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Facilitating Dynamic Assessment of Psychological Interventions

Wisnes, Roger
Master thesis
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master thesis (3.348Mb)
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https://hdl.handle.net/11250/2827082
Utgivelsesdato
2021-07-16
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  • Master theses [69]
Sammendrag
The mental healthcare system requires an improvement in patient accessibility and a decrease in resource dependency. Internet-Delivered Psychological Treatment (IDPT) is a tool with a documented positive effect to bring about this improvement. However, there is still more research needed in this field to reduce patient dropout rates. One hypothesis for increasing user adherence in IDPT systems is to create a personalized user experience for the individual patient through adaptive strategies. This study examines how to facilitate the implementation of well-documented (rule-based) algorithms for such adaptiveness. Through the work, the research methodology Design Science was used to design and develop a digital artifact for an open-source, early-stage prototype of an IDPT framework. The intention of the artifact was to facilitate the implementation of rule-based adaptive algorithms, by simplifying the process of creating and adapting Cognitive Behavioral Therapy (CBT)-based treatment programs. The result of the study is an artifact that provides a graphical representation of the structure and content of CBT-based treatment programs. The representation is a hierarchical layout with three levels of interactive network graphs where nodes represent the elements of the CBT program (interventions, modules, and tasks), and the edges represent the relationships between these elements. Along with the graphs, detailed views of the information within the elements are also provided. The study concludes that the graphical representation of the content of a CBT-based treatment program within IDPT can simplify the previously mentioned process by clarifying how the elements of the CBT program are related to each other, and thus provide the therapist with an easier way to correct any errors and omissions within the elements, and adjust criteria that adaptive algorithms can use.
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The University of Bergen
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