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Intuitive decision making and bias: Examination of their role in the initial mental-health intake with ethnically and racially diverse populations (Intuition and Bias)
Start date: Nov 1, 2008, End date: Oct 31, 2012 PROJECT  FINISHED 

The proposed project investigates the complexity of provider decision-making process during the initial mental-health interview (intake) with ethnically and racially diverse populations. We focus on examining intuitive decisions and explore the effect of explicit and implicit bias on decisions related to patient care, including, diagnosis, treatment recommendations, and assessment of rapport. Making medical decision during the mental health intake is the foundation for the proper patient care, but can be a challenging goal given the high level of uncertainty it involves. Such uncertainty is more pronounced in making intuitive decisions with diverse populations. However, little is know about the mechanisms contributing to clinical uncertainty and particularly to intuitive decisions.The current proposal aims to bridge this gap and reduce mental health service disparities by improving intuitive clinical decisions and reducing bias with ethnically and racially diverse populations. It builds on the Institute of Medicine’s (2002) analysis highlighting the role of biases, stereotyping and uncertainty in the patient provider interaction as contributors to service disparities. The specific aims of the study are: Aim 1: investigate the effect of explicit and implicit bias on intuitive decision making through a quantitative experimental design with a on-clinical sample. Aim 2: investigate the effect of explicit and implicit bias on intuitive decision making through a mixed methods experimental design with mental health clinicians providing services to ethnically and racially diverse population. Aim 3: assess clinician reactions to the recommended improvements to the decisions making process developed in Aims 1 and 2, using consensus groups. At the end of this project we hope to make feasible and concrete recommendations to improve the intuitive decision making process and reduce bias with diverse patients as well as make recommendations to improve clinical training.
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