Evidence map›Paper›PMID 30206093›Full record

ArticleBMJ open2018

Features for medically serious suicide attempters who do not have a strong intent to die: a cross-sectional study in rural China.

Long Sun, Jie Zhang, Dorian A Lamis

Abstract read
In one paragraph

Article in BMJ open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 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

3 authors.

Long SunCenter for Suicide Prevention Research, School of Public Health, Shandong University, Jinan, China.ORCID 0000-0002-3070-8427
Jie ZhangCenter for Suicide Prevention Research, School of Public Health, Shandong University, Jinan, China.
Dorian A LamisDepartment of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia, USA.

Funding

Culture, Risk Factors and Suicide Attempt in Rural ChinaR01MH068560 · NIMH · RESEARCH FOUNDATION OF SUNY AT BUFFALO STATE COLLEGE · PI ZHANG, JIE · 2005 to 2013
$2.0M
NIMH NIH HHS R01 MH068560
6 · The paper itself

Abstract

objectivePrevious studies have implied that there were many Chinese suicide attempters who did not want to die by suicide. In the current study, we explored the factors which were associated with low levels of suicide intent. We also examined features for medically serious suicide attempters who do not have a strong intent to die in rural china.

designCross-sectional study.

settingThe interviews occurred between May 2012 and July 2013 in 13 rural counties in Shandong and Hunan provinces, China.

participantsSubjects were 791 medically serious suicide attempters whose injury and wounds were so serious they required hospitalisation or immediate medical care.

resultsThe results supported that less years of education (β=-0.11, p=0.037), religious beliefs (β=1.20, p=0.005), living alone (β=1.92, p=0.017), negative life events (β=0.29, p=0.003), low levels of impulsivity (β=-0.10, p=0.013) and mental disorders (β=2.82, p<0.001) were associated with higher levels of suicide intent.

conclusionResults imply that there are some medically serious suicide attempters with a higher education and/or exhibit impulsivity who do not want to die by suicide. These findings can inform practice to prevent suicide in rural China.

Indexed as

Mental DisordersSuicidal IdeationSuicide, AttemptedSurvivorsWounds and InjuriesAdultChinaCross-Sectional StudiesFemaleHumansImpulsive BehaviorIntentionMaleRisk FactorsRural PopulationSocioeconomic Factorsmedically serious suiciderural Chinasuicide attempterssuicide intent

Identifiers

PMID30206093
PMCPMC6144317

What OpenQuestion holds

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LicenceCC BY
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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.