Response: assessing the instruments

Predictors of Posttraumatic Stress Disorder, Anxiety Disorders, Depressive Disorders, and Any Mental Health Condition Among U.S. Soldiers and Marines, 2001-2011

Understanding mental health disorder diagnosis and treatment seeking among active-duty military personnel is a topic with both clinical and policy implications. It has been well documented in military populations that individual-level military experience, including deployment history and combat exposure, influences mental health outcomes, but the impact of unit-level factors is less well understood. In the current study, we used administrative longitudinal data to examine a comprehensive set of unit- and individual-level predictors of posttraumatic stress disorder (PTSD), non-PTSD anxiety disorders, depressive disorders, and overall mental health diagnoses among Army and Marines Corps personnel. Using Cox survival models for time-dependent variables, we analyzed time from military accession (between January 1, 2001 and December 31, 2011) until first mental health diagnosis for 773,359 soldiers and 332,093 Marines. Prior diagnosis of a substance abuse disorder during one's military career, hazard ratios (HRs) = 1.68-3.10, and cumulative time spent deployed, HRs = 1.11-2.04, were the most predictive risk factors for all outcomes. Male sex, HRs = 0.35-0.57, and officer rank, HRs = 0.13-0.23, were the most protective factors. Unit-level rate of high deployment stress was a small but significant predictor of all outcomes after controlling for individual-level deployment history and other predictors, HRs = 1.01-1.05. Findings suggest both unit- and individual-level risk and protective factors of mental health diagnoses associated with treatment seeking. Clinical, including mental health assessment and management, and policy implications related to the military environment and the individual as it relates to mental health disorders are discussed.

Rapid and Accurate Behavioral Health Diagnostic Screening: Initial Validation Study of a Web-Based, Self-Report Tool (the SAGE-SR)

Background

The Structured Clinical Interview for DSM (SCID) is considered the gold standard assessment for accurate, reliable psychiatric diagnoses; however, because of its length, complexity, and training required, the SCID is rarely used outside of research.

Objective

This paper aims to describe the development and initial validation of a Web-based, self-report screening instrument (the Screening Assessment for Guiding Evaluation-Self-Report, SAGE-SR) based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) and the SCID-5-Clinician Version (CV) intended to make accurate, broad-based behavioral health diagnostic screening more accessible within clinical care.

Methods

First, study staff drafted approximately 1200 self-report items representing individual granular symptoms in the diagnostic criteria for the 8 primary SCID-CV modules. An expert panel iteratively reviewed, critiqued, and revised items. The resulting items were iteratively administered and revised through 3 rounds of cognitive interviewing with community mental health center participants. In the first 2 rounds, the SCID was also administered to participants to directly compare their Likert self-report and SCID responses. A second expert panel evaluated the final pool of items from cognitive interviewing and criteria in the DSM-5 to construct the SAGE-SR, a computerized adaptive instrument that uses branching logic from a screener section to administer appropriate follow-up questions to refine the differential diagnoses. The SAGE-SR was administered to healthy controls and outpatient mental health clinic clients to assess test duration and test-retest reliability. Cutoff scores for screening into follow-up diagnostic sections and criteria for inclusion of diagnoses in the differential diagnosis were evaluated.

Results

The expert panel reduced the initial 1200 test items to 664 items that panel members agreed collectively represented the SCID items from the 8 targeted modules and DSM criteria for the covered diagnoses. These 664 items were iteratively submitted to 3 rounds of cognitive interviewing with 50 community mental health center participants; the expert panel reviewed session summaries and agreed on a final set of 661 clear and concise self-report items representing the desired criteria in the DSM-5. The SAGE-SR constructed from this item pool took an average of 14 min to complete in a nonclinical sample versus 24 min in a clinical sample. Responses to individual items can be combined to generate DSM criteria endorsements and differential diagnoses, as well as provide indices of individual symptom severity. Preliminary measures of test-retest reliability in a small, nonclinical sample were promising, with good to excellent reliability for screener items in 11 of 13 diagnostic screening modules (intraclass correlation coefficient [ICC] or kappa coefficients ranging from .60 to .90), with mania achieving fair test-retest reliability (ICC=.50) and other substance use endorsed too infrequently for analysis.

Conclusions

The SAGE-SR is a computerized adaptive self-report instrument designed to provide rigorous differential diagnostic information to clinicians.

Accuracy of self-report, biological tests, collateral reports and clinician ratings in identifying substance use disorders among adults with schizophrenia

Identifying substance use disorders among adults with schizophrenia presents unique challenges but is critical to research and practice. This study examined: (a) the accuracy of assessments completed using various approaches in identifying substance use disorders, (b) their ability to discriminate between disorders of abuse and dependence, and (c) the benefits of using multiple indicators to identify substance use disorders. Data are from the Clinical Antipsychotic Trials of Intervention Effectiveness study. The sample comprised 1,460 community-based adults with schizophrenia, 15.8% (n = 230) of whom were positive for a current (past month) drug or alcohol use disorder using the Structured Clinical Interview for DSM-IV Disorders (SCID). Clinician ratings, self-report, collateral reports, and results of hair and urine tests were compared to SCID diagnoses. Congruence with SCID diagnoses was good across approaches and evidence for superiority of one approach over another was limited. No approach discriminated between abuse and dependence. There was limited benefit of using multiple indicators. Findings suggest that the decision regarding the "best" approach for identifying substance use disorders among adults with schizophrenia may be made through consideration of practical issues and assessment purpose, rather than selection of the approach that yields the most accurate diagnostic assessment.