Search

Importance: On March 31, 2017, Netflix released the show 13 Reasons Why, sparking immediate criticism from suicide prevention organizations for not following media recommendations for responsible suicide portrayal and for possible suicide contagion by media. To date, little research has been conducted into the associations between the show and suicide counts among its young target audience.Objective: To analyze the changes in suicide counts after the release of 13 Reasons Why.Design, Setting, and Participants: For this time series analysis, monthly suicide data for the age groups 10 to 19 years, 20 to 29 years, and 30 years or older for both US males and females from January 1, 1999, to December 31, 2017, were extracted from the Centers for Disease Control and Prevention's WONDER (Wide-ranging Online Data for Epidemiologic Research) database. Twitter and Instagram posts were used as a proxy to estimate the amount of attention the show received through social media from April 1, 2017, to June 30, 2017. Autoregressive integrated moving average time series models were fitted to the pre-April 2017 period to estimate suicides among the age groups and to identify changes in specific suicide methods used. The models were fitted to the full time series with dummy variables for (1) April 2017 and (2) April 1, 2017, to June 30, 2017. Data were analyzed in December 2018 and January 2019.Main Outcomes and Measures: Suicide data before and after the release of the show in 2017.Results: Based on social media data, public interest in the show was highest in April 2017 and was negligible after June 2017. For 10- to 19-year-old males and females, increases in the observed values from April to June 2017 were outside the 95% confidence bands of forecasts. Models testing 3-month associated suicide mortality indicated 66 (95% CI, 16.3-115.7) excess suicides among males (12.4% increase; 95% CI, 3.1%-21.8%) and 37 (95% CI, 12.4-61.5) among females (21.7% increase; 95% CI, 7.3%-36.2%). No excess suicide mortality was seen in other age groups. The increase in the hanging suicide method was particularly high (26.9% increase; 95% CI, 15.3%-38.4%).Conclusions and Relevance: Caution must be taken in interpreting these findings; however, the suicide increase in youth only and the signal of a potentially larger increase in young females all appear to be consistent with a contagion by media and seem to reinforce the need for collaboration toward improving fictional portrayals of suicide. [ABSTRACT FROM AUTHOR]

Objective: In the United States, there was an increase in calls to helplines following media reporting of Robin Williams' suicide. We aimed to determine whether this was the case in Australia., Method: The helpline services Lifeline and Beyond Blue provided us with weekly data on calls received for 2013-2015. We conducted interrupted time series regression analyses to determine whether there was an increase in the average weekly number of calls received by each helpline in two periods after the story about Williams' suicide broke (1 week and 4 weeks)., Results: We found strong evidence of an increase in calls to Lifeline (incidence rate ratio [IRR] =1.13; 95% confidence interval [CI] =1.02-1.25; p = 0.016) and Beyond Blue (IRR = 1.32; 95% CI = 1.09-1.59; p = 0.004) in the week after Williams' suicide was first reported. We found no evidence of higher than normal call volumes for Lifeline (IRR = 1.04; 95% CI = 0.99-1.10; p = 0.104) or Beyond Blue (IRR = 1.10; 95% CI = 1.00-1.22; p = 0.058) over the four weeks following Williams' death, however, suggesting that calls leveled out over this period., Conclusion: Suicide prevention experts and media professionals must work together to minimize the negative impacts of reports on suicide and maximize their positive ones. In cases where the story is likely to receive extensive international coverage, it may be important for local media to encourage help-seeking., (© 2020 The American Association of Suicidology.)

Background: Economic evaluation of individual interventions can have limited usefulness due to the potential for methodological confounding, particularly for those decision contexts where strategies involving multiple interventions are required., Aims: To introduce readers to different approaches of priority-setting, with a focus on economics-based examples of priority-setting in mental health., Method: A selective review of the priority-setting literature, with particular attention given to the mental health context and economics-based approaches., Results: Six priority-setting approaches in mental health are described and assessed., Conclusions: Priority-setting approaches that incorporate methodological rigour, due process for involving stakeholders and broad-based notions of "benefit", are likely to be of most use to mental healthcare decision-makers. Challenges, both in relation to data bases and method remain, but are within the capacity of the mental health research community to resolve.

Increased efforts are needed to promote adolescent health in all areas investigated in this study. Differences both in prevalence and socioeconomic patterning between Norway and the United States indicate that the major challenges differ between the two countries. The results also emphasize the need to undertake joint efforts to use measurements that make national data sets comparable across countries.