Computer-assisted Self-Assessment in Persons with Severe Mental Illness
Published in: Journal of Clinical Psychiatry, v. 65, no. 10, Oct. 2004, p.1343-1351
Posted on RAND.org on December 31, 2003
BACKGROUND: It has been difficult to improve care for severe mental illness (SMI) in usual care settings because clinical information is not reliably and efficiently managed. Methods are needed for efficiently collecting this information to evaluate and improve health care quality. Audio computer-assisted self-interviewing (ACASI) can facilitate this data collection and has improved outcomes for a number of disorders, suggesting the need to test its accuracy and reliability in people with SMI. METHOD: Ninety patients with DSM-IV schizophrenia or schizoaffective disorder (N = 45) or bipolar disorder (N = 45) recruited between Oct. 15, 2002, and July 1, 2003, were randomly assigned to 1 of 2 study groups and completed 2 standardized symptom surveys (Revised Behavior and Symptom Identification Scale and the symptom severity scale of the Schizophrenia Outcomes Module 2) 20 minutes apart in a crossover study design. Half of the patients first completed the scales via an in-person inter-view, and the other half first completed the scales via an ACASI survey self-administered through an Internet browser using a touchscreen developed to meet the cognitive needs of people with SMI. We evaluated attitudes toward ACASI, understanding of the ACASI survey, internal consistency, correlations between the ACASI and inter-view modes, concurrent validity, and a possible administration mode bias. RESULTS: All ACASI and in-person interview scales had similar internal reliability, high correlations (r = 0.78-1.00), and mean scores similar enough as not to be different at p < .05. A large majority rated the ACASI survey as easier, more enjoyable, more preferable if monthly completion of a survey were required, and more private, and 97% to 99% perfectly answered questions about how to use it. CONCLUSION: ACASI data collection is reliable among people with bipolar disorder and schizophrenia and could be a valuable tool to improve their care.