Rates of suicide in the United States are at a more than 20-y high. Suicide contagion, or spread of suicide-related thoughts and behaviors through exposure to sensationalized and harmful content is a ...well-recognized phenomenon. Health authorities have published guidelines for news media reporting on suicide to help prevent contagion; however, uptake of recommendations remains limited. A key barrier to widespread voluntary uptake of suicidereporting guidelines is that more sensational content is perceived to be more engaging to readers and thus enhances publisher visibility and engagement; however, no empirical information exists on the actual influence of adherence to safe-reporting practices on reader engagement. Hence, we conducted a study to analyze adherence to suicide-reporting guidelines on news shared on social media and to assess how adherence affects reader engagement. Our analysis of Facebook data revealed that harmful elements were prevalent in news articles about suicide shared on social media while the presence of protective elements was generally rare. Contrary to popular perception, closer adherence to safe-reporting practices was associated with a greater likelihood of an article being reshared (adjusted odds ratio AOR = 1.19, 95% confidence interval CI = 1.10 to 1.27) and receiving positive engagement (“love” reactions) (AOR = 1.20, 95% CI = 1.13 to 1.26).Mean safe-reporting scores were lower in the US than other English-speaking nations and variation existed by publisher characteristics. Our results provide empirical evidence that improved adherence to suicide-reporting guidelines may benefit not only the health of individuals, but also support publisher goals of reach and engagement.
Suicide mortality data are a critical source of information for understanding suicide-related trends in the United States. However, official suicide mortality data experience significant delays. The ...Google Symptom Search Dataset (SSD), a novel population-level data source derived from online search behavior, has not been evaluated for its utility in predicting suicide mortality trends.
We identified five mental health related variables (suicidal ideation, self-harm, depression, major depressive disorder, and pain) from the SSD. Daily search trends for these symptoms were utilized to estimate national and state suicide counts in 2020, the most recent year for which data was available, via a linear regression model. We compared the performance of this model to a baseline autoregressive integrated moving average (ARIMA) model and a model including all 422 symptoms (All Symptoms) in the SSD.
Our Mental Health Model estimated the national number of suicide deaths with an error of −3.86 %, compared to an error of 7.17 % and 28.49 % for the ARIMA baseline and All Symptoms models. At the state level, 70 % (N = 35) of states had a prediction error of <10 % with the Mental Health Model, with accuracy generally favoring larger population states with higher number of suicide deaths.
The Google SSD is a new real-time data source that can be used to make accurate predictions of suicide mortality monthly trends at the national level. Additional research is needed to optimize state level predictions for states with low suicide counts.
•Official suicide mortality data experience significant delays.•The Google Symptom Search Dataset can be used to make accurate predictions of suicide mortality trends at the national level.•State-level predictions using the Google Symptom Search Dataset are more accurate for larger population states.
Adverse childhood experiences (ACEs), which include abuse and neglect and various household challenges such as exposure to intimate partner violence and substance use in the home, can have negative ...impacts on the lifelong health of affected individuals. Among various strategies for mitigating the adverse effects of ACEs is to enhance connectedness and social support for those who have experienced them. However, how the social networks of those who experienced ACEs differ from the social networks of those who did not is poorly understood.
In this study, we used Reddit and Twitter data to investigate and compare social networks between individuals with and without ACE exposure.
We first used a neural network classifier to identify the presence or absence of public ACE disclosures in social media posts. We then analyzed egocentric social networks comparing individuals with self-reported ACEs with those with no reported history.
We found that, although individuals reporting ACEs had fewer total followers in web-based social networks, they had higher reciprocity in following behavior (ie, mutual following with other users), a higher tendency to follow and be followed by other individuals with ACEs, and a higher tendency to follow back individuals with ACEs rather than individuals without ACEs.
These results imply that individuals with ACEs may try to actively connect with others who have similar previous traumatic experiences as a positive connection and coping strategy. Supportive interpersonal connections on the web for individuals with ACEs appear to be a prevalent behavior and may be a way to enhance social connectedness and resilience in those who have experienced ACEs.
Understanding changes in the incidence rates and lethality of suicidal acts may explain increasing suicide rates.
To examine trends in the incidence rates and lethality of suicidal acts from 2006 to ...2015 among persons aged 10 to 74 years.
This cross-sectional study was conducted from May 2, 2018, to January 30, 2019. Medically treated nonfatal suicide attempts were identified from the 2006 to 2015 Nationwide Inpatient Sample and Nationwide Emergency Department Sample databases. Suicides were identified from the 2006 to 2015 mortality files of the National Vital Statistics System.
The incidence rate of suicidal acts was calculated by dividing the number of total suicidal acts by the US population. Lethality was measured through the case fatality rates (CFRs) of suicidal acts by dividing the number of suicides by the total number of suicidal acts.
A total of 1 222 419 (unweighted) suicidal acts, which included both suicides and nonfatal suicide attempts, were identified from 2006 to 2015. Overall, the incidence rates of total suicidal acts increased 10% from 2006 to 2015 (annual percentage change APC, 0.8%; 95% CI, 0.3%-1.3%), and the CFRs of suicidal acts increased 13% during the 2006 to 2015 period (APC, 2.3%; 95% CI, 1.3%-3.3%). In subgroup analyses, incidence rates increased by 1.1% (95% CI, 0.6%-1.6%) per year for female individuals during the 2006 to 2015 period but remained stable for male individuals. The CFRs increased for both sexes (APC, 5.0% 95% CI, 3.1%-6.9% since 2010 for female individuals; 1.6% 95% CI, 0.6%-2.5% since 2009 for male individuals). Incidence rates increased among adolescents from 2011 to 2015 and among older adults aged 65 to 74 years throughout the 2006 to 2015 period. Conversely, the CFRs increased since 2009 among persons aged 20 to 44 years (APC, 3.7%; 95% CI, 2.5%-5.0%) and since 2012 for those aged 45 to 64 years (APC, 2.7%; 95% CI, 0.0%-5.4%). Persons aged 20 to 44 years and 45 to 64 years experienced increases in suicidal acts by more lethal means, whereas adolescents and older adults aged 65 to 74 years showed increased incidence by all means.
This study found increased suicidal acts among female persons, adolescents, and older adults aged 65 to 74 years, implying the need to address emerging or exacerbating suicide risk factors for these populations. The findings on the increased lethality particularly among persons aged 20 to 64 years highlighted the need to reduce access to materials that could be used as lethal means among persons at risk of suicide. These findings on population-level epidemiologic patterns can be used to guide the development of comprehensive suicide prevention strategies.
Stigma associated with substance use and addiction is a major barrier to overdose prevention. Although stigma reduction is a key goal of federal strategies to prevent overdose, there is limited data ...to assess progress made in reducing use of stigmatizing language about addiction.
Using language guidelines published by the federal National Institute on Drug Abuse (NIDA), we examined trends in use of stigmatizing terms about addiction across four popular public communication modalities: news articles, blogs, Twitter, and Reddit. We calculate percent changes in the rates of articles/posts using stigmatizing terms over a five-year period (2017–2021) by fitting a linear trendline and assess statistically significant trends using the Mann-Kendall test.
The rate of articles containing stigmatizing language decreased over the past five years for news articles (−68.2 %, p < 0.001) and blogs (−33.6 %, p < 0.001). Among social media platforms, the rate of posts using stigmatizing language increased (Twitter 43.5 %, p = 0.01) or remained stable (Reddit 3.1 %, p = 0.29). In absolute terms, news articles had the highest rate of articles containing stigmatizing terms over the five-year period (324.9 articles per million) compared to 132.3, 18.3, and 138.6 posts per million for blogs, Twitter, and Reddit, respectively.
Use of stigmatizing language about addiction appears to have decreased across more traditional, longer-format communication modalities such as news articles. Additional work is needed to reduce use of stigmatizing language on social media.
•Guidelines exist to prevent stigmatizing language about substance use and addiction.•Stigmatizing language about substance use and addiction has decreased over time in news articles.•Work to reduce stigmatizing language about substance use and addiction on social media is needed.
Delta-8 tetrahydrocannabinol (THC) is a psychoactive cannabinoid found in small amounts naturally in the cannabis plant; it can also be synthetically produced in larger quantities from hemp-derived ...cannabidiol. Most states permit the sale of hemp and hemp-derived cannabidiol products; thus, hemp-derived delta-8 THC products have become widely available in many state hemp marketplaces, even where delta-9 THC, the most prominently occurring THC isomer in cannabis, is not currently legal. Health concerns related to the processing of delta-8 THC products and their psychoactive effects remain understudied.
The goal of this study is to implement a novel topic modeling approach based on transformers, a state-of-the-art natural language processing architecture, to identify and describe emerging trends and topics of discussion about delta-8 THC from social media discourse, including potential symptoms and adverse health outcomes experienced by people using delta-8 THC products.
Posts from January 2008 to December 2021 discussing delta-8 THC were isolated from cannabis-related drug forums on Reddit (Reddit Inc), a social media platform that hosts the largest web-based drug forums worldwide. Unsupervised topic modeling with state-of-the-art transformer-based models was used to cluster posts into topics and assign labels describing the kinds of issues being discussed with respect to delta-8 THC. Results were then validated by human subject matter experts.
There were 41,191 delta-8 THC posts identified and 81 topics isolated, the most prevalent being (1) discussion of specific brands or products, (2) comparison of delta-8 THC to other hemp-derived cannabinoids, and (3) safety warnings. About 5% (n=1220) of posts from the resulting topics included content discussing health-related symptoms such as anxiety, sleep disturbance, and breathing problems. Until 2020, Reddit posts contained fewer than 10 mentions of delta-8-THC for every 100,000 cannabis posts annually. However, in 2020, these rates increased by 13 times the 2019 rate (to 99.2 mentions per 100,000 cannabis posts) and continued to increase into 2021 (349.5 mentions per 100,000 cannabis posts).
Our study provides insights into emerging public health concerns around delta-8 THC, a novel substance about which little is known. Furthermore, we demonstrate the use of transformer-based unsupervised learning approaches to derive intelligible topics from highly unstructured discussions of delta-8 THC, which may help improve the timeliness of identification of emerging health concerns related to new substances.
Rates of suicide are increasing rapidly among youth. Social media messages and online games promoting suicide are a concern for parents and clinicians. We examined the timing and location of social ...media posts about one alleged youth suicide game to better understand the degree to which social media data can provide earlier public health awareness.
We conducted a search of all public social media posts and news articles on the Blue Whale Challenge (BWC), an alleged suicide game, from January 1, 2013, through June 30, 2017. Data were retrieved through multiple keyword search; sources included social media platforms Twitter, YouTube, Reddit, Tumblr, as well as blogs, forums, and news articles. Posts were classified into three categories: individual “pro”-BWC posts (support for game), individual “anti”-BWC posts (opposition to game), and media reports. Timing and location of posts were assessed.
Overall, 95,555 social media posts and articles about the BWC were collected. In total, over one-quarter (28.3%) were “pro”-BWC. The first U.S. news article related to the BWC was published approximately 4 months after the first English language U.S. social media post about the BWC and 9 months after the first U.S. social media post in any language. By the close of the study period, “pro”-BWC posts had spread to 127 countries.
Novel online risks to mental health, such as prosuicide games or messages, can spread rapidly and globally. Better understanding social media and Web data may allow for detection of such threats earlier than is currently possible.
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