Google Trends reveals increases in internet searches for insomnia during the 2019 coronavirus disease (COVID-19) global pandemic

Patient Demand for Ophthalmologists in the United States: A Google Trends Analysis

PURPOSE

To study geographic patterns in ophthalmologist supply and patient demand for services in the United States.

METHODS

Google Trends data for the keywords "ophthalmology" and "ophthalmologist" between 2004 and 2019 were queried and normalized to determine relative search volumes (RSV) for each United States state. Ophthalmologist density was calculated by dividing the number of practicing ophthalmologists by the State Census Bureau population estimates. RSV values were divided by ophthalmologist density and normalized to calculate the relative demand index (RDI) for each state. The number of accredited ophthalmology programs per state was acquired through the Accreditation Council for Graduate Medical Education.

RESULTS

Ophthalmologist concentration was highly heterogeneous across the country. The states with the highest concentration of ophthalmologist per 10,000 people were Washington, DC (1.42), Maryland (0.94), Massachusetts (0.87), and New York (0.86), while the lowest were Wyoming (0.19), Idaho (0.36), New Mexico (0.38), and Nevada (0.39). RSVs ranged from 36 (Alaska and North Dakota) to 100 (Michigan). The highest RDI was found in South Dakota (100), Delaware (84), Michigan (66), and Arizona (56). The lowest RDI was in Washington, DC (0), Hawaii (7), Oregon (8), and Montana (14). The highest number of ophthalmology residency programs were in New York (18), Texas (9), and California (9), whereas 12 states lacked residency programs altogether.

CONCLUSIONS

In this study, we found a wide range in the geographic distribution of ophthalmologists and residency programs in the United States. States with the highest relative demand index may represent areas most at risk of unmet medical needs.

Three measures of internet use, social media use and video game playing as predictors of insomnia during the pandemic among students

Existing research indicates that the relationship between digital technology use and insomnia can largely depend on which digital technology measure and which insomnia measure is considered. Data on 4261 Slovenian tertiary students was gathered through an online survey in February 2021, which included measures of depression and insomnia symptoms, as well as measures of internet, social media and video game use divided into three measurement levels (use, duration of use, addictive use). Regression analysis revealed an apparent effect of measurement level, where addictive use measures consistently outperformed other technology use measures in predicting insomnia. Regardless of measurement level, social media use seems to produce more risk for insomnia, compared to playing video games or general internet use for leisure purposes. Importantly, a single measure of depression symptoms explained more variance in insomnia than the nine measures of digital technology use combined, meaning that the effect of digital technology on sleep should not be overstated. Most of the effect of social media use on insomnia may in fact be explained by understanding users' depression symptoms. In case of gaming, a larger part of its effect on insomnia is independent of depression symptoms.

Does seasonality affect snoring? A study based on international data from the past decade

BACKGROUND

Though snoring is often regarded as a harmless condition that coincides with sound sleep, it is a sleep disorder that can be a potential indicator of more severe conditions such as sleep apnea syndrome. In the present study, we investigated the association between seasonal variations and snoring.

METHOD

Search index for snoring (SIS) data were obtained from Google Trends and Baidu Index. SIS data were collected for the USA, India, Germany, Russia, Japan, Australia, China, and Brazil from 2011 to 2020, with the periodicity of the relationship between seasonal time series data and snoring evaluated using a time series decomposition model.

RESULT

The highest average SIS growth rates from 2011 to 2020 were observed for Brazil, Japan, and Germany, with average SIS values of 94%, 68%, and 49%, respectively. The SIS of the USA, Russia, Japan, Brazil, Australia, Germany, and India increased by 22.3%, 12.4%, 11.9%, 35.4%, 12.3%, 28.0%, and 55.8%, respectively, in comparison with their SIS values in 2019, whereas for China, it decreased by 13.7%. Relative to countries in the southern hemisphere, those in the northern hemisphere showed comparable SIS trends, increasing from September to February and decreasing from March to August.

CONCLUSION

The SIS data showed cyclical changes over the study period. The search index for snoring increased during the cold season or the heating season, suggesting that snoring is associated with seasonal changes.

[Analysis with Google Trends and Our World in Data on Global Mental Health in the Context of the covid-19 Pandemic]

Introduction

During the covid-19 pandemic, mental health services were unable to cope with the high demand from the population, so many people chose to search the Internet for information that could help them cope with the psychological process they were experiencing at the time. The aim of this study was to characterize the global search trend for the term «psychiatry» in the context of covid-19 using Google Trends and Our World in Data.

Methods

Descriptive-cross-sectional study on global search trends for Psychiatry in the context of covid-19 under the terms «psychiatry», «depression», «anxiety», «stress», «insomnia» and «suicide» in the category of health, this was conducted over the period 2020-2021 and time graphs were generated.

Results

The term «psychiatry» remained at a consistently high relative search volume (between 60 and 90), with a significant and gradual search in the month of April. The relative search volume for «depression», «anxiety» and «stress» remained constant with some non-significant fluctuations over the period 2020-2021. The term «insomnia» was predominant between January and June 2020, gradually declining in April and remaining constant until October 2021. Finally, the term «suicide» had a fluctuating RBV between 60 and 100 during this period.

Conclusions

During the study period, the topics related to mental health and the speciality of psychiatry remained constant, with some fluctuating, but not outstanding variations.

Internet searches for "insomnia" and "suicide" mediated by stay-at-home behaviors in 45 countries during the first 12 months of the COVID-19 pandemic

BACKGROUND

This study aimed to investigate (1) the mental health impacts (i.e., insomnia and suicide ideas) of the COVID-19 pandemic and (2) the mediation effects of stay-at-home levels on those impacts.

METHODS

This study investigated monthly national COVID-19 deaths, stay-at-home levels, and internet searches for words for "insomnia" and "suicide" across 45 countries during the first year of the COVID-19 pandemic (March 1, 2020, to February 28, 2021). We used the changes of internet search volumes for "insomnia" and "suicide" (from the Google Trends database) to represent the mental health impacts, and the time of cell phone activity at the residence (from Google Location History) to estimate the stay-at-home effects. We computed the proportion mediated (PM) caused by stay-at-home levels in the COVID-19 impacts on insomnia and suicide ideas, respectively.

RESULTS

Throughout the first year of the COVID-19 pandemic, national COVID-19 deaths significantly correlated to increased internet searches for "insomnia" but decreased searches for "suicide". In addition, the mediation effect was significant in the first six-month of COVID-19-related increases in insomnia (PM = 42.6 %, p = 0.016), but this effect was not significant (PM = 13.1 %, p = 0.270) in the second six-month. By contrast, the mediation effect was not significant in the first six-month of COVID-19-related decrease in suicide ideation (PM = 8.1 %, p = 0.180), but this effect was significant (PM = 39.6 %, p = 0.014) in the second six-month.

CONCLUSIONS

Stay-at-home levels significantly mediated both increased insomnia and decreased suicide ideas, but within different time frames.

COVID-19 Related Early Google Search Behavior and Health Communication in the United States: Panel Data Analysis on Health Measures

The COVID-19 outbreak at the end of December 2019 spread rapidly all around the world. The objective of this study is to investigate and understand the relationship between public health measures and the development of the pandemic through Google search behaviors in the United States. Our collected data includes Google search queries related to COVID-19 from 1 January to 4 April 2020. After using unit root tests (ADF test and PP test) to examine the stationary and a Hausman test to choose a random effect model, a panel data analysis is conducted to investigate the key query terms with the newly added cases. In addition, a full sample regression and two sub-sample regressions are proposed to explain: (1) The changes in COVID-19 cases number are partly related to search variables related to treatments and medical resources, such as ventilators, hospitals, and masks, which correlate positively with the number of new cases. In contrast, regarding public health measures, social distancing, lockdown, stay-at-home, and self-isolation measures were negatively associated with the number of new cases in the US. (2) In mild states, which ranked one to twenty by the average daily new cases from least to most in 50 states, the query terms about public health measures (quarantine, lockdown, and self-isolation) have a significant negative correlation with the number of new cases. However, only the query terms about lockdown and self-isolation are also negatively associated with the number of new cases in serious states (states ranking 31 to 50). Furthermore, public health measures taken by the government during the COVID-19 outbreak are closely related to the situation of controlling the pandemic.

Linking chronic stress to insomnia symptoms in older adults: The role of stress co-occurrence during the pandemic

Studies examining the associations of chronic stressors with sleep health in older adults have shown conflicting results. While the COVID-19 pandemic increased perceived stress at the population level, less is known about chronic stressors experienced by older adults in the context of the COVID-19 pandemic and its impact on sleep health in an aging population. This study aims to examine the association of older adults' chronic stress with insomnia symptoms during the first year of the COVID-19 pandemic. A cross-sectional analysis was performed using early-release COVID-19 data from the Health and Retirement Study. Data on chronic stressors and insomnia symptoms in older adults (N = 2021; mean age = 68.8) were examined. Co-occurrence network analysis, latent class analysis, Rao-Scott χ² tests, and multivariable logistic regression were used to characterize the co-occurrence of chronic stressors and associations with insomnia symptoms. The most common co-occurring chronic stressors during the first year of the COVID-19 pandemic were self-health issues, family-health issues, and financial stress. Older adults experiencing frequent stress co-occurrence had 91% higher odds of difficulty initiating sleep (p < 0.001), 40% higher odds of frequent nocturnal awakening (p = 0.028), and 83% higher odds of nonrestorative sleep (p < 0.001). However, adjustment for health risk factors and COVID-19 concerns attenuated the effects, leaving strongest association for difficulty initiating sleep (odds ratio = 1.51, p = 0.010). Frequent stress co-occurrence plays an important role linking chronic stress to insomnia symptoms in an aging population. Ongoing research is needed to examine the lingering effects of frequent stress co-occurrence on older adults' sleep health in the post COVID-19 era.

Impact of COVID-19 on public social life and mental health: a statistical study of google trends data from the USA

The COVID-19 pandemic has caused a significant disruption in the social lives and mental health of people across the world. This study aims to asses the effect of using internet search volume data. We categorize the widely searched keywords on the internet in several categories, which are relevant in analyzing the public mental health status. Corresponding to each category of keywords, we conduct an appropriate statistical analysis to identify significant changes in the search pattern during the course of the pandemic. Binary segmentation method of changepoint detection, along with the combination of ARMA-GARCH models are utilized in this analysis. It helps us detect how people's behavior changed in phases and whether the severity of the pandemic brought forth those shifts in behaviors. Interestingly, we find that rather than the severity of the outbreak, the long duration of the pandemic has affected the public health status more. The phases, however, align well with the so-called COVID-19 waves and are consistent for different aspects of social and mental health. We further observe that the results are typically similar for different states as well.

Causal Model Analysis of the Effect of Formalism, Fear of Infection, COVID-19 Stress on Firefighters' Post-Traumatic Stress Syndrome and Insomnia

As the front line of epidemic prevention, firefighters are responsible for the transportation of infected cases. Firefighters are under a lot of stress from the new COVID-19, especially the fear that they may contract the virus at work and spread the virus to their families. In particular, the framework of this study incorporates Riggs' formalism variables. When firefighters think that the epidemic prevention regulations are inconsistent with the actual epidemic prevention, it will increase their work pressure on COVID-19. In this study, firefighters from all over Taiwan were used as the respondents, and a total of 453 respondents were obtained. This study uses confirmatory factor analysis and structural equation modeling to test the established hypotheses. The findings confirm that formalism, fear of self and family infection are positively influencing COVID-19 stress. COVID-19 stress positively affects PTSD and insomnia. COVID-19 stress negatively affects problem-focused strategies. Problem-focused strategies negatively affect post-traumatic stress disorder.

Self-efficacy in Insomnia Symptom Management after Digital CBT-I Mediates Insomnia Severity during the COVID-19 Pandemic

STUDY OBJECTIVES

Digital cognitive behavioral therapy for insomnia (dCBT-I) can reduce acute insomnia and depressive symptoms and prevent symptom recurrence. The current study evaluated self-efficacy in managing insomnia symptoms as a potential mediator of the relationship between prior dCBT-I and subsequent insomnia and depressive symptoms assessed during the coronavirus 2019 (COVID-19) pandemic.

METHOD

Participants were 208 adults who completed a randomized controlled trial of dCBT-I versus sleep education in 2016-2017 and also completed self-report assessments of insomnia, depression, and self-efficacy in managing insomnia symptoms. Data were collected in May 2020, five weeks into state-wide COVID-19 stay-at-home orders. Regression and mediation analyses were used to evaluate the extent to which self-efficacy accounted for the relationship between treatment condition and improvement in insomnia and depressive symptoms from pre-treatment to COVID-19 follow-up.

RESULTS

Prior dCBT-I predicted greater self-efficacy in managing insomnia symptoms. Self-efficacy accounted for 49% and 67% of the protective effect of dCBT-I against COVID-era insomnia and depressive symptoms, respectively.

CONCLUSIONS

This study affirms the importance of self-efficacy as a key intervention outcome and potential mechanism by which dCBT-I predicts future sleep and mental health. Future studies that evaluate the role of self-efficacy in treatment effectiveness and resilience can provide additional clues about how to optimize dCBT-I for maximum benefit to public health.

Seasonal Patterns and Trends in Dermatoses in Poland

Background: The amount of data available online is constantly increasing, including search behavior and tracking trends in domains such as Google. Analyzing the data helps to predict patient needs and epidemiological events more accurately. Our study aimed to identify dermatology-related terms that occur seasonally and any search anomalies during the SARS-CoV-2 pandemic. Methods: The data were gathered using Google Trends, with 69 entries between January-2010 and December-2020 analyzed. We conducted the Seasonal Mann–Kendal Test to determine the strength of trends. The month with the highest seasonal component (RSV) and the lowest seasonal component (RSV) was indicated for every keyword. Groups of keywords occurring together regularly at specific periods of the year were shown. Results: We found that some topics were seasonally searched in winter (e.g., herpes, scabies, candida) and others in summer (e.g., erythema, warts, urticaria). Conclusions: Interestingly, downward trends in searches on sexually transmitted diseases in comparison with increased infection rates reported officially show a strong need for improved sexual education in Poland. There were no significant differences in trends for coronavirus-related cutaneous symptoms during 2020. We have shown that the seasonality of dermatologically related terms searched in Poland via Google did not differ significantly during SARS-CoV-2 pandemic.

A Google Trends Approach to Identify Distinct Diurnal and Day-of-Week Web-Based Search Patterns Related to Conjunctivitis and Other Common Eye Conditions: Infodemiology Study

Background

Studies suggest diurnal patterns of occurrence of some eye conditions. Leveraging new information sources such as web-based search data to learn more about such patterns could improve the understanding of patients’ eye-related conditions and well-being, better inform timing of clinical and remote eye care, and improve precision when targeting web-based public health campaigns toward underserved populations.

Objective

To investigate our hypothesis that the public is likely to consistently search about different ophthalmologic conditions at different hours of the day or days of week, we conducted an observational study using search data for terms related to ophthalmologic conditions such as conjunctivitis. We assessed whether search volumes reflected diurnal or day-of-week patterns and if those patterns were distinct from each other.

Methods

We designed a study to analyze and compare hourly search data for eye-related and control search terms, using time series regression models with trend and periodicity terms to remove outliers and then estimate diurnal effects. We planned a Google Trends setting, extracting data from 10 US states for the entire year of 2018. The exposure was internet search, and the participants were populations who searched through Google’s search engine using our chosen study terms. Our main outcome measures included cyclical hourly and day-of-week web-based search patterns. For statistical analyses, we considered P<.001 to be statistically significant.

Results

Distinct diurnal (P<.001 for all search terms) and day-of-week search patterns for eye-related terms were observed but with differing peak time periods and cyclic strengths. Some diurnal patterns represented those reported from prior clinical studies. Of the eye-related terms, “pink eye” showed the largest diurnal amplitude-to-mean ratios. Stronger signal was restricted to and peaked in mornings, and amplitude was higher on weekdays. By contrast, “dry eyes” had a higher amplitude diurnal pattern on weekends, with stronger signal occurring over a broader evening-to-morning period and peaking in early morning.

Conclusions

The frequency of web-based searches for various eye conditions can show cyclic patterns according to time of the day or week. Further studies to understand the reasons for these variations may help supplement the current clinical understanding of ophthalmologic symptom presentation and improve the timeliness of patient messaging and care interventions.

Increased sleep duration and delayed sleep timing during the COVID-19 pandemic

Many studies have examined how the 2019 Coronavirus Disease (COVID-19) has impacted sleep health. Early evidence suggests that lockdown policies worldwide have led to changes in sleep timing, duration, and quality; however, few studies have attempted to look at the longer-term effects across multiple countries in a large data set. This study uses self-reported data from 64,858 users of the Sleep As Android smartphone application from around the world over a 24-month period in 2019 to 2020. We found a significant but modest increase in time in bed (TIB), as well as a significant delay in sleep timing that was especially prominent on weekdays. While this effect persisted throughout the year, differences in sleep timing were more widespread and pronounced in the earlier months of the pandemic. We observed a small overall increase in TIB when comparing 2020 to 2019, but these changes depended on location and time of year, suggesting that sleep duration may have more closely tracked the progression of the pandemic in each country. Our findings suggest that pandemic-induced changes in lifestyle, such as remote work and lockdown policies, may have facilitated later sleep timing but that these changes may diminish as restrictions are lifted.

Associations of lockdown stringency and duration with Google searches for mental health terms during the COVID-19 pandemic: A nine-country study

OBJECTIVES

We examined the associations of lockdown stringency and duration with Google searches for four mental health concepts (i.e., "Anxiety," "Depression," "Suicide," "Mental Health") in nine countries (i.e., Hungary, India, Iran, Italy, Paraguay, Serbia, South Africa, Spain, Turkey) during the COVID-19 pandemic.

METHODS

We retrieved national-level data for each country from Google Trends and the Global Panel Database of Pandemic Policies. In our primary analysis, we used data from all countries to estimate a set of multilevel regression models examining associations of overall lockdown stringency and lockdown duration with relative search volumes for each mental health term. We repeated the models after replacing overall lockdown stringency with each of the lockdown stringency components.

RESULTS

A negative association was found between overall lockdown stringency and "Depression." Lockdown duration and the most stringent stay-at-home requirements were negatively associated with "Anxiety." Policies that recommended or required the cancelation of public events evidenced negative associations with "Depression," whereas associations between policies that required some or all levels of schooling to close and "Depression" were positive. Policies that recommended or required workplaces to close and those that enforced quarantines on non-citizens arriving from high-risk regions or closed borders entirely were negatively associated with "Suicide."

CONCLUSIONS

Lockdown duration and some lockdown policies during the COVID-19 pandemic were generally associated with significantly lower, rather than higher, Google searches for selected mental health terms. These findings could be used alongside other evidence to develop future lockdown strategies that are sensitive to mental health issues during public health crises.

A comprehensive evaluation of COVID-19 policies and outcomes in 50 countries and territories

The COVID-19 pandemic struck the world unguarded, some places outperformed others in COVID-19 containment. This longitudinal study considered a comparative evaluation of COVID-19 containment across 50 distinctly governed regions between March 2020 and November 2021. Our analysis distinguishes between a pre-vaccine phase (March–November 2020) and a vaccinating phase (December 2020–November 2021). In the first phase, we develop an indicator, termed lockdown efficiency (LE), to estimate the efficacy of measures against monthly case numbers. Nine other indicators were considered, including vaccine-related indicators in the second phase. Linear mixed models are used to explore the relationship between each government policy & hygiene education (GP&HE) indicator and each vital health & socioeconomic (VH&SE) measure. Our ranking shows that surveyed countries in Oceania and Asian outperformed countries in other regions for pandemic containment prior to vaccine development. Their success appears to be associated with non-pharmaceutical interventions, acting early, and adjusting policies as needed. After vaccines have been distributed, maintaining non-pharmacological intervention is the best way to achieve protection from variant viral strains, breakthrough infections, waning vaccine efficacy, and vaccine hesitancy limiting of herd immunity. The findings of the study provide insights into the effectiveness of emerging infectious disease containment policies worldwide.

Impact of Breast Cancer Awareness Month on Public Interest in the United States between 2012 and 2021: A Google Trends Analysis

Breast Cancer Awareness Month (BCAM) has a long history of over 30 years, established in 1985 to occur every October, and the National Breast Cancer Foundation now leads the operation. There have been no studies to evaluate the impact of the BCAM on public awareness of breast cancer. We analyzed the impact of BCAM on public awareness of breast cancer in the U.S. from 2012 to 2021 using the relative search volume (RSV) of Google Trends as a surrogate. We also analyzed the impact of Lung Cancer Awareness Month (LCAM) and Prostate Cancer Awareness Month (PCAM) on public awareness of lung and prostate cancer, respectively, to see differences in their effectiveness among the health observances for the top three most common cancers in the U.S. We performed a joinpoint regression analysis to identify statistically significant time points of a change in trend. There were joinpoints around BCAM for “Breast cancer” every year from 2012 to 2021, with a significant increase in the weekly RSVs from 21.9% to 46.7%. Except for 2013 and 2015 for “Lung cancer,” when significant increases in the RSV at 1.8% and 1.2% per week were observed around LCAM, no joinpoints were noted around LCAM or PCAM. These results imply that BCAM has successfully improved the public awareness of breast cancer in the U.S. compared to other representative health observances, likely due to the effective involvement of non-medical industries, influencers affected by breast cancer, and an awareness symbol.

Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis

Background

Google Trends is an infoveillance tool widely used by the scientific community to investigate different user behaviors related to COVID-19. However, several limitations regarding its adoption are reported in the literature.

Objective

This paper aims to provide an effective and efficient approach to investigating vaccine adherence against COVID-19 via Google Trends.

Methods

Through the cross-correlational analysis of well-targeted hypotheses, we investigate the predictive capacity of web searches related to COVID-19 toward vaccinations in Italy from November 2020 to November 2021. The keyword "vaccine reservation" query (VRQ) was chosen as it reflects a real intention of being vaccinated (V). Furthermore, the impact of the second most read Italian newspaper (vaccine-related headlines [VRH]) on vaccine-related web searches was investigated to evaluate the role of the mass media as a confounding factor. Fisher r-to-z transformation (z) and percentage difference (δ) were used to compare Spearman coefficients. A regression model V=f(VRH, VRQ) was built to validate the results found. The Holm-Bonferroni correction was adopted (P*). SEs are reported.

Results

Simple and generic keywords are more likely to identify the actual web interest in COVID-19 vaccines than specific and elaborated keywords. Cross-correlations between VRQ and V were very strong and significant (min r²=0.460, P*<.001, lag 0 weeks; max r²=0.903, P*<.001, lag 6 weeks). The remaining cross-correlations have been markedly lower (δ>55.8%; z>5.8; P*<.001). The regression model confirmed the greater significance of VRQ versus VRH (P*<.001 vs P=.03, P*=.29).

Conclusions

This research provides preliminary evidence in favor of using Google Trends as a surveillance and prediction tool for vaccine adherence against COVID-19 in Italy. Further research is needed to establish the appropriate use and limits of Google Trends for vaccination tracking. However, these findings prove that the search for suitable keywords is a fundamental step to reduce confounding factors. Additionally, targeting hypotheses helps diminish the likelihood of spurious correlations. It is recommended that Google Trends be leveraged as a complementary infoveillance tool by government agencies to monitor and predict vaccine adherence in this and future crises by following the methods proposed in this paper.

Utilizing Big Data From Google Trends to Map Population Depression in the United States: Exploratory Infodemiology Study

BACKGROUND

The epidemiology of mental health disorders has important theoretical and practical implications for health care service and planning. The recent increase in big data storage and subsequent development of analytical tools suggest that mining search databases may yield important trends on mental health, which can be used to support existing population health studies.

OBJECTIVE

This study aimed to map depression search intent in the United States based on internet-based mental health queries.

METHODS

Weekly data on mental health searches were extracted from Google Trends for an 11-year period (2010-2021) and separated by US state for the following terms: "feeling sad," "depressed," "depression," "empty," "insomnia," "fatigue," "guilty," "feeling guilty," and "suicide." Multivariable regression models were created based on geographic and environmental factors and normalized to the following control terms: "sports," "news," "google," "youtube," "facebook," and "netflix." Heat maps of population depression were generated based on search intent.

RESULTS

Depression search intent grew 67% from January 2010 to March 2021. Depression search intent showed significant seasonal patterns with peak intensity during winter (adjusted P<.001) and early spring months (adjusted P<.001), relative to summer months. Geographic location correlated with depression search intent with states in the Northeast (adjusted P=.01) having higher search intent than states in the South.

CONCLUSIONS

The trends extrapolated from Google Trends successfully correlate with known risk factors for depression, such as seasonality and increasing latitude. These findings suggest that Google Trends may be a valid novel epidemiological tool to map depression prevalence in the United States.

Impact of the world hand hygiene and global handwashing days on public awareness between 2016 and 2020: Google trends analysis

BACKGROUND

Scientific evidence suggest that hand hygiene as one of the most effective measures to control infection. To promote good hand hygiene practices, the World Health Organization introduced May 5 as World Hand Hygiene Day (WHHD), and international stakeholders established Global Handwashing Day (GHD) on October 15. However, its contributions to raising public awareness of hand hygiene is unclear.

METHODS

This study evaluates the impact of the WHHD and GHD on the public awareness of hand hygiene in Japan, the United Kingdom, the United States, and worldwide from 2016 to 2020, using the relative search volume of "Hand hygiene" in Google Trends as a surrogate. To identify a statistically significant timepoint of a trend change, we performed Joinpoint regression analysis.

RESULTS

Upticks of the relative search volumes as well as joinpoints were noted worldwide around the WHHD and GHD from 2016 to 2019, but no joinpoints were identified around the WHHD and GHD in 2020. No such changes were observed in Japan, the United Kingdom, and the United States during these periods.

CONCLUSIONS

While the WHHD was originally established to raise awareness of hand hygiene in healthcare facilities, our result suggests that the WHHD and GHD may not have effectively disseminated the importance of hand hygiene to the general public at a country level. Additional policy measures to advocate hand hygiene to the public are necessary to communicate its benefits.

A new infodemiological approach through Google Trends: longitudinal analysis of COVID-19 scientific and infodemic names in Italy

The scientific community has classified COVID-19 as the worst pandemic in human history. The damage caused by the new disease was direct (e.g., deaths) and indirect (e.g., closure of economic activities). Within the latter category, we find infodemic phenomena such as the adoption of generic and stigmatizing names used to identify COVID-19 and the related novel coronavirus 2019 variants. These monikers have fostered the spread of health disinformation and misinformation and fomented racism and segregation towards the Chinese population. In this regard, we present a comprehensive infodemiological picture of Italy from the epidemic outbreak in December 2019 until September 2021. In particular, we propose a new procedure to examine in detail the web interest of users in scientific and infodemic monikers linked to the identification of COVID-19. To do this, we exploited the online tool Google Trends. Our findings reveal the widespread use of multiple COVID-19-related names not considered in the previous literature, as well as a persistent trend in the adoption of stigmatizing and generic terms. Inappropriate names for cataloging novel coronavirus 2019 variants of concern have even been adopted by national health agencies. Furthermore, we also showed that early denominations influenced user behavior for a long time and were difficult to replace. For these reasons, we suggest that the assignments of scientific names to new diseases are more timely and advise against mass media and international health authorities using terms linked to the geographical origin of the novel coronavirus 2019 variants.

Sleep Quality, Insomnia Symptoms, and Depressive Symptomatology among Italian University Students before and during the Covid-19 Lockdown

The COVID-19 pandemic led world authorities to adopt extraordinary measures to counteract the spread of the virus. The Italian government established a national lockdown from 9 March to 3 May 2020, forcing people in their homes and imposing social distancing. During the pandemic emergency, university students emerged as a vulnerable category. Indeed, higher rates of sleep problems and mental disorders were reported in this population. However, these outcomes were derived from cross-sectional investigations adopting retrospective assessments. Retrospective evaluations suffer from different biases, putatively leading to erroneous outcomes. To overcome this limitation, we adopted a between-subject approach comparing a sample of 240 Italian undergraduate university students assessed in 2016 (mean age ± standard deviation, 20.39 ± 1.42, range 18–25; 80.42% females), with an age/gender-matched sample of university students assessed during the third week of lockdown in Spring 2020. We evaluated sleep quality, insomnia symptoms, and depressive symptomatology using validated questionnaires. We found worse sleep quality, a delayed bedtime, and more severe insomnia and depression symptoms in the students sampled under COVID-19 restrictive measures. We suggest paying special attention to this at-risk population during the current pandemic emergency and applying preventive and supportive interventions to limit the exacerbation of sleep and psychological problems.

The impact of the UK COVID-19 pandemic on patient-reported health outcomes after stroke: a retrospective sequential comparison

Background and purpose

The COVID-19 pandemic and related social isolation measures are likely to have adverse consequences on community healthcare provision and outcome after acute illnesses treated in hospital, including stroke. We aimed to evaluate the impact of the COVID-19 pandemic on patient-reported health outcomes after hospital admission for acute stroke.

Methods

This retrospective study included adults with acute stroke admitted to the University College Hospital NHS Foundation Trust Hyperacute Stroke Unit. We included two separate cohorts of consecutively enrolled patients from the same geographical population at two time points: 16th March–16th May 2018 (pre-COVID-19 pandemic); and 16th March–16th May 2020 (during the COVID-19 pandemic). Patients in both cohorts completed the validated Patient Reported Outcomes Measurement Information System–29 (PROMIS-29 version 2.0) at 30 days after stroke.

Results

We included 205 patients who were alive at 30 days (106 admitted before and 99 admitted during the COVID-19 pandemic), of whom 201/205 (98%) provided patient-reported health outcomes. After adjustment for confounding factors, admission with acute stroke during the COVID-19 pandemic was independently associated with increased anxiety (β = 28.0, p < 0.001), fatigue (β = 9.3, p < 0.001), depression (β = 4.5, p = 0.002), sleep disturbance (β = 2.3, p = 0.018), pain interference (β = 10.8, p < 0.001); and reduced physical function (β = 5.2, p < 0.001) and participation in social roles and activities (β = 6.9, p < 0.001).

Conclusion

Compared with the pre-pandemic cohort, patients admitted with acute stroke during the first wave of the COVID-19 pandemic reported poorer health outcomes at 30 day follow-up in all domains. Stroke service planning for any future pandemic should include measures to mitigate this major adverse impact on patient health.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-021-10819-9.

The prevalence of insomnia among health care workers amid the COVID-19 pandemic: An umbrella review of meta-analyses

BACKGROUND

Health care workers (HCWs) during the COVID-19 pandemic experience numerous psychological problems, including stress and anxiety. These entities can affect their sleep quality and predispose them to insomnia. The aim of the present study was to investigate the prevalence of insomnia among HCWs during the COVID-19 crisis via an umbrella review.

METHODS

The PRISMA guideline was used to conduct this review. By searching relevant keywords in databases of Scopus, PubMed, Web of Science, and Google Scholar, studies that reported the prevalence of insomnia among HCWs during the COVID-19 pandemic (January 2020 to the end of January 2021) and had been published in English were identified and evaluated. The random effects model was used for meta-analysis, and the I² index was used to assess heterogeneity. The Egger test was used to determine publication bias. Based on the results of the primary search, 96 studies were identified, and ultimately 10 eligible studies entered the meta-analysis phase.

RESULTS

The results of the umbrella review of meta-analyses showed that the prevalence of insomnia among HCWs during the COVID-19 pandemic was 36.36% (95% CI: 33.36-39.36, I² = 59.6%, p = 0.006).

CONCLUSIONS

The results of this umbrella review of meta-analyses showed a relatively high prevalence of insomnia among HCWs during the COVID-19 pandemic. As insomnia can be associated with other psychological problems, policymakers and health managers should regularly screen HCWs for psychological disorders as well as a possible tendency for suicide. Furthermore, by treating insomnia, one can reduce the incidence of these psychological disorders.

Pre-existing and post-pandemic insomnia symptoms are associated with high levels of stress, anxiety, and depression globally during the COVID-19 pandemic

STUDY OBJECTIVES

The coronavirus disease 2019 (COVID-19) pandemic has led to an increased prevalence of insomnia and mental health symptoms globally. However, most studies to date have not examined mental health symptoms between individuals with insomnia, either pre-existing or developing post-pandemic compared with good sleepers. This study examined differences in stress, anxiety, and depression between individuals with pre-existing insomnia symptoms, post-pandemic insomnia symptoms, and no insomnia symptoms in response to the COVID-19 pandemic.

METHODS

A cross-sectional survey was completed by 2724 participants from 67 countries during the COVID-19 pandemic. Perceived stress, anxiety, and depressive symptoms were compared between individuals with post-pandemic insomnia symptoms (n = 1007), pre-existing insomnia symptoms (n = 804), and no insomnia symptoms (n = 913).

RESULTS

Post-pandemic insomnia symptoms were associated with higher levels of stress, anxiety, and depression than pre-existing or no insomnia symptoms (P < .001). Pre-existing insomnia symptoms were also associated with higher levels of stress, anxiety, and depression than no insomnia symptoms (P < .001). Individuals who met likely criteria for acute insomnia also reported higher stress, anxiety, and depression than those with insomnia disorder (P < .001). Across all groups, individuals reporting a previous mental health diagnosis had worse stress, anxiety, and depression than those without a previous mental health diagnosis (P < .001). Last, individuals from South Africa reported higher levels of stress, anxiety, and depression than other countries (P < .01).

CONCLUSIONS

Internationally, individuals with pre-existing and post-pandemic insomnia symptoms may be more susceptible to stress, anxiety, and depression during the COVID-19 pandemic. Public health initiatives should include insomnia management to improve mental health during the pandemic.

CITATION

Meaklim H, Junge MF, Varma P, Finck WA, Jackson ML. Pre-existing and post-pandemic insomnia symptoms are associated with high levels of stress, anxiety, and depression globally during the COVID-19 pandemic. J Clin Sleep Med. 2021;17(10):2085-2097.

Insomnia, anxiety, and depression during the COVID-19 pandemic: an international collaborative study

Importance and study objective

The COVID-19 pandemic has produced unprecedented changes in social, work, and leisure activities, which all have had major impact on sleep and psychological well-being. This study documented the prevalence of clinical cases of insomnia, anxiety, and depression and selected risk factors (COVID-19, confinement, financial burden, social isolation) during the first wave of the pandemic in 13 countries throughout the world.

Design and participants

International, multi-center, harmonized survey of 22 330 adults (mean age = 41.9 years old, range 18–95; 65.6% women) from the general population in 13 countries and four continents. Participants were invited to complete a standardized web-based survey about sleep and psychological symptoms during the first wave of the COVID-19 pandemic from May to August 2020.

Results

Clinical insomnia symptoms were reported by 36.7% (95% CI, 36.0–37.4) of respondents and 17.4% (95% CI, 16.9–17.9) met criteria for a probable insomnia disorder. There were 25.6% (95% CI, 25.0–26.2) with probable anxiety and 23.1% (95% CI, 22.5–23.6) with probable depression. Rates of insomnia symptoms (>40%) and insomnia disorder (>25%) were significantly higher in women, younger age groups, and in residents of Brazil, Canada, Norway, Poland, USA, and United Kingdom compared to residents from Asian countries (China and Japan, 8% for disorder and 22%–25% for symptoms) (all Ps < 0.01). Proportions of insomnia cases were significantly higher among participants who completed the survey earlier in the first wave of the pandemic relative to those who completed it later. Risks of insomnia were higher among participants who reported having had COVID-19, who reported greater financial burden, were in confinement for a period of four to five weeks, and living alone or with more than five people in same household. These associations remained significant after controlling for age, sex, and psychological symptoms.

Conclusion and relevance

Insomnia, anxiety, and depression were very prevalent during the first wave of the COVID-19 pandemic. Public health prevention programs are needed to prevent chronicity and reduce long-term adverse outcomes associated with chronic insomnia and mental health problems.

Home-Based Sleep Sensor Measurements in an Older Australian Population: Before and during a Pandemic

Older adults are susceptible to poor night-time sleep, characterized by short sleep duration and high sleep disruptions (i.e., more frequent and longer awakenings). This study aimed to longitudinally and objectively assess the changes in sleep patterns of older Australians during the 2020 pandemic lockdown. A non-invasive mattress-based device, known as the EMFIT QS, was used to continuously monitor sleep in 31 older adults with an average age of 84 years old before (November 2019-February 2020) and during (March-May 2020) the COVID-19, a disease caused by a form of coronavirus, lockdown. Total sleep time, sleep onset latency, wake after sleep onset, sleep efficiency, time to bed, and time out of bed were measured across these two periods. Overall, there was no significant change in total sleep time; however, women had a significant increase in total sleep time (36 min), with a more than 30-min earlier bedtime. There was also no increase in wake after sleep onset and sleep onset latency. Sleep efficiency remained stable across the pandemic time course between 84-85%. While this sample size is small, these data provide reassurance that objective sleep measurement did not deteriorate through the pandemic in older community-dwelling Australians.

Relationships Between Internet Use and Sleep Duration in Chinese Adults: A Cross-Sectional Study

Purpose

Most studies that examined the relationship between internet use and sleep were conducted mainly in children and adolescents, and we know little about the use of internet among adults. The purpose of this study is to understand the internet use patterns of Chinese adults and to measure their associations with sleep duration from variety, frequency and type.

Methods

A total of 19,730 samples were selected from 2018 data of the China Health and Retirement Longitudinal study. Internet usage was obtained by specific questions, and the range of sleep period was grouped according to recommendations from the National Sleep Foundation. Kruskal–Wallis H-test and the chi-squared test were used for basic descriptive analysis, and multinomial logistic regression was used to analyze the relationships between internet use and sleep duration. Stata version 15.0 was used for data cleaning, and SPSS version 20.0 was used for statistics analysis.

Results

After screening, a total of 6346 persons were included in the analysis, of which 3148 (49.61%) were males and 3198 (50.39%) were females. Age ranged from 21 to 95 years, most persons were over 45 years old, with the median age of 56 years. Only 1180 (18.59%) participants used the internet, and almost all of them used mobile phones (1137, 96.36%), the other three types were desktop computer (232, 19.66%), laptop computer (69, 5.85%) and tablet (73, 6.19%). There were 912 (77.28%) and 268 (22.71%) participants who used only one and two or more types, respectively. In the unadjusted model, both short sleep and long sleep were associated with internet use compared with normal sleep duration (0.806 [0.708–0.918] p = 0.001; 0.345 [0.251–0.475] p < 0.000). After adjusting for all covariates, the association between long sleep and internet use still persisted (0.612 [0.433–0.865] p = 0.005), but no significant difference was found in short sleep (0.929 [0.803–1.075] p = 0.325).

Conclusion

Internet use was found to be closely associated with sleep and the duration of sleep negatively affected, which may provide new ideas for sleep hygiene recommendations and healthy media use. This conclusion needs more evidence to support.

Sleep in adults from the UK during the first few months of the coronavirus outbreak

The coronavirus disease 2019 (COVID-19) outbreak emerged at the end of 2019 and quickly spread around the world. Measures to counter COVID-19, including social distancing and lockdowns, created an unusual situation that had the potential to impact a variety of behaviours, including sleep, which is crucial for health and well-being. Data were obtained through an online survey. The total sample comprised 19,482 participants from the UK. Participants were asked several questions regarding sleep quality and quantity. Each participant completed the questionnaires once during a data collection period spanning January 20 to March 31, 2020. Data provided by different participants during different weeks (spanning time-periods just before COVID-19 was identified in the UK and during the early weeks following its arrival) were compared using analysis of variance tests and regressions. Regression analyses controlling for age, sex and ethnicity revealed significant associations of small magnitude between date of survey completion and sleep quality, sleep latency, number of awakenings and composite score of poor sleep quality. These analyses also indicated small increases in eveningness tendency as the study progressed. There was no change in sleep duration or time spent awake at night. The COVID-19 outbreak did not appear to impact negatively sleep in a substantial manner during the early stages in the UK. The small increases in sleep quality variables (except for time spent awake at night and sleep duration) and eveningness are nonetheless of interest. Further research is needed to understand how best to provide support to those most in need of a good night's sleep during this unprecedented time.

Impact of the World Antimicrobial Awareness Week on public interest between 2015 and 2020: A Google Trends analysis

OBJECTIVES

To evaluate the impact of the World Antimicrobial Awareness Week (WAAW) on public awareness of antimicrobial resistance using Google Trends analysis.

METHODS

The impact of WAAW on public awareness of 'antimicrobial resistance' (AMR), 'antibacterial', and 'antibiotics' in Japan, the UK, the United States, and worldwide from 2015 to 2020 was analyzed, using the relative search volume (RSV) of Google Trends as a surrogate. A joinpoint regression analysis was performed to identify a statistically significant time point of a change in trend.

RESULTS

No joinpoints around WAAW were identified in Japan, the United Kingdom, or the United States from 2015 to 2020 with RSVs of 'AMR', whereas increasing RSVs were noted worldwide in 2017 and 2020. Further, there were decreasing RSVs of 'antibiotics' in the first half of 2020, which could be due to the COVID-19 pandemic. The study results suggest that WAAW did little to improve public awareness of AMR in the selected countries despite its contribution worldwide.

CONCLUSIONS

This study implies that we need to develop a more effective method to improve public awareness to fight against AMR.

Stress and sleep in college students prior to and during the COVID-19 pandemic

Within the short timeframe of the COVID-19 pandemic, there has been increasing interest in its potential impact on psychological stress and sleep. Using standardized self-report measures, we examined differences in stress and sleep by comparing responses from three independent samples of undergraduates in the United States. Samples were obtained prior to COVID-19 (Spring 2019) and at two periods during the pandemic (Spring 2020 and Summer 2020) which corresponded to an increasing impact of COVID-19 at the local level. Within the combined sample of 1222 students, 94% identified as Hispanic. Contrary to our hypotheses, stress, sleep quality and insomnia were not significantly higher in the samples collected during the COVID-19 pandemic. However, in support of our hypotheses, bedtime and waketime were significantly later during the pandemic, and sleep duration was significantly longer. Although scores on the global measure of sleep quality did not differ across semesters, supplemental exploratory analyses demonstrated a more complex picture of differences in sleep variables. Among the findings, there was evidence of greater sleep latency, greater sleep medication use and poorer sleep efficiency during the pandemic. Our results suggest that, within the US college student population, COVID-19's impact on stress and sleep may not be entirely negative.

Google searches for bruxism, teeth grinding, and teeth clenching during the COVID-19 pandemic

Purpose

Whether coronavirus disease 2019 (COVID-19) pandemic has an impact on bruxism represents an important gap of knowledge. This study evaluated the trends in Google searches, as an indication of public interest and demand, for bruxism and its symptoms during the COVID-19 pandemic.

Methods

Google Trends was queried for bruxism, teeth grinding, and teeth clenching both worldwide and in the United States. Two periods in 2020 (March 15–May 9 and May 10–October 17) were compared to similar periods of 2016–2019 to investigate both initial and short-term interest.

Results

The relative search volume of bruxism, teeth grinding, and teeth clenching was not significantly different between 2020 and 2016–2019 worldwide or in the United States in the March 15–May 9 period. Only the search for teeth grinding showed an increase worldwide. In the May 10–October 17 period, the relative search volume of bruxism, teeth grinding, and teeth clenching all was significantly higher in 2020 compared to 2016–2019 both worldwide and in the United States.

Conclusion

The study showed that the relative search volume for bruxism, teeth grinding, and teeth clenching, as an indication of public interest and demand, was increased both worldwide and in the United States during the May–October 2020 period compared to similar periods of the previous 4 years. Dentists should address this increased public interest and demand for information seeking for bruxism. Follow-up studies monitoring long-term interest as a real-time surveillance and evaluating whether increased internet searches are linked to an actual increase or worsening of bruxism and its symptoms in the clinic are required.

Reliability of Google Trends: Analysis of the Limits and Potential of Web Infoveillance During COVID-19 Pandemic and for Future Research

Background: Alongside the COVID-19 pandemic, government authorities around the world have had to face a growing infodemic capable of causing serious damages to public health and economy. In this context, the use of infoveillance tools has become a primary necessity. Objective: The aim of this study is to test the reliability of a widely used infoveillance tool which is Google Trends. In particular, the paper focuses on the analysis of relative search volumes (RSVs) quantifying their dependence on the day they are collected. Methods: RSVs of the query coronavirus + covid during February 1-December 4, 2020 (period 1), and February 20-May 18, 2020 (period 2), were collected daily by Google Trends from December 8 to 27, 2020. The survey covered Italian regions and cities, and countries and cities worldwide. The search category was set to all categories. Each dataset was analyzed to observe any dependencies of RSVs from the day they were gathered. To do this, by calling i the country, region, or city under investigation and j the day its RSV was collected, a Gaussian distributionX i = X ( σ i , x ¯ i ) was used to represent the trend of daily variations ofx i j = R S V s i j . When a missing value was revealed (anomaly), the affected country, region or city was excluded from the analysis. When the anomalies exceeded 20% of the sample size, the whole sample was excluded from the statistical analysis. Pearson and Spearman correlations between RSVs and the number of COVID-19 cases were calculated day by day thus to highlight any variations related to the day RSVs were collected. Welch's t-test was used to assess the statistical significance of the differences between the average RSVs of the various countries, regions, or cities of a given dataset. Two RSVs were considered statistical confident when t < 1.5 . A dataset was deemed unreliable if the confident data exceeded 20% (confidence threshold). The percentage increase Δ was used to quantify the difference between two values. Results: Google Trends has been subject to an acceptable quantity of anomalies only as regards the RSVs of Italian regions (0% in both periods 1 and 2) and countries worldwide (9.7% during period 1 and 10.9% during period 2). However, the correlations between RSVs and COVID-19 cases underwent significant variations even in these two datasets ( M a x   | Δ |   =   +   625 % for Italian regions, and M a x   | Δ | =   + 175 %   for countries worldwide). Furthermore, only RSVs of countries worldwide did not exceed confidence threshold. Finally, the large amount of anomalies registered in Italian and international cities' RSVs made these datasets unusable for any kind of statistical inference. Conclusion: In the considered timespans, Google Trends has proved to be reliable only for surveys concerning RSVs of countries worldwide. Since RSVs values showed a high dependence on the day they were gathered, it is essential for future research that the authors collect queries' data for several consecutive days and work with their RSVs averages instead of daily RSVs, trying to minimize the standard errors until an established confidence threshold is respected. Further research is needed to evaluate the effectiveness of this method.

Baidu Index and COVID-19 Epidemic Forecast: Evidence From China

With the global spread of the Coronavirus epidemic, search engine data can be a practical tool for decision-makers to understand the epidemic's trends. This article uses trend analysis data from the Baidu search engine, the most widely used in China, to analyze the public's attention to the epidemic and the demand for N95 masks and other anti-epidemic materials and information. This kind of analysis has become an important part of information epidemiology. We have analyzed the use of the keywords "Coronavirus epidemic," "N95 mask," and "Wuhan epidemic" to judge whether the introduction of real-time search data has improved the efficiency of the Coronavirus epidemic prediction model. In general, the introduction of the Baidu index, whether in-sample or out-of-sample, significantly improves the prediction efficiency of the model.

Impact of the World Inflammatory Bowel Disease Day and Crohn's and Colitis Awareness Week on Population Interest Between 2016 and 2020: Google Trends Analysis

Background

More than 6 million people are affected by inflammatory bowel disease (IBD) globally. The World IBD Day (WID, May 19) and Crohn's and Colitis Awareness Week (CCAW, December 1-7) occur yearly as national health observances to raise public awareness of IBD, but their effects are unclear.

Objective

The aim of this study was to analyze the relationship between WID or CCAW and the public health awareness on IBD represented by the Google search engine query data.

Methods

This study evaluates the impact of WID and CCAW on the public awareness of IBD in the United States and worldwide from 2016 to 2020 by using the relative search volume of "IBD," "ulcerative colitis," and "Crohn's disease" in Google Trends. To identify significant time points of trend changes (joinpoints), we performed joinpoint regression analysis.

Results

No joinpoints were noted around the time of WID or CCAW during the study period in the search results of the United States. Worldwide, joinpoints were noted around WID in 2020 with the search for "IBD" and around CCAW in 2017 and 2019 with the search for "ulcerative colitis." However, the extents of trend changes were modest without statistically significant increases.

Conclusions

These results posed a question that WID and CCAW might not have worked as expected to raise public awareness of IBD. Additional studies are needed to precisely estimate the impact of health observances to raise the awareness of IBD.