Background: To estimate the prevalence and correlates of clinician-diagnosed DSM-IV nonaffective psychosis (NAP) in a national household survey.
Methods: Data came from the United States National Comorbidity Survey Replication (NCS-R). A screen for NAP was followed by blinded sub-sample clinical reappraisal interviews. Logistic regression was used to impute clinical diagnoses to respondents who were not re-interviewed. The method of Multiple Imputation (MI) was used to estimate prevalence and correlates.
Results: Clinician-diagnosed NAP was well predicted by the screen (area under the curve [AUC] = .80). The MI prevalence estimate of NAP (standard error in parentheses) is 5.0 (2.6) per 1000 population lifetime and 3.0 (2.2) per 1000 past 12 months. The vast majority (79.4%) of lifetime and 12-month (63.7%) cases met criteria for other DSM-IV hierarchy-free disorders. Fifty-eight percent of 12-month cases were in treatment, most in the mental health specialty sector.
Conclusions: The screen for NAP in the NCS-R greatly improved on previous epidemiological surveys in reducing false positives, but coding of open-ended screening scale responses was still needed to achieve accurate prediction. The lower prevalence estimate than in total-population incidence studies raises concerns that systematic nonresponse bias causes downward bias in survey prevalence estimates of NAP.