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识别生态瞬间评估研究中的粗心反应:从事后分析到实时数据监测。

Identification of careless responding in ecological momentary assessment research: From posthoc analyses to real-time data monitoring.

机构信息

Department of Psychology.

出版信息

Psychol Methods. 2022 Dec;27(6):958-981. doi: 10.1037/met0000312. Epub 2021 Sep 16.

DOI:10.1037/met0000312
PMID:34582244
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11565177/
Abstract

With the emerging ubiquity of cell phones, ecological momentary assessment (EMA) as a set of methods enable researchers to study momentary social, psychological, and affective responses to everyday life. Additionally, EMA enables researchers to acquire longitudinal data without the need for multiple lab visits. As the use of EMA in research increases, so too does the necessity of determining what constitutes valid or careless individual EMA responses to ensure validity and replicability of findings. Currently, EMA studies solely consider the response rate of a participant for exclusion. Yet, other features of an assessment can help to determine whether a response is careless or implausible. Here, we examined over 18,000 EMA text message responses of individual affect items to derive a data-driven model of what constitutes a "careless response." Results from this study indicate that an overly fast time to complete items (≤ 1 s), an overly narrow within assessment response variance ( ≤ 5), and the percentage of items that fall at the mode (≥ 60%) are independent and reliable indicators of a careless response. Excluding careless responses such as these remove implausible positive correlations among psychometric antonyms (e.g., relaxed and anxious). Further, by identifying and removing careless responses, we also identify careless responders, participants who could be removed from group analyses. We use these results to develop and introduce an R package, EMAeval, so EMA researchers may similarly identify careless responses and responders either online during data collection or posthoc, after data collection has completed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

摘要

随着手机的普及,生态瞬间评估 (EMA) 作为一套方法,使研究人员能够研究日常生活中瞬间的社会、心理和情感反应。此外,EMA 使研究人员能够在不需要多次实验室访问的情况下获得纵向数据。随着 EMA 在研究中的应用越来越多,确定什么构成了对个体 EMA 反应的有效或粗心的必要性也越来越大,以确保研究结果的有效性和可重复性。目前,EMA 研究仅考虑参与者的反应率作为排除标准。然而,评估的其他特征也可以帮助确定一个反应是否是粗心或不可信的。在这里,我们检查了超过 18000 个个体情感项目的 EMA 文本消息反应,以得出一个由数据驱动的“粗心反应”构成模型。这项研究的结果表明,完成项目的时间过快(≤1 秒)、评估内的反应方差过窄(≤5)以及处于模式的项目百分比过高(≥60%)是粗心反应的独立且可靠的指标。排除这些粗心反应,如不可信的心理对立词(如放松和焦虑)之间的正相关。此外,通过识别和排除粗心反应,我们还可以识别粗心的反应者,即那些可以从组分析中删除的参与者。我们使用这些结果开发并引入了一个 R 包 EMAeval,以便 EMA 研究人员可以在数据收集过程中或数据收集完成后在线或事后识别粗心反应和反应者。(PsycInfo 数据库记录(c)2023 APA,保留所有权利)。

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