Web Search Trends Research Articles

From science to society: Exploring the nexus between obesity research and public awareness in Brazil

Raising public awareness about the medical aspects of obesity is crucial in Brazil, given its escalating prevalence. This study investigated the correlation between scientific research on obesity in the country and public awareness by scrutinizing scientific publications and online search trends. Scientific data were sourced from Dimensions, while online engagement data were extracted from Google Trends. Key metrics were analyzed, including scientific publication trends, Altmetrics, news image trends, YouTube trends, and web search trends. Linear regression and the Mann-Kendall test assessed trends, and Principal Component Analysis (PCA) explored dataset variations.Scientific publications on obesity in Brazil consistently increased from 2004 to 2023, reflecting growing scientific interest. The number of publications increased from 300 in 2004 to 7566 in 2022, representing a 25-fold increase. However, web search trends among the general population declined by 79 % during the same period, indicating ineffective "knowledge translation”. Altmetrics and news image trends fluctuated, while YouTube trends exhibited a decline. The disparity between scientific publications and public web search trends highlights the necessity for more efficient scientific information communication.The gap between scientific publishing and public web search trends highlights the need for improved scientific communication. Measures such as formal science communication training for scientists, leveraging social media, embracing arts-based approaches, and nurse advocacy can facilitate informed public discourse and foster interest in obesity-related topics.

Public interest trends for COVID-19 and pandemic trajectory: A time-series analysis of US state-level data.

Google Trends provides spatiotemporal data for user-specific terms scaled from less than 1 (lowest relative popularity) to 100 (highest relative popularity) as a proxy for the public interest. Here we use US state-level data for COVID-19 to examine popularity trends during the pandemic evolution. We used "coronavirus" and "covid" search terms and set the period up from January 1st, 2020, to November 12, 2022. We measured the agreement on web rankings between states using the nonparametric Kendall's W (0 for no concordance to 1 for perfect agreement). We compiled state-level weekly data on COVID-19 incidence and mortality and scaled state curves from 0 to 100 through a min-max normalization process. We used a dynamic time-warping algorithm to calculate similarities between the popularity, mortality, and incidence of COVID-19. The methodology is a pattern recognition process between time series by distance optimization. The similarity was mapped from 0 to 1, with 1 indicating perfect similarity and 0 indicating no similarity. The peak in popularity was in March 2020, succeeded by a decline and a prolonged period of fluctuation around 20%. Public interest rose briefly at the end of 2021, to fall to a low activity of around 10%. This pattern was remarkably consistent across states (Kendal's W 0.94, p < 0.001). Web search trends were an impression of contagion growth: Overall, popularity-mortality trajectories yielded higher similarity indices (median 0.78; interquartile range 0.75-0.82) compared to popularity-incidence trajectories (median 0.74; interquartile range 0.72-0.76, Wilcoxon's exact p<0.001). The popularity-mortality trajectories had a very strong similarity (>0.80) in 19/51 (37%) regions, as opposed to only 4/51 (8%) for popularity-incidence trajectories. State-level data show a fading public concern about COVID-19, and web-search popularity patterns may reflect the COVID-19 trajectory in terms of cases and mortality.

Is it possible to estimate the number of patients with COVID-19 admitted to intensive care units and general wards using clinical and telemedicine data?

Gabaldi et al. utilized telemedicine data, web search trends, hospitalized patient characteristics, and resource usage data to estimate bed occupancy during the COVID-19 pandemic. The results showcase the potential of data-driven strategies to enhance resource allocation decisions for an effective pandemic response. To develop and validate predictive models to estimate the number of COVID-19 patients hospitalized in the intensive care units and general wards of a private not-for-profit hospital in São Paulo, Brazil. Two main models were developed. The first model calculated hospital occupation as the difference between predicted COVID-19 patient admissions, transfers between departments, and discharges, estimating admissions based on their weekly moving averages, segmented by general wards and intensive care units. Patient discharge predictions were based on a length of stay predictive model, assessing the clinical characteristics of patients hospitalized with COVID-19, including age group and usage of mechanical ventilation devices. The second model estimated hospital occupation based on the correlation with the number of telemedicine visits by patients diagnosed with COVID-19, utilizing correlational analysis to define the lag that maximized the correlation between the studied series. Both models were monitored for 365 days, from May 20th, 2021, to May 20th, 2022. The first model predicted the number of hospitalized patients by department within an interval of up to 14 days. The second model estimated the total number of hospitalized patients for the following 8 days, considering calls attended by Hospital Israelita Albert Einstein's telemedicine department. Considering the average daily predicted values for the intensive care unit and general ward across a forecast horizon of 8 days, as limited by the second model, the first and second models obtained R² values of 0.900 and 0.996, respectively and mean absolute errors of 8.885 and 2.524 beds, respectively. The performances of both models were monitored using the mean error, mean absolute error, and root mean squared error as a function of the forecast horizon in days. The model based on telemedicine use was the most accurate in the current analysis and was used to estimate COVID-19 hospital occupancy 8 days in advance, validating predictions of this nature in similar clinical contexts. The results encourage the expansion of this method to other pathologies, aiming to guarantee the standards of hospital care and conscious consumption of resources. Developed models to forecast bed occupancy for up to 14 days and monitored errors for 365 days. Telemedicine calls from COVID-19 patients correlated with the number of patients hospitalized in the next 8 days.

Navigating Uncharted Waters via Web Search Trends: The Impact and Recovery of the Pacific Tourism Industry Amidst the COVID-19 Pandemic

The Tourists’ regular leveraging of web searches on Pacific tourism industries in Fiji, indicates insights into macroeconomic behavior during and after the devasting pandemic lookout. In this research, the authors adopted a method of quantitative research to collect and analyze numerical data to identify patterns, relationships, and trends among web search results on accommodation bookings in the Pacific. Statistical examination of tourist web search trends transcends interpretation of tourist preferences, and decision-making processes in the travel and tourism industry. Web search trends during the pandemic have significantly dropped for accommodation bookings in the Pacific. The impact of the pandemic on the tourism industry in the Pacific has been severe, still, there are signs of recovery as Pacific countries slowly reopen their borders and implement travel bubbles with neighboring nations. The industry is expected to recover gradually, but it may take several months before tourist accommodation bookings and web searches return to a stable level. This paper highlights the severe impact of the pandemic on the Pacific tourism industry. It discusses prospects for recovery as countries work towards reopening and revitalizing tourism sectors by optimizing search algorithms and user experiences.

Confirmation Bias in Seeking Climate Information: Employing Relative Search Volume to Predict Partisan Climate Opinions

In an increasingly digitized world, online information-seeking (OIS) behaviors have reflected people’s intentions and constituted a critical component in synthesizing public opinion. Climate change is among the gravest threats facing the world today, and previous studies have adopted OIS data to gauge public interest in climate change. However, such studies have ignored the psychological attributes of search keywords and the role of social identities in influencing OIS. This study explores whether search strategies align with the expected confirmation biases of regions with different partisan beliefs. We use spatial web search trends to show the significant differences in the search keywords adopted by the Democrat-majority (“climate change”) versus the Republican-majority (“global warming”) regions of the United States. Furthermore, using the region-level search and survey data (2008–2018), we demonstrate that the preferential use of search keywords can predict climate opinions. This study concludes by discussing the significant findings and the open questions for future work.

The cost of anti-Asian racism during the COVID-19 pandemic.

Anti-Chinese sentiment increased during the COVID-19 pandemic, presenting as a considerable spike in overt violence and hatred directed at Asian American individuals. However, it is less clear how subtle patterns of consumer discrimination, which are difficult to directly observe yet greatly impact Asian American livelihoods, changed through the pandemic. Here we examine this in the context of restaurants-ubiquitous small businesses that sell goods that are closely entwined with ethnicity. Using a series of surveys, online search trends and consumer traffic data, we find that Asian restaurants experienced an 18.4% decrease in traffic (estimated US$7.42 billion lost revenue in 2020) relative to comparable non-Asian restaurants, with greater decreases in areas with higher levels of support for Donald Trump. Our findings are consistent with the roles of collective blame, out-group homogeneity and ethnic misidentification in explaining how anti-China rhetoric can harm the Asian American community, underlining the importance of avoiding racism and stigmatization in political and public health communications.

Trends in Web Searches About the Causes and Treatments of Autism Over the Past 15 Years: Exploratory Infodemiology Study.

BackgroundNinety percent of adults in the United States use the internet, and the majority of internet users report looking on the web for health information using search engines. The rising prevalence of autism spectrum disorder (ASD), uncertainty surrounding its etiology, and variety of intervention approaches contribute to questions about its causes and treatments. It is not known which terms people search most frequently about ASD and whether web search queries have changed over time. Infodemiology is an area of health informatics research using big data analytics to understand web search behavior.ObjectiveThe objectives were to (1) use infodemiological data to analyze trends in web-based searches about the causes and treatments of ASD over time and (2) inform clinicians and ASD organizations about web queries regarding ASD.MethodsGoogle Trends was used to analyze web searches about the causes and treatments of ASD in the United States from 2004 to 2019. The search terms analyzed for queries about causes of ASD included vaccines, genetics, environmental factors, and microbiome and those for therapies included applied behavior analysis (ABA), gluten-free diet, chelation therapy, marijuana, probiotics, and stem cell therapy.ResultsGoogle Trends results are normalized on a scale ranging from 0 to 100 to represent the frequency and relative interest of search topics. For searches about ASD causes, vaccines had the greatest frequency compared to other terms, with an initial search peak observed in 2008 (scaled score of 81), reaching the highest frequency in 2015 (scaled score of 100), and a current upward trend. In comparison, searches about genetics, environmental factors, and microbiome occurred less frequently. For web searches about ASD therapies, ABA consistently had a high frequency of search interest since 2004, reaching a maximum scaled score of 100 in 2019. The analyses of chelation therapy and gluten-free diet showed trending interest in 2005 (scaled score of 68) and 2007 (scaled score of 100), respectively, followed by a steady decline since (scaled scores of only 10 and 16, respectively, in 2019). Searches related to ASD and marijuana showed a rise in 2009 (scaled score of 35), and they continue to trend upward. Searches about probiotics and stem cell therapy have been relatively low (scaled scores of 22 and 18, respectively), but are gradually gaining interest. Web search volumes for stem cell therapy in 2019 surpassed both gluten-free diet and chelation therapy as web-searched interventions for ASD.ConclusionsGoogle Trends is an effective infodemiology tool to analyze large-scale web search trends about ASD. The results showed informative variation in search trends over 15 years. These data are useful to inform clinicians and organizations about web queries on topics related to ASD, identify knowledge gaps, and target web-based education and knowledge translation strategies.

Videoconferencing and Virtual Worlds in Tourism Language Education – Practical Evaluation of the Systematic Approach in the Czech Context

Abstract Language learning in tourism is increasingly embracing digital technologies for both synchronous and asynchronous content delivery and interaction. Blended learning combining online and traditional face-to-face forms as well as immersive forms such as 3D virtual worlds, where participants may travel as they learn from the comfort of their sofa, offer promising benefits, namely in times of pandemic and other turbulent events. Involving culturally and geographically distant tutors in the learning process may increase learners’ motivation as well as satisfaction, provided that the course curricula and lesson plans utilize the potential by appropriate selection of activities. Despite all the potential benefits, however, troubles caused by the increased complexity of digitally enhanced courses may ruin learners’ experience. The paper provides a conceptual basis for a systemic approach in planning, creating, and delivering courses, considering both technical and psychological aspects, which may assist in the prevention or mitigation of the challenges. To provide a relevant context, presentations of several language schools are briefly examined. The study of changes in their presentations between 2014 and 2021, in the light of web search trends, provides an additional glimpse into the evolution of the adoption and perception of relevant forms of education and technologies, further supporting the necessity of a systematic approach. Experience from three separate projects implementing innovative language courses collected both qualitatively and quantitatively via questionnaires is summarized, pointing out both successes and challenges.

Web Search Trends of Implementing the Patient Autonomy Act in Taiwan.

Background: The Patient Autonomy Act was implemented in Taiwan on 6 January 2019. It is the first patient-oriented act in Taiwan, and also the first special act to completely protect patient autonomy in Asia. Our study aimed to investigate the web resources citizens were able to access on the eve of the implementation of the Patient Autonomy Act in Taiwan. Methods: Patient Autonomy Act-related web resources were searched for by entering 10 related terms individually into the Google search engine in January 2019 and again in April 2019. Search activity data were analyzed using Google Trends. Results: “Advance care planning” and “advance decision” were the most relevant keywords for finding information about the Patient Autonomy Act on the eve of the act’s implementation in Taiwan. The main online information sources were non-governmental websites including news sites and online magazines. The related search volume only increased on the eve of implementation. Conclusions: Even though the Patient Autonomy Act was first published three years before its implementation, the related search volume only increased on the eve of its implementation. Therefore, whether the three-year buffer between its publication and implementation was necessary requires further investigation.

Global Interest for Health Professions Education: A Geographic and Temporal Analyses Through Web Search Differences from 2010-2019

Purpose: The purpose of this study was to analyze the spatio-temporal differences in web search trends for dental degrees (DD), medical degrees (MD), and nursing degrees (ND) across 197 countries from 2010 to 2019. Method: A search string was used to initiate a search query using Google Trends. The parameters used were DD, MD, and ND as search terms; worldwide as Location; 2010 to 2019 as time range; health education &amp; medical training as category; and web search as database. Data were downloaded and analyzed. Results: Via one-way ANOVA and post hoc Dunnett test, the searches for DD were found to be significantly lower in 2011 (3.2 ± 0.3, p = .044), 2012 (2.6 ± 0.2, p &lt; .001), 2013 (2.8 ± 0.3, p = .006), 2014 (3.0 ± 0.3, p = .017), and 2015 (2.9 ± 0.3, p = .010) compared to the year 2010 (4.5 ± 0.6); the searches for MD was significantly higher in 2019 (84.5 ± 2.5, p = .002) compared to the year 2010 (73.0 ± 1.7); and the searches for ND were statistically significantly higher in 2015 (28.9 ± 1.1, p = .024) and 2019 (31.7 ± 1.1, p = .001) compared to the year 2010 (24.5.0 ± 1.2). The search trend for MD increased in 31 countries and decreased in 14 countries while searches for ND increased in 40 countries and decreased in 5 countries as determined by a two-way ANOVA with Holm-Sidak’s multiple comparison test. The 12-month forecast for the search interests of these health professions predicted a rise in the third quarter and an abrupt decline at the end of the year. Conclusions: Geographic and time factors affect the search interests for health professions. In a span of a decade, the disparity of interests shown by the low interests for DD and ND compared to MD in some countries underscores the need to promote these professions to fill the future health care workforce.

Public interest through web search trends of neuromodulation treatments in the United States

Maternal antenatal depression may alter offspring neurodevelopment, but long follow-up studies are lacking. We studied the risks for mood disorders and schizophrenia in adult offspring of antenatally depressed mothers, taking account parental severe mental disorders.In the general population-based Northern Finland 1966 Birth Cohort with 12,058 children, 13.9% of the mothers reported themselves depressed at mid-gestation. The offspring were followed 43 years. Severe mood disorders and schizophrenia in the offspring and severe mental disorders in the parents were detected using the Care Register for Healthcare. Maternal smoking during pregnancy, perinatal complications, fathers´ social class, family type at birth, and grand multiparity were considered as confounding variables.The offspring of antenatally depressed mothers had an elevated risk for depression (adjusted OR 1.5; 95% CI 1.03–2.2), compared to cohort members without maternal antenatal depressed mood. The offspring with maternal antenatal depressed mood and parental severe mental disorder had markedly elevated risks for depression (3.3; 1.8–6.2), and schizophrenia (3.9; 2.0–7.5), compared to the offspring without one or both of these risk factors.Maternal antenatal depressed mood was determined by one question and did not necessarily signify a clinical condition. Data on maternal postnatal mood was not available.The offspring with maternal antenatal depressed mood and parental severe mental disorder had high risk for depression and schizophrenia. Early interventions in parental severe mental disorder might present an opportunity for decreasing the risk for mood disorders and schizophrenia in the offspring.

S108. Public Interest Through Web Search Trends of Neuromodulation Treatments in the United States From 2013 to 2018

Public interest in FDA-approved neuromodulation treatments has not been explored in the literature. Our aim is to compare web search trends, an indicator of public interest, of neuromodulation treatments.

Public interest through web search trends of neuromodulation treatments in the United States

Public interest through web search trends of neuromodulation treatments in the United States

Comparative analysis of web search trends between experts and public for medicinal herbs in Korea

Ethnopharmacological relevanceThe information and knowledge about ethno-medicinal herbs are getting stronger interest in Global and Korea after the agreement of the Nagoya Protocol. However, it is known that there is a serious asymmetry of ethno-medicinal information between experts and public, thus this study aimed to analyze the similarities and differences in interest between experts and public for medicinal herbs in Korea through big data analysis. Materials and methodsThe medicinal herbs selected in this study were the top 10 herbs in terms of the amounts purchased by TKM centers. And two representative web search engines were selected to collect the web search logs, i.e. big data, of experts and public for medicinal herbs in Korea. Comparative analysis was accomplished through descriptive statistical analysis, Pearson's correlation coefficient, and time-series graph analysis. ResultsThe web search traffic logs were collected for the past three years (2012–2014) from OASIS and NAVER, which are the representative web search engines of experts and public respectively in Korea. First, regarding OASIS, the most searched medicinal herb was Angelicae Gigantis Radix while the least searched was Alismatis Rhizoma; for NAVER, the most searched medicinal herb was Paeoniae Radix, unlike OASIS, and the least searched was Alismatis Rhizoma, as with OASIS. The coefficient between rank of herbs and OASIS was –0.401, and that between rank of herbs and NAVER was –0.387, and the correlational coefficient for web search trends of OASIS and NAVER during the past three years was 0.438. Also the correlation of interest between experts and public for each herb on monthly web trends basis was similar with regard to Glycyrrhizae Radix et Rhizoma and Angelicae Gigantis Radix, but different with regard to the other 8 medicinal herbs. Finally, significant outcomes or suggestions were figured out through time-series graph analysis. ConclusionThis study presents meaningful results concerning the similarities and differences in interest between experts and public for popular medicinal herbs in Korea. Contrary to the common assumption that there exists big different interest between experts and public, this study revealed that there is apparent similar interest between experts and public on popular medicinal herbs in Korea.

Web-search trends shed light on the nature of lunacy: Relationship between moon phases and epilepsy information-seeking behavior

In old and modern times and across cultures, recurrent seizures have been attributed to the lunar phase. It is unclear whether this relationship should be classified as a myth or whether a true connection exists between moon phases and seizures. We analyzed the worldwide aggregated search queries related to epilepsy health-seeking behavior between 2005 and 2012. Epilepsy-related Internet searches increased in periods with a high moon illumination. The overall association was weak (r=0.11, 95% confidence interval: 0.07 to 0.14) but seems to be higher than most control search queries not related to epilepsy. Increased sleep deprivation during periods of full moon might explain this positive association and warrants further study into epilepsy-related health-seeking behavior on the Internet, the lunar phase, and its contribution to nocturnal luminance.