Quantifying reactivity to digital dietary assessment and the moderating influence of active information processing

用于评估行为的数字化工具，如计步器、智能手机传感器和智能手机应用程序，包括数字生态瞬时评估（EMA），越来越多地用于心理学研究。这些工具允许在现实生活中和实时评估行为，从而减少回忆偏差，提高调查结果的有效性。然而，使用这些工具收集的数据的有效性仍然可能是有限的，因为研究参与的影响，如测量反应。虽然已经对自我报告数据中的测量反应进行了许多研究，显示出对各种健康行为的小但一致的影响，但尚未很好地理解测量反应是否以及在多大程度上发生在行为的数字客观评估中。虽然关于身体活动和药物依从性的第一项研究表明，数字客观评估也容易产生测量反应，但尚未对其他行为进行研究，包括对饮食行为的数字评估。因此，本项目旨在调查数字饮食评估中是否以及在何种条件下发生测量反应。具体来说，第一个目标是量化对数字饮食评估的反应程度以及它如何随时间变化。其次，它的目的是调查主动信息处理作为一个潜在的测量反应性的机制。为了实现这些目标，将连续进行三项研究。前两项研究将使用在线调查（研究1，N = 180）和为期7天的EMA，然后进行定性访谈（研究2，N = 40），调查文献中使用的不同数字饮食评估协议是否在主动信息处理程度上存在差异。根据结果，将选择涉及最少和最活跃的信息处理的数字饮食评估方案在研究2中进行进一步研究（N = 400）。参与者将被随机分配到四组中的一组，其中记录过程期间和之后的主动信息处理程度将被操纵，并使用相应版本的研究应用程序连续14天记录他们的食物摄入量。根据收集的数据，将比较各组之间的测量反应性，并在整个研究期间研究其时间过程。深入了解数字饮食评估协议中测量反应的效应大小，时间过程和潜在机制，将有助于通过指导数字饮食评估工具的选择和开发来减少未来研究中的测量反应。因此，它将允许在现实生活中提供更准确的饮食行为见解，这将最终有利于公共卫生研究。

Digital tools for assessing behaviour, such as pedometers, smartphone sensors and smartphone apps including digital Ecological Momentary Assessment (EMA) are increasingly used in psychological research. These tools allow to assess behaviour in real-life and real-time, thus reduce recall bias and increase the validity of the findings. However, the validity of data collected using these tools still might be limited because of research participation effects such as measurement reactivity. While numerous studies have been conducted on measurement reactivity in self-report data, showing small but consistent effects across various health behaviours, it is not yet well understood whether and to what extent measurement reactivity occurs in digital objective assessment of behaviour. While first studies on physical activity and medication adherence suggest that also digital objective assessment is prone to measurement reactivity, no studies were yet conducted on other behaviours, including digital assessment of eating behaviour. The present project therefore aims to investigate whether and under which conditions measurement reactivity occurs in digital dietary assessment. Specifically, the first aim is to quantify the extent to which reactivity to digital dietary assessment occurs and how it changes across time. Second, it aims to investigate active information processing as a potential underlying mechanism of measurement reactivity. To address these aims, three consecutive studies will be conducted. The first two studies will investigate whether different digital dietary assessment protocols used in the literature differ in the degree of active information processing using an online survey (Study 1, N = 180) and a 7 day EMA followed by qualitative interviews (Study 2, N = 40). Based on the results, the digital dietary assessment protocols involving the least and the most active information processing will be selected to be further investigated in Study 2 (N = 400). Participants will be randomly allocated to one of four groups in which the degree of active information processing during and after the recording process will be manipulated, and record their food intake with the respective version of the study app for 14 consecutive days. Based on the collected data, measurement reactivity will be compared between groups and its time course will be studied across the study period. A deeper understand of the effect size, time course and underlying mechanisms of measurement reactivity in digital dietary assessment protocols will contribute to reduce measurement reactivity in future research by guiding the selection and development of digital dietary assessment tools. It will thus allow to provide more accurate insights into eating behaviour in real-life settings, which will ultimately benefit public health research.