BACKGROUND: Suicide poses a substantial public health challenge globally, with the elderly population being particularly vulnerable. Research into suicide risk factors among elderly inpatients with non-psychiatric disorders remains limited. This inve...
AIMS: Studies conducted during the COVID-19 pandemic found high occurrence of suicidal thoughts and behaviours (STBs) among healthcare workers (HCWs). The current study aimed to (1) develop a machine learning-based prediction model for future STBs us...
OBJECTIVE: Patients with cancer have a high risk of suicide. However, evidence-based preventive measures remain unclear. This study aimed to investigate suicide prevention strategies for hospitalized patients with cancer by analyzing nationwide patie...
Traditional clinical risk assessment tools proved inadequate for reliably identifying individuals at high risk for suicidal behavior. As a result, machine learning (ML) techniques have become progressively incorporated into psychiatric care. This stu...
BACKGROUND: Screening for suicide ideation and suicide attempts is crucial for adolescents, yet accurately predicting these outcomes remains a significant challenge. The relationship between non-suicidal self-injury and suicide ideation and attempts ...
Young adults with childhood sexual abuse (CSA) are an especially vulnerable group to suicide. Suicide encompasses different phases, but for CSA survivors the salient factors precipitating suicide are rarely studied. In this study, from a progressive ...
INTRODUCTION: Suicide remains a critical global public health issue, with approximately 800,000 deaths annually. Despite various prevention efforts, suicide rates are rising, highlighting the need for more effective strategies. Traditional suicide ri...
Suicide causes over 700,000 deaths annually worldwide. Mental disorders are closely linked to suicidal ideation, but predicting suicide remains complex due to the multifaceted nature of contributing factors. Traditional assessment tools often fail to...
BACKGROUND: Ecological momentary assessment (EMA) captures dynamic processes suitable to the study of suicidal ideation and behaviors. Artificial intelligence (AI) has increasingly been applied to EMA data in the study of suicidal processes.
Introducción: la ideación suicida es el pensamiento de autoeliminación no siempre reportada por los pacientes en test de depresión. El objetivo fue identificar y analizar síntomas depresivos del cuestionario de salud del paciente-9 asociados a ideaci...