Introduction:

The research I will be presenting will focus on the identification and quantification of gender and sex biases among healthcare providers and their impact on the different tasks involved in the clinical management of a patient: assessment of symptoms, medical and clinical; patient monitoring, vital signs measurement, and clinical status assessment; tests and diagnostic procedures according to the initial patient evaluation; initial and main diagnosis; treatment administration; assessment of patient progress, response, and final status; and communication with the patient. The stage of the academic and professional trajectory in which these biases originate and their evolution over the years of study and training of medical students and practicing physicians will also be analyzed and identified.

 

Theoretical framework

 

Historically, gender inequalities in health have been addressed through biological, methodological, or social explanations. These three approaches have produced evidence that focuses on how these differences result from inequalities in access to social protection resources or a significant difference in the level of exposure to important health risk factors, such as unhealthy behaviors, occupational risks, or inequalities in the distribution of domestic burdens and care responsibilities (Schmitz & Lazarevič, 2020). These explanations are important, relevant, and pertinent for identifying sources and causes of health inequalities.

However, another related to gender and sex inequalities in health is the role that healthcare systems themselves, and the professionals working within them, can play in contributing to or reducing these differences. Despite this, less attention has been given to this phenomenon in research. Biases are known to be a source of perpetuating health inequalities because they contribute to generating assumptions and stereotypes that, in turn, can influence and cause differences in decision-making in the clinical setting based on various factors, including gender (Chapman et al., 2013). Ultimately, the channels through which these biases embed themselves in institutions can translate into observable inequalities in the form of errors and inaccuracies in different phases of the clinical management (Champagne-Langabeer & Hedges, 2021; Chapman et al., 2013; FitzGerald & Hurst, 2017; Piccardi et al., 2018; Westergaard et al., 2019). Therefore, it is logical to assume that part of the inequalities and differences in the health conditions of men and women could be attributed to biases present in the design of healthcare institutions and the professionals working within them.

 

Notwithstanding,  we still do not know when and how these biases originate, how they evolve throughout the academic and professional career of medical doctors and whether clinical simulations are a good method to identify such biases. My research will provide answers in regards to these fundamental questions and will contribute to this research gap.

 

Research design:

In order to achieve the main goals of my research, we will use clinical simulation tools. We will use data collected in collaboration with the clinical simulation departments of medical faculties participating in the study, including the University of Barcelona, Pompeu Fabra University, the University of Lleida, and Rovira i Virgili University. This data will be collected through simulations that medical degree students, specialization master's students, junior physicians (MIR), and senior physicians, hereafter referred to as "healthcare providers," must perform as part of their medical training. In close collaboration with evaluators, observations will be systematically collected through standardized and homogenous evaluations. Simulated scenarios, along with the randomization of the patient’s sex and the random assignment of participants to treatment (female simulated patients) and control groups (male simulated patients), will allow the identification of gender and sex biases in the clinical management of patients by healthcare providers.

The participants in the study will be asked to (voluntarily) take a survey after performing the simulation, which includes questions about attitudes on gender, feminism and political ideology.

Additionally, we will assess the syllabus and the curricula of the teaching programs of the participating universities to identify if there is any relationship between the type of teaching offered by the universities, the subjects included in the curriculum, their content, and the performance of their students in clinical simulations.

Results from the simulations will be compared to:

1. Results from the survey, in order to assess whether there is any correlation between explicit gender biases (attitudes on gender, feminism and ideology) and implicit biases (observed differences in the clinical management of a patient).
2. The syllabus and curricula included in the teaching programs of the universities participating in the study.

Hypothesis and expected results:

• Regarding the existence of gender biases in healthcare providers.
  • H: Healthcare providers exhibit gender and sex biases in the clinical management of the patient.
  • H: Gender and sex biases evolve and vary throughout their academic and professional career, increasing as the clinical experience of healthcare providers grows.
• Regarding the impact of gender biases on clinical patient management,
  • H: The management of female patients in simulations shows more errors in different phases and tasks of clinical management than male patients.
  • H: Implicit gender and sex biases in health are independent of explicit attitudes related to gender equality, feminism, or the ideology of healthcare providers.
• Regarding clinical simulations as a tool for detecting biases,
  • H: Clinical simulations are a good tool for detecting gender and sex biases in clinical practice.