The BHI is proud to support female scientists who are producing innovative work in the brain-heart field. Women’s Brain Health Day highlights the importance of recognizing biological differences between men and women and integrating these factors into research.At the BHI, researchers are committed to producing inclusive, impactful science that enhances brain-health outcomes for all genders.
Women’s Brain Health Day
Women are disproportionately affected by many brain health conditions, including Alzheimer’s disease, dementia, depression, and anxiety. Despite this, women have historically been understudied and underrepresented in clinical trials, and even in basic research, female mice were not routinely included in studies until the 2010s (1). Biological, hormonal, lifestyle, and social factors affect women differently, making it essential to incorporate sex and gender into both basic and clinical research to advance effective treatment and prevention strategies for all.
Each year on December 2nd, Canada recognizes Women’s Brain Health Day, a day that celebrates groundbreaking progress in women’s brain health while highlighting the importance of gender-informed research. The day was established by the Women’s Brain Health Initiative (WBHI), an international movement that funds, showcases, and raises awareness on the unique aspects of brain health for women. The high prevalence of certain brain disorders in women prompted the WBHI to call for research that fully considers sex and gender. Sex refers to biological and physiological characteristics, while gender encompasses social, cultural, and identity factors; both dimensions are essential to understanding brain health disparities.
This year for Women’s Brain Health Day, we are highlighting two female BHI scientists who are conducting cutting-edge research in the brain-heart field, while intentionally including sex and gender as a key variable. In doing so, their work ensures that women are well-represented and benefit equally from research findings. Dr. Karen Bouchard, a researcher studying the connection between loneliness and heart failure, and Dr. Juan Li, a data scientist investigating predictive modelling for Parkinson’s disease diagnosis, were both interviewed on how they integrate gender into their research and why advancing women’s brain health is so important.
Dr. Karen Bouchard
Dr. Karen Bouchard is an Associate Scientist and the Director of the Social Connections lab at the University of Ottawa Heart Institute, where her research examines how social factors, including loneliness, can impact cardiovascular health (2,3). Loneliness, which has been named as a major modern health concern by the World Health Organization, is defined as the feeling of isolation or disconnection, even when surrounded by others (4). Loneliness is increasingly common in individuals facing chronic conditions at a younger age, including heart failure. Their BHI project, titled “Alone, in a crowded room: A Canada-wide, participatory mixed methods study on loneliness in patients with early onset heart failure” seeks to characterize loneliness in young to middle-aged adults with heart failure, with the ultimate goal of identifying supports to alleviate loneliness in this group.
The team is intentional about integrating gender, along with other underrepresented demographics, into all aspects of their project design. A focus of their BHI research is to explore the sociocultural factors associated with loneliness in people with heart failure. Notably, women are 30% more likely than men to report feeling socially isolated or lonely, highlighting the importance of female representation in clinical studies in this area (5).
“My research, funded by the BHI, will determine just how common loneliness is among women with premature heart failure and the factors that contribute to this loneliness. The results from this work will provide more direction as to what we can do as a community to help support these women,” Dr. Bouchard explains.
When asked which area of research she considers most important for advancing women’s brain health, Dr. Bouchard shared her thoughtful insights:
“To really understand women's brain health, I firmly believe that we need research that spans and combines insights from several disciplines, including the biological, health, and social sciences, and also less traditionally incorporated fields, including the humanities. Studying the historical evolutions of women's health and brain research in Canada may provide some important insight into contemporary healthcare access barriers, for example. Working within our disciplinary silos, and using the same research methods, to understand complex topics, such as women's brain health, is just not going to cut it. The future is looking bright though. The BHI, for example, is an inter-and transdisciplinary-minded organization that is focused on building bridges across disciplines and fostering cross-collaborations.”
Dr. Bouchard also emphasized the importance of including the voices of patient partners in all research, particularly women with lived experience, to ensure that studies are intentional, informed, and practical. Engaging women in this way and including them on research teams, she explains, “enhances the quality and relevancy of the research, which may ultimately lead to better health outcomes.”
Together, Dr. Bouchard’s research underscores the profound impact that social and cultural factors, such as loneliness, can have on women’s cardiovascular and brain health. By intentionally integrating gender, diverse demographics, and patient voices into her work, she is helping to ensure that research is relevant and capable of improving real-world health outcomes for women.
Dr. Juan Li
Dr. Juan Li, a data scientist and Senior Clinical Research Associate at the Ottawa Hospital Research Institute, uses predictive modelling and machine learning to improve the efficiency of Parkinson’s disease (PD) diagnosis. Together with her team, Dr. Li has developed an easy-to-use predictive tool for PD, called PREDIGT, which includes a questionnaire and a smell test (given that loss of smell can be one of the earliest PD symptoms) (6). This tool can currently distinguish PD patients from healthy controls with 97% accuracy and from other neurological disorders (such as stroke, dementia, and Alzheimer’s disease) with 81% accuracy (7). BHI is now funding the integration of cardiovascular measurements into the tool, as orthostatic hypotension and reduced heart rate variability are linked to PD but not to other neurological conditions. Dr. Li and her team are investigating whether including measures such as heart rate and blood pressure can further improve the model’s accuracy in differentiating PD from other neurological diseases.
From the very inception of PREDIGT, when it began as a mathematical equation and did not yet include biological measurements from patients, Dr. Li incorporated sex into the model (the “G” in PREDIGT stands for Gender). Parkinson’s disease is approximately 1.5 times more prevalent in men than in women, although this ratio can vary in certain genetic forms of the disease. This gender disparity underscores the need for gender-informed research in PD. In related neurodegenerative disorders, such as dementia and Alzheimer’s disease, the prevalence is notably higher in women, further highlighting the importance of considering sex and gender in brain health research.
In building the PREDIGT model, Dr. Li has always stratified for both males and females to ensure the tool performs effectively for both genders. When asked why it is important to consider women in brain health research, Dr. Li explained:
“In principle, we should always consider sex/gender in doing research, both in basic science and clinical research. Particularly, for Parkinson’s disease, sex is known to be the second most important risk factor, following age, and is included in our PREDIGT Questionnaire as a predictor. Regarding the smell test, females are known to have higher smell test scores than their male counterparts, it is thus important to adjust the raw smell test score by sex and age to accurately assess one’s sense of smell and predict their risk of PD. In our clinical trial to pilot the PREDIGT-PD toolkit (The Ottawa Trial), we ensured that representative number of women were enrolled into the study and we are happy to report that the model had similar diagnostic performance within male and female participants.”
Furthermore, Dr. Li emphasizes the need to encourage the broader research community to integrate women’s brain health into studies “through education and training.” She notes that funding agencies and journals are increasingly requiring the consideration of sex and gender in all aspects of research design and implementation. According to Dr. Li, this “external pressure [will] ensure more researchers start to consider and integrate sex into their study.”
Dr. Li’s research highlights the importance of sex- and gender-informed analyses, even when these factors are not the primary focus of the study. Her work demonstrates how predictive models that account for biological differences between men and women create tools that are both precise and widely applicable.
Reflecting on Women’s Brain Health at the BHI
The BHI is proud to highlight the work of Dr. Bouchard and Dr. Li, whose research demonstrates the wide range of approaches necessary to support and advance women’s brain health. Women’s Brain Health Day serves both as a call for awareness and a celebration of scientists addressing historical gender inequities in the field. To learn more and discover how you can support this movement, visit the Women’s Brain Health Initiative website.
The BHI research presented here sets a standard for work that is intentional and applicable for all. On this day, we honour all the researchers who intentionally include all genders in their study designs and examine how sex- and gender-informed lived experience shapes brain and heart health.
References
- Beery AK. Inclusion of females does not increase variability in rodent research studies. Curr Opin Behav Sci. 2018 Oct;23:143–9.
- Bouchard, Karen [Internet]. University of Ottawa Heart Institute. Available from: https://www.ottawaheart.ca/profile/bouchard-karen
- Social Connections Lab [Internet]. Social Connections Lab. 2025. Available from: https://www.socialconnectionslab.ca/
- WHO Commission on Social Connection [Internet]. World Health Organization. 2025. Available from: https://www.who.int/groups/commission-on-social-connection
- Canadian Social Survey: Loneliness in Canada [Internet]. Statistics Canada. 2021. Available from: https://www150.statcan.gc.ca/n1/daily-quotidien/211124/dq211124e-eng.htm
- Li J, Grimes K, Saade J, Tomlinson JJ, Mestre TA, Schade S, et al. Development of a simplified smell test to identify Parkinson’s disease using multiple cohorts, machine learning and item response theory. npj Parkinsons Dis. 2025 Apr 23;11(1):85.
- Li J, Mestre TA, Mollenhauer B, Frasier M, Tomlinson JJ, Trenkwalder C, et al. Evaluation of the PREDIGT score’s performance in identifying newly diagnosed Parkinson’s patients without motor examination. npj Parkinsons Dis. 2022 July 29;8(1):94.