About the development of decision support systems in psychotherapy: The validation of an individualized prediction model with sequential analysis
ZEITSCHRIFT FUR KLINISCHE PSYCHOLOGIE UND PSYCHOTHERAPIE. Bd. 34. H. 3. 2005 S. 165 - 175
Erscheinungsjahr: 2005
Publikationstyp: Zeitschriftenaufsatz
Doi/URN: 10.1026/1616-3443.34.3.165
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Inhaltszusammenfassung
Background and objective: This paper examines new research concepts to support treatment modality decisions at the start of treatment as well as adaptive decision making during the course of psychotherapy. A strategy is developed, which can be used especially under the circumstances of established practice research networks, to predict and to track patient progress in clinical routine as well as generating large data bases of indiviual psychotherapy patients for further research. Method and r...Background and objective: This paper examines new research concepts to support treatment modality decisions at the start of treatment as well as adaptive decision making during the course of psychotherapy. A strategy is developed, which can be used especially under the circumstances of established practice research networks, to predict and to track patient progress in clinical routine as well as generating large data bases of indiviual psychotherapy patients for further research. Method and results: Data are used from 619 patients, treated in outpatient centers in Switzerland and Germany and a data disaggregation strategy from avalanche research is applied in order to define a patient-specific sample for each patient. Using this patient-specific sample a growth curve model is used to model an expected treatment course for each patient under the condition of being treated in a disorder-specific (n = 262) or a combined disorder-specific and interpersonal therapy modality (n = 356). Following that, a sequential analysis is applied as a validation strategy to evaluate the appropriateness of those individual predictions. Conclusions: The use of that analytic strategy and the practical utility in different clinical settings is discussed. Furthermore results are presented in terms of their implications for supporting treatment modality decisions at patient intake, evaluating treatment progress and the identification of negative developments in treatment, as well as choosing optimal alternatives. » weiterlesen» einklappen