ABSTRACT

Improving our understanding of post-stroke fatigue is crucial to develop more effective interventions. This effort may be hampered by the methods used to assess fatigue, which usually rely on retrospective memory reports. However, such reports are prone to memory bias and may not capture variability in fatigue in daily life; thereby failing to adequately represent symptom experience. This study aimed to assess the strength of the relationship between real-time experience of post-stroke fatigue and the commonly used retrospective Fatigue Severity Scale (FSS). Thirty individuals with stroke completed 10 daily questionnaires about momentary (here-and-now) fatigue for six consecutive days using the mHealth application PsyMate^TM (Experience Sampling Method). From these real-time fatigue ratings (N = 1012), we calculated three indices: total average, peak fatigue, and fatigue on the final day. Afterwards, participants rated their fatigue retrospectively with the FSS. Results showed weak to moderate and strong correlations (range: .334, .667), with retrospective reports capturing up to 44% of the variance in the indices of momentary fatigue. Exploratory analyses also revealed that even individuals with similar total FSS scores demonstrated highly different day-to-day fatigue patterns. We conclude that retrospective measures may provide an incomplete view of post-stroke fatigue and diurnal variation therein.

摘要

提高我们对中风后疲劳的理解对于开发更有效的干预措施至关重要。这种努力可能会受到用于评估疲劳的方法的阻碍，这些方法通常依赖于回顾性记忆报告。然而，此类报告容易产生记忆偏差，并且可能无法捕捉日常生活中疲劳的变化；从而无法充分代表症状体验。本研究旨在评估卒中后疲劳的实时体验与常用的回顾性疲劳严重程度量表 (FSS) 之间关系的强度。30 名中风患者使用mHealth应用程序 PsyMate ^TM连续六天完成了 10 份关于瞬时（此时此地）疲劳的每日问卷（经验抽样方法）。根据这些实时疲劳评级 ( N  = 1012)，我们计算了三个指数：总平均、疲劳峰值和最后一天的疲劳。之后，参与者使用 FSS 回顾性地评估他们的疲劳程度。结果显示出弱到中度和强相关性（范围：0.334、0.667），回顾性报告捕获了高达 44% 的瞬时疲劳指数方差。探索性分析还显示，即使是具有相似 FSS 总分的个体也表现出截然不同的日常疲劳模式。我们得出的结论是，回顾性测量可能对中风后疲劳和其中的日变化提供不完整的视图。