Good vibrations

Okeke, Fabian; Sobolev, Michael; Dell, Nicola; Estrin, Deborah

doi:10.1145/3229434.3229463

Cited by 89 publications

(27 citation statements)

References 43 publications

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“…We suspect these results to be conservative estimates of the effectiveness since we did not enforce or incentivise compliance. Similar to past research (Okeke, Sobolev, Dell, et al, 2018), smartphone tracking alone, which constituted our control condition, in the absence of digital nudges did not lead to a change in mobile usage. It is becoming clear that self-monitoring is insufficient and that other solutions such as digital nudges are required to regulate phone usage.…”

Section: Discussionsupporting

confidence: 67%

“…Our research approach and findings are of practical significance. In prior research, solutions of mobile overuse relied on applications that were specifically developed for research purposes (Allcott et al, 2020;Hiniker et al, 2016;Okeke, Sobolev, Dell, et al, 2018) which limits their scope. The advantage of using commercially developed screen time apps like we did in our study, is that they are available on the majority of smartphones.…”

Section: Discussionmentioning

confidence: 99%

“…They can reduce self-interruptions and stress (Kim et al, 2017) as well as smartphone usage (Ko et al, 2015). At the opposite end of the continuum lie passive digital nudges including reminders and feedback messages (Hiniker et al, 2016), screen changes or vibrations (Okeke, Sobolev, Dell, et al, 2018). Passive nudges do not require specific actions from users and do not limit the ability to use the phone (as opposed to time limits).…”

Section: Previous Research On Solutions For Reducing Screen Timementioning

confidence: 99%

See 2 more Smart Citations

Digital Nudges for Screen Time Reduction: A Randomized Control Trial with Performance and Wellbeing Outcomes

Zimmermann¹,

Sobolev²

2020

Preprint

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Many people want to reduce their smartphone usage to increase productivity and well-being, but fail to accomplish this goal. We conduct a randomized control trial with a student population (N=112) over three weeks to test the effectiveness of two widely available digital nudges for screen time reduction. Along with a tracking-only control condition, a passive digital nudge (i.e., grayscale mode) was compared to an active digital nudge (i.e., time limits). The passive nudge led to an immediate, significant reduction of objectively measured screen time compared to the control condition. Conversely, the active nudge led to a smaller and gradual screen time reduction. Those in the control condition, who simply tracked their usage, did not lower their screen time. As opposed to the popular belief that reducing screen time is beneficial, we found no immediate causal effects of reducing screen time on subjective well-being and academic performance.

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Section: Discussionsupporting

confidence: 67%

Section: Discussionmentioning

confidence: 99%

Section: Previous Research On Solutions For Reducing Screen Timementioning

confidence: 99%

See 1 more Smart Citation

Digital Nudges for Screen Time Reduction: A Randomized Control Trial with Performance and Wellbeing Outcomes

Zimmermann¹,

Sobolev²

2020

Preprint

Self Cite

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“…Another common form of presentation were different kinds of notifications that alerted the participants: text messages #6 , push notifications #3a,#3b,#15a , and popup message dialogues #11a,#4,#12a . The most insistent awareness intervention, created by Okeke et al (2018), started smartphone vibrations when a time quota for a distracting website (in their case, Facebook) was exceeded #10a,#10b . The smartphone vibrated until the user left the distracting website.…”

Section: Findings and Analysismentioning

confidence: 99%

Digital self‐control interventions for distracting media multitasking ‐ A systematic review

Biedermann

Schneider

Drachsler

2021

Computer Assisted Learning

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Digital distractions can interfere with goal attainment and lead to undesirable habits that are hard to get red rid of. Various digital self‐control interventions promise support to alleviate the negative impact of digital distractions. These interventions use different approaches, such as the blocking of apps and websites, goal setting, or visualizations of device usage statistics. While many apps and browser extensions make use of these features, little is known about their effectiveness. This systematic review synthesizes the current research to provide insights into the effectiveness of the different kinds of interventions. From a search of the ‘ACM’, ‘Springer Link’, ‘Web of Science’, ’IEEE Xplore’ and ‘Pubmed’ databases, we identified 28 digital self‐control interventions. We categorized these interventions according to their features and their outcomes. The interventions showed varying degrees of effectiveness, and especially interventions that relied purely on increasing the participants' awareness were barely effective. For those interventions that sanctioned the use of distractions, the current literature indicates that the sanctions have to be sufficiently difficult to overcome, as they will otherwise be quickly dismissed. The overall confidence in the results is low, with small sample sizes, short study duration, and unclear study contexts. From these insights, we highlight research gaps and close with suggestions for future research.

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“…190]. Moreover, new design interventions developed by HCI researchers have mostly been informed by user interviews and intuitions of interface designers [78,105,195], or by theories including cognitive load theory [37], Social Cognitive Theory [94] and nudge theory [90,136]. Meanwhile, the dual systems and valuebased models prominent in current cognitive neuroscience research on self-regulation 1 [22,28,165,168,191,200] have yet to be applied [cf.…”

Section: Introductionmentioning

confidence: 99%

Self-Control in Cyberspace

Lyngs

Lukoff

Slovák

et al. 2019

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

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Many people struggle to control their use of digital devices. However, our understanding of the design mechanisms that support user self-control remains limited. In this paper, we make two contributions to HCI research in this space: first, we analyse 367 apps and browser extensions from the Google Play, Chrome Web, and Apple App stores to identify common core design features and intervention strategies afforded by current tools for digital self-control. Second, we adapt and apply an integrative dual systems model of self-regulation as a framework for organising and evaluating the design features found. Our analysis aims to help the design of better tools in two ways: (i) by identifying how, through a wellestablished model of self-regulation, current tools overlap and differ in how they support self-control; and (ii) by using the model to reveal underexplored cognitive mechanisms that could aid the design of new tools. * Also with

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Good vibrations

Cited by 89 publications

References 43 publications

Digital Nudges for Screen Time Reduction: A Randomized Control Trial with Performance and Wellbeing Outcomes

Digital Nudges for Screen Time Reduction: A Randomized Control Trial with Performance and Wellbeing Outcomes

Digital self‐control interventions for distracting media multitasking ‐ A systematic review

Self-Control in Cyberspace

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