No abstract

Although improvement of clients' state is a central concern for psychotherapy, relatively little is known about how change in outcome variables unfolds during psychotherapy. Client progress may follow highly variable temporal courses, and this variation in treatment courses may have important clinical implications. By analyzing treatment progress using growth mixture modeling up to the 6th session in a sample of 192 outpatients treated under routine clinic conditions, the authors identified 5 client groups based on similar progress on the short form versions of the Clinical Outcomes in Routine Evaluation-Outcome Measure. The shapes of early change typical for these client groups were characterized by (a) high initial impairment, (b) low initial impairment, (c) early improvement, (d) medium impairment with continuous treatment progress, or (e) medium impairment with discontinuous treatment progress. Moreover, the shapes of early change were associated with different treatment outcomes and durations, and several intake variables (depression, anxiety, and age) enabled prediction of the shape of early change and/or prediction of individual treatment progress within client groups with similar shapes of change.

As proposed by the dose-effect model, the expected course of improvement in psychotherapy appears to follow a negatively accelerated pattern of change, irrespective of the duration of the treatment. However, our results also suggest that the rate of change is not constant across various treatment lengths. As proposed by the "good enough level" model, longer treatments are associated with less rapid rates of change.

Background: Mental health literacy is a prerequisite for early recognition and intervention in mental disorders. The aims of this paper are to determine whether a sample of university students recognise different symptoms of depression and schizophrenia and to reveal factors influencing correct recognition.

Empirical methods have been found to be superior to clinical judgment for the purpose of correctly identifying patients at risk for treatment failure and, hence, to enhance psychotherapy outcomes. The development and evaluation of an empirical approach aimed at supporting clinical decisions during the course of psychotherapy is described. The tool provides predictions based on a patient-specific sampling strategy called the nearest neighbors method and on growth curve approaches to model an expected treatment course for each patient. Using session-by-session data from an outpatient center in the US (N = 4365), this new empirically derived decision model was evaluated and compared with a clinically based approach loosely based on an adaptation of clinically significant change concepts. The empirically derived decision system was found to be superior to the rational clinically based one in almost all measures of prediction accuracy, indicating its potential to identify patients at risk for treatment failure.