Publications by authors named "David N Bertollo"

National data indicate that patients treated with buprenorphine for opiate use disorders are more likely to be White, highly educated, and to have greater incomes than those receiving methadone, but patterns of buprenorphine dissemination across demographic areas have not been documented in major metropolitan areas where poverty, minority populations and injection heroin use are concentrated. Rates of buprenorphine and methadone treatment are compared among areas of New York City defined by their income and ethnic/racial composition. Residential social areas (hereinafter called social areas) were defined as aggregations of ZIP codes with similar race/ethnicity and income characteristics, and were formed based on clustering techniques.

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Background: Falling duration of psychiatric inpatient stays over the past 2 decades and recent recommendations to tighten federal regulation of electroconvulsive therapy (ECT) devices have focused attention on trends in ECT use, but current national data have been unavailable.

Methods: We calculated the annual number of inpatient stays involving ECT and proportion of general hospitals conducting the procedure at least once in the calendar year with a national sample of discharges from 1993 to 2009. We estimated adjusted probabilities that inpatients with severe recurrent major depression (n = 465,646) were treated in a hospital that conducts ECT and, if so, received the procedure.

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Background: Black Americans with depression were less likely to receive electroconvulsive therapy (ECT) than whites during the 1970s and 80s. This pattern was commonly attributed to treatment of blacks in lower quality hospitals where ECT was unavailable. We investigated whether a racial difference in receiving ECT persists, and, if so, whether it arises from lesser ECT availability or from lesser ECT use within hospitals conducting the procedure.

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This column describes the nonproprietary software Talker, used to adapt screening instruments to audio computer-assisted self-interviewing (ACASI) systems for low-literacy populations and other populations. Talker supports ease of programming, multiple languages, on-site scoring, and the ability to update a central research database. Key features include highly readable text display, audio presentation of questions and audio prompting of answers, and optional touch screen input.

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