Media releases

  • COVID-19 saw more residents transfer to Canadian long-term care on ‘inappropriate’ antipsychotics: Brock-led study

    MEDIA RELEASE – December 17, 2024 – R0143

    A disproportionately high number of people admitted to long-term care facilities during the COVID-19 pandemic’s first year were on antipsychotic medications, recently published Brock-led research has found.

    The newly arrived residents, who mostly came from hospitals and community settings, were also prescribed these drugs without a psychosis diagnosis, says the study’s lead author, Assistant Professor of Health Sciences Luke Turcotte.

    “When a person doesn’t have any indications of psychosis, then we consider these medications to be potentially inappropriate for this population,” he says. “Because people on antipsychotic medications are at greater risk of falls, stroke and all-cause mortality, these shouldn’t be the first line of treatment for persons living with dementia.”

    In their study, “Antipsychotic Medication Use Among Newly Admitted Long-term Care Residents During the COVID-19 Pandemic in Canada,” the research team identified about 84,000 people who were newly admitted to long-term care facilities in Alberta, British Columbia and Ontario between March 5, 2018, and March 4, 2021.

    New admissions were grouped into categories based on the referral sources, including hospitals, assisted living facilities and private homes, in-patient continuing care and rehabilitation facilities, psychiatric wards and other sources.

    Using data from the Canadian Institute for Health Information (CIHI), the research team compared antipsychotic medication use among people admitted before and during the COVID-19 period who had not been diagnosed with psychosis, as well as where they came from.

    The rate of “inappropriate prescriptions” for newly admitted residents rose from 22 per cent in 2018-19 to 27 per cent in 2020-21, the study says.

    The researchers also found fewer residents underwent a process called “deprescribing,” where patients are taken off medications that may no longer be needed or could be causing harm.

    Turcotte says antipsychotic medications are often used “off-label” to manage behaviours such as agitation, aggression and resistance to care, which are ways that persons living with dementia may express unmet needs and concerns.

    “It’s unclear why antipsychotic use in hospitals increased,” he says. “It’s likely that visitor restrictions limited families’ ability to support and advocate for their loved ones in the unfamiliar and potentially distressing hospital environment.”

    This latest research follows up on a previous study Turcotte published last year. It examined the impact of the pandemic on numerous measures of quality of care in Canadian long-term care homes and found an increase in antipsychotic drug use was widespread in Canadian long-term care facilities during the first year of the pandemic.

    The current study, published last month, did a deeper dive on this issue. It revealed that some of this increase was due to people arriving at long-term care facilities already on the antipsychotic medications coupled with a lower deprescribing rate within the first three months of their stay.

    Turcotte says delirium prevention initiatives, like Ontario Health’s Delirium Aware Safer Healthcare (DASH) campaign, are part of the solution.

    “These medications are often first administered to treat delirium, and their use can persist after the person leaves the hospital,” he says. “It’s important that we continue to empower health-care professionals to use person-centred approaches that put an emphasis on understanding each person’s life story and tailoring care to their individual needs.”

    Led by Turcotte, the research team includes researchers from St. Joseph’s Health Care in London, Western University, the Lawson Research Institute in London, Dalhousie University in Halifax, SE Health in Markham, University of Toronto, University of Waterloo, St. Joseph’s Health System, and Sinai Health, Toronto.

    For more information or for assistance arranging interviews:

    * Sarah Ackles, Communications Specialist, Brock University [email protected] or 289-241-5483

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    Categories: Media releases

  • Research shows how math can predict when people will — or won’t — share news

    MEDIA RELEASE – December 10, 2024 – R0142

    Discussing big news stories online is a common experience among those who use social media. But at what point do people decide to share – or not share – posts with friends, family and followers?

    It turns out math could reveal the answer.

    Brock University Assistant Professor of Mathematics and Statistics Pouria Ramazi and his international research collaborators from Canada, Iran and Hong Kong have used a mathematical model to predict when individuals will both start and stop behaviours when other people are doing the same thing.

    For decades, the “linear threshold model” has provided a framework for understanding the timing of people’s actions. This model assumes each person has a unique tipping point — called the threshold — that determines when they will adopt a behaviour based on the fraction of the population exhibiting it around them, says Ramazi.

    “If, let’s say, only 10 per cent of my friends are talking about something, I may not share it,” he says. “But if 50 per cent spread that news, it looks like it is getting important, so I may want to also talk about it.”

    What was missing in the model until now was an “upper threshold” to set a cap on when the individual would stop adopting the behaviour, such as talking about the news, says Ramazi.

    A bi-threshold model could guide marketers, officials, businesses and others to estimate an approximate level of outreach before overselling their message, he says.

    In their recent study, “Enough but not too many: A bi-threshold model for behavioral diffusion,” the researchers say previous social science research has revealed the possibility of this upper threshold through three mechanisms.

    One is the “congestion effect,” where someone may want to hit the beach with a few friends, for example, but probably not if the beach is packed.

    The second is the “snob effect” in which a fashion-conscious person, for example, will purchase an outfit to stand out from the crowd but will stop wearing it when the clothing becomes too trendy.

    The third mechanism, “saturation,” occurs when spreading news, gossip, jokes or other information becomes less appealing as more people know about it.

    To test the existence of this upper threshold, Ramazi and colleagues used social media datasets gathered from three situations: the 2012 discovery in physics of a new heavy particle on Twitter, now known as X, coverage of the popular Melbourne Cup horse race on X and discussion on the COVID-19 vaccination campaign on the Chinese social media platform Weibo.

    The datasets included measures of social media behaviour — such as postings, likes and mentions — as well as the number of contacts for each user included in the study.

    The team used data-driven techniques to group users based on their available information and estimated the lower and upper thresholds for each group based on their social media behaviour.

    The researchers then created and evaluated two models for the three situations: one model with just the lower threshold, or point at which people would start sharing information on social media, and another with both a lower and an upper threshold, or point when people would stop sharing.

    “The model that used both the lower threshold and the upper threshold was able to better predict the spread of the news in the population, sometimes by orders of magnitude more accurately,” he says. “This suggests that this second, upper threshold does exist in at least some social contexts.”

    Ramazi says the findings provide insights into how groups behave, such as how information spreads or new ideas are adopted, and that this knowledge can help improve strategies in areas such as marketing, public health and policy-making. He adds that future research can verify this model in other real-world scenarios and analyze the resulting decision-making dynamics theoretically.

     

    For more information or for assistance arranging interviews:

    *Sarah Ackles, Communications Specialist, Brock University [email protected] or 289-241-5483

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    Categories: Media releases