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

博士论文研究：开发和测试新策略来检测强化纵向自我报告方法中的疏忽反应

• 批准号: 2150617
• 负责人: Genevieve Dunton
• 金额: $ 1.79万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-15 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2150617&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Developing; Testing

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.

该博士学位论文研究项目将研究参与者对移动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方法之一。由于智能手机的流行，研究人员可以选择对参与者的智能手机进行实时重复调查。但是，参与者可能会选择不对调查做出反应，或者可以在不完全关注的情况下做出回应。当前，缺乏有关如何检测和管理后一种调查反应的后一种问题的数据和指导。对调查的注意力不集中可能导致数据质量差，并影响研究结论的准确性。这项研究将在纵向和反复的调查中检查不专心的反应。该项目将建立何时以及为什么不专心响应可能发生的模型，并提供有关提高自我报告措施有效性的预防策略的见解。该项目还将生成用于检测数据质量不佳的建议并提出预防措施。该项目产生的数据和技术将公开可用。改进的研究方法论和更准确的研究结论将使政策形成和基于循证的决策以及通过科学新闻业，教育和研究受益于社会。本研究项目将将不集中的响应检测元素从在线调查研究中转化为一项强化生态货币评估（EMA）研究，以开发可用于未来深入培养长期研究的新颖和实践策略。由于移动技术方面的进步，使用智能手机在自然环境中访问个人的希望有所增加。 EMA是一种实时抽样策略，研究人员可以用来收集自我报告数据的重复度量，例如当前的经验，行为和情绪，从而产生了更加生态有效的数据。但是，鉴于完成重复调查的潜在负担，维持参与者的参与可能会具有挑战性，并且缺乏有关如何管理负担导致数据质量降低的研究和指导。该项目将1）测试检测哪些调查可能无效的准确性或指标，2）使用混合方法方法来确定哪些因素会增加参与不专心响应的可能性，3）模型如何模拟数据分析中包括这些无效的调查在结果中的偏差。这些分析的结果是，将制定指南进行纵向研究。该奖项反映了NSF的法定任务，并认为使用基金会的知识分子优点和更广泛的影响审查标准，被认为值得通过评估。