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Sleeping With Technology
Christel De Maeyer
De 'Quantified Self' revolutie
5 december 2013

Personal Informatics, a solution for behavior change
in preventive healthcare?
Overview
sleep efficiency 97% last night, feeling crispy!

•
•
•
•
•
•
•

Personal Informatics?
Behavior Design?
Overview of tools I research
Research Question
How? Fogg’s MAT model and Behavior Grid
Theory in real world practise
Results
Personal Informatics
• A set of tools to map behavior
• Aim to change behavior
• Biggest market today lifestyle, wellbeing, health,
40.000 mobile health apps in 2012
• 60% US is tracking exercise, diets, weight
• 33 % tracks other aspects, sleep patterns, blood
pressure, blood sugar
• 27 % Internet users track health data online
• 9 % Signed up for text messaging health alerts
Connecting

Anything
Anyone
Anytime
Self-Tracking Apps
Eatery App

Lift App

Runkeeper App
Self-Tracking Devices
Self-Tracking Devices Dashboards
Behavior Design
• Persuasive technology – Behavior
design
• Target audience is central – starting
from habits-behavior
• Triggers – Hot and Cold
• Simplicity
• Three core motivators
Model for understanding
persuasive side of devices and
software application
Simplicity factors
depending on person
and context to create
more ability, the
more ability the more
motivation
-

Fogg, 2008

Time
Money
Braincycles
Physical effort
Social acceptance
Non-Routine
3 Core Motivators each 2 facets

Fogg, 2008
Measuring Behavior and
Behavioral Change

Fogg, 2010, Behavior Grid and Wizzard
Hot and Cold triggers

Put HOT triggers in the path of motivated people
Is 24/7 self-monitoring creating
enough awareness and persuasion to
get a balanced lifestyle?

Will it bring a general wellbeing with
self-monitored people?
Behavior change through technology or
Persuasive Technology
Measuring:
Calorie burning
Food Intake
Steps
Physical Activity
Sleep

Body Media armband as a measuring device
Sampling

Gender

Age

Culture

Lifestyle
Mid-Long Period Research

Phase I
Fall
tracking

October November

Phase II
Silent
Period

December
- February

Phase III
Spring
tracking

MarchApril
Taxonomy of Self-Monitoring
Data interpretation

Coaching/feedback
loop

Goal setting

Selfmonitoring
process

Adapted taxonomy

Personal
Coaching
Ananthanarayan, Siek, 2012
Fogg, 2007
Phase I Fall 2012

Findings
Phase II Winter
8 out of 10 experimenters
stop self-tracking

3 core motivators
- Sensation: pleasure, ‘new’, curiosity
- Anticipation: hope, trigger to change
something
- Social cohesion: being part of
something cool, group feeling

device created dependencies:
without device =
Back to old routines, less awareness

Phase III Spring 2013

3 core motivators turn into
negative behavior with some
participants:
Sensation: ‘new’ & ‘curiosity’ gone
Anticipation: confrontation with data
Social cohesion: rejection, outside
world reactions

Phase III 2 women dropped out –
Data frustration- Problems with the device
One only tracked herself for 20 % ignorable data
Men more consistent focus on sleep and activity
Women focus on weight loss, more difficult to do
Findings – Dot and Span Behavior
Ability factors/Context factors: (Money, Time,
Brain Cycles, Physical Effort, None-Routine, Out
of the Ordinary)
Device:
• Fall: feels comfortable, identifies with it, but
first signs of ‘Out of the ordinary’
• Spring: doing good = ‘takes time’, less comfort
in long time wearing, outsiders remarks ‘Out
of the ordinary’
Findings – Dot and Span Behavior
Behavior:
• Fall: small changes, creating routines
instructed, brain cycles (cognitive investment)
made
• Spring: due to stop, routine not established,
lack of maintenance in habit forming and
cognitive effort
Findings – Dot and Span Behavior
Culture and season:
• Culture: SF vibrant city, nature aspects,
attractive to be active (not representative for
US!). BE city vs rural area, latter more
attractive
• Season: SF weather is a trigger to go outside.
BE seasonal effect, weather dependency high,
less activity
Conclusion
• Facilitate (triggers and higher the ability, instead of
motivate behavior change)
• Simplicity stimulates behavior change
• What do we want people to do?
• Help people what they already want to do
• It has to be very easy! (LarkLife – Body Media)
• Zeo Bedside Model versus Zeo Mobile
• Mainstream? Intuitive, discrete, second skin, less
expensive, seamless synchronizing process, data
presentation, there needs to be a need!
Thanks
Christel De Maeyer
christeldm@gmail.com
http://Sleepingwithtechnology.com

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Quantified Self Revolution December 2013

  • 1. Sleeping With Technology Christel De Maeyer De 'Quantified Self' revolutie 5 december 2013 Personal Informatics, a solution for behavior change in preventive healthcare?
  • 2. Overview sleep efficiency 97% last night, feeling crispy! • • • • • • • Personal Informatics? Behavior Design? Overview of tools I research Research Question How? Fogg’s MAT model and Behavior Grid Theory in real world practise Results
  • 3. Personal Informatics • A set of tools to map behavior • Aim to change behavior • Biggest market today lifestyle, wellbeing, health, 40.000 mobile health apps in 2012 • 60% US is tracking exercise, diets, weight • 33 % tracks other aspects, sleep patterns, blood pressure, blood sugar • 27 % Internet users track health data online • 9 % Signed up for text messaging health alerts
  • 8. Behavior Design • Persuasive technology – Behavior design • Target audience is central – starting from habits-behavior • Triggers – Hot and Cold • Simplicity • Three core motivators
  • 9. Model for understanding persuasive side of devices and software application Simplicity factors depending on person and context to create more ability, the more ability the more motivation - Fogg, 2008 Time Money Braincycles Physical effort Social acceptance Non-Routine
  • 10. 3 Core Motivators each 2 facets Fogg, 2008
  • 11. Measuring Behavior and Behavioral Change Fogg, 2010, Behavior Grid and Wizzard
  • 12. Hot and Cold triggers Put HOT triggers in the path of motivated people
  • 13. Is 24/7 self-monitoring creating enough awareness and persuasion to get a balanced lifestyle? Will it bring a general wellbeing with self-monitored people?
  • 14. Behavior change through technology or Persuasive Technology Measuring: Calorie burning Food Intake Steps Physical Activity Sleep Body Media armband as a measuring device
  • 16. Mid-Long Period Research Phase I Fall tracking October November Phase II Silent Period December - February Phase III Spring tracking MarchApril
  • 17. Taxonomy of Self-Monitoring Data interpretation Coaching/feedback loop Goal setting Selfmonitoring process Adapted taxonomy Personal Coaching Ananthanarayan, Siek, 2012 Fogg, 2007
  • 18. Phase I Fall 2012 Findings Phase II Winter 8 out of 10 experimenters stop self-tracking 3 core motivators - Sensation: pleasure, ‘new’, curiosity - Anticipation: hope, trigger to change something - Social cohesion: being part of something cool, group feeling device created dependencies: without device = Back to old routines, less awareness Phase III Spring 2013 3 core motivators turn into negative behavior with some participants: Sensation: ‘new’ & ‘curiosity’ gone Anticipation: confrontation with data Social cohesion: rejection, outside world reactions Phase III 2 women dropped out – Data frustration- Problems with the device One only tracked herself for 20 % ignorable data Men more consistent focus on sleep and activity Women focus on weight loss, more difficult to do
  • 19. Findings – Dot and Span Behavior Ability factors/Context factors: (Money, Time, Brain Cycles, Physical Effort, None-Routine, Out of the Ordinary) Device: • Fall: feels comfortable, identifies with it, but first signs of ‘Out of the ordinary’ • Spring: doing good = ‘takes time’, less comfort in long time wearing, outsiders remarks ‘Out of the ordinary’
  • 20. Findings – Dot and Span Behavior Behavior: • Fall: small changes, creating routines instructed, brain cycles (cognitive investment) made • Spring: due to stop, routine not established, lack of maintenance in habit forming and cognitive effort
  • 21. Findings – Dot and Span Behavior Culture and season: • Culture: SF vibrant city, nature aspects, attractive to be active (not representative for US!). BE city vs rural area, latter more attractive • Season: SF weather is a trigger to go outside. BE seasonal effect, weather dependency high, less activity
  • 22. Conclusion • Facilitate (triggers and higher the ability, instead of motivate behavior change) • Simplicity stimulates behavior change • What do we want people to do? • Help people what they already want to do • It has to be very easy! (LarkLife – Body Media) • Zeo Bedside Model versus Zeo Mobile • Mainstream? Intuitive, discrete, second skin, less expensive, seamless synchronizing process, data presentation, there needs to be a need!

Notas del editor

  1. US-Eu pricing body mediaAdoption – diffusion – micro and macro -
  2. Transtheoretical model Does Body Media has the ingredients to create awareness, persuasion to change behavior and maintain behavior changes. Simplicity –Three core motivators Hot versus cold triggers – hot triggers in motivated people’s path.
  3. Decrease fearIncrease hope – in our research losing weight, getting more active, different planningIncrease pleasure Decrease pain – medical conditionsIncrease acceptance –in case of overweight, getting less overweighted, Decrease Rejection
  4. Using Fogg’s behavior grid to map the profiles of the particpants and see their behavior change and progress during the tracking periods
  5. HotEmail with linkCold BilboardsCompanies who build Habit creation, users are very tied to the service, the more they use it, it becomes a habit - routine
  6. Google docs platform, weekly surveys, interviews, mingling in the group
  7. Purposeful sampling or non-probability sample, to go in depth on the behavior changes, and sometimes this asks for more privacy and trust Experimental Group - 10 participants, 5 male, 5 female. Age ranges from 30-60 Higher education but no early adopters!Culture difference we have 4 people in the US (3 in experimental group and 1 in control group) – California – San Francisco and 13 in Europe - Belgium (7 in experimental group and 6 in control group)Control group, unfortunately here only 7 participants who have no armband but are more or less matching profiles , and get the same treatment as experimental groupEarly and later majority group
  8. During tracking periods particpants get weekly surveys to fill in, in addition the experimental group sends excel export from Body Madia Activity Manager
  9. Personal coaching