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The effects of the cognitive bias of unrealistic optimism in the adoption of preventive measures against COVID-19 in dentistry
INTRODUCTION: The bias of unrealistic optimism is people’s tendency to believe that they are less likely to experience negative events than others. Dental professionals are part of a high-risk group for COVID-19. OBJECTIVES: The objective of this study is to investigate whether unrealistic optimism...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Associação Nacional de Medicina do Trabalho (ANAMT)
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9444221/ https://www.ncbi.nlm.nih.gov/pubmed/36118059 http://dx.doi.org/10.47626/1679-4435-2022-834 |
Sumario: | INTRODUCTION: The bias of unrealistic optimism is people’s tendency to believe that they are less likely to experience negative events than others. Dental professionals are part of a high-risk group for COVID-19. OBJECTIVES: The objective of this study is to investigate whether unrealistic optimism bias, concern, and regret can affect the adoption of preventive measures by these professionals. METHODS: We conducted a cross-sectional observational study of dentists recruited remotely by using an electronic form sent by email and social media. A five-point scale was used to identify whether unrealistic optimism, concern, and regret affected the adoption of preventive measures. The study included a total of 339 dentists. The group considered to be unrealistically optimistic accounted for 24.8% of the sample. RESULTS: Unrealistic optimism negatively affected the use of protective equipment by dental professionals. Conversely, concern positively affected preventive measures. CONCLUSIONS: Although most dentists are realistic about the risk of infection compared with their peers, those with optimistic bias might be more susceptible to the disease, as they tend not to adopt recommended protective measures in the workplace. Future studies should also investigate ways of debiasing. |
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