Bipolar disorder (BD) is a chronic psychiatric condition characterized by large episodic changes in mood and energy. Recently, BD has been proposed to be conceptualized as chronic cyclical mood instability, as opposed to the traditional view of alternating discrete episodes with stable periods in-between. Recognizing this mood instability may improve care and call for high-frequency measures coupled with advanced statistical models. To uncover empirically derived mood states, a multilevel hidden Markov model (HMM) was applied to 4-month ecological momentary assessment data in 20 patients with BD, yielding ∼9,820 assessments in total. Ecological momentary assessment data comprised self-report questionnaires (5 × daily) measuring manic and depressive constructs. Manic and depressive symptoms were also assessed weekly using the Altman Self-Rating Mania Scale and the Quick Inventory for Depressive Symptomatology Self-Report. Alignment between HMM-uncovered momentary mood states and weekly questionnaires was assessed with a multilevel linear model. HMM uncovered four mood states: neutral, elevated, mixed, and lowered, which aligned with weekly symptom scores. On average, patients remained < 25 hr in one state. In almost half of the patients, mood instability was observed. Switching between mood states, three patterns were identified: patients switching predominantly between (a) neutral and lowered states, (b) neutral and elevated states, and (c) mixed, elevated, and lowered states. In all, elevated and lowered mood states were interspersed by mixed states. The results indicate that chronic mood instability is a key feature of BD, even in "relatively" euthymic periods. This should be considered in theoretical and clinical conceptualizations of the disorder. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

中文翻译：

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双相情感障碍患者情绪不稳定的证据：将多级隐马尔可夫模型应用于强化纵向生态瞬时评估数据。


双相情感障碍 (BD) 是一种慢性精神疾病，其特征是情绪和精力的大幅间歇性变化。最近，人们提出将 BD 概念化为慢性周期性情绪不稳定，这与交替离散发作及其间的稳定期的传统观点相反。认识到这种情绪不稳定可能会改善护理，并需要采取高频措施与先进的统计模型相结合。为了揭示经验得出的情绪状态，我们将多级隐马尔可夫模型 (HMM) 应用到 20 名 BD 患者的 4 个月生态瞬时评估数据中，总共产生了约 9,820 个评估。生态瞬时评估数据包括测量躁狂和抑郁结构的自我报告问卷（每天 5 次）。每周还使用奥特曼躁狂自评量表和抑郁症状自我报告快速清单评估躁狂和抑郁症状。使用多级线性模型评估 HMM 发现的瞬时情绪状态与每周问卷调查之间的一致性。 HMM 发现了四种情绪状态：中性、升高、混合和降低，这与每周症状评分一致。平均而言，患者处于一种状态的时间小于 25 小时。几乎一半的患者情绪不稳定。在情绪状态之间切换时，确定了三种模式：患者主要在（a）中性和低落状态、（b）中性和升高状态以及（c）混合、升高和降低状态之间切换。总而言之，情绪高涨和低落的状态中都夹杂着混合状态。结果表明，即使在“相对”情绪正常的时期，慢性情绪不稳定也是双相情感障碍的一个关键特征。在该疾病的理论和临床概念化中应考虑这一点。 （PsycInfo 数据库记录 (c) 2024 APA，保留所有权利）。