了解 ALSPAC 中同意共享超市购物数据的调节因素。

Romana Burgess, A. Skatova, Poppy Taylor
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引用次数: 0

摘要

导言与背景购物数据是一种宝贵的资源,可为消费者行为和健康提供洞察力。近年来,人们对将购物数据用于健康研究的兴趣与日俱增。然而,人们对愿意与研究人员分享购物数据者的特征知之甚少。目标与方法本研究旨在调查影响个人决定是否同意为研究目的共享其购物数据的因素。我们将利用一项队列研究--雅芳父母与子女纵向研究 (ALSPAC) --的数据来解决这个问题。我们将借鉴 2018 年一项调查的答复,该调查询问了 ALSPAC 参与者对超市会员卡的使用情况、他们对与 ALSPAC 共享这些数据的接受程度以及他们对潜在隐私问题的看法。在 4462 名受访者中,65.4% 表示至少拥有一张英国大型超市或商店会员卡。其中,88.4%的受访者表示愿意与 ALSPAC 分享这些数据用于研究目的。在今天,即 2023 年左右,参与者明确表示同意或不同意共享这些数据。我们的分析方法将考虑生理性别、种族、教育、就业、社会经济地位和焦虑等因素,将其作为同意过程的潜在调节因素。我们计划采用多种标准统计方法来分析数据集中的抽样偏差,包括回归模型和相关性测试。与数字足迹的相关性我们的研究将为越来越多的关于队列研究与数字足迹数据集之间数据关联的文献做出贡献。结果本研究的结果将为了解影响参与者就数据共享做出同意决定的因素提供有价值的见解。我们将为正在进行的有关隐私和数字足迹数据使用道德的讨论做出贡献,并为该领域制定更具包容性的同意程序提供信息。结论与启示本研究将为数字足迹领域的同意实践提供信息,识别并解决潜在的同意障碍,并为目前有关负责任地、合乎道德地使用购物数据的讨论做出贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Understanding moderators of consent regarding the sharing of supermarket shopping data in ALSPAC.
Introduction & BackgroundShopping data is a valuable resource, offering insights into consumer behaviour and health. In recent years, there has been a growing interest in using shopping data for the purposes of health research. However, little is known about the characteristics of those who are willing to share their shopping data with researchers. Objectives & ApproachThis study aims to investigate the factors that influence individuals' decisions to consent to sharing their shopping data for research purposes. We will leverage data from a cohort study – the Avon Longitudinal Study of Parents and Children (ALSPAC) – to address this question. We will draw upon the responses of a 2018 survey, which asked ALSPAC participants about their use of supermarket loyalty cards, their perceived acceptability of sharing this data with ALSPAC, and their perspectives on potential privacy concerns. Of the 4,462 respondents, 65.4% indicated ownership of at least one major UK supermarket or store loyalty card. Among these, 88.4% expressed a potential willingness to share this data with ALSPAC for research purposes. In the present day – around 2023 – participants have explicitly either granted or withheld consent for the sharing of this data. Our analysis approach will consider factors such as biological gender, ethnicity, education, employment, socioeconomic status, and anxiety as potential moderators to the consent process. We plan to employ a mix of standard statistical methods to analyse sampling biases in the dataset, including regression modelling and correlation tests. Relevance to Digital FootprintsOur study will contribute to the growing body of literature on data linkage between cohort studies and digital footprints datasets. ResultsThe findings from this study will offer valuable insights into the factors influencing participants' consent decisions regarding data sharing. We will contribute to ongoing discussions about privacy and the ethical use of digital footprints data, informing the development of more inclusive consent processes in this field. Conclusions & ImplicationsThis study will inform consent practices in the realm of digital footprints, identifying and addressing potential barriers to consent, and contributing to the ongoing discourse on the responsible and ethical use of shopping data.
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