Implicit Bias

This project-also known as "Accountability for Care through Undoing Racism \& Equity for Moms" or ACURE4Moms-aims to reduce Black-White maternal health disparities using multi-level interventions designed to decrease bias in prenatal care, improve care coordination, and increase social support. ACURE4Moms is a pragmatic 4-arm cluster randomized controlled trial conducted with 39 prenatal practices across North Carolina. Practices have been randomly assigned to receive either: Arm 1 (Standard Care): North Carolina Medicaid Care management for high-risk pregnancies; Arm 2 (Data Accountability and Transparency): North Carolina Medicaid Care Management + Practice-level Data Accountability interventions; Arm 3 (Community-Based Doula Support): North Carolina Medicaid Care Management + Community-Based Doula support intervention for high-risk patients during pregnancy and postpartum; or Arm 4 (Data Accountability and Transparency + Community-Based Doula Support): North Carolina Medicaid Care Management + Both Arms 2 and 3 interventions. During each practice's 2-year intervention period, the practice will initiate prenatal care for \~750-1,500 patients (up to 60,000 patients total), whose outcomes the investigators will follow and compare between arms until all these patients have reached 1-year post-delivery.

Healthcare providers' implicit bias has been identified as a contributor to longstanding health inequities via negative impacts on the patient-clinician relationship and biased delivery of high-quality evidence-based practices (EBP). The implementation of any EBP runs the risk of worsening existing health disparities due to inequitable access, delivery, or benefit of the intervention. Clinician bias can be a critical and unaddressed determinant of implementation for any EBP. Although some implicit bias interventions for healthcare providers are emerging, studies have rarely included mental health professionals. In a previously NIMH funded project, our research team iteratively developed a brief (\~45 minutes), interactive online Virtual Implicit Bias Reduction and Neutralization Training (VIBRANT) for school mental health clinicians with promising preliminary findings. The current study will test the effectiveness of VIBRANT-an implementation strategy for promoting equitable adoption, penetration, fidelity, and sustainment of EBPs. One highly learnable, efficient, and scalable EBP that is particularly well-suited for the education sector is Measurement-Base Care (MBC)-the systematic collection of patient-reported progress data to inform clinical decision-making. The proposed study aims to (1) evaluate VIBRANT's feasibility to promote equitable adoption, penetration, fidelity, and sustainment of MBC, with a validated, brief, interactive online training for MBC; (2) examine VIBRANT's impact on proximal mechanisms of change including clinicians' implicit bias as well as distal youth mental health outcomes (i.e., symptoms and functioning) with Black and Latinx youth, and (3) assess feasibility of research procedures for a future large-scale efficacy trial.

Implicit bias is a form of bias in which a person's automatic and unintentional thoughts of another person or group influence either positively or negatively their behavior or the decisions they make. Studies show that healthcare providers have the same amount of bias as any other person and that it can affect patient care. However, in the emergency room, which is fast-paced and there is a high number of patients, implicit bias may be higher. Therefore, this study will look at emergency care center (ECC) providers' willingness to change their implicit bias behaviors. After, it will provide implicit bias education designed for the ECC to the healthcare providers at SMHCS Sarasota campus and assess whether it improved their willingness to change implicit bias behaviors when compared to the providers in the SMHCS Venice campus who did not receive the education.

This study will examine the impact of training primary care providers (PCPs) in motivational interviewing (MI) using artificial intelligence (AI) to augment the training process. MI is a patient-centered approach to engaging patients in their own care. There will be a control group and two intervention groups, with the intervention groups receiving a different amount of MI training. The hypothesis is that the AI-augmented MI training will result in improved patient outcomes, improved clinician wellbeing, and reduced behavioral manifestation of clinician biases. This mixed-methods project will also collect qualitative data from structured interviews and focus groups with participating PCPs to examine perceived facilitators and barriers to the use of the MI approach in primary care.