1. Jaejeung Kim, Hayoung Jung, Minsam Ko, Uichin Lee
GoalKeeper: Exploring Interaction Lockout Mechanisms for Regulating Smartphone Use
Thanks for the introduction.
Jaejeung Kim, Hayoung Jung, Minsam Ko, Uichin Lee

2. Ever tried to reduce smartphone use?
Have you ever tried to reduce your smartphone use? (pause) I tried many times! What happened next?
Ever tried to reduce smartphone use?

3. We often fail.
Yes, I know. We often fail!

4. We often fail.
But why?
But why that happens?

5. Rational “long-run self”
Conflicting two-selves
(Fudenberg and Levine, 2006)
Initial goal setting when you are
Rational “long-run self”
Impulsive “short-run self”
(e.g., “I will spend less than an hour a day on smartphone”)
Later suffer from
According to the dual-self model, we have conflicting two-selves residing in us!
>> We have a Spock-like “rational” long-run self
>> At the same time, we have a Homer Simpson like “impulsive” short-run self
When it comes to smartphone usage, you have “initial goal setting when you’re in the rational state >> by committing to yourself, “I’ll spend less than an hour a day”
However, later you suffer from the “impulsive” self >>> by watching Youtube videos endlessly
Which leads to goal failure
Drew Fudenberg and David K Levine A dual-self model of impulse control. American economic review 96, 5 (2006), 1449–1476.
(e.g., watching multiple YouTube videos consecutively)
Which leads to goal achievement failure

6. Technical Support for Self-Regulation
persuasive
(e.g., self-tracking, feedback, reinforcement)
restrictive
(e.g., device lockout for 30 minutes)
Commitment Intensity
LOW
HIGH
HCI researchers and practitioners designed various technical support tools for self-regulation,
>> which requires varying levels of users’ commitment.
Ranging
>> from minimal commitment with persuasive support like self-tracking and feedback
>> to high commitment with restrict support like device lockout

7. Technical Support for Usage Regulation: Persuasive
“Persuasive technology is designed to change attitudes or behaviors of the users through persuasion and social influence, but not through coercion” [B.J. Fogg, 2002]
Usage tracking/reflection
RescueTime, ManicTime, Slife
Status bar, widgets reduced non-work related web usage [Lottridge et al. 2012]
<RescueTime>
Goal setting and reinforcement
MyTime allows users to set daily goals, and sends timeout messages when violated [Hiniker et al., CHI 2016]
Awarding badges to help reinforce behavior maintenance [Ostashewski et al. 2015]
<MyTime>
Many tools support persuasive features like usage tracking/reflection w/ status bar, widgets
Also these tools often help you set the goals and reinforce your goal achievements with badges and social ranking

8. Technical Support for Usage Regulation: Restrictive
Microboundary
A small obstacle prior to an interaction (e.g., a short lockout) creates a brief moment for reflecting on what users are doing [Cox et al., CHI16] [Kim et al., CHI19]
<LockNType CHI’19>
Temporary Blocking
Voluntarily blocking phone use (e.g., 1 hour lockout) decreased screen time and lowered the burden of managing interruptions [Ko et al., CSCW15]
<NUGU CSCW’15>
There are also restrictive tools, which require higher commitment
** introduce a brief discomfort called microboundary to help users to be more mindful
** let users temporarily block their phone use
** let users to set screen time goals, but punish them with device lockout if they failed to meet the goals
Enforcing Lockouts
Coco’s Video restricts children from watching videos by locking out the target app for 3 min [Hiniker et al., CHI18]
Apple’s Screen Time (recently added)
<Coco’s Video CHI’18>

9. Technical Support for Usage Regulation: Restrictive
Microboundary
A small obstacle prior to an interaction (e.g., a short lockout) creates a brief moment for reflecting on what users are doing [Cox et al., CHI16] [Kim et al., CHI19]
<LockNType(CHI’19)>
Temporary Blocking
Voluntarily blocking phone use (e.g., 1 hour lockout) decreased screen time and lowered the burden of managing interruptions [Ko et al., CSCW15]
<NUGU CSCW’15>
This work focuses on “goal setting and device lockout” >> which are very popular among recent intervention software
Enforcing Lockouts
Coco’s Video restricts children from watching videos by locking out the target app for 3 min [Hiniker et al., CHI18]
Apple’s Screen Time (recently added)
<Coco’s Video, CHI’18>

10. Key Concept of Restrictive Approaches
Commitment Device
"voluntarily imposed restriction as an attempt to increase the likelihood of achieving goals” [Rogers et al., 2014]
The key concept of such restrictive approaches is based on commitment device
> it is a voluntarily imposed restriction as an attempt to increase the likelihood of accomplishing goals

11. Key Concept of Restrictive Approaches
Commitment Device
"voluntarily imposed restrictions as an attempt to increase the likelihood of achieving goals” [Rogers et al., 2014]
Device lockout as a commitment device for better self-regulating smartphone use
Indeed, device lockout is used as a form of commitment devices for better self-regulating smartphone use

12. Research Goal
Comparatively understand how different commitment intensities of device lockout influence goal setting and screen time
However, none of the prior studies examine
> How different commitment intensities of device lockout influence goal setting and screen time

13. Research Questions RQ1: Goal Settings
How do people set screen time goals with different degrees of lockout intensities (i.e., non-lockout, weak-lockout, strong-lockout)?
RQ2: Screen Time
How do different degrees of lockout intensities influence screen time?
RQ3: User Experiences
What are the user experiences, preferences and perceived emotions with different methods?
Regarding goal setting, we answer “
Regarding screen time, we answer “
Regarding user experience aspects, we answer “

14. GoalKeeper: Goal Setting
Voluntarily set weekday & weekend screen time goal
Daily Screen Time Goal
Allowed to modify their goal only once
To answer these questions, we designed “GoalKeeper”
First of all, GoalKeeper allows you to set daily screen time goals for weekdays and weekend
We recommended users with achievable goals based on their usage history
Also, we allowed users to modify their goals only once per week
Recommendation of 10~20% reduction time (based on user’s baseline usage data)

15. GoalKeeper: Intervention (After Exceeding Screen-time Goals)
Commitment Device Intensity
LOW
HIGH
#1: Non-Lockout
Show a pop-up message for creating micro-boundaries (i.e., unlocking, or every 15 min of more use)
You have exceeded your screen time goal!
Screen Time Goal: 35 min Current Use Time: 50 min
15 minutes have been exceeded
Will you continue to use?
#2: Weak-Lockout
Lockout followed by 15 min use allowance, but lockout time increments after each use (i.e., 1, 5, 15, 30, 60 min)
After a 5 min lockout, you will be given additional 15 min for use. Next lockout duration will be increased to 15 min.
#3: Strong-Lockout
Device is completely locked out until midnight
You have reached your screen time goal. You can use after midnight.
We tested three different commitment devices, when users exceed screen time goals,
Non-lockout condition: it only shows a pop-up message to discourage further use
Weak-lockout condition: it is more or like “password lockout” in that it only temporarily locks out a user’s phone
>>> But lockout duration keeps increasing after each 15 min of use
Strong-lockout: completely locks out your phone until midnight
(Of course you can still make phone calls)

16. Experiment Participants Within-group experiment design
44 students (mean age = 21.7; sd = 3.4) recruited in campus (8 dropped)
Within-group experiment design
Used three different versions each week; counter-balanced (6 groups)
Four-week, in-situ deployment
Baseline period
Intervention period
We recruited 44 students and conducted four week in-situ deployment
We designed a within-group experiment
We had 1 week for baseline measurement, and three weeks for treatments
>> We counter-balanced the order effects by creating six groups
>> Each group used three conditions in a different sequence
Week 1
Week 2
Week 3
Week 4
Usage logging without intervention
Exit Survey
Exit Interview
Counter-balanced (6 groups)
Non-Lockout
Weak-Lockout
Strong-Lockout

17. RQ1. Screen Time Commitment: Initial Goals
Weekday (RM ANOVA)
F (2, 34) = 2.537, p = .094, η2 = .130
Weekends (RM ANOVA)
F (2, 34) = 1.331, p = .278, η2 = .073
Daily Screen Time Goal (min)
None (Pop-up)
Weak-Lockout
Strong-Lockout
First of all, we checked initial goals across different conditions in both weekdays and weekends.
As you can see here, we do not find any significant differences >> across different conditions and between weekdays/weekends
Daily Screen Time Goal
No statistical differences observed on initial goal setting

18. RQ1. Screen Time Commitment: Modified Goals20 15 8
Pop-up
Weak-Lockout
Strong-Lockout
Participants expressed concerns over being locked out (particularly in urgent/necessary situations, and out-of-routine contexts such as short trips)
We then checked how many users actually modified their goals.
In our experiment, users were given one chance of modification per week.
We found that stronger restriction resulted in more users modifying their goals
From our interview, our participants expressed concerns over being locked out
particularly in urgent/necessary situations, and out-of-routine contexts such as short trips
Stronger restriction  more users modified their goals

19. RQ2. Impact of Lockouts on Screen Time
Mean Daily Screen Time (min)
Mean Daily Screen Time (min) =
None (Pop-up)
Weak Lockout
Strong Lockout
None (Pop-up)
Weak Lockout
Strong Lockout
We then checked the impact of lockouts on screen time on weekday and weekend.
In both cases, screen time decreased when compared with baseline conditions
Stronger lockout intensity resulted in less screen time only on weekdays
> No significant different was observed during weekends
Weekday Screen Time Comparison
Weekend Screen Time Comparison
Screen time decreased across different conditions
Stronger lockout intensity, less screen time (only on weekdays)

20. RQ3. User Experiences and Preferences
Mean Perceived Frustration
None (Pop-up)
Weak Lockout
Strong Lockout
None (Pop-up)
Weak Lockout
Strong Lockout
Finally, we checked user experiences and preferences.
> Users’ feeling of frustration and coercion increased > as lockout intensity increases
Perceived Frustration (NASA-TLX) (max 100 points)
Perceived Coercion (5 point Likert scale)
F (2, 34) = 2.227, p = .023*, η2 = .199
F (2, 34) = , p < .000**, η2 = .542
Frustration/coercion increased as lockout intensity increases

21. RQ3. User Experiences and Preferences
66.7%
None (Pop-up)
Weak Lockout
Strong Lockout
Despite frustration and coercion,
> we found that users preferred “lockout” mechanisms for self-regulating smartphone use,
> and weak-lockout was most preferred
User Preferences (post-hoc survey)
Weak-lockout intervention was most preferred among users

22. Effective vs. Acceptable
Commitment Device should be …
Effective vs. Acceptable
in achieving a goal
for continued use
Our results showed that
> device lockouts are effective in achieving screen time goals
> at the same time, device lockouts should be designed
>>> so that they are acceptable for continued use
That’s why we suggest > “persuasive and flexible commitment device design for screen time management
Towards persuasive & flexible commitment device design for screen time management

23. Persuasive Commitment Device: Effectiveness
Guided, Adaptive, and Systematic Support
We can design persuasive commitment devices to improve effectiveness, by
> guiding achievable goal setting, increasing goal awareness
> as well as nudging users to try more challenging interaction lockouts
>>>>> our users often said they want to use strong lockouts
>>>>> when users need better self-regulation (like facing deadlines or exams)
Guiding Achievable Goal Setting & Increasing Goal Awareness
Participants tended to underestimate usage time (~40 min) and neglect their goals
 Guide users to set reasonable goals and increase goal awareness for self-regulation
Nudging Users to Try More Challenging Interaction Lockouts
The greater the lockout intensity, the less is the smartphone screen time
 Track the users’ needs and lockout usage patterns, then gradually vary lockout intensity, by challenging users (e.g., ‘making small changes’ [H. Oinas-Kukkonen 2009])

24. Flexible Commitment Device: Acceptability
Limited, Context-Aware Flexibility Support
Flexibility w/ Clear Boundaries
V.S
Flexibility in Goal Setting/Changing but “With Clear Boundaries”
Let them set their own screen time goals (authority for goal setting)
 Yet, limited flexibility: e.g., ‘one-time’ chance of modifying a screen time goal
Flexibility by Supporting “Out-of-routine” Contexts
Needs of flexibility in out-of-routine contexts (e.g., one-day business trip)
 Context-aware flexibility support [Lee 2019] (e.g., by checking deviation from routines)
At the same time,
>> we can design flexible commitment devices to improve acceptability, By
>> allowing users to set and change their goals
>> allowing them to make exceptions on out-of-routine or urgent situations
------for that, we can use ubicomp tools such as routine detection and context-awareness
Of course, these flexibilities require “clear boundaries” so that we can ensure effectiveness

25. Commitment Device Intensity
GoalKeeper: Exploring Interaction Lockout Mechanisms for Regulating Smartphone Use
Jaejeung Kim, Hayoung Jung, Minsam Ko, Uichin Lee
Persuasive
Non-Lockout (pop-up warning)
Restrictive
Weak-Lockout (temporary lockout) Strong-Lockout (complete lockout)
Commitment Device Intensity
LOW
HIGH
Goal Setting
Screen time goals were not significantly different, but more goal modifications observed in lockout conditions
Stronger lockout is more effective (only during weekdays; no differences in weekends)
Higher perceived frustration and coercion in lockout conditions, and yet many preferred lockout conditions
Towards persuasive & flexible design for screen time management (e.g., goal setting/awareness, limited flexibility, adaptive/context-aware lockout)
Screen Time
To summarize our main contributions are
>> to experiment with different interaction lockout mechanisms
>> to provide novel design insights for screen time management using commitment devices
User Experiences
Design Implications

26. Appendix

27. (GoalKeeper System Design)
이와 함께 기존 설득적 시스템에서 많이 활동되었던 "일시적 잠금" 기능도 함께 넣어서 목표시간 기반 차단과 함께 어떻게 활용되는지도 함께 보았습니다.
Usage Timeline and Statistics Screen

28. (GoalKeeper System Design)
이와 함께 기존 설득적 시스템에서 많이 활동되었던 "일시적 잠금" 기능도 함께 넣어서 목표시간 기반 차단과 함께 어떻게 활용되는지도 함께 보았습니다.
Self-triggered limit
“Break Button” is a self-triggered, temporal break mode
Widely used timeboxing technique in persuasive computing domain
[NUGU, CSCW’15; Lock N’ Lol, CHI’16; Lets Focus, Ubicomp’17; PomodoLock, Ubicomp’17; Coco’s Video, CHI’18)

29. RQ1. Goal Time Commitment Behaviors
Weekday:
- Non-ilm: 258.3
<Weekday >
<Weekend >
Modification differences in the weekend goals between the non-ILM and strong-ILM conditions were significant

30. RQ3. User Experiences and Preferences
Positives
Negatives
Non-Lockout
Provided a sense of alert not to use
Able to voluntarily mitigate use
Easy to ignore
Not enough “power” to trigger “action”
Weak-Lockout
Induced natural task change from device to non-device
Appropriate incentives (chance to use) and penalties
Continued phone usage by waiting for unlock
사용자 인터뷰를 통해 각 버젼에 대한 긍정/부정적 측면들을 알아보았고, 단순 경고 버젼은 그냥 무시해버리고 계속 사용하는 경우가 많다고 했습니다. 약한 잠금은 적절한 잠금 벌칙과 허용이 섞여 있어서 선호되었지만 일시적 잠금을 당하면서도 잠깐 사용 가능한 시간을 노리고 계속 사용한다는 피험자도 있었습니다. 마지막으로 강한 잠금은 강력하게 사용을 줄일 수 있는 역할을 한다고 하며 긍정적으로 평가된 반면 사용 시간을 초과할 까봐 걱정하는 부정적인 감정을 호소하는 경우도 있었습니다.
Strong-Lockout
Strong reduction of use time
Enforced careful planning of use
Perceived burden of being locked
Arousal of negative emotion during the locked period
Attempts of workarounds observed

31. RQ3. User Experiences and Preferences
선호도 측면에서는 전체적으로 약한 잠금이 가장 선호되었습니다. 이 안에서 스마트폰 중독군과 비중독군을 나누서 살펴보았을 때는 중독군은 잠김에 대한 부정적인 감정으로 인해 단순 경고버젼을 월등히 선호하는 경향이 있었고 비중독은 약한 잠금을 가장 선호했습니다.
<Preferences evaluated by addiction/non-addiction groups>
Addiction group felt more negative about lockout, preferring non-lockout more than the non-addiction group.

32. RQ2. Impact of Lockouts on Screen Time
<Weekday Screen Time Comparison>
<Weekend Screen Time Comparison>
Weekday: Baseline vs. Intervention
Non-ILM: [t(35) = 1.739, p = .091, d = 0.21]
Weak-ILM: [t (35) = 2.801, p = .008**, d = 0.35]
Strong-ILM: [t (35) = 3.507, p = .001**, d = 0.54]
Weekend: Baseline vs. Intervention
Non-ILM: [t(35) = 3.656, p = .001**, d = 0.56]
Weak-ILM: [t(35) = 3.440, p = .002**, d = 0.51]
Strong-ILM: [t (35) = 2.755, p = .009**, d = 0.53]
가장 중요한 실제 스마트폰 사용 시간의 차이를 봤습니다. 베이스라인 대비해서 주중-경고버젼을 제외한 나머지 모두 다 사용 시간이 줄었습니다.
Screen time decreased in all conditions compared to the baseline, except for the weekday/non-lockout condition

33. RQ2. Impact of Lockouts on Smartphone Use Time
<Weekday Use Time>
<Weekend Use Time>
Weekday Use Time (RM ANOVA)
[F (2, 34) = 5.114, p = .011*, η2 = .231]
Weekend Use Time (RM ANOVA)
[F (2, 34) = 0.108, p = .898, η2 = .006]
세가지 버젼간의 차이가 있는지는 반복측정아노바로 보았습니다. 사후분석 결과 주중의 경고버젼과 강한 잠금 버젼간의 차이만 유의미했고 나머지는 유의미하지 않았습니다. 또한 예상대로 강한 잠금일수록 사용 시간이 더 적었습니다.
주말 시간의 사용의 차이는 없었습니다.
Post-hoc comparisons (Bonferroni)
non/strong-ILMs (p=.008**); weak/strong-ILMs (p=.068), non/weak-ILM (p=.223)
Only weekday interventions were statistically significant.
The stronger lockout intensity is, the less time spent.

34. RQ3. User Experiences and Preferences
Perceived Frustration (NASA-TLX) (max 100 points)
Perceived Coercion (5 point Likert scale)
사용 경험 중 짜증이나 강제성을 얼마나 느꼈는지에 대해 알아보았습니다. 짜증/스트레스의 경우 사후분석 결과 경고와 강한잠금간 유의미한 차이를 보였습니다. 강한 잠금일수록 또 높은 짜증/스트레스를 받았고, 강제성은 셋간 모두 유의미한 차이가 있었습니다. 역시 경고-일시적 잠금-강한 잠금 순이었습니다.
perceived frustration using an item from the NASA-TLX assessment. We slightly modified the item as follows: “When you are using this application to achieve the goal of reducing your smartphone use, how much negative emotions, including anxiety, disappointment, pressure, and stress did you perceive?” On a scale of 0 (none) to 100 (very much)
F (2, 34) = 2.227, p = .023*, η2 = .199
F (2, 34) = , p < .000**, η2 = .542
Statistical difference in frustration between non/strong lockout
Perceived coercion increased as the lockout intensity increased