Faculty Bibliography

OBJECTIVE:Research on pediatric bipolar disorder (PBD) has grown substantially in the past 7 years; updating a 2011 meta-analysis of PBD prevalence could improve understanding of factors that influence prevalence. DATA SOURCES:A literature review of papers published in English was updated in 2018 using PubMed and PsycINFO. Search terms included pediatric, child, "bipolar disorder," bipolar, mania, prevalence, epidemiology, community, adolescent, and youth. STUDY SELECTION:Inclusion criteria were (1) youth epidemiologic sample, (2) number of youth with bipolar spectrum disorders reported, and (3) prevalence rates for youth differentiated from prevalence for those over age 21 years (if both included). Of 2,400 articles retrieved, 44 were evaluated and 8 new were included. DATA EXTRACTION:Prevalence rates for each bipolar subtype were recorded as reported; hypothesized moderators (eg, study characteristics, environmental factors) were also coded. RESULTS:Eight additional studies resulted in a total sample of 19 studies, tripling the sample size to N = 56,103 and n = 1,383 with bipolar disorder. Seven studies were from the United States, and 12 were from South America, Central America, or Europe. Weighted average prevalence of bipolar spectrum disorders was 3.9% (95% CI, 2.6%-5.8%). There was significant heterogeneity across studies (Q = 759.82, df = 32, P < .0005). The pooled rate of bipolar I was 0.6% (95% CI, 0.3%-1.2%); these rates were also heterogeneous (Q = 154.27, df = 13, P < .0001). Predictors of higher bipolar spectrum disorder prevalence were the use of broad bipolar criteria (P < .0001), older minimum age (P = .005), and lifetime prevalence (P = .002). Newer studies were associated with lower rates (P < .0001). CONCLUSIONS:The updated meta-analysis confirms that rates of bipolar spectrum disorders are not higher in the United States than in other Western countries, nor are rates increasing over time. Nonstandard diagnostic criteria result in highly variable prevalence rates, as does focusing on narrow definitions of PBD to the exclusion of the full spectrum. Consistent application of validated criteria could help to settle questions regarding PBD prevalence. Studies from non-Western countries are needed to refine understanding of international prevalence and risk factors.

Suicide is the second leading cause of death among young people. Both mental illness and social factors are associated with suicide in adolescents, and youth with mental disorders often experience social deficits, which may compound risk. The cumulative effects of mental disorders and social factors on suicidal ideation and behaviors (SIB) in adolescents have not previously been explored. Adolescents 13-18 years of age (N = 6,447; 49% female, 65% non-Hispanic White) participated in the National Comorbidity Survey Replication Adolescent Supplement. Adolescents were interviewed to assess mental health diagnoses, history of SIB, and relationship quality. Parents completed self-reports about adolescent mental health and family characteristics. Logistic regression estimated associations of friend, sibling, and family relationships with 12-month SIB and lifetime suicide attempt (SA); associations between relationships, SIB, and SA were compared across classes of mental disorders. Friendship negativity (odds ratio [OR] = 1.20, 95% confidence interval (CI) [1.04, 1.40]), and family conflict (OR = 1.26, 95% CI [1.13, 1.41]), were positively associated with SIB, beyond the risk conferred by mental disorders, particularly mood disorders (OR = 4.75, 95% CI [3.20, 7.05]). Friendship positivity (OR = 0.89, 95% CI [0.80, 0.99]); sibling relationship positivity (OR = 0.79, 95% CI [0.68, 0.91]); family cohesion (OR = 0.77, 95% CI [0.69, 0.87]); maternal care (OR = 0.76, 95% CI [0.69, 0.84]); and paternal care (OR = 0.68, 95% CI [0.59, 0.78]), were inversely associated with SIB. Sibling relationship positivity, family conflict, and paternal care were similarly associated with SA. Self-reported adolescent friend and family relationship characteristics are associated with SIB and SA beyond the risk conferred by mental disorders. This suggests that perceptions of friend and family relationships may be an appropriate target to reduce suicide risk among adolescents.

Over the past two decades, research on pediatric bipolar disorder has grown geometrically. The diagnosis of pediatric bipolar disorder was met with enthusiasm, which in healthy doses catalyzed change, and skepticism, which in good measure pushes for rigor. Skepticism led to productive questions about the phenomenology of pediatric bipolar disorder and how best to diagnose and treat it. With regard to prevalence, key questions included whether it was increasing over time, and whether it was limited to the United States. In 2011, we published a meta-analysis addressing the prevalence questions; results indicated that bipolar disorder manifested at statistically indistinguishable rates in youth community samples across the world. In their recent paper, Parry et al. examine the studies included in the 2011 meta-analysis using a qualitative approach. Their opinion piece represents a step backwards; every study has shortcomings, but in focusing on a dozen individual studies, Parry et al. fail to take into account the preponderance of evidence - literally thousands of articles across countries, cohorts and methodologies - that support the existence of bipolar disorder in both prepubescent youth and adolescents. This commentary addresses misperceptions regarding the diagnosis of bipolar disorder in youth, particularly with regard to cross-informant agreement, to present converging data from international sources regarding the onset of bipolar disorder in childhood, and to correct the false claim that pediatric bipolar disorder is controversial. As clinicians and researchers, we have an obligation to do what we can to improve the lives of youth affected by mental illness. Denying the existence of a serious mood disorder will not serve the best interests of young people and will perpetuate the long delays many experience before getting an accurate diagnosis, appropriate treatment, and a fair chance at a good quality of life.

OBJECTIVE:Most studies of pediatric bipolar disorder (BP) combine youth who have manic symptoms, but do not meet criteria for BP I/II, into one "not otherwise specified" (NOS) group. Consequently, little is known about how youth with cyclothymic disorder (CycD) differ from youth with BP NOS. The objective of this study was to determine whether youth with a research diagnosis of CycD (RDCyc) differ from youth with operationalized BP NOS. METHOD:Participants from the Course and Outcome of Bipolar Youth study were evaluated to determine whether they met RDCyc criteria. Characteristics of RDCyc youth and BP NOS youth were compared at baseline, and over eight-years follow-up. RESULTS:Of 154 youth (average age 11.96 (3.3), 42% female), 29 met RDCyc criteria. RDCyc youth were younger (p = .04) at baseline. Over follow-up, RDCyc youth were more likely to have a disruptive behavior disorder (p = .01), and were more likely to experience irritability (p = .03), mood reactivity (p = .02), and rejection sensitivity (p = .03). BP NOS youth were more likely to develop hypomania (p = .02), or depression (p = .02), and tended to have mood episodes earlier in the eight-year follow-up period. LIMITATIONS:RDCyc diagnoses were made retrospectively and followed stringent criteria, which may highlight differences that, under typical clinical conditions and more vague criteria, would not be evident. CONCLUSION:There were few differences between RDCyc and BP NOS youth. However, the ways in which the groups diverged could have implications; chronic subsyndromal mood symptoms may portend a severe, but ultimately non-bipolar, course. Longer follow-up is necessary to determine the trajectory and outcomes of CycD symptoms.

BACKGROUND:There is substantial evidence that bipolar disorder (BD) manifests on a spectrum rather than as a categorical condition. Detection of people with subthreshold manifestations of BD is therefore important. The Hypomania Checklist-32 (HCL-32) was developed as a tool to identify such people. PURPOSE:The aims of this paper were to: (1) investigate the factor structure of HCL-32; (2) determine whether the HCL-32 can discriminate between mood disorder subtypes; and (3) assess the familial aggregation and cross-aggregation of hypomanic symptoms assessed on the HCL with BD. PROCEDURES:Ninety-six probands recruited from the community and 154 of their adult first-degree relatives completed the HCL-32. Diagnosis was based on semi-structured interviews and family history reports. Explanatory factor analysis and mixed effects linear regression models were used. FINDINGS:A four-factor ("Activity/Increased energy," "Distractibility/Irritability", "Novelty seeking/Disinhibition, "Substance use") solution fit the HCL-32, explaining 11.1% of the total variance. The Distractibility/Irritability score was elevated among those with BP-I and BP-II, compared to those with depression and no mood disorders. Higher HCL-32 scores were associated with increased risk of BD-I (OR = 1.22, 95%CI 1.14-1.30). The "Distractibility/Irritability" score was transmitted within families (β = 0.15, p = 0.040). However, there was no familial cross-aggregation between mood disorders and the 4 HCL factors. CONCLUSIONS:Our findings suggest that the HCL-32 discriminates the mood disorder subtypes, is familial and may provide a dimensional index of propensity to BD. Future studies should explore the heritability of symptoms, rather than focusing on diagnoses.

BACKGROUND:Accurate assessment of pediatric bipolar disorder (BD) is important for allocating appropriate treatment, but it is complicated by significant heterogeneity in symptom presentation and high rates of comorbidity. Investigating clinical subtypes of the disorder may help to clarify diagnostic boundaries and inform targeted treatment. This study used a full diagnostic instrument to examine symptom patterns among youth with BD. METHOD:Trained interviewers completed the Washington University Kiddie Schedule for Affective Disorders and Schizophrenia (WASH-U-KSADS) with 71 children (7 to 13 y of age) and families as part of the baseline assessment for a randomized clinical trial of Child- and Family-focused Cognitive-Behavioral Therapy (CFF-CBT) compared with treatment as usual (TAU) for pediatric BD. All participants met DSM-IV-TR criteria for a bipolar spectrum disorder. Hierarchical and K-means cluster analyses were performed. Resultant clusters were compared on symptom severity and psychosocial functioning at baseline and across treatment. RESULTS:Two distinct symptom profiles emerged: "dysregulated/defiant" and "classic presentation." The dysregulated/defiant cluster was characterized by more externalizing and disruptive behaviors, whereas the classic cluster presented with more severe depression, hallmark manic symptoms, anxiety, and inattention. CFF-CBT consistently promoted psychosocial coping skills, such as problem solving and self-control, for the dysregulated/defiant cluster. TAU also promoted these skills among the individuals in the classic presentation group but not those with symptoms in the dysregulated/defiant cluster. DISCUSSION:Pediatric BD may be characterized by distinct phenotypes with unique etiologies and pathways to impairment. The use of a parametric approach to classify the diverse symptom presentations helped yield valuable insights into how to promote the best prognosis for improved functional outcomes in CFF-CBT versus TAU for youth with pediatric BD.

Shifting definitions and differences in the conceptualization of bipolar disorders have contributed to long diagnostic delays, poor reliability, and inconsistent findings. Rating scales are independent of clinical judgment and offer a reliable way to assess manic symptoms, making them good tools to improve both clinical and research diagnoses of bipolar disorder. However, there are dozens of candidates, with few obvious distinguishing characteristics, making it difficult to select one. Our goal was to metaanalyze the diagnostic accuracy of rating scales designed to identify [hypo]manic symptoms. Additionally, we explored potential moderator variables including global region, translation into a different language, and sample composition. Nearly 4000 articles were identified with searches in PubMed and PsycINFO, yielding 127 effect sizes from 103 studies that met the following inclusion criteria: (a) statistics reported by which a standardized effect size could be calculated, (b) participants age 18 + years, (c) reference diagnoses made by semistructured/structured diagnostic interview, (d) results published in English. Multivariate mixed regression models accounted for multiple effect sizes nested within sample. One hundred twenty-seven effect sizes across 14 rating scales were evaluated. There was significant heterogeneity across effect sizes; Cochran's Q(126 df) = 1622.08, p < .00005, and substantial variance components both within (σ2 = .057) and between samples (σ2 = .253). Four measures performed similarly well and significantly better than some competitors after controlling for design and reporting features. The best rating scales offer an inexpensive, efficient way to improve research and clinical diagnostic processes across diverse populations, and could also complement formal diagnoses for examining secular and cultural trends. (PsycINFO Database Record

This study investigated the clinical utility of the Achenbach System of Empirically Based Assessment (ASEBA) for identifying youth at risk for suicide. Specifically, we investigated how well the Total Problems scores and the sum of two suicide-related items (#18 "Deliberately harms self or attempts suicide" and #91 "Talks about killing self") were able to distinguish youth with a history of suicidal behavior. Youth (N = 1117) aged 5-18 were recruited for two studies of mental illness. History of suicidal behavior was assessed by semi-structured interviews (K-SADS) with youth and caregivers. Youth, caregivers, and a primary teacher each completed the appropriate form (YSR, CBCL, and TRF, respectively) of the ASEBA. Areas under the curve (AUCs) from ROC analyses and diagnostic likelihood ratios (DLRs) were used to measure the ability of both Total Problems T scores, as well as the summed score of two suicide-related items, to identify youth with a history of suicidal behavior. The Suicide Items from the CBCL and YSR performed well (AUCs = 0.85 and 0.70, respectively). The TRF Suicide Items did not perform better than chance, AUC = 0.45. The AUCs for the Total Problems scores were poor-to-fair (0.33-0.65). The CBCL Suicide Items outperformed all other scores (ps = 0.04 to <0.0005). Combining the CBCL and YSR items did not lead to incremental improvement in prediction over the CBCL alone. The sum of two questions from a commonly used assessment tool can offer important information about a youth's risk for suicidal behavior. The low burden of this approach could facilitate wide-spread screening for suicide in an increasingly at-risk population.

This study investigated the diagnostic and clinical utility of the parent-rated Screen for Child Anxiety Related Emotional Disorders (SCARED-P) for detecting youth anxiety disorders. Youth ages 6 to 12 years, 11 months were recruited from 9 outpatient mental health clinics (N = 707). Consensus diagnoses were based on semistructured interviews (Schedule for Affective Disorders and Schizophrenia for School-Age Children) with youth and caregivers; 31% were diagnosed with at least one anxiety disorder. Caregivers completed the SCARED-P to describe youth anxiety levels. SCARED-P scores were not considered during the consensus diagnoses. Areas under the curve (AUCs) from receiver operating characteristic analyses and diagnostic likelihood ratios (DLRs) quantified performance of the SCARED-P total score and subscale scores (generalized anxiety disorder and separation anxiety disorder). SCARED-P total scores had variable efficiency (AUCs = .69-.88), and Generalized Anxiety Disorder and Separation Anxiety subscale scores were excellent (AUCs = .86-.89) for identifying specific anxiety disorders. Optimal subscale cutoff scores were computed to help rule in (DLRs = 2.7-5.4) or rule out (DLRs < 1.0) anxiety disorders among youth. Results suggest that the Generalized Anxiety Disorder and Separation Anxiety SCARED-P subscales accurately identify their respective matched diagnoses. DLRs may aid clinicians in screening for youth anxiety disorders and improve accuracy of diagnosis.