Clinical Guide to the Evidence-Based Assessment Approach to Diagnosis and Treatment

Youngstrom, Eric A.; Choukas‐Bradley, Sophia; Calhoun, Casey D.; Jensen‐Doss, Amanda

doi:10.1016/j.cbpra.2013.12.005

Cited by 95 publications

(92 citation statements)

References 35 publications

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“…You also see that on a questionnaire about family history of psychiatric illness, Cecilia has endorsed anxiety. Using the probability nomogram (see Figure 2), you begin with a base rate for anxiety disorders of 20%, which is consistent with the referral pattern at your clinic (Youngstrom et al, 2014). Next, you incorporate the knowledge that Roger’s mother has an anxiety disorder, which increases Roger’s risk by about 5 times.…”

Section: Discussionmentioning

confidence: 64%

“…Though an evidence-based approach will improve accuracy of the estimated likelihood of a diagnosis, information needed to take advantage of this approach can be difficult to find. Providing likelihood ratios for commonly-used clinical tools and demonstrating how to integrate them into an evidence-based approach to assessment may help to improve the assessment and diagnosis of childhood disorders, and facilitate successful treatment (Christon, McLeod, & Jensen-Doss, 2014; Youngstrom, Choukas-Bradley, Calhoun, & Jensen-Doss, 2014). One effective, relatively simple way of incorporating evidence-based practices into assessment is to use a nomogram (Figure 1) to determine diagnostic probabilities (Straus, Glasziou, Richardson, & Haynes, 2011).…”

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confidence: 99%

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Diagnostic Efficiency of Caregiver Report on the SCARED for Identifying Youth Anxiety Disorders in Outpatient Settings

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Halverson

et al. 2016

Journal of Clinical Child & Adolescent Psychology

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Objective 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. Method Youth aged 6 to 12.9 were recruited from 9 outpatient mental health clinics (N=707). Consensus diagnoses were based on semi-structured interviews (KSADS) 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). Results SCARED-P total scores had variable efficiency (AUCs=.69-.88) and GAD 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. Conclusion Results suggest that the GAD 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.

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Section: Discussionmentioning

confidence: 64%

mentioning

confidence: 99%

Diagnostic Efficiency of Caregiver Report on the SCARED for Identifying Youth Anxiety Disorders in Outpatient Settings

Meter

You

Halverson

et al. 2016

Journal of Clinical Child & Adolescent Psychology

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“…There is a growing interest in psychology to combine scientific validity and clinical relevance (Youngstrom, Choukas-Bradley, & Calhoun, 2015). This evidencebased assessment approach appears important in older adults for whom the evaluation and the management of healthcare issues are often complicated by comorbidity.…”

Section: Introductionmentioning

confidence: 98%

Short STAI-Y anxiety scales: validation and normative data for elderly subjects

Bergua

Meillon

Potvin

et al. 2015

Aging & Mental Health

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“…In this regard, it is noteworthy that clinicians achieved lower reliability for DMDD than for pediatric bipolar diagnoses in the DSM-5 field trials (Regier et al 2012). Semistructured approaches (Rettew et al 2009) or checklists as a way of augmenting the family's description of the presenting problem could be helpful in improving the reproducibility of diagnoses (Croskerry 2003;Gawande 2010;Youngstrom et al 2014).…”

Section: Discussionmentioning

confidence: 99%

Disruptive Mood Dysregulation Disorder and Bipolar Disorder Not Otherwise Specified: Fraternal or Identical Twins?

Fristad

Wolfson

Algorta

et al. 2016

Journal of Child and Adolescent Psychopharmacology

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Objective: The purpose of this study was to examine similarities and differences between disruptive mood dysregulation disorder (DMDD) and bipolar disorder not otherwise specified (BP-NOS) in baseline sociodemographic and clinical characteristics and 36 month course of irritability in children 6-12.9 years of age. Methods: A total of 140 children with DMDD and 77 children with BP-NOS from the Longitudinal Assessment of Manic Symptoms cohort were assessed at baseline, then reassessed every 6 months for 36 months. Results: Groups were similar on most sociodemographic and baseline clinical variables other than most unfiltered (i.e., interviewer-rated regardless of occurrence during a mood episode) Young Mania Rating Scale (YMRS) and parent-reported General Behavior Inventory-10 Item Mania (PGBI-10M) items. Children with DMDD received lower scores on every item (including irritability) except impaired insight; differences were significant except for sexual interest and disruptiveaggressive behavior. Children with DMDD received lower scores on eight of 10 PGBI-10M items, the other two items rated irritability. Youth with DMDD were significantly less likely to have a biological parent with a bipolar diagnosis than were youth with BP-NOS. Children with DMDD were more likely to be male and older than children with BP-NOS, both small effect sizes, but had nearly double the rate of disruptive behavior disorders (large effect). Caregiver ratings of irritability based on the Child and Adolescent Symptom Inventory-4R (CASI-4R) were comparable at baseline; the DMDD group had a small but significantly steeper decline in scores over 36 months relative to the BP-NOS group (b = -0.24, SE = 0.12, 95% CI -0.48 to -0.0004). Trajectories for both groups were fairly stable, in the midrange of possible scores. Conclusions: In a sample selected for elevated symptoms of mania, twice as many children were diagnosed with DMDD than with BP-NOS. Children with DMDD and BP-NOS are similar on most characteristics other than manic symptoms, per se, and parental history of bipolar disorder. Chronic irritability is common in both groups. Comprehensive evaluations are needed to diagnose appropriately. Clinicians should not assume that chronic irritability leads exclusively to a DMDD diagnosis.

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Clinical Guide to the Evidence-Based Assessment Approach to Diagnosis and Treatment

Cited by 95 publications

References 35 publications

Diagnostic Efficiency of Caregiver Report on the SCARED for Identifying Youth Anxiety Disorders in Outpatient Settings

Diagnostic Efficiency of Caregiver Report on the SCARED for Identifying Youth Anxiety Disorders in Outpatient Settings

Short STAI-Y anxiety scales: validation and normative data for elderly subjects

Disruptive Mood Dysregulation Disorder and Bipolar Disorder Not Otherwise Specified: Fraternal or Identical Twins?

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