RESUMO
OBJECTIVE: As part of the National Suicide Prevention Lifeline's crisis response system, the Lifeline Crisis Chat Network (LCC) answers chats from hundreds of thousands of at-risk individuals yearly. The study's objective was to assess the effectiveness of these online crisis interventions. METHOD: Data from 39,911 pre-chat surveys and 13,130 linked pre- and post-chat surveys completed by LCC chatters from October 2017-June 2018 were analyzed. The relationship of several effectiveness measures with chatter demographics, pre-chat distress, suicidal ideation, and chatters' perceptions of engagement with their counselors was examined using a series of logistic regression analyses. RESULTS: Chatters were significantly and substantially less distressed at the end of the chat intervention than at the beginning. By the end of the chat, two-thirds of suicidal chatters reported that the chat had been helpful, while just under half reported being less suicidal. CONCLUSIONS: Our study offers empirical evidence for the Lifeline's online crisis chat services' effectiveness, but also highlights areas for improvement. This is of critical import in light of the recent designation of 988 as the nationwide number for the Lifeline beginning in 2022, which will increase the Lifeline's prominence in providing suicide prevention and mental health crisis interventions in the United States.
Assuntos
Linhas Diretas , Prevenção do Suicídio , Intervenção em Crise , Humanos , Ideação Suicida , Inquéritos e Questionários , Estados UnidosRESUMO
We discuss computational language analysis as it pertains to suicide prevention research, with an emphasis on providing non-technologists with an understanding of key issues and, equally important, considering its relation to the broader enterprise of suicide prevention. Our emphasis here is on naturally occurring language in social media, motivated by its non-intrusive ability to yield high-value information that in the past has been largely unavailable to clinicians.
