Social Web Mining for Suicide Prevention

According to a recent and alarming WHO (World Health Organisation) report (September 4, 2014), one person dies of suicide every 40 seconds in the world. Suicide is the third-leading cause of death for 15- to 24-year-olds, according to the Centers for Disease Control and Prevention , after accidents and homicide.

This major public health issue need prevention strategies especially directed to at-risk populations. Since 2013, more than 2 billion users are enrolled in social networks such as Twitter or Facebook. Young adults (ages 18 to 29) are the most likely to use social media - fully 90% do.

Consequently, in this project, we focus on suicide prevention in social media network..

The aim of this project is the validation of the algorithm. This algorithm build a decision support system that monitor young people at-risk based on large volume of heterogeneous data collected through social media to improve suicide prevention.

Completed

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Key information

Conditions

Suicidal Behaviors Behavior Behavioral Symptoms Self-Injurious Behavior Suicide

Age range

15 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Uhmontpellier

Montpellier, 34295, France

About this study

This study is composed of two steps :

9 subjects were recruited. After patients agreement, computer scientists were accessing to patient social network profile. Computer scientists were not able to visualize the content of publications, just run the algorithm that will analyse the content of messages (text, frequency, emoticons…)

The algorithm defines the 3 most at-risk periods of suicide behaviors, on the next month. This result were compared to periods found by psychiatric interview. The psychiatrist then confirmed or not to LIRM whether periods found by the algorithm conrrespond to those defined by the psychitrist. No data of the social network were collected.

the 2nd step aim to improve the algorithm by collecting sociodemographic and clincal data related to patients included.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Major patient
Minor patient with parents approval
Patient hospitalized due to suicide attempt or suicide ideations
Frequent active user of social netword (Facebook, Instagram, Youtube, Twitter)

Exclusion criteria

Patient's refusal to participate

Treatment and study plan

Primary outcomes

sensitivity of the algorithm

Time frame: 1 day

baseline

Sponsors and collaborators

Lead sponsor

University Hospital, Montpellier

Other

Collaborators

LIRMM - Montpellier - France

Registry information

Official study title

Social Web Mining for Suicide Prevention of Young People

Acronym: Don't Do It

Important dates

Study start: 2017
Primary completion: 2017
Study completion: 2020
First posted: Aug 9, 2019
Registry last updated: Sep 2, 2021

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Completed