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http://dx.doi.org/10.1145/3313831.3376672

# ‘I Just Want to Hack Myself to Not Get Distracted’:
Evaluating Design Interventions for Self-Control on Facebook

Ulrik Lyngs1, Kai Lukoff2, Petr Slovak3, William Seymour1, Helena Webb1,
Marina Jirotka1, Jun Zhao1, Max Van Kleek1, Nigel Shadbolt1

1Department of Computer Science, University of Oxford, UK  {ulrik.lyngs,
william.seymour, helena.webb, marina.jirotka,
jun.zhao, max.van.kleek<EMAIL_ADDRESS>2Human Centered Design &
Engineering, University of Washington, Seattle, US<EMAIL_ADDRESS>3Department
of Informatics, King’s College London, UK<EMAIL_ADDRESS>
(2020)

###### Abstract

Beyond being the world’s largest social network, Facebook is for many also one
of its greatest sources of digital distraction. For students, problematic use
has been associated with negative effects on academic achievement and general
wellbeing. To understand what strategies could help users regain control, we
investigated how simple interventions to the Facebook UI affect behaviour and
perceived control. We assigned 58 university students to one of three
interventions: goal reminders, removed newsfeed, or white background
(control). We logged use for 6 weeks, applied interventions in the middle
weeks, and administered fortnightly surveys. Both goal reminders and removed
newsfeed helped participants stay on task and avoid distraction. However, goal
reminders were often annoying, and removing the newsfeed made some fear
missing out on information. Our findings point to future interventions such as
controls for adjusting types and amount of available information, and flexible
blocking which matches individual definitions of ‘distraction’.

###### doi:

https://doi.org/10.1145/3313831.3376672

###### keywords:

Facebook; problematic use; self-control; distraction; ICT non-use; addiction;
focus; interruptions

††conference: CHI’20, April 25–30, 2020, Honolulu, HI, USA

<ccs2012> <concept> <concept_id>10003120.10003121.10011748</concept_id>
<concept_desc>Human-centered computing Empirical studies in HCI</concept_desc>
<concept_significance>500</concept_significance> </concept> </ccs2012>

[500]Human-centered computing Empirical studies in HCI

##  1 Introduction

Research on ‘Problematic Facebook Use’ (PFU) has investigated correlations
between Facebook use and negative effects on outcomes such as level of
academic achievement [37] and subjective wellbeing [60, 59]. Here, a cross-
cutting finding is that negative outcomes are associated with subjective
difficulty at exerting self-control over use, as well as specific use patterns
including viewing friends’ wide-audience broadcasts rather than receiving
targeted communication from strong ties [14, 60].

Much of this work has focused on self-control over Facebook use in student
populations [3, 46, 48], with media multitasking research finding that
students often give in to use which provides short-term ‘guilty pleasures’
over important, but aversive academic tasks [78, 90, 62]. In the present
paper, we present a mixed-methods study exploring how two interventions to
Facebook — goal reminders and removing the newsfeed — affect university
students’ patterns of use and perceived control over Facebook use. To
triangulate self-report with objective measurement, our study combined usage
logging with fortnightly surveys and post-study interviews.

We found that both interventions helped participants stay on task and use
Facebook more in line with their intentions. In terms of usage patterns, goal
reminders led to less scrolling, fewer and shorter visits, and less time on
site, whereas removing the newsfeed led to less scrolling, shorter visits, and
less content ’liked’. However, goal reminders were often experienced as
annoying, and removing the newsfeed made some participants fear missing out on
information. After the study, participants suggested a range of design
solutions to mitigate self-control struggles on Facebook, including controls
for filtering or removing the newsfeed, reminders of time spent and use goals,
and removing features that drive engagement. As an exploratory study, this
work should be followed by confirmatory studies to assess whether our findings
replicate, and how they may generalise beyond a student population.

##  2 Related work

###  2.1 Struggles with Facebook use

Whereas many uses of Facebook offer important benefits, such as social
support, rapid spread of information, or facilitation of real-world
interactions [80], a substantial amount of research has focused on negative
aspects [60]. For example, studies have reported correlations between patterns
of Facebook use and lower academic achievement [79, 88], low self-esteem,
depression and anxiety [53], feelings of isolation and loneliness [3], and
general psychological distress [16]. Such ‘Problematic Facebook Use’ (PFU) has
been studied under various names (including ‘Facebook dependence’ [89] and
‘Facebook addiction’[6]), but a recent review summarised a common definition
across papers as ‘problematic behaviour characterised by addictive-like
symptoms and/or self-regulation difficulties related to Facebook use leading
to negative consequences in personal and social life’ [60].

A large number of studies have in turn correlated measures of PFU with
patterns of use and personality traits. Here, researchers often distinguish
between use that is more ‘active’ (creating content and communicating with
friends) and use that is more ‘passive’ (consuming content created by others
without actively engaging), with the former being linked to more positive
correlates of subjective wellbeing [15, 27, 31, 33] and the latter to more
negative [52, 87].

Moreover, most studies have found that ‘problematic users’ tend to spend more
time on Facebook [60], including a recent study by researchers at Facebook
with direct access to server logs: users who experienced their use as
problematic (i.e., reported negative impact on sleep, relationships, or
work/school performance, plus lack of control over use) spent more time on the
platform, especially at night, as well as more time looking at profiles and
less time browsing the newsfeed, and were more likely to deactivate their
accounts [17].

Depending on the specific tools and thresholds used for assessing use as
‘problematic’, prevalence estimates vary widely, from 3.1% in a representative
sample of US users [17] to 47% in a study of Malaysian university students
([42] see also [9, 46, 89]). The upper bounds of such estimates suggest that,
at least at a mild levels, it is very common for people to struggle with using
Facebook in accordance with their goals [36]. This is supported by studies of
multitasking and media use finding that people very often perceive their use
of digital media to be in conflict with other important goals (61.2% of use
occurrences in an experience sampling study by Reinecke and Hofmann [76]), and
that Facebook in particular is one of the most common sources of media-induced
procrastination [78, 90].

###  2.2 Interventions and digital self-control tools

Catering to users struggling with self-control over digital device use, a
growing niche exists for ‘digital self-control’ tools on online stores for
apps and browser extensions. Such tools promise to support user self-control
through interventions such as removing distracting element from websites,
tracking and visualising use, or rewarding intended behaviour [58]. In
particular, many browser extensions focus on adjusting _Facebook_ in ways
intended to help self-control, for example by removing the newsfeed [43] or
hiding numerical metrics such as like count [35].

No studies have assessed how interventions found in these tools may alleviate
self-control struggles on Facebook. However, some recent studies have
investigated how temporarily deactivating or not logging in to Facebook affect
subjective wellbeing [5, 64, 84, 86]. The findings from these studies have
largely been in agreement, with Allcott et al. [5] the largest to date: in a
study where 580 participants were randomly assigned to deactivate their
accounts for four weeks, and compared to 1,081 controls, Facebook deactivation
increased offline activities (including socialising with family and friends
and watching TV) and subjective wellbeing, and decreased online activity
(including other social media than Facebook). Moreover, Facebook deactivation
caused a large and persistent reduction in Facebook use after the experiment.

For many users, however, deactivating or deleting their Facebook account
presents too tall a barrier to action for tackling problematic use. Most users
have more targeted non-use goals than “abstinence”, such as reducing time
scrolling the newsfeed (but not time posting in a university social group), or
reducing time spent on Facebook during final exams (but not during vacations,
cf. [17, 88]). Some existing research similarly supports positive effects on
wellbeing of targeted non-use, including research on active versus passive
social media use [14, 39, 87]. Therefore, investigating interventions found in
digital self-control tools for Facebook presents an exciting research
opportunity, as they represent less extreme measures than deactivation that
may have positive effects.

##  3 Overview of study

On this background, we set out to study how two interventions found in popular
browser extensions for scaffolding self-control on Facebook — specifically,
_adding goal prompts and reminders_ and _removing the newsfeed_ — affect
patterns of use and perceived control on Facebook among university students.
We designed a mixed-methods study that attempted to address common limitations
in related studies:

  * •

Most studies rely on self-reported Facebook use, which complicates
interpretation because self-report often correlates poorly with actual use of
digital devices [26, 25, 66, 81]. Therefore, we combined surveys and
interviews with logging of use, to triangulate subjective self-report and
objective measurement.

  * •

Nearly all studies, apart from deactivation studies, have used cross-sectional
designs, making it very difficult to interpret causality [60]. Therefore, we
randomly assigned participants to intervention groups and compared an initial
baseline to a subsequent intervention as well as post-intervention block.

Our choice of interventions is described in the ‘Pre-study’ section below.
Based on existing research on self-control struggles in relation to Facebook
use, our research questions were as follows:

  * •

RQ1 (Amount of use): How do goal reminders (Cgoal) or removing the newsfeed
(Cno-feed) impact time spent and visits made?

  * •

RQ2 (Patterns of use): How do goal reminders (Cgoal) or removing the newsfeed
(Cno-feed) impact patterns of use (e.g., passive / active)?

  * •

RQ3 (Control): How do goal reminders (Cgoal) or removing the newsfeed (Cno-
feed) impact perceived control?

  * •

RQ4 (Post-intervention effects): Do the effects (RQ1-3) of goal reminders
(Cgoal) or removing the newsfeed (Cno-feed) persist after interventions are
removed?

  * •

RQ5 (Self-reflection): Do the interventions enable participants to reflect on
their struggles with Facebook use in ways that might inform the design of more
effective interventions?

Whereas RQ1-4 follow from the background literature reviewed, RQ5 was a
generative research question pointing towards new design solutions. We did not
envision participants being ‘vessels of truth’ in relation to which design
interventions would solve their struggles, but were interested in what
suggestions the interventions might inspire as design probes.

##  4 Methods

Study materials, anonymised data, and analysis scripts are available via the
Open Science Framework at osf.io/qtg7h.

###  4.1 Pre-study

####  4.1.1 Reviewing Facebook self-control tools

In February 2018, we searched for browser extensions for supporting self-
control on Facebook on the Chrome Web store and identified 50 such extensions
implementing a range of interventions (see study materials for the list). Most
(36 out of 50) let the user remove or alter distracting elements, with more
than half (27/50) specifically hiding the newsfeed (e.g., ‘Newsfeed
Eradicator’ [43] removes the newsfeed and optionally replaces it with a
motivational quote). Others implemented interventions such as time limits
(e.g., setting a daily limit and prompting the user to stop using Facebook or,
like _Auto Logout_ [54], force closing it when the time has passed), goal
reminders (e.g., asking the user what she needs to do on Facebook and
subsequently providing reminders, _Focusbook_ [28]) or providing rewards or
punishments (e.g., transferring money out of one’s bank account if use is
above a set limit, _Timewaste Timer_ [73]).

####  4.1.2 Selecting interventions to investigate guided by a dual systems
model of self-control

To categorise these interventions, we relied on a recent review of
functionality in digital self-control tools, which grouped their main design
features into the types _block/removal_ , _self-tracking_ , _goal advancement_
, and _reward/punishment_ , which in turn were mapped to psychological
mechanisms in a dual systems model of self-regulation [58]. This model
distinguishes between behaviour under non-conscious ‘System 1’ control, i.e.,
when the external environment or internal states trigger habits or instinctive
responses; and behaviour that is under conscious ‘System 2’ control, i.e.,
when goals, intentions, and rules held in working memory trigger behaviour.
For example, a student might check Facebook as the first thing when opening
his laptop, because this context triggers a habitual check-in via System 1
control. Alternatively, the student might open Facebook because he has a
conscious goal of messaging a friend.

According to this model—which we return to in the Discussion—‘self-control’ is
the capacity of conscious System 2 control to override System 1 responses when
the two are in conflict. For example, one might have a conscious goal to not
check one’s phone at the dinner table and a need to use self-control to
suppress one’s checking habit, in order to align behaviour with this goal (see
[58] for details, cf. [49]).

_C no-feed_ For our first experimental condition, Cno-feed, we chose removing
the newsfeed, because this was by far the most common approach among the
extensions reviewed. Viewed through the dual systems model lens, removing the
newsfeed represents a _block/removal_ strategy which scaffolds self-control on
Facebook by preventing unwanted System 1 control from being triggered by the
newsfeed, and supporting System 2 control by preventing distracting
information from crowding out working memory and make the user forget her goal
[58].

_C goal_ To compare this to a different strategy, we selected a _goal
advancement_ intervention as a second experimental condition (Cgoal),
specifically the one implemented by _Focusbook_ [28], which prompts the user
to type in their goal when visiting Facebook and then periodically reminds
them of this goal. According to the dual systems model, this scaffolds self-
control in a way that is distinct from removing the newsfeed, namely, by
keeping the goals the user wishes to achieve present in working memory,
thereby enabling System 2 control. We chose _Focusbook_ ’s implementation,
because it had the largest number of users among the extensions reviewed that
implemented alternatives to _block/removal_ strategies.

_C control_ In order to control for ‘demand characteristics’ and placebo
effects [11, 65], we also included a control condition (Ccontrol). In this
condition, we changed the background colour of Facebook from light grey to
white, which we did not hypothesise to have any significant effect on
behaviour or perceived control.

###  4.2 Materials

####  4.2.1 Study conditions

Figure 1: Mockup of study conditions: Cgoal (adding a goal prompt when
visiting the site that every few minutes pops up a reminder), Cno-feed
(removing the newsfeed), and Ccontrol (white background). See study materials
for screenshots.

The study conditions are shown in Figure 1.
We implemented the interventions as Chrome extensions written in JavaScript
and CSS: during the intervention block, the extension script for Ccontrol
turned the background colour of Facebook white. For Cno-feed, the extension
script hid the webpage elements containing the newsfeed. For Cgoal, the
extension script was a modified version of _Focusbook_ (the source code for
which is available on GitHub [28]), where we forced safe-for-work-mode (i.e.,
avoiding foul language in reminders) and altered prompts that expressed
disapproval to neutral reminders (e.g., changing “Fine, just tell me why you
needed to open Facebook” to “Tell me why you needed to open Facebook”). The
extension prompted the user to type in why they opened Facebook when they went
to the site, and after 1-3 minutes popped up a reminder of what they typed,
along with a snooze button. Until the snooze button was pressed, the banner
containing the prompt slowly expanded to take up more and more screenspace.

####  4.2.2 Logging of use

Following recent work [88], we used the open-source browser extension
‘Research tool for Online Social Environments’ (ROSE) [71, 72] to log Facebook
use in the Google Chrome browser. We used this extension to record usage
metrics (e.g., timestamps when a browser tab with Facebook was brought in and
out of focus, number of clicks) and specific interactions (e.g., viewing a
profile, liking content). To preserve privacy, the extension gave interactions
(e.g., content liked) an anonymous identifier in stored data without storing
any identifying information about the actual content engaged with. The ROSE
extension was installed on participants’ laptop in addition to the extension
for their intervention condition.

####  4.2.3 Surveys/interviews

Opening survey: The opening survey included (i) demographic information, (ii)
basic information about participants’ use of Facebook (when they got an
account, devices they use to access the site, prior use of self-control tools
for Facebook), and (iii) two individual difference measures (susceptibility to
types of distraction [61] and a Big Five personality measure [32]).

Repeated surveys: The survey administered after each study block included
three measures:
(i) The Passive and Active Facebook Use Measure (PAUM; [31]), which assesses
frequency of activities on Facebook. The measure is factored into the usage
dimensions ‘active social’ (items including “Posting status updates”,
“Chatting on FB chat”), ‘active non-social’ (e.g., “Creating or RSVPing to
events”, “Tagging photos”), and ‘passive’ (e.g., “Checking to see what someone
is up to”, “Browsing the newsfeed passively (without liking or commenting on
anything)”).
(ii) The Multidimensional Facebook Intensity Scale [67], which assesses
agreement with statements about Facebook use (e.g., “I feel bad if I don’t
check my Facebook daily”) and is factored into the dimensions ‘persistence’,
‘boredom’, ‘overuse’ and ‘self-expression’.
(iii) The Single-Item Self-Esteem Scale [77], a commonly used measure of self-
esteem in psychological research.

In addition, the survey after the intervention block included items on whether
the changes affected perceived control, or how participants accessed Facebook
on laptop vs smartphone.

Interviews: After the study, we conducted semi-structured interviews with all
participants. Main topics probed were (i) whether the interventions worked as
expected, (ii) how participants experienced the interventions (example
question: “When [changes in the participant’s condition], what was that
like?”), (iii) what changes participants might wish to make to Facebook to
support their intended use (example question: “If you could build any
extension you wanted to change the way Facebook appears and works to make it
work better for you, what might you want to do?”).

5-month follow-up survey: Five months after the study, we sent participants an
optional brief survey, assessing whether (and if so, how) the study had led to
enduring changes in how they use Facebook.

###  4.3 Recruitment

Participants were recruited from colleges at the University of Oxford, using a
combination of mailouts, posters, and Facebook posts. Recruitment materials
described the study as a study on ‘Facebook distraction’, investigating ‘which
parts of Facebook distract users, and what might be done about it’.
Recruitment targeted non-first year students aged 18-30, who felt they were
‘often distracted by Facebook’. Participation was compensated with a £20
Amazon gift card.

###  4.4 Procedure

Figure 2: Flowchart of the study procedure

A flowchart of the study procedure is shown in Figure 2.
Participants were randomly assigned to conditions. At an initial meeting,
participants filled in the opening survey and installed two extensions on
their laptop for the Chrome browser: the ROSE extension for logging use and
our extension for modifying Facebook according to their assigned condition.
Participants were instructed to use Chrome whenever they accessed Facebook on
their laptop throughout the study period, and informed that the extensions
would ‘anonymously measure how you spend time on the site’ and ‘may change how
Facebook appears at some point during the study period’. The logging period
lasted six weeks, grouped into three two-week blocks. By the end of each
block, participants were sent a survey link on Friday at 3pm and a reminder
two days later. The first block served as a baseline, with no changes made to
Facebook. In the second block, interventions were applied from Monday 9am
(announced with a pop-up the first time participants visited Facebook) to
Monday 9am two weeks later. The third block served as a new baseline
measurement (post-intervention) with Facebook returned to normal. By the end
of this block, a pop-up thanked participants for taking part and directed them
to sign up for an interview and debriefing.

A subset of participants (n = 11) began the tracking period one week later
than the others.

###  4.5 Data pre-analysis

Quantitative data: On rare occasions, the ROSE extension did not correctly
record entries to or exits from Facebook, which resulted in some instances
where the calculated duration of active focus on a tab with Facebook was
unrealistically long (more than 24 hours in one case). To handle such
instances, we excluded visits longer than one hour when analysing visit
durations (144 tab visits out of a total of 120,002).111See study materials
for the precise data processing workflow from raw data to reported results.

Interview transcription and thematic analysis: Two of the authors transcribed
and conducted thematic analysis of all the interviews and free-text survey
responses. The recordings were iteratively transcribed and analysed using an
open-coding approach. The authors reviewed transcripts and identified emerging
codes individually, and regularly discussed emerging codes.

Thematic analysis was conducted in the Dedoose software; quantitative analyses
were conducted in R.

##  5 Results

58 students (21 male) took part. For 8 participants, the intervention failed
(on some Windows laptops, security settings prompted participants to turn the
extensions off), and 1 participant deactivated his Facebook account during the
study. Survey and logging data from these participants, as well as their
interview statements about the interventions, were excluded from analysis. In
addition, 2 participants deleted the ROSE extension before the debriefing -
and with it their logged use - and for 1 participant the interview recording
device failed. This left us with survey data from 49 participants, logging
data from 47 participants, and interview data from 57 participants for
analysis. Median interview length was 23m 51s (sd = 5m 5s).

In the following, we first report general characteristics of participants and
their Facebook use, as well as introductory notes on how interventions were
used and perceived. Afterwards, we report results grouped by research
question.

###  5.1 Participant characteristics

Participants’ median age was 22.5 (min = 19, max = 38) years. 90% had had a
Facebook account for six years or longer, and the median number of Facebook
friends was 900 (min = 200, max = 2200). All participants used Facebook on
their laptop, and 96% also used it on their smartphone. On smartphone, most
(78%) used the Facebook and Messenger apps, 8% used the web browser (instead
of the Facebook app) plus the Messenger app, 6% used only the Messenger app,
and 2% (1 participant) used only the smartphone’s web browser to access
Facebook.

Most participants (71%) had never used digital self-control tools for
Facebook. Among those who had, the most commonly used tools blocked access (7
participants) or removed the newsfeed (3 participants). 3 participants
currently used such tools; one used _Newsfeed Eradicator_ (which removes the
newsfeed), another used _Self-control_ (which blocks social media), and the
third used an ad blocker (which we did not consider a self-control tool).

###  5.2 Overall Facebook use

Across all participants and the entire study period, the median number of
daily tab visits to Facebook was 23 (min = 5, max = 138). The median break
length between visits to Facebook was 69.5 seconds (min = 11, max = 445). The
median of participants’ average amount of daily time spent was approximately
21 minutes (min = 4m, max = 2h 56m).

Often, a number of successive tab visits was logged within a short span of
time (e.g., if participants switched back and forth between active application
windows). Following Cheng et al. [17], we calculated the number of ‘sessions’
as the number of times where the break between two visits to Facebook was
longer than 60 seconds. The median number of daily sessions on Facebook was 11
(min = 1, max = 101).

###  5.3 Intervention use and perceptions

The Cgoal extension did not record what participants typed when prompted for
their goal, as we wanted to study effects of goal reminders without
participants adapting or self-censoring from knowing responses might be read
by the researchers. However, we asked in the interviews how they had used it.
Most said they wrote short, descriptive, but generic notes for what they did
(“I would type shorthand in for what I was about to do, so most of the time I
would say something like ‘reply to messages’ or just ‘messages’ or ‘post
something on a group’ or something like that”, P4). Some also said they
occasionally wrote meaningless or ‘unsavoury’ things when they found the goal
prompt annoying or disruptive (“I think sometimes I tried to type in, like,
not really proper words and it said, ‘give me a proper answer’ and I was like
‘dammit’!”, P27). In Cno-feed, one participant said the newsfeed occasionally
flashed on screen very briefly before being hidden by our script (“sometimes i
saw like a millisecond of something and I was like ‘oh that’s interesting, I
would like to see that’ but then it wasn’t there”, P56).

In Ccontrol, a couple of participants said the white background made content
stand out less on their screen (“white background definitely makes it harder
to… I don’t think it’s easier to read…”, P1). Others, however, found it
aesthetically pleasing (“I just liked Facebook more… it felt more… I mean it
felt more Nordic, it wasn’t grey and boring, it was white and nice…”, P30) and
wanted it to persist (“is there a way that I can keep the background white?”,
P15).

###  5.4 RQ1 (Amount of use): How do goal reminders or removing the newsfeed
impact time spent and visits made?

Figure 3: Time spent and number of visits made to Facebook. Comparing baseline
and intervention, goal reminders were associated with less daily time (A),
fewer tab visits (B), and a trend towards shorter visits (C). Removing the
newsfeed was associated with shorter visits (C). Comparing the post-
intervention block to baseline, goal reminders were associated with fewer
visits, suggesting an enduring effect of the intervention.

The logging data and qualitative data suggested that Cgoal led to less time
spent and fewer and shorter visits, whereas Cno-feed led to shorter visits
(Figure 3):

Usage logging showed that in Cgoal, average daily time on Facebook was
significantly lower during the intervention block than in the baseline (median
daily time in baseline: 27m 14s, median in intervention: 15m 5s, _p_ = 0.01,
_r_ = 0.63, Wilcoxon signed rank test); number of daily visits declined
(median number of visits in baseline = 29.4, median in intervention = 10.6,
_p_ = 0.01, _r_ = 0.63, Wilcoxon signed rank test); and there was a trend
towards shorter visits (mean tab visit duration in baseline = 1m 25s, mean in
intervention = 1m 15s, _t_(14) = 1.96, _p_ = 0.07, _d_ = 0.51). In Cno-feed,
only visit length declined significantly (mean visit length in baseline = 1m
12s, mean in intervention = 56s, _t_(13) = 2.81, _p_ = 0.01, _d_ =
0.75).222Reported effect sizes are Cohen’s _d_ for t-tests [19] and _r_ for
Wilcoxon signed rank tests [29], computed with the rstatix package for R [45].

Participants’ reports in the surveys and interviews agreed with the logging
data:
In Cgoal, two common themes were that the intervention reduced amount of time
on Facebook on laptop (“yeah i think I used it less and when I was using it I
wasn’t using it for very long, like a minute maybe”, P45interview333Subscripts
indicate whether quotes are from survey free text responses or from post-study
interviews, and in some cases also show participants’ study condition.;
“definitely used it a bit less”, P21interview) and that reduced use was partly
caused by the intervention being annoying/stressful (“This programme made me
annoyed thus I would spent [sic] less time on Facebook”, P32survey; “The
changes stressed me to get done with my task and then close facebook”,
P40survey).

In Cno-feed, participants had mixed opinions on whether or not it reduced
amount of use. Some felt it reduced their use (“limited overall usage”,
P28survey, “I think I used it less erm for shorter periods of time”
P55interview) but others felt it only changed their newsfeed use without
affecting amount per se (“The lack of newsfeed is welcome … Facebook usage on
my laptop has not changed/barely changed”, P27survey; “I spent a lot of time
actually on facebook but messaging other people and not just looking through
my wall”, P54interview).

###  5.5 RQ2 (Patterns of use): How do goal reminders or removing the newsfeed
impact patterns of use?

Figure 4: Scores on the Passive and Active Facebook Use Measure by condition.
Comparing the intervention to the baseline block, removing the newsfeed
reduced scores on the ’passive’ dimension (A), as well as (as expected)
individual items ’Browsing the newsfeed passively (without liking or
commenting on anything)’s (B) and ’Browsing the newsfeed actively (liking and
commenting on posts, pictures and updates)’ (C). Goal reminders reduced only
passive newsfeed browsing (B). Comparing post-intervention and baseline,
removing the newsfeed was associated with reduced passive newsfeed browsing
post-intervention (B).

The logging, survey, and interview data suggested that both Cgoal and Cno-feed
affected patterns of use: Cgoal selectively reduced passive scrolling of the
newsfeed, whereas Cno-feed (as expected) reduced all behaviour related to the
newsfeed (Figure 4).

Thus, _usage logging_ showed that average daily scrolling declined by 42% in
Cgoal (comparing intervention to baseline, _t_(14) = 2.39, _p_ = 0.03, _d_ =
0.62), and by 73% in Cno-feed (_t_(13) = 4.15, _p_ = 0.001, _d_ = 1.11).
Moreover, in Cno-feed, the number of times content was liked declined (median
number of likes during baseline = 16, median during intervention = 7, _p_ =
0.002, _r_ = 0.88, Wilcoxon signed rank test).

In the _surveys_ , scores on the Passive and Active Facebook Use Measure
dimensions showed that participants in Cno-feed had substantially lower scores
on ‘passive’ use in the intervention than in the baseline block (_t_(13) =
4.8, _p_ = 0.0003, _d_ = 1.28). We explored effects on more granular elements
of Facebook use by comparing baseline and intervention scores separately for
each item of the PAUM.444The reported p-values are not corrected for multiple
comparisons — these should be considered exploratory results to be followed-up
with confirmatory studies. Two items showed significant variation with
condition: “Browsing the newsfeed passively (without liking or commenting on
anything)” and “Browsing the newsfeed actively (liking and commenting on
posts, pictures and updates)”: in Cgoal, participants reported less passive,
but not active, browsing of the newsfeed during the intervention block
compared to baseline (Passive browsing: _p_ = 0.03, _r_ = 0.57, Active
browsing: _p_ = 1, _r_ = 0.05, Wilcoxon signed rank test). In Cno-feed,
participants reported less passive as well as less active newsfeed browsing
(Passive browsing: _p_ = 0.001, _r_ = 0.89, Active browsing: _p_ = 0.01, _r_ =
0.69, Wilcoxon signed rank test). Moreover, participants in Cno-feed showed a
trend towards lower scores on “Commenting (on statuses, wall posts, pictures,
etc)” (_p_ = 0.09, _r_ = 0.46, Wilcoxon signed rank test).

The quantitative results were supported by the qualitative data:
for participants in both experimental conditions, a recurrent theme was that
the interventions caused decreased browsing of the newsfeed (“I did feel very
aware when scrolling down my newsfeed, and cut it down”, P19goal_survey;
“definitely meant I spent less time scrolling on newsfeed on my laptop”,
P55no-feed_survey), and increased use of Facebook for other, more deliberate
purposes (“a big facebook post or whatever not just passively…scrolling”,
P41goal_interview; “messaging other people and not just looking through my
wall”, P54no-feed_interview).
In Cgoal, participants said the effects were driven by the intervention making
them search for reasons to justify being on the site (“Being asked why I was
opening Facebook was really helpful as it made me question why”,
P41goal_survey; “less likely to aimlessly browse, as I couldn’t justify it”,
P45goal_survey). In Cno-feed, participants said the lack of a newsfeed made
them seek out alternative options that were often more productive and
deliberate (“procrastination was more productive in that I was uhm seeking
things out to read or to do that were more intentional, I suppose, and less
kind of mindless which I guess the newsfeed is”, P12no-feed_interview).
(Changed patterns of use related to perceived control are reported below.)

###  5.6 RQ3 (Control): How do goal reminders or removing the newsfeed impact
perceived control?

Figure 5: Responses from survey question on control included in the survey
administered by the end of the intervention block: ’During the last two weeks,
did the changes made to Facebook on your laptop affect how in control you felt
over your use of the site on your laptop?’

The qualitative data suggested that Cgoal and Cno-feed supported control in
the sense of helping participants avoid unintended use and staying on task,
but at the cost of being annoying/frustrating (Cgoal) or leading to fear of
missing out (Cno-feed).

When exploring survey responses in the Multidimensional Facebook Intensity
Scale, the only of its four dimensions that showed significant differences
between the baseline and intervention blocks was _overuse_ : scores on this
measure trended towards decrease during the intervention in all conditions
(Ccontrol: _t_(18) = 2.37, _p_ = 0.03, _d_ = 0.54, Cno-feed: _t_(13) = 1.99,
_p_ = 0.07, _d_ = 0.53, Cgoal: t(14) = 1.75, _p_ = 0.1, _d_ = 0.45), perhaps
suggesting that the study procedure across conditions made participants
reflect on use.

When asked directly in a survey item following the intervention block whether
the changes made to Facebook made them feel less or more in control of their
use, Ccontrol had no impact, while participants seemed divided about the
impact of the experimental conditions (Figure 5).

The qualitative data seemed to provide the explanation:
In both Cgoal and Cno-feed, it was a strong theme in the surveys and
interviews that the interventions helped participants stay on their intended
task during use (“used it less for stuff that I wasn’t intending when I opened
it”, P4goal_interview; “I’ll kind of forget that I’m doing work and start
scrolling so it was useful to not be able to do that”, P47no-feed_interview).
A subtheme was that this included making it easier to disengage from use
(“it’s good to get this reminder of ‘hey you can get off this thing’ ”,
P31goal_interview; “it was easier just to log out, just check what I had to
and then leave facebook” P54no-feed_interview). In Cgoal, participants said
the reason the intervention helped them stay on task was that it helped them
snap out of automatic use, that is, stop themselves when they engaged in
unintended behaviour (“[the reminder] sort of snaps you out of that trance,
you know what I mean?”, P21interview). In Cno-feed, participants said the
intervention stopped unintended behaviours from being triggered in the first
place (“there is nothing here [referring to the newsfeed], like ‘what did I
want?’, you know, so then I went and contacted the person or looked at the
specific thing that I wanted, not what I saw and kinda wanted at the moment”,
P56interview).

At the same time, there were downsides to the interventions in that Cgoal was
frequently annoying or frustrating, especially because it was not sensitive to
context (“I use facebook just to message people and I found this extremely
annoying because I need to tell someone something and then this thing comes up
and I’d just get annoyed…” P32interview), and that Cno-feed led to fear of
missing out (“missing out on a lot because actually a lot of the ways I
interact with people on facebook is things I see on the newsfeed”,
P12interview).

####  5.6.1 Cross-device use

When asked if the interventions changed how they used Facebook on smartphone
vs laptop, 86% of participants in Cgoal and 57% in Cno-feed answered ‘Yes’
(compared to 6% in Ccontrol, $\chi^{2}$ = 65.19, _p_ < 0.001).

Unpacking this in the qualitative data, participants in both experimental
conditions expressed that cross-device access helped them manage the
interventions’ downsides, while still enjoying the positive effects (“if I was
scrolling through the newsfeed or checking events, then it wouldn’t be
annoying because I shouldn’t be doing that on my laptop while I’m working, and
if it was something like sending messages about work, contacting friends and
asking for help then I could use my phone”, P40goal_interview; “I could reap
the benefits of the newsfeed but without being sucked into it on two
platforms”, P28no-feed_survey), and so they sometimes used their smartphone
for activities on Facebook the interventions interfered with, but as a more
deliberate choice (“you’re working on your laptop, uhm, and then it’s very
easy to just click new tab, but having to get your phone out…”,
P19goal_interview; “the time I did spend on my phone was more, like, focused
because I was actually looking for things I missed out on on my laptop”,
P55no-feed_interview).

###  5.7 RQ4 (Post-intervention effects): Do the effects (RQ1-3) of goal
reminders or removing the newsfeed persist after interventions are removed?

Comparing post-intervention to baseline, Cgoal and Cno-feed were associated
with some persisting effects, with participants in Cgoal engaging in fewer
daily visits and some feeling that the intervention helped build a habit of
more intentional use, and participants in Cno-feed engaging in less passive
newsfeed browsing.

Thus, in terms of _amount of use_ , participants in Cgoal made fewer daily
visits post-intervention compared to baseline (median number of daily visits
in first baseline = 29.4, median in post-intervention block = 9.8, _p_ =
0.003, _r_ = 0.72, Wilcoxon signed rank test).
In terms of _patterns of use_ , participants in Cno-feed reported less passive
browsing of the newsfeed post-intervention compared to baseline (_p_ = 0.007,
_r_ = 0.78, Wilcoxon signed rank test). In the interviews, some Cno-feed
participants expressed feeling less attracted by the newsfeed when it returned
(“I found myself less interested in the newsfeed”, P10interview).
In terms of _perceived control_ , some participants in Cgoal said the
intervention helped them build a persisting habit of asking themselves what
their intention of use was when visiting the site (“from this week there is a
habit being built… asking myself why I’m opening Facebook and that habit’s
perpetuated more or less to this week”, P34interview, “I’m still aware every
time I open Facebook, I’m just a bit more aware every time… it’s not the
reflex anymore now that I’ve had that experience where I have to write
everything down”, P1interview).

###  5.8 RQ5 (Self-reflection): Do the interventions enable participants to
reflect on their struggles in ways that might inform the design of more
effective interventions?

In the interviews, nearly all participants expressed feeling conflicted about
Facebook, in that they found it too useful or engrained in their lives to do
without, but also an ongoing source of distraction and self-control struggles.
They readily suggested a range of design solutions to mitigate self-control
struggles. The extent to which interventions were perceived as freely chosen
was important to how it was received, and participants did not trust Facebook
to provide solutions.

####  5.8.1 Struggles with Facebook use

Too useful to do without, but source of distraction and self-control
struggles: On the one hand, Facebook provided functionality participants could
not — or would not — do without, especially messaging, events, groups, and
pages. On the other, Facebook was frequently distracting and caused them to
waste time and feel frustrated (“I just want…to hack myself to have the self-
control to, like, not get distracted… I literally just use it as distraction”,
P42no-feed). In particular, participants struggled to use Facebook in line
with their intentions. Main aspects included (i) going to the site to do one
thing, but then forgetting this goal (“there is one specific trigger that I
need to open facebook, but because when I open the page immediately there is
tons of information there, like erm notifications, and you scroll down endless
streaming… so very easily I could be distracted”, P34goal), (ii) internal
conflict between short-term gratification and longer-term goals (“might find
them [videos] funny in the short term but when I think about it in the bigger
picture it is a complete waste of time”, P48control), and (iii) using Facebook
purely out of habit. In relation to the latter, emotional states, especially
boredom, were mentioned as triggers of habitual use (“if I’m in that erm not
very motivated state… I’ll literally just find myself opening it, without even
thinking that I’m doing it”, P17control).

####  5.8.2 Specific suggestions for design solutions

Four themes emerged in relation to specific design suggestions for mitigating
these struggles:

Control over the newsfeed: More than half of participants explicitly said the
newsfeed did not give them what they wanted, and they desired easy ways to
filter it, limit it, or turn it off. Some had tried customising their
newsfeeds, but found Facebook’s means of doing so tedious and ineffective (“I
browse through shit that I don’t want to see and I keep on clicking on ‘I
don’t like this’, ‘this is not interesting’ and of course it keeps on adding
new stuff so that doesn’t solve the problem basically”, P51control). Solution
suggestions included simple ways to filter the newsfeed (“a slider to modify
the amount you see people who are on your newsfeed at different percentiles”,
P49goal, “two different ones, like you could have a ‘friends’ or like ‘photos’
or something”, P17control), reducing the amount of information (“maybe it
should be limited to like ten posts and you wouldn’t get another ten until the
next hour”, P45goal, “if it was instead like blank and then you opt-in to who
you actually wanna see on your newsfeed as opposed to opt-out”, P44no-feed),
or being able to remove it altogether.

Raise awareness of time spent or usage goals: Participants often lost track of
time spent, or of their usage goals, and wanted reminders that raised
awareness. These should be easily accessible (“you wouldn’t want it to be
buried in settings, something that was actively shown to you I think that
would be useful”, P52control), and let users judge whether their use was
appropriate (“if I saw like ‘you’ve spent 2 minutes today’, like ‘great, I’ve
got loads of time that I can waste tomorrow because I’ve been good today’ ”,
P6goal). Participants in Cgoal said the timing and intrusiveness should be
calibrated differently to the reminders they experienced in the study (“less
in-your-face… so maybe more, longer intervals and not the expanding thing… if
I could change it to longer intervals and maybe a bit less invasive then I
think it would actually help”, P4goal).

Remove ‘addictive’ features: Participants wished to remove or modify features
driving them to use the site. Specific features mentioned included
notifications (“get rid of notifications… if I didn’t have things popping up
every 30 minutes like ‘this has happened’ I don’t think I would think about
Facebook’, P6goal), viral videos, and games (“things like game suggestions and
like all that sort of stuff I would definitely get rid of cause… I don’t want
to play games … ‘stop bugging me’ ”, P55no-feed). One interesting suggestion
was to be able to display content as text-only (“limit it to like text-only
posts when you’re working so that you’re not bothered by videos and algorithms
and photos”, P45goal).

Flexible blocking to meet individual definitions of distraction: Participants
suggested blocking solutions that could adapt to the type — or timing — of use
they found distracting. Thus, some said blocking access altogether was too
inflexible to be useful (“there are useful uses of Facebook that aren’t just
waste of time…a blanket, like, ‘don’t do anything on Facebook’… it’s not
practical for those people who have to use Facebook”, P41goal). Suggestions
for useful solutions included being able to block or allow specific
functionality within Facebook, block access only during specific times (“sync
it with a timetable, like lectures or something”, P45goal), or even
automatically detect if activity is engaged with as a distraction.

####  5.8.3 Generic solution needs

People differ in what they seek on Facebook and the design solutions they
prefer: Some participants wanted to block or remove distractions, whereas
others preferred less intrusive solutions, such as goal reminders. Similarly,
even though most participants were dissatisfied with the newsfeed, some wanted
it to prioritise close ties, whereas others wanted it to prioritise pages they
follow (“I wouldn’t want to see anyone’s posts, I would only want to see posts
by things I wanted to follow, whether that’s petitions or science papers”,
P20no-feed).

Interventions can ‘backfire’ if overly intrusive and/or not freely chosen:
Participants felt interventions could make people to rebel against them if too
intrusive and/or if they did not feel in charge. In terms of _intrusiveness_ ,
some felt blocking tools could backfire for this reason (“I feel like most
people in their nature, if you have something restrictive… then you kinda want
to rebel against it”, P56no-feed). In terms of _feeling in control_ , some
participants suggested this could change their reaction to the very same
intervention. For example, a participant in Cgoal felt the goal reminders were
too intrusive and led to resistance (“I got very used to clicking out of it
and like, I’m just gonna stay on just out of spite”, P19goal), but thought she
would react differently if she controlled the reminders herself (“it would be
a bit different if it was me, if I could actually write the messages… I think
that’d help me, and knowing it was me, so it wasn’t anyone else”).

Scepticism about design solutions coming from Facebook: Participants did not
trust Facebook to provide effective solutions for mitigating self-control
struggles, because this was seen as going against their business interests
(”you wonder how much they’d try to just give people the information that
doesn’t really reflect badly on them”, P36control; “Facebook’s interest is for
people to spend more time on it ’cause then they’ll get more ad revenue, so…”,
P45goal).

##  6 Discussion

Figure 6: Summary of main findings for RQ1-4. ’L’ = logged usage data, ’S’ =
quantitative survey data, ’Q’ = qualitative data from surveys and interviews.
For quantitative data, arrows indicate direction of the effect when _p_ < .10,
and effect sizes are marked with an asterisk when _p_ < .05.

Figure 6 summarises findings from RQ1-4: both Cgoal and Cno-feed reduced
unintended Facebook use (RQ3), with the downside that Cgoal was often
experienced as annoying and Cno-feed made some fear missing out on information
(cf. “FOMO”, [74]). On amount of use (RQ1), Cgoal reduced daily time, number
of visits, and visit length, whereas Cno-feed reduced visit length. On
patterns of use (RQ2), Cgoal and Cno-feed reduced scrolling and passive
newsfeed browsing, and Cno-feed in addition reduced active newsfeed browsing
and amount of content ’liked’. On post-intervention effects (RQ4), Cgoal was
associated with fewer visits and Cno-feed with less passive newsfeed browsing.
In terms of reflections on struggles and solutions (RQ5), participants felt
conflicted because Facebook was a source of distraction and self-control
struggles but also vital to staying connected, i.e., too useful to avoid. They
suggested specific design solutions related to control over the newsfeed,
reminders of time spent and usage goals, removing ‘addictive’ features, and
flexible blocking. Their preferred solutions (as well as the information
sought on Facebook) differed, however, and they felt that solutions might
‘backfire’ if overly intrusive and/or not freely chosen. We now discuss design
implications as well as some of the limitations and future work.

###  6.1 Evaluating the experimental interventions

Focusing specifically on the ability to use Facebook in line with one’s
conscious intentions —– which is at the very core of self-control [23] —–
which of our two experimental interventions is more effective? Goal reminders
and removing the newsfeed represent contrasting, and potentially
complementary, strategies. In our study, both strategies had a positive effect
on perceived control and a significant effect on behaviour, with Cgoal helping
people ’snap out’ of unintended behaviour and Cno-feed preventing unintended
behaviours from being triggered. While these results suggest that both
interventions have potential, as an exploratory study with a restricted
sample, further research is needed to draw definitive conclusions about
robustness, effect sizes, and individual differences. However, contextualising
our study within related research in psychology and HCI can provide some
predictions:

One possible approach is to apply a dual systems model of self-regulation (as
called for in recent HCI research [20, 70, 2, 58]). From this perspective,
goal reminders are a ‘System 2’ intervention which supports conscious self-
control by bringing the goals into working memory that the user wishes to
control her behaviour in relation to. Removing the newsfeed is both a ‘System
1’ and ‘System 2’ intervention which prevents unwanted automatic responses
from being triggered by the newsfeed, and supports conscious self-control by
preventing attention-grabbing information from crowding out working memory and
making the user forget her goal.
A recent comprehensive review of digital behaviour change interventions found
that providing information about the consequences of behaviour (a System 2
intervention) tends to be unsuccessful, despite being the most common
technique. The authors argued that targeting unconscious habit formation
(System 1) should be the focus for interventions that aim at long-term
efficacy [70]. Similarly, psychological research has found that people who are
better at self-control tend to develop habits that make their intended
behaviour more reliant on automatic processes (System 1) and less on conscious
in-the-moment self-control (System 2), and/or reduce their exposure to
‘temptations’ in the first place [30, 23, 24]. This may be because effective
System 2 control depends not only on remembering longer-term goals, but also
on one’s motivation to exert control relative to those goals, which can
fluctuate with emotional state (cf. participants who said they were more
likely to go on Facebook when bored or unmotivated [10, 41, 56]).

We therefore expect removing the newsfeed to be more generally effective than
goal reminders, because it reduces the amount of potentially distracting
information and thus the need for in-the-moment conscious control. In our
study, the qualitative data did suggest that Cgoal fostered a habit of asking
oneself about one’s purpose when visiting Facebook. However, given the above,
the likelihood of effective control through a habit of goal awareness should
depend on what content is available and how that content is perceived: the
more ‘engaging’ the content, the greater the risk that goal awareness will not
by itself provide sufficient control motivation [10, 83, 56]. Goal reminders
should therefore exhibit larger variation in effectiveness, and may be less
useful for individuals whose newsfeeds contain more attention-grabbing content
and/or who struggle more with inhibiting distractions in general. This would
align with recent findings that those who find Facebook more valuable are also
(somewhat paradoxically) more likely to find their use problematic [17].
Similarly, prior work suggest that blocking off online distractions is more
effective for individual who are more susceptible to social media distractions
[61] (cf. [56, 63]). These strategies are, however, not mutually exclusive and
can be combined in effective interventions, as is already the case in many
digital self-control tools (e.g., _Todobook_ [7], which removes Facebook’s
newsfeed and replaces it with a to-do list reminding the user of her goals).

###  6.2 Designing future interventions

Broadly, participants’ suggested design solutions related to either _altering
the information landscape_ (by filtering the newsfeed, removing features
driving engagement, or blocking distracting elements) or _raising awareness to
help navigation within this landscape_ (by adding reminders of time spent or
usage goals). These suggestions could be compared to the many existing
interventions on online stores, analysed using a dual systems or other model,
and strategies more likely to be effective implemented and evaluated. Here, we
discuss implications of the cross-cutting theme that interventions should be
experienced as freely chosen and not overly intrusive to avoid ‘backfiring’
and motivate people to rebel against an intervention instead of being helped
by it (cf. [56]).

Given that participants preferred different interventions — with some wanting
restrictive blocking tools — it is not a solution to only consider, e.g., non-
intrusive addition of user controls [38]. Rather, designers should keep in
mind that the effectiveness of the exact same restriction or intrusion may
depend on whether it is perceived by the user as self-imposed or externally
imposed [12, 82, 13]. An implication is that interventions should be carefully
framed as being supportive of the user’s personal goals (cf. [82, 8]). For
example, blocking tools may wish to remind the user why their past self
decided to impose restrictions on their present self [22]. Current examples
‘in the wild’ include browser extensions for website blocking that display
motivational quotes or task reminders when users navigate to distracting sites
[58].

One exciting avenue for future tools is systems that can learn the user’s
personal definition of distraction and in what contexts to, e.g.,
automatically impose or not impose limits. This was suggested by one of our
participants, and is being explored in some HCI research, e.g. _HabitLab_,
which rotates between interventions to discover what best helps a user limit
time on specific websites [51]. A useful such system in the context of
Facebook would not simply limit time, but rather assist the user in carrying
out their goals, for example by dynamically blocking elements such as the
newsfeed if the user’s current goal is to create an event. Such a hypothetical
system could be highly useful, but it would be crucial to its success that its
interventions were perceived by the user as being in her own interest. In
addition, it would need to _really_ understand the user to be functional [57],
creating a possible trade-off between privacy and the ‘fit’ of the
intervention. Facebook itself, with its deep knowledge of user behaviour,
might be in the best position to explore this approach, but we note that
participants in our study were deeply sceptical about Facebook’s motivations
and did not expect design solutions coming from Facebook to be ‘on their side’
(cf. [21, 68]).

###  6.3 Limitations and future work

Confounding variables: A possible criticism is that less scrolling and shorter
visits when removing the newsfeed occur simply because there is nothing to
scroll. We note that removing the newsfeed did not make scrolling impossible —
it remained relevant on all other pages than the home screen — and thus
scrolling remains a useful measure. Moreover, reduced time is often an
explicit goal for users, and so time spent in the face of reduced content is a
relevant outcome.
Lack of cross-device tracking: We logged Facebook use on laptop only and did
not quantify effects of the interventions on cross-device use. It is important
in future work to assess potential ‘spillover’ effects between devices when
applying interventions meant to scaffold self-control [50, 55, 47], and so we
encourage follow-up studies to explore how our methods could be supplemented
by, e.g., smartphone logging.
Retrospective self-report: In the surveys and interviews, participants
retrospectively reported their experience, which is subject to recall biases
[44, 75]. As self-control often involves one’s past self setting goals for
one’s future self (e.g., in blocking tools), retrospective reflection is very
informative [57], but it would be interesting in future research to include
experience sampling methods to assess in-the-moment experience [76].
Granular interventions and usage measures: Standard measures of Facebook use
were not optimal for assessing granular interventions on laptop only: most
measures consider global use, and factor into broad dimensions. For example,
we found the Passive and Active Facebook Use Measure’s overall dimensions too
broad to capture the behavioural changes our interventions introduced. We flag
this as a consideration for future study designs.
Sampling: Our sample size was restricted, to allow us to conduct interviews
with all participants, and further research is required to assess whether our
exploratory results will replicate (ideally in pre-registered studies with
minimum sample size guided by our effect size estimates, cf. [18]). Moreover,
our recruitment was restricted to university students. Whereas previous
research suggests that struggles with Facebook use are particularly pronounced
in this population, and that finding effective interventions in this
population therefore is important, further research is needed to assess how
our findings might generalise. Finally, our recruitment process may have
selected for participants who were highly motivated to change their use of
Facebook and/or who used it extensively. Motivation is central to self-control
[40], but we did not assess this explicitly. Our participants’ baseline levels
of logged use, and scores on the Multidimensional Facebook Intensity Scale,
were fairly average compared to previous studies ([69, 88], see supplementary
analysis on osf.io/qtg7h), future work will benefit from explicitly measuring
participants’ level of motivation.

##  7 Conclusion

Imagining what success for digital self-control on Facebook and beyond looks
like is not an academic exercise, but a practical and urgent concern as
evidenced by the recent hearing on ‘Persuasive Technology’ in the US senate
[85], and a UK All Party Parliamentary Group’s call for a ‘duty of care’ to be
established on social media companies [4]. We encourage future HCI work in
this space to assess possible design interventions with open and transparent
research methods, to provide the evidence base needed to assist regulators in
moving towards a benevolent future [34].

##  8 Acknowledgements

We thank Felix Epp for assistance with the ROSE extension; Michael Inzlicht
and Nick Yeung for feedback on the study design; and Nadia Flensted Høgholt
for feedback on the study design, participant communication, and design of
Facebook usage visualisations.

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