COVID-19 media fatigue: predictors of decreasing interest and avoidance of COVID-19–related news

Bunevičienė, Inesa; Bunevičius, R.; Bagdonas, Sarunas; Bunevičius, Adomas

doi:10.1016/j.puhe.2021.05.024

Cited by 39 publications

(36 citation statements)

References 22 publications

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“…As hypothesized, people who reported higher levels of pandemic fatigue were those with lower levels of concern, who perceived they are unlikely to be infected, who believed the disease was spreading slowly, who thought they would experience mild disease if infected, or those with depression. Although no causal inferences can be inferred here, other studies have found that less fear of COVID-19 predicted diminished interest in or avoidance of COVID-19 news [41], which is part of the pandemic fatigue definition. In addition, information avoidance predicted a reluctance to engage in COVID-19 preventive behaviors in China [43].…”

Section: Comparison With Prior Workcontrasting

confidence: 65%

“…As a result, they play a crucial role in the increase of incidence rates in several countries, such as in Spain during the summer of 2021 [40]. Younger age was also found to be associated with greater risk of decreasing or diminished interest and avoidance of news about COVID-19 [41]. Therefore, it is necessary to develop campaigns and information strategies specifically addressed to this group of population to overcome these difficulties.…”

Section: Comparison With Prior Workmentioning

confidence: 99%

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Psychometric Properties of the COVID-19 Pandemic Fatigue Scale: Cross-sectional Online Survey Study

Rodríguez‐Blázquez¹,

Romay‐Barja²,

Falcón³

et al. 2022

JMIR Public Health Surveill

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Background Pandemic fatigue is defined as feelings of demotivation to follow preventive measures against COVID-19, together with decreased trust in government and frequency of information-seeking behaviors. Objective This study aims to analyze the psychometric properties of the COVID-19–specific pandemic fatigue scale according to classical test theory (CTT) and Rasch model approaches in the general Spanish population. Methods This was a cross-sectional study in a representative sample of 1018 adults who completed an online survey in November 2020 in the framework of the COVID-19 Snapshot Monitoring (COSMO)-Spain project. The assessments included the 6-item COVID-19 Pandemic Fatigue Scale (CPFS) and other COVID-19–related variables: COVID-19 infection, adherence to preventive behaviors, information-seeking behavior, self-efficacy, worry, and cognitive and affective risk perception. Data quality, acceptability, reliability, and validity were analyzed according to CTT, and the fit to the Rasch model, unidimensionality, appropriateness of the response scale, item local independency, reliability (person-separation index [PSI]), and item-person distribution were also calculated. Results The mean CPFS score was 17.06 (SD 5.04, range 6-30), with higher scores for women, younger participants, participants who never seek information on COVID-19, those who think they would contract a mild disease in case of infection, those with higher level of worry about coronavirus/COVID-19, and those who felt depressed or felt the coronavirus/COVID-19 is spreading slowly (all P<.01). The Cronbach alpha for the CPFS was 0.74. In the confirmatory factor analysis, one factor was identified (root mean square error of approximation [RMSEA]=.02; comparative fit index [CFI]=.99; χ25=8.06, P=.15). The CPFS showed good fit to the Rasch model (χ 224=42.025, P=.01, PSI=.642), unidimensionality (binomial 95% CI –.005 to .045), and item local independency. Conclusions Our results suggest that the CPFS has moderate reliability and internal consistency and it is composed of a single dimension. It is a useful tool to ascertain the level of pandemic fatigue in the general population, which may help to guide the communication and information strategies to face the COVID-19 pandemic.

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Section: Comparison With Prior Workcontrasting

confidence: 65%

Section: Comparison With Prior Workmentioning

confidence: 99%

Psychometric Properties of the COVID-19 Pandemic Fatigue Scale: Cross-sectional Online Survey Study

Rodríguez‐Blázquez¹,

Romay‐Barja²,

Falcón³

et al. 2022

JMIR Public Health Surveill

View full text Add to dashboard Cite

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“…2 shows the proportion of articles per publication source. There is considerable variation in the distribution across sources, with the most articles coming from Yahoo Finance (92,605), MarketScreener (79,551), express.co.uk (44,942), Reuters (23,861), CNBC (20,968), MarketWatch (20,962), TheGuardian (18,953), CNN (17,006), The New York Times (13,784), The Conversation (5,352) and The Motley Fool (3,154). The remaining sources have a relatively low distribution of articles (< 2,500 each).…”

Section: Characteristics Of the Datasetmentioning

confidence: 99%

“…As agenda-setters, journalists fuel and respond to these information needs [4]. But in the case of COVID-19, news media's herd behavior cascaded in overreporting on the topic, such that the longer the pandemic lasted, the more people became "coronavirus-news-fatigued" [3,5]. Decisionmakers in organizations engage in issue management to cope with exogenous challenges such as those posed by the pandemic crisis.…”

Section: Introductionmentioning

confidence: 99%

Agenda-Setting for COVID-19: A Study of Large-Scale Economic News Coverage Using Natural Language Processing

Businger

Dollfus

et al. 2022

Int J Data Sci Anal

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Over the past two years, organizations and businesses have been forced to constantly adapt and develop effective responses to the challenges of the COVID-19 pandemic. The acuteness, global scale and intense dynamism of the situation make online news and information even more important for making informed management and policy decisions. This paper focuses on the economic impact of the COVID-19 pandemic, using natural language processing (NLP) techniques to examine the news media as the main source of information and agenda-setters of public discourse over an eight-month period. The aim of this study is to understand which economic topics news media focused on alongside the dominant health coverage, which topics did not surface, and how these topics influenced each other and evolved over time and space. To this end, we used an extensive open-source dataset of over 350,000 media articles on non-medical aspects of COVID-19 retrieved from over 60 top-tier business blogs and news sites. We referred to the World Economic Forum’s Strategic Intelligence taxonomy to categorize the articles into a variety of topics. In doing so, we found that in the early days of COVID-19, the news media focused predominantly on reporting new cases, which tended to overshadow other topics, such as the economic impact of the virus. Different independent news sources reported on the same topics, showing a herd behavior of the news media during this global health crisis. However, a temporal analysis of news distribution in relation to its geographic focus showed that the rise in COVID-19 cases was associated with an increase in media coverage of relevant socio-economic topics. This research helps prepare for the prevention of social and economic crises when decision-makers closely monitor news coverage of viruses and related topics in other parts of the world. Thus, monitoring the news landscape on a global scale can support decision-making in social and economic crises. Our analyses point to ways in which this monitoring and issues management can be improved to remain alert to social dynamics and market changes.

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“…COVID-19 information avoidance among the elderly should therefore be taken seriously. However, previous studies on COVID-19 information avoidance has mainly focused on populations at large, college students, and consumers [ 14 , 27 , 28 , 29 , 30 , 31 ]. No studies, to the best of our knowledge, have been undertaken on COVID-19 information avoidance among elderly people.…”

Section: Introductionmentioning

confidence: 99%

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

Gao

Ding

2022

IJERPH

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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.

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COVID-19 media fatigue: predictors of decreasing interest and avoidance of COVID-19–related news

Cited by 39 publications

References 22 publications

Psychometric Properties of the COVID-19 Pandemic Fatigue Scale: Cross-sectional Online Survey Study

Psychometric Properties of the COVID-19 Pandemic Fatigue Scale: Cross-sectional Online Survey Study

Agenda-Setting for COVID-19: A Study of Large-Scale Economic News Coverage Using Natural Language Processing

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

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