IMPORTANCE Suicide is the second leading cause of death among adolescents between the ages of 15 and 24 years. Adolescents who are sexual minorities experience elevated rates of suicide attempts.OBJECTIVE To evaluate the association between state same-sex marriage policies and adolescent suicide attempts. DESIGN, SETTING, AND PARTICIPANTSThis study used state-level Youth Risk Behavior Surveillance System (YRBSS) data from January 1, 1999, to December 31, 2015, which are weighted to be representative of each state that has participation in the survey greater than 60%. A difference-in-differences analysis compared changes in suicide attempts among all public high school students before and after implementation of state policies in 32 states permitting same-sex marriage with year-to-year changes in suicide attempts among high school students in 15 states without policies permitting same-sex marriage. Linear regression was used to control for state, age, sex, race/ethnicity, and year, with Taylor series linearized standard errors clustered by state and classroom. In a secondary analysis among students who are sexual minorities, we included an interaction between sexual minority identity and living in a state that had implemented same-sex marriage policies.INTERVENTIONS Implementation of state policies permitting same-sex marriage during the full period of YRBSS data collection.MAIN OUTCOMES AND MEASURES Self-report of 1 or more suicide attempts within the past 12 months. RESULTS Among the 762 678 students (mean [SD] age, 16.0 [1.2] years; 366 063 males and 396 615 females) who participated in the YRBSS between 1999 and 2015, a weighted 8.6% of all high school students and 28.5% of students who identified as sexual minorities reported suicide attempts before implementation of same-sex marriage policies. Same-sex marriage policies were associated with a 0.6-percentage point (95% CI, -1.2 to -0.01 percentage points) reduction in suicide attempts, representing a 7% relative reduction in the proportion of high school students attempting suicide owing to same-sex marriage implementation. The association was concentrated among students who were sexual minorities.CONCLUSIONS AND RELEVANCE State same-sex marriage policies were associated with a reduction in the proportion of high school students reporting suicide attempts, providing empirical evidence for an association between same-sex marriage policies and mental health outcomes.

Increased use of RD provides an exciting opportunity for obtaining unbiased causal effect estimates when experiments are not feasible or when we want to evaluate programs under "real-life" conditions. Although treatment eligibility in medicine, epidemiology, and public health is commonly determined by threshold rules, use of RD in these fields has been very limited until now.

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BackgroundThe pathway from evidence generation to consumption contains many steps which can lead to overstatement or misinformation. The proliferation of internet-based health news may encourage selection of media and academic research articles that overstate strength of causal inference. We investigated the state of causal inference in health research as it appears at the end of the pathway, at the point of social media consumption.MethodsWe screened the NewsWhip Insights database for the most shared media articles on Facebook and Twitter reporting about peer-reviewed academic studies associating an exposure with a health outcome in 2015, extracting the 50 most-shared academic articles and media articles covering them. We designed and utilized a review tool to systematically assess and summarize studies’ strength of causal inference, including generalizability, potential confounders, and methods used. These were then compared with the strength of causal language used to describe results in both academic and media articles. Two randomly assigned independent reviewers and one arbitrating reviewer from a pool of 21 reviewers assessed each article.ResultsWe accepted the most shared 64 media articles pertaining to 50 academic articles for review, representing 68% of Facebook and 45% of Twitter shares in 2015. Thirty-four percent of academic studies and 48% of media articles used language that reviewers considered too strong for their strength of causal inference. Seventy percent of academic studies were considered low or very low strength of inference, with only 6% considered high or very high strength of causal inference. The most severe issues with academic studies’ causal inference were reported to be omitted confounding variables and generalizability. Fifty-eight percent of media articles were found to have inaccurately reported the question, results, intervention, or population of the academic study.ConclusionsWe find a large disparity between the strength of language as presented to the research consumer and the underlying strength of causal inference among the studies most widely shared on social media. However, because this sample was designed to be representative of the articles selected and shared on social media, it is unlikely to be representative of all academic and media work. More research is needed to determine how academic institutions, media organizations, and social network sharing patterns impact causal inference and language as received by the research consumer.

Regression discontinuity analyses can generate estimates of the causal effects of an exposure when a continuously measured variable is used to assign the exposure to individuals based on a threshold rule. Individuals just above the threshold are expected to be similar in their distribution of measured and unmeasured baseline covariates to individuals just below the threshold, resulting in exchangeability. At the threshold exchangeability is guaranteed if there is random variation in the continuous assignment variable, e.g., due to random measurement error. Under exchangeability, causal effects can be identified at the threshold. The regression discontinuity intention-to-treat (RD-ITT) effect on an outcome can be estimated as the difference in the outcome between individuals just above (or below) versus just below (or above) the threshold. This effect is analogous to the ITT effect in a randomized controlled trial. Instrumental variable methods can be used to estimate the effect of exposure itself utilizing the threshold as the instrument. We review the recent epidemiologic literature reporting regression discontinuity studies and find that while regression discontinuity designs are beginning to be utilized in a variety of applications in epidemiology, they are still relatively rare, and analytic and reporting practices vary. Regression discontinuity has the potential to greatly contribute to the evidence base in epidemiology, in particular on the real-life and long-term effects and side-effects of medical treatments that are provided based on threshold rules – such as treatments for low birth weight, hypertension or diabetes.