The integration problem is a key challenge in contemporary psychiatry and refers to difficulties in combining different explanations of mental disorders into a coherent model. Modern approaches suggest that the factors of influence that need to be integrated can be categorized into four domains: biological, experiential, sociocultural, and existential. One proposed way to address this challenge is through an integrative research approach involving the construction of a personalized network model (PNM), a data-driven representation of an individual’s condition that connects all four domains of influence on mental disorders in a non-hierarchical manner. However, this framework has so far lacked systematic methodological guidelines for constructing such models.
The aim of this master’s thesis was to develop a methodological framework to guide the collection, selection, and analysis of data in a longitudinal mixed-methods study. Over the course of one year, we followed six participants who ranged diagnostically from the normative population to individuals experiencing symptoms of mood disorders. Data were collected monthly using ecological momentary assessment, partially structured phenomenological interviews, and the MASQ questionnaire (Mood and Anxiety Symptom Questionnaire). Based on the developed methodology, we constructed PNMs for each participant and treated each as a case study. We critically evaluated the feasibility and applicability of the proposed method and assessed its capacity to adequately represent the participants’ psychological states and track changes in their lived experience over time.
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