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The city of London, Ontario is home to a vibrant health research community. On Wednesday, May 9, researchers from across the city gathered to discuss the importance of equity, diversity and inclusivity (EDI) in the careers of health researchers. Through participation at Exchange: A London Health Research Day Forum on Diversity & Inclusivity, guests discussed the challenges associated with EDI and potential solutions for the future.

Exchange was held the evening before London Health Research Day, the region’s premier research showcase event which features nearly 400 trainee presentations. Trainees are the future of Canadian science and EDI is crucial to that future. This is a topic of national importance that has garnered attention and action from the federal government, funding agencies and scientists across the country.

Recognizing the importance of this topic, Canada’s Minister of Science, The Honorable Kirsty Duncan, and local Member of Parliament for London North Centre, MP Peter Fragiskatos, shared video greetings with Exchange guests.

“The Exchange event highlights a vital area of discussion. It is important to not only recognize but embrace the differences between scientists and the diverse perspectives they bring to research,” said Rebecca Sullivan, a third year PhD candidate at Western University’s Schulich School of Medicine & Dentistry, training in Savita Dhanvantari’s lab at Lawson Health Research Institute, and one of the organizers of the event. “Becoming aware of our own unconscious biases and trying to change these culturally ingrained implicit associations is the only way to make active change in science!”

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Above: Rebecca Sullivan, a third year PhD candidate, leading a scenario-based group activity at Exchange

The evening’s first presenter was Dr. Janet Smylie, Director of the Well Living House Applied Research Centre for Indigenous Infant, Child and Family Health at St. Michael’s Hospital and CIHR Applied Public Health Research Chair in Indigenous Health Knowledge and Information. Dr. Smylie, who also delivered the keynote presentation at London Health Research Day, spoke about the role of anti-Indigenous racism and discrimination within health care professions, including its impact on research. This included a discussion of Dr. Smylie’s own research in the field of Indigenous health.

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Above: Dr. Janet Smylie presenting on "Addressing anti-Indigenous racism and discrimination within health care professions"

Greta Bauer, PhD, a professor in the Department of Epidemiology and Biostatistics at Schulich Medicine & Dentistry, spoke about the role of epidemiology as a toolkit for building equity in health research. This included a discussion on incorporating intersectionality and multidimensionality into population health research methodology.

“The purpose of this work is to give researchers the measurement and statistical tools they need to shift the focus from studying broad population average effects to more heterogeneity within populations,” said Greta. “The whole point is to better study not only diversity in health outcomes, but in the processes that generate those outcomes.”

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Above: Greta Bauer, PhD, presenting on "Epidemiology as a toolkit for building equity"

This talk was followed by a presentation on Gender-Based Analysis Plus (GBA+). GBA+ is an analytical tool used to assess how diverse groups of women, men and gender-diverse people may experience policies, programs and initiatives. The “plus” in GBA+ acknowledges that GBA goes beyond biological (sex) and socio-cultural (gender) differences. We all have multiple identity factors that intersect to make us who we are; GBA+ also considers many other identity factors, like race, ethnicity, religion, age, and mental or physical disability. GBA+ is a method for collecting and reviewing data in an unbiased manner, one that leaves aside many of the assumptions that can mask the GBA+ impacts of a given initiative. Alysha Croker, PhD, Manager, Tri-Agency Institutional Program Secretariat, discussed how GBA+ is being used in research and grant funding, including at the federal funding agencies.

“Diverse research teams can lead to more innovation, greater collective intelligence and an increased capacity to tackle complex issues,” said Alysha, when discussing the importance of EDI in the careers of health researchers.

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Above: Alysha Croker, PhD, presenting on "Incorporating Gender-Based Analysis Plus (GBA+) in research and beyond"

The evening also included a presentation from Shantal Feltham, founder and CEO of Stiris Research, a North American clinical trials management company based in London. Shantal discussed the importance of ensuring that clinical trials are designed to recruit diverse research participants that represent real patient populations. She also discussed her own experiences and perspectives as a female entrepreneur.

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Above: Shantal Feltham delivering a presentation titled "That’s a great idea – It’ll never work"

A group of health research trainees concluded the night with a scenario-based presentation and activity. Audience members were divided into small groups and given a diversity scenario to discuss. Topics ranged from the experiences of LGBTQ+ researchers, racial diversity, physical ability barriers in research labs and more. Notes and ideas from these conversations were recorded and displayed the next day at London Health Research Day.

“Exchange highlighted EDI in health research in action. It featured talks by leading female researchers on issues in Indigenous health and LGBTQ health, implementation of equity in the Canada Research Chairs program, and female entrepreneurship in the field of health research,” said Savita Dhavantari, PhD, assistant director and scientist at Lawson and assistant professor at Schulich Medicine & Dentistry. Savita was also one of the Exchange organizers and the facilitator for the event. “Above all, I hope attendees were encouraged to be fearless in advocating for equity, diversity and inclusivity in health research.”

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Above: Guests at Exchange discussing a diversity scenario

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Above: Savita Dhanvantari, PhD, facilitating the Exchange event

Keynote speaker at joint mental health research day says compassion in action has proven benefit

Compassion in mental health care – and in all health care – is “what separates good from really great” patient outcomes, Calgary-based researcher Shane Sinclair, PhD, told mental health researchers during a conference Oct. 30, 2024, in London.

Sinclair, who heads the Compassion Research Lab at the University of Calgary, was the invited keynote speaker at the Joint Mental Health Research and Innovation Day, attended by about 130 people.

The event was hosted by Lawson Research Institute, London Health Sciences Centre Research Institute and Schulich School of Medicine & Dentistry.

The day also featured 17 poster presentations and 17 oral presentations on different aspects of mental health research. It’s one of the premier annual education-and-development events in mental health science regionally.

This year’s event showcased how compassion could transform health policy, partnerships, systems, care, research and service delivery.

Compassion, respect and excellence are core values of St. Joseph’s Health Care London.

Sinclair noted that the key role of compassion – responding to someone’s suffering with understanding and action – is evidence-based.  

“We do patient-informed and patient-targeted research. And we’ve found compassion makes a difference in how people heal.”
-Shane Sinclair, PhD, compassion researcher

His lab examined the outcomes and satisfaction among patients at 14 emergency rooms across Alberta and found compassion to be the greatest predictor of quality care ratings.  

“What separates good from really great comes down to compassion. These things matter,” Sinclair said.

“It improves their health and their quality of life. It reduces health-care costs, reduces adverse medical outcomes and helps build patients’ trust in the medical information and direction they receive,” he said. 

Psychiatric disorders are often difficult to diagnose. As research advances, we are learning there are multiple subtypes of illness that differ in symptoms and treatment needs, making classification even harder. Post-traumatic stress disorder (PTSD) is one example. Individuals with the more common type of PTSD experience active defensive responses like hyperarousal or outbursts of emotion while those with the dissociative subtype experience additional passive defensive responses like ‘shutting down’ or out-of-body experiences.

In a new study from Lawson Health Research Institute and Western University, researchers combined brain imaging and machine learning to classify with 92 per cent accuracy whether individuals had PTSD and whether or not it was the dissociative subtype. The results highlight the promise of brain imaging as a tool for early diagnosis of psychiatric illness, helping to predict symptom development and treatment needs. 

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Brains scans and machine learning were combined to classify PTSD with 92 per cent accuracy. 

The study involved 181 research participants, including those diagnosed with the more common form of PTSD, the dissociative subtype of PTSD, and healthy individuals with no history of PTSD. They participated in functional magnetic resonance imaging (fMRI) at St. Joseph’s Health Care London and Robarts Research Institute.

Researchers used the high-powered imaging to analyze patterns of resting-state brain activity where participants simply remained in a state of restful wakefulness in an fMRI scanner. The team found that unique patterns of brain activity differed significantly between the three groups.

“Our research group has been leading a number of studies that have shown differences in brain activity and neural connections between healthy individuals and those with different subtypes of PTSD,” says Dr. Ruth Lanius, a researcher at Lawson, professor at Schulich School of Medicine & Dentistry at Western University and psychiatrist at London Health Sciences Centre. “This study further validates that unique patterns of brain activity are associated with different forms of PTSD.”

In the second part of the study, the research team inputted the patterns of brain activity into a machine learning computer algorithm. They found the machine learning system could analyze brain scans to predict whether an individual had PTSD, the dissociative subtype of PTSD or no PTSD with 92 per cent accuracy. 

“Our study suggests brain activity can be used to assist diagnosis of psychiatric disorders and help predict symptoms,” says Andrew Nicholson, PhD, lead author on the study and a post-doctoral fellow at Schulich Medicine & Dentistry who is conducting research at Lawson.  “Patterns of brain activity are objective biomarkers that could be used to diagnose PTSD and, with more research, even predict response to treatment.”

Objective biomarkers hold promise for transforming psychiatric medicine.

“The field of psychiatry does not currently have objective biomarkers like those used to diagnose and understand other illnesses or diseases like cancer,” says Nicholson. “By discovering and validating patterns of brain activity as biomarkers, we can bring objective measures to psychiatry and transform patient care.”

The study, “Machine learning multivariate pattern analysis predicts classification of posttraumatic stress disorder and its dissociative subtype: A multimodal neuroimaging approach,” is published in Psychological Medicine.