The impact of history of depression and access to weapons on suicide risk assessment: a comparison of ChatGPT-3.5 and ChatGPT-4.

The aim of this study was to evaluate the effectiveness of ChatGPT-3.5 and ChatGPT-4 in incorporating critical risk factors, namely history of depression and access to weapons, into suicide risk assessments. Both models assessed suicide risk using scenarios that featured individuals with and without a history of depression and access to weapons. The models estimated the likelihood of suicidal thoughts, suicide attempts, serious suicide attempts, and suicide-related mortality on a Likert scale. A multivariate three-way ANOVA analysis with Bonferroni post hoc tests was conducted to examine the impact of the forementioned independent factors (history of depression and access to weapons) on these outcome variables. Both models identified history of depression as a significant suicide risk factor. ChatGPT-4 demonstrated a more nuanced understanding of the relationship between depression, access to weapons, and suicide risk. In contrast, ChatGPT-3.5 displayed limited insight into this complex relationship. ChatGPT-4 consistently assigned higher severity ratings to suicide-related variables than did ChatGPT-3.5. The study highlights the potential of these two models, particularly ChatGPT-4, to enhance suicide risk assessment by considering complex risk factors.

Workplace interventions to prevent suicide: A scoping review.

OBJECTIVES: To map organisational interventions for workplace suicide prevention, identifying the effects, mechanisms, moderators, implementation and economic costs, and how interventions are evaluated. BACKGROUND: Suicide is a devastating event that can have a profound and lasting impact on the individuals and families affected, with the highest rates found among adults of work age. Employers have a legal and ethical responsibility to provide a safe working environment for their employees, which includes addressing the issue of suicide and promoting mental health and well-being. METHODS: A realist perspective was taken, to identify within organisational suicide prevention interventions, what works, for whom and in what circumstances. Published and unpublished studies in six databases were searched. To extract and map data on the interventions the Effect, Mechanism, Moderator, Implementation, Economic (EMMIE) framework was used. Mechanisms were deductively analysed against Bronfenbrenner's socio-ecological model. RESULTS: From 3187 records screened, 46 papers describing 36 interventions within the military, healthcare, the construction industry, emergency services, office workers, veterinary surgeons, the energy sector and higher education. Most mechanisms were aimed at the individual's immediate environment, with the most common being education or training on recognising signs of stress, suicidality or mental illness in oneself. Studies examined the effectiveness of interventions in terms of suicide rates, suicidality or symptoms of mental illness, and changes in perceptions, attitudes or beliefs, with most reporting positive results. Few studies reported economic costs but those that did suggested that the interventions are cost-effective. CONCLUSIONS: It seems likely that organisational suicide prevention programmes can have a positive impact on attitudes and beliefs towards suicide as well reducing the risk of suicide. Education, to support individuals to recognise the signs and symptoms of stress, mental ill health and suicidality in both themselves and others, is likely to be an effective starting point for successful interventions.

Asynchronous Versus Synchronous Screening for Depression and Suicidality in a Primary Health Care System: Quality Improvement Study.

Background: Despite being a debilitating, costly, and potentially life-threatening condition, depression is often underdiagnosed and undertreated. Previsit Patient Health Questionnaire-9 (PHQ-9) may help primary care health systems identify symptoms of severe depression and prevent suicide through early intervention. Little is known about the impact of previsit web-based PHQ-9 on patient care and safety. Objective: We aimed to investigate differences among patient characteristics and provider clinical responses for patients who complete a web-based (asynchronous) versus in-clinic (synchronous) PHQ-9. Methods: This quality improvement study was conducted at 33 clinic sites across 2 health systems in Northern California from November 1, 2020, to May 31, 2021, and evaluated 1683 (0.9% of total PHQs completed) records of patients endorsing thoughts that they would be better off dead or of self-harm (question 9 in the PHQ-9) following the implementation of a depression screening program that included automated electronic previsit PHQ-9 distribution. Patient demographics and providers' clinical response (suicide risk assessment, triage nurse connection, medication management, electronic consultation with psychiatrist, and referral to social worker or psychiatrist) were compared for patients with asynchronous versus synchronous PHQ-9 completion. Results: Of the 1683 patients (female: n=1071, 63.7%; non-Hispanic: n=1293, 76.8%; White: n=831, 49.4%), Hispanic and Latino patients were 40% less likely to complete a PHQ-9 asynchronously (odds ratio [OR] 0.6, 95% CI 0.45-0.8; P<.001). Patients with Medicare insurance were 36% (OR 0.64, 95% CI 0.51-0.79) less likely to complete a PHQ-9 asynchronously than patients with private insurance. Those with moderate to severe depression were 1.61 times more likely (95% CI 1.21-2.15; P=.001) to complete a PHQ-9 asynchronously than those with no or mild symptoms. Patients who completed a PHQ-9 asynchronously were twice as likely to complete a Columbia-Suicide Severity Rating Scale (OR 2.41, 95% CI 1.89-3.06; P<.001) and 77% less likely to receive a referral to psychiatry (OR 0.23, 95% CI 0.16-0.34; P<.001). Those who endorsed question 9 "more than half the days" (OR 1.62, 95% CI 1.06-2.48) and "nearly every day" (OR 2.38, 95% CI 1.38-4.12) were more likely to receive a referral to psychiatry than those who endorsed question 9 "several days" (P=.002). Conclusions: Shifting depression screening from in-clinic to previsit led to a dramatic increase in PHQ-9 completion without sacrificing patient safety. Asynchronous PHQ-9 can decrease workload on frontline clinical team members, increase patient self-reporting, and elicit more intentional clinical responses from providers. Observed disparities will inform future improvement efforts.

Emerging Trends of Self-Harm Using Sodium Nitrite in an Online Suicide Community: Observational Study Using Natural Language Processing Analysis.

Background: There is growing concern around the use of sodium nitrite (SN) as an emerging means of suicide, particularly among younger people. Given the limited information on the topic from traditional public health surveillance sources, we studied posts made to an online suicide discussion forum, "Sanctioned Suicide," which is a primary source of information on the use and procurement of SN. Objective: This study aims to determine the trends in SN purchase and use, as obtained via data mining from subscriber posts on the forum. We also aim to determine the substances and topics commonly co-occurring with SN, as well as the geographical distribution of users and sources of SN. Methods: We collected all publicly available from the site's inception in March 2018 to October 2022. Using data-driven methods, including natural language processing and machine learning, we analyzed the trends in SN mentions over time, including the locations of SN consumers and the sources from which SN is procured. We developed a transformer-based source and location classifier to determine the geographical distribution of the sources of SN. Results: Posts pertaining to SN show a rise in popularity, and there were statistically significant correlations between real-life use of SN and suicidal intent when compared to data from the Centers for Disease Control and Prevention (CDC) Wide-Ranging Online Data for Epidemiologic Research (⍴=0.727; P<.001) and the National Poison Data System (⍴=0.866; P=.001). We observed frequent co-mentions of antiemetics, benzodiazepines, and acid regulators with SN. Our proposed machine learning-based source and location classifier can detect potential sources of SN with an accuracy of 72.92% and showed consumption in the United States and elsewhere. Conclusions: Vital information about SN and other emerging mechanisms of suicide can be obtained from online forums.

Specific effects of cumulative childhood trauma on suicidality among youths.

BACKGROUND: Suicidality was very high among individuals who suffered from childhood trauma. The distribution of cumulative childhood trauma among youths remains unclear, as well as the specific effects of cumulative childhood trauma on suicidality. This study attempted to explore the distribution of cumulative childhood trauma and examine the specific effects of cumulative childhood trauma on suicidality. METHODS: A cross-sectional design was employed in this study, with 117,769 college students recruited from 63 universities in Jilin Province, China. All variables were measured by corresponding self-report questionnaires. The Venn diagram was used to represent the distribution of single and cumulative childhood trauma. ANOVA and chi-square tests were conducted to identify the high-risk suicide groups. Multiple linear regression analysis was performed to examine risk factors for suicidality for overlapping subtypes. RESULTS: 27,671 (23.5%) participants reported suffering from childhood trauma, of which 49.5% were male (Mage = 19.59, SD = 1.76). The "physical neglect" group accounted for the largest proportion (31.5%). Suicidality was the highest in the "overlap of childhood neglect, emotional abuse, and physical abuse" group (2.0%). Depression, obsessive-compulsive disorder, and post-traumatic stress disorder were common risk factors for suicidality. LIMITATIONS: This study was limited by cross-sectional studies and self-report bias. CONCLUSIONS: The childhood trauma subtype group with the largest proportion was not necessarily the highest suicidality. Both the largest group and the highest-risk suicide group require special attention to their respective risk factors.

Machine learning approach for the development of a crucial tool in suicide prevention: The Suicide Crisis Inventory-2 (SCI-2) Short Form.

The Suicide Crisis Syndrome (SCS) describes a suicidal mental state marked by entrapment, affective disturbance, loss of cognitive control, hyperarousal, and social withdrawal that has predictive capacity for near-term suicidal behavior. The Suicide Crisis Inventory-2 (SCI-2), a reliable clinical tool that assesses SCS, lacks a short form for use in clinical settings which we sought to address with statistical analysis. To address this need, a community sample of 10,357 participants responded to an anonymous survey after which predictive performance for suicidal ideation (SI) and SI with preparatory behavior (SI-P) was measured using logistic regression, random forest, and gradient boosting algorithms. Four-fold cross-validation was used to split the dataset in 1,000 iterations. We compared rankings to the SCI-Short Form to inform the short form of the SCI-2. Logistic regression performed best in every analysis. The SI results were used to build the SCI-2-Short Form (SCI-2-SF) utilizing the two top ranking items from each SCS criterion. SHAP analysis of the SCI-2 resulted in meaningful rankings of its items. The SCI-2-SF, derived from these rankings, will be tested for predictive validity and utility in future studies.

Suicide prevention: reflections on progress over the past decade.

Interest in preventing suicides has increased greatly in recent years. In this Personal View, we consider the general global developments related to suicide prevention that have occurred in the decade since The Lancet Psychiatry was first published in 2014. We then review specific advances during this period, first, in relation to public health initiatives, and second, with regard to clinical developments. Finally, we examine some of the challenges that currently confront individuals and organisations responsible for designing and implementing suicide prevention measures.

Epidemiological characteristics and behaviors of online broadcast suicidality in China: implications for targeted prevention strategies.

Objectives: Suicide is a global health concern, exacerbated by stigma around mental illnesses. Online platforms like Twitter and Sina Weibo have seen a rise in "online broadcast suicide," where individuals share suicidal thoughts and actions. However, there is limited understanding of the epidemiological characteristics, particularly in China. This study aims to analyze the demographics and behaviors of individuals engaging in online broadcast suicide in China to inform targeted prevention strategies. Methods: A total of 525 incidents were identified through systematic retrieval of relevant news reports from online sources. Subsequently, a content analysis was performed on these reports to extract detailed information on the characteristics of each individual incident. Results: Among the incidents analyzed, the male-to-female ratio was 1:1.6, with an average age of 23.1 ± 5.9 years. Approximately 71.9% took place in Southern China. Unemployment was reported in 15.0% of incidents. Relationship breakup (62.3%) was cited as the leading cause of suicide. Wrist cutting (58.2%) emerged as the predominant suicide method, and home (36.2%) was the most common location for these tragic events. Instant messaging apps were the primary platforms (54.7%) for conveying suicidal thoughts and actions. Additionally, among the 525 incidents examined, 12.0% disclosed having a mental disorder, and 7.6% had a history of prior suicide attempts. Significant variations were observed across age, gender, region, and occupation categories. Conclusion: This study emphasizes the importance of developing suicide prevention programs for internet users. Besides, interventions should be customized to meet the specific needs of various populations.

Nursing students' experience of approaching risk for suicide behaviour through simulated environments: A content analysis study.

BACKGROUND: Suicide is a major public health problem, especially among the young population. Nurses are in a unique position to prevent it due to their constant contact with patients. However, addressing suicidal behaviour can be complicated by the emotional responses it elicits. Simulation has been shown to be an effective tool to increase the self-confidence of nursing students in dealing with these sensitive situations in a safe environment prior to dealing with real patients. AIM: To explore nursing students' perceptions, thoughts, and emotions about their performance in dealing with risk for suicidal behaviour through simulated scenarios. DESIGN: Qualitative descriptive study. METHODS: Students of Mental Health and Psychiatric II in the third year of the Nursing course at the University of Málaga were invited to explain their experience by answering a questionnaire of three open-ended questions following their participation in the simulated scenarios of the course. RESULTS: A total of 72 students participated. Content analysis of the written responses identified three main themes: (i) Emotions experienced during the simulation; (ii) Self-criticism of the performance/intervention; (iii) Student evaluation of the learning experience. Most of the students indicated at some point during the clinical scenario, they had felt anxiety, proposing possible improvements in their own performance. The clinical scenario that elicited the most negative emotions was that of a person diagnosed with borderline personality disorder. CONCLUSION: Clinical simulations contribute to a better understanding of nursing practice with mental health patients and the need for training in emotional and therapeutic communication skills among students.

Using Large Language Models to Understand Suicidality in a Social Media-Based Taxonomy of Mental Health Disorders: Linguistic Analysis of Reddit Posts.

Background: Rates of suicide have increased by over 35% since 1999. Despite concerted efforts, our ability to predict, explain, or treat suicide risk has not significantly improved over the past 50 years. Objective: The aim of this study was to use large language models to understand natural language use during public web-based discussions (on Reddit) around topics related to suicidality. Methods: We used large language model-based sentence embedding to extract the latent linguistic dimensions of user postings derived from several mental health-related subreddits, with a focus on suicidality. We then applied dimensionality reduction to these sentence embeddings, allowing them to be summarized and visualized in a lower-dimensional Euclidean space for further downstream analyses. We analyzed 2.9 million posts extracted from 30 subreddits, including r/SuicideWatch, between October 1 and December 31, 2022, and the same period in 2010. Results: Our results showed that, in line with existing theories of suicide, posters in the suicidality community (r/SuicideWatch) predominantly wrote about feelings of disconnection, burdensomeness, hopeless, desperation, resignation, and trauma. Further, we identified distinct latent linguistic dimensions (well-being, seeking support, and severity of distress) among all mental health subreddits, and many of the resulting subreddit clusters were in line with a statistically driven diagnostic classification system-namely, the Hierarchical Taxonomy of Psychopathology (HiTOP)-by mapping onto the proposed superspectra. Conclusions: Overall, our findings provide data-driven support for several language-based theories of suicide, as well as dimensional classification systems for mental health disorders. Ultimately, this novel combination of natural language processing techniques can assist researchers in gaining deeper insights about emotions and experiences shared on the web and may aid in the validation and refutation of different mental health theories.

Risk factors and their association network for young adults' suicidality: a cross-sectional study.

BACKGROUND: Understanding the intricate influences of risk factors contributing to suicide among young individuals remains a challenge. The current study employed interpretable machine learning and network analysis to unravel critical suicide-associated factors in Chinese university students. METHODS: A total of 68,071 students were recruited between Sep 2016 and Sep 2020 in China. Students reported their lifetime experiences with suicidal thoughts and behaviors, categorized as suicide ideation (SI), suicide plan (SP), and suicide attempt (SA). We assessed 36 suicide-associated factors including psychopathology, family environment, life events, and stigma. Local interpretations were provided using Shapley additive explanation (SHAP) interaction values, while a mixed graphical model facilitated a global understanding of their interplay. RESULTS: Local explanations based on SHAP interaction values suggested that psychoticism and depression severity emerged as pivotal factors for SI, while paranoid ideation strongly correlated with SP and SA. In addition, childhood neglect significantly predicted SA. Regarding the mixed graphical model, a hierarchical structure emerged, suggesting that family factors preceded proximal psychopathological factors, with abuse and neglect retaining unique effects. Centrality indices derived from the network highlighted the importance of subjective socioeconomic status and education in connecting various risk factors. CONCLUSIONS: The proximity of psychopathological factors to suicidality underscores their significance. The global structures of the network suggested that co-occurring factors influence suicidal behavior in a hierarchical manner. Therefore, prospective prevention strategies should take into account the hierarchical structure and unique trajectories of factors.

Protocol for process evaluation of ARTEMIS cluster randomised controlled trial: an intervention for management of depression and suicide among adolescents living in slums in India.

INTRODUCTION: There are around 250 million adolescents (10-19 years) in India. The prevalence of mental health-related morbidity among adolescents in India is approximately 7.3%. Vulnerable subpopulations among adolescents such as those living in slum communities are particularly at risk due to poor living conditions, financial difficulty and limited access to support services. Adolescents' Resilience and Treatment nEeds for Mental Health in Indian Slums (ARTEMIS) is a cluster randomised controlled trial of an intervention that intends to improve the mental health of adolescents living in slum communities in India. The aim of this paper is to describe the process evaluation protocol for ARTEMIS trial. The process evaluation will help to explain the intervention outcomes and understand how and why the intervention worked or did not work. It will identify contextual factors, intervention barriers and facilitators and the adaptations required for optimising implementation. METHODS: Case study method will be used and the data will include a mix of quantitative metrics and qualitative data. The UK Medical Research Council's guidance on evaluating complex interventions, the Reach, Efficacy, Adoption, Implementation and Maintenance Framework and the Affordability, Practicability, Effectiveness and cost-effectiveness, Acceptability, Safety/Side Effects and, Equity criteria will be used to develop a conceptual framework and a priori codes for qualitative data analysis. Quantitative data will be analysed using descriptive statistics. Implementation fidelity will also be measured. DISCUSSION: The process evaluation will provide an understanding of outcomes and causal mechanisms that influenced any change in trial outcomes. ETHICS AND DISSEMINATION: Ethics Committee of the George Institute for Global Health India (project number 17/2020) and the Research Governance and Integrity Team, Imperial College, London (ICREC reference number: 22IC7718) have provided ethics approval. The Health Ministry's Screening Committee has approved to the study (ID 2020-9770). TRIAL REGISTRATION NUMBER: CTRI/2022/02/040307.

Effectiveness of a school-based Life Gatekeeper Training Program on suicide prevention in China: protocol for a randomized controlled trial.

BACKGROUND: With suicide as a leading cause of death, the issue of children and adolescent suicide risks is in the spotlight today. To empower teachers in primary and secondary schools to serve as gatekeepers and to ensure the safety of children and adolescents, the systematically tailored and localized Life Gatekeeper suicide prevention program was designed for Chinese schools. OBJECTIVE: With the ultimate goal of preventing child and adolescent suicide, we aim to outline a research protocol for examining outcomes of the recently created standardized school-based Life Gatekeeper program in reducing teachers' stigma, increasing their knowledge, willingness to intervene, and perceived competence. METHODS: Participants will be recruited from eligible primary and secondary schools. Cluster sampling will be used to randomly assign each school to either the intervention group or the control group. The primary outcomes are stigma against suicide, suicide literacy, perceived competence, and willingness to intervene with suicidal individuals, which will be measured using the Stigma of Suicide Scale, the Literacy of Suicide Scale, and the Willingness to Intervene Against Suicide Questionnaire, respectively. Measurements will be taken at four time points, including pre-intervention, immediately after the intervention, 6-month follow-up, and 1-year follow-up. CONCLUSIONS: The current study features innovative implementation in the real world, by using a randomized controlled trial design to examine the effectiveness of a school-based gatekeeper program among primary and secondary school teachers, following a sequence of defined and refined steps. The research will also investigate the viability of a school-based gatekeeper program for primary and secondary school teachers that could be quickly and inexpensively implemented in a large number of schools.

Variations in healthcare utilization for mental health problems prior to suicide by socioeconomic status: a Norwegian register-based population study.

BACKGROUND: Suicide poses a major public health challenge, claiming around 650 lives annually in Norway. There is limited understanding of mental healthcare utilization patterns preceding suicide, particularly relating to socioeconomic status (SES). This study analyzes mental health service use among Norwegian citizens aged 20-64 from 2009 to 2021, emphasizing disparities related to SES. METHODS: This is a population-wide registry-based study. We include mental health consultations with both primary and specialist healthcare services, and investigate patterns of service use regarding educational attainment, employment status and income and compare this to the population in general. All suicides in the period (N = 4731) are included in the study. The aim is to investigate potential discrepancies in service use the year and month preceding suicide, seeking to enhance targeted preventive interventions. RESULTS: Our results show significant variations in healthcare use for mental health problems the last year preceding suicide, according to the components of SES, for both men and women. Those with higher education utilize the mental healthcare services prior to suicide to a higher degree than men and women with high school education or less, whereas employed men and men with high income level have significantly lower mental healthcare usage prior to suicide both the last year and month compared to the non-employed men and men with low-income level. Employed women also had a lower mental healthcare usage, whereas the results regarding income are not significant for women. CONCLUSION: Mental healthcare use prior to suicide varies across the SES components. Notably, the SES groups exhibit heterogeneity, with gendered patterns. Targeted interventions for low consultation rates among employed men, and men with high income and lower education are needed, while women, and men in at-risk groups, such as the non-employed and those with low income, demonstrate higher mental healthcare utilization, warranting comprehensive suicide prevention measures.