Predictors of weight discussion in primary care consultations: A multilevel modeling approach

Abstract

ObjectiveTo understand how primary care weight-related communication processes are influenced by individual differences in primary care practitioner (PCP) and patient characteristics and communication use. MethodsTwo multilevel logistic regression models were calculated to predict the occurrence of 1) weight-related discussion and 2) weight-related consultation outcomes. Coded communication data (Roter Interaction Analysis System) from 218 video-recorded consultations between PCPs and patients with overweight and obesity in Scottish primary care practices were combined with their demographic data to develop the multilevel models. ResultsWeight-related discussions were more likely to occur when a greater proportion of PCP’s total communication was partnership building and activating communication. More discrete weight discussions during a consultation predicted weight-related consultation outcomes. Patient BMI positively predicted both weight-related discussion and consultation outcomes. ConclusionThis work demonstrates that multilevel modeling is a viable approach to investigating coded primary care weight-related communication data and that it can provide insight into the impact that various patient and PCP factors have on these communication processes. Practice implicationsThrough the increased use of partnership building and activating communications, and by engaging in shorter, but more frequent, discussions about patient weight, PCPs may better facilitate weight-related discussion and weight-related consultation outcomes for their patients.