22q11DS may endure several negative long-term outcomes that may be potentially modifiable with treatment. Supplementary Data Supplementary data can be found at: http://www.jpepsy.oxfordjournals.org/. Funding This work was supported by the National Institutes of Health (grant number R01MH064824). Conflicts of interest: None declared. References Achenbach T. M. , Rescorla L. A. ( 2003 ). Manual for the ASEBA adult forms and profiles . Burlington, VT : University of Vermont . Antshel K. M. , Faraone S. V. , Fremont W. , Monuteaux M. C. , Kates W. R. , Doyle A. , Mick E. , Biederman J. ( 2007 ). Comparing ADHD in velocardiofacial syndrome to idiopathic ADHD. A preliminary study . Journal of Attention Disorders , 11 , 64 – 73 . doi: 10.1177/1087054707299397 Google Scholar CrossRef Search ADS PubMed Antshel K. M. , Hendricks K. , Shprintzen R. , Fremont W. , Higgins A. M. , Faraone S. V. , Kates W. R. ( 2013 ). The longitudinal course of attention deficit/hyperactivity disorder in velo-cardio-facial syndrome . Journal of Pediatrics , 163 , 187 – 193 . doi: 10.1016/j.jpeds.2012.12.026 Google Scholar CrossRef Search ADS PubMed Antshel K. M. , Phillips M. H. , Gordon M. , Barkley R. , Faraone S. V. ( 2006 ). Is ADHD a valid disorder in children with intellectual delays? Clinical Psychology Review , 26 , 555 – 572 . Google Scholar CrossRef Search ADS PubMed APA . ( 2000 ). Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) ( 4th ed. ). Washington, DC : American Psychiatric Association . APA . ( 2013 ). Diagnostic and Statistical Manual of Mental Disorders ( 5th ed. ). Washington, DC : American Psychiatric Publishing . Barkley R. , Fischer M. , Smallish L. , Fletcher K. ( 2006 ). Young adult outcome of hyperactive children: Adaptive functioning in major life activities . Journal of the American Academy of Child and Adolescent Psychiatry , 45 , 192 – 202 . Google Scholar CrossRef Search ADS PubMed Biederman J. , Petty C. R. , Fried R. , Doyle A. E. , Spencer T. , Seidman L. J. , Gross L. , Poetzl K. , Faraone S. V. ( 2007 ). Stability of executive function deficits into young adult years: A prospective longitudinal follow-up study of grown up males with ADHD . Acta Psychiatrica Scandinavica , 116 , 129 – 136 . doi: 10.1111/j.1600-0447.2007.01008.x Google Scholar CrossRef Search ADS PubMed Botto L. D. , May K. , Fernhoff P. M. , Correa A. , Coleman K. , Rasmussen S. A. , Merritt R. K. , O'Leary L. A. , Wong L. Y. , Elixson E. M. , Mahle W. T. , Campbell R. M. ( 2003 ). A population-based study of the 22q11.2 deletion: Phenotype, incidence, and contribution to major birth defects in the population . Pediatrics , 112 , 101 – 107 . Google Scholar CrossRef Search ADS PubMed Bussing R. , Zima B. T. , Gary F. A. , Garvan C. W. ( 2003 ). Barriers to detection, help-seeking, and service use for children wit ADHD symptoms . The Journal of Behavioral Health Services and Research , 30 , 176 – 189 . Google Scholar CrossRef Search ADS PubMed Cannon-Spoor H. E. , Potkin S. G. , Wyatt R. J. ( 1982 ). Measurement of premorbid adjustment in chronic schizophrenia . Schizophrenia Bulletin , 8 , 470 – 484 . http://dx.doi.org/10.1093/schbul/8.3.470 Google Scholar CrossRef Search ADS PubMed de Schipper E. , Lundequist A. , Wilteus A. L. , Coghill D. , de Vries P. J. , Granlund M. , Holtmann M. , Jonsson U. , Karande S. , Levy F. , Al-Modayfer O. , Rohde L. , Tannock R. , Tonge B. , Bölte S. ( 2015 ). A comprehensive scoping review of ability and disability in ADHD using the International Clssification of Functioning, Disability, and Health-Children and Youth Version (ICF-CY) . European Child and Adolscent Psychiatry , 24 , 859 – 871 . doi: 10.1007/s00787-015-0727-z Google Scholar CrossRef Search ADS Faraone S. V. , Asherson P. , Banaschewski T. , Biederman J. , Buitelaar J. K. , Ramos-Quiroga J. A. , Rohde L. A. , Sonuga-Barke E. J. , Tannock R. , Franke B. ( 2015 ). Attention-deficit/hyperactivity disorder . Nature Reviews Disease Primers , 1 , 15 – 20 . doi: 10.1038/nrdp.2015.20 Faraone S. V. , Biederman J. , Mick E. ( 2005 ). The age-dependent decline of attention deficit hyperactivity disorder: A meta-analysis of follow-up studies . Psychological Medicine , 36 , 159 – 165 . http://dx.doi.org/10.1017/S003329170500471X Google Scholar CrossRef Search ADS Gothelf D. , Gruber R. , Presburger G. , Dotan I. , Brand-Gothelf A. , Burg M. , Inbar D. , Steinberg T. , Frisch A. , Apter A. , Weizman A. ( 2003 ). Methylphenidate treatment for attention-deficit/hyperactivity disorder in children and adolescents with velocardiofacial syndrome: An open-label study . Journal of Clinical Psychiatry , 64 , 1163 – 1169 . Google Scholar CrossRef Search ADS PubMed Green T. , Weinberger R. , Diamond A. , Berant M. , Hirschfeld L. , Frisch A. , Zarchi O. , Weizman A. , Gothelf D. ( 2011 ). The effect of methylphenidate on prefrontal cognitive functioning, inattention, and hyperactivity in velocardiofacial syndrome . Journal of Child and Adolescent Psychopharmacology , 21 , 589 – 595 . doi: 10.1089/cap.2011.0042 Google Scholar CrossRef Search ADS PubMed Hurtig T. , Ebeling H. , Taanila A. , Miettunen J. , Smalley S. , McGough J. , Loo S. K. , Järvelin M. R. , Moilanen I. ( 2007 ). ADHD symptoms and subtypes: Relationship between childhood and adolescent symptoms . Journal of the American Academy of Child and Adolescent Psychiatry , 46 , 1605 – 1613 . Google Scholar CrossRef Search ADS PubMed Jopp D. A. , Keys C. B. ( 2001 ). Diagnostic overshadowing reviewed and reconsidered . American Journal of Mental Retardation , 106 , 416 – 433 . doi: 10.1352/0895-80172001 Google Scholar CrossRef Search ADS PubMed Kaufman J. , Birmaher B. , Brent D. , Rao U. M. A. , Flynn C. , Moreci P. , Williamson D. , Ryan N. ( 1997 ). Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): Initial reliability and validity data . Journal of the American Academy of Child & Adolescent Psychiatry , 36 , 980 – 989 . Google Scholar CrossRef Search ADS Kolko D. J. , Kazdin A. E. ( 1993 ). Emotional/behavioral problems in clinic and nonclinic children: Correspondence among child, parent and teacher reports . Journal of Child Psychology and Psychiatry and Allied Disciplines , 34 , 991 – 1006 . Google Scholar CrossRef Search ADS Lara C. , Fayyad J. , de Graaf R. , Kessler R. C. , Aguilar-Gaxiola S. , Angermeyer M. , Demytteneare K. , de Girolamo G. , Haro J. M. , Jin R. , Karam E. G. , Lépine J. P. , Mora M. E. , Ormel J. , Posada-Villa J. , Sampson N. ( 2009 ). Childhood predictors of adult attention-deficit/hyperactivity disorder: Results from the World Health Organization World Mental Health Survey Initiative . Biological Psychiatry , 65 , 46 – 54 . Google Scholar CrossRef Search ADS PubMed Lo-Castro A. , D'Agati E. , Curatolo P. ( 2011 ). ADHD and genetic syndromes . Brain and Development , 33 , 456 – 461 . doi: 10.1016/j.braindev.2010.05.011 Google Scholar CrossRef Search ADS PubMed Mackenzie G. B. , Wonders E. ( 2016 ). Rethinking intelligence quotient exclusion criteria practices in the study of attention deficit hyperactivity disorder . Frontiers in Psychology , 7 , 794. doi: 10.3389/fpsyg.2016.00794 Google Scholar CrossRef Search ADS PubMed Milich R. ( 1994 ). The response of children with ADHD to failure: If at first you don't succeed, do you try, try again? School Psychology Review , 23 , 11 – 28 . Neely R. J. , Green J. L. , Sciberras E. , Hazell P. , Anderson V. ( 2016 ). Relationship between executive functioning and symptoms of attention-deficit/hyperactivity disorder and Autism spectrum disorder in 6-8 year old children . Journal of Autism and Developmental Disorders , 46 , 3270 – 3280 . doi: 10.1007/s10803-016-2874-6. Google Scholar CrossRef Search ADS PubMed O'Brien R. F. , Kifuji K. , Summergrad P. ( 2006 ). Medical conditions with psychiatric manifestations . Adolescent Medicine Clinics , 17 , 49 – 77 . doi: 10.1016/j.admecli.2005.10.007 Google Scholar PubMed Ousley O. , Rockers K. , Dell M. , Coleman K. , Cubells J. F. ( 2007 ). A review of neurocognitive and behavioral profiles associated with 22q11 deletion syndrome: Implications for clinical evaluation and treatment . Current Psychiatry Reports , 9 , 148 – 158 . doi: 10.1007/s11920-007-0085-8 Google Scholar CrossRef Search ADS PubMed Owens J. S. , Goldfine M. E. , Evangelista N. M. , Hoza B. , Kaiser N. M. ( 2007 ). A critical review of self-perceptions and the positive illusory bias in children with ADHD . Clinical Child and Family Psychology Review , 10 , 335 – 351 . Google Scholar CrossRef Search ADS PubMed Philip N. , Bassett A. ( 2011 ). Cognitive, behavioural and psychiatric phenotype in 22q11.2 deletion syndrome . Behavavioral Genetics , 41 , 403 – 412 . doi: 10.1007/s10519-011-9468-z Google Scholar CrossRef Search ADS Reynolds C. R. , Kamphaus R. W. ( 1992 ). Behavior Assessment Scales for Children (BASC) . Circle Pines, MN : American Guidance Service . Roth R. M. , Isquith P. K. , Gioia G. ( 2006 ). Behavior Rating Inventory of Executive Function®–Adult Version (BRIEF-A) . Lutz, FL : Psychological Assessment Resources . Schneider M. , Debbané M. , Bassett A. S. , Chow E. W. C. , Fung W. L. A. , van den Bree M. B. M. , Murphy K. C. , Niarchou M. , Kates W. R. , Antshel K. M. , Fremont W. , McDonald-McGinn D. M. , Gur R. E. , Zackai E. H. , Vorstman J. , Duijff S. N. , Klaassen P. W. , Swillen A. , Gothelf D. , Green T. , Weizman A. , Van Amelsvoort T. , Evers L. , Boot E. , Shashi V. , Hooper S. R. , Bearden C. E. , Jalbrzikowski M. , Armando M. , Vicari S. , Murphy D. G. , Ousley O. , Campbell L. E. , Simon T. J. , Eliez S. ( 2014 ). Psychiatric disorders from childhood to adulthood in 22q11.2 deletion syndrome: Results from the International Consortium on Brain and Behavior in 22q11.2 Deletion Syndrome . American Journal of Psychiatry , 171 , 627 – 639 . doi: 10.1176/appi.ajp. Google Scholar CrossRef Search ADS PubMed Shprintzen R. J. , Higgins A. M. , Antshel K. , Fremont W. , Roizen N. , Kates W. ( 2005 ). Velo-cardio-facial syndrome . Current Opinion in Pediatrics , 17 , 725 – 730 . Google Scholar CrossRef Search ADS PubMed Shprintzen R. J. ( 2000 ). Velo-cardio-facial syndrome: A distinctive behavioral phenotype . Mental Retardation and Developmental Disabilities Research Reviews , 6 , 142 – 2779 . http://dx.doi.org/10.1002/1098-2779(2000)6:2<142::AID-MRDD9>3.0.CO;2-H Google Scholar CrossRef Search ADS PubMed Sparrow S. , Cicchetti D. , Balla D. ( 2005 ). Vineland Adaptive Behavior Scales (Vineland-II) ( 2nd ed. ). San Antonio, TX : Pearson Education . Spencer T. , Biederman J. , Mick E. ( 2007 ). Attention-deficit/hyperactivity disorder: Diagnosis, lifespan, comorbidities, and neurobiology . Journal of Pediatric Psychology , 32 , 631 – 642 . doi: 10.1093/jpepsy/jsm005 Google Scholar CrossRef Search ADS PubMed Swanson E. N. , Owens E. B. , Hinshaw S. P. ( 2012 ). Is the positive illusory bias illusory? Examining discrepant self-perceptions of competence in girls with ADHD . Journal of Abnormal Child Psychology , 40 , 987 – 998 . doi: 10.1007/s10802-012-9615-x Google Scholar CrossRef Search ADS PubMed Tang S. X. , Yi J. J. , Calkins M. E. , Whinna D. A. , Kohler C. G. , Souders M. C. , McDonald-McGinn D. M. , Zackai E. H. , Emanuel B. S. , Gur R. C. , Gur R. E. ( 2014 ). Psychiatric disorders in 22q11.2 deletion syndrome are prevalent but undertreated . Psychological Medicine , 44 , 1267 – 1277 . doi: 10.1017/S0033291713001669 Google Scholar CrossRef Search ADS PubMed Weissman M. M. ( 1999 ). Social Adjustment Scale- Self-report (SAS-SR) User’s Manual . North Tonawanda, NY : Multi-Health Systems, Inc . © The Author(s) 2018. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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Journal of Pediatric PsychologyOxford University Press

Published: Jan 25, 2018

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