A mixed methods study of perceptions of bias among neonatal intensive care unit staff

Background Inequity in neonatology may be potentiated within neonatal intensive care units (NICUs) by the effects of bias. Addressing bias can lead to improved, more equitable care. Understanding perceptions of bias can inform targeted interventions to reduce the impact of bias. We conducted a mixed methods study to characterize the perceptions of bias among NICU staff. Methods Surveys were distributed to all staff (N = 245) in a single academic Level IV NICU. Respondents rated the impact of bias on their own and others' behaviors on 5-point Likert scales and answered one open-ended question. Kruskal-Wallis test (KWT) and Levene's test were used for quantitative analysis and thematic analysis was used for qualitative analysis. Results We received 178 responses. More respondents agreed that bias had a greater impact on others' vs. their own behaviors (KWT p < 0.05). Respondents agreed that behaviors were influenced more by implicit than explicit biases (KWT p < 0.05). Qualitative analysis resulted in nine unique themes. Conclusions Staff perceive a high impact of bias across different domains with increased perceived impact of implicit vs. explicit bias. Staff perceive a greater impact of others' biases vs. their own. Mixed methods studies can help identify unique, unit-responsive approaches to reduce bias. Impact Healthcare staff have awareness of bias and its impact on their behaviors with patients, families, and staff. Healthcare staff believe that implicit bias impacts their behaviors more than explicit bias, and that they have less bias than others. Healthcare staff have ideas for strategies and approaches to mitigate the impact of bias. Mixed method studies are effective ways of understanding environment-specific perceptions of bias, and contextual assets and barriers when creating interventions to reduce bias and improve equity. Generating interventions to reduce the impact of bias in healthcare requires a context-specific understanding of perceptions of bias among staff.