Further Evidence of the Diagnostic Utility of the Child Behavior Checklist for Identifying Pediatric Bipolar I Disorder

In Memoriam: Professor Joseph Biederman's Contributions to Child and Adolescent Psychiatry

OBJECTIVE

To provide an overview of Joe Biederman's contributions to child and adolescent psychiatry.

METHOD

Nine colleagues described his contributions to: psychopharmacology, comorbidity and genetics, pediatric bipolar disorder, autism spectrum disorders, Tourette's and tic disorders, clinical and neuro biomarkers for pediatric mood disorders, executive functioning, and adult ADHD.

RESULTS

Joe Biederman left us with many concrete indicators of his contributions to child and adolescent psychiatry. He set up the world's first pediatric psychopharmacology clinic and clinical research program in child adolescent psychiatry. As a young faculty member he began a research program that led to many awards and eventual promotion to full professor at Harvard Medical School. He was for many years the most highly cited researcher in ADHD. He achieved this while maintaining a full clinical load and was widely respected for his clinical acumen.

CONCLUSION

The world is a better place because Joe Biederman was here.

Further Evidence of an Association Between a Positive Child Behavior Checklist-Bipolar Profile and a Diagnosis of Pediatric Bipolar Disorder: A Meta-Analysis

Background

Previous research has found that a unique profile of the Child Behavior Checklist comprising of aggregate elevations of the Attention, Anxiety/Depression and Aggression scales (A-A-A profile, CBCL-Bipolar (BP) profile, CBCL-Dysregulation profile (DP); henceforth CBCL-BP/DP profile) is associated with a clinical diagnosis of pediatric bipolar (BP) disorder.

Objective

The main aim of the study is to evaluate the strength of the association between the CBCL-BP/DP profile and the clinical diagnosis of pediatric BP disorder through a meta-analysis.

Methods

A literature search was performed to identify studies that examined the association between a positive CBCL-BP/DP profile and a clinical diagnosis of pediatric BP disorder. The meta-analyses first examined studies assessing the rates of a positive CBCL-BP/DP profile in youth with BP disorder versus those with 1) ADHD, anxiety/depression, or disruptive behavior disorders (DBDs), and 2) non-bipolar controls. The second analysis evaluated studies examining the rates of pediatric BP disorder in youth with and without a positive CBCL-BP/DP profile.

Results

Eighteen articles met our inclusion and exclusion criteria, and fifteen articles had adequate data for meta-analysis. Results showed that BP youth were at significantly increased odds of having a positive CBCL-BP/DP profile compared to those with other psychiatric disorders (i.e., ADHD, anxiety/depression, or DBDs) (pooled OR=4.34, 95% CI=2.82, 8.27; p<0.001) and healthy control groups (pooled OR=34.77, 95% CI=2.87, 420.95; p=0.005). Further, meta-analysis results showed that youth with a positive CBCL-BP/DP profile were at significantly increased odds of having a BP disorder diagnosis compared to those without (pooled OR=4.25, 95% CI=2.12, 8.52; p<0.001).

Conclusion

Our systematic review and meta-analysis of the extant literature provides strong support for the association between the CBCL-BP/DP profile and pediatric BP disorder.

A Comprehensive Review of Computer-Aided Diagnosis of Major Mental and Neurological Disorders and Suicide: A Biostatistical Perspective on Data Mining

The World Health Organization (WHO) suggests that mental disorders, neurological disorders, and suicide are growing causes of morbidity. Depressive disorders, schizophrenia, bipolar disorder, Alzheimer's disease, and other dementias account for 1.84%, 0.60%, 0.33%, and 1.00% of total Disability Adjusted Life Years (DALYs). Furthermore, suicide, the 15th leading cause of death worldwide, could be linked to mental disorders. More than 68 computer-aided diagnosis (CAD) methods published in peer-reviewed journals from 2016 to 2021 were analyzed, among which 75% were published in the year 2018 or later. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol was adopted to select the relevant studies. In addition to the gold standard, the sample size, neuroimaging techniques or biomarkers, validation frameworks, the classifiers, and the performance indices were analyzed. We further discussed how various performance indices are essential based on the biostatistical and data mining perspective. Moreover, critical information related to the Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines was analyzed. We discussed how balancing the dataset and not using external validation could hinder the generalization of the CAD methods. We provided the list of the critical issues to consider in such studies.

Can the Child Behavior Checklist (CBCL) help characterize the types of psychopathologic conditions driving child psychiatry referrals?

Background:

Little is known about the scope of problems driving referrals to child and adolescent psychiatry services. Identifying the full range of mental disorders affecting a particular child can help triage the child to a clinician with the appropriate level of expertise. The Child Behavior Checklist (CBCL) is an easy-to-use assessment tool that may provide invaluable information regarding the severity of the presenting complaints and also aid in the referral process.

Objective:

To assess the utility of the CBCL to gain insights into the type of clinical problems driving referrals of youth to an outpatient pediatric psychiatry clinic.

Method:

The sample consisted of 418 newly referred youth 4-18 years of age of both sexes. Parents completed the CBCL assessing psychopathology and competence. Rates of patients with elevated T-scores on each scale were calculated for the whole group and stratified by sex and age (≤12 versus >12).

Results:

The CBCL identified high rates of psychopathology affecting referred youth. It also provided information on the type of suspected disorders affecting a particular child as well as their severity, critical information to guide likely differing clinical needs and therapeutic approaches. It also helped identify a high number of youth affected with multiple psychopathological conditions, likely to require a high level of clinical attention. Overall, males were significantly more impaired than females but there were no major differences between children and adolescents.

Conclusions:

The CBCL can aid in the identification of individual and comorbid mental disorders affecting youth seeking mental health services by providing specific information about the presence and the severity of specific suspected disorder. These findings have implications for prioritizing scarce resources in child mental health and for improved consideration of the complexity of clinical presentations to pediatric psychiatry programs of any type.