Inattention, Hyperactivity, and Impulsivity in Youth with Ocd: Comorbid Adhd Or a Consequence of Obsessions and Compulsions?

INATTENTION, HYPERACTIVITY, AND IMPULSIVITY IN YOUTH WITH OCD: COMORBID ADHD OR A CONSEQUENCE OF OBSESSIONS AND COMPULSIONS?

ANDREW GILES GUZICK

A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2016

To the families who participated in this study

ACKNOWLEDGMENTS

This thesis would not have been possible without the support and guidance of Dr. Gary

R. Geffken, Dr. Joseph P.H. McNamara, Dr. Regina Bussing, Mr. Adam M. Reid, and Ms.

Amanda Balkhi. I would also like to thank Dr. Wayne Goodman and collaborators at the

University of South Florida (USF), Drs. Tanya Murphy and Eric Storch, who were instrumental in writing the grant that funded this study and for leading data collection at the USF site. I would also like to thank the other members of the study team who helped collect these data and all the families who participated in the study.

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 7

LIST OF FIGURES ...... 8

LIST OF ABBREVIATIONS ...... 9

ABSTRACT ...... 10

CHAPTER

1 INTRODUCTION ...... 12

2 METHODS ...... 19

Participants ...... 19 Procedure ...... 20 Measures ...... 20 Demographics ...... 20 Children’s Yale-Brown Obsessive-Compulsive Scale (CYBOCS) ...... 20 Swanson, Nolan, and Pelham-IV (SNAP-IV) ...... 21 Children’s Depression Rating Scale-Revised (CDRS-R) ...... 21 Treatment-Emergent Activation and Suicidality Assessment Profile (TEASAP) ...... 22 Statistical Analyses ...... 22 Preliminary Covariate Analyses ...... 22 Aim 1: Predicting Change in OCD Severity ...... 23 Aim 2: ADHD Symptom Reduction during Treatment ...... 23 Hypothesis 1: ADHD symptoms at baseline will be significantly greater than ADHD symptoms at the end of treatment ...... 23 Hypothesis 2: Reduction in OC symptoms will predict reduction in ADHD symptoms ...... 23

3 RESULTS ...... 26

Preliminary Correlational Analyses ...... 26 Aim 1. Predicting OC Symptom Reduction ...... 26 Aim 2. ADHD Symptom Reduction during Treatment ...... 27 Hypothesis 1: ADHD symptoms at baseline will be significantly greater than ADHD symptoms at the end of treatment ...... 27 Hypothesis 2: Reduction in OC symptoms will predict reduction in ADHD symptoms ...... 27

4 DISCUSSION ...... 33

REFERENCES ...... 39

BIOGRAPHICAL SKETCH ...... 45

LIST OF TABLES

Table page

2-1 Sample demographics (n=48) ...... 25

3-1 Correlations between potential regression model covariate and independent and dependent variables of interest...... 30

3-2 Regression model predicting change in CYBOCS score before and after treatment ...... 30

3-3 Regression model predicting change in SNAP-IV score before and after treatment ...... 31

LIST OF FIGURES

Figure page

3-1 Mean ADHD symptom reduction across treatment...... 32

3-2 ADHD symptom reduction among those in remission and those not in remission ...... 32

LIST OF ABBREVIATIONS

ADHD Attention-Deficit/Hyperactivity Disorder

CBT-E/RP Cognitive-Behavioral Therapy with Exposure and Response Prevention

CDRS-R Children’s Depression Rating Scale-Revised

CYBOCS Children’s Yale-Brown Obsessive-Compulsive Scale

K-SADS-PL Schedule for Affective Disorders and Schizophrenia for School-Age Children- Present and Lifetime Version

OC Obsessive-Compulsive

OCD Obsessive-Compulsive Disorder

RegSert Regular Titration of Sertraline

SlowSert Slow Titration of Sertraline

SNAP-IV Swanson, Nolan, and Pelham-IV

SSRI Selective Serotonin Reuptake Inhibitor

TEASAP Treatment-Emergent Activation and Suicidality Assessment Profile

Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science

INATTENTION, HYPERACTIVITY, AND IMPULSIVITY IN YOUTH WITH OCD: COMORBID ADHD OR A CONSEQUENCE OF OBSESSIONS AND COMPULSIONS?

Andrew Giles Guzick

May 2016

Chair: Gary R. Geffken Major: Psychology

Attention-Deficit/Hyperactivity Disorder (ADHD) is reported to be highly comorbid in children and adolescents with Obsessive-Compulsive Disorder (OCD) and has been shown to cause substantial functional impairment and hinder treatment response. It may be, however, that obsessive distress and compulsive rituals cause inattention, impulsivity, and other ADHD-like symptoms. If this were the case, the reported comorbidity rate may be an overestimate of the true prevalence of ADHD in youth with OCD. Analyses in the present thesis tested this hypothesis by evaluating whether children who successfully complete combined psychological- psychopharmacological treatment for OCD experience a reduction in both ADHD and OC symptoms. It also evaluated whether ADHD symptoms measured continuously predict treatment outcome. A paired-samples t-test revealed modest, significant reductions in parent-reported

ADHD symptoms after treatment. Hierarchical linear regression analyses indicated that OC symptom reduction predicted ADHD symptom reduction, suggesting that children who respond to OCD treatment also experience a reduction in inattention, hyperactivity, and impulsivity.

Regression analyses failed to support the hypothesis that greater ADHD symptoms at baseline predict treatment outcome. These results indicate that obsessional distress may exacerbate

inattention, hyperactivity, and impulsivity, often resulting in inappropriate diagnoses of ADHD in those with OCD.

CHAPTER 1 INTRODUCTION

Obsessive-Compulsive Disorder (OCD) is a debilitating psychiatric condition characterized by obsessive, intrusive, disturbing thoughts, and/or compulsive behaviors that are done in an attempt to alleviate the distress caused by obsessions. (American Psychiatric

Association, 2013). Once thought to be relatively rare in childhood, it is now recognized that early adolescence is one of the peak times at which people are at risk for developing OCD

(Chabane et al., 2005). In addition to causing substantial impairment in school, social, and family functioning, children with OCD are more likely to have other psychological conditions including major depression, anxiety disorders, and externalizing problems such as Attention-

Deficit/Hyperactivity Disorder (ADHD; Ivarsson, Melin, & Wallin, 2008).

ADHD is estimated to occur in 18-43% of children with OCD (Geller et al., 2001;

Ivarsson et al., 2008; Storch et al., 2007; Storch et al., 2008). The high risk for ADHD in children with OCD is particularly alarming when considering the detrimental effects of co- occurring ADHD and OCD. Specifically, those with both OCD and ADHD often have an earlier age of onset compared to those with OCD only, are even more functionally impaired, perform worse in school, and have higher rates of other comorbid conditions like major depression, tic disorders, and disruptive behavior disorders (Geller et al., 2002; Geller et al., 2003; Masi et al.,

2006; Walitza et al., 2008).

When considering all the adverse effects of ADHD symptoms on OCD presentation, it is not surprising that ADHD hinders successful OCD treatment outcome as well (Geller et al.,

2003; Storch et al., 2008; Walitza et al., 2008). The first-line recommended treatment for children with OCD is cognitive behavioral therapy with exposure and response prevention (CBT-

E/RP) in mild to moderate cases and in combination with selective serotonin reuptake inhibitors

SSRIs) in severe cases (Koran, Hanna, Hollander, Nestadt, & Simpson, 2007; Freeman et al.,

2014). During CBT-E/RP, children are challenged to face obsession-inducing stimuli systematically without engaging in compulsions in order to overcome obsessive fear (Piacentini,

Langley, & Roblek, 2007). Children and adolescents with OCD and ADHD may have more trouble engaging in CBT-E/RP compared to their OCD peers without ADHD due to more difficulty resisting compulsive urges, or encoding corrective information following exposure exercises (Storch et al., 2008). It has also been found that children with OCD and ADHD have worse outcomes following SSRI treatment (Geller et al., 2003), though these findings have not been consistently replicated (Masi et al., 2006). Following successful inpatient treatment, those with both OCD and ADHD are more likely to experience a relapse of symptoms compared to patients with OCD without ADHD (Walitza et al., 2008). These studies, however, have always examined ADHD as a dichotomous diagnostic factor, rather than examining inattention, hyperactivity, and impulsivity continuously, despite mounting evidence that ADHD can be appropriately classified as a disorder on a “spectrum” (Asherson & Trzaskowski, 2015). Put differently, all children are inattentive, impulsive, and hyperactive to some degree; it may be more useful to assess these symptoms continuously, rather than setting a cutoff for a clinically meaningful level of symptoms. The present thesis seeks to examine the impact of ADHD symptoms assessed as a continuous variable, rather than dichotomously, as a predictor of combined treatment outcome (CBT-E/RP+SSRIs) in youth with OCD.

The high prevalence of ADHD in OCD occurs in the context of recent controversy regarding the over-diagnosis of ADHD in childhood, as many argue that youth may experience improved attentional abilities and decreased hyperactivity and impulsivity through normal development, and thus diagnosing ADHD at a young age could be problematic (e.g.

Bruchmüller, Margraf, & Schneider, 2012). Despite an increasing public perception that ADHD is over-diagnosed, evidence from systematic reviews fails to find support for this hypothesis based on current diagnostic approaches (Goldman, Genel, Bezman, & Slanetz, 1998; Sciutto &

Eisenberg, 2007). Incorrect diagnoses are especially less likely to occur in studies using validated diagnostic measures and clinical interviews, including all studies listed above that evaluated co-occurring ADHD in children with OCD. Though people with OCD and ADHD compared with people with ADHD only often demonstrate similar types, number, and severity of

ADHD symptoms (Geller et al., 2002), evidence from familial, clinical, and neuropsychological studies is beginning to indicate that the reported comorbidity rate may be an overestimation of the true prevalence of ADHD in OCD (Abramovitch, Dar, Hermesh, & Schweiger, 2012).

Though some studies have indicated that there are shared familial risk factors for developing both conditions, a careful analysis suggests there is also evidence to the contrary.

Geller and colleagues (2007a) concluded that the disorders share similar familial risk factors, as first-degree relatives of children with ADHD and those of children with ADHD and OCD are equally likely to have ADHD, and are both more likely than family members of healthy controls to have ADHD. Similarly, family members of those with OCD and ADHD and those with OCD only are equally likely to have OCD, and both are significantly more likely to have OCD than relatives of healthy children (Geller et al., 2007b). They also found, however, that first-degree family members of children with ADHD and OCD were significantly more likely to have OCD than family members of children with ADHD only and of healthy controls, and there was no significant difference in risk for OCD between relatives of children with ADHD and healthy controls. Similar results were found in a study investigating children with OCD and ADHD, children with OCD only, and healthy controls. First-degree relatives of children with ADHD and

OCD were significantly more likely to have ADHD than relatives of healthy controls and children with OCD only, while there was no significant difference in the rate of ADHD between the OCD only and healthy control groups (Geller et al., 2007b). Together, these results indicate that there are independent genetic risk factors for developing ADHD and OCD that may be unrelated to one another.

Consistent with this model is the opposing clinical presentations of ADHD and OCD, as

ADHD is characterized by impulsive (i.e. thoughtless and spontaneous) behavior, while OCD is characterized by compulsive behaviors that are more deliberate in nature. The clinical signatures of each disorder are intuitively contrasting, and occur on the opposite sides of an “impulsive- deliberate” spectrum of behavior. OCD is characterized by a need for control (Obsessive

Compulsive Cognitions Working Group, 1997), low novelty-seeking (Alonso et al., 2008), and an inhibited temperament (Van Ameringen, Mancini, and Oakman, 1998). Meanwhile, children with ADHD tend to score highly on measures of novelty-seeking (Donfrancesco et al., 2015), sensation-seeking (Blaskey, Harris, & Nigg, 2008), and risk-taking (Drechsler, Rizzo, &

Steinhausen, 2008).

Both ADHD and OCD are characterized by frontostriatal dysfunction, which have been proposed to underlie cognitive deficits observed in both conditions. Relatively consistent impairments in several executive functions have been found in those with OCD compared with healthy controls, including set shifting (Aycicegi, Dinn, Harris, & Erkmen, 2003; Lawrence et al., 2005), complex problem-solving (Lacerda et al., 2003; Lucey et al., 1997), and response inhibition (Aycicegi et al., 2003; Chamberlain, Blackwell, Fineberg, Robbins, & Sahakian,

2005). Adults with OCD also demonstrate deteriorated working memory and attentional abilities

(Abramovitch, Abramowitz, & Mittleman, 2013). Similar deficits are a hallmark of ADHD

(Frazier et al., 2004; Hervey, Epstein, & Curry, 2004). These neuropsychological deficits span the lifespan in those with ADHD, with consistent patterns of impairment in both children and adults. Results from a recent meta-analysis, however, failed to find statistically significant neuropsychological deficits in children with OCD in any cognitive domain (attention, executive function, working memory, visuospatial skills, memory, and processing speed) despite relatively consistent results in the adult literature (Abramovitch et al., 2015). These findings exist despite literature that supports fronto-striatal hyperactivity in children as well as adults with OCD, indicating that cognitive performance deficits may develop over time as the cognitive system is more strained (Fitzgerald et al., 2011).

Despite relatively similar patterns of impairment on functional measures of cognition in those with OCD and those with ADHD, the neurological explanation for executive deficits in each disorder are antithetical; while OCD is linked with frontostriatal hyperactivity, perhaps driven by a desire for more control over planning and certainty, ADHD is characterized by hypoactivity in these regions, as impulsivity may be related to a lack of planning or inhibitory control (Abramovitch et al., 2012; Rubia, Cubillo, Woolley, Brammar, and Smith, 2011). This supports a recently proposed “executive overload” model of OCD, which proposes that deficits in inhibitory control, performance monitoring, and other executive functions are a consequence of repeated attempts to control thoughts, leading to exhaustion of the executive system

(Abramovitch et al., 2012). Indeed, Abramovitch and colleagues (2012) found that while adults with OCD and adults with ADHD were impaired across neuropsychological measures compared with healthy controls, self-reported impulsivity was significantly correlated with OC symptom severity and response inhibition only among adults with OCD, but not among adults with ADHD or healthy controls. These results indicate that obsessions and compulsions are tied to ADHD

symptoms and response inhibition (i.e. a measure of executive dysfunction) among people with

OCD, but the two constructs are unrelated in people with subclinical levels of OC symptoms.

Abramovitch, Dar, Mittelman, and Schweiger (2013) replicated and extended these findings. In a comparison between adults with OCD, adults with ADHD, and healthy controls, they again found significant positive correlations between self-reported ADHD symptoms and OC symptoms only in the OCD group. They also showed that among healthy controls and adults with ADHD, childhood ADHD symptoms were strongly positively correlated with current

ADHD symptoms. Since OCD is often developed later in life, however (in their sample mean age of onset was 19.0 years [SD=6.8 years]), they did not expect this to be the case in those with

OCD. Their hypothesis was supported; only childhood impulsivity was moderately related to adult impulsivity in participants with OCD, but total ADHD symptoms, inattention, and hyperactivity in childhood were non-significantly correlated with these symptoms currently.

Similar results are echoed in the pediatric literature; deficits across multiple domains of parent- reported executive functioning, including set-shifting, inhibition, emotional control, planning and organizing, self-monitoring, and initiating tasks have been associated with increased OC symptom severity in children with the disorder (McNamara et al., 2014).

These findings beg the question of whether diagnosed ADHD in children with OCD always represents true ADHD pathology. It may be the case that OC symptoms cause inattention, hyperactivity, and impulsivity in many people with OCD, often leading to inappropriate ADHD diagnoses. In childhood OCD, this may manifest in externalizing symptoms exacerbated by the presence of OCD. For instance, children with OCD may have difficulty staying in their seat during class or paying attention to their parents due to having repeated intrusive thoughts, rather than having underlying inattentive, hyperactive dispositions. This hypothesis has never been

tested in children with the disorder, however, despite higher rates of ADHD identification in children compared with adults. Frontostriatal dysfunction tends to normalize following successful treatment of children and adolescents with OCD, and thus attentional abilities and impulsivity may improve as well (Freyer et al., 2011). If that is the case, ADHD symptoms may reduce following treatment that targets OC symptoms, and that reduction would be expected to correspond with reductions in OCD severity.

Study Aims

Aim 1. To investigate the impact of baseline ADHD symptoms on OCD treatment outcome.

Hypothesis 1: Elevated ADHD symptoms at baseline will predict less OC symptom reduction at the end of treatment. It is predicted that children with more severe ADHD symptoms will have more trouble resisting compulsions during treatment and may not encode corrective information following exposure exercises, leading to poorer response to treatment.

Aim 2. To investigate whether ADHD symptoms decline following successful treatment of

OCD.

Hypothesis 2a: ADHD symptoms at the end of treatment will be lower than ADHD symptoms measured at baseline. Children and adolescents who go through CBT-E/RP and SSRI treatment generally experience significant OC symptom relief. OC symptoms are hypothesized to be inherently tied to ADHD symptoms, and thus ADHD symptoms are expected to reduce as well.

Hypothesis 2b: Reductions in OC symptoms across treatment will predict reductions in ADHD symptoms. Since ADHD symptoms are expected to be caused by OC symptoms, those who experience relatively more OC symptom relief are expected to also experience relatively more

ADHD symptom reduction.

CHAPTER 2 METHODS

Participants

Participants were 48 children and adolescents enrolled in a randomized controlled trial investigating multimodal (CBT-E/RP+SSRI) treatment for OCD. Inclusion criteria for the study were: 1) age 7-17 years old, 2) a primary diagnosis of OCD as determined by a licensed psychologist or psychiatrist and the Schedule for Affective Disorders and Schizophrenia for

School-Age Children- Present and Lifetime Version (K-SADS-PL; Kaufman et al., 2000), 3) a score of at least 18 on the Children’s Yale-Brown Obsessive Compulsive Scale (Scahill et al.,

1997), 4) English speaking and ability to read. Exclusionary criteria were: 1) prior adequate trial of SSRIs, 2) history of rheumatic fever, serious autoimmune disorder, or other serious medical condition, 3) inability to swallow study medication, 4) presence of suicidal ideation or history of suicide attempt in the past year, 5) pregnancy or having unprotected sex in females, 6) presence of comorbid DSM-IV psychosis, bipolar disorder, autism, anorexia, or substance abuse, and 7) taking psychiatric medication other than psychostimulants for ADHD. Of note, three children in the present study were on a stable regimen of psychotimulants, and eight (17%) qualified for an

ADHD diagnosis per the cutoffs recommended for the parent-report ADHD measure described below and based the K-SADS-PL. Though 56 children were originally enrolled in the study, eight were lost to follow-up. Of the remaining 48, 28 were male (58%) and 46 identified as

Caucasian (96%), with one participant identifying as Black/African (2%) and one identifying as

Asian (2%). The mean age among participants was 11.75 years old (SD=3.23). Sample demographics are presented in Table 2-1.

Procedure

Participants were enrolled in a randomized controlled trial that compared three groups undergoing combined CBT-E/RP+SSRI treatment. Treatment was delivered at two sites: the

University of South Florida and the University of Florida. In each treatment group, children received 18 consecutive weeks of medication management with a board certified child and adolescent psychiatrist, and beginning at the fifth week, engaged in 14 consecutive weeks of

CBT-E/RP. Therapists were post-doctoral associates supervised by licensed psychologists trained and experienced in CBT-E/RP. In the first group (“RegSert+CBT-E/RP,” n=15, 31%),

SSRI dosages could be increased up to 50mg per week if tolerated, reaching a maximum dose of

200mg as quickly as by the fifth week. In the second group (“SlowSert+CBT-E/RP,” n=17,

35%), dosages could only be increased by 25mg per week when increases were tolerated, reaching the maximum possible dosage of 200mg no sooner than the ninth week. In the last group (“Placebo+CBT-E/RP,” n=16, 33%), participants received sham medication for the entire trial. Treating psychiatrists and psychologists were blind to group assignment. The study was approved by the institutional review boards at both sites. The purposes and benefits of the study were reviewed with each family, and parent consent and child assent were obtained prior to study involvement.

Measures

Demographics

Demographic data, including participant age and gender, were collected via a self-report measure at the beginning of the study.

Children’s Yale-Brown Obsessive-Compulsive Scale (CYBOCS)

The CYBOCS is a psychometrically validated, semi-structured assessment of OC symptoms in children (Scahill et al., 1997; Storch et al., 2004). The CYBOCS includes two five-

item sections measuring both obsessions and compulsions, each section assessing time taken by symptoms, distress, functional impairment, control over symptoms, and resistance against symptoms. Each item is scored from 0-4, with higher numbers indicating increased severity. The two sections are combined to create a total score ranging from 0-40. The CYBOCS was administered at the first and last sessions of treatment.

Swanson, Nolan, and Pelham-IV (SNAP-IV)

The SNAP-IV is a psychometrically sound, parent-report measure of externalizing symptoms in childhood (Bussing et al., 2008; Swanson et al., 2001). The measure consists of three factors, including a nine-item inattention factor, a nine-item hyperactivity-impulsivity factor, and an eight-item oppositional/defiant factor. For the present study, parents only completed the inattention and hyperactivity-impulsivity items. The two factors can be summed to create a total score reflecting total ADHD symptom severity. Parents completed the SNAP-IV at the first and last sessions of treatment.

Children’s Depression Rating Scale-Revised (CDRS-R)

The CDRS-R is a 17-item clinician-rated interview of childhood depressive symptoms.

The instrument is conducted with both parent and child and has demonstrated good psychometric properties, including strong inter-rater and test-retest validity, as well as criterion-related and construct validity (Mayes et al., 2010; Poznanski and Mokros, 1996). A measure of depression was included in this analysis as a covariate measure, as depression was shown to hinder treatment outcome in this sample (Meyer et al., 2014) and has been related to ADHD symptomology (Cataldo et al., 2005). The CDRS-R was administered at the end of weeks 1-9,

13, and 17.

Treatment-Emergent Activation and Suicidality Assessment Profile (TEASAP)

The TEASAP is a psychometrically sound parent-report measure of common side-effects of SSRIs (Reid et al., 2010; Bussing et al., 2013). The measure is divided into five common side- effect domains, including mania, irritability, jitteriness/akathesis, disinhibition, and self-harm.

SSRI side-effects as measured by the TEASAP have also been shown to impact treatment outcome (Reid et al., 2015), and certain side-effects measured in the TEASAP may manifest clinically as symptoms of ADHD (e.g. jitteriness, disinhibition), and thus the TEASAP was used as a covariate measure in statistical models. The TEASAP was administered at sessions 1-9, 13, and 17.

Statistical Analyses

There were no differences in treatment response or pre-trial clinical characteristics among the RegSert+CBT-E/RP, SlowSert+CBT-E/RP, and Placebo+CBT-E/RP groups (Storch et al., 2013). Thus, for the present study, the three groups were combined to evaluate change over treatment for the entire sample.

Preliminary Covariate Analyses

Preliminary correlational analyses were used to assess appropriate covariates to use in regression models. The main dependent and independent variables of interest were 1) baseline

SNAP-IV, 2) change in CYBOCS, and 3) change in SNAP-IV. Change scores were calculated by taking the difference of the measurements at the first and final sessions of treatment. Though many have deemed change scores to be unreliable due to regression to the mean and measurement error (e.g. Cronbach & Furby, 1970), others have suggested that difference scores have strengths in their intuitiveness, and are not nearly as susceptible to regression to the mean as some theorists propose (Allison, 1990; Rogosa, 1995). Dummy-coded treatment group, age, and gender were included as possible covariates.

Aim 1: Predicting Change in OCD Severity

To assess whether ADHD symptoms at baseline predict reductions in OC symptoms, hierarchical linear regression was used with an OCD change score (CYBOCS at baseline-

CYBOCS at final session) as the dependent variable. Five-hundred bootstrapped samples were used to account for non-normal distributions in variables. In the first step of the model, baseline

CYBOCS score was used to control for regression to the mean among participants with higher baseline severity scores. Each subsequent covariate was then entered in its own step: gender, baseline-centered TEASAP (the average TEASAP score compared to the first measurement was used to capture medication side-effects), and average CDRS-R score during treatment. In the final step, baseline SNAP-IV scores were included in the model.

Aim 2: ADHD Symptom Reduction during Treatment

Hypothesis 1: ADHD symptoms at baseline will be significantly greater than ADHD symptoms at the end of treatment

To assess whether ADHD symptoms reduced across treatment, a 500 bootstrapped samples paired t-test was used, comparing baseline SNAP-IV scores and SNAP-IV scores at the final session of treatment.

Hypothesis 2: Reduction in OC symptoms will predict reduction in ADHD symptoms

To assess whether changes in OCD severity predict changes in ADHD, another 500- bootstrapped hierarchical linear regression was used. In the current model, change in SNAP-IV scores was used as the dependent variable (baseline SNAP-IV score minus the SNAP-IV score at the final session). Similar to the first model, baseline SNAP-IV was entered in the first step to control for regression to the mean among individuals who scored relatively highly on the first measurement. The following variables were each entered by themselves in sequential steps: gender, baseline-centered TEASAP (using the same method as described above), and mean

CDRS-R scores during treatment. In the final step, both baseline CYBOCS and change in

CYBOCS scores (baseline CYBOCS score minus CYBOCS score at the final session) were entered. Though change in CYBOCS was the primary variable of interest in this model, baseline

CYBOCS was also entered as a covariate to control for regression to the mean among participants who had relatively high CYBOCS scores at baseline.

Table 2-1. Sample demographics (n=48) Age in years M (SD) 11.8 (3.2) Gender N (%) Male 28 (58) Female 20 (42) Race N (%) White/Caucasian 46 (95.8) Black/African American 1 (2.1) Asian 1 (2.1)

CHAPTER 3 RESULTS

Preliminary Correlational Analyses

For Aim 1, dummy coded RegSert group assignment vs. other groups, SlowSert group assignment vs. other groups, age, and gender (male=0, female=1) were correlated with the IV and DV of interest: baseline SNAP-IV score and change in CYBOCS score. Only gender was significantly correlated with baseline ADHD severity, with male gender being significantly correlated with SNAP-IV scores (r=-.334, p=.020). Thus, gender was included as a covariate in the regression model in Aim 1.

For Aim 2, dummy coded RegSert group assignment vs. other groups, SlowSert group assignment vs. other groups, age, and gender (male=0, female=1) were correlated with change in

SNAP-IV scores. The IV of interest in this model was change in CYBOCS, which revealed no significant correlations, as described above. Again, gender was related to SNAP-IV change across treatment, with boys experiencing a greater decrease in ADHD symptoms (r=-.291, p=.045). This is likely due to regression to the mean, as boys started with higher SNAP-IV scores, and thus have more arithmetic opportunity for decline. Thus, gender was also included as a covariate in the regression model in Aim 2.

Overall, gender was significantly correlated with both baseline SNAP-IV and change in

SNAP-IV score, and thus it was included as a covariate in subsequent analyses. Preliminary correlations are summarized in Table 3-1.

Aim 1. Predicting OC Symptom Reduction

In the first step in the regression, baseline CYBOCS score was entered as a predictor of change in CYBOCS score (pre-CYBOCS minus post-CYBOCS). Higher baseline CYBOCS scores were significantly positively associated with CYBOCS change (β=.350, p=.028), with the

initial model explaining 12.1% of the variance in CYBOCS change (adjusted R2=.103). In the next step, gender was added, which was a non-significant predictor of CYBOCS change (β=.039, p=.75) and only explained an additional 0.3% of the variance in CYBOCS change (R2=.123, adjusted R2=.085). Baseline-centered TEASAP was entered in the next step, which was a non- significant predictor (β=.010, p=.94) that did not improve the model (R2=.123, adjusted R2=.065).

Mean depression during treatment was added in the next step, which significantly predicted

CYBOCS change (β=-.405, p=.002) and explained an additional 15.6% of the variance in

CYBOCS change (R2=.279, adjusted R2=.212).

The final model, which included baseline SNAP-IV scores, only explained an additional

0.1% of the variance in CYBOCS change (R2=.280, adjusted R2=.194). Baseline SNAP-IV scores did not significantly predict CYBOCS change (β=-.027, p=.846). In the final regression model, predictors that were previously significant remained significant. Final regression coefficients and other pertinent parameters are presented in Table 3-2.

Aim 2. ADHD Symptom Reduction during Treatment

Hypothesis 1: ADHD symptoms at baseline will be significantly greater than ADHD symptoms at the end of treatment

SNAP-IV scores at baseline (M=18.6, SD=13.1) were greater than SNAP-IV scores at the end of treatment (M=15.5, SD=11.9). Bootstrapped paired-samples t-tests indicated that this difference represented a small, significant effect (t[47]=2.560, p=.01, Cohen’s D=.245). See

Figure 3-1 for a visual depiction of SNAP-IV before and after treatment.

Hypothesis 2: Reduction in OC symptoms will predict reduction in ADHD symptoms

The dependent variable for the present analysis was change in SNAP-IV scores

(measured as baseline SNAP-IV minus SNAP-IV at the final treatment session). Baseline SNAP-

IV was entered in the first step of the regression, which was a significant predictor of SNAP-IV

change (β=.465, p=.008), explaining 21.6% of the variance in SNAP-IV change (adjusted

R2=.199). In step 2, gender was added to the model, which was a non-significant predictor (β=-

.153, p=.359) that explained an additional 2.1% of the variance in SNAP-IV change (R2=.237, adjusted R2=.203). Adding average SSRI side-effects, as measured by baseline-centered mean

TEASAP scores, explained an additional 8.9% of the variance in the DV (R2=.326, adjusted

R2=.281). In this model, baseline SNAP-IV scores became non-significant (β=.300, p=.092), and mean SSRI side-effects were almost significant in predicting ADHD change, such that a one standard deviation increase in SSRI side-effects corresponded with a .319 standard deviation decrease in ADHD symptom reduction (β=-.319, p=.050). In the next step, mean CDRS-R scores were added to the model, which were a non-significant predictor of SNAP-IV change (β=-.217, p=.150), explaining and additional 4.3% of the variance (R2=.369, adjusted R2=.310). In that model, baseline ADHD symptoms again became a significant predictor (β=.341, p=.028) and

TEASAP remained trending towards significance (β=-.260, p=.070).

The final model added baseline CYBOCS score and CYBOCS change score, as calculated by the first CYBOCS score minus the last CYBOCS score. Baseline CYBOCS was non-significant (β=-.208, p=.128), but CYBOCS change was highly predictive of SNAP-IV change, such that a one standard deviation reduction in OCD symptoms corresponded with a

.399 standard deviation reduction in ADHD symptoms (β=.399, p=.004). This model explained an additional 11.5% of the variance in SNAP-IV change, with the final model explaining about

41% of the variance in SNAP-IV change (R2=.484, adjusted R2=.409). Estimated regression coefficients and other pertinent parameters for the final regression model are presented in Table

3-3.

To provide a visual depiction of this pattern of results, Figure 3-2 shows change in

ADHD symptoms across treatment for each participant. Participants were divided into two groups based on whether or not they met “remission” status at the end of treatment, as indicated by at least a 45% reduction in OC symptoms (Storch, Lewin, De Nadai, & Murphy, 2010).

Inspection of this figure shows that among children in the “remission” group, 8 of 9 participants with baseline SNAP-IV scores above 20 showed symptom reduction after OCD treatment, while there is no easily discernable pattern among those in the “not in remission” group1.

1 This approach is meant as a descriptive aid in the interpretation of these results, but do not reflect the statistical analysis used (i.e., participants were not broken up into “remission” and “not in remission” groups in the regression).

Table 3-1. Correlations between potential regression model covariate and independent and dependent variables of interest Correlation coefficients Baseline SNAP-IV ∆SNAP-IV ∆CYBOCS RegSert+CBT-E/RP vs. others .168 -.056 -.170 SlowSert+CBT-E/RP vs. others -.207 -.015 .008 Age -.068 -.195 -.038 Gender -.334 -.291* .002 *p<.05; Note: RegSert+CBT-E/RP: Regular Titration of Sertraline; SlowSert+CBT-E/RP: Slow Titration of Sertraline; ∆: Change (baseline score minus final score)SNAP-IV: Swanson Nolan and Pelham-IV; CYBOCS: Children’s Yale-Brown Obsessive-Compulsive Scale

Table 3-2. Regression model predicting change in CYBOCS score before and after treatment

2 2 B β p R Adjusted R Baseline CYBOCS .767* 0.443* .014 .280 .194 Gender 2.565 0.162 .230 Baseline-centered TEASAP .066 0.068 .569 Mean CDRS-R -.420** -0.409** .004 Baseline SNAP-IV .016 -0.027 .846 *p<.05, **p<.01 Note: SNAP-IV: Swanson Nolan and Pelham-IV; TEASAP: Treatment Emergent Activation and Suicidality Assessment Profile; CDRS-R: Children’s Depression Rating Scale-Revised, CYBOCS: Children’s Yale-Brown Obsessive-Compulsive Scale

Table 3-3. Regression model predicting change in SNAP-IV score before and after treatment

2 2 B β p R Adjusted R Baseline SNAP-IV severity .219* 0.336* .024 .484 .409 Gender -3.324 -0.194 .172 Baseline-centered TEASAP -.297† -0.282† .062 Mean CDRS-R symptoms -.055 -0.049 .756 Baseline CYBOCS symptoms -.389 -0.208 .128 Δ CYBOCS .432** 0.399** .004 *p<.05, **p<.01 Note: SNAP-IV: Swanson Nolan and Pelham-IV; TEASAP: Treatment Emergent Activation and Suicidality Assessment Profile; CDRS-R: Children’s Depression Rating Scale-Revised, CYBOCS: Children’s Yale-Brown Obsessive-Compulsive Scale

Figure 3-1. Mean ADHD symptom reduction across treatment.

In remission (≥45% CYBOCS reduction): Not in remission:

Figure 3-2. ADHD symptom reduction among those in remission and those not in remission

CHAPTER 4 DISCUSSION

Results from this study reveal that ADHD symptoms decline following OCD treatment, and that success in treatment predicts relatively greater improvement in ADHD symptoms.

Children in the present study underwent an intervention that specifically targeted OC symptoms, and not secondary problems like inattention or hyperactivity. Thus, changes in secondary outcomes such as ADHD can be attributed to the targeted OCD intervention. Though reductions in ADHD symptoms were significant, they were largely modest, and may not have reflected clinically meaningful change in many children (Figure 3-1). It may be more appropriate to conclude that OCD exacerbates inattention, hyperactivity, and impulsivity, rather than causes these symptoms. That said, descriptive analyses presented in Figure 3-2 show that several children who were in remission at the end of treatment with severe ADHD symptoms at baseline experienced dramatic reductions in ADHD symptoms, but the same cannot be said for those not in remission. Together, these findings indicate that among many children with OCD, ADHD symptoms are inherently tied to their obsessions and compulsions.

The hypothesis that ADHD symptoms at the beginning of treatment would hinder treatment was unsupported; parent-reported ADHD symptoms at baseline failed to predict OC symptom reduction during treatment. At first glance, this finding appears to contradict previous literature that found a strong detrimental effect of ADHD comorbidity on CBT-E/RP treatment outcome (Storch et al., 2008). In the present study, the majority of children had subclinical

ADHD symptoms at baseline, potentially limiting our ability to detect an effect of elevated

ADHD symptomology. In light of previous literature, this result indicates that only severe levels of ADHD may impede treatment outcome. Future studies should to continue to investigate this hypothesis.

These findings provide support for the recently proposed “executive overload” model of

OCD (Abramovitch et al., 2012). Deficits in frontal/executive functions like attention, working memory, planning, and organization are commonly associated with ADHD, and are often thought to manifest as impulsivity and hyperactivity in children. That said, previous studies have failed to consistently find neurocognitive deficits that are hallmarks of ADHD such as inattention and executive dysfunction in children with OCD despite relatively consistent findings in the adult literature that point to the contrary (Abramovitch et al., 2015). Thus, it may be that the clinical features of ADHD, such as restlessness or inattention during conversations, appear before functional cognitive deficits are observed. This phenomenon would be expected to be reflected in parent-report measures of ADHD, such as the SNAP-IV used in this study. In many cases, parent-reported ADHD symptoms such as difficulty staying seated in class or following instructions may be a consequence of OC symptoms. It may be that having OCD for longer periods of time puts tremendous strain on the cognitive system, such that performance-based cognitive deficits are only observed in adults with the condition, but that the clinical expression of frontal dysfunction manifests in childhood.

Inattention, impulsivity, and hyperactivity in OCD and ADHD may be appropriately conceptualized through the Yerkes-Dotson law, which proposes that mental and/or physiological arousal improves performance to a certain point, but hinders performance when arousal becomes too high (Yerkes & Dotson, 1908). Through this lens, perhaps individuals with ADHD and those with OCD fall on opposite sides of a “Yerkes-Dotson” curve, as inattention and impulsivity may be exacerbated by low levels of cognitive arousal in those with ADHD and by excessive frontal activity in those with OCD.

Depressive symptoms often remit following successful treatment of OCD (Meyer et al.,

2014), but the same has not been said about ADHD. These data indicate that OCD may exacerbate externalizing problems like ADHD as well. This notion may be somewhat counterintuitive to many mental health professionals, as ADHD is often thought of as representative of unchanging, inherent dysfunction in the brain. Practitioners and researchers alike may diagnose ADHD in children with OCD when impairing levels of inattention, hyperactivity, and/or impulsivity are observed. As this study and others report, this phenomenon may instead be a consequence of severe obsessive anxiety and compulsive rituals, rather than true ADHD presence.

This last point brings attention to limitations in our current first-line psychiatric classification system. Structured diagnostic interviews are regarded as the gold-standard assessments of psychopathology. The principal method of making diagnoses under this system is to determine whether a person endorses a certain number of symptoms on a “checklist,” which may not reflect the true underlying nature psychopathology. Indeed, several children in this study who met criteria for ADHD at the beginning of treatment may have failed to reach clinical thresholds at the end of the study. This points further to the need for research into alternative diagnostic systems in clinical psychology and psychiatry, as symptom checklists may not fully capture the nature of a given person’s mental health problems.

One conclusion that may be drawn from this study is that clinicians should be cautious with a diagnosis of ADHD in children with OCD. An incorrect diagnosis can unnecessarily place children on psychostimulant medication, on which they can become dependent and may misuse

(Wilens et al., 2008). Misdiagnosis could also affect their attentional self-efficacy, putting them at risk for self-handicapping and underachieving in a variety of contexts. Instead, it may be

useful to take a “response-to-intervention” approach to diagnosing ADHD in this population; when a child presents with a primary diagnosis of OCD and co-occurring inattention and/or hyperactivity-impulsivity, it may be useful to initially target only obsessive-compulsive symptoms in treatment. If treatment is completed and successful, children may often also experience a clinically meaningful reduction in ADHD. If ADHD symptoms remain despite an adequate trial of CBT-E/RP, SSRIs, or their combination, augmentation strategies such as behavioral management or psychostimulant treatment may be helpful.

The findings of this study are strengthened by a randomized controlled trial design, as children in this study underwent tightly regulated treatment protocols. This type of design strengthens the ability to draw conclusions about the effects of treatment on secondary outcomes like ADHD. Though three children in the study were receiving psychostimulant treatment for

ADHD, inclusion criteria mandated that they be on a stable dosage (i.e. unchanging for at least three months). Thus, all children received treatment that explicitly targeted OCD, and changes in

ADHD can be attributed to an OCD intervention, rather than uncontrolled psychiatric and/or psychological treatment. This was the first study to test whether ADHD symptoms in OCD are a consequence of obsessional distress in a pediatric population.

Though findings from this thesis support recent literature reaching similar conclusions about the nature of ADHD symptoms in people with OCD (Abramovitch et al., 2012; 2013), our results are preliminary in nature and are limited by a low sample size and relatively few children diagnosed with ADHD (n=8/48). Children did not receive a diagnostic interview at the end of treatment, limiting our ability to test whether any of the eight children diagnosed with ADHD at the beginning of the study no longer met DSM-IV diagnostic criteria for the disorder. The study would have further benefitted from functional measures of attention, more comprehensive

assessments of ADHD symptoms (e.g. a clinical interview at the end of treatment, other self- report measures), and more frequent measurements of ADHD symptoms throughout treatment in order to assess change more reliably.

Future research should replicate these findings with a larger sample using more comprehensive measures of ADHD. Cross-sectional studies comparing children with ADHD, children with OCD, and healthy controls on various measures of internalizing and externalizing symptoms could provide another avenue of inquiry to determine the reliability of ADHD diagnoses in children with OCD. Future research could also investigate whether the pattern of findings described in this thesis occur in children with other internalizing disorders; it may be the case that generalized anxiety or depression also exacerbate ADHD-like symptoms. Some investigators have begun to investigate other externalizing features that are tied to OCD; specifically, research into coercive and disruptive behaviors in OCD has emerged in the past few years (e.g. Lebowitz, Omar, & Leckman, 2011; Lebowitz, Storch, MacLeod, & Leckman, 2014).

In their work, Lebowitz and colleagues describe the common phenomenon of children imposing demands on parents and others to accommodate their obsessions and compulsions (e.g. depriving parents of sleep by demanding them to sleep with them or assist in bedtime rituals; forcing parents to only have certain foods in the house, refusing to go certain “dangerous” places with the family). It may be the case that more generalized defiance may also be spurred by OCD, as oppositional defiant disorder is highly comorbid in OCD (Storch et al., 2010). Research should investigate whether both generalized and OCD-specific defiance reduce following successful treatment of OCD as well.

ADHD is considered by many to be the clinical expression of unchanging, chronic brain dysfunction. Results from this study indicate that inattention, hyperactivity, and impulsivity

reduce following success in an OCD-specific intervention that did not explicitly target any of these symptoms, and thus other factors may contribute to the externalizing symptoms associated with ADHD. Mental health problems are often tied together, and strict diagnostic categories rarely capture the depth and complexity of psychological distress. ADHD-like symptoms are just one of the consequences of OCD that extend beyond its specific diagnostic checklist, and future work should continue to identify secondary cognitive, behavioral, and emotional sequalae of

OCD and other psychological disorders.

REFERENCES

Abramovitch, A., Abramowitz, J. S., & Mittelman, A. (2013). The neuropsychology of adult obsessive-compulsive disorder: a meta-analysis. Clinical Psychology Review, 33(8), 1163–1171.

Abramovitch, A., Abramowitz, J. S., Mittelman, A., Stark, A., Ramsey, K., & Geller, D. A. (2015). Research Review: Neuropsychological test performance in pediatric obsessive– compulsive disorder–a meta‐analysis. Journal of Child Psychology and Psychiatry.

Abramovitch, A., Dar, R., Hermesh, H., & Schweiger, A. (2012). Comparative neuropsychology of adult obsessive‐compulsive disorder and attention deficit/hyperactivity disorder: Implications for a novel executive overload model of OCD. Journal of Neuropsychology, 6(2), 161-191.

Allison, P. D. (1990). Change scores as dependent variables in regression analysis. Sociological Methodology, 20(1), 93-114.

Alonso, P., Menchón, J. M., Jiménez, S., Segalàs, J., Mataix-Cols, D., Jaurrieta, N., ... & Pujol, J. (2008). Personality dimensions in obsessive–compulsive disorder: Relation to clinical variables. Psychiatry Research, 157(1), 159-168.

American Psychiatric Association (2013). Diagnostic and Statistical Manual of Mental Disorders, 5th ed. American Psychiatric Publishing, Arlington, VA.

Asherson, P., & Trzaskowski, M. (2015). Attention-Deficit/Hyperactivity disorder is the extreme and impairing tail of a continuum. Journal of the American Academy of Child and Adolescent Psychiatry. 54(4), 249.

Aycicegi, A., Dinn, W. M., Harris, C. L., & Erkmen, H. (2003). Neuropsychological function in obsessive-compulsive disorder: Effects of comorbid conditions on task performance. European Psychiatry: The Journal of the Association of European Psychiatrists, 18(5), 241-248.

Blaskey, L. G., Harris, L. J., & Nigg, J. T. (2008). Are sensation seeking and emotion processing related to or distinct from cognitive control in children with ADHD? Child Neuropsychology: A Journal On Normal and Abnormal Development In Childhood And Adolescence, 14(4), 353-371.

Bruchmüller, K., Margraf, J., & Schneider, S. (2012). Is ADHD diagnosed in accord with diagnostic criteria? Overdiagnosis and influence of client gender on diagnosis. Journal of Consulting and Clinical Psychology, 80(1), 128.

Bussing, R., Fernandez, M., Harwood, M., Hou, W., Garvan, C. W., Eyberg, S. M., & Swanson, J. M. (2008). Parent and teacher SNAP-IV ratings of attention deficit hyperactivity disorder symptoms psychometric properties and normative ratings from a school district sample. Assessment, 15(3), 317-328.

Bussing, R., Murphy, T. K., Storch, E. A., McNamara, J. P., Reid, A. M., Garvan, C. W., & Goodman, W. K. (2013). Psychometric properties of the Treatment-Emergent Activation and Suicidality Assessment Profile (TEASAP) in youth with OCD. Psychiatry Research, 205(3), 253-261.

Cataldo, M, G., Nobile, M. Lorusso, M. L., Battaglia, M., & Moleteni, M. (2005). Impulsivity in depressed children and adolescents: A comparison between behavioral and neuropsychological data. Psychiatry Research, 136, 123-133

Chabane, N., Delorme, R., Golmard, J., Krebs, M., Leboyer, M., Millet, B., & Mouren-Simeoni, M. (2005). Admixture analysis of age at onset in obsessive-compulsivedisorder. Psychological Medicine, 35(2), 237-243.

Chamberlain, Blackwell, A. D., Fineberg, N. A., Robbins, T. W., & Sahakian, B. J. (2005). The neuropsychology of obsessive compulsive disorder: The importance of failures in cognitive and behavioural inhibition as candidate endophenotypic markers. Neuroscience & Biobehavioral Reviews, 29(3), 399-419.

Cronbach, L. J., & Furby, L. (1970). How we should measure" change": Or should we?. Psychological bulletin, 74(1), 68.

Donfrancesco, R., Di Trani, M., Porfirio, M. C., Giana, G., Miano, S., & Andriola, E. (2015). Might the temperament be a bias in clinical study on attention-deficit hyperactivity disorder (ADHD)?: Novelty Seeking dimension as a core feature of ADHD. Psychiatry Research, 227(2), 333-338.

Drechsler, R., Rizzo, P., & Steinhausen, H. (2008). Decision-making on an explicit risk-taking task in preadolescents with attention-deficit/hyperactivity disorder. Journal of Neural Transmission, 115(2), 201-209.

Fitzgerald, K. D., Welsh, R. C., Stern, E. R., Angstadt, M., Hanna, G. L., Abelson, J. L., & Taylor, S. F. (2011). Developmental alterations of frontal-striatal-thalamic connectivity in obsessive-compulsive disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 50(9), 938-948.

Frazier, T. W., Demarree, H. A., & Youngstrom, E. A. (2004). A meta-analysis of intellectual and neuropsychological test performance in attention-deficit/ hyperactivity disorder. Neuropsychology, 18, 543–555.

Freeman, J., Garcia, A., Frank, H., Benito, K., Conelea, C., Walther, M., & Edmunds, J. (2014). Evidence base update for psychosocial treatments for pediatric obsessive-compulsive disorder. Journal of Clinical Child & Adolescent Psychology, 43(1), 7-26.

Freyer, T., Kloppel, S., Tuscher, O., Kordon, A., Zurowski, B., Kuelz, A. -., . . . Voderholzer, U. (2011). Frontostriatal activation in patients with obsessive-compulsive disorder before and after cognitive behavioral therapy. Psychological Medicine, 41(1), 207-216.

Geller, D. A., Biederman, J., Faraone, S., Agranat, A., Cradock, K., Hagermoser, L., . . . Coffey, B. J. (2001). Developmental aspects of obsessive compulsive disorder: Findings in children, adolescents, and adults. The Journal of Nervous and Mental Disease, 189(7), 471-477.

Geller, D. A., Biederman, J., Faraone, S. V., Cradock, K., Hagermoser, L., Zaman, N., ... & Spencer, T. J. (2002). Attention-deficit/hyperactivity disorder in children and adolescents with obsessive-compulsive disorder: fact or artifact?. Journal of the American Academy of Child & Adolescent Psychiatry, 41(1), 52-58.

Geller, D. A., Coffey, B., Faraone, S., Hagermoser, L., Zaman, N. K., Farrell, C. L., ... & Biederman, J. (2003). Does comorbid attention-deficit/hyperactivity disorder impact the clinical expression of pediatric obsessive-compulsive disorder?. CNS Spectrums, 8(04), 259-264.

Geller, D., Donnelly, C., Lopez, F., Rubin, R., Newcorn, J., Sutton, V., et al. (2007a). Atomoxetine treatment for pediatric patients with attention-deficit/hyperactivity disorder with comorbid anxiety disorder. Journal of the American Academy of Child and Adolescent Psychiatry, 46, 1119-1127.

Geller, D., Petty, C., Vivas, F., Johnson, J., Pauls, D., & Biederman, J. (2007b). Further evidence for co-segregation between pediatric obsessive compulsive disorder and attention deficit hyperactivity disorder: a familial risk analysis. Biological Psychiatry, 61(12), 1388-1394.

Goldman, L. S., Genel, M., Bezman, R. J., & Slanetz, P. J. (1998). Diagnosis and treatment of attention-deficit/hyperactivity disorder in children and adolescents. Jama, 279(14), 1100- 1107.

Hervey, A. S., Epstein, J. N., & Curry, J. F. (2004). Neuropsychology of adults with attention- deficit/hyperactivity disorder: A meta-analytic review. Neuropsychology, 18(3), 485-503.

Ivarsson, T., Melin, K., & Wallin, L. (2008). Categorical and dimensional aspects of comorbidity in obsessive-compulsive disorder (OCD). European Child & Adolescent Psychiatry, 17(1), 20-31.

Kaufman, J., Birmaher, B., Brent, D., Rao, U., & Ryan, N. (1996). Kiddie-Sads-present and Lifetime version (K-SADS-PL). Pittsburgh, University of Pittsburgh, School of Medicine.

Koran, L.M., Hanna, G.L., Hollander, E., Nestadt, G., & Simpson, H.B. (2007). Practice guideline for the treatment of patients with obsessive-compulsive disorder. American Psychiatric Publishing, Arlington, VA.

Lacerda A.L.T., Dalgalarrondo P., Caetano D., et al. (2003) Neuropsychological performance and regional cerebral blood flow in obsessive–compulsive disorder. Progress in Neuro- Psychopharmacology & Biological Psychiatry, 27, 657–665

Lawrence, N, S., Wooderson, S., Mataix-Cols, D., David, R., Speckens, A., & Phillps, M, L., (2005). Decision making and set shifting impairments are associated with distinct symptom dimensions in obsessive-compulsive disorder. Neuropsychology, 20, 409-419

Lebowitz, E. R., Omer, H., & Leckman, J. F. (2011). Coercive and disruptive behaviors in pediatric obsessive-compulsive disorder. Depression and Anxiety,28(10), 899-905.

Lebowitz, E. R., Storch, E. A., MacLeod, J., & Leckman, J. F. (2014). Clinical and family correlates of coercive-disruptive behavior in children and adolescents with obsessive- compulsive disorder. Journal of Child and Family Studies.

Lucey J.V., Burness C.E., Costa D.C. (1997) Wisconsin card sorting task (errors)and cerebral blood flow in obsessive-compulsive disorder. British Journal of Medical Psychology, 70, 403–411.

Masi, G., Millepiedi, S., Mucci, M., Bertini, N., Pfanner, C., & Arcangeli, F. (2006). Comorbidity of obsessive-compulsive disorder and attention-deficit/hyperactivity disorder in referred children and adolescents. Comprehensive Psychiatry, 47(1), 42-47.

Mayes, T. L., Bernstein, I. H., Haley, C. L., Kennard, B. D., & Emslie, G. J. (2010). Psychometric properties of the Children's Depression Rating Scale–Revised in adolescents. Journal of Child and Adolescent Psychopharmacology, 20(6), 513-516.

McNamara, J. P., Reid, A. M., Balkhi, A. M., Bussing, R., Storch, E. A., Murphy, T. K., ... & Geffken, G. R. (2014). Self-regulation and other executive functions relationship to pediatric OCD severity and treatment outcome. Journal of Psychopathology and Behavioral Assessment, 36(3), 432-442.

Meyer, J. M., Mcnamara, J. P., H., Reid, A. M., Storch, E. A., Geffken, G. R., . . . Bussing, R. (2014). Prospective relationship between obsessive-compulsive and depressive symptoms during multimodal treatment in pediatric obsessive-compulsive disorder. Child Psychiatry and Human Development, 45(2), 163-72.

Obsessive Compulsive Cognitions Working Group. (1997). Cognitive assessment of obsessive- compulsive disorder. Behaviour Research and Therapy, 35(7), 667-681.

Piacentini, J., Langley, A., & Roblek, T. (2007). Cognitive-Behavioral Treatment of Childhood OCD: Its Only a False Alarm Therapist Guide. Oxford University Press.

Poznanski, E. O., & Mokros, H. B. (1996). Children's Depression Rating Scale, Revised (CDRS- R). Los Angeles: Western Psychological Services.

Reid, A. M., McNamara, J. P., Murphy, T. K., Guzick, A. G., Storch, E. A., Geffken, G. R., & Bussing, R. (2015). Side-effects of SSRIs disrupt multimodal treatment for pediatric OCD in a randomized-controlled trial. Journal of Psychiatric Research, 71, 140-147.

Reid, J. M., Storch, E. A., Murphy, T. K., Bodzin, D., Mutch, P. J., Lehmkuhl, H., ... & Goodman, W. K. (2010). Development and psychometric evaluation of the treatment- emergent activation and suicidality assessment profile. In Child & youth care forum, 39 (2), 113-124).

Rogosa, D. (1995). Myths and methods:“Myths about longitudinal research” plus supplemental questions. The Analysis of Change, 3, 66.

Rubia, K., Cubillo, A., Woolley, J., Brammer, M. J., & Smith, A. (2011). Disorder-specific dysfunctions in patients with attention-deficit/hyperactivity disorder compared to patients with obsessive-compulsive disorder during interference inhibition and attention allocation. Human Brain Mapping, 32(4), 601-611.

Scahill, L., Riddle, M. A., McSwiggin-Hardin, M., Ort, S. I., King, R. A., Goodman, W. K., ... & Leckman, J. F. (1997). Children's Yale-Brown obsessive compulsive scale: reliability and validity. Journal of the American Academy of Child & Adolescent Psychiatry, 36(6), 844- 852.

Sciutto, M. J., & Eisenberg, M. (2007). Evaluating the evidence for and against the overdiagnosis of ADHD. Journal of Attention Disorders, 11(2), 106-113.

Storch, E. A., Bussing, R., Small, B. J., Geffken, G. R., McNamara, J. P., Rahman, O., . . . Murphy, T. K. (2013). Randomized, placebo-controlled trial of cognitive-behavioral therapy alone or combined with sertraline in the treatment of pediatric obsessive- compulsive disorder. Behaviour Research and Therapy, 51(12), 823-829.

Storch, E. A., Lack, C., Merlo, L. J., Marien, W. E., Geffken, G. R., Grabill, K., . . . Goodman, W. K. (2007). Associations between miscellaneous symptoms and symptom dimensions: An examination of pediatric obsessive-compulsive disorder. Behaviour Research and Therapy, 45(11), 2593-2603.

Storch, E. A., Lewin, A. B., Geffken, G. R., Morgan, J. R., & Murphy, T. K. (2010). The role of comorbid disruptive behavior in the clinical expression of pediatric obsessive-compulsive disorder. Behaviour Research and Therapy, 48(12), 1204-1210.

Storch, E. A., Lewin, A. B., De Nadai, A. S., & Murphy, T. K. (2010). Defining treatment response and remission in obsessive-compulsive disorder: a signal detection analysis of the children's yale-brown obsessive compulsive scale. Journal of the American Academy of Child & Adolescent Psychiatry, 49(7), 708-717.

Storch, E. A., Merlo, L. J., Larson, M. J., Geffken, G. R., Lehmkuhl, H. D., Jacob, M. L., ... & Goodman, W. K. (2008). Impact of comorbidity on cognitive-behavioral therapy response in pediatric obsessive-compulsive disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 47(5), 583-592.

Storch, E. A., Murphy, T. K., Geffken, G. R., Soto, O., Sajid, M., Allen, P., ... & Goodman, W. K. (2004). Psychometric evaluation of the Children's Yale–Brown Obsessive-Compulsive Scale. Psychiatry Research, 129(1), 91-98.

Swanson, J. M., Kraemer, H. C., Hinshaw, S. P., Arnold, L. E., Conners, C. K., Abikoff, H. B., ... & Wu, M. (2001). Clinical relevance of the primary findings of the MTA: success rates based on severity of ADHD and ODD symptoms at the end of treatment. Journal of the American Academy of Child & Adolescent Psychiatry, 40(2), 168-179.

Van Ameringen, M., Mancini, C., & Oakman, J. M. (1998). The relationship of behavioral inhibition and shyness to anxiety disorder. The Journal of Nervous and Mental Disease, 186(7), 425-431.

Walitza, S., Zellmann, H., Irblich, B., Lange, K. W., Tucha, O., Hemminger, U., ... & Warnke, A. (2008). Children and adolescents with obsessive-compulsive disorder and comorbid attention-deficit/hyperactivity disorder: preliminary results of a prospective follow-up study. Journal of Neural Transmission, 115(2), 187-190.

Wilens, T. E., Adler, L. A., Adams, J., Sgambati, S., Rotrosen, J., Sawtelle, R., . . . Fusillo, S. (2008). Misuse and diversion of stimulants prescribed for ADHD: A systematic review of the literature. Journal of the American Academy of Child and Adolescent Psychiatry, 47(1), 21-31.

Yerkes, RM, & Dodson, JD. (1908). The relation of strength of stimulus to rapidity of habit- formation. Journal of Comparative Neurology and Psychology, 18, 459-482.

BIOGRAPHICAL SKETCH

Andrew G. Guzick is a second-year graduate student in the Department of Clinical and

Health Psychology at the University of Florida. After earning a bachelor’s degree in psychology from Vassar College in 2013, he volunteered in the Division of Medical Psychology at the

University of Florida as a research assistant, helping with their OCD treatment outcome projects.

He also served as a therapist aide for the division during this time, assisting in exposure-based treatments for individuals seeking treatment in their clinic. Andrew was offered the opportunity to begin his graduate studies in clinical psychology at the University of Florida in Fall, 2014, and continued working in the Division of Medical Psychology as a graduate assistant. Since beginning graduate school, Andrew’s interest in OCD, anxiety disorders, and related disorders has continued to grow. He strongly identifies with the scientist-practitioner model, with an interest in pursuing clinically applicable research that can help improve our understanding of

OCD and related disorders and enhance treatment outcomes.