A team of faculty members from across MacEwan University is studying a new online learning tool designed to help social work and psychiatric nursing students identify signs of clinical depression in older adults.
“It’s easy to miss talking about geriatric depression when we’re concerned about a person being at risk for falls or when they have other urgent health concerns,” says Dr. Anna Azulai, assistant professor of social work. “But left unaddressed, geriatric depression can have devastating consequences for quality of life. It also exacerbates other health concerns, worsens overall health prognosis and increases healthcare costs.”
Identifying and treating clinical depression in older adults, on the other hand, can enhance quality of life and decrease the burden of other diseases. And when social workers, nurses and other members of interprofessional care teams can recognize signs of depression in a timely way and refer older adults to appropriate supports, treatment can happen faster, says Azulai.
Geriatric depression by the numbers
Geriatric depression affects 15 per cent of older adults living in their own homes, almost 21 per cent of older adults who require home care and over 38 per cent of older adults in long-term care facilities.
Azulai believes those numbers are likely understated, given the pandemic’s mental health implications, the stigma older adults might feel about mental health conditions, and because signs of geriatric depression can easily be misinterpreted as normal parts of the aging process and go underreported.
Working with MacEwan’s Clinical Simulation Centre and eLearning Office, the research team created a learning module that includes a virtual simulation of a depression screening interview. In the video, an actor plays an older client connecting online with an off-camera clinician. Students watch the interaction unfold, focusing on the client’s answers as the clinician asks questions from two depression screening tools and suicide assessment protocol.
“We wanted to realistically capture the dynamic that happens between clinician and client experiencing symptoms of clinical depression, and model for students how to include screening questions in a meaningful and empathetic conversation, not just a series of questions,” says Azulai.
Social work students in a fourth-year gerontology class are currently testing the module and contributing to a research project that will gauge this approach’s effectiveness. Students take a pretest to check their baseline knowledge, complete the module and then do a post-test to measure their learning about geriatric depression and how to screen for it. In the Winter term, a second round of students – a fourth-year social work advanced practice course and a first-year psychiatric nursing foundations course – will use the module.
Once the research team has collected all of the data from this pilot, they plan to use it to adjust the module and potentially expand it to other disciplines at MacEwan, including nursing and physical and occupational therapy. There is also the potential to use the module as a professional development and interprofessional training tool outside of the university, says Azulai.
“If we find this approach is successful in our classrooms, we can expand it into other settings where, because of COVID-19, virtual assessments are now happening more than ever before,” says Azulai. “Our hope is that supporting interprofessional teams in this way can provide more holistic services for clients.”
The module was developed with the support from Chunyan Zhang, a simulation technologist with the university’s Clinical Simulation Centre, and Mavis Leung, an educational technology facilitator. The research project team includes Azulai; Brandi Pawliuk, teaching faculty in the Department of Nursing Practice ; Dr. Jill Vihos, assistant professor and chair in the Department of Professional Nursing and Allied Health; Dr. Hongmei Tong, assistant professor of social work; Lynn Feist, director of eLearning; and Ellen Brown, associate professor of nursing at Florida International University. This project is funded with internal project grant funding from MacEwan's Office of Research Services.
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