Generalized Multiplicative Model for Assessing Outcome in Psychotherapy: Subjective Well-Being

The study presents the performance of generalized multiplicative model (GMultM) for assessing outcome in psychotherapy. GMultM is a flexible nonlinear regression method which is able to predict the impact of subjects' psychological variables (common factors such as inner directedness, time competence, sociotropy, and perfectionism, locus of control, body dissatisfaction, neuroticism, and alexithymia) as well as their changes on the outcome of psychotherapy. This nonlinear regression model including interaction effects among predictors has a higher explanatory power to predict treatment outcome, compared to any linear model. Also, GMultMs are accurate and easily interpretable models, compared to complex models such as, for example, based on nonlinear dynamics, complexity, stochastic optimization control theories, etc. A case study of rhythmic movement therapy (RMT) for increasing the level of subjective well-being (SWB) is presented. Results revealed that: (a) the GMultM not only predicts the current levels of SWB satisfactorily but also allows obtaining the partial response functions of psychological predictors of SWB directly as a result of estimation of model's parameters; (b) GMultM predicts the changes in SWB after RMT intervention in each participant satisfactorily and thus can be applied as the individualized assessment tool for psychotherapy's outcome.