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Thirty-Third Annual Meeting of the Society for Research in Psychopathology

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168. Borderline personality pathology as a network of temporally connected symptoms

Background: Current conceptualizations of borderline personality pathology are limited by certain unwarranted assumptions. Following the disease model, it is assumed that symptoms co-occur due to an underlying common cause. Network psychometricians have proposed a fundamentally different conceptualization: symptoms co-occur not because of a common cause but because of direct dynamic associations among symptoms. This study aims to understand borderline personality pathology as a network of temporally connected symptoms.

Methods: Participants were 21 undergraduate students endorsing 5 or more symptoms on the McLean Screening Instrument for BPD (Zanarini et al., 2003). Following baseline assessment, participants were prompted to answer a Qualtrics-based survey of BPD symptoms twice each day for 40 days.

Results: Temporal network analysis was implemented using R packages qgraph and mlVAR which yield within person contemporaneous and temporal network of symptoms. Nodes with the highest in-degree included impulsive behavior and fluctuations in mood. Nodes with the highest out-degree were fear of abandonment and dissociation. Network structure and comparison between contemporaneous and temporal networks will be visually presented.

Conclusions: The present study demonstrates how BPD symptoms interact witheach other over time and maintain the disordered state within-person. By identifying the most central nodes, temporal network analysis can inform personalized treatment.

Haya Fatimah
University of South Florida

Lance Rappaport
Windsor University

Alexandria Choate
University of South Florida

Marina Bornovalova
University of South Florida


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