1. No category

The biggest loser thinks long-term: Decision-making
predictors of weight-management success
Gilly Koritzky, Ph.D.
Obesity: a prominent public health problem
Obesity and its adverse effects on health have become prevalent worldwide
(USA: Over 30% of adults are obese).
Even a small weight loss of 5% is considered beneficial (CDCP).
Weight management is about making better choices.
The Neuroscience of Eating-Related Decisions
Obesity (like addiction) is affected by the joint activity of two brain systems:
Motivation
Reflection, Self-control
Long-term considerations,
planning, inhibitory control.
Drives, craves related to
incentives and rewards.
Predicting success in weight management
Weight-management interventions are mostly ineffective.
• Attrition is a common problem; 32% on average (Moroshko et al., 2011)
• Only ~25% of dieters lose as much as 5% of their weight (Appel et al.,
2011; Johnson et al., 2008).
Commonly reported correlates:
Younger age (attrition), female gender (attrition), lower education level,
numerous past weight-loss attempts, unrealistic weight-loss expectations, low
body image.
No consistent set of predictors has been identified.
Theory-driven explanations are scarce.
Prediction based on decision making style
Understanding the “cognitive risk factors” should enhance professionals’
ability to increase completion rates and improve health outcomes for more
individuals.
A focus on individual differences.
The Expectancy-Valence (EV) Model
Busemeyer & Stout, 2002
Captures three underlying components of behavior in decision tasks that
involve repeated selection between alternatives.
• The subjective sensitivity to gains vs. losses.
• The person’s recency = how much she/he is affected by new
information.
• The person’s consistency = how likely she/he is to prefer the highestexpectancy alternative (probabilistic).
Individual parameters are estimated via an analysis of trial-to-trial choice
making.
Recency
Reflection
(Koritzky et al., 2013)
Sensitivity to gain/loss
Drive, reward
(Premkumar et al., 2008;
Chan et al., 2014)
Method
Participants: Clients in evidence-based weight-management program.
• 80% women
• Mean age: 44
• Mean initial weight: 207 lbs; Body Mass Index: 34.11 (SD=7.06).
16 weeks long; weekly meetings with therapists.
You won:
100,
You lost:
250
We measured decision making and analyzed the results using the EV
Model.
Attrition study*
N=52 ; 35% attrition
No differences in initial weight, BMI, age, employment status, or number
of prior weight-loss attempts (education level: marginally significant).
Completers
N=34
Dropouts
N=18
Recency
0.25
(0.37)
0.25
(0.36)
Weight Gains/ Losses *
0.57
(0.30)
0.72
(0.22)
Consistency
3.28
(3.18)
3.57
(1.68)
* p < 0.05, two-sample t-test.
* Published as: Koritzky, Dieterle, Rice, Jordan, & Bechara (2014). Decision making,
sensitivity to reward, and attrition in weight management. Obesity, 22, 1904-1909.
Weight loss
N=43 completers of the program (≥12 weeks)
No differences in initial weight, BMI, age, employment status, or
education level.
A difference in # of prior weight-loss attempts.
Unsuccessful
n=31
Successful
n=12
Recency*
0.43
(0.43)
0.11
(0.36)
Weight Gains/ Losses Consistency
0.57
2.55
(0.33)
(2.50)
0.56
4.01
(0.25)
(4.00)
* p < 0.05, two-sample t-test.
Connecting the dots
Weight loss
Attrition
Recency
Sensitivity to gain
Reflection
(Koritzky et al., 2013)
Drive, reward
(Premkumar et al., 2008;
Chan et al., 2014)
Gilly Koritzky koritzky@usc.edu
Obesity and Gender
Drive, reward
Linked with Obesity?
E.g., Davis et al., 2007;
Nederkoorn et al., 2006.
The sample
Obese
30 ≤ BMI
Control
20≤BMI<25
40
36
19 (48%)
17 (47%)
Height inch
5’ 7” (3.9)
5’ 8” (3.2)
Weight lbs
224.52 (31.5)
149.9 (15.5)
BMI
34.69 (3.67)
22.8 (1.58)
N
Women
Measures of the Drive/Reward System
The Impulsiveness Questionnaire (Eysenck et al., 1985).
“Do you often buy things on impulse?"
"Do you generally do and say things without stopping to think?”
ANOVA
12
Rate on Impulsiveness scale
Yes/ No
Interaction:
Obese
Normal weight
10
F(1,72)=6.33, p=0.014
8
6
4
2
0
Men
Women
Delay of Gratification Task (Newman et al., 1992)
Win 5 NIS:
80%
5
40%
Obese
Normal weight
Prop. of delayed button choice
10 sec
ANOVA
100%
Interaction:
80%
F(1,61)=4.41, p=0.04
60%
40%
20%
0%
Men
Women
Obesity and Gender
Reflection
Linked with Obesity?
No evidence
(e.g., Davis et al., 2010).
Studies on drug addiction show such links in men
(e.g., Bechara et al., 2001; Lane et al. 2004).
The risk taking task (after Lane et al., 2004)
Will obese men display high risk taking
(low Reflective-system activity)?
% of risky choices
Obese
Normal weight
60%
ANOVA
50%
Interaction:
40%
F(1,72)=9.75, p=0.003
30%
20%
10%
0%
Men
Women
These findings suggest that the “cognitive profile” of
obese men and women is not the same.*
Reflection
Drive, reward
* Published as: Koritzky, Yechiam, Bukay, & Milman, (2012). Obesity and risk taking: A
male phenomenon. Appetite, 59, 289–297.
Obese
Non obese
Obese Men and Women Differ in Brain-Activation
Patterns Related to Decision Making: A Pilot Study
Obese Women
Obese Men