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The World Mental Health (WMH) Survey Initiative was a coordinated series of general population surveys of mental, substance use, and behavioral disorders conducted in countries across all World Health Organization (WHO) regions. The approach taken by WMH was to conduct rigorous general population surveys in nationally representative samples in many countries throughout the world, to generate data from these surveys on the prevalence, severity, course, and treatment of mental disorders. Data were collected using the WHO Composite International Diagnostic Interview (CIDI) which uses both ICD-10 and DSM-III diagnostic criteria. This survey was conducted in Nigeria and utilized the Efik, Hausa, Igbo, and Yoruba versions of the CIDI.

This study addressed whether it is better to expand the scope of collaborative care programs to treat patients with more complex psychiatric disorders or to facilitate successful referrals to specialty mental health care. The primary objective of this study is to compare Telepsychiatry Collaborative Care (TCC) and Telepsychiatry Enhanced Referral (TER) from the patient and provider perspective. The secondary objective is to determine whether patients not engaging and responding to TER, improve with Phone-Psychiatry Enhanced Referral (PER). There are four specific aims.

Aim #1: To quantitatively compare the treatment experience, engagement, self-reported clinical outcomes, and recovery-oriented outcomes of patients initially randomized to TCC and TER.

Aim #2: For the subset of patients randomized to TER who do not engage in treatment and are still symptomatic at 6 months, quantitatively compare treatment experience, treatment engagement, self-reported clinical outcomes and recovery-oriented outcomes of patients randomized to continued-TER or PER.

Aim #3: To gain an in-depth understanding of patients' and providers' treatment experience, qualitatively compare those randomized to TCC, TER and PER.

Aim #4: To examine treatment heterogeneity among subgroups of patients randomized to TCC and TER based on race/ethnicity, age and clinical severity.

The Epidemiologic Catchment Area (ECA) program of research was initiated in response to the 1977 report of the President's Commission on Mental Health. The purpose was to collect data on the prevalence and incidence of mental disorders and on the use of and need for services by the mentally ill. Independent research teams at five universities (Yale University, Johns Hopkins University, Washington University, Duke University, and University of California at Los Angeles), in collaboration with the National Institute for Mental Health, conducted the studies with a core of common questions and sample characteristics. The sites were areas that had previously been designated as Community Mental Health Center catchment areas: New Haven, Connecticut, Baltimore, Maryland, St. Louis, Missouri, Durham, North Carolina, and Los Angeles, California. Each site sampled over 3,000 community residents and 500 residents of institutions, yielding 20,861 respondents overall. The longitudinal ECA design incorporated two waves of personal interviews administered one year apart and a brief telephone interview in between (for the household sample). The diagnostic interview used in the ECA was the NIMH Diagnostic Interview Schedule (DIS), Version III (with the exception of the Yale Wave I survey, which used Version II). Diagnoses were categorized according to the DIAGNOSTIC AND STATISTICAL MANUAL OF MENTAL DISORDERS, 3rd Edition (DSM-III). Diagnoses derived from the DIS include manic episode, dysthymia, bipolar disorder, single episode major depression, recurrent major depression, atypical bipolar disorder, alcohol abuse or dependence, drug abuse or dependence, schizophrenia, schizophreniform, obsessive compulsive disorder, phobia, somatization, panic, antisocial personality, and anorexia nervosa. The DIS uses the Mini-Mental State Examination (MMSE), which measures cognitive functioning, as an indirect measure of the DSM-III Organic Mental Disorders. In the ECA survey, this diagnosis is called cognitive impairment.

This collection features data from 17,327 participants across 2,005 variables. Data from the Los Angeles, California, Catchment (UCLA) are not included. Baseline data (Wave 1) and Wave 2 data were linked to the National Death Index through 2007, which includes primary and contributing causes of death, International Classification of Disease (ICD) codes, and nature of injury variables.

Objective: To meta-analyze the diagnostic efficiency of checklists for discriminating pediatric bipolar disorder (PBD) from other conditions. Hypothesized moderators included (a) informant - we predicted caregiver report would produce larger effects than youth or teacher report; (b) scale content - scales that include manic symptoms should be more discriminating; and (c) sample design - samples that include healthy control cases or impose stringent exclusion criteria are likely to produce inflated effect sizes.

Methods: Searches in PsycINFO, PubMed, and GoogleScholar generated 4094 hits. Inclusion criteria were (1) sufficient statistics to estimate a standardized effect size, (2) age 18 years or less, and (3) at least 10 cases (4) with diagnoses of PBD based on semi-structured diagnostic interview. Multivariate mixed regression models accounted for nesting of multiple effect sizes from different informants or scales within the same sample.

Results: Data included 63 effect sizes from 8 rating scales across 27 separate samples (N=11,941 youths, 1,834 with PBD). The average effect size was g=1.05. Random effect variance components within study and between study were significant, ps<.00005. Informant, scale content, and sample design all explained significant unique variance, even after controlling for design and reporting quality.

Discussion: Checklists have clinical utility for assessing PBD. Caregiver reports discriminated PBD significantly better than teacher and youth self report, although all three showed discriminative validity. Studies using "distilled" designs with healthy control comparison groups, or stringent exclusion criteria, produced significantly larger effect size estimates that could lead to inflated false positive rates if used as described in clinical practice.