Duke Neuroscientists Find that Using Imagination Exercises Help Older Adults Better Understand Pandemic Risks
The COVID-19 pandemic has created a serious and prolonged public health emergency. Older adults have been at substantially greater risk of hospitalization, intensive care unit admission and death due to COVID-19. As of February 2021, over 81% of COVID-19-related deaths in the US occurred in people over the age of 65. Growing evidence from around the world suggests that age is the greatest risk factor for severe COVID-19 illness and for the experience of adverse health outcomes. Effectively communicating health-related risk information requires tailoring interventions to the needs of older adults.
Using a new informational intervention with a nationally representative sample of 546 US residents, Duke neuropsychologists, including DUPRI’s Gregory Samanez-Larkin, found that older adults reported increased perceived risk of COVID-19 transmission after imagining a personalized scenario with social consequences. Although older adults tended to forget numerical information over time, the personalized simulations elicited increases in perceived risk that persisted over a 1–3 week delay. “The personalized imagination exercise worked better than just hearing the numerical statistics for older people,” said Samanez-Larkin. “This highlights the importance of tailoring public health messages to specific audiences.” These results bear broad implications for communicating information about health risks to older adults and suggest new strategies to combat annual influenza outbreaks.
The study appears in the August 2021 edition of Nature Aging and was recently featured in the Duke Today.
The study was funded by discretionary funding from the Duke Trinity College of Arts and Sciences to G.R.S.-L. and a US National Institute on Aging grant (no. R01-AG058574) awarded to G.R.S.-L. and R.C. A.H.S. is supported by a Graduate Research Fellowship from the National Science Foundation and a Postgraduate Scholarship from the Natural Sciences and Engineering Research Council of Canada. We thank A. Chande, S. Lee, Q. Nguyen, S. J. Beckett, T. Hilley, C. Andris and J. S. Weitz at Georgia Tech and M. Harris at Stanford for openly sharing the tools they developed to assess local virus levels, which made the present studies possible.