ReviewPsychopathology2025
A Phenomenological Reappraisal of Dynamical Systems in Psychopathology.
Review in Psychopathology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundDynamical systems theory (DST) has recently gained traction as a framework to describe and predict the progression of psychopathology. However, a number of challenges to the application of DST to psychopathology have arisen, including the heterogeneity of symptom measures and the lack of theoretical underpinnings to describe the temporal unfolding of psychiatric illnesses. SUMMARY: In this article, we aim to show how the integration of methods from phenomenology may strengthen the application of DST in psychopathology research. We explore how phenomenological psychopathology can improve DST-based investigations in two key ways: (1) by specifying the core symptoms of interest in psychopathological states in a more precise manner by focusing on subjective experiences, and (2) by deepening our theoretical understanding of how these symptoms evolve in severity over time. We show how incorporating phenomenologically informed measures of experience can complement DST using clinical high risk (CHR) for psychosis as a test case, and we demonstrate the utility of combining phenomenologically informed theory and DST by examining the ipseity-disturbance model (IDM) of psychosis development. We close by offering a vision for the broader integration of DST and phenomenological research methods within psychopathological research. KEY MESSAGES: Phenomenological investigations can synergize with and advance the use of DST to better understand and predict psychiatric disorders and transitions in states of mental health.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.