Feedforward Presentation to the University of Illinois

December 4, 2012
University of Illinois at Urbana-Champaign

Feedforward
Support Emotive Learning for Enduring Lifestyle Change

Amber Howard, Ph.D.

Director of Research and Education
New Kind

Lecturer
North Carolina State University
College of Design, Graphic and Industrial Design

amberhoward.net
amber@amberhoward.net
@amberkhoward

Overview
Introduction
Conceptual Framework
Purpose
Research Framework
Research Methodology
Results
Conclusion

December 4, 2012 | Feedforward | Amber Howard, Ph.D. | 2 / 115

Change for good
The designer

What wasn’t
now is.

Change for good
The Hope

Make the
world better

Change for good
The Hope

Make the life
world better

Change for good
The predicament

Make the life
change
world better

Change for good
The predicament

Make the life
change =
world better
challenge the status quo


Change for good
The predicament

Make the life
change =
world better
challenge the status quo
view the situation differently


Change for good
The promise

Find a gap, don’t create a need.


Change for good
Atmospheres of impact

What change do you want to make? Find the gap in each atmosphere.

culture

beliefs

behaviors

things


Change for good
Intended experiences

What experiences do you want to create and reinforce?

culture

e
nc
iebeliefs
r
x pe
e
behaviors

things


Change for good
Experiences for change

Current strategies focus on ability, will, and social pressure (Patterson, 2008)

skill motivation

social


Change for good
Moving forward

... but there’s more to it.


The setting
The Social Issue
The Obstacles
Design’s Role


The Social Issue
Obesity affects millions of people each year

11% of the population will become obese in the next 7 years (Wang, et al., 2008)

30% obese 30% obese

7 YEARS 41% obese 41% obese

75% overweight
75% overweight
65% overweight
65% overweight

2008 2015


The Social Issue

11% of the population will become more at risk for:

Heart disease, High blood pressure, Diabetes, Cancers, and Premature mortality (CDC, 2009)

30% obese 30% obese


75% overweight
75% overweight
65% overweight
65% overweight

2008 2015


The Social Issue

Currently costs $177 billion/year in medical expenses (CDC, 2009)

other
30% obese

Medicaid 7 YEARS 41% obese 41% obese
Medicare

out of 75% overweight
75% overweight
65% overweight pocket

2008 2015


The Social Issue

Minimized or prevented by changing daily behaviors

30% obese 30% obese


75% overweight
75% overweight
65% overweight
65% overweight

2008 2015


The Social Issue
We know what to change

Habits and behaviors are the key determinates of future health (Healey & Zimmerman, 2009)

Depends on our willingness and ability to prioritize for our future health every day

eating behaviors health / chronic disease


The Social Issue

Health issues pervade mainstream media

Knowledge Access Support

Online References Organic Food Products Food Movements
Documentaries Dieting Food Products Weight loss Programs
Best-selling Books Health-Conscious Restaurants Health Management Apps
Magazines National Initiatives


The Social Issue

We know which behaviors and lifestyles are healthy

We have access to appropriate resources

We know how to perform the behaviors

We care about our future health

access + skill + motivation = change
right?


The Social Issue
Lifestyle change is easier said than done

Relapse despite knowing what we should do (Adolfsson, Carlson, Unden, & Rossner, 2002)

1/2yr 1yr 2yr

n
median weight loss

-1

-2

80%
-3

relapse


The Social Issue

Despite our best intentions, we fail to act on them (Orbell and Sheeran, 2009)

We revert back to old habits without realizing it

access + skill + motivation ≠ change


The obstacles

The trainer knows, but the elephant is set in its ways.

“Today this mind does not stray and is under the harmony of
control, even as a wild elephant is controlled by the trainer.”
— Buddha

“If passion drives, let reason hold the reins.”
— Benjamin Franklin


The obstacles

We tend to attribute less emotional value to the future

Intertemporal choice (Wilson, 2001)

Current feelings bias predictions about future feelings

present future


The obstacles


Future Discounting (Gilbert, 2006)

Care more about an immediate outcome than a future one

present ≠ future


The obstacles


Future Discounting (Receiving $20, Gilbert, 2006)

today = 61.5

60

1 day = 53.6
7 days = 53.3

30 dayS = 50.9
50

185 dayS = 46.5

365 dayS = 42.2

05 01 00 150 200 250 300 350 400
days from now


The obstacles

An exercise in self-control and will power

Delayed Gratification

The Marshmallow Study (Mischel, 1972)

1/3 succeed


The obstacles


“Time discounting plays an especially important role in
decisions concerning health. Virtually all health-related
decisions involve trade-offs between short-term and
long-term gains.”
— Economist George Lowenstein, Psychologists Daniel Read and Roy Baumeister


The obstacles

An exercise in self-control and will power

Cognitive load can distract us from our health goals (Baumeister & Muraven, 2000)

or

< 3 digits > 3 digits


The obstacles

Physiological components of lifestyle

Stress can distract us from our health goals (Epel et al., 2001)

stress increases cravings for sweet foods
fried
fatty
salty


The obstacles

Physiological components of lifestyle

Locus of Control (Tice, Bratslovsky, & Baumeister, 2001)

Stress leads to short-term decisions (Rodrigues, LeDoux, & Sapolsky, 2009)

internal control

long-term decisions

external control

stress short-term decisions

chance


Design’s Role
Redefining Healthcare

Design mediates our relationship to the food we eat

Monitoring our health progress

Generating healthy recipes on the fly

Referencing food information

we experience and learn healthy lifestyles
through designed conditions


Design’s Role

Decentralized and self-initiated

Tailored personal health management and coaching tools

Body Area Network (BAN) technology

We use tools to help us control health-related behaviors


Design’s Role





Design’s Role

Tactical solutions

We learn appropriate behaviors, but remain dependent on the system

Prescribes disjointed tasks (though straightforward and easy to execute)

Demands continual reminders, motivators, and feedback to ensure compliance

Emphasizes reflective learning (data visualization)

through designed conditions
we manage tactics for health


Design’s Role

Tactical solutions

It’s all about enabling the trainer to control the elephant.

culture

beliefs

behaviors

things


Design’s Role
Design can do better

Strategic opportunities

Address the emotive underpinnings of behavior and lifestyles

Foster a different mindset/bias regarding eating practices

“So much [of design] is focused on the moment
of decision making. We need to create rewards
around other (influences) on behavior…to motivate
immediate and long-lasting behavior change.”
— Robert Fabricant, Frog Design


Design’s Role
Design can do better

Strategic opportunities

culture

e
nc
iebeliefs
r
x pe
e
behaviors

things


Design’s Role
True lifestyle change

Our biases align with our health goals

We impulsively choose the healthy option

We are not tempted by old habits


Design’s Role
A design theory to support lifestyle change

Change biases that guide preferences, interpretations, decisions, and actions

Target emotive learning processes

Function beyond the realm of conscious control

“Do you like marshmallows?”


Feedforward: A Design Theory
Conceptual Framework Diagram


Conditions for emotive learning

Timing matters

Provide anticipatory conditions for a pre-experience

Activate a mindset and associated biases

Set the stage for behaviors to unfold

past
feedback present
feedforward future



Timing matters

Seek patterns among subtle cues

Frame, or contextualize, situations with minimal information

Automatically facilitate motivation and goal pursuit

present activate bias



Timing matters

Anticipate what will likely happen within the given constraints

Adapt behavior to prepare and/or adjust for change

Develop subtle associations among cues

present activate bias future



Timing matters

Anticipate what will likely happen within the given constraints

Adapt behavior to prepare and/or adjust for change

Develop subtle associations among cues




Modulate the emotive learning process

Anticipatory cues before the situation

Skew the constraints from which the bias activates

Modulates the perception of the situation





Consolidate the associations as a predictive model

increase the chances of achieving enduring lifestyle change

sent activate bias future consolidate for
predictive model



Expose intermittently throughout the day

passive exposure skews motivation & goal pursuit

(thank you, pattern matching)




Develop preferred biases pervasively through daily routines

Influence short- and long-term frame of reference, or worldview

Decide which bias we want to embody going into a situation (not by happenstance)

past
feedback present
feedforward future


Research informing the theory

Louis Cheskin, clinical psychologist and marketing innovator (Cheskin, 1947)

How design mediates our subsequent experience of products

Affects the taste of food

Affects the value we attribute to eating it



Priming

Anticipatory cues activate implicit memory

Frames the subsequent responses

Does not require awareness or recollection of the priming stimuli

“One remarkable feature of priming is that, unlike other forms
of cognitive memory, it is nonconscious. A person perceiving a
familiar object is not aware that what is perceived is as much
an expression of memory as it is of perception.”

— Endel Tulving and Daniel Schacter



Priming Examples

Elderly stereotype affects behavior (Bargh, Chen, & Burrows, 1996)



Priming Examples

Elderly stereotype affects behavior (Bargh, Chen, & Burrows, 1996)

Faster recognition of “butter” when “bread” precedes it (Meyer & Schvaneveldt, 1971)

Ambient sad music affects perceived slope of a hill (Proffitt, 2006)

Images of eyes affect honesty at the coffee station (Bateson et al., 2006)

Warm beverage affects perception of strangers (Wiliams & Bargh, 2008)

Professor persona affects score in trivial pursuit (Dijksterhuis and Knippenberg, 2005)

Rude/Polite and Cooperation/Competition (Bargh & Williams, 2006)



Embodiment and Neuroplasticity

Consciousness emerges from emotive processes (Ashby, 1956; McClelland & Rumelhart, 1986)

Pleasure in anticipation (dopamine solidifies connections) (Hawkins, 2004; Carter et al., 2009)

Deep-seated biases are not permanent (Kihlstrom, 1987; Hebb, 1949; Merzenich, 1984; LeDoux, 1999)

“The brain knows more than the conscious mind reveals.”

— Neuroscientist Antonio Damasio



Embodiment and Neuroplasticity Examples

The Iowa Gambling Task (Damasio, 2005)

Anticipation • emotions • feel without knowing why (LeDoux, 1996)

70 cards later



Calm Technology (Brown & Wieser, 1995)

Ubiquitous computing as an ambient influence on our behaviors



Louis Cheskin

Priming

Embodiment and Neuroplasticity

Calm Technology

formalizes a body of research regarding anticipatory cues


A design theory

Leveraging design prior to decisions and actions

Frame a mindset through which to interpret a situation

Influence our ability to adopt healthy behaviors and achieve long-lasting lifestyle change

informs design conditions for emotive learning


Constraint Matching
Feedforward
Bias goal state by introducing Identify Cues
additional constraints to the
system (Increase occurrence of
goal state cues)

Co
nst
ing

rain
eek

As
e

t Int
nt S

sign
pat
set
ind Constrai

erpretin
Antici

Value
M
&
Emotive Learning
te

g
Sta

Rapid Cycle
oal
Bias G

r
to

Ex
ing

c
tra ec

Co
at

At ut
ion
d

n
el

rge li st
d so rai
Mo Cha on nt
tive in tC Tes
Refine Predic tra ting
Cons



Constraint Matching
Seeking
limits the range of stimuli Identify Cues
we consider relevant and
meaningful (Barrett et al., 2007)

Co
nst
ing

rain
eek

As
e

t Int
nt S

sign
pat
set
ind Constrai

erpretin
Antici

Value
M
&
Emotive Learning
te

g
Sta

Rapid Cycle
oal
Bias G

Progressive
Cycle
r
to

Ex
ing

c
tra ec

Co
at

At ut
ion
d

n
el

rge li st
d so rai
Mo Cha on nt
tive in tC Tes
Cons



Constraint Matching
identifies internal and external
cues that correspond with the Identify Cues
anticipated stimuli
(Kosslyn S. , 1995)

Co
nst
ing

rain
eek

As
e

t Int
nt S

sign
pat
set
nd Constrai

erpretin
Antici

Value
i
M
&
te

g
Sta
oal
Bias G

Progressive
Cycle
r
to

Ex
ing

c
tra ec

Co
at

At ut
ion
d

n
el

rge li st
d so rai
Mo Cha on nt
tive tC Tes
Refine Predic rain ting
Const



raint Interpreting
assigns greater emotive value Const
to the neural networks that
Assign Value
match expectancies
(Oschner et al., 2004)

g
hin

Con
atc

ues

stra
int M

Exe
fy C

int Te
cutio
Identi
Constra

sting
n
Ch
a

Co
te rg
eA
g

pa

ns
kin

i
tic ttr

tr
An ain act
ee tC or
tS on
ain sol
str ida
Con ting
set

Progressive

Refin
Mind

Cycle
December 4, 2012 | Feedforward | Amber Howard, Ph.D. | 65 / 115 eP
&


Constraint Testing
Testing
anticipatory behavior and action Execution
(Butz, Sigaud, & Gerard, 2007)

Co
g

nst
tin
rpre

rain
Ch
arg
e

t Co
Inte

Valu

e At

nsolida
Constraint

Assign
Re

tractor
fin
Emotive Learning e

ting

P
Rapid Cycle

Progressiv
Cycle
es

u An
ing

yC tic

Co
tif
ch

ipa

n
Iden at st
rai te
M nt
int Se sG
stra eki oal
Con ng Stat
e & Mindset


ictive Model
red
eP
efin

R

Bia
Progressive

s Go
Cycle
traint Consolidating
Cons

al State & Mind
Consolidating
Connections within the Attractor
Charge
attractor network strengthen
or weaken depending on the
network’s accuracy

set
(Sutton & Barto, 1998)

Co
g

nst
stin

rain
Ant
nt Te

tion

t See
icipa
Constrai

Execu

te

king
Emotive Learning

Rapid Cycle

de

I
e nt

C
alu
g

on
ify
tin

nV

s
re tra Cu
Assig es
erp int
Int Ma
raint tch
ing
Const


ictive Model
red
eP
efin

R

Bia
Progressive

s Go
Cycle
traint Consolidating
Cons

al State & Mind
Predictive Model
Attractor
Charge
accurate predictions are
strengthened to enable more
prominent and clear signals
within the network

set
(Carter et al, 2009)

Co
g

nst
stin

rain
Ant
nt Te

tion

t See
icipa
Constrai

Execu

te

king
Emotive Learning

Rapid Cycle

de

I
e nt

C
alu
g

on
ify
tin

nV

s
re tra Cu
Assig es
erp int
Int Ma
raint tch
ing
Const



Constraint Matching
Feedforward
Bias goal state by introducing Identify Cues
additional constraints to the
system (Increase occurrence of
goal state cues)

Co
nst
ing

rain
eek

As
e

t Int
nt S

sign
pat
set
ind Constrai

erpretin
Antici

Value
M
&
Emotive Learning
te

g
Sta

Rapid Cycle
oal
Bias G

Progressive
Cycle
r
to

Ex
ing

c
tra ec

Co
at

At ut
ion
d

n
el

rge li st
d so rai
Mo Cha on nt
tive in tC Tes
Cons




“When learning occurs in a way consistent with the laws
that govern brain plasticity, the process of the brain can
be improved so that we learn and perceive with greater
precision, speed, and retention.”
— Neuroscientist Michael Merzenich, Father of Neuroplasticity


Research
Purpose of the Theory
Purpose of the Study


Purpose of the Theory
Propose a design theory for lifestyle change

Feedforward

Align design strategy with our emotive learning process

Provide anticipatory cues that frame our perception of an emerging situation

Align biases with intended lifestyle goals

Foster preference, behavior, and bias change


Purpose of the study
Test the theory

Feedforward

Deploy a mobile design strategy into a naturalistic setting

Prime for a future health-oriented mindset

Measure the preferential, behavioral, and bias effects of prolonged priming

Analyze the short- and long-term effects


Research
Research Questions


Central Research Question

To what extent can designed mobile interaction that primes
for a future health-oriented mindset before meal and snack
times influence preferences, behaviors, and biases toward
healthy eating practices among young adult college students
at risk for obesity?


Central Research Question

cause To what extent can designed mobile interaction that
strategy primes for a future health-oriented mindset
when before meal and snack times
effect influence preferences, behaviors, and biases
domain toward healthy eating practices
who among young adult college students at risk for obesity?


Sub-Research Questions

cause To what extent can designed mobile interaction that
strategy primes for a future health-oriented mindset
when before meal and snack times for one week
Q1 influence the perceived desirability of healthy foods
Q2 influence the proportion of healthy food consumed
Q3 influence future health biases
who among young adult college students at risk for obesity?


Research Methodology
Participants
Research Design
Variables
Instruments


Overview of Study

Preference Repeated Measure ANOVA
Survey: Rate appetite Margin of Error
Survey: Rate craving ANCOVA

Purposive
Sampling Behavior Logistic Regression
SMS Reported intake Repeated Measure ANOVA
Conclusions about
Survey: Food Choice Margin of Error
the design theory
Stratified Chi Square Test for Variance
Random ANCOVA
Assignment

Bias Repeat Measure ANOVA
IAT Response Times Margin of Error
Survey: Time Perspective ANCOVA


Participants
Recruitment

Purposive Sampling

IRB approval

Recruited from 3 cross-disciplinary courses

Received extra credit for participation

Participation was voluntary

Screened for ownership and usage of a mobile phone

Similar settings, routines, and stress cycles


Participants
Sample Size

117 participants completed the full study

58 treatment group / 59 control group

10% attrition rate (from 130 participants)

23% over minimum requirement


Participants
Questionnaire

Demographic, Personal Health, and Mobile Phone Behaviors


Participants
Demographics

4%
Latin
10% Amer.
Other

40% 40%
men 13%men
African Amer.
60%
women 60%
Caucasian

3%
10% under- 14%
obese weight cook 2+
meals/day

women 60%
Caucasian

Participants
Demographics

3%
10% under- 14%
obese weight cook 2+
meals/day

21%
overweight
50%
don’t cook
37%
65% cook 1 meal/day
average

16%
14%
currently
1 diet
dieting

37%
65% cook 1 meal/day
average

Participants
Demographics

16%
14%
currently
1 diet
dieting

56%
30%
never dieted
+2 diets
74%
not currently dieting


Participants
Group Assignment

Stratified Random Assignment (matching)

BMI Gender Zimbardo Dieting Phone Use Group

M P
F
<18.5
P
F
F
M P
18.5– F
24.9 P
F
F
M P
25– F
29.9 P
F
F
M P
F
>30
P
F
F


RESEARCH DESIGN
Modified Solomon Group Design

Week 1 Week 2 Week 3 Week 4 Week 5
Baseline Treatment Follow up 1 Follow up 2
Group

1A 2A 3A 3B 1B 2B 3C
••___________________________________ ••________________ 1C 2C 3D
••________________ 1

X
3A 1A 2A 3B 3C 1B 2B
_________________•• __________________________________ •• 3D 1C 2C
________________•• 2

1B 2B 3C
••________________ 1C 2C 3D
••________________ 3
3C 1B 2B 3D 1C 2C
________________•• ________________•• 4

R

1A 2A 3A 3B 1B 2B 3C 1C 2C 3D

(X)
••___________________________________ ••________________ ••________________ 5
3A 1A 2A 3B 3C 1B 2B
_________________•• __________________________________ •• 3D 1C 2C
________________•• 6
1B 2B 3C 1C 2C 3D
••________________ ••________________ 7
3C 1B 2B 3D 1C 2C
________________•• ________________•• 8

• : Preference 1 : Preference
• : Bias 2 : Bias
__ : Behavior 3 : Behavior


Variables
Independent Variable (Treatment Condition)

Prime for future health-oriented mindset

Delivered through MMS within the hour preceding meal and snack times


Variables
Control Variable

Neutral point of comparison

Delivered through MMS within the hour preceding meal and snack times


Variables / Instruments
Dependent Variables (Effects)

Perceived desirability of healthy foods

Online survey

How appetizing is the food in the photograph?

How often do you crave the food in the photograph?


Feedforward Presentation to the University of Illinois

Feedforward Presentation to the University of Illinois

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