HIV Risk Behavior among Outpatients at a State Psychiatric Hospital: Prevalence and Risk Modeling

Abstract

The purpose of this archival study was to determine the prevalence and correlates of HIV-related risk behavior among adults with a severe and persistent mental illness (SPMI). Hospital records at a public psychiatric hospital were reviewed to obtain data on demographic and psychiatric characteristics, sexual behavior, and substance use. Data were available from 889 (73%) of 1214 eligible outpatients. Of these 889 patients, 49% were sexually active, 52% used alcohol, and 18% used street drugs during the past year. Eleven percent were at high risk for HIV infection: 7% reported having 3 or more sexual partners, 3% had been infected with an STD, 3% had traded sex, and fewer than 1% had shared injection equipment. HIV-risk status was modeled with logistic regression using diagnosis, type of residence, drug and alcohol use, and demographic variables; five- and six-predictor models were derived for two HIV-risk indicators. A bootstrap simulation supported the reliability of each model. We conclude that approximately one-half of adults living with a SPMI are sexually active, and a minority engages in behaviors that increase risk of HIV infection. Routine screening for HIV risk in psychiatric settings can identify patients who may benefit from risk reduction programs.

Figure 1

Each panel displays the probability of being Sexually Active during the past year as a function of participant age. The thick lines plot the estimated probability of risk and the thin lines form pointwise 95% confidence bands around that estimate, as derived from the six-predictor logistic regression model; dashed lines show estimates for African-American participants, solid lines for non-African-Americans. The four panels correspond to the possible combinations of two indicator variables in the regression model: schizophrenic diagnosis (Yes/No) and self-reported alcohol use within the past year (Yes/No). Thus, the figure portrays four of the six predictors in the logistic regression model (ROC curve area = 0.722). The predictors not represented in the figure are DAST risk classification score and residence type (supervised vs. unsupervised); adding those two predictors increases the ROC curve area to 0.734.

Figure 2

The open circles plot the estimated risk probability for the High Risk marker, as derived from the five-predictor logistic regression model; the attached vertical lines portray pointwise 95% confidence intervals. The abscissa is DAST risk status, one of the five predictors in the model. Each of the other predictors is an indicator variable distinguishing two subsets of participants; the upper panel in each section shows predictions for one subset, the lower panel for the other subset of participants. (Except for the second section, the upper panel represents increased probability of High Risk.) First section: African-Americans vs. all others; second section: males with diagnosis of Schizoprenia vs. all others; third section: males with “Never married” or “Unknown marital status” vs. all others; fourth section: females who reported having had six or more drinks on a single occasion vs. all others. The area under the ROC curve is 0.761 using all five predictors; the strongest single predictor is the DAST classification (ROC area = 0.670).