The Race Towards Digital Wellbeing

Roffarello, Alberto Monge; Russis, Luigi De

doi:10.1145/3290605.3300616

Cited by 97 publications

(70 citation statements)

References 38 publications

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“…Vanden Abeele (2020, p. 13) considers this concept to refer to the "subjective individual experience of optimal balance between the benefits and drawbacks obtained from mobile connectivity." For many, this involves becoming more intentional with how digital media are used (Roffarello & De Russis, 2019), and aligning device use with general goals (Parry et al, 2020).…”

Section: Digital Wellbeing Applications: Adoption Use and Perceived mentioning

confidence: 99%

“…A growing body of research investigates applications relating to digital wellbeing through a variety of quantitative, qualitative, and design-led approaches (Roffarello & De Russis, 2019;Oeldorf-Hirsch & Chen, 2020;Parry et al, 2020;Rooksby et al, 2016;Saariketo, 2019). Studies in related areas have used various adoption models to investigate user motivations and behaviour.…”

Section: Self-monitoring and Digital Wellbeing Applicationsmentioning

confidence: 99%

“…In a review of 42 Android applications related to digital wellbeing Roffarello and De Russis (2019) found that, while a majority of applications include features which support monitoring of device use, they rarely include features that restrict device or application access.…”

Section: Self-monitoring and Digital Wellbeing Applicationsmentioning

confidence: 99%

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Digital Wellbeing Applications: Adoption, Use and Perceived Effects

Parry¹,

Roux²,

Morton³

et al. 2020

Preprint

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Increasingly, mobile applications enable people to monitor and regulate their smartphone use inthe support of digital wellbeing. Herein we report a mixed-methods study involving the collection of both quantitative and qualitative data from a student sample conducted with the aim of investigating, firstly, the adoption of applications designed to support digital wellbeing, secondly, the factors that influence the continued use of such applications and, thirdly, the effects users perceive these applications to have on their digital wellbeing. The outcomes of this study highlight the importance of individual motivations and the need to understand digital wellbeing as more than simply the use of an application but, rather, a subjective consideration of the place of digital media in an individual’s life. The present study provides a rich descriptive account of the temporal variability, person-specificity, and device-contingent nature of digital wellbeing.

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Section: Digital Wellbeing Applications: Adoption Use and Perceived mentioning

confidence: 99%

Section: Self-monitoring and Digital Wellbeing Applicationsmentioning

confidence: 99%

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Digital Wellbeing Applications: Adoption, Use and Perceived Effects

Parry¹,

Roux²,

Morton³

et al. 2020

Preprint

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“…However, the technical comparison of existing and our proposed system in terms of services, architectural style, design, and state-ofthe-art technologies are discussed in our previous published work [7]. Habit formation, in particular, could play an essential role in digital well-being applications, supporting behavior change towards more effective use of technology and ensuring the long-term effects of the adapted behavior [9]. Hence, our analysis drives the contribution through the following research questions (1) How to quantify the complex behavior…”

Section: Wellness Management Applicationsmentioning

confidence: 99%

“…https://esurvey.uid.com/project!overview9 Google Scholar based Citation 9449 (viewed on 15/08/2020) VOLUME 4, 2016…”

mentioning

confidence: 99%

Towards User-Centric Intervention Adaptiveness: Influencing Behavior-Context Based Healthy Lifestyle Interventions

et al. 2020

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In the era of digital well-being, smart gadgets are the unobtrusive sources of acquiring information. A variety of personalized wellness applications support self-quantification based recommendations to provide wellness status for achieving personalized targets. However, these applications are unable to promote the induction of new healthy habits and thus are not too much effective for long term as users tend to loose their interest. Thus, we have proposed a methodology for User-Centric Adaptive Intervention based on behavior change theory for maintaining end-users' interest. The methodology consists of four steps: (1) quantification of behavior based on contributing factors governed by expert-driven rules; (2) behavior-context based mapping for the identification of behavior status of the user; (3) selection of appropriate way of intervention to get fruitful outcomes; and finally (4) feedback based evaluation on the basis of recorded activities and questionnaires for satisfaction. A comprehensive healthy behavior index-based quantification supports the machine learning-based prediction model for behavior-context mapping. Furthermore, the evaluation is performed through implicit and explicit feedback analysis along with the accuracy of the behavior-context prediction model through multiple scenarios to cover comprehensive situations. The ensemble classifier suggests the accuracy of 98.02% for the behavior-context prediction model, which is higher than the other classifiers. The gain in behavior change is drawn from implicit feedback, which depicts that behavior context-based methods have improved the adaptation in behavior at a steady pace for the long term. The explicit feedback from 99 end-users of wellness application based on the proposed methodology obtained Good and Desired status for widely used System Usability Score and AttrakDiff tools respectively.

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Algorithmic Content Recommendations on a Video-Sharing Platform Used by Children

Radesky,

Bridgewater,

Black

et al. 2024

JAMA Netw Open

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ImportanceFree video-sharing platforms (VSPs) make up a high proportion of children’s daily screen use. Many VSPs make algorithmic recommendations, appearing as thumbnail images from the video, which content creators use to advertise their video content.ObjectiveTo explore how VSP thumbnails use attention-capture designs to encourage engagement with content and to test whether VSP algorithmic recommendations offer more problematic thumbnail features over time.Design, Setting, and ParticipantsIn this cross-sectional study conducted in January 2022, researchers mimicked the search behavior of children on a popular VSP by randomly clicking on recommended videos in order to test whether thumbnail designs changed over 20 sequential video engagements. A digital, footprint-free data collection setting was created by using a new computer and wireless internet router. Data were collected from YouTube via an internet browser not logged into a user account. Data analysis occurred from April to December 2022.ExposuresManual searches using 12 top-searched terms popular with school-aged children were conducted. Researchers captured the video thumbnails recommended at the end of each video and randomly clicked subsequent videos for 20 sequential engagements.Main Outcomes and MeasuresThumbnail content codes were developed through iterative review of screenshots by a multidisciplinary research team and applied by trained coders (reliability, κ &gt;.70). The prevalence of problematic thumbnail content and change in prevalence over 20 engagements was calculated using the Cochran-Armitage trend test.ResultsA total of 2880 video thumbnails were analyzed and 6 features were coded, including visual loudness; drama and intrigue; lavish excess and wish fulfillment; creepy, bizarre, and disturbing; violence, peril, and pranks; and gender stereotypes. A high proportion contained problematic features including the creepy, bizarre, and disturbing feature (1283 thumbnails [44.6%]), violence, peril, and pranks feature (1170 thumbnails [40.6%]), and gender stereotypes feature (525 thumbnails [18.2%]). Other features included attention-capture designs such as the visual loudness feature (2278 thumbnails [79.1%]), drama and intrigue feature (2636 thumbnails [91.5%]) and lavish excess and wish fulfillment feature (1286 thumbnails [44.7%]). Contrary to the hypotheses, problematic feature prevalence did not increase over time, but the gender stereotypes feature increased with more engagement in the recommendations feed (P for trend &lt; .001).Conclusions and RelevanceIn this study of video recommendations for search terms popular with children, thumbnails contained problematic and attention-capturing designs including violent, stereotyped, and frightening themes. Research is needed to understand how children respond to thumbnail designs and whether such designs influence the quality of content children consume.

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The Race Towards Digital Wellbeing

Cited by 97 publications

References 38 publications

Digital Wellbeing Applications: Adoption, Use and Perceived Effects

Digital Wellbeing Applications: Adoption, Use and Perceived Effects

Towards User-Centric Intervention Adaptiveness: Influencing Behavior-Context Based Healthy Lifestyle Interventions

Algorithmic Content Recommendations on a Video-Sharing Platform Used by Children

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