2017
DOI: 10.1007/s41133-017-0006-2
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Measuring Affective Well-Being by the Combination of the Day Reconstruction Method and a Wearable Device: Case Study of an Aging and Depopulating Community in Japan

Abstract: Affective well-being indicates the changes in the predominance of positive or negative affects of people in response to their daily experiences. For measuring affective well-being, people are usually asked to indicate their affective states in several episodes that they experienced in a day. However, such conventional methods have been problematic in terms of their burdensomeness on participants and the validity of the rating. To overcome these problems, we attempted to introduce a new approach for measuring a… Show more

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Cited by 5 publications
(3 citation statements)
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“…The DRM aims to capture an entire day's experience while curtailing opportunities for recall biases, limiting participant burden and providing a cost-effective alternative to more burdensome experience sampling methodologies (Sonnenberg et al , 2012; Diener & Tay, 2014). The DRM is widely used to measure subjective well-being in everyday life and has been applied both in large representative population surveys such as the American Time Use Survey and the German Socio-Economic Panel (Krueger et al , 2009; Anusic et al , 2017) and in smaller-scale studies focused on specific topics (Srivastava et al , 2008; Daly et al , 2010; Knabe et al , 2010; Bakker et al , 2013; Daly et al , 2014; Ishio & Abe, 2017; Lee et al , 2017).…”
Section: Naturalistic Monitoring and The Drmmentioning
confidence: 99%
“…The DRM aims to capture an entire day's experience while curtailing opportunities for recall biases, limiting participant burden and providing a cost-effective alternative to more burdensome experience sampling methodologies (Sonnenberg et al , 2012; Diener & Tay, 2014). The DRM is widely used to measure subjective well-being in everyday life and has been applied both in large representative population surveys such as the American Time Use Survey and the German Socio-Economic Panel (Krueger et al , 2009; Anusic et al , 2017) and in smaller-scale studies focused on specific topics (Srivastava et al , 2008; Daly et al , 2010; Knabe et al , 2010; Bakker et al , 2013; Daly et al , 2014; Ishio & Abe, 2017; Lee et al , 2017).…”
Section: Naturalistic Monitoring and The Drmmentioning
confidence: 99%
“…The majority of existing approaches using data, for example, through Data-Driven Design (DDD) studies, used big data, e.g., social media and online reviews of commercially available products, as data sources (Bertoni, 2020;. A few examples include biological data (Ishio and Abe, 2017), pictures (Carter and Mankoff, 2005), video recordings (Arvola et al, 2017), use of smart speaker (Gorkovenko et al, 2019), and use of baby bottle (Bogers et al, 2016). The studies suggest that behavioral data can be used to explore users' contexts in user research (Gorkovenko et al, 2023).…”
Section: Introductionmentioning
confidence: 99%
“…Some researchers measure affective SWB retrospectively, by asking a single question, like “Taking all things together, how would you say that you are these days: very happy, pretty happy, or not too happy?” [ 7 ], or using rating scales, such as the Positive (e.g., cheerful) and Negative (e.g., irritable) Affect Schedule, where people rate the intensity of several emotions over a specific time frame [ 8 ]. Others prefer to measure affective SWB by capturing actual momentary affective states experienced in daily life [ 9 ], because global retrospective measures could be biased by personality traits, current mood, and limits on the number of recalled memories [ 10 ]. Regardless of the affective SWB measurements, most studies have focused on between-person differences in the levels of affect, either in general or at particular points in time, often overlooking the importance of the rhythm of affect over the course of the day [ 6 ].…”
Section: Introductionmentioning
confidence: 99%