Randomized Trial Testing MyPlate.gov vs Calorie Counting

Discussion Tips

The federal government advocates for both a Diabetes Prevention Program (DPP) Calorie Counting (CC) and Dietary Approaches to Stop Hypertension (DASH)-based MyPlate approach to decrease overweight and obesity. The MyPlate intervention is considered cognitively simpler than the DPP-based Calorie Counting intervention and results in similar body fat reduction. This study randomized a predominantly Latine sample who received care from a federally qualified health center to either the MyPlate or Calorie Counting intervention, comparing satiation, satiety, waist circumference, and body weight at 6 and 12 months.

Discussion Questions

• What questions were asked by this study and why do they matter?

• Does the study not meeting enrollment targets concern you? Would your clinic have similar issues enrolling patients into lifestyle interventions?

• How adequately do you think the questions measuring satiation and satiety capture these concepts? In general, how is construct validity assessed?

• What is a continuous variable? What are the advantages and disadvantages of continuous variables? Which outcome variables were continuous?

• Why do study planners use focus groups and stakeholder interviews to review study designs and assessment measures? How might this impact an intervention’s potential success, community buy in, and the ethics of performing research among vulnerable populations?

• What are some ways measurement error was addressed for the outcomes of the study? Do you trust waist circumferences measured over clothes with a correction factor more than without a correction factor?

• What is a CONSORT diagram and why did reporting CONSORT diagrams become standard for clinical trials? What important information can be gleaned from reviewing this trial’s CONSORT diagram?

• Is the degree of attrition observed for this trial typical for lifestyle intervention trials? Was this trial’s attrition rate harmful to the internal validity of the study? What is multivariable imputation and why is it important for missing data?

• What are the main study findings?

• The authors adjusted for age, sex, marital status, educational attainment, and race/ethnicity in their primary analysis. What is the advantage of adjusting for covariates in randomized trials? Why is it important that covariates for adjustment are pre-specified before the analysis of trial data?

• How comparable is the study sample to similar patients in your practice or region? What is your judgment about the transportability of the findings?

• What aspects of the study setting and study participants are important for interpreting this trial’s findings?

• How might this study change your practice? What does it imply for health care policy?

• What testable hypotheses and research questions remain?