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Designing for Digital Detox: Making Social Media Less Addictive with Digital Nudges


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Social media addiction concerns have increased steadily over the past decade. Digital nudges have previously been shown to hold enormous potential to change behavior. However, it is not clear how they might be designed to combat social media addiction. In this late-breaking work, we aim at clarifying this issue by investigating how digital nudges can reduce the addictive features of social media and other addictive sites. More precisely, we present the design of NUDGE, a novel browser extension that aims to make social media less addictive by delivering digital nudges founded on behavioral science. We conducted a preliminary evaluation of NUDGE with 67 actual users and 14 university students. Our results show that NUDGE (1) helped users to become reflective of their social media usage , (2) possibly decreased their time spent, and (3) made the experience more pleasant.
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Designing for Digital Detox: Making
Social Media Less Addictive with
Digital Nudges
Aditya Kumar Purohit
University of Neuchâtel
Neuchâtel, Switzerland
Louis Barclay
Johannesburg, South Africa
Adrian Holzer
University of Neuchâtel
Neuchâtel, Switzerland
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CHI ’20 Extended Abstracts, April 25–30, 2020, Honolulu, HI, USA.
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ACM ISBN 978-1-4503-6819-3/20/04.
Social media addiction concerns have increased steadily
over the past decade. Digital nudges have previously been
shown to hold enormous potential to change behavior.
However, it is not clear how they might be designed to
combat social media addiction. In this late-breaking work,
we aim at clarifying this issue by investigating how digital
nudges can reduce the addictive features of social me-
dia and other addictive sites. More precisely, we present
the design of NUDGE, a novel browser extension that aims
to make social media less addictive by delivering digital
nudges founded on behavioral science. We conducted a
preliminary evaluation of NUDGE with 67 actual users and
14 university students. Our results show that NUDGE (1)
helped users to become reflective of their social media us-
age, (2) possibly decreased their time spent, and (3) made
the experience more pleasant.
Author Keywords
Digital nudge; Social media addiction; Digital wellbeing;
Digital Detox; Digital Addiction
CCS Concepts
Human-centered computing User studies; Social
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Our dependence on technology is on the rise, and as a
consequence, an estimated 210 million people are suffering
from social media addiction worldwide [20]. This condition
makes individuals overly concerned about, and increasingly
dependent on, online social networks (OSN) [3]. Social me-
dia were designed as web-based technologies built to facil-
itate messaging and sharing of content between people [6].
At the same time, many social media companies, including
Facebook, Twitter, and YouTube, rely on the continued at-
tention of users for their revenue generation [19], in what
is sometimes called the attention economy [9]. As a result,
these technologies are now designed to be intrinsically per-
suasive [1] to attract people’s attention [8]. This has conse-
quences such as impairing interpersonal relationships [16],
and/or psychological health and well-being [30].
Figure 1: Hook model adapted
from Eyal [11]
In this paper, we argue that the same design principles that
create addiction could be leveraged to mitigate it. More
specifically, digital nudges, i.e. design features that steer
people’s decisions without banishing freedom of choice, can
be used in welfare-promoting directions [25]. We present
specific digital nudges that can be used by designers to
mitigate the addictive features of social media. Further,
we present the implementation of these nudges in a novel
Chrome extension called NUDGE. Finally, we present a pre-
liminary evaluation of NUDGE with 67 actual users and 14
students who assessed its usability and effectiveness.
This research project follows the steps of the design sci-
ence research methodology (DSRM) [24]. The paper first
identifies the problem (Introduction). Second, it presents the
objectives of a solution by describing the addictive model
used in social media (Hooked on Social Media). Third, it
presents the design of a solution and a real word demon-
strator (i.e., NUDGE) before providing a preliminary evalua-
tion. Finally, it concludes and presents future work.
Hooked on Social Media
The design of social media platforms is intentionally en-
gineered to be addictive and exploit vulnerabilities in hu-
man psychology [1]. This intentional design results in un-
desirable platform usage that can lead to addictive usage
patterns [22]. One model that many companies adopt for
the development of habit-forming social media products
is the Hook model [11]. This model draws on behaviorist
principles to build habits [26]. It describes a four-phase it-
erative process for software design that encourages habit
formation. The process starts with (1) a trigger that leads
to (2) an action, which produces (3) a reward and ultimately
creates (4) an investment. Successfully utilizing these four
phases produces an addictive feedback loop where the
more users receive rewards and invest, the more they will
be incentivized to respond to triggers and perform actions,
which in turn will produce more rewards and investments
and so on (see Figure 1).
A trigger operates as a foundation on which habits are
formed. Internal triggers hinge on thoughts and emotions
like boredom, pre-existing routines, and loneliness, prompt-
ing the user to take mindless actions. External triggers
could be, for instance, notifications indicating the arrival of a
new message in the user’s environment. A trigger prompts
an individual to take action by supplying cues.
The action phase is based on the Fogg behavior model [12].
When sufficient ability and motivation exist with a trigger, an
action occurs. Actions in social media are typically brows-
ing, posting, commenting, or reacting. Social media plat-
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forms increase the ability of users to take actions by making
actions more accessible. For instance, YouTube presents
personalized recommendations on the right side of its web-
site, reducing the burden to search for similar videos. The
motivation to seek pleasure, social acceptance, and to
avoid pain and social rejection increase the chance that
the user will take action.
Figure 2: Potential digital nudges
to combat the design context of the
Hook Model
Giving users rewards after they have taken action brings
them to social media platforms over and over again. Re-
wards can be of three types [11]: the ‘tribe’, the ‘hunt’, and
the ‘self’. The rewards of the tribe are social rewards such
as comments and likes. The rewards of the hunt are the
consumption of new content, for instance, on the endless
News Feed on Facebook. The rewards of the self are in-
trinsic rewards of mastery, competence, and completion,
for instance, on platforms like LinkedIn completion of profile
increases visibility to recruiters.
Investment increases the likelihood of users returning to
social media platforms as they have invested value in the
form of content, data, followers, and reputation [11]. The
investment on the platform increases the possibility of users
responding to the next trigger to start the cycle once again.
The objectives of a solution to address the social media ad-
diction problem should address these four phases in order
to break users free from the vicious cycle.
Designing for Digital Detox
Hereafter, we illustrate, with scenarios, how designers could
leverage digital nudges to counteract the various phases
of the Hook model. Figure 2 provides an overview of the
different digital detox nudges.
Dismissing Triggers
Imagine a user called Thomas. Like many other mobile
phone users, he receives around 100 notifications from
social media per day (external triggers), indicating a new
message is received. Also, every so often, Thomas visits
his favorite social media platform almost unconsciously out
of boredom (internal triggers). The following two nudges
could work on dismissing these triggers and thus preventing
users from accessing social media in the first place:
Hiding Nudge: Hiding nudge operates by obscuring
a trigger so that it becomes harder to respond to [7].
After Thomas enters the social media platform, notifi-
cations within the platform can be hidden so that they
fail to trigger an action.
Default Nudge: Default options are very powerful,
as it takes effort to deviate from the default environ-
ment set by some intervention [28, 14, 10]. Typical
examples are opt-out rather than opt-in approaches.
In our context, social media platforms could be turned
off by default, i.e., Thomas is not taken directly to
Facebook, but to another page by default where he is
asked if he is sure he would like to visit Facebook, in
which case he has to switch Facebook on mindfully.
Limiting User Action
After Thomas enters the social media platform, algorithms
supply personalized content. The tailored content increases
the opportunity of action on the platform; thus, Thomas
ends up looking at linked content that he was not interested
in the first place, but was conveniently accessible. The fol-
lowing nudge could limit his action on social media:
Creating Friction: In the course of interaction with
technology, frictions hinder people from painlessly
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achieving their goals [21]. Usually, systems are de-
signed to lower friction. However, in our context, fric-
tion creates an opportunity for the user to interact
mindfully. Frictions could be introduced by asking if
Thomas wants to see video or post recommendations
in the sidebar of social media; thus, making it harder
for Thomas to click on other content mindlessly.
Figure 3: (1) Notifications on
Facebook (2) Hiding nudge hides
notifications on Facebook
Figure 4: (1) Sidebar on YouTube
with personalized content (2)
Sidebar on YouTube with Friction
nudge to confirm actions
Figure 5: Default nudge in NUDGE
switching off
Reducing Reward
Once Thomas is online, the infinite scrolling offered by
websites as well as the likes of his posts produce rewards
to make him stay longer on the site. In addition to hiding
nudge that can also be used to reduce the impact of likes
and comments from others, the two following nudges can
reduce the rewards of staying on the site:
Pause-reminders: Pause-reminders break users free
from addictive continuous scrolling [2] by creating an
interface that reduces hunt rewards. In this case, the
pause-reminder makes Thomas aware of his mind-
less scrolling.
Feedback nudge: Feedback about time spent on an
app combined with negative reinforcement could re-
duce the rewards of users from staying on social me-
dia [23]. Given the scenario, Thomas could be pre-
sented with a timer that shows how much time he has
already spent on social media.
Reduce Investment
Thomas has invested in his favorite social media in the form
of following various pages and friends which keeps bringing
him back on the social media platform. The following nudge
could reduce that investment:
Unfollow nudge: According to the Fogg behavior
model [12], with increased ability, sufficient motiva-
tion, and a trigger, an action occurs. Presently on
social media platforms, unfollowing friends, groups,
and pages is a strenuous task. Alternatively, Thomas
could be presented with a prompt that makes unfol-
lowing friends, groups, and pages automized.
In this section, we present a demonstration of the nudges
described above in a tool for digital detox called NUDGE.
Technically NUDGE is a Chrome extension written in JavaScript
that provides an overlay on certain predefined websites. It
uses custom JavaScript code and CSS with injected HTML
to create this overlay. NUDGE currently has 1,200 weekly
active users.
The hiding nudge in NUDGE hides notifications to counter
triggers (See Figure 3). NUDGE creates friction by conceal-
ing certain sections of websites that keep the users sucked
in longer than they want. For instance, sections such as
sidebars displaying personalized recommendations on
YouTube, and sponsored ads and links on Facebook. If the
user desires to see these sections, they have to hover over
the NUDGE logo and decide to choose either ‘Show once’ or
‘Show always.’ (See Figure 4).
The default nudge intervention in NUDGE switches off so-
cial media websites, which means that when users enter
the URL of Facebook, for instance, they are not taken di-
rectly to Facebook, but to another page that requires them
to drag a slider across the screen in order to proceed to
Facebook. The slider gets stickier to drag with every visit.
In other words, increasing your visits to a particular web-
site will make the slider harder to drag, thus also adding a
friction component to the default nudge (See Figure 5).
The pause-reminder nudge disrupts mindless infinite scrolling
to keep users away from rewards of the hunt on social me-
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dia (See Figure 6). NUDGE reduces the reward further by
presenting a feedback nudge that overlays on the user in-
terface. The feedback nudge grows on the screen every
five minutes a user spends on a social media site. It does
not stop a user from taking action, but keeps the user more
aware of the time they are spending (See Figure 7).
Figure 6: Pause-reminder Nudge
Figure 7: (1) Feedback nudge in
NUDGE (2) Feedback nudge
growing on screen every five
minutes a user spends on
Figure 8: Unfollow Nudge
Finally, to undermine investment, an unfollow nudge is
available. It allows a user to unfollow 100% of their friends,
pages, and groups, and permanently get rid of their clut-
tered News Feed. Once a user has enabled the feature,
with the assistance of the ‘auto-unfollow’ feature, unfollow-
ing happens automatically (See Figure 8).
We conducted a preliminary evaluation of NUDGE with uni-
versity students and with actual users. A survey was pushed
on the Facebook platform for actual users to provide their
feedback. In two weeks, we received 67 responses, which
is a 24.8% response rate out of 270 active users of Face-
book out of the 1,200 NUDGE active users. For the students,
we introduced NUDGE to first-year business students (about
51 students) at the University of Neuchâtel, Switzerland. 14
students agreed to be a part of the evaluation.
The students were instructed to install NUDGE on the Chrome
browser and given two days to test it. Then the students
were asked to fill out the SUS [5] and AttrakDiff 2 [17] ques-
tionnaire to assess usability. The ability to generate reliable
results even with small sample sizes makes SUS valuable
[29]. The goal of the survey with students and actual users
was to make a preliminary assessment of (1) usability (2)
effectiveness and (3) design.
Is NUDGE usable and effective?
On the SUS scale for general usability, NUDGE achieved
a mean score of 79.8, which indicates between Good and
Excellent usability [5]. We used the short version of the
AttrakDiff 2 survey to evaluate the hedonic and pragmatic
qualities of NUDGE. The results are presented in Figure 9.
The results show mostly positive attractive (ATT), hedo-
nic (HQ), and pragmatic (PG) measures. The extension is
viewed as neither cheap nor premium.
To assess if users believed NUDGE reduced their Facebook
usage and at the same time made Facebook more enjoy-
able, we have assessed two items (1) “NUDGE reduces
time spent on Facebook” and (2) “NUDGE makes Facebook
more enjoyable” on a Likert scale from ‘Strongly disagree’
to ‘Strongly agree’ from actual users. 67 actual users re-
sponded to the items. We applied a one-sample Wilcoxon
signed-rank test to both the items that indicated the median
for the first item was significantly different from 3, Z= 6.35,
p< .001, with a strong effect size (r = .78). It can be seen
in Figure 10 that 59.7% of the users think NUDGE reduces
their Facebook usage. The median for the second item was
significantly different from 3, Z= 3.48, p< 0.01, with a mod-
erate effect size (r = .43). We can observe in Figure 10 that
22.4% users agree and 35.8% strongly agree that NUDGE
makes Facebook more enjoyable.
We were also interested in collecting diverse perspectives
about the efficacy and experiences of NUDGE. The actual
users were presented with two open questions: 1) What
is the best thing about NUDGE? And 2) What is the worst
thing about NUDGE? 65 actual users provided open-ended
comments. The analysis was completed using grounded
theory [27]. By coding the data through line-by-line, we
articulated emergent themes. Here we discuss the major
One theme that emerged was the various ways in which
users relished NUDGE. Automatic unclutter, automates, and
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auto-unfollow were recurring codes from the users. As an
example, the following comment was coded as automates:
“Simple one-click automatization that really completes the
task of deleting my facebook feed.Another comment that
was coded as auto-unfollow: “I didn’t have to select one
by one all the friends or pages I didn’t want to follow any-
more.While users reported how much they valued the au-
tomatic unfollow feature, for some users automatic unfollow
evoked a sense of loss. For example, “Deleting my feed
was a drastic choice, but it’s cut my time there like tenfold.
Figure 9: AttrakDiff 2 results
highlighting median values. N= 14
Figure 10: Survey results N = 67.
Another interesting theme was whether digital nudge in-
terventions of NUDGE made users mindful of their actions.
One user saw the interventions as an incentive to remain
mindful. For example, " It acts as an incentive to be mindful
of my web use." A code that kept occurring was rationaliz-
ing; a user reported: "The notification that shows how many
pages you’ve scrolled. It is really excellent and works every
time to make me stop mindlessly scrolling." Another user
commented: "having to slide the bar across. It creates an
opportunity for mindfulness that I didn’t have before. It’s a
pain when I have to be on social media a lot in one day for
work, but the tradeoff is worth it because every time I have
to decide: Do I need to be here?."
Privacy Threat
One common area of concern for the users was that of pri-
vacy. In particular, some users found themselves to be feel-
ing as if they are losing control of their data. For instance,
one user reported, "I felt as if I took a risk in relation to my
FB-data, by giving over some control to Nudge." In some
cases, users developed skepticism " I did feel skeptical
about letting a relative alien add-on interfere with my face-
book." One user stated, " Not sure about the privacy thing."
Several users asked for greater possibility of customization.
Codes like customizing, personalizing, and customizability
were recurrent. For instance, one user reported, " I wish
there could be some kind of middle ground. Like a feed with
only my best friends and favorite pages? And no sponsored
content?". Another user reported on customizing rainbow
timer, "Maybe there should be an option for how much time
it takes to add each ring to make it faster? Or an option to
slightly adjust the color of the rings?".
Conclusion and Future Work
In this paper, we introduced and evaluated NUDGE, a Chrome
extension designed to counter the cycle of addictive design
contexts employed by social media platforms. These pre-
liminary results show how system designers can design and
channel digital nudges to combat social media addiction. It
is relevant to note that NUDGE utilizes a counter-intuitive de-
sign approach to decrease the usability of social media plat-
forms. Users appreciated NUDGE and believed that NUDGE
reduced their Facebook usage and, at the same time, made
Facebook more enjoyable. Future research could build on
previous work on unorthodox usability (e.g., [13, 4, 15, 18])
and investigate how reducing social media usability could
improve the user experience. The design evaluation of
NUDGE and its shortcomings presented in this paper will al-
low designers to build effective, likable, and practical digital
detox apps. In the future, we aim to grasp a more in-depth
understanding of the described nudges individually by con-
ducting RCTs with a combination of usage log data and
survey results. Furthermore, we will deeply investigate the
concerns of privacy, sadness following a loss of investment,
and bringing the ability to customize digital nudges.
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[1] A. Alutaybi, E. Arden-Close, J. McAlaney, A.
Stefanidis, K. Phalp, and R. Ali. 2019. How Can Social
Networks Design Trigger Fear of Missing Out?. In
2019 IEEE International Conference on Systems, Man
and Cybernetics (SMC). 3758–3765. DOI:
[2] Emelie Andersson. 2019. Pause-reminders in mobile
[3] Cecilie Schou Andreassen. 2015. Online social
network site addiction: A comprehensive review.
Current Addiction Reports 2, 2 (2015), 175–184.
[4] Paul M. Aoki and Allison Woodruff. 2005. Making
Space for Stories: Ambiguity in the Design of Personal
Communication Systems. In CHI’05. 181–190.
[5] Aaron Bangor, Philip T. Kortum, and James T. Miller.
2008. An Empirical Evaluation of the System Usability
Scale. International Journal of Human–Computer
Interaction 24, 6 (2008), 574–594. DOI:
[6] Jaclyn Cabral. 2008. Is generation Y addicted to social
media. Future of children 18 (2008), 125.
[7] Ana Caraban, Evangelos Karapanos, Daniel
Gonçalves, and Pedro Campos. 2019. 23 Ways to
Nudge: A Review of Technology-Mediated Nudging in
Human-Computer Interaction. In Proceedings of the
2019 CHI Conference on Human Factors in Computing
Systems. ACM, 503.
[8] Marta E. Cecchinato, John Rooksby, Alexis Hiniker,
Sean Munson, Kai Lukoff, Luigina Ciolfi, Anja Thieme,
and Daniel Harrison. 2019. Designing for Digital
Wellbeing: A Research & Practice Agenda. In
Extended Abstracts of the 2019 CHI Conference on
Human Factors in Computing Systems (CHI EA ’19).
ACM, New York, NY, USA, Article W17, 8 pages. DOI:
[9] Thomas H Davenport and John C Beck. 2001. The
attention economy: Understanding the new currency of
business. Harvard Business Press.
[10] Isaac Dinner, Eric J. Johnson, Daniel G. Goldstein,
and Kaiya Liu. 2011. Partitioning default effects: Why
people choose not to choose. Journal of Experimental
Psychology: Applied 17, 4 (dec 2011), 332–341. DOI:
[11] Nir Eyal. 2014. Hooked: How to build habit-forming
products. Penguin UK.
[12] Brian J Fogg. 2009. A behavior model for persuasive
design. In Proceedings of the 4th international
Conference on Persuasive Technology. ACM, 40.
[13] William W Gaver, Jacob Beaver, and Steve Benford.
2003. Ambiguity as a resource for design. In ACM
CHI’03. 233–240.
[14] Claus Ghesla, Manuel Grieder, and Jan Schmitz.
2019. Nudge for Good? Choice Defaults and Spillover
Effects. Frontiers in Psychology 10 (2019), 178. DOI:
[15] Dimitris Grammenos. 2014. Abba-dabba-ooga-booga-
hoojee-goojee-yabba-dabba-doo: stupidity, ignorance
& nonsense as tools for nurturing creative thinking. In
CHI’14 EA.
CHI 2020 Late-Breaking Work
CHI 2020, April 25–30, 2020, Honolulu, HI, USA
LBW126, Page 7
[16] Eduardo Guedes, Antonio Egidio Nardi, Flávia Melo
Campos Leite GuimarÃ, Sergio Machado, and Anna
Lucia Spear King. 2016. Social networking, a new
online addiction: a review of Facebook and other
addiction disorders. MedicalExpress 3 (02 2016).
[17] Marc Hassenzahl, Michael Burmester, and Franz
Koller. 2003. AttrakDiff: Ein Fragebogen zur Messung
wahrgenommener hedonischer und pragmatischer
Qualität. Vieweg+Teubner Verlag, Wiesbaden,
187–196. DOI: 9_19
[18] Adrian Holzer, Andrii Vozniuk, Sten Govaerts, Harry
Bloch, Angelo Benedetto, and Denis Gillet. 2015.
Uncomfortable Yet Fun Messaging with Chachachat.
In Proceedings of the 2015 Annual Symposium on
Computer-Human Interaction in Play (CHI PLAY ’15).
ACM, New York, NY, USA, 547–552. DOI:
[19] Logan Kugler. 2018. Getting Hooked on Tech.
Commun. ACM 61, 6 (May 2018), 18–19. DOI:
[20] Phil Longstreet and Stoney Brooks. 2017. Life
satisfaction: A key to managing internet & social media
addiction. Technology in Society 50 (2017), 73–77.
[21] Thomas Mejtoft, Sarah Hale, and Ulrik Söderström.
2019. Design Friction. In Proceedings of the 31st
European Conference on Cognitive Ergonomics
(ECCE 2019). Association for Computing Machinery,
New York, NY, USA, 41–44. DOI:
[22] Christian Montag, Zhiying Zhao, Cornelia Sindermann,
Lei Xu, Meina Fu, Jialin Li, Xiaoxiao Zheng, Keshuang
Li, Keith M Kendrick, Jing Dai, and Benjamin Becker.
2018. Internet Communication Disorder and the
structure of the human brain: initial insights on
WeChat addiction. Scientific Reports 8, 1 (2018),
2155. DOI:
[23] 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). ACM, New York, NY, USA,
Article 4, 12 pages. DOI:
[24] Ken Peffers, Tuure Tuunanen, Marcus A Rothenberger,
and Samir Chatterjee. 2007. A design science
research methodology for information systems
research. Journal of management information systems
24, 3 (2007), 45–77.
[25] Aditya Kumar Purohit and Adrian Holzer. 2019.
Functional Digital Nudges: Identifying Optimal Timing
for Effective Behavior Change. In Extended Abstracts
of the 2019 CHI Conference on Human Factors in
Computing Systems (CHI EA ’19). ACM, New York,
NY, USA, Article LBW0147, 6 pages. DOI:
[26] Nick Seaver. 2018. Captivating algorithms:
Recommender systems as traps. Journal of Material
Culture (2018), 1359183518820366.
[27] Anselm Strauss and Juliet Corbin. 1994. Grounded
theory methodology. Handbook of qualitative research
17 (1994), 273–85.
CHI 2020 Late-Breaking Work
CHI 2020, April 25–30, 2020, Honolulu, HI, USA
LBW126, Page 8
[28] Richard H Thaler and Cass R Sunstein. 2009. Nudge:
Improving decisions about health, wealth, and
happiness. Penguin.
[29] Thomas S Tullis and Jacqueline N Stetson. 2004. A
comparison of questionnaires for assessing website
usability. In Usability professional association
conference, Vol. 1. Minneapolis, USA.
[30] Patti M Valkenburg, Jochen Peter, and Alexander P
Schouten. 2006. Friend networking sites and their
relationship to adolescents’ well-being and social
self-esteem. CyberPsychology & Behavior 9, 5 (2006),
CHI 2020 Late-Breaking Work
CHI 2020, April 25–30, 2020, Honolulu, HI, USA
LBW126, Page 9
... Designers could address the issue from the user's perspective and use ML to detect when a user is becoming addicted and eventually reinforce non-addictive behaviours. For example, recent research has proven the effectiveness of nudges introduced when users start showing symptoms of digital addiction (Okeke et al., 2018;Purohit, Barclay & Holzer, 2020;Tiersen & Calvo, 2021). ...
... In fact, digital experiences purposely built to be 'non-addictive' have already started to appear. Some of them rely on the creation of less addictive and more mindful interactions through the addition of nudges or design friction (Okeke et al., 2018;Purohit, Barclay & Holzer, 2020). A further development of this research could investigate how more ethical (hence "non-addictive") experiences could generate positive interest not only for their end users, but also for decision makers of tech companies. ...
Conference Paper
Full-text available
Due to the novel design paradigm brought about by artificial intelligence (AI), addictive technology is becoming more common and harder to resist. In order to counterbalance the rise of technological addiction, an effort should be made by all the actors involved in the complex world of addictive digital experiences. This paper focuses on the role of designers. It is based on a literature review on addiction to digital experiences based on the evolution of human–machine interactions, highlighting challenges brought by AI within the emerging “more-than-human” perspective. The introduction of a systemic perspective that considers new meeting points between datasets and algorithms can help designers understand how their products can lead to addiction and how addiction is created in the context of “AI factories”. By reinforcing their ethical approach and treating AI as a design material, UX designers can become the bearers of a more responsible mindset and re-humanize addictive technology.
... In terms of SM design, the findings reported here suggest that platforms should be designed to support more conscious, reflective use and minimise automatic, impulsive use. For example, SM platforms could include optional friction and mindful-inducing prompts to support disengagement [19,47,64]. Platforms could also allow users greater active control over the valence of content exposed during breaks, e.g., allowing users to notify dyads of their openness to negative content, and options to filter feeds based on content valence. ...
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... Conversely, attempts to correct addictive behavior using digital therapeutics are also increasing. According to research on digital nudges for reducing social media addiction, digital nudges are intended to help individuals gain a more objective view of their social media use, control their usage time, and have a more pleasant experience [70]. Additionally, with the current surge in behavioral therapy attempts via smartphone apps, the usage of smartphones as a treatment tool is demonstrating promise [71]. ...
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Addiction in adolescence is increasing and has a significant impact on physical and mental health. Notably, addictions can be comorbid and affect each other. Despite the recent growing interest in food addiction (FA) and problematic smartphone use (PSU), few studies have investigated their association in adolescents. We investigated the relationship between FA and PSU in adolescents and the effects of eating behaviors. A total of 209 adolescents (44.5% male; mean age = 12.86 ± 0.7 years) participated in the current school-based community study. We found a positive correlation between the dimensional Yale Food Addiction Scale for Children 2.0 (dYFAS-C2.0) and the Smartphone Overdependence Scale after adjusting for age, sex, body mass index, and socioeconomic status. The high-risk PSU group accounted for 17.2% of participants. Furthermore, this group showed 2.3 times higher dYFAS-C2.0 scores than the general group. Emotional overeating and satiety responsiveness were correlated with PSU. A comprehensive evaluation of addiction symptoms is needed for proper intervention, especially in adolescents with symptoms of abnormal eating behaviors.
... Syvertsen et al. (2020) also warn of the loss of sense of space and the disturbance of the perception of time. The online connection, more specifically the connection to the social networks, can also lead to the distortion of the image itself in a negative way, a consequence of the constant comparison with others, and then, excessive use is also associated with problems of users' self-esteem (Purohit, Barclay & Holzer, 2020). Furthermore, the continued use of social networks contributes to the phenomenon of FOMO (Fear of Missing Out), which consists of the constant concern of not being present, while others are experiencing rewarding and pleasant experiences, shared online (Formica, 2015). ...
The chapter aims to demonstrate the growing importance of the concept of 'digital detox' as a segment of the tourism market to indicate the reasons and factors that encourage its demand, the diversity of establishments, the strategies employed by them, the limits, facilitating the adaptation to market conditions , and assisting in the development of marketing strategies that respond to customer needs. Through a content analysis of some research papers from the last 10 years and websites, as well as an interview with the founder from one of the establishments specialized in "disconnection with technologies" experiences , the "Offline House," this study presents inputs on marketing (digital), tourism (niches), and consumer behavior.
... As mentioned above, booster sessions, or further integration of the content into existing curriculums might achieve this. Further, it could be fruitful to pair educational-style interventions with technology-based interruptions such that youth are further nudged when using social media [77]. Finally, considering how to incorporate perceptions of peer norms into the intervention to decrease potential concerns regarding the negative impacts on social relationships of implementing the strategies included in the intervention may be useful [78]. ...
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Although the negative effect of social media use among youth on body image and eating concerns has been established, few classroom-based resources that can decrease these effects through targeting social media literacy skills have been developed. This study aimed to test the efficacy of SoMe, a social media literacy body image, dieting, and wellbeing program for adolescents , through a cluster randomized controlled trial. Participants (n = 892; Mage = 12.77, SD = 0.74; range 11-15; 49.5% male) were randomized by school (n = 8) to receive either weekly SoMe (n = 483) or control sessions (lessons as usual; n = 409) over 4 weeks in their classroom. Participants completed surveys at four timepoints (baseline, 1-week post-intervention, and 6-and 12-month follow-up) assessing body dissatisfaction, dietary restraint, strategies to increase muscles (primary outcomes), self-esteem and depressive symptoms (secondary outcomes), and internalization of appearance ideals and appearance comparison (exploratory outcomes). Modest positive intervention effects were found in dietary restraint and depressive symptoms at 6-month follow-up in girls but few positive effects emerged for boys. The findings provide only preliminary support for a social media literacy intervention, but suggest the usefulness of both identifying those who benefit most from a universally delivered intervention and the need to refine the intervention to maximize intervention effects.
... While social media has enhanced information dissemination [42], several challenges are associated with social media. Examples of these challenges are online toxicity, hate speech, fake news, and general negativity [8,24,33,35,43]. Some users might, for example, want to turn off news about COVID-19, as this content may cause anxiety to them or block political content during elections. ...
Conference Paper
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Controlling the quality of social media feeds poses an issue for many users. Platforms such as Twitter give users some options to influence their feeds. Still, the selection of content predominantly relies on implicit rather than explicit user actions, as manual options for "cleaning the feed" are often cumbersome and difficult to use for most users. Here, we present Take Back Control, a web browser extension that gives users control to hide undesirable content from their social media feeds. The extension combines JavaScript (for hiding the content) and machine learning (for deciding what content to hide). Our current demonstration includes three filter types: Toxic, Political, and Negative content, with a possibility to add more filters, all of this with the overarching aim of helping end users control the information visible in their social media feeds.
Recent years have seen growing public concern about the effects of persuasive digital technologies on public mental health and well-being. As the draws on our attention reach such staggering scales and as our ability to focus our attention on our own considered ends erodes ever further, the need to understand and articulate what is at stake has become pressing. In this ethical viewpoint, we explore the concept of attentional harms and emphasize their potential seriousness. We further argue that the acknowledgment of these harms has relevance for evolving debates on digital inequalities. An underdiscussed aspect of web-based inequality concerns the persuasions, and even the manipulations, that help to generate sustained attentional loss. These inequalities are poised to grow, and as they do, so will concerns about justice with regard to the psychological and self-regulatory burdens of web-based participation for different internet users. In line with calls for multidimensional approaches to digital inequalities, it is important to recognize these potential harms as well as to empower internet users against them even while expanding high-quality access.
Despite growing understanding of the addictive qualities of the Internet, and rising concerns about the effects of excessive Internet use on personal well-being and mental health, the corresponding ethical debate is still in its infancy, and many of the relevant philosophical and conceptual frameworks are underdeveloped. Our goal in this chapter is to explore some of this evolving terrain. While there are unique ethical considerations that pertain to the formalization of a disorder related to excessive Internet use, our ethical concerns (and indeed our mental health concerns) about whether certain technologies undermine well-being can and should be far broader than the debates about the appropriateness of particular diagnostic categories. In this chapter, we introduce some of these wider debates with regard to persuasive digital technologies—particularly those which aim to maximize use, or even to encourage compulsive engagement—as well as the difficulty in articulating the harms involved in excessive Internet use, especially where such use has not led to functional impairment. Following these conversations, we briefly consider some more practical ethical implications, including regulation of certain design features, concerns about growing socioeconomic inequality in online services, and whether there should be a “right to disconnect.”
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Social Network Sites (SNSs) are meant to facilitate interaction between people. The design of SNSs employs persuasive techniques with the aim of enhancing the user experience but also increasing interaction and user retention. Examples include the personalisation of content, temporarily available feeds, and notification and alert features. Socialness is now being embedded in new paradigms such as the Internet of Things and cyber-physical systems where devices can link people to each other and increase relatedness and group creation. One of the phenomena associated with such persuasion techniques is the experience of Fear of Missing Out (FoMO). FoMO typically refers to the preoccupation of SNS users with being deprived of interaction while offline. The salience, mood modification and conflict typically experienced as part of FoMO, are symptoms of digital addiction (DA). Despite recognition of the widespread experience of FoMO, existing research focuses on user psychology to interpret it. The contribution of SNS design in triggering FoMO remains largely unexplored. In this paper, we conduct a multi-stage qualitative research including interviews, a diary study and three focus group sessions to explore the relationship between SNS features and FoMO. Our findings demonstrate how the different SNS features act as persuasion triggers for certain kinds of FoMO. Also, we suggest features that could be introduced to social network sites to allow individuals to manage FoMO and identify the principles and challenges associated with engineering them.
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Digital nudges hold enormous potential to change behavior. Despite the appeal to consider timing as a critical factor responsible for the success of digital nudges, a comprehensive organizing framework to guide the design of digital nudges considering nudge moment is yet to be provided. In this paper, we advance the theoretical model to design digital nudges by incorporating three key components: (1) Identifying the optimal digital nudge moment (2) Inferring this optimal moment and (3) Delivering the digital nudge at that moment. We further discuss the existing work and open research avenues.
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Ten years ago, Thaler and Sunstein introduced the notion of nudging to talk about how subtle changes in the ‘choice architecture’ can alter people's behaviors in predictable ways. This idea was eagerly adopted in HCI and applied in multiple contexts, including health, sustainability and privacy. Despite this, we still lack an understanding of how to design effective technology-mediated nudges. In this paper we present a sys- tematic review of the use of nudging in HCI research with the goal of laying out the design space of technology-mediated nudging –the why (i.e., which cognitive biases do nudges combat) and the how (i.e., what exact mechanisms do nudges employ to incur behavior change). All in all, we found 23 distinct mechanisms of nudging, grouped in 6 categories, and leveraging 15 different cognitive biases. We present these as a framework for technology-mediated nudging, and discuss the factors shaping nudges’ effectiveness and their ethical implications.
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Policy makers increasingly use choice defaults to promote “good” causes by influencing socially relevant decisions in desirable ways, e.g., to increase pro-environmental choices or pro-social behavior in general. Such default nudges are remarkably successful when judged by their effects on the targeted behaviors in isolation. However, there is scant knowledge about possible spillover effects of pro-social behavior that was induced by defaults on subsequent related choices. Behavioral spillover effects could eliminate or even reverse the initially positive effects of choice defaults, and it is thus important to study their significance. We report results from a laboratory experiment exploring the subsequent behavioral consequences of pro-social choice defaults. Our results are promising: Pro-social behavior induced by choice defaults does not result in adverse spillover effects on later, subsequent behavior. This finding holds for both weak and strong choice defaults. JEL Classification: C91, D01, D04
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WeChat represents one of the most popular smartphone-based applications for communication. Although the application provides several useful features that simplify daily life, a growing number of users spend excessive amounts of time on the application. This may lead to interferences with everyday life and even to addictive patterns of use. In the context of the ongoing discussion on Internet Communication Disorder (ICD), the present study aimed to better characterize the addictive potential of communication applications, using WeChat as an example, by examining associations between individual variations in tendencies towards WeChat addiction and brain structural variations in fronto-striatal-limbic brain regions. To this end levels of addictive tendencies, frequency of use and structural MRI data were assessed in n = 61 healthy participants. Higher tendencies towards WeChat addiction were associated with smaller gray matter volumes of the subgenual anterior cingulate cortex, a key region for monitoring and regulatory control in neural networks underlying addictive behaviors. Moreover, a higher frequency of the paying function was associated with smaller nucleus accumbens volumes. Findings were robust after controlling for levels of anxiety and depression. The present results are in line with previous findings in substance and behavioral addictions, and suggest a similar neurobiological basis in ICD.
Conference Paper
Traditionally, many consumer-focused technologies have been designed to maximize user engagement with their products and services. More recently, many technology companies have begun to introduce digital wellbeing features, such as for managing time spent and for encouraging breaks in use. These are in the context of, and likely in response to, renewed concerns in the media about technology dependency and even addiction. The promotion of technology abstinence is also increasingly widespread, e.g., via digital detoxes. Given that digital technologies are an important and valuable feature of many people's lives, digital wellbeing features are arguably preferable to abstinence. However, how these are defined and designed is something that needs to be explored further. In this one-day workshop we welcome both industry and academic participants to discuss what digital wellbeing means, who is responsible for it, and whether and how we should design for it going forward.
Algorithmic recommender systems are a ubiquitous feature of contemporary cultural life online, suggesting music, movies, and other materials to their users. This article, drawing on fieldwork with developers of recommender systems in the US, describes a tendency among these systems’ makers to describe their purpose as ‘hooking’ people – enticing them into frequent or enduring usage. Inspired by steady references to capture in the field, the author considers recommender systems as traps, drawing on anthropological theories about animal trapping. The article charts the rise of ‘captivation metrics’ – measures of user retention – enabled by a set of transformations in recommenders’ epistemic, economic, and technical contexts. Traps prove useful for thinking about how such systems relate to broader infrastructural ecologies of knowledge and technology. As recommenders spread across online cultural infrastructures and become practically inescapable, thinking with traps offers an alternative to common ethical framings that oppose tropes of freedom and coercion.
Conference Paper
Digital overuse on mobile devices is a growing problem in everyday life. This paper describes a generalizable mobile intervention that combines nudge theory and negative reinforcement to create a subtle, repeating phone vibration that nudges a user to reduce their digital consumption. For example, if a user has a daily Facebook limit of 30 minutes but opens Facebook past this limit, the user's phone will issue gentle vibrations every five seconds, but the vibration stops once the user navigates away from Facebook. We evaluated the intervention through a three-week controlled experiment with 50 participants on Amazon's Mechanical Turk platform with findings that show daily digital consumption was successfully reduced by over 20%. Although the reduction did not persist after the intervention was removed, insights from qualitative feedback suggest that the intervention made participants more aware of their app usage habits; and we discuss design implications of episodically applying our intervention in specific everyday contexts such as education, sleep, and work. Taken together, our findings advance the HCI community's understanding of how to curb digital overload.
Are technology companies maximizing profits by making users addicted to their products?
Internet and social media addictions continue to grow as our dependence on technology increases. Estimates posit that over 210 million people worldwide suffer from this. Given its influence on users, reducing these addictions are of importance. Previous research demonstrates the importance of emotional states in affecting addiction behaviors. Through the Cognitive-Behavioral Model of Pathological Internet Usage, the role of life satisfaction in reducing both generalized Internet addiction and social media addiction is explored. Additionally, how happiness and stress affect these addictions through life satisfaction is examined. Results show that life satisfaction has significant effects on both generalized Internet addiction and the specific addiction to social media. For addicted individuals, there may be deep-rooted issues in their lives, lowering their satisfaction and driving their continued or increased addictions to Internet technologies.