Stieger Stefan, Schmid Irina, Altenburger Philip, Lewetz David
Department of Psychology and Psychodynamics, Karl Landsteiner University of Health Sciences, Krems an der Donau, Austria.
Front Psychiatry. 2020 Nov 26;11:538122. doi: 10.3389/fpsyt.2020.538122. eCollection 2020.
New technologies (e.g., smartphones) have made it easier to conduct Experience Sampling Method (ESM) studies and thereby collect longitudinal data . However, limiting interruption burden (i.e., the strain of being pulled out of everyday life) remains a challenge, especially when assessments are frequent and/or must be made immediately after an event, such as when capturing the severity of clinical symptoms in everyday life. Here, we describe a wrist-worn microcomputer programmed with a Physical Analogue Scale (PAS) as a novel approach to ESM in everyday life. The PAS uses the position of a participant's forearm between flat and fully upright as a response scale like a Visual Analogue Scale (VAS) uses continuous ratings on a horizontal line. We present data from two pilot studies (4-week field study and lab study) and data from a 2-week ESM study on social media ostracism (i.e., when one's social media message is ignored; = 53 participants and 2,272 event- and time-based assessments) to demonstrate the feasibility of this novel approach for event- and time-based assessments, and highlight advantages of our approach. PAS angles were accurate and reliable, and VAS and PAS values were highly correlated. Furthermore, we replicated past research on cyber ostracism, by finding that being ignored resulted in significantly stronger feelings of being offended, which was more pronounced when ignored by a group compared to a single person. Furthermore, participants did not find it overly difficult to complete the assessments using the wearable and the PAS. We suggest that the PAS is a valid measurement procedure in order to assess fleeting and/or frequent micro-situations in everyday life. The source code and administration application are freely available.
新技术（如智能手机）使进行经验取样法（ESM）研究并进而收集纵向数据变得更加容易。然而，限制干扰负担（即从日常生活中抽身的压力）仍然是一项挑战，尤其是当评估频繁且/或必须在事件发生后立即进行时，比如在捕捉日常生活中临床症状的严重程度时。在此，我们描述一种编程有物理模拟量表（PAS）的腕戴式微型计算机，作为日常生活中ESM的一种新方法。PAS使用参与者前臂在平放和完全竖起之间的位置作为反应量表，就像视觉模拟量表（VAS）使用水平线上的连续评分一样。我们展示了两项试点研究（为期4周的现场研究和实验室研究）的数据，以及一项关于社交媒体排斥（即一个人的社交媒体信息被忽略时；n = 53名参与者和2272次基于事件和时间的评估）的为期2周的ESM研究的数据，以证明这种新方法用于基于事件和时间的评估的可行性，并突出我们方法的优点。PAS角度准确可靠，VAS和PAS值高度相关。此外，我们重复了过去关于网络排斥的研究，发现被忽略会导致明显更强烈的被冒犯感，与被一个人忽略相比，被一群人忽略时这种感觉更明显。此外，参与者发现使用可穿戴设备和PAS完成评估并没有太难。我们认为PAS是一种有效的测量程序，可用于评估日常生活中短暂和/或频繁出现的微观情境。源代码和管理应用程序可免费获取。
