Modeling the Engagement-Disengagement Cycle of Compulsive Phone Use

Tran, Jonathan; Yang, Katie; Davis, Katie; Hiniker, Alexis

doi:10.1145/3290605.3300542

Cited by 60 publications

(22 citation statements)

References 50 publications

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“…Hiniker et al [19] corroborated that phone use behaviors show distinct patterns between instrumental and ritualistic use of smartphones. Tran et al [49] constructed a descriptive model of the cycle of compulsive checking and identified triggers that start and end compulsive phone use. They discovered that the experience of compulsive phone checking depends on the meaningfulness of the experience, which is mostly determined by informational or social rewards.…”

Section: Understanding Smartphone Use Behaviorsmentioning

confidence: 99%

“…It is important to note that some design components of the current social media apps are designed to encourage users to make impulsive choices, making it harder to self-regulate regretful uses, corresponding to the "dark patterns" [10,49,50]. One pattern we observed is placing attractive system recommended features in the middle of paths that a user must pass by (e.g., YouTube's Future designs for digital wellbeing should consider how to mitigate the inclination to impulsive choices and increase awareness of larger, later rewards through design for better self-regulation.…”

Section: Why People Repeat Regretful Use: Delay Discount and Impulsiv...mentioning

confidence: 99%

“…Designing an effective intervention against smartphone use that users regret calls for more nuanced analyses of which parts of use users want to gain information about and refrain from, based on the understanding of how phone use experiences vary inside an app. Previous analyses on smartphone use examine various behavior aspects, such as compulsive use [49], habitual use [41], and meaningful use [37]. However, as each work focuses on a specific behavior of phone use, it lacks a comprehensive understanding of which parts of phone or app use the users are satisfied with and which they want to improve.…”

Section: Introductionmentioning

confidence: 99%

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Reflect, not Regret: Understanding Regretful Smartphone Use with App Feature-Level Analysis

Cho

Choi

Kim

et al. 2021

Proc. ACM Hum.-Comput. Interact.

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Digital intervention tools against problematic smartphone usage help users control their consumption on smartphones, for example, by setting a time limit on an app. However, today's social media apps offer a mix of quasiessential and addictive features in an app (e.g., Instagram has following feeds, recommended feeds, stories, and direct messaging features), which makes it hard to apply a uniform logic for all uses of an app without a nuanced understanding of feature-level usage behaviors. We study when and why people regret using different features of social media apps on smartphones. We examine regretful feature uses in four smartphone social media apps (Facebook, Instagram, YouTube, and KakaoTalk) by utilizing feature usage logs, ESM surveys on regretful use collected for a week, and retrospective interviews from 29 Android users. In determining whether a feature use is regretful, users considered different types of rewards they obtained from using a certain feature (i.e., social, informational, personal interests, and entertainment) as well as alternative rewards they could have gained had they not used the smartphone (e.g., productivity). Depending on the types of rewards and the way rewards are presented to users, probabilities to regret vary across features of the same app. We highlight three patterns of features with different characteristics that lead to regretful use. First, "following"-based features (e.g., Facebook's News Feed and Instagram's Following Posts and Stories) induce habitual checking and quickly deplete rewards from app use. Second, recommendation-based features situated close to actively used features (e.g., Instagram's Suggested Posts adjacent to Search) cause habitual feature tour and sidetracking from the original intention of app use. Third, recommendation-based features with bite-sized contents (e.g., Facebook's Watch Videos) induce using "just a bit more," making people fall into prolonged use. We discuss implications of our findings for how social media apps and intervention tools can be designed to reduce regretful use and how feature-level usage information can strengthen self-reflection and behavior changes.

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Section: Understanding Smartphone Use Behaviorsmentioning

confidence: 99%

Section: Why People Repeat Regretful Use: Delay Discount and Impulsiv...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reflect, not Regret: Understanding Regretful Smartphone Use with App Feature-Level Analysis

Cho

Choi

Kim

et al. 2021

Proc. ACM Hum.-Comput. Interact.

View full text Add to dashboard Cite

show abstract

“…Harmon and Mazmanian [42] suggest that many smartphone users find themselves in a perpetual state of tension, where they want to use their phones in a manner different than they currently do. Tran et al [75] investigate the related phenomenon of compulsive phone use, which is usually both begun and ended by external triggers rather than by a user's willful intentions. Baumer et al [9] also suggest sense of agency, łdefined as an individual's perception that their actions are under their own controlž [9, p. 2], as a central construct that can be used to organize and understand the disparate motivations that both users and non-users cite for their technology practices.…”

Section: Related Work 21 Volitionality and Technology Non/usementioning

confidence: 99%

“…Some work argues that social media, such as Facebook, should be seen as potentially addictive [2,37,43], though others question the utility or validity of this notion for understanding people's use of a communication technology [20,65]. Other work notes the automatic or compulsive nature with which some people use social technologies, as well as the lengths to which they go to curtail that use [56,64,75]. Prior work has also highlighted systematic barriers that can prevent those who want to use social media from doing so [70, 81ś83].…”

Section: Introductionmentioning

confidence: 99%

Who has a Choice?: Survey-Based Predictors of Volitionality in Facebook Use and Non-use

Skeba

Saxena

Lee

et al. 2021

Proc. ACM Hum.-Comput. Interact.

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This paper examines volitionality of Facebook usage, that is, which individuals feel they have a choice about whether or not to use the site. It analyzes data from two large surveys, conducted three years apart. Across the two surveys, a variety of factors impacted whether or not respondents saw their Facebook usage as a matter of their own choice, such as engaging in non-use behaviors, measures of Facebook addiction, a sense of their own agency, and, across both studies, level of education. These results expand on prior literature around technology use and non-use, especially in terms of which populations may feel obligated to use, or be unwillingly prevented from using, social media such as Facebook. Furthermore, they provide potential implications both for future work and for technology policy.

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Motives for digital social multitasking (DSMT) and problematic phone use among adolescents

Yang

Ariati

Pham

et al. 2023

Journal of Adolescence

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Introduction: Phone use during face-to-face interactions (i.e., digital social multitasking [DSMT]) is a growing activity among adolescents. DSMT appears to be a risk factor for problematic phone use, but little is known about why adolescents engage in DSMT and how different motives of DSMT would be associated with problematic phone use. Drawing on the framework of DSMT and the uses and gratifications theory, this study explored (1) the motives of adolescent DSMT and (2) the direct and indirect relationships between DSMT motives and problematic phone use via the level and perception of DSMT. Method: The study involved survey data from 517 adolescents in the United States recruited through the Qualtrics panels (M age = 14.83, SD = 1.93) in the fall of 2020. The sample's gender and racial/ethnic distributions were nationally representative. Results: We developed a scale measuring adolescent DSMT motives, which showed that adolescents engaged in DSMT because of enjoyment and connection, boredom, information, and habitual use. The motive of habitual use was associated with problematic phone use both directly and indirectly via level of DSMT and perceived distraction caused by DSMT. The information motive was directly associated with problematic phone use, while the boredom motive was indirectly associated with problematic phone use via perceived distraction. Conversely, the motive of enjoyment and connection was related to lower problematic phone use both directly and indirectly via lower perceived distraction. Conclusion:The study identifies DSMT-related risk and protective factors for problematic phone use. The findings should help adults recognize adaptive versus maladaptive forms of DSMT among adolescents and develop proper guidance and intervention.

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Modeling the Engagement-Disengagement Cycle of Compulsive Phone Use

Cited by 60 publications

References 50 publications

Reflect, not Regret: Understanding Regretful Smartphone Use with App Feature-Level Analysis

Reflect, not Regret: Understanding Regretful Smartphone Use with App Feature-Level Analysis

Who has a Choice?: Survey-Based Predictors of Volitionality in Facebook Use and Non-use

Motives for digital social multitasking (DSMT) and problematic phone use among adolescents

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