Doctoral Dissertation Research: Developing and Testing Novel Strategies to Detect Inattentive Responding in Intensive Longitudinal Self-Report Methods

这个博士论文研究项目将调查参与者对移动的调查的反应的准确性。调查是研究人员了解人口行为和态度的最佳途径之一。由于智能手机的普及，研究人员可以选择在参与者的智能手机上进行真实的重复调查。然而，参与者可能选择不对调查作出答复，或可能在没有充分注意的情况下作出答复。目前，在如何发现和管理调查中的后一个不注意回答问题方面缺乏数据和指导。对调查的不认真回应可能会导致数据质量差，影响研究结论的准确性。本研究将探讨在纵向和重复调查的不注意反应。该项目将建立模型，说明何时以及为何可能发生注意力不集中的反应，并提供有关预防战略的见解，以提高自我报告措施的有效性。该项目还将提出检测数据质量差的建议，并提出预防措施。该项目产生的数据和技术将公开提供。改进的研究方法和更准确的研究结论将有利于政策的形成和基于证据的决策，以及通过科学的新闻，教育和研究的社会。本研究项目将把在线调查研究的疏忽反应检测元素转化为密集的生态货币评估（EMA）研究，以开发新的和实用的策略，可以推荐给未来的密集纵向研究。由于移动的技术的进步，使用智能手机访问自然环境中的个人的前景越来越好。EMA是一种实时采样策略，研究人员可以使用它来收集自我报告数据的重复测量，例如当前的经历，行为和情绪，从而获得更具生态有效性的数据。然而，鉴于完成重复调查可能带来的负担，维持参与者的参与可能具有挑战性，而且在如何管理因负担而降低的数据质量方面缺乏研究和指导。该项目将1）测试准确性或指标，以检测哪些调查可能无效，2）使用混合方法来确定哪些因素会增加参与疏忽响应的可能性，以及3）建模如何将这些无效调查纳入数据分析中产生结果偏差。作为这些分析的结果，将制定进行纵向研究的指导方针。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估。

This doctoral dissertation research project will investigate the accuracy of participants' responses to mobile surveys. Surveys are one of the best ways for researchers to learn about the behaviors and attitudes of a population. Due to the popularity of smartphones, researchers have the option of conducting real time repeated surveys on participants' smartphones. However, participants may choose not to respond to the surveys or may respond without fully paying attention. Currently, there is a lack of data and guidance on how to detect and manage the latter problem of inattentive responding in surveys. Inattentive response to surveys may result in poor data quality and affect the accuracy of research conclusions. This research will examine inattentive responding in longitudinal and repeated surveys. The project will establish models of when and why inattentive responding is likely to occur and provide insights into preventive strategies to increase the validity of self-report measures. The project also will generate recommendations for detecting poor data quality and suggest preventative measures. Data and techniques resulting from this project will be made publicly available. Improved research methodology and more accurate research conclusions will benefit policy formation and evidence-based decision making, as well as society through scientific journalism, education, and research.This research project will translate inattentive response detection elements from online survey research to an intensive ecological monetary assessment (EMA) study to develop novel and practical strategies that could be recommended for future intensive longitudinal studies. Due to advancements in mobile technology, there is increased promise of using smartphones to access individuals in their natural environment. EMA is a real-time sampling strategy that researchers can use to collect repeated measures of self-report data such as current experiences, behaviors, and moods, resulting in more ecologically valid data. However, sustaining participant engagement can be challenging given the potential burden from completing repeated surveys, and there is a lack of research and guidance on how to manage decreased data quality due to burden. This project will 1) test the accuracy or indices to detect which surveys may be invalid, 2) use a mixed methods approach to determine what factors increase the probability of engaging in inattentive responding, and 3) model how including these invalid surveys in data analysis creates deviations in results. As a result of these analyses, guidelines will be developed for conducting longitudinal studies.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.