ABSTRACT
Background: Since December 2019, an unexplained pneumonia has broken out in Wuhan, Hubei Province, China. In order to prevent the rapid spread of this disease, quarantine or lockdown measures were taken by the Chinese government. These measures turned out to be effective in containing the contagious disease. In spite of that, social distancing measures, together with disease itself, would potentially cause certain health risks among the affected population, such as sleep disorder. We herein conducted this web search analysis so as to examine the temporal and spatial changes of public search volume of the mental health topic of "insomnia" during COVID-19 pandemic in China. Methods: The data sources included Baidu Index (BDI) to analyze related search terms and the official website of the National Health Commission of the People's Republic of China to collect the daily number of newly confirmed COVID-19 cases. Following a descriptive analysis of the overall search situation, Spearman's correlation analysis was used to analyze the relationship between the daily insomnia-related search values and the daily newly confirmed cases. The means of search volume for insomnia-related terms during the COVID-19 outbreak period (January 23rd, 2020 to April 8th, 2020) were compared with those during 2016-2019 using Student's t test. Finally, by analyzing the overall daily mean of insomnia in various provinces, we further evaluated whether there existed regional differences in searching for insomnia during the COVID-19 outbreak period. Results: During the COVID-19 outbreak period, the number of insomnia-related searches increased significantly, especially the average daily the BDI for the term "1 min to fall asleep immediately". Spearman's correlation analysis showed that 6 out of the 10 insomnia-related keywords were significantly positively related to the daily newly confirmed cases. Compared with the same period in the past four years, a significantly increased search volume was found in 60.0% (6/10) insomnia-related terms during the COVID-19 outbreak period. We also found that Guangdong province had the highest number of searches for insomnia-related during the pandemic. Conclusions: The surge in the number of confirmed cases during the COVID-19 pandemic has led to an increase in concern and online searches on this topic of insomnia. Further studies are needed to determine whether the search behavior truly reflect the real-time prevalence profile of relevant mental disorders, and further to establish a risk prediction model to determine the prevalence risk of psychopathological disorders, including insomnia, using insomnia-related BDI and other well-established risk factors.
ABSTRACT
Background Since December 2019, an unexplained pneumonia has broken out in Wuhan, Hubei Province, China. In order to prevent the rapid spread of this disease, quarantine or lockdown measures were taken by the Chinese government. These measures turned out to be effective in containing the contagious disease. In spite of that, social distancing measures, together with disease itself, would potentially cause certain health risks among the affected population, such as sleep disorder. We herein conducted this web search analysis so as to examine the temporal and spatial changes of public search volume of the mental health topic of “insomnia” during COVID-19 pandemic in China. Methods The data sources included Baidu Index (BDI) to analyze related search terms and the official website of the National Health Commission of the People's Republic of China to collect the daily number of newly confirmed COVID-19 cases. Following a descriptive analysis of the overall search situation, Spearman's correlation analysis was used to analyze the relationship between the daily insomnia-related search values and the daily newly confirmed cases. The means of search volume for insomnia-related terms during the COVID-19 outbreak period (January 23rd, 2020 to April 8th, 2020) were compared with those during 2016–2019 using Student's t test. Finally, by analyzing the overall daily mean of insomnia in various provinces, we further evaluated whether there existed regional differences in searching for insomnia during the COVID-19 outbreak period. Results During the COVID-19 outbreak period, the number of insomnia-related searches increased significantly, especially the average daily the BDI for the term “1 min to fall asleep immediately”. Spearman's correlation analysis showed that 6 out of the 10 insomnia-related keywords were significantly positively related to the daily newly confirmed cases. Compared with the same period in the past four years, a significantly increased search volume was found in 60.0% (6/10) insomnia-related terms during the COVID-19 outbreak period. We also found that Guangdong province had the highest number of searches for insomnia-related during the pandemic. Conclusions The surge in the number of confirmed cases during the COVID-19 pandemic has led to an increase in concern and online searches on this topic of insomnia. Further studies are needed to determine whether the search behavior truly reflect the real-time prevalence profile of relevant mental disorders, and further to establish a risk prediction model to determine the prevalence risk of psychopathological disorders, including insomnia, using insomnia-related BDI and other well-established risk factors. COVID-19;Internet;Baidu index;Insomnia;Web search.
ABSTRACT
BACKGROUND: Recent years have seen an increased incidence of social anxiety due to increasing intensive use of social media, especially among young adults. OBJECTIVE: The present study aimed to translate the original English version of Social Anxiety Scale for Social Media Users (SAS-SMU) into Chinese, examine its applicability among Chinese College students via reliability and validity indexes, and investigate the influencing factors contributing to SAS-SMU. METHODS: A cross-sectional study was conducted among a cohort of 1307 Chinese college students, 486 males and 821 females, aged 20.75 ± 3.13 years old. The original version of SAS-SMU was translated into Chinese using the backward and forward translation procedure. An exploratory factor analysis (EFA) and a confirmatory factor (CFA) analysis were used for construction of underlying factor structure. Criterion-related validity was assessed using Interaction anxiousness scale (IAS) and the "extraversion" domain of Eysenck Personality Short Scale (EPQ-R-S). Cronbach's alpha coefficient was computed for evaluation of internal consistency. A multivariate stepwise linear regression analysis was conducted for determining the potential correlates of SMU-related social anxiety. RESULTS: The final Chinese version of SAS-SMU had 21 items. Item analysis, exploratory factor, EFA, and CFA jointly supported a three-factor structure of the translated version, defined as social recognition anxiety, interaction anxiety, and privacy concern anxiety, respectively. The three-factor structure of this scale showed configural, metric, scalar measurement invariance across gender. Cronbach's alpha coefficient of the scale and its three subscales were 0.96, 0.93, 0.94, and 0.91, respectively. The mean SAS-SMU overall score for each college student was 51.63 ± 16.32, with 21.64 ± 7.24 (recognition anxiety), 17.10 ± 6.30 (interaction anxiety), 12.90 ± 4.61 (privacy concern anxiety) for each subscale, respectively. IAS score, mobile phone addiction index (MPAI) score, EPQ-E score, time spent on social media per week, relationship with parents, childhood life status, whether being an only child, and cyber bullying experience can explain 51.1% of the variance of SMU related social anxiety. CONCLUSION: Based on the data, the Chinese version of SAS-SMU has shown to be satisfactory in psychometric properties. Subjects prone to interaction anxiousness, addictive smartphone use, extraversion personality trait, bad relationship with parents, unfortunate childhood life, only-child status, and having cyberbullying experience tend to have a higher level of SMU related social anxiety.