The influencing factors of cyberchondria in residents in China during the COVID-19 epidemic: health anxiety and online information seeking behavior. Cross-sectional study. (Preprint)

2020 ◽  
Author(s):  
Aijing Luo ◽  
Xiao-Qing Peng ◽  
Yang Chen ◽  
Yi-Chuan Zhang ◽  
Fei Liu ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Information Seeking ◽  
Health Anxiety ◽  
Information Seeking Behavior ◽  
Online Information ◽  
Traditional Media ◽  
Related Information ◽  
Seeking Behavior ◽  
Health Related ◽  
Online Information Seeking

BACKGROUND Cyberchondria is considered “the anxiety-amplifying effects of online health-related searches”, and associated with health anxiety and online health-related information seeking behavior. However, data on the prevalence and influencing variables of cyberchondria are still scarce. Until now, there have been few studies on cyberchondria in residents in China, especially in the context of COVID-19 outbreaks in China. OBJECTIVE To investigate the prevalence and influencing factors of cyberchondria in residents in China during the epidemic period of coronavirus disease 2019. METHODS The participants were 674 community residents of a Chinese city surveyed from February 1 to 15, 2020. We administered online measures, including the Chinese Short Form of the Cyberchondria Severity Scale (CSCS), Short Health Anxiety Inventory (SHAI), eHealth Literacy Scale (eHEALS), Patient Health Questionnaire-15 (PHQ-15), and COVID-19-related online information seeking behavior questionnaire. RESULTS In our study, the average CSCS total score of residents was 30.65±11.53 during the virus epidemic; 79.4% of participants had a moderate level of cyberchondria, while 11.1% experienced a higher level of cyberchondria. Gender, age, monthly income, education level, personal illness with Helicobacter pylori infection, relatives’ illness with chronic bronchitis, COVID-19-related online information seeking frequency and duration were all significantly associated with the CSCS total score (p<.05), SHAI total score (β=0.598>0, P<.05), and eHEALS score (β=0.162>0, P<.05). Searching for information on diagnosing COVID-19 (β=2.28>0, P<.05) and the use of general search engines (β=1.867>0, P<.05) were independent risk factors for cyberchondria, while searching lasting less than 10 minutes each (β=-2.992<0, P<.05), the use of traditional media digital platforms (β=-1.650<0,P<.05), and the use of professional medical communication platforms (β=-4.189<0,P<.05) were independent protective factors for cyberchondria. CONCLUSIONS Most Chinese residents have a moderate level of cyberchondria, and cyberchondria has a strong positive association with health anxiety in residents in China during the virus epidemic. Searching online for less than 10 minutes for COVID-19-related information is an adoptable suggestion, and choosing a traditional media digital platform and a professional medical communication platform are recommended and helpful for alleviating cyberchondria.

scholarly journals The Status and Influencing Factors of Cyberchondria During the COVID-19 Epidemic. A Cross-Sectional Study in Nanyang City of China

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiao-Qing Peng ◽  
Yang Chen ◽  
Yi-Chuan Zhang ◽  
Fei Liu ◽  
Hai-Yan He ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Information Seeking ◽  
Health Anxiety ◽  
Physical Symptoms ◽  
Information Seeking Behavior ◽  
Online Information ◽  
The Status ◽  
Seeking Behavior ◽  
Health Related ◽  
Online Information Seeking

Cyberchondria is considered “the anxiety-amplifying effects of online health-related searches.” During the COVID-19 pandemic, people are likely to search health-related information online for reassurance because of fear and related physical symptoms, while cyberchondria may be triggered due to the escalation of health anxiety, different online seeking behavior preference, information overload, and insufficient e-health literacy. This study aimed to investigate the status and influencing factors of cyberchondria in residents in China during the epidemic period of COVID-19. The participants were 674 community residents of Nanyang city surveyed from February 1 to 15, 2020. We administered online measures, including the Chinese Short Form of the Cyberchondria Severity Scale (C-CSS-12), Short Health Anxiety Inventory (SHAI), eHealth Literacy Scale (eHEALS), Patient Health Questionnaire-15 (PHQ-15), and COVID-19-related online information seeking behavior questionnaire. In our study, the average C-CSS-12 total score of residents was 30.65 ± 11.53 during the virus epidemic; 25% of participants scored 22 or below, 50% scored 23 to 38, and 21.9% scored 39 to 60. The SHAI total score (β = 0.598 &gt; 0, P &lt; 0.001), the use of general search engines (β = 1.867 &gt; 0, P = 0.039), and searching for information on how to diagnose COVID-19 (β = 2.280 &gt; 0, P = 0.020) were independent risk factors for cyberchondria, while searching lasting less than 10 min each (β = −2.992 &lt; 0, P = 0.048), the use of traditional media digital platforms (β = −1.650 &lt; 0, P = 0.024) and professional medical communication platforms (β = −4.189 &lt; 0, P = 0.007) were independent protective factors. Our findings showed that nearly a quarter of the participants scored 39 or higher on the C-CSS-12 in Nanyang city during the pandemic, which should be taken seriously. Health anxiety and COVID-19-related online information seeking behavior including online duration, topics and choice on different information channels were important influencing factors of cyberchondria. These findings have implications for further research and clinical practice on cyberchondria in China.

Tips for Tracking Web Information Seeking Behavior

2011 ◽  
pp. 89-118
Author(s):  
Brian Detlor ◽  
Maureen Hupfer ◽  
Umar Ruhi
Keyword(s):  
Individual Differences ◽  
Information Seeking ◽  
Information Seeking Behavior ◽  
Online Information ◽  
Tracking Data ◽  
Portal Site ◽  
Making Sense ◽  
Web Information ◽  
Seeking Behavior ◽  
Online Information Seeking

This chapter provides various tips for practitioners and researchers who wish to track end-user Web information seeking behavior. These tips are derived in large part from the authors’ own experience of collecting and analyzing individual differences, task, and Web tracking data to investigate people’s online information seeking behaviors at a specific municipal community portal site (myhamilton.ca). The tips discussed in this chapter include: (1) the need to account for both task and individual differences in any Web information seeking behavior analysis; (2) how to collect Web metrics through deployment of a unique ID that links individual differences, task, and Web tracking data together; (3) the types of Web log metrics to collect; (4) how to go about collecting and making sense of such metrics; and (5) the importance of addressing privacy concerns at the start of any collection of Web tracking information.

scholarly journals Digital health literacy and online information seeking in times of COVID-19. A cross-sectional survey among university students in Germany (Preprint)

2020 ◽  
Author(s):  
Kevin Dadaczynski ◽  
Orkan Okan ◽  
Melanie Messer ◽  
Angela Y. M. Leung ◽  
Rafaela Rosário ◽  
...  
Keyword(s):  
Social Media ◽  
Health Literacy ◽  
University Students ◽  
Information Seeking ◽  
Digital Health ◽  
Online Information ◽  
Cross Sectional ◽  
Related Information ◽  
Health Related ◽  
Online Information Seeking

BACKGROUND Digital communication technologies play an important role in governments’ and public health authorities’ health communication strategies during the COVID-19 pandemic. The internet and social media have become important sources of health-related information on the coronavirus and on protective behaviours. In addition, the COVID-19 infodemic spreads faster than the coronavirus itself, which interferes with governmental health-related communication efforts. This puts national public health containment strategies in jeopardy. Therefore, digital health literacy is a key competence to navigate coronavirus-related information and service environments. OBJECTIVE This study aimed to investigate university students’ digital health literacy and online information seeking behaviours during the early stages of the coronavirus pandemic in Germany. METHODS A cross-sectional study among N=14,916 university students aged ≥18 from 130 universities across all sixteen federal states of Germany was conducted using an online survey. Along with sociodemographic characteristics (sex, age, subjective social status) measures included five subscales from the Digital Health Literacy Instrument (DHLI), which was adapted to the specific coronavirus context. Online information seeking behaviour was investigated by examining the online sources used by university students and the topics that students search for in connection with the coronavirus. Data were analysed using univariate and bivariate analyses. RESULTS Across digital health literacy dimensions, the greatest difficulties could be found for assessing the reliability of health-related information (42.3%) and the ability to determine whether the information was written with commercial interest (38.9%). Moreover, respondents also indicated that they most frequently have problems finding the information they are looking for (30.4%). When stratified according to sociodemographic characteristics, significant differences were found with female university students reporting a lower DHLI for the dimensions of ‘information searching’ and of ‘evaluating reliability’. Search engines, news portals and public bodies’ websites were most often used by the respondents as sources to search for information on COVID-19 and related issues. Female students were found to use social media and health portals more frequently, while male students used Wikipedia and other online encyclopaedias as well as YouTube more often. The use of social media was associated with a low ability to critically evaluate information, while opposite differences were observed for the use of public websites. CONCLUSIONS Although digital health literacy is, in summary, well developed in university students, a significant proportion of students still face difficulties with certain abilities to deal with information. There is need to strengthen the digital health literacy capacities of university students using tailored interventions. Improving the quality of health-related information on the internet is also key. CLINICALTRIAL

Tips for Tracking Web Information Seeking Behavior

2010 ◽  
pp. 256-283
Author(s):  
Brian Detlor ◽  
Maureen Hupfer ◽  
Umar Ruhi
Keyword(s):  
Individual Differences ◽  
Information Seeking ◽  
Information Seeking Behavior ◽  
Online Information ◽  
Tracking Data ◽  
Portal Site ◽  
Making Sense ◽  
Web Information ◽  
Seeking Behavior ◽  
Online Information Seeking

This chapter provides various tips for practitioners and researchers who wish to track end-user Web information seeking behavior. These tips are derived in large part from the authors’ own experience of collecting and analyzing individual differences, task, and Web tracking data to investigate people’s online information seeking behaviors at a specific municipal community portal site (myhamilton.ca). The tips discussed in this chapter include: (1) the need to account for both task and individual differences in any Web information seeking behavior analysis; (2) how to collect Web metrics through deployment of a unique ID that links individual differences, task, and Web tracking data together; (3) the types of Web log metrics to collect; (4) how to go about collecting and making sense of such metrics; and (5) the importance of addressing privacy concerns at the start of any collection of Web tracking information.

Functional Model to Online Information Seeking

2020 ◽  
pp. 28-37
Author(s):  
Ashwani Kumar
Keyword(s):  
Information Seeking ◽  
Functional Model ◽  
Information Seeking Behavior ◽  
Online Information ◽  
Online Platform ◽  
Proposed Model ◽  
Seeking Behavior ◽  
Online Information Seeking

This chapter focuses on developing a Functional Model of Online Information Seeking Behavior of Academicians to the effective seeking of an online platform. The unavailability of standard, uniform, and multilingual supportive model is the major reason to prepare this proposal. The proposed model will help in an enhancement of the utilization of the databases provided by government-funded agencies. The main aim of this chapter is to explore the online information seeking behavior and provide a functional model to effective seeking approaches for the academicians.

scholarly journals Online InformationSeeking and Disease Prevention Intent During COVID-19 Outbreak

2020 ◽  
pp. 107769902096151
Author(s):  
Jinhui Li ◽  
Han Zheng
Keyword(s):  
Disease Prevention ◽  
Information Seeking ◽  
Online Survey ◽  
Subjective Norms ◽  
Affective Responses ◽  
Information Seeking Behavior ◽  
Online Information ◽  
Seeking Behavior ◽  
Online Information Seeking ◽  
Practical Implications

Guided by the risk information seeking and processing (RISP) model, this study aims to examine the key determinants that predispose individuals’ online information seeking behavior and prevention intent during the COVID-19 outbreak. Through an online survey with 741 respondents in China, results indicate that affective responses, informational subjective norms, and information insufficiency are positively related to online information seeking about COVID-19. Furthermore, online information seeking is positively associated with prevention intent, and attitude toward prevention partially mediates this association. Finally, theoretical and practical implications of this study are discussed in the context of COVID-19.

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