Passive sensing of anhedonia and amotivation in a transdiagnostic sample.

IF 3.1 Q2 PSYCHIATRY
Adam J Culbreth,Deanna M Barch,Subigya Nepal,Dror Ben-Zeev,Andrew Campbell,Erin K Moran
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引用次数: 0

Abstract

Anhedonia and avolition are core clinical features of schizophrenia, bipolar disorder, and major depressive disorder, which have been traditionally assessed using clinical rating scales. However, recent developments in mobile technology allow for measurement of anhedonia and amotivation using passive sensors (e.g., global positioning system and actigraphy) and surveys completed in daily life (i.e., ecological momentary assessment [EMA]). The current study examined associations between clinical rating scales assessing anhedonia and amotivation and passive sensing measures. We aimed to determine the added value of passive sensing measures in explaining variability in clinical interviews, compared to models using EMA alone. We recruited a transdiagnostic sample (schizophrenia = 41, bipolar disorder = 47, and major depressive disorder = 48) to complete an in-person assessment session, as well as a 2-week EMA and passive sensing protocol. Passive sensing measures included physical distance traveled, number of phone calls sent/received, and number of texts sent/received. EMA included the assessment of interest and enjoyment in daily activities. We found that reports of interest/enjoyment in daily activities significantly predicted gold standard, clinical rating scales of anhedonia and avolition across diagnostic groups (standardized β = -0.208, p = .015, model R2 = .04). Including participant distance traveled into this model aided our ability to explain variance (standardized β = -0.280, p < .001, model R² = .12). Finally, adding call (standardized β = -0.170, p = .039) and text (standardized β = -0.198, p = .022) data further improved variance explained (model R² = .18). These data suggest that passive sensor streams strengthen the associations between assessments in daily life and gold standard ratings of anhedonia and avolition, suggesting "added value" in using these approaches to understand motivational experience in people with psychotic and mood pathology. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
在一个诊断样本中的快感缺乏和动机的被动感知。
快感缺乏和逃避是精神分裂症、双相情感障碍和重度抑郁症的核心临床特征,传统上使用临床评定量表对其进行评估。然而,移动技术的最新发展允许使用无源传感器(例如,全球定位系统和活动记录仪)和在日常生活中完成的调查(例如,生态瞬间评估[EMA])来测量快感缺乏症和动机。目前的研究检查了临床评定量表评估快感缺乏症和动机和被动感知措施之间的联系。与单独使用EMA的模型相比,我们的目的是确定被动感知措施在解释临床访谈变异性方面的附加价值。我们招募了一个跨诊断样本(精神分裂症= 41,双相情感障碍= 47,重度抑郁症= 48)来完成一个面对面的评估会议,以及一个为期2周的EMA和被动感知方案。被动感知措施包括物理距离,发送/接收的电话数量,发送/接收的短信数量。EMA包括对日常活动的兴趣和享受的评估。我们发现,对日常活动的兴趣/享受的报告显著地预测了诊断组中快感缺乏症的金标准、临床评定量表和自发性(标准化β = -0.208, p = 0.015,模型R2 = 0.04)。将参与者所走的距离纳入该模型有助于我们解释方差(标准化β = -0.280, p < .001,模型R²= .12)。最后,加入呼叫(标准化β = -0.170, p = 0.039)和文本(标准化β = -0.198, p = 0.022)数据进一步改善了方差解释(模型R²= 0.18)。这些数据表明,被动传感器流加强了日常生活中的评估与快感缺乏症和自发性的黄金标准评级之间的联系,表明使用这些方法来理解精神病和情绪病理学患者的动机体验具有“附加价值”。(PsycInfo Database Record (c) 2025 APA,版权所有)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
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