Whereas sudden gains and losses (large shifts in symptom severity) in patients receiving psychotherapy appear abrupt and hence may seem unexpected, hypotheses from complex-systems theory suggest that sudden gains and losses are actually preceded by certain early-warning signals (EWSs). We tested whether EWSs in patients’ daily self-ratings of the psychotherapeutic process predicted future sudden gains and losses. Data were collected from 328 patients receiving psychotherapy for mood disorders who completed daily self-ratings about their therapeutic process using the Therapy Process Questionnaire (TPQ). Sudden gains and losses were classified from the Problem Intensity scale of the TPQ. The other items of the TPQ were used to compute the EWSs. EWSs predicted an increased probability for sudden gains and losses in a 4-day predictive window. These results show that EWSs can be used for real-time prediction of sudden gains and losses in clinical practice.

Objective: The feasibility of a high-frequency real-time monitoring approach to psychotherapy is outlined and tested for patients' compliance to evaluate its integration to everyday practice. Criteria concern the ecological momentary assessment, the assessment of therapy-related cognitions and emotions, equidistant time sampling, real-time nonlinear time series analysis, continuous participative process control by client and therapist, and the application of idiographic (person-specific) surveys.Methods: The process-outcome monitoring is technically realized by an internet-based device for data collection and data analysis, the Synergetic Navigation System. Its feasibility is documented by a compliance study on 151 clients treated in an inpatient and a day-treatment clinic.Results: We found high compliance rates (mean: 78.3%, median: 89.4%) amongst the respondents, independent of the severity of symptoms or the degree of impairment. Compared to other diagnoses, the compliance rate was lower in the group diagnosed with personality disorders.Conclusion: The results support the feasibility of high-frequency monitoring in routine psychotherapy settings. Daily collection of psychological surveys allows for the assessment of highly resolved, equidistant time series data which gives insight into the nonlinear qualities of therapeutic change processes (e.g., pattern transitions, critical instabilities).

Objective: While destabilization periods characterized by high variability and turbulence in a patient's psychological state might seem obstructive for psychotherapy, a complex systems approach to psychopathology predicts that these periods are actually beneficial as they indicate possibilities for reorganization within the patient. The present study tested the hypothesis that destabilization is related to better treatment outcome. Method: 328 patients who received psychotherapy for mood disorders completed daily self-ratings about their psychotherapeutic process. A continuous measure of destabilization was defined as the relative strength of the highest peak in dynamic complexity, a measure for variability and turbulence, in the self-ratings of individual patients. Results: Destabilization was found to be related to better treatment outcome. When improvers and non-improvers were analyzed separately, destabilization was found to be related to better treatment outcome in improvers but not in nonimprovers. Conclusions: Destabilization in daily self-ratings of the psychotherapeutic process is associated with better treatment outcome. The identification of destabilization periods in process-monitoring data is clinically relevant. During destabilization, patients are believed to be increasingly sensitive to the effects of therapy. Clinicians could tailor their interventions to these sensitive periods.