Lab #4: May 2, 2008
Today’s Article:
Goodrick, G.K., Poston, S.C., Kimball, K.T., Reeves,
R.S., & Foreyt, J.P. (1998). Nondieting versus dieting treatment for overweight binge-eating women.
Journal of Consulting and Clinical Psychology, 66,
363-368.
1

• Causation
– To identify whether the treatment produces change in weight/BMI and/or binge-eating
• What might a demonstration study examining this issue look like?
• What might an explanation study examining this issue look like?
2

• Independent Variables (causes)
– Dieting treatment:
• non-dieting treatment
• dieting treatment
• wait-list control
• Dependent Variables (outcomes)
– obesity (operationalized: BMI, weight change)
– binge eating (operationalized: BES)
• Covariates
– Exercise (operationalized: self-report of exercise)
– Attendance (operationalized: classes attended) 3

• Random assignment into treatment groups
– Dieting group
– Non-dieting group
– Wait list control group
• What is gained by random assignment?
4

• Units: Overweight, binge-eating women
• Treatment: Non-dieting and Dieting treatments
• Observations: Weight and bingeeating habits (also exercise and attendance)
• Setting: Not discussed; likely a formal treatment setting for obesity at the Behavioral Medicine
Research Center at Baylor
University in Houston Texas
5

• Attrition: 16% of those assigned to conditions dropped out
– Authors attempted to lower attrition rates by obtaining a $200 deposit
– Authors did conduct Intention to
Treat analyses (with the assumption that the missing data values were equal to baseline values)
– Compared baseline scores and demographics
6

• Significant childhood traumas that were influencing eating/exercise/body weight behaviors (at least for some) —could have been included as a covariate.
• Hypothetical
– Resentful Demoralization: Participants could have been irritated or felt initial defeat if they were assigned to a treatment they felt was less effective.
(violates SUTVA).
– Compensatory Rivalry: Perhaps the
WLC group did so well because they sought an outside treatment. (violates
SUTVA).
7

• Diffusion of treatment
– p. 365-366: the diet condition may have been contaminated by nonbehavioral modeling factors;
“therapist drift”
• Inadequate explication of constructs
– p. 367: the study used those who scored 21 or higher on the BES, but this cutoff may be too low (i.e., some Ss were not binge eaters); did not measure frequency of binge eating
8

• Mono-operation bias
– Presence of binge eating was assessed only by the BES when other methods are possible
• Reactivity effects
– E.g., participants may want to present themselves in a favorable light by reporting greater amounts of exercise
9

• Results may not generalize to those with a diagnosis of binge eating disorder
• Results may not generalize to men
• Results may not generalize to those participants who did not meet the screening criteria (e.g., age, BMI, smokers)
• Results may not generalize to areas outside of Houston
• Results may not generalize to folks who are illiterate or who do not pass by the locations of recruitment advertisements
10

Threats to
Statistical Conclusion Validity
• Low statistical power: When no significant difference is found between conditions (e.g., no difference between DT and WLC) power is always a concern
– Researchers did address power by placing fewer participants in the control group than in the treatment groups
• Violation of statistical assumptions:
Participants were treated in groups, which may violate the assumption of independent observations
11

• Proximal Similarity:
Women with higher BES scores would have more closely reflected the
“binge-eating” population
• Find ways to ensure the integrity of the treatments
12