Impact of Child and Maternal Weight on Healthcare Trainee Clinical Assessment Decision Making: A Virtual Human Study

Abstract

Abstract

Background:

Adult literature documents that healthcare providers rely on patient characteristics, such as age, race, and weight, when making clinical decisions. However, little research has examined these biases among pediatric populations. This study aimed to examine the impact of child and maternal weight and race on clinical decision-making of healthcare trainees in the context of a pediatric pain assessment using standardized virtual pediatric patients and mothers.

Methods:

Ninety-two healthcare trainees read a standardized clinical vignette describing a child with chronic pain, which was accompanied by eight virtual human (VH) scenes—each with a child and mother. Scenes varied by the dyad's race, child's weight status, and mother's weight status. For each scene, participants were asked to make six healthcare assessment ratings.

Results:

Participants rated children (M = 42.44 vs. 48.69; p < 0.001) and mothers (M = 51.06 vs. 65.31; p < 0.001) with obesity as being less likely to adhere to physician recommendations compared with healthy weight children and mothers. Child patients with obesity (M = 38.88 vs. 30.08; p < 0.001) and mothers with obesity (M = 49.71 vs. 43.71; p < 0.001) were also rated as bearing more responsibility for the child's health status compared with healthy weight peers.

Conclusions:

This study provides evidence that child and mother weight can impact clinical decision-making, as well as for the utility of VH technology in studying decision-making among healthcare trainees and providers.