Date of Submission
Doctor of Psychology (PsyD)
Robert A DiTomasso, PhD, ABPP, Chair, Department of Psychology
Barbara Golden, Psy. D, ABPP, Chairperson
Petra Kottsieper, PhD
Victor Lidz, PhD
This study attempted to predict mental health/substance abuse treatment initial appointment attendance, utilizing specific social, provider, institutional, medical, and psychological risk factors through the use of a logistic regression model. The initial frequency analysis revealed that only 155 individuals were ever scheduled to attend an appointment of the original data set (N=298). The majority of individuals could not be scheduled due to unavailability, disinterest, latency and other reasons. A new data set was created from individuals who were scheduled and variables were collapsed across categories to include: length of wait time to appointment, CD4 count, prescribed medications, reason for referral, and past history/ current substance abuse in the model. This study did not find any of the identified risk factors or the proposed model (c2 (6, N=155) =5.66, p= .46) to be significantly predictive of treatment attendance. However, the clinical implications of pre-treatment dropout (or never attending) in this study support the importance of a behavioral health model of treatment. The findings of this study suggest pre-treatment dropout could be decreased with integrated treatment in the primary care setting, especially for HIV/AIDS patients.
Amodio, Rachel D., "Predicting Initial Mental Health/Substance Abuse Treatment Attendance in HIV/AIDS Patients: An Exploration of Risk Factors" (2013). PCOM Psychology Dissertations. 267.