Gritters Noah M, Harmata Gail I S, Buyukgok Deniz, Hazegh Pooya, Hoth Karin F, Barsotti Ercole John, Fiedorowicz Jess G, Williams Aislinn J, Richards Jenny Gringer, Sathyaputri Leela, Schmitz Samantha L, Long Jeffrey D, Wemmie John A, Magnotta Vincent A
Carver College of Medicine, The University of Iowa, IA, United States; Department of Radiology, The University of Iowa, IA, United States.
Department of Radiology, The University of Iowa, IA, United States; Department of Psychiatry, The University of Iowa, IA, United States; Iowa Neuroscience Institute, The University of Iowa, IA, United States.
J Affect Disord. 2025 Mar 1;372:470-480. doi: 10.1016/j.jad.2024.12.040. Epub 2024 Dec 11.
Suicide attempts are more prevalent in people with bipolar I disorder (BD-I) than in the general population. Most prior studies of suicide in BD-I have focused on separate emotion-related assays or clinician-administered scales, whereas a single, brief, and multidimensional battery of self-report measures has not yet been explored. Here, we utilized the NIH Toolbox Emotion Battery (NIHTB-EB) to assess various emotional measures, determine which were cross-sectionally associated with prior suicide attempt in BD-I, evaluate whether the NIHTB-EB could be used to identify past suicide attempt in BD-I with machine learning, and compare model performance versus using clinical mood scales. The study included 39 participants with BD-I and history of suicide attempt, 48 with BD-I without history of suicide attempt, and 58 controls. We found that 9 of the 17 measures were associated with past suicide attempt in BD-I. The initial random forest model indicated that the most important distinguishing variables were perceived stress, emotional support, anger-hostility, anger-physical aggression, perceived rejection, loneliness, and self-efficacy. Overall, the models utilizing NIHTB-EB measures performed better (69.0 % to 70.1 % accuracy) than the model containing clinical mood scale information without the NIHTB-EB measures (57.5 % accuracy). These findings suggest the NIHTB-EB could be a useful and easy-to-deploy tool in understanding the role of emotion-related measures in suicide in BD-I. Furthermore, these results highlight specific emotional subdomains that could be promising targets for longitudinal studies or interventions aimed at reducing suicide in BD-I.
双相I型障碍(BD-I)患者的自杀未遂情况比普通人群更为普遍。此前大多数关于BD-I自杀的研究都集中在单独的情绪相关检测或临床医生实施的量表上,而尚未探索过单一、简短且多维度的自我报告测量组合。在此,我们使用美国国立卫生研究院工具箱情绪量表(NIHTB-EB)来评估各种情绪测量指标,确定哪些指标与BD-I患者既往自杀未遂存在横断面关联,评估NIHTB-EB是否可用于通过机器学习识别BD-I患者过去的自杀未遂情况,并将模型性能与使用临床情绪量表进行比较。该研究纳入了39名有BD-I且有自杀未遂史的参与者、48名有BD-I但无自杀未遂史的参与者以及58名对照者。我们发现,17项测量指标中有9项与BD-I患者过去的自杀未遂有关。初始随机森林模型表明,最重要的区分变量是感知压力、情感支持、愤怒-敌意、愤怒-身体攻击、感知被拒、孤独感和自我效能感。总体而言,使用NIHTB-EB测量指标的模型表现更好(准确率为69.0%至70.1%),优于不包含NIHTB-EB测量指标的临床情绪量表信息模型(准确率为57.5%)。这些发现表明,NIHTB-EB可能是一个有用且易于应用的工具,有助于理解情绪相关测量指标在BD-I自杀中的作用。此外,这些结果突出了特定的情绪子领域,它们可能是旨在减少BD-I自杀的纵向研究或干预措施的有前景的目标。