Facing up to Frailty

Falls. Lengthy hospitalisation. Loss of independence. Nursing home placement. Death. These are some of the consequences of a clinical condition known as frailty. This course will assist you to face up to frailty – to identify and address it early and help people live happier, healthier lives at home.

About this course

This is a free, self-paced online course.

We often hear the term “frail”, especially as people get older. But what does being frail really mean? Should we accept frailty as a consequence of old age, or can we do something about it? Come and navigate through this taster course to find out how facing up to frailty may just be the missing link to living and ageing well. You’ll hear from people with lived experience of frailty, health professionals and researchers to find out ways to identify and manage frailty, all designed to help people live happier, healthier lives in their own homes and communities for longer.

Course structure

Is frailty the missing link to living and ageing well?
How do you identify someone who is frail and what to do next?
How is frailty addressed?

Why you should do this course?

Meet people with lived experience of frailty, health professionals and researchers to gain a better understanding of frailty as a recognised clinical condition
Learn some of the ways that older people, family members and health professionals can identify frailty
Get some ideas for how to address frailty early and improve the quality of life for people living with frailty
Adapt this information to any setting, regardless of whether you’re a health professional, a family member of someone who is at risk of frailty, an older person, or just curious!

Who is this course for?

This course is for anyone who requires a nuanced perspective on an ageing population and its challenges and is well-suited to health care professionals and public administrators.

Meet the Expert

Dr Debra Palesy

Dr Debra Palesy is a lecturer in the Faculty of Health, at UTS. She has 30 years’ experience in clinical nursing practice, curriculum development and education for a range of health professionals in both acute care and community-based health care settings.

Debra is particularly interested in teaching and learning in socially-isolated health care settings, where workers, such as home care workers and rural nurses, do not have access to direct supervision and support.

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Dr Karen Watson

Dr Karen Watson is an aged care clinician and academic, focused on the care needs of older people in a variety of health settings. She is also a registered nurse with a background in naturopathy. Her research has examined complementary therapy interventions for the behavioural management of older people with and without dementia.

Karen is particularly interested in supporting the care needs of older people challenged by changes in cognition that can occur with healthy ageing and dementia. She holds an adjunct research fellow position with the MARCs Institute of Brain, Behaviour and Development, where she is assisting the Time Travelling with Technology project team to investigate the feasibility and effectiveness of Google Liquid Galaxy and web resources as an intervention for reducing behavioural and psychological symptoms of people with dementia. Karen holds an undergraduate and postgraduate lecturer position where she coordinates and teaches aged care.

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Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.

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Facing up to Frailty

About this course

Course structure

Why you should do this course?

Who is this course for?

Meet the Expert

Related Courses

Modern Slavery in the Home

Human Rights and Emerging Technologies: Research and Capacity Building

Human Rights and Emerging Technologies: an Interdisciplinary Approach

Statistical Thinking

Forecasting NBN Broadband Service Demand

Machine Learning in Train Network Operations

Acknowledgement of Country

START DATE	Start anytime
MODE	Online
DURATION	Self paced