Cited By
View all- Jiang JLi SLi XXu YZhao JAn P(2024)BIG-AOME: Designing Bodily Interaction Gamification towards Anti-sedentary Online Meeting Environments (Preprint)JMIR Serious Games10.2196/62778Online publication date: 31-May-2024
Changing Computer-Usage Behaviors: What Users Want, Use, and Experience
Pages 53 - 60
Abstract
Computer-related behavior change is helpful for well-being. We conducted a survey to investigate three research questions and further inform the design of computer-related behavior change applications. RQ1: What do people want to change and why/how? RQ2: What applications do people use or have used, why do they work or not, and what additional support is desired? RQ3: What are helpful/unhelpful computer breaks and why? Our survey had 68 participants and three key findings. First, time management is a primary concern, but emotional and physical side-effects are also important. Second, site blockers, self-trackers, and timers are commonly used, but they are ineffective as they are easy-to-ignore and not personalized. Third, away-from-computer breaks, especially involving physical activity, are helpful, whereas on-screen breaks are unhelpful, especially when they are long, because they are not refreshing. We recommend personalized and closed-loop computer-usage behavior change support and especially encouraging off-the-computer computer breaks.
References
[1]
Gabriel Barata, Hugo Nicolau, and Daniel Gonçalves. 2012. AppInsight: what have I been doing?. In Proceedings of the International Working Conference on Advanced Visual Interfaces(AVI ’12). Association for Computing Machinery, New York, NY, USA, 465–472. https://doi.org/10.1145/2254556.2254645
[2]
Judith Borghouts, Duncan P. Brumby, and Anna L. Cox. 2020. TimeToFocus: Feedback on Interruption Durations Discourages Distractions and Shortens Interruptions. ACM Transactions on Computer-Human Interaction 27, 5 (Aug. 2020), 32:1–32:31. https://doi.org/10.1145/3396044
[3]
Scott A Cambo, Daniel Avrahami, and Matthew L Lee. 2017. BreakSense: Combining physiological and location sensing to promote mobility during work-breaks. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. 3595–3607.
[4]
Seyma Kucukozer Cavdar, Tugba Taskaya-Temizel, Mirco Musolesi, and Peter Tino. 2020. A Multi-perspective Analysis of Social Context and Personal Factors in Office Settings for the Design of an Effective Mobile Notification System. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4, 1 (March 2020), 15:1–15:38. https://doi.org/10.1145/3381000
[5]
Woohyeok Choi, Sangkeun Park, Duyeon Kim, Youn-kyung Lim, and Uichin Lee. 2019. Multi-Stage Receptivity Model for Mobile Just-In-Time Health Intervention. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 2 (June 2019), 39:1–39:26. https://doi.org/10.1145/3328910
[6]
J Clement. 2020. Coronavirus: Impact on Online Usage in the US-Statistics & Facts. Hamburg: Statista (2020).
[7]
Jeffrey A Clements and Randall Boyle. 2018. Compulsive technology use: Compulsive use of mobile applications. Computers in Human behavior 87 (2018), 34–48.
[8]
Elena Di Lascio, Shkurta Gashi, Juan Sebastian Hidalgo, Beatrice Nale, Maike E. Debus, and Silvia Santini. 2020. A Multi-Sensor Approach to Automatically Recognize Breaks and Work Activities of Knowledge Workers in Academia. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4, 3 (Sept. 2020), 78:1–78:20. https://doi.org/10.1145/3411821
[9]
Daniel A Epstein, Daniel Avrahami, and Jacob T Biehl. 2016. Taking 5: Work-breaks, productivity, and opportunities for personal informatics for knowledge workers. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. 673–684.
[10]
Hayley Guillou, Kevin Chow, Thomas Fritz, and Joanna McGrenere. 2020. Is Your Time Well Spent? Reflecting on Knowledge Work More Holistically. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems(CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–9. https://doi.org/10.1145/3313831.3376586
[11]
Jane M Healy. 1999. Failure to connect: How computers affect our children’s minds–for better and worse. Simon and Schuster.
[12]
Donghan Hu and Sang Won Lee. 2019. ScreenTrack: Using Visual History for Self-tracking Computer Activities and Retrieving Working Context. In The Adjunct Publication of the 32nd Annual ACM Symposium on User Interface Software and Technology(UIST ’19). Association for Computing Machinery, New York, NY, USA, 44–46. https://doi.org/10.1145/3332167.3357110
[13]
Sanghoon Kang and Terri R Kurtzberg. 2019. Reach for your cell phone at your own risk: The cognitive costs of media choice for breaks. Journal of behavioral addictions 8, 3 (2019), 395–403.
[14]
Harmanpreet Kaur, Alex C. Williams, Daniel McDuff, Mary Czerwinski, Jaime Teevan, and Shamsi T. Iqbal. 2020. Optimizing for Happiness and Productivity: Modeling Opportune Moments for Transitions and Breaks at Work. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems(CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–15. https://doi.org/10.1145/3313831.3376817
[15]
Jaejeung Kim, Hayoung Jung, Minsam Ko, and Uichin Lee. 2019. GoalKeeper: Exploring Interaction Lockout Mechanisms for Regulating Smartphone Use. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 1 (March 2019), 16:1–16:29. https://doi.org/10.1145/3314403
[16]
Jaejeung Kim, Joonyoung Park, Hyunsoo Lee, Minsam Ko, and Uichin Lee. 2019. LocknType: Lockout Task Intervention for Discouraging Smartphone App Use. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems(CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3290605.3300927
[17]
Young-Ho Kim, Eun Kyoung Choe, Bongshin Lee, and Jinwook Seo. 2019. Understanding Personal Productivity: How Knowledge Workers Define, Evaluate, and Reflect on Their Productivity. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems(CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3290605.3300845
[18]
Daria J Kuss and Halley M Pontes. 2018. Internet addiction. Vol. 41. Hogrefe Verlag.
[19]
Kai Lukoff, Cissy Yu, Julie Kientz, and Alexis Hiniker. 2018. What Makes Smartphone Use Meaningful or Meaningless?Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 1 (March 2018), 22:1–22:26. https://doi.org/10.1145/3191754
[20]
Yuhan Luo, Bongshin Lee, Donghee Yvette Wohn, Amanda L. Rebar, David E. Conroy, and Eun Kyoung Choe. 2018. Time for Break: Understanding Information Workers’ Sedentary Behavior Through a Break Prompting System. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, 1–14. https://doi.org/10.1145/3173574.3173701
[21]
Ulrik Lyngs, Kai Lukoff, Petr Slovak, William Seymour, Helena Webb, Marina Jirotka, Jun Zhao, Max Van Kleek, and Nigel Shadbolt. 2020. ’I Just Want to Hack Myself to Not Get Distracted’ Evaluating Design Interventions for Self-Control on Facebook. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1–15.
[22]
Gloria Mark, Mary Czerwinski, and Shamsi T Iqbal. 2018. Effects of individual differences in blocking workplace distractions. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. 1–12.
[23]
Gloria Mark, Shamsi Iqbal, and Mary Czerwinski. 2017. How blocking distractions affects workplace focus and productivity. In Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. 928–934.
[24]
G-J Meerkerk, Regina JJM Van Den Eijnden, Ad A Vermulst, and Henk FL Garretsen. 2009. The compulsive internet use scale (CIUS): some psychometric properties. Cyberpsychology & behavior 12, 1 (2009), 1–6.
[25]
Andre N. Meyer, Gail C. Murphy, Thomas Zimmermann, and Thomas Fritz. 2017. Design Recommendations for Self-Monitoring in the Workplace: Studies in Software Development. Proceedings of the ACM on Human-Computer Interaction 1, CSCW (Dec. 2017), 79:1–79:24. https://doi.org/10.1145/3134714
[26]
Fabian Okeke, Michael Sobolev, Nicola Dell, and Deborah Estrin. 2018. Good vibrations: can a digital nudge reduce digital overload?. In Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services(MobileHCI ’18). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3229434.3229463
[27]
Jan C Panero, David M Lane, and H Albert Napier. 1997. PART I: The Computer use Scale: Four Dimensions of how People use Computers. Journal of Educational Computing Research 16, 4 (1997), 297–315.
[28]
Paula M Popovich, Karen R Hyde, Todd Zakrajsek, and Catherine Blumer. 1987. The development of the attitudes toward computer usage scale. Educational and psychological measurement 47, 1 (1987), 261–269.
[29]
John Rooksby, Parvin Asadzadeh, Mattias Rost, Alistair Morrison, and Matthew Chalmers. 2016. Personal Tracking of Screen Time on Digital Devices. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems(CHI ’16). Association for Computing Machinery, New York, NY, USA, 284–296. https://doi.org/10.1145/2858036.2858055
[30]
Noha Soliman Elserty, Nesma Ahmed Helmy, and Khaled Mohmed Mounir. 2020. Smartphone addiction and its relation to musculoskeletal pain in Egyptian physical therapy students. European Journal of Physiotherapy 22, 2 (2020), 70–78.
[31]
Aaseer Thamby Sam Subramani Parasuraman, Stephanie Wong Kah Yee, Bobby Lau Chik Chuon, and Lee Yu Ren. 2017. Smartphone usage and increased risk of mobile phone addiction: A concurrent study. International journal of pharmaceutical investigation 7, 3(2017), 125.
[32]
Yunlong Wang and Harald Reiterer. 2019. The Point-of-Choice Prompt or the Always-On Progress Bar? A Pilot Study of Reminders for Prolonged Sedentary Behavior Change. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems(CHI EA ’19). Association for Computing Machinery, New York, NY, USA, 1–6. https://doi.org/10.1145/3290607.3313050
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May 2021
228 pages
ISBN:9781450382038
DOI:10.1145/3429360
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Published: 07 September 2021
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View all- Jiang JLi SLi XXu YZhao JAn P(2024)BIG-AOME: Designing Bodily Interaction Gamification towards Anti-sedentary Online Meeting Environments (Preprint)JMIR Serious Games10.2196/62778Online publication date: 31-May-2024
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