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

基本信息

  • 批准号:
    2150617
  • 负责人:
  • 金额:
    $ 1.79万
  • 依托单位:
  • 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

项目摘要

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.
这个博士论文研究项目将调查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群行为和态度的最好方法之一。由于智能手机的普及,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。然而,参与者可能选择不回应调查,或者可能在没有充分关注的情况下回应。目前,关于如何发现和管理调查中回答不专心的后一个问题,缺乏数据和指导。对调查的反应不认真可能导致数据质量差,影响研究结论的准确性。本研究将在纵向和重复调查中检查注意力不集中的反应。该项目将建立模型,说明什么时候和为什么可能发生反应不专心的情况,并提供预防策略的见解,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向公众提供。改进的研究方法和更准确的研究结论将通过科学新闻、教育和研究使政策形成和基于证据的决策以及社会受益。本研究项目将把在线调查研究中的不注意反应检测元素转化为密集的生态货币评估(EMA)研究,以开发新颖实用的策略,为未来密集的纵向研究提供建议。由于移动技术的进步,使用智能手机在自然环境中访问个人的可能性越来越大。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,如当前的经历、行为和情绪,从而获得更有效的生态数据。然而,鉴于完成重复调查的潜在负担,维持参与者的参与可能具有挑战性,并且缺乏关于如何管理由于负担而导致的数据质量下降的研究和指导。该项目将1)测试准确性或指数,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增加了参与不专心响应的可能性,以及3)在数据分析中如何将这些无效调查纳入结果偏差的模型。作为这些分析的结果,将制定进行纵向研究的指导方针。该奖项反映了美国国家科学基金会的法定使命,并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,被认为值得支持。

项目成果

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