Unilateral termination of psychotherapy and the Decision Action Pathway Interactive Network (DAPIN) model
The effectiveness of psychological therapies has received increasing attention in recent years with a confidant optimism building in the strong research evidence for its efficacy. However, criticism comes from the study of attrition from therapy in routine clinical practice, which studies show can reach from 30 to 60%. Searches for the causes of attrition have uncovered a multitude of correlations but only socio-economic variables emerge as significant predictors of attrition. This present study proposes and tests a theoretical model with clear implications for practice and research. In reviewing three broad literatures on health service use the concept of the Decision Action Pathway Interactive Network (DAPIN) began to emerge. Health decisions are seen as taking place within an emerging decision/action pathway that is subject to a dynamic interaction network. Decisions are made by individuals based on rational calculations, with network interactions providing the mechanism by which the social factors influence the decision/action pathway. Empirical testing of DAPIN consisted of the construction of a patient self-report cost attached to therapy attendance (CATA) measure that could be used to determine whether people of low SES do in fact have higher network costs attached to attending therapy and whether this is related to higher attrition. A small sample of patients attending their first appointment completed CATA and those who unilaterally terminated in the first four sessions compared with those who continued therapy. Weak support was obtained for the DAPIN model. The Demand sub-scale of CAT A proved to be a powerful predictor of unilateral termination from therapy (attrition) at the early stage of therapy attendance and provides a useful short tool for routine clinical practice. The small and idiosyncratic sample used meant that the DAPIN model could not be adequately tested. However, the evidence accumulated suggests that the model is worthy of more extensive testing.