1 Exploring Experiments 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,

2 Purpose of Research 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?

3 Variables of Interest 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)

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

5 Cook and Campbell’s UTOS Units: Overweight, binge-eating women Treatment: Non-dieting and Dieting treatments Observations: Weight and binge- eating 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

6 Threats to Internal Validity 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

7 Threats to Internal Validity 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).

8 Threats to Construct Validity Diffusion of treatment –p : the diet condition may have been contaminated by non- behavioral 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

9 Threats to Construct Validity 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

10 Threats to External Validity 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

11 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

12 Improving the research 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