Background A growing number of studies indicate that sensationalist reporting of suicide is associated with increases in suicide rates, but in the light of some negative findings, the issue has remained controversial. The aim of this study was to evaluate the best current evidence on the association between celebrity suicide stories and subsequent suicides. Methods Literature searches of six data sources (Medline, Psychlit, Communication Abstracts, Education Resources Information Center, Dissertation Abstracts and Australian Public Affairs Database (APAIS)) were conducted. Studies were included if they (1) adopted an ecological design, (2) focused on celebrity suicide, (3) had completed suicide as outcome variable, (4) analysed suicide rates across all suicide methods, (5) used data from after World War II and (6) satisfied basic quality criteria. Results 10 studies with totally 98 suicides by celebrities met the criteria. The pooled estimate indicated a change in suicide rates (suicides per 100 000 population) of 0.26 (95% CI 0.09 to 0.43) in the month after a celebrity suicide. There was substantial heterogeneity between studies, which was explained by the type of celebrity (entertainment elite vs others) and the region of study, as indicated by mixed-effects meta-regression. The region-of-study–specific effect of reporting a suicide by an entertainment celebrity was 0.64 (95% CI 0.55 to 0.73) in North America, 0.58 (95% CI 0.47 to 0.68) in Asia, 0.36 (95% CI −0.10 to 0.61) in Australia and 0.68 (95% CI 0.51 to 0.85) in Europe. There was no indication of publication bias. Conclusions Reports on celebrity suicide are associated with increases in suicides. Study region and celebrity type appear to have an impact on the effect size.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

Despite the common use of contagion to analogize the spread of suicide, there is a lack of rigorous assessment of the underlying concept or theory supporting the use of this term. The present study aims to examine the varied definitions and potential utility of the term contagion in suicide-related research. 100 initial records and 240 reference records in English were identified as relevant with our research objectives, through systematic literature screening. We then conducted narrative syntheses of various definitions and assessed their potential value for generating new research. 20.3% of the 340 records used contagion as equivalent to clustering (contagion-as-cluster); 68.5% used it to refer to various, often related mechanisms underlying the clustering phenomenon (contagion-as-mechanism); and 11.2% without clear definition. Under the category of contagion-as-mechanism, four mechanisms have been proposed to explain how suicide clusters occurred: transmission (contagion-as-transmission), imitation (contagion-as-imitation), contextual influence (contagion-as-context), and affiliation (contagion-as-affiliation). Contagion-as-cluster both confounds and constrains inquiry into suicide clustering by blending proposed mechanism with the phenomenon to be studied. Contagion-as-transmission is, in essence, a double or internally redundant metaphor. Contagion-as-affiliation and contagion-as-context involve mechanisms that are common mechanisms that often occur independently of apparent contagion, or may serve as a facilitating background. When used indiscriminately, these terms may create research blind spots. Contagion-as-imitation combines perspectives from psychology, sociology, and public health research and provides the greatest heuristic utility for examining whether and how suicide and suicidal behaviors may spread among persons at both individual and population levels. Clarifying the concept of “suicide contagion” is an essential step for more thoroughly investigating its mechanisms. Developing a clearer understanding of the apparent spread of suicide-promoting influences can, in turn, offer insights necessary to build the scientific foundation for prevention and intervention strategies that can be applied at both individual and community levels.

Background: Traditional offline assessment of suicide probability is time consuming and difficult in convincing at-risk individuals to participate. Identifying individuals with high suicide probability through online social media has an advantage in its efficiency and potential to reach out to hidden individuals, yet little research has been focused on this specific field.Objective: The objective of this study was to apply two classification models, Simple Logistic Regression (SLR) and Random Forest (RF), to examine the feasibility and effectiveness of identifying high suicide possibility microblog users in China through profile and linguistic features extracted from Internet-based data.Methods: There were nine hundred and nine Chinese microblog users that completed an Internet survey, and those scoring one SD above the mean of the total Suicide Probability Scale (SPS) score, as well as one SD above the mean in each of the four subscale scores in the participant sample were labeled as high-risk individuals, respectively. Profile and linguistic features were fed into two machine learning algorithms (SLR and RF) to train the model that aims to identify high-risk individuals in general suicide probability and in its four dimensions. Models were trained and then tested by 5-fold cross validation; in which both training set and test set were generated under the stratified random sampling rule from the whole sample. There were three classic performance metrics (Precision, Recall, F1 measure) and a specifically defined metric “Screening Efficiency” that were adopted to evaluate model effectiveness.Results: Classification performance was generally matched between SLR and RF. Given the best performance of the classification models, we were able to retrieve over 70% of the labeled high-risk individuals in overall suicide probability as well as in the four dimensions. Screening Efficiency of most models varied from 1/4 to 1/2. Precision of the models was generally below 30%.Conclusions: Individuals in China with high suicide probability are recognizable by profile and text-based information from microblogs. Although there is still much space to improve the performance of classification models in the future, this study may shed light on preliminary screening of risky individuals via machine learning algorithms, which can work side-by-side with expert scrutiny to increase efficiency in large-scale-surveillance of suicide probability from online social media.

Objectives:This study examines in what exchange patterns that three types of intergenerational support are associated with elderly parents' life satisfaction, and whether elderly parents' evaluation on parent-child relationship plays a mediation role on those associations. Method: Data were drawn from Hong Kong Panel Survey for Poverty Alleviation. Respondents aged 65 and over were included ( N=504). Three types of support, namely, daily-living, financial, and emotional support were examined in four patterns-the over-benefited , under-benefited , reciprocal and no flow of exchange. A multivariable linear regression was applied to investigate the association between pattern of intergenerational exchange and life satisfaction, and mediation analysis was employed to examine the mediating role of satisfaction with parent-child relationship on their associations. Results: Elderly parents were less satisfied with their lives when they had no flow of exchange in daily-living support, and more satisfied when they were under-benefited in financial support, and over-benefited or reciprocal in emotional support. Elderly parents’ satisfaction with parent–child relationship mediated the association between exchange of emotional support and life satisfaction; but not the association between daily-living or financial support and life satisfaction. Conclusion: Different types of intergenerational support are associated with elderly parents’ life satisfaction in different patterns.