Dropout prediction in a public mental health intervention for sub-threshold and mild panic disorder

Abstract

AbstractDropout is a common and serious problem in psychological research and practice. When participants terminate treatment prematurely, this may have methodological and clinical consequences. The aim of this study was to identify predictors of dropout in a sample of patients (N = 217) with sub-threshold and mild panic disorder treated with a public mental health intervention programme based on cognitive-behavioural principles. Three groups of possible baseline predictors were selected from the literature: (1) socio-demographic, (2) personal, and (3) illness-related variables. A total of 51 (23.5%) participants were classified as dropouts. Dropouts were further subdivided into pretreatment dropouts (n = 17) who attended no course sessions at all and regular dropouts (n = 34) who attended 1–5 course sessions. Multivariable logistic regression analyses were used to identify independent predictors of dropout. Few variables were significantly associated with increased odds of dropout and the total explained variance was small. Fewer years of education was the only independent predictor of total dropout and male gender was associated with more pretreatment dropout. No independent predictors were found for regular dropout. It can be concluded that it is difficult to precisely predict dropout risk in patients participating in a public mental health intervention for panic symptoms.