ArticlePsychological medicine2019
Identification and initial validation of empirically derived bipolar symptom states from a large longitudinal dataset: an application of hidden Markov modeling to the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study.
Article in Psychological medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 18 citations in OpenAlex.
- The dynamic influence of exercise on emotional state among people with a history of mood disorder.Psychiatry research · 2026Article
- The Dynamics of Mood in Bipolar Disorder: How Mathematical Models Help Phenotype Individuals, Forecast Mood, and Clarify Underlying Mechanisms.Current psychiatry reports · 2025Review
- Day-to-day variability in sleep and activity predict the onset of a hypomanic episode in patients with bipolar disorder.Journal of affective disorders · 2025Observational
- Capturing crisis dynamics: a novel personalized approach using multilevel hidden Markov modeling.Frontiers in psychiatry · 2024Article
- Specificity of affective dynamics of bipolar and major depressive disorder.Brain and behavior · 2023Article
- A critical evaluation of dynamical systems models of bipolar disorder.Translational psychiatry · 2022Review
- Mania and bipolar depression: complementing not opposing poles-a post-hoc analysis of mixed features in manic and hypomanic episodes.International journal of bipolar disorders · 2021Article
- Dynamics of data-driven microstates in bipolar disorder.Journal of psychiatric research · 2021Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundAlthough bipolar disorder (BD) is a fundamentally cyclical illness, a divided model of BD that emphasizes polarity over cyclicity has dominated modern psychiatric diagnostic systems since their advent in the 1980s. However, there has been a gradual return to conceptualizations of BD which focus on longitudinal course in the research community due to emerging supportive data. Advances in longitudinal statistical methods promise to further progress the field.
methodsThe current study employed hidden Markov modeling to uncover empirically derived manic and depressive states from longitudinal data [i.e. Young Mania Rating Scale and Montgomery-Asberg Depression Rating Scale responses across five occasions from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study], estimate participants' probabilities of transitioning between these states over time (n = 3918), and evaluate whether clinical variables (e.g. rapid cycling and substance dependence) predict participants' state transitions (n = 3229).
resultsAnalyses identified three empirically derived mood states ('euthymic,' 'depressed,' and 'mixed'). Relative to the euthymic and depressed states, the mixed state was less commonly experienced, more temporally unstable, and uniquely associated with rapid cycling, substance use, and psychosis. Individuals assigned to the mixed state at baseline were relatively less likely to be diagnosed with BD-II (v. BD-I), more likely to present with a mixed or (hypo)manic episode, and reported experiencing irritable and elevated mood more frequently.
conclusionsThe results from the current study represent an important step in defining, and characterizing the longitudinal course of, empirically derived mood states that can be used to form the foundation of objective, empirical attempts to define meaningful subtypes of affective illness defined by clinical course.
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