Many of the most effective behavior change principles can only be implemented in technologies that adapt to users based on their feedback, such as coaching websites, wearable technologies, and apps that help us make lifestyle changes. In this session, Brian Cugelman, PhD will discuss his communication-based approach to persuasive design, and discuss the interactive parts of his behavior change taxonomy. You’ll learn which psychological principles can only be used when you design two-way interactive technologies, and which options are totally “off the table” when you opt to design one-way technologies. You’ll enjoy an interactive presentation followed by an open Q&A session. Brian Cugelman, PhD obtained his Doctorate with the Statistical Cybermetrics Research Group, a world-leading team of Internet researchers, where he focused on the science of digital behavior change. As a scientist, his research has been published in JMIR, the world’s top e-health journal. Brian has advised numerous organizations on using technology for individual and social-level change, with the Pentagon inviting Brian to present his research to their Cyber Influence Project. Brian ran his first online behavior change campaign in 1998, with his early work in online social change recognized by the United Nations General Assembly. Dr. Cugelman teaches the science of digital behavior change through his firm AlterSpark, and provides consulting services on behavior change technology and data science.

1. THE PSYCHOLOGY OF FEEDBACK
INSPIRATION FOR ASS-KICKING WEARABLES
Action Design NYC
Brian Cugelman, PhD
@cugelman
New York City
30 March 2015

2. BRIAN CUGELMAN, PHD
2
imcba.comalterspark.com

3. AGENDA
• Collecting data (input)
• Data science (processing)
• Interventions (Output)
• Cooking and digital psychology
• Domain 7. Audience Feedback
3

4. STARTING QUESTION
What feedback can you capture,
that’s useful to your users, that can
inspire them to take positive action?
How can you add feedback-based
persuasive design principles to
boost your impact?

5. Mind
Body
Relations
Ambience
Collecting data
(input)
•Research-based feedback
•Manual data capture
•Interaction-based data
capture
•Automated data porting
•Sensor-based data
capture
Data science
(processing)
•Algorithms
•Statistics
•Correlations
Interventions
(Output)
Hardware
•Mobile
•Wearable devices
•Desktop
Software
•Applications

6. COLLECTING DATA (INPUT)
6

7. DATA CAPTURE BY SENSORS
• A transducer that
converts a signal in
one form of energy to a
signal in another
• Detects changes in
quantities and
converts them into an
output, generally an
electrical or optical
signal

8. SENSORS WITH HUNDREDS OF SUB-CATEGORIES
AND THOUSANDS OF OPTIONS
• Thermal, heat, temperature
• Acoustic, sound, vibration
• Electric current, electric potential, magnetic, radio
• Environment, weather, moisture, humidity
• Flow, fluid velocity
• Ionizing radiation, subatomic particles
• Position, angle, displacement, distance, speed,
acceleration
• Optical, light, imaging, photon
• Pressure
• Force, density, level
• Proximity, presence
• Chemical

9. E-HEALTH SENSOR PLATFORM V2.0
(ARDUINO AND RASPBERRY PI)
1. Pulse,
2. Oxygen in blood (SPO2)
3. Airflow (breathing)
4. Body temperature
5. Electrocardiogram (ECG)
6. Glucometer
7. Galvanic skin response (GSR
- sweating)
8. Blood pressure
(sphygmomanometer)
9. Patient position
(accelerometer)
10. Muscle/eletromyography
sensor (EMG)
10 different sensors in a dev kit for about $500

10. DATA SCIENCE (PROCESSING)
10

11. PROCESSING DATA
Detecting
• Mind
• Body
• Ambience
• Relations
Challenge
• Making sense of complex
multi-device signals
• Lots of data: 400 MB/day from
a mobile with millions of
records on full throttle
• Accurately detecting events
that matter to people
• Building human centered
algorithms 11

12. INTERVENTIONS (OUTPUT)
12

13. COOKING AND DIGITAL PSYCHOLOGY
13

14. INFLUENCE CAPACITY COMES FROM
PERSUASIVE INGREDIENTS BLENDED INTO
OPTIMIZED RECIPES
Pilot 2011

15. OPTIMIZATION: THE MIX OF INGREDIENTS THAT
ACHIEVES THE MOST IMPACT WITH THE LEAST EFFORT
15
Number of persuasive ingredients
Influencepotential
How do you know when you have too few or too many?
Too
few
Too
many
Just right
Cugelman, B., Thelwall, M., & Dawes, P. (2011). Online Interventions for Social Marketing Health
Behavior Change Campaigns: A Meta-Analysis of Psychological Architectures and Adherence Factors.
Journal of Medical Internet Research, 13(1), e17.

16. INTERACTIVE INFLUENCE MODEL
16

17. WHAT INGREDIENTS MAKE MOTIVATING
WEARABLE TECH
17

18. Feedback loop (self-regulation)
18
Compare goal to
performance
(reaction)
Behavioral
outcome
(variable)
Set a goal
(reference value)
Barriers &
friction
(disturbance)
Receive feedback
on performance
(input)
Perform
behavior
(output)
Carver, C. and M. Scheier (2005). On the structure of behavioral self-regulation. Handbook of self-regulation. M. Boekaerts, P. Pintrich and M. Zeidner. San
Diego, USA, Guilford Press.
Forget the science of
attrition a moment. How
long could you realistically
stay on this never ending
self-regulation loop,
without falling off the
bandwagon.

19. PSYCHOLOGICAL ARCHITECTURE OF
HEALTH BEHAVIOR CHANGE TECHNOLOGIES
CUGELMAN, B., THELWALL, M., & DAWES, P. (2011) Online interventions for social marketing health behavior change
campaigns: A meta-analysis of psychological architectures and adherence factors. Journal of Medical Internet Research, 13(1),
e17. http://www.jmir.org/2011/1/e17/
19
EffectSize(d)
Interventions(%)

20. Let’s take a realistic
approach to habit
formation with 66 avg
days and most people
abandoning your
technology after just
a few sessions.
20

21. DOMAIN 7. AUDIENCE FEEDBACK
21

22. SEQUENTIAL REQUESTS
22
Can you sign this petition?
Can you donate $100?
Would you donate $100?
Ok, how about $10?
[P-702]

23. SHOPPING CART ABANDONMENT:
DOOR IN THE FACE
23Wang, D. (2014). 13 Amazing Abandoned Cart Emails (And What You Can Learn From Them).

24. REMINDERS AND PROMPTS
24
[P-703]
Engaging at the right time (kairos)

25. TARGETED, PERSONALIZED, TAILORED
ADAPTED FROM KREUTER ET AL. (2000)
25
1.Input
2. Output
Personalized
Targeted
Tailored
No
feedback
Lots of
feedback
Generic
Interpersonal
Generic Individualized
[P-705]
[P-706]
[P-707]

26. PERSONALIZATION AND RECOMMENDATION ENGINES
26
Targeting [P-705]
Tailoring [P-707]Personalization [P-706]

27. TARGETING IS LIKE TAILORING FOR A GROUP
27
Group A
Group B
Group C
Group D

28. WHY DOES TAILORING WORK
1. Unnecessary information is eliminated
2. The information is personally relevant to the
individual
3. People pay more attention to information that is
personally relevant
4. People are more likely to act on information that
they have pondered in-depth
28

29. SETTING GOALS AND MAKING COMMITMENTS
(INTENTIONS)
29
[P-708]

30. PERSONAL ACTION PLAN
30
[P-709]

31. PERSONAL BARRIERS AND FRICTION
31
Goal
Cugelman, B., M. Thelwall, et al. (2011). "Online Interventions for Social Marketing Health Behavior
Change Campaigns: A Meta-Analysis of Psychological Architectures and Adherence Factors." Journal
of Medical Internet Research 13(1): e17.
Drivers
Friction
[P-710]

32. FEEDBACK ON PERFORMANCE
Cugelman, B., M. Thelwall, et al. (2011). "Online Interventions for Social Marketing Health
Behavior Change Campaigns: A Meta-Analysis of Psychological Architectures and
Adherence Factors." Journal of Medical Internet Research 13(1): e17.
[P-711]

33. 33

34. REINFORCEMENT
A reinforcer is anything that occurs with an act
that increases the odds of it happening again.
34
Negative reinforcer Positive reinforcer
[P-712]
Something someone wantsSomething someone wants
to avoid

35. PUNISHING AND REWARDING
WITH DIALOGUE BOXES
Nasty Mac
35
FAILURE
You have NOT reached your goal.
LOSER!
You’re not yet finished.
Try harder. Lazy bugger.
Never degrade, insult, or offend.
For negative feedback, focuses on positive encouragement or loss aversion.
Punishment can undermine users’ motivation, confidence, and boost the odds
that they avoid your technology like a nasty person.
[P-712 b] Nice Mac
SUCCESS
You’ve reached your goal.
CONGRATULATION!!!
You’ve finished. Way to go!
[P-712 a]

36. DON’T CONFUSE
MOTIVATION WITH REINFORCEMENT
Before acting While acting After
Motivation
(Incentives / Loss aversion)
Reinforcement
(Rewards / Punishments)
Don’t confuse threats of loss aversion with punishment.
Be careful with punishment, and only use it with care.

37. ENDING QUESTION
What feedback can you capture,
that’s useful to your users, that can
inspire them to take positive action?
How can you add feedback-based
persuasive design principles to
boost your impact?

38. CLOSING
38

39. Thanks so much.
39
Stay in touch in Twitter:
@cugelman
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