Related Experiment Video
Updated: Jul 9, 2025

06:05
The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
Published on: February 19, 2021
1.3K
Implementation of a Chief Resident Selection Process Designed to Mitigate Bias: Lessons Learned.
Rachel J Katz-Sidlow1, Kirsten L Roberts1, Dacone A Elliott1
1Pediatrics, Jacobi Medical Center, Albert Einstein College of Medicine, Bronx, USA.
Cureus
|December 4, 2023
Summary
Implementing an inclusive chief resident selection process mitigated bias and was well-received by residents and faculty. This approach enhances diversity in academic medicine leadership.
Area of Science:
- Medical Education
- Healthcare Leadership
- Diversity and Inclusion
Background:
- Chief residency selection processes can be opaque and biased, impacting diversity in academic medicine.
- Inclusive chief resident (CR) selection is crucial for promoting diversity in physician leadership.
- Current CR selection methods may perpetuate existing disparities.
Purpose of the Study:
- To implement and evaluate an inclusive chief resident selection process designed to mitigate bias.
- To assess the acceptability and satisfaction of residents and faculty with the new selection process.
Main Methods:
- A four-step opt-out process was developed: nomination survey, structured interviews, clinical review, and holistic review.
- Each step was scored using a rubric, excluding examination scores and "fit" to minimize bias.
- The process was implemented for the 2021-2022 academic year, followed by a departmental survey in January 2023.
Main Results:
- Survey response rates were 47% for residents and 29% for faculty.
- A majority of residents (64%) and all faculty (100%) were satisfied, finding the process fair and inclusive.
- Nearly 80% of residents and 100% of faculty supported repeating the process.
Conclusions:
- An inclusive chief resident selection process that mitigates bias is feasible and acceptable.
- The implemented process demonstrated high satisfaction among residents and faculty.
- Residency programs are encouraged to adopt inclusive, bias-mitigating CR selection practices.
Related Concept Videos
Randomized Experiments
7.0K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Simple randomization
Simple...
7.0K
Confirmation Biases
5.5K
The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
5.5K
Bias
4.2K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
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...
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...
4.2K
Bias in Epidemiological Studies
291
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
291
Blind Procedures
10.6K
Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which...
10.6K
Strategies for Assessing and Addressing Confounding
102
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
102

