Perspektiven einer evidenzbasierten und personalisierten Psychotherapie
Der Trierer Therapie Navigator (TTN)
Abstract
Zusammenfassung.Theoretischer Hintergrund: Der Diskurs um eine evidenz-basierte und personalisierte (bzw. „Precision“) Medizin sowie zur Umsetzung von Evaluation und Qualitätssicherung hat in den letzten Jahren auch Einfluss auf die Psychotherapieforschung genommen. Dies gilt in Bezug auf die patientenspezifische Auswahl von Behandlungen (u. a. personalisierte Vorhersagen) als auch für die dynamische Anpassung von Interventionen im Therapieverlauf (adaptive Indikation, Feedback, Problemlösetools). Fragestellung und Methode: Im Bereich der differentiellen Indikation sind mittlerweile unterschiedliche Algorithmen („machine learning“) und Netzwerkmodelle zur Vorhersage erprobt worden. Für eine empirisch gestützte adaptive Indikation bilden insbesondere die Studien zum psychometrischen Feedback sowie die Entwicklung von Problemlösetools für Risikopatient_innen die Grundlage. Ergebnisse: Diese Grundlagenforschung war die Basis für die Entwicklung eines Entscheidungssystems (Trierer Therapie Navigator, TTN) zur Vorhersage der optimalen Behandlungsstrategie und des Abbruchrisikos. Darüber hinaus enthält der TTN ein adaptives Modellierungselement des Behandlungsverlaufs. Es können damit Risikopatienten für einen Behandlungsmisserfolg identifiziert und Behandlungsoptimierungen über Problemlösetools unterstützt werden. Schlussfolgerungen: In vorliegender Arbeit werden zentrale neue Ansätze einer evidenz-basierten und personalisierten Psychotherapie zusammenfassend dargestellt sowie die Anwendung in der klinischen Praxis diskutiert.
Abstract.Background and objective: The discourse on evidence-based and personalized (or precision) medicine and the implementation of evaluation and quality monitoring in recent years has also had an impact on psychotherapy research. This relates to both patient-specific treatment selection (i. e., personalized predictions) and dynamic adaptation of interventions during the course of therapy (feedback, clinical support tools). Method: In the field of personalized predictions, several algorithms (i. e., machine learning) and network models have been applied to predict the optimal treatment protocol, the risk of drop-out, or the effects of specific treatment strategies. The basis for a personalized and empirically supported adaptive feedback and support system is mainly provided by studies of psychometric feedback and the development of clinical support tools for patients at risk of deterioration. Results and conclusion: This article describes central contemporary approaches in this field of research and discusses implementation in clinical practice by means of the Trier Treatment Navigator (TTN).
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