The effect of fear and situational motivation on online information avoidance: The case of COVID-19

The effect of fear on health information searching behavior during the pandemic: The case of COVID-19

BACKGROUND AND OBJECTIVES

Fear can cause people to panic, lead to erroneous decisions, and trigger inappropriate behavior. This study aims to investigate the effects of fear of COVID-19 on the perception of the reliability and the use of health information sources.

METHODS

This study is both a cross-sectional and explanatory study. The participants selected by convenience sampling method were 323 students attending a state university in Turkey. The Fear of COVID-19 Scale (FCV-19S) and the Health Information Sources Survey were used as data collection tools. Descriptive statistics, correlation coefficients, and linear regression analyses were used.

RESULTS

The participants' mean FCV-19S score was 2.30 ± 0.93 on a five-point Likert scale. In the range of 0-10, the information source with the highest reliability perception mean score was the doctor (8.05 ± 2.54), whereas that with the highest usage was the Internet (7.98 ± 2.77). Although the fear of COVID-19 had a negative effect on Internet use (b = -0.38; p < 0.05), the effects on the use of other health information sources were positive (b = 0.37-0.83; p < 0.05). Trust in radio (b = 0.60; p < 0.05) and newspapers/magazines (b = 0.49; p < 0.05) also increased with fear.

CONCLUSIONS

These results showed that as university students' fear of COVID-19 increased, the use of the Internet for health information decreased; however, the use of doctors, nurses, pharmacists, other health workers, scientific articles, television, radio, and newspapers/journals increased. Nurses were the source of information whose use increased the most, along with increased fear. The findings can guide health policies to be followed. Not only doctor talks but also nurse talks and scientific videos should be increased on the Internet, social media, and other mass media.

Infodemic: Challenges and solutions in topic discovery and data process

BACKGROUND

The Coronavirus Disease 2019 (COVID-19) pandemic was a huge shock to society, and the ensuing information problems had a huge impact on society at the same time. The urgent need to understand the Infodemic, i.e., the importance of the spread of false information related to the epidemic, has been highlighted. However, while there is a growing interest in this phenomenon, studies on the topic discovery, data collection, and data preparation phases of the information analysis process have been lacking.

OBJECTIVE

Since the epidemic is unprecedented and has not ended to this day, we aimed to examine the existing Infodemic-related literature from January 2019 to December 2022.

METHODS

We have systematically searched ScienceDirect and IEEE Xplore databases with some search limitations. From the searched literature we selected titles, abstracts and keywords, and limitations sections. We conducted an extensive structured literature search and analysis by filtering the literature and sorting out the available information.

RESULTS

A total of 47 papers ended up meeting the requirements of this review. Researchers in all of these literatures encountered different challenges, most of which were focused on the data collection step, with few challenges encountered in the data preparation phase and almost none in the topic discovery section. The challenges were mainly divided into the points of how to collect data quickly, how to get the required data samples, how to filter the data, what to do if the data set is too small, how to pick the right classifier and how to deal with topic drift and diversity. In addition, researchers have proposed partial solutions to the challenges, and we have also proposed possible solutions.

CONCLUSIONS

This review found that Infodemic is a rapidly growing research area that attracts the interest of researchers from different disciplines. The number of studies in this field has increased significantly in recent years, with researchers from different countries, including the United States, India, and China. Infodemic topic discovery, data collection, and data preparation are not easy, and each step faces different challenges. While there is some research in this emerging field, there are still many challenges that need to be addressed. These findings highlight the need for more articles to address these issues and fill these gaps.