Literature DB >> 26219609

Are There Linguistic Markers of Suicidal Writing That Can Predict the Course of Treatment? A Repeated Measures Longitudinal Analysis.

Mira Brancu, David Jobes, Barry M Wagner, Jeffrey A Greene, Timothy A Fratto.   

Abstract

The purpose of this pilot study was to predict resolution of suicidal ideation and risk over the course of therapy among suicidal outpatients (N = 144) using a novel method for analyzing Self- verses Relationally oriented qualitative written responses to the Suicide Status Form (SSF). A content analysis software program was used to extract word counts and a repeated measures longitudinal design was implemented to assess improvement over time. Patients with primarily Relationally focused word counts were more likely to have a quicker suicide risk resolution than those with more Self-focused word counts (6-7 sessions versus 17-18 sessions). Implications of these data are discussed, including the potential for enhancing treatment outcomes using this method with individuals entering treatment.

Entities:  

Keywords:  linguistic markers; longitudinal; predictors; qualitative; suicide risk

Mesh:

Year:  2015        PMID: 26219609     DOI: 10.1080/13811118.2015.1040935

Source DB:  PubMed          Journal:  Arch Suicide Res        ISSN: 1381-1118


  4 in total

1.  What Do You Say Before You Relapse? How Language Use in a Peer-to-peer Online Discussion Forum Predicts Risky Drinking among Those in Recovery.

Authors:  Rachel Kornfield; Catalina L Toma; Dhavan V Shah; Tae Joon Moon; David H Gustafson
Journal:  Health Commun       Date:  2017-08-09

2.  A Randomized Controlled Trial of the Collaborative Assessment and Management of Suicidality (CAMS) Versus Treatment as Usual (TAU) for Suicidal College Students.

Authors:  Jacqueline Pistorello; David A Jobes; Robert Gallop; Scott N Compton; Nadia Samad Locey; Josephine S Au; Samantha K Noose; Joseph C Walloch; Jacquelyn Johnson; Maria Young; Yani Dickens; Patricia Chatham; Tami Jeffcoat
Journal:  Arch Suicide Res       Date:  2020-04-10

3.  Psycholinguistic changes in the communication of adolescent users in a suicidal ideation online community during the COVID-19 pandemic.

Authors:  Johannes Feldhege; Markus Wolf; Markus Moessner; Stephanie Bauer
Journal:  Eur Child Adolesc Psychiatry       Date:  2022-08-26       Impact factor: 5.349

4.  Detecting Recovery Problems Just in Time: Application of Automated Linguistic Analysis and Supervised Machine Learning to an Online Substance Abuse Forum.

Authors:  Rachel Kornfield; Prathusha K Sarma; Dhavan V Shah; Fiona McTavish; Gina Landucci; Klaren Pe-Romashko; David H Gustafson
Journal:  J Med Internet Res       Date:  2018-06-12       Impact factor: 5.428

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.