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BRIEF RESEARCH REPORT article

Front. Psychiatry
Sec. Personality Disorders
Volume 15 - 2024 | doi: 10.3389/fpsyt.2024.1501911

Capturing crisis dynamics: A novel personalized approach using multilevel hidden Markov modelling

Provisionally accepted
Emmeke Aarts Emmeke Aarts 1*Barbara Montagne Barbara Montagne 2Thomas van der Meer Thomas van der Meer 1Muriel A Hagenaars Muriel A Hagenaars 1
  • 1 Utrecht University, Utrecht, Netherlands
  • 2 GGz Centraal, Ermelo, Netherlands

The final, formatted version of the article will be published soon.

    Background: Prevention of (suicidal) crisis starts with appreciating its dynamics. However, crisis is a complex multidimensional phenomenon and how it evolves over time is still poorly understood.This study aims to clarify crisis dynamics by clustering fluctuations in the interplay of cognitive, affective, and behavioral (CAB) crisis factors within persons over time into latent states.To allow for fine grained information on CAB factors over a prolonged period of time, ecological momentary assessment data comprised of self-report questionnaires (3 × daily) on five CAB symptoms (self-control, negative affect, contact avoidance, contact desire and suicidal ideation) was collected in twenty-six patients (60 measurements per patient). Empirically-derived crisis states and personalized state dynamics were isolated utilizing multilevel hidden Markov models.In this proof-of-concept study, four distinctive and ascending CAB-based crisis states were derived. On the sample level, remaining within the current CAB crisis state from one fivehour interval to the next was most likely, with staying likeliness decreasing with ascending states.When residing in CAB crisis state 2 or higher, it was least likely to transition back to CAB crisis state 1. However, large patient heterogeneity was observed in both the tendency to remain within a certain CAB crisis state and transitioning between crisis states.The uncovered crisis states using multilevel HMM quantify and visualize the pattern of crisis trajectories at the patient individual level. The observed differences between patients underlines the need for future innovation in personalized crisis prevention, and statistical models that facilitate such a personalized approach.

    Keywords: Crisis prevention, Personality Disorders, Experience Sampling Method, Hidden markov model, Mobile health (mHealth)

    Received: 25 Sep 2024; Accepted: 16 Dec 2024.

    Copyright: © 2024 Aarts, Montagne, van der Meer and Hagenaars. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Emmeke Aarts, Utrecht University, Utrecht, Netherlands

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.