Literature DB >> 30944915

Identification of Imminent Suicide Risk Among Young Adults using Text Messages.

Alicia L Nobles1, Jeffrey J Glenn2, Kamran Kowsari3, Bethany A Teachman4, Laura E Barnes5.   

Abstract

Suicide is the second leading cause of death among young adults but the challenges of preventing suicide are significant because the signs often seem invisible. Research has shown that clinicians are not able to reliably predict when someone is at greatest risk. In this paper, we describe the design, collection, and analysis of text messages from individuals with a history of suicidal thoughts and behaviors to build a model to identify periods of suicidality (i.e., suicidal ideation and non-fatal suicide attempts). By reconstructing the timeline of recent suicidal behaviors through a retrospective clinical interview, this study utilizes a prospective research design to understand if text communications can predict periods of suicidality versus depression. Identifying subtle clues in communication indicating when someone is at heightened risk of a suicide attempt may allow for more effective prevention of suicide.

Entities:  

Keywords:  H.1.2 User/Machine Systems; I.5 Pattern Recognition; J.3 Life and Medical Sciences: Health; J.4 Social and Behavioral Sciences: Psychology; depression; mental health; social media; suicide; text messages

Year:  2018        PMID: 30944915      PMCID: PMC6442737          DOI: 10.1145/3173574.3173987

Source DB:  PubMed          Journal:  Proc SIGCHI Conf Hum Factor Comput Syst


  8 in total

1.  Can Text Messages Identify Suicide Risk in Real Time? A Within-Subjects Pilot Examination of Temporally Sensitive Markers of Suicide Risk.

Authors:  Jeffrey J Glenn; Alicia L Nobles; Laura E Barnes; Bethany A Teachman
Journal:  Clin Psychol Sci       Date:  2020-05-28

2.  Tweet Classification to Assist Human Moderation for Suicide Prevention.

Authors:  Ramit Sawhney; Harshit Joshi; Alicia Nobles; Rajiv Ratn Shah
Journal:  Proc Int AAAI Conf Weblogs Soc Media       Date:  2021-05-22

3.  Robust suicide risk assessment on social media via deep adversarial learning.

Authors:  Ramit Sawhney; Harshit Joshi; Saumya Gandhi; Di Jin; Rajiv Ratn Shah
Journal:  J Am Med Inform Assoc       Date:  2021-07-14       Impact factor: 4.497

4.  Suicide Risk and Protective Factors in Online Support Forum Posts: Annotation Scheme Development and Validation Study.

Authors:  Stevie Chancellor; Steven A Sumner; Corinne David-Ferdon; Tahirah Ahmad; Munmun De Choudhury
Journal:  JMIR Ment Health       Date:  2021-11-08

Review 5.  Ethics and Law in Research on Algorithmic and Data-Driven Technology in Mental Health Care: Scoping Review.

Authors:  Piers Gooding; Timothy Kariotis
Journal:  JMIR Ment Health       Date:  2021-06-10

Review 6.  Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review.

Authors:  Onur Asan; Avishek Choudhury
Journal:  JMIR Hum Factors       Date:  2021-06-18

7.  Can acute suicidality be predicted by Instagram data? Results from qualitative and quantitative language analyses.

Authors:  Rebecca C Brown; Eileen Bendig; Tin Fischer; A David Goldwich; Harald Baumeister; Paul L Plener
Journal:  PLoS One       Date:  2019-09-10       Impact factor: 3.240

8.  A Framework for Applying Natural Language Processing in Digital Health Interventions.

Authors:  Burkhardt Funk; Shiri Sadeh-Sharvit; Ellen E Fitzsimmons-Craft; Mickey Todd Trockel; Grace E Monterubio; Neha J Goel; Katherine N Balantekin; Dawn M Eichen; Rachael E Flatt; Marie-Laure Firebaugh; Corinna Jacobi; Andrea K Graham; Mark Hoogendoorn; Denise E Wilfley; C Barr Taylor
Journal:  J Med Internet Res       Date:  2020-02-19       Impact factor: 5.428

  8 in total

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