Surveillance of Australian suicidal behaviour using the internet?

The association of internet searches and actual suicide in Spain

High suicide rates are a major issue in Spain, to the extent that they are the main non-natural cause of death in this country. The present study analyses the relationship between Internet searches and actual suicide rates in Spain. For this purpose, we employ data from actual suicide rates and Google® searches for Spain, differencing by the means used to commit suicide. Our results show that suicide ("suicidio") search term seems to be positively associated with higher total suicide rates, in addition to suicides using poison, suffocation and jumping. The suicide ("suicidio") topic presents similar results to the suicide search term, and suicide by car crash also seems to be associated with Internet searches of this topic.

Hindcasts and forecasts of suicide mortality in US: A modeling study

Deaths by suicide, as well as suicidal ideations, plans and attempts, have been increasing in the US for the past two decades. Deployment of effective interventions would require timely, geographically well-resolved estimates of suicide activity. In this study, we evaluated the feasibility of a two-step process for predicting suicide mortality: a) generation of hindcasts, mortality estimates for past months for which observational data would not have been available if forecasts were generated in real-time; and b) generation of forecasts with observational data augmented with hindcasts. Calls to crisis hotline services and online queries to the Google search engine for suicide-related terms were used as proxy data sources to generate hindcasts. The primary hindcast model (auto) is an Autoregressive Integrated Moving average model (ARIMA), trained on suicide mortality rates alone. Three regression models augment hindcast estimates from auto with call rates (calls), GHT search rates (ght) and both datasets together (calls_ght). The 4 forecast models used are ARIMA models trained with corresponding hindcast estimates. All models were evaluated against a baseline random walk with drift model. Rolling monthly 6-month ahead forecasts for all 50 states between 2012 and 2020 were generated. Quantile score (QS) was used to assess the quality of the forecast distributions. Median QS for auto was better than baseline (0.114 vs. 0.21. Median QS of augmented models were lower than auto, but not significantly different from each other (Wilcoxon signed-rank test, p > .05). Forecasts from augmented models were also better calibrated. Together, these results provide evidence that proxy data can address delays in release of suicide mortality data and improve forecast quality. An operational forecast system of state-level suicide risk may be feasible with sustained engagement between modelers and public health departments to appraise data sources and methods as well as to continuously evaluate forecast accuracy.

Predicting the Number of Suicides in Japan Using Internet Search Queries: Vector Autoregression Time Series Model

BACKGROUND

The number of suicides in Japan increased during the COVID-19 pandemic. Predicting the number of suicides is important to take timely preventive measures.

OBJECTIVE

This study aims to clarify whether the number of suicides can be predicted by suicide-related search queries used before searching for the keyword "suicide."

METHODS

This study uses the infoveillance approach for suicide in Japan by search trends in search engines. The monthly number of suicides by gender, collected and published by the National Police Agency, was used as an outcome variable. The number of searches by gender with queries associated with "suicide" on "Yahoo! JAPAN Search" from January 2016 to December 2020 was used as a predictive variable. The following five phrases highly relevant to suicide were used as search terms before searching for the keyword "suicide" and extracted and used for analyses: "abuse"; "work, don't want to go"; "company, want to quit"; "divorce"; and "no money." The augmented Dickey-Fuller and Johansen tests were performed for the original series and to verify the existence of unit roots and cointegration for each variable, respectively. The vector autoregression model was applied to predict the number of suicides. The Breusch-Godfrey Lagrangian multiplier (BG-LM) test, autoregressive conditional heteroskedasticity Lagrangian multiplier (ARCH-LM) test, and Jarque-Bera (JB) test were used to confirm model convergence. In addition, a Granger causality test was performed for each predictive variable.

RESULTS

In the original series, unit roots were found in the trend model, whereas in the first-order difference series, both men (minimum tau 3: -9.24; max tau 3: -5.38) and women (minimum tau 3: -9.24; max tau 3: -5.38) had no unit roots for all variables. In the Johansen test, a cointegration relationship was observed among several variables. The queries used in the converged models were "divorce" for men (BG-LM test: P=.55; ARCH-LM test: P=.63; JB test: P=.66) and "no money" for women (BG-LM test: P=.17; ARCH-LM test: P=.15; JB test: P=.10). In the Granger causality test for each variable, "divorce" was significant for both men (F₁₀₄=3.29; P=.04) and women (F₁₀₄=3.23; P=.04).

CONCLUSIONS

The number of suicides can be predicted by search queries related to the keyword "suicide." Previous studies have reported that financial poverty and divorce are associated with suicide. The results of this study, in which search queries on "no money" and "divorce" predicted suicide, support the findings of previous studies. Further research on the economic poverty of women and those with complex problems is necessary.

Is Google Trends a useful tool for tracking mental and social distress during a public health emergency? A time-series analysis

BACKGROUND

Google Trends data are increasingly used by researchers as an indicator of population mental health, but few studies have investigated the validity of this approach during a public health emergency.

METHODS

Relative search volumes (RSV) for the topics depression, anxiety, self-harm, suicide, suicidal ideation, loneliness, and abuse were obtained from Google Trends. We used graphical and time-series approaches to compare daily trends in searches for these topics against population measures of these outcomes recorded using validated self-report scales (PHQ-9; GAD-7; UCLA-3) in a weekly survey (n = ~70,000) of the impact COVID-19 on psychological and social experiences in the UK population (21/03/2020 to 21/08/ 2020).

RESULTS

Self-reported levels of depression, anxiety, self-harm/suicidal ideation, self-harm, loneliness and abuse decreased during the period studied. There was no evidence of an association between self-reported anxiety, self-harm, abuse and RSV on Google Trends. Trends in Google topic RSV for depression and suicidal ideation were inversely associated with self-reports of these outcomes (p = 0.03 and p = 0.04, respectively). However, there was statistical and graphical evidence that self-report and Google searches for loneliness (p < 0.001) tracked one another.

LIMITATIONS

No age/sex breakdown of Google Trends data available. Survey respondents were not representative of the UK population and no pre-pandemic data were available.

CONCLUSION

Google Trends data do not appear to be a useful indicator of changing levels of population mental health during a public health emergency, but may have some value as an indicator of loneliness.

The association between internet searches and suicide in Spain

Apart from disease, suicide has been the first cause of death in Spain since it overcame the victims of traffic accidents in the year 2007. Nevertheless, in spite of the high number of people affected by it every year, it is an almost silenced issue in this country. In the present research work we make use of Internet suicide-related search terms and official suicide rates for Spain to analyze whether these searches are related to actual suicides between 2004 and 2017. We find that the search terms "commit suicide", "commit suicide without pain" and "suicide" (as search term and as topic) are positively related to actual suicide rates. Thus, the Internet seems to be a consult tool for potential suicide victims in Spain which, joined to an increasing trend in the use of the Internet by the Spanish population, opens the gate for interventions through the results obtained in these Internet searches.

Mapping population mental health concerns related to COVID-19 and the consequences of physical distancing: a Google trends analysis

Background: The 2020 Coronavirus pandemic is a major international public health challenge.  Governments have taken public health protection measures to reduce the spread of the virus through non-pharmalogical measures. The impact of the pandemic and the public health response on individual and population mental health is unknown.  Methods: We used Google Trends data (1 Jan 2020 -  30 Mar 2020) to investigate the impact of the pandemic and government measures to curb it on people's concerns, as indexed by changes in search frequency for topics indicating mental distress, social and economic stressors and mental health treatment-seeking. We explored the changes of key topics in Google trends in Italy, Spain, USA, UK, and Worldwide in relation to sentinel events during the pandemic. Results: Globally there appears to be significant concerns over the financial and work-related consequences of the pandemic, with some evidence that levels of fear are rising. Conversely relative searching for topics related to depression and suicide fell after the pandemic was announced, with some evidence that searches for the latter have risen recently. Concerns over education and access to medication appear to be particular social stressors. Whilst searches for face-to-face treatments have declined, those for self-care have risen. Conclusions: Monitoring Google trends shows promise as a means of tracking changing public concerns. In weeks to come it may enable policy makers to assess the impact of their interventions including those aiming to limit negative consequences, such as government funded financial safety nets.

Mapping population mental health concerns related to COVID-19 and the consequences of physical distancing: a Google trends analysis

Background: The 2020 Coronavirus pandemic is a major international public health challenge.  Governments have taken public health protection measures to reduce the spread of the virus through non-pharmalogical measures. The impact of the pandemic and the public health response on individual and population mental health is unknown.  Methods: We used Google Trends data (1 Jan 2020 - 1 Apr 2020) to investigate the impact of the pandemic and government measures to curb it on people's concerns, as indexed by changes in search frequency for topics indicating mental distress, social and economic stressors and mental health treatment-seeking. We explored the changes of key topics in Google trends in Italy, Spain, USA, UK, and Worldwide in relation to sentinel events during the pandemic. Results: Globally there appears to be significant concerns over the financial and work-related consequences of the pandemic, with some evidence that levels of fear are rising. Conversely searching for topics related to depression and suicide fell after the pandemic was announced, with some evidence that searches for the latter have risen recently. Concerns over education and access to medication appear to be particular social stressors. Whilst searches for face-to-face treatments have declined, those for self-care have risen. Conclusions: Monitoring Google trends shows promise as a means of tracking changing public concerns. In weeks to come it may enable policy makers to assess the impact of their interventions including those aiming to limit negative consequences, such as government funded financial safety nets.

Google Searches and Suicide Rates in Spain, 2004-2013: Correlation Study

Background

Different studies have suggested that web search data are useful in forecasting several phenomena from the field of economics to epidemiology or health issues.

Objective

This study aimed to (1) evaluate the correlation between suicide rates released by the Spanish National Statistics Institute (INE) and internet search trends in Spain reported by Google Trends (GT) for 57 suicide-related terms representing major known risks of suicide and an analysis of these results using a linear regression model and (2) study the differential association between male and female suicide rates published by the INE and internet searches of these 57 terms.

Methods

The study period was from 2004 to 2013. In this study, suicide data were collected from (1) Spain’s INE and (2) local internet search data from GT, both from January 2004 to December 2013. We investigated and validated 57 suicide-related terms already tested in scientific studies before 2015 that would be the best predictors of new suicide cases. We then evaluated the nowcasting effects of a GT search through a cross-correlation analysis and by linear regression of the suicide incidence data with the GT data.

Results

Suicide rates in Spain in the study period were positively associated (r<-0.2) for the general population with the search volume for 7 terms and negatively for 1 from the 57 terms used in previous studies. Suicide rates for men were found to be significantly different than those of women. The search term, “allergy,” demonstrated a lead effect for new suicide cases (r=0.513; P=.001). The next significant correlating terms for those 57 studied were “antidepressant,” “alcohol abstinence,” “relationship breakup” (r=0.295, P=.001; r=0.295, P=.001; and r=0.268, P=.002, respectively). Significantly different results were obtained for men and women. Search terms that correlate with suicide rates of women are consistent with previous studies, showing that the incidence of depression is higher in women than in men, and showing different gender searching patterns.

Conclusions

A better understanding of internet search behavior of both men and women in relation to suicide and related topics may help design effective suicide prevention programs based on information provided by search robots and other big data sources.

Search trends preceding increases in suicide: A cross-correlation study of monthly Google search volume and suicide rate using transfer function models

BACKGROUND

Various associations between monthly Google search volumes (MGSVs) and monthly suicide rates (MSRs) have been reported. However, these studies often analyzed a limited number of search terms using suboptimal statistical methods. While controlling for spurious associations, this study examined a wide array of suicide-related search terms to elucidate if their MGSVs correlated with future MSRs.

METHODS

MGSVs of 111 candidate suicide-related terms were calculated by averaging 10 time-series data per term obtained from Google Trends. Box-Jenkins transfer function modeling was applied to time-series data of MGSV and MSR among the total, male, and female populations of the United States between 2004 and 2017. Cross-correlation coefficients between MGSVs and MSRs were calculated at lags -3, -2, and -1. Sensitivity analysis identified cross-correlations whose direction and significance (p<0.05) persisted in two other time spans: 126 and 84 months.

RESULTS

Eighty-nine terms were analyzed. MGSVs of 31 terms significantly correlated with MSRs in the total, male, or female population. In the sensitivity analysis, three terms stably exhibited significant positive correlation: "generalized anxiety disorder" (total; lag -3), "anxiety disorder" (total and male; lag -3), and "laid off" (total, male, and female; lag -2). The term sleep problem (total and female; lag -1) consistently showed significant negative correlations.

LIMITATIONS

Sex- or age-specific search-volume data, lags of less than a month, and potential confounding factors of MGSV and MSR were not explored.

CONCLUSIONS

trends in MGSV of four terms tend to precede changes in MSR. These terms may enable more accurate forecasting of future suicides.

The Impact of Widely Publicized Suicides on Search Trends: Using Google Trends to Test the Werther and Papageno Effects

The objective of this study was to examine the impact of widely publicized suicides on the Werther and Papageno Effects using internet search trends. A list of widely publicized suicides from 2010 through 2018 was compiled along with dates of death for each of these individuals. Google.com/trends data were then collected for searches for "how to suicide" and "suicide prevention" for 14 days prior to a widely publicized suicide/14 days after a widely publicized suicide and 7 days prior to a widely publicized suicide/7 days after a widely publicized suicide. Comparisons were then made between these time periods for "how to suicide" and "suicide prevention." Some celebrities, such as Robin Williams (2014) and Aaron Hernandez (2017) were associated with increased searches. However, for many there was no increase in search trends. Limited support was found for the impact of widely publicized suicides on internet search trends with one case supporting a Werther Effect and one case supporting a Papageno Effect. The finding that only some celebrities were associated with increased searches may be a byproduct of the impact of celebrity status on these effects, with more prominent celebrities having the greatest impact.

Developing an early warning system of suicide using Google Trends and media reporting

BACKGROUND

Conventional surveillance systems for suicides typically suffer from a substantial time lag of six months to two years. This study aims to develop an early warning system of possible suicide outbreaks in Hong Kong using Google Trends and suicide-related media reporting.

METHODS

Data on 3,534 suicides from 2011 to 2015 were obtained from Hong Kong Census and Statistics Department, and the Coroner's Court. Using data from Google Trends and features extracted from media reporting on suicide news, we fitted Poisson regression models to predict the number and estimate the intensity of suicides on a weekly basis, for six subgroups, defined by gender and age. We adopted the cumulative sum (CUSUM) control chart-based method to identify outbreaks of suicide.

RESULTS

The proposed model was able to predict the number of suicides with reasonably low normalized root mean squared errors, ranging from 15.6% for young females to 24.16% for old females. The suicide intensity curves were well captured by the proposed models for young males and females, but not for other groups. The Sensitivity, Precision and F1 Score of the CUSUM-based method were 50%, 100% and 67% for young females, and 93%, 54% and 68% for young males.

LIMITATIONS

This study focused only on predicting the number of suicides in the current week, not in the future weeks. The model did not include social media, socioeconomic and climate data.

CONCLUSIONS

Our results indicate that Google Trends search terms and media reporting data may be valuable data sources for predicting possible outbreak of suicides in Hong Kong. The proposed system could support effective and targeted interventions.

The potential use of social media and other internet-related data and communications for child maltreatment surveillance and epidemiological research: Scoping review and recommendations

Collecting child maltreatment data is a complicated undertaking for many reasons. As a result, there is an interest by child maltreatment researchers to develop methodologies that allow for the triangulation of data sources. To better understand how social media and internet-based technologies could contribute to these approaches, we conducted a scoping review to provide an overview of social media and internet-based methodologies for health research, to report results of evaluation and validation research on these methods, and to highlight studies with potential relevance to child maltreatment research and surveillance. Many approaches were identified in the broad health literature; however, there has been limited application of these approaches to child maltreatment. The most common use was recruiting participants or engaging existing participants using online methods. From the broad health literature, social media and internet-based approaches to surveillance and epidemiologic research appear promising. Many of the approaches are relatively low cost and easy to implement without extensive infrastructure, but there are also a range of limitations for each method. Several methods have a mixed record of validation and sources of error in estimation are not yet understood or predictable. In addition to the problems relevant to other health outcomes, child maltreatment researchers face additional challenges, including the complex ethical issues associated with both internet-based and child maltreatment research. If these issues are adequately addressed, social media and internet-based technologies may be a promising approach to reducing some of the limitations in existing child maltreatment data.

Google and suicides: what can we learn about the use of internet to prevent suicides?

OBJECTIVES

This article studies the statistical relationship between the search propensity of suicide-related terms on Google and the number of suicides.

STUDY DESIGN

Suicide mortality data from all American states from January 2006 to November 2014 (n = 5372) and data on Google search intensity for the same period was collected.

METHODS

Regression analysis with dynamic components was performed to determine the relationship between search intensity and the number of suicides.

RESULTS

First, this article finds a positive simultaneous correlation between search intensity and the number of suicides. The magnitude of this relationship has grown from 2006 to 2014 suggesting an increased reliance on the internet for suicide-related information. Second, search propensity is a significant predictor for the number of suicides for youth and for males.

CONCLUSIONS

Suicide prevention websites should therefore be designed knowing that at-risk individuals in both groups are probably more prone to look for suicide-related information online.

Low validity of Google Trends for behavioral forecasting of national suicide rates

Recent research suggests that search volumes of the most popular search engine worldwide, Google, provided via Google Trends, could be associated with national suicide rates in the USA, UK, and some Asian countries. However, search volumes have mostly been studied in an ad hoc fashion, without controls for spurious associations. This study evaluated the validity and utility of Google Trends search volumes for behavioral forecasting of suicide rates in the USA, Germany, Austria, and Switzerland. Suicide-related search terms were systematically collected and respective Google Trends search volumes evaluated for availability. Time spans covered 2004 to 2010 (USA, Switzerland) and 2004 to 2012 (Germany, Austria). Temporal associations of search volumes and suicide rates were investigated with time-series analyses that rigorously controlled for spurious associations. The number and reliability of analyzable search volume data increased with country size. Search volumes showed various temporal associations with suicide rates. However, associations differed both across and within countries and mostly followed no discernable patterns. The total number of significant associations roughly matched the number of expected Type I errors. These results suggest that the validity of Google Trends search volumes for behavioral forecasting of national suicide rates is low. The utility and validity of search volumes for the forecasting of suicide rates depend on two key assumptions ("the population that conducts searches consists mostly of individuals with suicidal ideation", "suicide-related search behavior is strongly linked with suicidal behavior"). We discuss strands of evidence that these two assumptions are likely not met. Implications for future research with Google Trends in the context of suicide research are also discussed.

Tracking and predicting hand, foot, and mouth disease (HFMD) epidemics in China by Baidu queries

Hand, foot, and mouth disease (HFMD) is highly prevalent in China, and more efficient methods of epidemic detection and early warning need to be developed to augment traditional surveillance systems. In this paper, a method that uses Baidu search queries to track and predict HFMD epidemics is presented, and the outbreaks of HFMD in China during the 60-month period from January 2011 to December 2015 are predicted. The Pearson correlation coefficient (R) of the predictive model and the mean absolute percentage errors between observed HFMD case counts and the predicted number show that our predictive model gives excellent fit to the data. This implies that Baidu search queries can be used in China to track and reliably predict HFMD epidemics, and can serve as a supplement to official systems for HFMD epidemic surveillance.

A Google-based approach for monitoring suicide risk

People seeking information and news regarding suicide are likely to use the Internet. However, evidence of the relationship between suicide-related search volumes and national suicide-rates in different countries can be strikingly different. We aimed to investigate the relationship between suicide-rates and Google suicide-related search volumes in the Italian population (2008-2012) using the Italian mortality database that provided monthly national data concerning suicides (2008-2012). Moreover, this study aimed to identify future trends of national suicide rates on the basis of the results we obtained concerning the period 2013-14. Google Trends provided data of online monthly search-volumes of the term "suicide", "commit suicide" and "how to commit suicide" in Google Search and Google News (2008-2014). Google Search volumes for the term "suicide" lags suicide by three months (ρ=0.482, p-value<0.001), whereas no correlation was found between search volumes for "commit suicide" and "how to commit suicide" and national suicide rates. Google News search volumes for the three terms resulted in white noise. Apparently, online searches for suicide-related terms in Italy are more likely to be linked to factors other than suicidiality such as personal interest and suicide bereavement.

Heat stroke internet searches can be a new heatwave health warning surveillance indicator

The impact of major heatwave shocks on population morbidity and mortality has become an urgent public health concern. However, Current heatwave warning systems suffer from a lack of validation and an inability to provide accurate health risk warnings in a timely way. Here we conducted a correlation and linear regression analysis to test the relationship between heat stroke internet searches and heat stroke health outcomes in Shanghai, China, during the summer of 2013. We show that the resulting heatstroke index captures much of the variation in heat stroke cases and deaths. The correlation between heat stroke deaths, the search index and the incidence of heat stroke is higher than the correlation with maximum temperature. This study highlights a fast and effective heatwave health warning indicator with potential to be used throughout the world.

Estimating suicide occurrence statistics using Google Trends

Data on the number of people who have committed suicide tends to be reported with a substantial time lag of around two years. We examine whether online activity measured by Google searches can help us improve estimates of the number of suicide occurrences in England before official figures are released. Specifically, we analyse how data on the number of Google searches for the terms 'depression' and 'suicide' relate to the number of suicides between 2004 and 2013. We find that estimates drawing on Google data are significantly better than estimates using previous suicide data alone. We show that a greater number of searches for the term 'depression' is related to fewer suicides, whereas a greater number of searches for the term 'suicide' is related to more suicides. Data on suicide related search behaviour can be used to improve current estimates of the number of suicide occurrences.

ELECTRONIC SUPPLEMENTARY MATERIAL

The online version of this article (doi:10.1140/epjds/s13688-016-0094-0) contains supplementary material.

Examining the Relationship Between Past Orientation and US Suicide Rates: An Analysis Using Big Data-Driven Google Search Queries

Background

Internet search query data reflect the attitudes of the users, using which we can measure the past orientation to commit suicide. Examinations of past orientation often highlight certain predispositions of attitude, many of which can be suicide risk factors.

Objective

To investigate the relationship between past orientation and suicide rate by examining Google search queries.

Methods

We measured the past orientation using Google search query data by comparing the search volumes of the past year and those of the future year, across the 50 US states and the District of Columbia during the period from 2004 to 2012. We constructed a panel dataset with independent variables as control variables; we then undertook an analysis using multiple ordinary least squares regression and methods that leverage the Akaike information criterion and the Bayesian information criterion.

Results

It was found that past orientation had a positive relationship with the suicide rate (P≤.001) and that it improves the goodness-of-fit of the model regarding the suicide rate. Unemployment rate (P≤.001 in Models 3 and 4), Gini coefficient (P≤.001), and population growth rate (P≤.001) had a positive relationship with the suicide rate, whereas the gross state product (P≤.001) showed a negative relationship with the suicide rate.

Conclusions

We empirically identified the positive relationship between the suicide rate and past orientation, which was measured by big data-driven Google search query.

Searching for Suicide Methods

Abstract. Background: Helium gas suicides have increased in England and Wales; easy-to-access descriptions of this method on the Internet may have contributed to this rise. Aims: To investigate the availability of information on using helium as a method of suicide and trends in searching about this method on the Internet. Method: We analyzed trends in (a) Google searching (2004–2014) and (b) hits on a Wikipedia article describing helium as a method of suicide (2013–2014). We also investigated the extent to which helium was described as a method of suicide on web pages and discussion forums identified via Google. Results: We found no evidence of rises in Internet searching about suicide using helium. News stories about helium suicides were associated with increased search activity. The Wikipedia article may have been temporarily altered to increase awareness of suicide using helium around the time of a celebrity suicide. Approximately one third of the links retrieved using Google searches for suicide methods mentioned helium. Conclusion: Information about helium as a suicide method is readily available on the Internet; the Wikipedia article describing its use was highly accessed following celebrity suicides. Availability of online information about this method may contribute to rises in helium suicides.

The association of trends in charcoal-burning suicide with Google search and newspaper reporting in Taiwan: a time series analysis

PURPOSE

Some East/Southeast Asian countries have experienced a rapid increase in suicide by charcoal burning over the past decade. Media reporting and Internet use were thought to contribute to the epidemic. We investigated the association between method-specific suicide incidence and both Internet search volume and newspaper reporting in Taiwan.

METHOD

Weekly data for suicide, suicide-related Google search volume, and the number of articles reporting suicide in four major newspapers in Taiwan during 2008-2011 were obtained. Poisson autoregressive regression models were used to examine the associations between these variables.

RESULTS

In the fully adjusted models, every 10 % increase in Google searches was associated with a 4.3 % [95 % confidence interval (CI) 1.1-7.6 %] increase in charcoal-burning suicide incidence in the same week, and a 3.8 % (95 % CI 0.4-7.2 %) increase in the following week. A one-article increase in the United Daily was associated with a 3.6 % (95 % CI 1.5-5.8 %) increase in charcoal-burning suicide in the same week. By contrast, non-charcoal-burning suicide was not associated with Google search volume, but was associated with the Apple Daily's reporting in the preceding week.

CONCLUSIONS

We found that increased Internet searches for charcoal-burning suicide appeared to be associated with a subsequent increase in suicide by this method. The prevention of suicide using emerging methods may include monitoring and regulating online information that provides details of these methods as well as encouraging Internet service providers to provide help-seeking information.

Suicide-related Internet use: A review

OBJECTIVE

To systematically review research on how people use the Internet for suicide-related reasons and its influence on users. This review summarises the main findings and conclusions of existing work, the nature of studies that have been conducted, their strengths and limitations, and directions for future research.

METHOD

An online search was conducted through PsycINFO, PubMed, Ovid MEDLINE and CINAHL databases for papers published between 1991 and 2014. Papers were included if they examined how the Internet was used for suicide-related reasons, the influence of suicide-related Internet use, and if they presented primary data, including case studies of Internet-related suicide attempts and completions.

RESULTS

Findings of significant relationships between suicide-related search trends and rates of suicide suggest that search trends may be useful in monitoring suicide risk in a population. Studies that examine online communications between people who are suicidal can further our understanding of individuals' suicidal experiences. While engaging in suicide-related Internet use was associated with higher levels of suicidal ideation, evidence of its influence on suicidal ideation over time was mixed. There is a lack of studies directly recruiting suicidal Internet users. Only case studies examined the influence of suicide-related Internet use on suicidal behaviours, while no studies assessed the influence of pro-suicide or suicide prevention websites. Online professional services can be useful to suicide prevention and intervention efforts, but require more work in order to demonstrate their efficacy.

CONCLUSIONS

Research has shown that individuals use the Internet to search for suicide-related information and to discuss suicide-related problems with one another. However, the causal link between suicide-related Internet use and suicidal thoughts and behaviours is still unclear. More research is needed, particularly involving direct contact with Internet users, in order to understand the impact of both informal and professionally moderated suicide-related Internet use.

The use of google trends in health care research: a systematic review

BACKGROUND

Google Trends is a novel, freely accessible tool that allows users to interact with Internet search data, which may provide deep insights into population behavior and health-related phenomena. However, there is limited knowledge about its potential uses and limitations. We therefore systematically reviewed health care literature using Google Trends to classify articles by topic and study aim; evaluate the methodology and validation of the tool; and address limitations for its use in research.

METHODS AND FINDINGS

PRISMA guidelines were followed. Two independent reviewers systematically identified studies utilizing Google Trends for health care research from MEDLINE and PubMed. Seventy studies met our inclusion criteria. Google Trends publications increased seven-fold from 2009 to 2013. Studies were classified into four topic domains: infectious disease (27% of articles), mental health and substance use (24%), other non-communicable diseases (16%), and general population behavior (33%). By use, 27% of articles utilized Google Trends for casual inference, 39% for description, and 34% for surveillance. Among surveillance studies, 92% were validated against a reference standard data source, and 80% of studies using correlation had a correlation statistic ≥0.70. Overall, 67% of articles provided a rationale for their search input. However, only 7% of articles were reproducible based on complete documentation of search strategy. We present a checklist to facilitate appropriate methodological documentation for future studies. A limitation of the study is the challenge of classifying heterogeneous studies utilizing a novel data source.

CONCLUSION

Google Trends is being used to study health phenomena in a variety of topic domains in myriad ways. However, poor documentation of methods precludes the reproducibility of the findings. Such documentation would enable other researchers to determine the consistency of results provided by Google Trends for a well-specified query over time. Furthermore, greater transparency can improve its reliability as a research tool.

A Google Trends-based approach for monitoring NSSI

Non-suicidal self-injury (NSSI) is an intentional, direct, and socially unacceptable behavior resulting in the destruction of one’s own body tissues with no intention of dying or committing suicide, even though it is associated with a higher risk of attempted, planned, or just considered suicide. In this preliminary report, we introduce the concept of “NSSI 2.0”; that is to say, the study of the Internet usage by subjects with NSSI, and we introduce a Google Trends-based approach for monitoring NSSI, called NSSI infodemiology and infoveillance. Despite some limitations, Google Trends has already proven to be reliable for infectious diseases monitoring, and here we extend its application and potentiality in the field of suicidology. Ad hoc web portals and surveys could be designed in light of the reported results for helping people with NSSI.

Accessing suicide-related information on the internet: a retrospective observational study of search behavior

Background

The Internet’s potential impact on suicide is of major public health interest as easy online access to pro-suicide information or specific suicide methods may increase suicide risk among vulnerable Internet users. Little is known, however, about users’ actual searching and browsing behaviors of online suicide-related information.

Objective

To investigate what webpages people actually clicked on after searching with suicide-related queries on a search engine and to examine what queries people used to get access to pro-suicide websites.

Methods

A retrospective observational study was done. We used a web search dataset released by America Online (AOL). The dataset was randomly sampled from all AOL subscribers’ web queries between March and May 2006 and generated by 657,000 service subscribers.

Results

We found 5526 search queries (0.026%, 5526/21,000,000) that included the keyword "suicide". The 5526 search queries included 1586 different search terms and were generated by 1625 unique subscribers (0.25%, 1625/657,000). Of these queries, 61.38% (3392/5526) were followed by users clicking on a search result. Of these 3392 queries, 1344 (39.62%) webpages were clicked on by 930 unique users but only 1314 of those webpages were accessible during the study period. Each clicked-through webpage was classified into 11 categories. The categories of the most visited webpages were: entertainment (30.13%; 396/1314), scientific information (18.31%; 240/1314), and community resources (14.53%; 191/1314). Among the 1314 accessed webpages, we could identify only two pro-suicide websites. We found that the search terms used to access these sites included “commiting suicide with a gas oven”, “hairless goat”, “pictures of murder by strangulation”, and “photo of a severe burn”. A limitation of our study is that the database may be dated and confined to mainly English webpages.

Conclusions

Searching or browsing suicide-related or pro-suicide webpages was uncommon, although a small group of users did access websites that contain detailed suicide method information.