Weight Bias in Pediatric Inpatient Care
Elizabeth E Halvorson1, Thomas Curley2, Mariah Wright2
1Department of Pediatrics (EE Halvorson and JA Skelton).
Insights
Most pediatric inpatient providers show implicit weight bias, affecting care for children with obesity. Patients and families also perceive weight bias within the hospital setting.
Area of Science:
- Pediatric Healthcare
- Medical Bias Studies
- Obesity Research
Background:
- Weight bias is known to affect medical care but has not been extensively studied in pediatric inpatient settings.
- Understanding provider and patient perspectives on weight bias is crucial for improving healthcare quality.
Purpose of the Study:
- To quantify implicit and explicit weight bias among pediatric inpatient providers.
- To qualitatively explore providers' attitudes towards children with obesity.
- To understand patient and family perceptions of weight bias in the hospital.
Main Methods:
- A mixed-methods approach was used, combining validated tests for implicit (Implicit Association Test) and explicit (Crandall's Anti-Fat Attitudes Questionnaire) bias.
- Semistructured key informant interviews were conducted with pediatric providers (hospitalists, residents, nurses), patients (aged 7-17), and their parents/guardians.
- Interview data were analyzed using an inductive approach to identify recurrent themes.
Main Results:
- 71% of the 28 enrolled pediatric providers demonstrated moderate to strong implicit weight bias, while explicit bias scores were generally lower.
- Qualitative findings revealed seven themes, including the existence of weight bias, shared responsibility for childhood obesity, potential provider bias towards parents, and the impact of patient weight on care.
- Participants discussed the importance of terminology and preferences for addressing obesity in outpatient versus inpatient settings.
Conclusions:
- Pediatric healthcare providers, patients, and families recognize that obesity can impact care within the pediatric inpatient setting.
- Provider weight bias is a significant factor identified by all stakeholders.
- Further research and interventions are needed to address weight bias in pediatric healthcare.
Objective:
Weight bias can influence medical care but has not been studied in the pediatric inpatient setting. We will quantify implicit and explicit weight bias of pediatric inpatient providers and qualitatively explore providers' attitudes toward children with obesity and patient/family perceptions of weight bias in the hospital.
Methods:
We performed a mixed-methods study including semistructured key informant interviews and validated tests for implicit (Implicit Association Test) and explicit (Crandall's Anti-Fat Attitudes Questionnaire) bias with pediatric hospitalists, residents, and acute care nurses. We performed semistructured key informant interviews with pediatric inpatients aged 7 to 17 years and the patient's parent(s) or guardian(s). Interviews were coded using an inductive approach to identify recurrent themes.
Results:
We enrolled 28 pediatric providers, 12 patients, and 12 parents/guardians. In total, 71% of providers exhibited moderate or strong implicit weight bias, with generally lower scores for explicit bias. Qualitative analysis identified seven themes: the existence of weight bias, shared responsibility for a child's obesity, a potential for provider bias toward the parents of pediatric patients with obesity, possible effects of patient weight on inpatient care, importance of terminology in addressing obesity, and the possibility of addressing obesity inpatient but a preference for obesity to be addressed in the outpatient setting.
Conclusions:
Health care providers, patients, and families in the pediatric inpatient setting identified multiple ways that obesity could impact care, including provider weight bias.
Related Concept Videos
01:31Confirmation Biases
01:12Hindsight Biases
01:22Bias
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
00:57Weighted Mean
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
01:17Correspondence Bias
01:29Self-Serving Bias