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Susan Michie on Muck Rack

Susan Michie

United Kingdom
As seen in: Color Research & Application, Nature, The Guardian, Wiley Online Library, Los Angeles Times, BMJ Open, BMJ Quality & Safety, Journal of Epidemiology and Community Health, MDPI, Taylor & Francis Online and
Professor of Health Psychology & Director of Centre for Behaviour Change, UCL, UK. Independent SAGE. Rapidly building a network on @SusanMichie.bsky.social
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Articles

Building an AI-Ready Evidence Base for Behavior Change

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By Susan Michie
| NEJM AI Verified
Reference 1 Abstract Notes Supplementary Material Information & Authors Metrics & Citations Get Access References Media Tables Share Abstract AI has begun to make an impact on the development of interventions to promote healthier behaviors and assist with disease management, primarily through apps and chatbots, but also in health communication campaigns and government policies.
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AI and the future of behavioural science

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By Alexandra Chesterfield, Elisabeth Costa, Oliver Hauser, Dario Krpan, Susan Michie
| LSE Connect Verified
Artificial Intelligence (AI) is transforming various aspects of behavioural science. For example, AI-driven models are being used to predict human behaviour and decision-making, and to design personalized behavioural interventions. AI can also be used to generate artificial research participants on whom behavioural interventions can be tested instead of on humans.
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Motivational effectiveness of prosocial public health messaging to reduce respiratory infection risk: a systematic review and meta-analysis - Communications Medicine

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By Aikaterini Grimani, Susan Michie, Michael Kelly
| Nature Verified
Abstract Clear communication is essential for the effective uptake of public health interventions promoting protective behaviours for respiratory infection control. The emergence of novel infectious diseases, particularly the COVID-19 pandemic, has highlighted the need for rapid adaptation of established and new behavioural practices. However, there remains limited knowledge concerning effective strategies for disseminating risk-reduction information and predicting population responses.
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