Systematic item selection process applied to developing item pools for assessing multiple mental health problems

Abstract

Objectives: Given high rates of comorbidity among mental disorders, better methods to rapidly screen across multiple mental disorders are needed. Building on existing Patient Reported Outcomes Measurement Information System (PROMIS) item banks, the present study aimed to select items to assess panic disorder, social anxiety disorder, obsessive-compulsive disorder, posttraumatic stress disorder, adult attention-deficit hyperactivity disorder, substance use disorder, suicidal thoughts and behaviors, and psychosis. Study Design and Setting: A four-stage process to select items involved systematic literature searches, item refinement and standardization, obtaining feedback from consumers and experts, and reduction of item pools in preparation for calibration in a population-based sample. Results: From 6,900 items collected across the eight mental health conditions, 2,002 were standardized and rated by small groups of consumers and experts. Expert ratings of item relevance tended to correlate moderately with consumer ratings, with variation across conditions. An algorithm was used to generate final item pools ranging from 45 to 75 items. Conclusion: The study successfully applied a systematic process to select items for assessing a range of mental disorders. This process for item selection may be applied to additional mental and physical health conditions. The calibration of the present item pools into final item banks will enable the development of flexible measures to assess risk of mental health problems, although more effectively accounting for comorbidity.