Successfully reported this slideshow.
Your SlideShare is downloading. ×

The Race Towards Digital Wellbeing: Issues and Opportunities

Ad

e-Lite
https://elite.polito.it
THE RACE TOWARDS DIGITAL WELLBEING: ISSUES AND OPPORTUNITIES
ALBERTO MONGE ROFFARELLO, LUIG...

Ad

ADDICTIVE BEHAVIOR
[BILLIEUX ET AL. 2015, DING ET AL. 2016]
SOCIAL INTERACTION
[TURKLE 2011, LEE ET AL. 2014, KO ET AL. 20...

Ad

PEOPLE OFTEN PERCEIVE
THEIR EXCESSIVE
SMARTPHONE USE AS
PROBLEMATIC, AND THEY
ARE WILLING TO ADOPT
DIFFERENT STRATEGIES TO...

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Ad

Check these out next

1 of 65 Ad
1 of 65 Ad

The Race Towards Digital Wellbeing: Issues and Opportunities

Download to read offline

Presentation of the paper "The Race Towards Digital Wellbeing: Issues and Opportunities" at the 2019 CHI Conference on Human Factors in Computing Systems, held in Glasgow, UK.

Presentation of the paper "The Race Towards Digital Wellbeing: Issues and Opportunities" at the 2019 CHI Conference on Human Factors in Computing Systems, held in Glasgow, UK.

More Related Content

The Race Towards Digital Wellbeing: Issues and Opportunities

  1. 1. e-Lite https://elite.polito.it THE RACE TOWARDS DIGITAL WELLBEING: ISSUES AND OPPORTUNITIES ALBERTO MONGE ROFFARELLO, LUIGI DE RUSSIS
  2. 2. ADDICTIVE BEHAVIOR [BILLIEUX ET AL. 2015, DING ET AL. 2016] SOCIAL INTERACTION [TURKLE 2011, LEE ET AL. 2014, KO ET AL. 2016] DISTRACTION [DABBISH ET AL. 2011, OULASVIRTA 2010]
  3. 3. PEOPLE OFTEN PERCEIVE THEIR EXCESSIVE SMARTPHONE USE AS PROBLEMATIC, AND THEY ARE WILLING TO ADOPT DIFFERENT STRATEGIES TO MITIGATE SUCH A BEHAVIOR
  4. 4. MANY DIFFERENT MOBILE APPS ARE DESIGNED AS TOOLS FOR CHANGING USERS’ BEHAVIOR WITH SMARTPHONES
  5. 5. WE’RE COMMITTED TO GIVING EVERYONE THE TOOLS THEY NEED TO DEVELOP THEIR OWN SENSE OF DIGITAL WELLBEING. SO THAT LIFE, NOT THE TECHNOLOGY IN IT, STAYS FRONT AND CENTER GOOGLE- DIGITAL WELLBEING INITIATIVE
  6. 6. 1. Which functionality do contemporary digital weelbeing apps have? 2. Are they effective and appreciated? 3. Do they have a relevant impact on users’ behavior?
  7. 7. 1. FUNCTIONALITY REVIEW (N = 42)
  8. 8. 1. FUNCTIONALITY REVIEW (N = 42) 2. REVIEWS’ ANALYSIS (N = 1128)
  9. 9. 1. FUNCTIONALITY REVIEW (N = 42) 2. REVIEWS’ ANALYSIS (N = 1128) 3. IN-THE-WILD STUDY (N = 38)
  10. 10. An overall perspective of contemporary mobile apps for changing smartphone behavior 1. FUNCTIONALITY REVIEW (N = 42) 2. REVIEWS’ ANALYSIS (N = 1128) 3. IN-THE-WILD STUDY (N = 38)
  11. 11. 1. FUNCTIONALITY REVIEW (N = 42) 2. REVIEWS’ ANALYSIS (N = 1128) 3. IN-THE-WILD STUDY (N = 38)
  12. 12. INTERVENTIONS 1. FUNCTIONALITY REVIEW TRACKING AND VISUALIZING DATA
  13. 13. INTERVENTIONS Charts 60% 1. FUNCTIONALITY REVIEW
  14. 14. INTERVENTIONS Time spent (phone) 52% Time spent (app) 48% Charts 60% 1. FUNCTIONALITY REVIEW
  15. 15. INTERVENTIONS Phone Unlocks 27% Time spent (phone) 52% App Checking 15% Time spent (app) 48% Charts 60% 1. FUNCTIONALITY REVIEW
  16. 16. INTERVENTIONS Time spent (phone) 52% Recap 38% Time spent (app) 48% Charts 60% 1. FUNCTIONALITY REVIEW Phone Unlocks 27% App Checking 15%
  17. 17. INTERVENTIONS 1. FUNCTIONALITY REVIEW TRACKING AND VISUALIZING DATA
  18. 18. TRACKING App & Phone Timers 26%-31% 1. FUNCTIONALITY REVIEW
  19. 19. TRACKING App & Phone Timers 26%-31% App & Phone Blockers 15%-26% 1. FUNCTIONALITY REVIEW
  20. 20. TRACKING App & Phone Timers 26%-31% App & Phone Blockers 15%-26% Social Comparison 14% Motivational Quotes 12% Rewards 10% 1. FUNCTIONALITY REVIEW
  21. 21. 1. FUNCTIONALITY REVIEW (N = 42) 2. REVIEWS’ ANALYSIS (N = 1128) 3. IN-THE-WILD STUDY (N = 38)
  22. 22. 1. FUNCTIONALITY REVIEW (N = 42) 2. REVIEWS’ ANALYSIS (N = 1128) 3. IN-THE-WILD STUDY (N = 38)
  23. 23. 2. REVIEWS’ ANALYSIS Why Users Like Digital Wellbeing Apps? useful for different use cases helpful for controlling unhealthy behaviors
  24. 24. GREAT TOOL TO FOCUS AND GET DOWN TO YOUR WORK. MADE ME MORE AWARE OF HOW I AM REALLY WORKING AND HOW MUCH I “THINK” I WAS WORKING. useful for different use cases
  25. 25. I USE THIS EVERY DAY TO TRACK MY SLEEP, ODDLY ENOUGH (SLEEP APPS DON’T ACCOMPLISH WHAT I NEED). THIS CONSISTENTLY SHOWS EXACTLY WHAT I NEED TO BE SURE I WAS ASLEEP. useful for different use cases
  26. 26. 2. REVIEWS’ ANALYSIS Why Users Like Digital Wellbeing Apps? useful for different use cases helpful for controlling unhealthy behaviors
  27. 27. I LIKED THE POSSIBILITY TO SEE HOW MUCH TIME I WASTE ON THE SMARPHONE, BUT AT THE SAME TIME THIS SHOCKED ME. I COULD NOT IMAGINE SUCH A THING. helpful for controlling unhealthy behaviors
  28. 28. A VERY SIMPLE YET USEFUL APPLICATION. IT HELPS ME TO TRACK MY TIME USING SMARTPHONE AND THIS APP ACTUALLY HELPED ME TO RECONSIDER MY TIME AND SPEND IT ON OTHER PRODUCTIVITY TASK. helpful for controlling unhealthy behaviors
  29. 29. HAVE FOUND VALUE IN THIS APP SINCE INSTALLING IT. I AM HOPING THAT AFTER A FEW MONTHS OF USE, I WILL NO LONGER NEED THE APP TO REMIND ME TO BE MORE DELIBERATE IN THE USE OF MY PHONE. helpful for controlling unhealthy behaviors
  30. 30. bypassable solutions 2. REVIEWS’ ANALYSIS Why Users Dislike Digital Wellbeing Apps? missing functionality
  31. 31. THE APP IS GOOD BUT IT IS NOT ABLE TO STOP ME TO OPEN THE APPS I AM ADDICTED TO...I CAN JUST SIMPLY UNINSTALL THIS APP IF I WANT TO USE THE RESTRICTED APPS. Bypassable solutions
  32. 32. THE PASSWORD TO THIS APP IS WITH MY WIFE, EVERY THIRD DAY I’M ASKING HER TO LOCK. THIS IS LIKE AN ANNOYING EXPERIENCE. Bypassable solutions
  33. 33. I LOVE THIS APP. MAKES BREAKING MY ADDICTION TO CELL PHONE MUCH EASIER. ALTHOUGH I STILL NEED STRONG WILL OF MY OWN. Bypassable solutions
  34. 34. bypassable solutions 2. REVIEWS’ ANALYSIS Why Users Dislike Digital Wellbeing Apps? missing functionality
  35. 35. NICE APP BUT I’D LIKE TO SEE SOME ADDITIONAL FEATURES, FOR EXAMPLE IF LIKE THE APP TO AUTOMATICALLY DETECT WHEN IN A MOVING VEHICLE AND ACTIVATE. missing functionality
  36. 36. CAN YOU SHOW AVG STATS OF ALL THE PEOPLE? TO SEE IF YOU ARE WAY ABOVE THE NORMAL PEOPLE IN PHONE USAGE. missing functionality
  37. 37. 1. FUNCTIONALITY REVIEW (N = 42) 2. REVIEWS’ ANALYSIS (N = 1128) 3. IN-THE-WILD STUDY (N = 38)
  38. 38. 1. FUNCTIONALITY REVIEW (N = 42) 2. REVIEWS’ ANALYSIS (N = 1128) 3. IN-THE-WILD STUDY (N = 38)
  39. 39. 3. IN-THE-WILD STUDY
  40. 40. 3. IN-THE-WILD STUDY TRACKING AND VISUALIZING DATA
  41. 41. 3. IN-THE-WILD STUDY TRACKING AND VISUALIZING DATA
  42. 42. 3. IN-THE-WILD STUDY INTERVENTIONS
  43. 43. 3. IN-THE-WILD STUDY INTERVENTIONS
  44. 44. 3. IN-THE-WILD STUDY 39 PARTICIPANTS 22.5 mean age, 14 female
  45. 45. 3. IN-THE-WILD STUDY 39 PARTICIPANTS 22.5 mean age, 14 female time
  46. 46. 3. IN-THE-WILD STUDY 39 PARTICIPANTS 22.5 mean age, 14 female time Week 1 COLLECTION PHASE (CP) silently logging data
  47. 47. 3. IN-THE-WILD STUDY 39 PARTICIPANTS 22.5 mean age, 14 female time Week 1 Week 2 and 3 COLLECTION PHASE (CP) silently logging data INTERVENTION PHASE (IP) visualizing data and using interventions
  48. 48. 3. IN-THE-WILD STUDY
  49. 49. 3. IN-THE-WILD STUDY
  50. 50. 3. IN-THE-WILD STUDY 233,59 MIN 196,50 MIN
  51. 51. 3. IN-THE-WILD STUDY
  52. 52. 3. IN-THE-WILD STUDY 121 UNLOCKS 117 UNLOCKS
  53. 53. 3. IN-THE-WILD STUDY • LESS TIME SPENT ON SOCIAL NETWORKS 37 min (CP) vs. 33 min (IP)
  54. 54. 3. IN-THE-WILD STUDY • SAME TIME SPENT ON MESSAGING APPS 26 min (CP) vs. 25 min (IP) • LESS TIME SPENT ON SOCIAL NETWORKS 37 min (CP) vs. 33 min (IP)
  55. 55. 3. IN-THE-WILD STUDY • SAME NUMBER OF «COMPULSIVE» SESSIONS 49 (CP) vs 52 (IP) • SAME TIME SPENT ON MESSAGING APPS 26 min (CP) vs. 25 min (IP) • LESS TIME SPENT ON SOCIAL NETWORKS 37 min (CP) vs. 33 min (IP)
  56. 56. FINDINGS
  57. 57. FINDINGS USEFUL FOR SOME SPECIFIC USE CASE, ONLY
  58. 58. FINDINGS USEFUL FOR SOME SPECIFIC USE CASE, ONLY FOCUS ON SELF-MONITORING
  59. 59. FINDINGS USEFUL FOR SOME SPECIFIC USE CASE, ONLY FOCUS ON SELF-MONITORING DESIGNED FOR BREAKING EXISTING HABITS
  60. 60. FINDINGS USEFUL FOR SOME SPECIFIC USE CASE, ONLY FOCUS ON SELF-MONITORING PERCEIVED AS BYPASSABLE DESIGNED FOR BREAKING EXISTING HABITS
  61. 61. FINDINGS USEFUL FOR SOME SPECIFIC USE CASE, ONLY FOCUS ON SELF-MONITORING NOT GROUNDED IN HABIT FORMATION NOR SOCIAL SUPPORT PERCEIVED AS BYPASSABLE DESIGNED FOR BREAKING EXISTING HABITS
  62. 62. e–Lite https://elite.polito.it THE RACE TOWARDS DIGITAL WELLBEING: ISSUES AND OPPORTUNITIES ALBERTO MONGE ROFFARELLO, LUIGI DE RUSSIS
  63. 63. Digital Diet App Usage Tracker Phone Usage Tracker Smartphone Addiction Avoid Distraction Screen Time KEYWORD-BASED SEARCH APP FILTERING >1000 downloads >50 reviews N = 42 digital wellbeing apps ANALYZE FUNCTIONALITY 1. FUNCTIONALITY REVIEW
  64. 64. 2. REVIEWS’ ANALYSIS THEMATIC ANALYSIS N = 1128 user reviews 50 reviews for each of the 42 digital wellbeing apps REVIEWS SCRAPING REVIEWS FILTERING >3 words >2015 English language

Editor's Notes

  • Thank you for the introduction. Today, on behalf of my co author I will present you our work on mobile apps for changing users’ behavior with smartphones.
  • Smartphones have become an integral part of our daily lives.
  • As smartphone use increases, however, so do studies about the negative impact of overusing technology. Smartphones have been found to be a source of distraction, and their excessive usage is a problem for mental health and social interaction. As a consequence, the term “smartphone addiction” has gained interest both in the literature and in mainstream media.



  • Despite using an addiction framing may not seem appropriate for widespread behaviors like mobile devices use, people often perceive their excessive smartphone use as problematic, and they are willing to adopt different strategies to mitigate such a behavior.

  • So, in response to this need, many diferent mobile apps for changing the own behavior with smartphones can be nowadays downloaded from app stores like the Google Play Store.
  • Even Google and Apple recently announced their commitment in designing technology truly helpful for everyone. They introduced, in the latest versions of their mobile operating systems new tools for monitoring, understanding, and limiting smartphone use, with the aim of promoting a more conscious use of technology. Google, in particular, called its initiative «Digital Wellbeing»
  • Despite the growing popularity of the digital wellbeing topic, however, it is yet unclear whether and how contemporary apps for changing smartphone behaviors work. This motivated us in exploring 3 research questions. So, what are the main characteristics of these apps? Are they effective and appreciated by users? Do they have a relevant impact on users’ behavior?

    So, answering these questions is fundamental to improve our knowledge of the problem and to design better digital wellbeing solutions.
  • To answer these questions, we performed 3 different studies. First, we conducted a review of the most common functionality offered by popular digital wellbeing apps.
  • Second, we conducted a thematic analysis on more than one thousand user reviews on these apps.
  • And third, we implemented our own digital wellbeing app, by integrating the most common features extracted during our functionality review, and we tested it in-the-wild.
  • Our final goal was to provide an overall perspective of contemporary mobile apps for changing behavior with smartphones, with the aim of identifying possible issues and opportunities to improve such solutions.
  • Ok, let’s start with the functionality review, that we conducted on a set of 42 popular digital wellbeing mobile applications extracted from the Google Play Store.

    3:00
  • We divided results into 2 main categories, one related to traking and visualizing user data, and the other related to interventions that users can set up to improve and personalize their smartphone use.
  • For what concern the first category, these apps typically use charts for visualizing user data, by providing different statistical summaries related to the usage of the phone, in general, or the usage of specific applications.
  • So, for example, these apps often track and visualze the time spent, in general with the phone, or with specific applications.
  • They sometimes visualize the number of times the user unlocks the phone, or the number of time the user opens a specific app.
  • Moreover, a consistent number of applications use some home-screen widgets or daily recaps to draw user attention.
  • Then, the majority of the analyzed apps provide the users with the possibility of changing their bhavior,through interventions.
  • Users can therofore set up timers to be notified when they are using the phone or a specific app for too long.
  • They can set up blockers, to block the usage of the entire phone or of a given app.
  • And they can also take a break from their devices, by silencing and locking them for a given amount of time to completely avoid distractions.
  • There are also some other less popular interventions, that range from the possibility of comparing statistics with other users, to the usage of motivational quotes and rewards.
  • After the functionality study
  • we perfomed a thematic analysis on more than one thousand user reviews left by users for the 42 apps retrived in the first study.


    4:56
  • In the analysis, we tried understand why users like or dislike applications for changing their behavior with smartphones.

    And the first reason why users like these apps is because they are useful for different use cases
  • Foe example, they are useful for situations requiring constant user attention, like studying and working, because they allow users to avoid distractions like notifications and self interruptions to, for example, check social networks.
  • Surprisingly, users also adopt such applications for use cases that are not the primary focus of these tools. An example is sleeping: according to some users, monitoring their smartphone usage is a convinient way of understanding their sleeping patterns.
  • Users also perceive digital wellbeing tools as helpful for controlling unhealthy behaviors
  • On the one hand, visualizing how much time users spent on smartphones can be shocking
  • But on the other hand, these information help users to reconsider their actions and to spend more time on other productive tasks such as studying and working.
  • In the light of these benefits, users hope that the new behaviors they started to adopt will continue even without the help of the tool. In other words, users would like to learn how to behave, thus maintaining a more consciuos use of the smartphone in the long term. Unfortunately, contemporary digital wellbeing tools focus on self-monitoring techniques and are not designed for this purpose: we can reasonably say that this hope cannot be satisfied.
  • Moreoveor, even the analyzed self-monitoring solutions are perceived as problematic, firstly because they are often not restrictive enough and can be easly bypassed.
  • Interventions like timers and blockers, for example, can always be ignored, and digital wellbeing apps can be easly unistalled. So even with a constant monitoring process, users may find it difficult to establish new behaviors for using the smartphone more consciously.
  • Users are therefore forced to use creative solutions to overcome such issues, like usig their wives for setting up secret password.
  • And so, as a consequece, despite some short-term benefits, users need a lot of willpower to coninue to use these tools.
  • So, it seems that contemporary digital wellbeing tools cannot be used to effectively change behavior in the long term, and even the same users recognize in their reviews, that the failure of these apps lies in the lack of different functionality.
  • Users, for example, suggest smarter and automatic interventions that detect the user activity.
  • Users also suggest the possibility of interacting with other users, for example to compare statistics.





    By using social approaches in these tools, people could have better awareness of normative behaviors and could also be better motivated to self-regulate their smartphone use.
  • So, with the first 2 qualitative studies we explored fuctionality and reviews, and we highlighted potential benefits and drawbacks of digital wellbeing solutions.


    8:40
  • To further understand, in a more quantitatively way, how contemporary digital wellbeing apps work, we devised a third, final study, to be conducted in-the-wild.

  • Our goal was not to explore new solutions, but to evaluate the existing ones. For this purpose, we designed our own digital wellbeing app, named Socialize, by implementing the most common features identified in our first functionality study.
  • Socialize allow users to track and visualiuze their smartphone usage data.
  • So, the upper part of the app shows information related to the usage of the phone, in general: the total time spent with the phone, the number of unlocks, and so on.

    Then, in the bottom part there is a list with some specific information for each used app.

    The user can click both on phone-level and app level information to access a more detaild view of the data, to visualize different types of charts.

    Finally, as a widget recap, Socialize constantly shows a notifcation that displays some basic information.
  • For what concerns interventions
  • With Socialize, users can set up different interventions. At phone level, they can set up timers by specifying a duration. They can also restrict the intervention for a given context, only, by specifying an activity and a location.

    In a similar way they can set up phone blockers, to block the usage of the phone in a given context.

    Users can do the same for each specific app, for example here I set up a timer on yoututube. And now, when I’m using youtube and the timer expires, I am notified with a popup, and I have the possibility of closing the app, or ignoring the intervention.


  • We tested Socialize in-the-wild by recruiting 39 participants


    10:58
  • And we set up a within-subject experiments.
  • The experiment lasted three weeks for each participant. In the first week, the collection phase, Socialize ran in the background and silently logged usage data.
  • Then, in the following 2 weeks, the intervention phase, participants could use all the functionality offered by Socialize: they could analyze statistics, setting up timers, blockers, and so on.
  • During the study, we measured, day by day, different metrics.
  • First of all, we measured the daily usage time of the smartphone
  • And we noticed that, on average, participants spent less time with their smarphones during the intervention phase.
  • Despite such a positive effect, Socialize didn’t influenced other metrics. Here the chart shows, for each day, the number of time participants unlocked their smarphones.
  • In this case, on average, participants didn’t change their behavior: they consistently unlocked their phone both in the collection and in the intervention phase.
  • Also other metrics confirmed that apps like Socialize are useful in some cases, but they fail in other situations. For example, participants who used Socialize reduced the time spent on social networks in the intervention phase
  • Unfortunately, this is not true for other types of applicatios, such as messaging apps.
  • Moreover, even with the help of Socialize, participants continued to use their smartphones very frequently, with many phone sessions at a distance of less than a minute. So, participants continued to demonstrate a, let’s say, compulsive checking behavior, even when using Socialize.
  • So, let’s summarize the findings we retrieved thanks to our 3 studies

    12:45
  • We found that contemporary apps for changing smartphones behavior are useful for some specific use cases, but they fail in other situations. The same users are often aware that such solutions are sometimes not sufficient, and that they need a lot of willpower to coninue to use these tools.
  • This could be due to the fact that these apps focus, by construction, on self-monitoring techniques. While self-tracking plays an important role in the behavior change process, it doesn’t support the formation of new habits, and it strongly depends on the monitoring behavior. Once the monitoring process stops, however, for example because the user gets bored, the behavior can revert to pre-interventions levels.
  • So, the digital wellbeing apps we analyzed are designed for breaking existing habits, rather then developing new behaviors. Breaking habits, however, is frustrating, and users need to be continuously motivated to keep on the monitoring process.

  • Moreover, such tools are often perceived as bypasable and not restictive enough. Even in the in-the-wild study of Socialize,for example, participants ingnored the majority of the intervetions they defined.
  • So, at the end, we can conclude that contemporary digital wellbeing apps are not grounded in habit formation nor social support literature.

    We claim that, besides focusing on self-monitoring, researchers should also take advantage of the habit formation literature. Habit formation could play an important role in digital wellbeing apps, by supporting behavior change and ensuring its long-term effects. One could envision, for example, the usage of goals and trigger events: new behaviors linked with some specific routine are in fact generally easier to remember, and each repetition reinforces that association, so this increases the probability of repeating the behavior in the future.

  • This concludes my presentation, thank you for your attention, and I’m open to questions
  • The study was composed of 3 main parts. In a first step, we performed a keyword-based search on the Google Play Store to extract a set of mobile apps explicitly designed for changing behavior with smartphones.

    Then we filtered the retrieved applications, by considering only apps with more than one thousand downloads, and with more than 50 user reviews.

    At the end, we perfomed our functionality review on a set of 42 digital wellbeing mobile applications.
  • We started by scraping 50 reviews for each of the 42 apps retrieved in the first study.

    Then we filitered the reviews by keeping only the most recent comments in English, and by removing short reviews that provided limited information

    At the end, we obtained a dataset of more than one thousand reviews.

×