What Drives Elderly People in China Away from COVID-19 Information?

Abstract

Background: A worrying phenomenon has emerged in recent years: a growing number of people have stopped seeking coronavirus disease 2019 (COVID-19) information and have started deliberately avoiding it. Even though the virulence of COVID-19 has now weakened, the proportion of severe illnesses and deaths in elderly people is still much higher than in other age groups. However, no study has focused on this topic. This is the first study to explore the level of COVID-19 information avoidance among elderly people, and to identify the barriers and potential factors associated therewith. Methods: Convenience sampling was used to recruit 907 elderly people in Wuhan, China. Data collection measures included a sociodemographic questionnaire, health information avoidance scale, information overload scale, general self-efficacy scale, and health anxiety inventory. Results: A total of 72.3% of elderly participants reported COVID-19 information avoidance. Regarding COVID-19-related information reading habits, 44.5% of the elderly only read the title, 16.0% merely skimmed through the content, and 22.9% skipped all relevant information. The most common reasons for this result were information overload (67.5%), underestimation of the infection risk (58.1%), and uselessness of information (56.4%). The main factors associated with COVID-19 information avoidance were recorded as information overload, age, health anxiety, and children (p < 0.05). Conclusions: China should strengthen its health communication regarding COVID-19 in accordance with the characteristics of elderly people, adopt more attractive publicity methods on traditional media, improve censorship about health information, and pay more attention to the childless elderly and the elderly aged 80 and above.

Role of Trust, Risk Perception, and Perceived Benefit in COVID-19 Vaccination Intention of the Public

“…This is inconsistent with the findings of Wise, Zbozinek, Michelini, Hagan, and Mobbs [ 65 ] and Joslyn, Savelli, Duarte, Burgeno, Qin, Han, and Gulacsik [ 66 ], who demonstrated that RPC can be used to predict the behavioral intention of the public. One possible reason for this inconsistency is the underestimation of the risks of the COVID-19 pandemic among Chinese adults [ 91 ]. Such underestimation may be due to the small number of COVID-19-related deaths in China [ 92 ].…”