Evidence map›Paper›PMID 36239594›Full record

ArticleThe Australian and New Zealand journal of psychiatry2023

Association of 7 million+ tweets featuring suicide-related content with daily calls to the Suicide Prevention Lifeline and with suicides, United States, 2016-2018.

Thomas Niederkrotenthaler, Ulrich S Tran, Hubert Baginski, Mark Sinyor, Markus J Strauss, Steven A Sumner, Martin Voracek, Benedikt Till, Sean Murphy, Frances Gonzalez and 4 more

Abstract read
In one paragraph

Article in The Australian and New Zealand journal of psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Thomas NiederkrotenthalerUnit Suicide Research & Mental Health Promotion, Department of Social and Preventive Medicine, Center for Public Health, Medical University of Vienna, Vienna, Austria.ORCID 0000-0001-9550-628X
Ulrich S TranWiener Werkstaette for Suicide Research, Vienna, Austria.ORCID 0000-0002-6589-3167
Hubert BaginskiComplexity Science Hub Vienna, Vienna, Austria.ORCID 0000-0002-8731-113X
Mark SinyorDepartment of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.ORCID 0000-0002-7756-2584
Markus J StraussUnit Suicide Research & Mental Health Promotion, Department of Social and Preventive Medicine, Center for Public Health, Medical University of Vienna, Vienna, Austria.
Steven A SumnerCenters for Disease Control and Prevention (CDC), National Center for Injury Prevention and Control, Atlanta, GA, USA.
Martin VoracekWiener Werkstaette for Suicide Research, Vienna, Austria.
Benedikt TillUnit Suicide Research & Mental Health Promotion, Department of Social and Preventive Medicine, Center for Public Health, Medical University of Vienna, Vienna, Austria.
Sean MurphyVibrant Emotional Health, National Suicide Prevention Lifeline, New York, NY, USA.
Frances GonzalezVibrant Emotional Health, National Suicide Prevention Lifeline, New York, NY, USA.
Madelyn GouldDepartments of Psychiatry and Epidemiology, Columbia University Irving Medical Center, New York State Psychiatric Institute, New York, NY, USA.
David GarciaComplexity Science Hub Vienna, Vienna, Austria.
John DraperVibrant Emotional Health, National Suicide Prevention Lifeline, New York, NY, USA.
Hannah MetzlerUnit Suicide Research & Mental Health Promotion, Department of Social and Preventive Medicine, Center for Public Health, Medical University of Vienna, Vienna, Austria.

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

objectiveThe aim of this study was to assess associations of various content areas of Twitter posts with help-seeking from the US National Suicide Prevention Lifeline (Lifeline) and with suicides.

methodsWe retrieved 7,150,610 suicide-related tweets geolocated to the United States and posted between 1 January 2016 and 31 December 2018. Using a specially devised machine-learning approach, we categorized posts into content about prevention, suicide awareness, personal suicidal ideation without coping, personal coping and recovery, suicide cases and other. We then applied seasonal autoregressive integrated moving average analyses to assess associations of tweet categories with daily calls to the US National Suicide Prevention Lifeline (Lifeline) and suicides on the same day. We hypothesized that coping-related and prevention-related tweets are associated with greater help-seeking and potentially fewer suicides.

resultsThe percentage of posts per category was 15.4% (standard deviation: 7.6%) for awareness, 13.8% (standard deviation: 9.4%) for prevention, 12.3% (standard deviation: 9.1%) for suicide cases, 2.4% (standard deviation: 2.1%) for suicidal ideation without coping and 0.8% (standard deviation: 1.7%) for coping posts. Tweets about prevention were positively associated with Lifeline calls (

conclusionThis is the first large-scale study to suggest that daily volume of specific suicide-prevention-related social media content on Twitter corresponds to higher daily levels of help-seeking behaviour and lower daily number of suicide deaths. PREREGISTRATION: As Predicted, #66922, 26 May 2021.

Indexed as

Social MediaSuicideData CollectionHumansSuicidal IdeationSuicide PreventionUnited Stateshelp-seekinginterrupted time seriesmedia effectsPapageno effectsocial mediasuicidesuicide preventionTwitterUnited States

Identifiers

PMID36239594
PMCPMC10947496

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.