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

ABSTRACT:

Background

Online communities provide support for individuals looking for help with suicidal ideation and crisis. As community data are increasingly used to devise machine learning models to infer who might be at risk, there have been limited efforts to identify both risk and protective factors in web-based posts. These annotations can enrich and augment computational assessment approaches to identify appropriate intervention points, which are useful to public health professionals and suicide prevention researchers.

Objective

This qualitative study aims to develop a valid and reliable annotation scheme for evaluating risk and protective factors for suicidal ideation in posts in suicide crisis forums.

Methods

We designed a valid, reliable, and clinically grounded proce

SUBMITTER: Chancellor S 

PROVIDER: S-EPMC8663675 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature