In this study, we focus on the terminal mental health condition, suicide and investigate methods to estimate suicide risk levels. Therapeutic pessimism concerns with the widely held belief that psychiatric patients are extremely difficult to treat, if not immune to treatment. These factors may coalesce into fragmented patient care due to frequently switching providers or fleeing psychiatric care altogether with possible consequences of deteriorating conditions leading to a suicide attempt. discuss the challenges of cultural and structural issues (e.g., the social stigma of a depression diagnosis), limited provider-patient contact time, over-reliance on medication use, inadequate training to fully appreciate the nuance of a multifactorial disease, lack of access to mental health services, and a sense of mistrust in broaching the topic of suicide. Further, it may serve as an alternative resource for self-help when therapeutic pessimism exists between the mental healthcare providers (MHPs) and patients. Suicide is an often-discussed topic among these social media users. Seventy-one percent of psychiatric patients, including adolescent, are active on social media. Social media provides an unobtrusive platform for individuals suffering from mental health disorders to anonymously share their inner thoughts and feelings without fear of stigma. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. įunding: Amit Sheth, Jyotishman Pathak, Krishnaprasad Thirunarayan, 1 R01 MH105384-01A1, National Institute of Mental Health, Amit Sheth, Krishnaprasad Thirunarayan, 5R01DA039454-02, National Institute on Drug Abuse, Amit Sheth, CNS-1513721 National Science Foundation, Amit Sheth, NSF Award 1761931, Spokes: MEDIUM: MIDWEST: Collaborative: Community-Driven Data Engineering for Substance Abuse Prevention in the Rural Midwest. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: The data is available through the public repository Zenodo at. Received: JAccepted: ApPublished: May 17, 2021Ĭopyright: © 2021 Gaur et al. (2021) Characterization of time-variant and time-invariant assessment of suicidality on Reddit using C-SSRS. The proposed approach can be integrated with clinical diagnostic interviews for improving suicide risk assessments.Ĭitation: Gaur M, Aribandi V, Alambo A, Kursuncu U, Thirunarayan K, Beich J, et al. Our results suggest that the time-variant approach outperforms the time-invariant method in the assessment of suicide-related ideations and supportive behaviors (AUC:0.78), while the time-invariant model performed better in predicting suicide-related behaviors and suicide attempt (AUC:0.64). In particular, we employ two deep learning approaches: time-variant and time-invariant modeling, for user-level suicide risk assessment, and evaluate their performance against a clinician-adjudicated gold standard Reddit corpus annotated based on the C-SSRS. In this work, we address this knowledge gap by developing deep learning algorithms to assess suicide risk in terms of severity and temporality from Reddit data based on the Columbia Suicide Severity Rating Scale (C-SSRS). The insights made possible by access to such data have enormous clinical potential-most dramatically envisioned as a trigger to employ timely and targeted interventions (i.e., voluntary and involuntary psychiatric hospitalization) to save lives. While prior artificial intelligence research has demonstrated the ability to extract valuable information from social media on suicidal thoughts and behaviors, these efforts have not considered both severity and temporality of risk. In the modern world, many individuals suffering from mental illness seek emotional support and advice on well-known and easily-accessible social media platforms such as Reddit. However, predicting when someone will attempt suicide has been nearly impossible. Suicide is the 10 th leading cause of death in the U.S (1999-2019).
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