Clinically useful and evidence-based mental health assessment requires the identification of strategies that maximize diagnostic accuracy, inform treatment planning, and make efficient use of clinician and patient time and resources. This study uses classification tree analyses to determine whether parent- and child-report instruments, alone or in combination, can accurately predict diagnoses as measured by the Anxiety Disorders Interview Schedule (ADIS). The ADIS, which is the gold-standard semistructured interview for anxiety disorders in children and adolescents, requires formal training and lengthy administration. Data were collected as part of the standard diagnostic assessment process for 201 patients (ages 5 to 17 years) in an urban outpatient psychiatry specialty clinic. Analyses examined 2 models to determine which predictors reached an acceptable level of diagnostic accuracy for generalized anxiety, social anxiety, and separation anxiety disorders. The first model used scores on a parent- and child-report anxiety measure combined with demographic factors, and the second model incorporated a broad-band measure of child psychopathology and a depression measure into the analysis. Although demographic factors did not emerge as accurate predictors in either model, particular measures, either alone or in combination, were able to predict specific ADIS diagnoses in some cases, allowing for the potential streamlining of ADIS administration. These results suggest that a classification-tree analysis lends itself to the construction of simple algorithms that have high clinical utility and may advance the feasibility and utility of evidence-based assessment strategies in real-world practice settings by balancing cost effectiveness, administration demands, and accuracy. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Unstructured clinical interviews are inaccurate tools for diagnostic decision-making. While structured diagnostic evaluations improve reliability, they are infrequently used in clinical practice. Empirical approaches are a hallmark of evidenced-based assessment and may reduce burdens of structured interviews. We explore two approaches to empirical prediction of diagnosis, the naïve nomogram, and classification tree analysis (CTA). To illustrate the clinical utility of each approach, we compared their use in a sample of 6-year-olds (N = 619) to predict structured-interview diagnoses of oppositional defiant disorder (ODD). Findings indicate the accuracy of both approaches in predicting the absence of a disorder and improved detection of ODD using CTA for subgroups of children. Both empirical prediction techniques have applicability to diagnostic decision-making in psychiatry and pediatrics. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Psychotropic medications are commonly prescribed to school-aged youth for the management of mental health concerns. This paper describes the current state of evidence for psychotropic medications in school-aged youth. More specifically, the following sections summarize relevant medication research trials and practice parameters pertaining to psychotropic medication prescribing as well as the specific medications indicated for a range of commonly presenting disorders and symptom clusters in school-aged youth. For each of these disorders and symptom clusters, key findings pertaining to the current state of science and practice are highlighted for the purpose of offering patients, clinicians, researchers, and policymakers with nuanced considerations for the role of psychopharmacology within the context of a larger “whole-child” approach to care that relies on the collaboration of providers and services across systems of care to promote optimal child and family health and wellness. The paper concludes with a discussion about supporting the use of medication treatments in schools, including considerations for ensuring effective family-school-health system collaboration to best meet youth mental health needs.

Background: Bright light therapy (BLT) has not been well-studied in adolescents with major depressive disorder, particularly in outpatient settings. Methods: We conducted an 8-week clinical trial of BLT in adolescents recruited from a primary care practice with moderate to severe major depression. Acceptability and feasibility were defined by daily use of the light box and integration into daily routines. To assess treatment effects, we utilized the Short Mood and Feelings Questionnaire (SMFQ) and actigraphic sleep variables. Results: Of the nine enrolled adolescents, the rate of daily use of the light therapy box was 100% at week 2, 78% at week 4 (n = 7), and 67% at weeks 6 and 8 (n = 6). Participants were better able to integrate midday BLT compared to morning BLT into their day-to-day routines. Mean depression scores improved during the 2-week placebo lead-in (dim red light—DRL) and continued to show significant improvement through 6 weeks of BLT. Sleep efficiency increased significantly (p = 0.046), and sleep onset latency showed a trend toward a significant decrease (p = 0.075) in the BLT phase compared to the DRL phase. Conclusion: Bright light treatment that was self-administered at home was feasible, acceptable, and effective for adolescent outpatients with depression. Findings support the development of larger, well-powered, controlled clinical trials of BLT in coordination with primary care.

One in five Americans experiences disability that affects their daily function because of impairments in mobility, cognitive function, sensory impairment, or communication impairment. The need for rehabilitation strategies to optimize function and reduce disability is a clear priority for research to address this public health challenge. The National Institutes of Health (NIH) recently published a Research Plan on Rehabilitation that provides a set of priorities to guide the field over the next 5 years. The plan was developed with input from multiple Institutes and Centers within the NIH, the National Advisory Board for Medical Rehabilitation Research, and the public. This article provides an overview of the need for this research plan, an outline of its development, and a listing of six priority areas for research. The NIH is committed to working with all stakeholder communities engaged in rehabilitation research to track progress made on these priorities and to work to advance the science of medical rehabilitation. This article is being published almost simultaneously in the following six journals: American Journal of Occupational Therapy, American Journal of Physical Medicine and Rehabilitation, Archives of Physical Medicine and Rehabilitation, Neurorehabilitation and Neural Repair, Physical Therapy, and Rehabilitation Psychology. Citation information is as follows: NIH Medical Rehabilitation Coordinating Committee. Am J Phys Med Rehabil. 2017;97(4):404—407.

The Interagency Committee on Human Nutrition Research (ICHNR) is charged with improving the planning, coordination, and communication among federal a