Suicide-related Internet use: A review

Mok, Katherine; Jorm, Anthony F.; Pirkis, Jane

doi:10.1177/0004867415569797

Cited by 61 publications

(62 citation statements)

References 55 publications

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“…Previous research has found that, indeed, online suiciderelated activity may be associated with later suicidal behavior. [25][26][27] For example, Fink et al 28 examined whether suicide deaths in the United States increased in the 4 months after Robin Williams' death while controlling for typical seasonal patterns of suicides. They found that suicide deaths were nearly 10% greater than expected-meaning that in addition to the thousands of people in the United States who die by suicide every month, more than 2,000 additional suicide deaths were observed after Robin Williams' death.…”

Section: Discussionmentioning

confidence: 99%

“…Coupling Fink et al results with the current findings, it is possible that Internet searches for suicide-related terms are related to increases in suicidal behavior. [25][26][27][28] Indeed, search volumes for suicide and depression are not only associated with the incidence of suicidal behavior in England, they also significantly improve the ability to predict the rate of suicide. 16…”

Section: Discussionmentioning

confidence: 99%

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Changes in Internet Suicide Search Volumes Following Celebrity Suicides

Ortiz

Forrest

Fisher

et al. 2019

Cyberpsychology, Behavior, and Social Networking

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Celebrity suicides that are reported heavily in the media may increase risk for others' suicidal behavior. This study examined whether Internet search volumes for suicide-related terms changed after three celebrity suicide deaths (Robin Williams, Chester Bennington, and Alexander McQueen) and three celebrities who died by means other than suicide (David Bowie, Azzedine Alaia, and Paul Walker). Suicide search terms included suicide, how to suicide, commit suicide, depression, hanging, and suicide prevention. Observed suicide search volumes in the United States were collected from Google Trends for the 10 weeks before and the 2 weeks following each celebrity's death. Predicted search volumes for the 14 days postdeath were forecasted from the predeath search volumes and predicted search volumes were then compared to the true, observed search volumes. Search volumes for suicide terms significantly increased following Robin Williams' suicide death. Some of the terms increased in search volume following Chester Bennington's and Alexander McQueen's suicide deaths, but not significantly. Most search volumes for nonsuicide celebrity deaths did not change following their deaths. Celebrity suicide deaths can lead to significant, national increases in Internet search volumes for suicide-related terms for celebrities of high prominence. Results highlight the critical importance of reporting suicide deaths in the media responsibly.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Changes in Internet Suicide Search Volumes Following Celebrity Suicides

Ortiz

Forrest

Fisher

et al. 2019

Cyberpsychology, Behavior, and Social Networking

View full text Add to dashboard Cite

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“…Cases of social media being used by individuals to express suicidal thoughts, look for suicide methods, or even live broadcast suicidal behaviors have been reported and studied in different countries [15-17] including China [18,19]. With Twitter and Facebook blocked in China, Sina Weibo (referred to as Weibo hereafter; Sina is a company name and Weibo literally means Microblog) is one of the most popular social media platforms among the Chinese population.…”

Section: Introductionmentioning

confidence: 99%

Assessing Suicide Risk and Emotional Distress in Chinese Social Media: A Text Mining and Machine Learning Study

Cheng¹,

Li²,

Kwok³

et al. 2017

J Med Internet Res

175

108

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BackgroundEarly identification and intervention are imperative for suicide prevention. However, at-risk people often neither seek help nor take professional assessment. A tool to automatically assess their risk levels in natural settings can increase the opportunity for early intervention.ObjectiveThe aim of this study was to explore whether computerized language analysis methods can be utilized to assess one’s suicide risk and emotional distress in Chinese social media.MethodsA Web-based survey of Chinese social media (ie, Weibo) users was conducted to measure their suicide risk factors including suicide probability, Weibo suicide communication (WSC), depression, anxiety, and stress levels. Participants’ Weibo posts published in the public domain were also downloaded with their consent. The Weibo posts were parsed and fitted into Simplified Chinese-Linguistic Inquiry and Word Count (SC-LIWC) categories. The associations between SC-LIWC features and the 5 suicide risk factors were examined by logistic regression. Furthermore, the support vector machine (SVM) model was applied based on the language features to automatically classify whether a Weibo user exhibited any of the 5 risk factors.ResultsA total of 974 Weibo users participated in the survey. Those with high suicide probability were marked by a higher usage of pronoun (odds ratio, OR=1.18, P=.001), prepend words (OR=1.49, P=.02), multifunction words (OR=1.12, P=.04), a lower usage of verb (OR=0.78, P<.001), and a greater total word count (OR=1.007, P=.008). Second-person plural was positively associated with severe depression (OR=8.36, P=.01) and stress (OR=11, P=.005), whereas work-related words were negatively associated with WSC (OR=0.71, P=.008), severe depression (OR=0.56, P=.005), and anxiety (OR=0.77, P=.02). Inconsistently, third-person plural was found to be negatively associated with WSC (OR=0.02, P=.047) but positively with severe stress (OR=41.3, P=.04). Achievement-related words were positively associated with depression (OR=1.68, P=.003), whereas health- (OR=2.36, P=.004) and death-related (OR=2.60, P=.01) words positively associated with stress. The machine classifiers did not achieve satisfying performance in the full sample set but could classify high suicide probability (area under the curve, AUC=0.61, P=.04) and severe anxiety (AUC=0.75, P<.001) among those who have exhibited WSC.ConclusionsSC-LIWC is useful to examine language markers of suicide risk and emotional distress in Chinese social media and can identify characteristics different from previous findings in the English literature. Some findings are leading to new hypotheses for future verification. Machine classifiers based on SC-LIWC features are promising but still require further optimization for application in real life.

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“…3 Data generated by users' web search query behavior in Internet search engines have been used to address a large number of medical problems, ranging from epidemiological aspects of various diseases 4,29 to monitoring suicide risk 30,31 or nonsuicidal self-injury 32 in a defined population. Accordingly, data related to web search query behavior has been also harnessed in pharmacovigilance for, for example, drug safety issues.…”

Section: Discussionmentioning

confidence: 99%

Linking Annual Prescription Volume of Antidepressants to Corresponding Web Search Query Data

Gahr¹,

Uzelac²,

Zeiss³

et al. 2015

Journal of Clinical Psychopharmacology

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Persons using the Internet to retrieve medical information generate large amounts of health-related data, which are increasingly used in modern health sciences. We analyzed the relation between annual prescription volumes (APVs) of several antidepressants with marketing approval in Germany and corresponding web search query data generated in Google to test whether web search query volume may be a proxy for medical prescription practice. We obtained APVs of several antidepressants related to corresponding prescriptions at the expense of the statutory health insurance in Germany from 2004 to 2013. Web search query data generated in Germany and related to defined search terms (active substance or brand name) were obtained with Google Trends. We calculated correlations (Person's r) between the APVs of each substance and the respective annual "search share" values; coefficients of determination (R) were computed to determine the amount of variability shared by the 2 variables. Significant and strong correlations between substance-specific APVs and corresponding annual query volumes were found for each substance during the observational interval: agomelatine (r = 0.968, R = 0.932, P = 0.01), bupropion (r = 0.962, R = 0.925, P = 0.01), citalopram (r = 0.970, R = 0.941, P = 0.01), escitalopram (r = 0.824, R = 0.682, P = 0.01), fluoxetine (r = 0.885, R = 0.783, P = 0.01), paroxetine (r = 0.801, R = 0.641, P = 0.01), and sertraline (r = 0.880, R = 0.689, P = 0.01). Although the used data did not allow to perform an analysis with a higher temporal resolution (quarters, months), our results suggest that web search query volume may be a proxy for corresponding prescription behavior. However, further studies analyzing other pharmacologic agents and prescription data that facilitate an increased temporal resolution are needed to confirm this hypothesis.

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Suicide-related Internet use: A review

Cited by 61 publications

References 55 publications

Changes in Internet Suicide Search Volumes Following Celebrity Suicides

Changes in Internet Suicide Search Volumes Following Celebrity Suicides

Assessing Suicide Risk and Emotional Distress in Chinese Social Media: A Text Mining and Machine Learning Study

Linking Annual Prescription Volume of Antidepressants to Corresponding Web Search Query Data

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