Search Results for « Suicide »

Suicide memes are memes used to express suicide-related thoughts or comment on suicide-related issues. Suicide memes are increasingly common on social media, yet remain poorly understood and potentially harmful. There is an urgent need to better understand their characteristics and to develop appropriate content moderation strategies that limits users' exposure to potentially harmful content. Currently, the absence of annotated datasets of suicide memes remains a key barrier to developing and evaluating automated moderation approaches. In this paper, we introduce FigSIM, the first dataset designed for fine-grained analysis of suicide memes. The dataset consists of 1049 memes, each annotated for (1) fine-grained suicide severity levels, (2) figurative phenomena (e.g., metaphors), and (3) suicide-related content (e.g., suicide method depiction). We benchmark 16 unimodal and multimodal models across three tasks: figurative language, suicide severity, and suicide-related content detection. Overall, FigSIM demonstrates that suicide memes pose unique challenges for both modeling and content moderation. Analysis revealed biases, such as underprediction of higher suicide severity levels, especially for figurative memes. The dataset (including splits used for analyses) is publicly available. Content Warning: This paper contains suicide-related content that may be triggering.

Suicide causes more than 49,000 deaths annually in the United States, 55% involving firearms. Suicide mortality varies substantially across US counties, but the role of large-scale social networks remains underexplored. We combine county-level suicide mortality data for 2010-2022 with the Facebook Social Connectedness Index (SCI) and measures of exposure to Extreme Risk Protection Orders (ERPOs). In population-weighted two-way fixed effects models adjusting for sociodemographic and economic characteristics, COVID-19, drug-overdose and alcohol-related mortality, poor mental health days, state firearm policies, and geographical proximity, a one-standard-deviation increase in the SCI-weighted suicide mortality rate of socially connected counties was associated with 2.47 additional deaths per 100,000 residents in the focal county (95% CI [0.97, 4.00]). A one-standard-deviation increase in ERPO social exposure was associated with 0.266 fewer deaths per 100,000 (coefficient -0.266; 95% CI [-0.403, -0.128]) after adjustment for geographical proximity and state-by-year fixed effects. The social-proximity association persisted under alternative neighborhood definitions and spatial-error models, and subgroup analyses showed heterogeneity by age. These findings show that both suicide mortality and the lower mortality associated with exposure to firearm-restriction policies are patterned along inter-county social ties beyond what is explained by geographical proximity alone.

We present a comprehensive evaluation framework for assessing Large Language Models' (LLMs) capabilities in suicide prevention, focusing on two critical aspects: the Identification of Implicit Suicidal ideation (IIS) and the Provision of Appropriate Supportive responses (PAS). We introduce \ourdata, a novel dataset of 1,308 test cases built upon psychological frameworks including D/S-IAT and Negative Automatic Thinking, alongside real-world scenarios. Through extensive experiments with 8 widely used LLMs under different contextual settings, we find that current models struggle significantly with detecting implicit suicidal ideation and providing appropriate support, highlighting crucial limitations in applying LLMs to mental health contexts. Our findings underscore the need for more sophisticated approaches in developing and evaluating LLMs for sensitive psychological applications.

INTRODUCTION: Over the past 20 years the WHO has considerably improved world mortality data. There are still shortcomings but more countries now report data and world-wide estimates are regularly made. METHODS: Data about mortality have been retrieved from the WHO world database. Worldwide injury mortality estimates for 2008 as well as trends of the suicide rate from 1950 to 2009 were analysed. RESULTS: Suicides in the world amount to 782 thousand in 2008 according to the WHO estimate, which is 1.4% of total mortality and 15% of injury mortality. The suicide rate for the world as a whole is estimated at 11.6 per 100,000 inhabitants. The male-female rate ratio of suicide is estimated to be highest in the European Region (4.0) and the lowest in the Eastern Mediterranean region (1.1). Among males the highest suicide rate in the 15-29 age group is in the SE Asian region, in the 45-59 age group in European males and for ages above 60 in the Western Pacific region. Females from SE Asia have a remarkably high suicide rate among 15-29-year-olds and from age 45 in the Western Pacific region. The leading country is currently Lithuania, with a suicide rate of 34.1 per 100,000 inhabitants. Also among males the suicide rate is the highest in Lithuania at 61.2. Among females South Korea with 22.1 is at the top of world suicide rates. CONCLUSIONS: During the past six decades, according to the WHO Japan, Hungary, and Lithuania have topped the list of world countries by suicide rate, but if the current trends continue South Korea will overtake all others in a few years. The heart of the problem of suicide mortality has shifted from Western Europe to Eastern Europe and now seems to be shifting to Asia. China and India are the biggest contributors to the absolute number of suicides in the world.

Introduction: To improve current public health strategies in suicide prevention and mental health, governments, researchers and private companies increasingly use information and communication technologies, and more specifically Artificial Intelligence and Big Data. These technologies are promising but raise ethical challenges rarely covered by current legal systems. It is essential to better identify, and prevent potential ethical risks. Objectives: The Canada Protocol - MHSP is a tool to guide and support professionals, users, and researchers using AI in mental health and suicide prevention. Methods: A checklist was constructed based upon ten international reports on AI and ethics and two guides on mental health and new technologies. 329 recommendations were identified, of which 43 were considered as applicable to Mental Health and AI. The checklist was validated, using a two round Delphi Consultation. Results: 16 experts participated in the first round of the Delphi Consultation and 8 participated in the second round. Of the original 43 items, 38 were retained. They concern five categories: "Description of the Autonomous Intelligent System" (n=8), "Privacy and Transparency" (n=8), "Security" (n=6), "Health-Related Risks" (n=8), "Biases" (n=8). The checklist was considered relevant by most users, and could need versions tailored to each category of target users.

Qin et al et al's (2000, this issue) epidemiological 's (2000, this issue) epidemiological study of risk factors for suicide in males and study of risk factors for suicide in males and females in Denmark reminds us that there females in Denmark reminds us that there are important gender differences in suicidal are important gender differences in suicidal behaviour.These reflect not only differences behaviour.These reflect not only differences in aetiology, which were the primary focus in aetiology, which were the primary focus of the Danish study, but also other import-of the Danish study, but also other important variations by gender in relation to risk, ant variations by gender in relation to risk, the nature of suicidal behaviour and its the nature of suicidal behaviour and its prevention and treatment.prevention and treatment.

Suicidal behavior is a leading cause of injury and death worldwide. Suicide has been associated with psychiatric illnesses such as depression and schizophrenia, as well as economic uncertainty, and social/cultural factors. This study proposes a neuroeconomic framework of suicide. Neuroeconomic parameters (e.g., risk-attitude, probability weighting, time discounting in intertemporal choice, and loss aversion) are predicted to be related to suicidal behavior. Neurobiological and neuroendocrinological substrates such as serotonin, dopamine, cortisol (HPA axis), nitric oxide, serum cholesterol, epinephrine, norepinephrine, gonadal hormones (e.g., estradiol and progesterone), dehydroepiandrosterone (DHEA) in brain regions such as the orbitofrontal/dorsolateral prefrontal cortex and limbic regions (e.g., the amygdala) may supposedly be related to the neuroeconomic parameters modulating the risk of suicide. The present framework puts foundations for "molecular neuroeconomics" of decision-making processes underlying suicidal behavior.

Suicidal behavior is a leading cause of injury and death worldwide. Information about the epidemiology of such behavior is important for policy-making and prevention. The authors reviewed government data on suicide and suicidal behavior and conducted a systematic review of studies on the epidemiology of suicide published from 1997 to 2007. The authors' aims were to examine the prevalence of, trends in, and risk and protective factors for suicidal behavior in the United States and cross-nationally. The data revealed significant cross-national variability in the prevalence of suicidal behavior but consistency in age of onset, transition probabilities, and key risk factors. Suicide is more prevalent among men, whereas nonfatal suicidal behaviors are more prevalent among women and persons who are young, are unmarried, or have a psychiatric disorder. Despite an increase in the treatment of suicidal persons over the past decade, incidence rates of suicidal behavior have remained largely unchanged. Most epidemiologic research on suicidal behavior has focused on patterns and correlates of prevalence. The next generation of studies must examine synergistic effects among modifiable risk and protective factors. New studies must incorporate recent advances in survey methods and clinical assessment. Results should be used in ongoing efforts to decrease the significant loss of life caused by suicidal behavior.