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Designing and Evaluating Behaviour Change
Technologies for and in the Real World
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Evangelos Karapanos
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Designing for Experience
How can technology provide a pleasurable
experience?
1940s
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1979 Apple II
Designing for Usability
1979 VisiCalc - “killer
app” for Apple II
1981 IBM XT/AT
1980s
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Designing for Experience
How can technology provide a pleasurable
experience?
2000s
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Designing for Wellbeing
How can technology have a positive impact on
people’s lives?
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Personal informatics
tools that helps us track our behaviours,
emotions, thoughts
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Physical activity
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Finances
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Time
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Behaviour Change Technologies
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Health
Human behaviour a key predictor over the
long-term
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Diabetic patients skip their insulin
medication 25% of the time
25,000 people a year go blind
Hundreds of thousands lose limbs, every year,
for something that's solvable.
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Physical Activity
Over 80% of the world's adolescent
population is insufficiently physically active.
Insufficient PA is a key risk factor for
noncommunicable diseases (NCDs) such as
cardiovascular diseases, cancer and diabetes.
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NC (chronic) diseases account for 40% of
mortality cases and 75% of health care costs
worldwide. Estimated increase of 42% by 2023.
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From cure to prevention
Gordon Brown: ”NHS [National Health Service] of
the future [being] one of patient power, with
patients engaged and taking control over their
own health and healthcare".
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How to design for Behaviour Change
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Theoretically and Empirically grounded
design
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Theoretically grounded design
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Evidence-based Behaviour Change Techniques
Michie et al. (2013)
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The simple acts of measuring one's target
behavior and comparing it to an external
standard or goal can result in lasting
improvements to that behavior.
Self-monitoring
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–Johnny Appleseed
self-monitoring
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Self-setting specific, proximal, and
difficult goals results in increased
performance
Goal Setting Theory
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Empirically grounded design
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Do our assumptions hold?
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Evaluating technologies in the wild
Interaction logs Wearable cameras
Experience
Sampling
Interaction logs
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Evaluating technologies in the wild
Interaction logs Wearable cameras
Experience
Sampling
Wearable cameras
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Evaluating technologies in the wild
Interaction logs Wearable cameras
Experience
Sampling
Experience sampling
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Evaluating technologies in the wild
Interaction logs Wearable cameras
Experience
Sampling
Interaction logs
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Habito
!! !
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goal setting
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historical data
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informational and
persuasive messages
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256 users downloaded Habito over
the course of 10 months
none of these users were recruited or rewarded towards usage
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How can we design glanceable feedback?
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Do our assumptions hold?
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1. Designed for all?
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stages of behavior change
questionnaire
understanding how different stages of ‘readiness’ impacted adoption
precontemplation currently have no intention of being active
contemplation not active but intend to be soon
preparation trying, but not regularly active
action regularly active, but for less than 6 months
maintenance regularly active for 6 months or more
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precontemplation
5 of 36, 14%
contemplation
preparation
action
maintenance
14 of 26, 54%
19 of 33, 58%
7 of 24, 29%
4 of 19, 21%
Readiness for use:
motivation and adoption
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2. Goal setting… or, accepting?
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Self-setting specific, proximal, and difficult
goals results in increased performance
Goal Setting Theory
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Self-setters walked more
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Self-setters were only 31% of users
The rest just accepted the preset goal
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3. Behaviour change through
Knowledge or self-regulation?
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Usage sessions
historical information was only accessed
in 30% of all usage sessions
even more, 87% of these concerned an ongoing day
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Glances
sessions in which users open and
close Habito with no additional
actions or inputs
57%, 5 sec
Review Engage
22%,12 sec 21%,45 sec
sessions with at least one
additional actions and last
up to 22 seconds
sessions with at least one
additional actions and last
more than 22 seconds
Usage sessions
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Glances
73%
Review Engage
18% 9%
Usage sessions
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No content
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participants were more
likely to initiate a new walk
when seeing a low number
of steps in the last hour
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participants were more
likely to initiate a new walk
when seeing a low number
of steps in the last hour
Participants who saw they walked
10 min or less over the past hour
had a 77% chance of starting a
new walk in the next 5 min
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Dual process theory
System 1 - automatic mind (intuition)
System 2 - rational mind (analytical reasoning)
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94% (165 of 176) systems designed
for the rational mind
Adams et al., 2015
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Behaviour change through
Knowledge or self-regulation?
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4. Unexpected things are to be expected
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participants were more likely to initiate a new
walk when closely ahead or behind of
others
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Hidden costs of self-monitoring
While self-monitoring led to short-term increase
in steps, it also lead to a decrease in
enjoyment of walking
Etkin (2015)
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Overjustification effect
When extrinsic motivations overshadow
intrinsic ones
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No matter how theoretically grounded your design is
test it in real life!
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No matter how theoretically grounded your design is
test it in real life!
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Question what your assumptions are, about
how people will use your product
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Question what your assumptions are, about
how people will use your product
Thank you
Evangelos Karapanos
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http://persuasive.cut.ac.cy/