Evidence map›Paper›PMID 31522256›Full record

ReviewCurrent psychiatry reports2019

Fatal and Non-fatal Self-Injury in the USA: Critical Review of Current Trends and Innovations in Prevention.

Gonzalo Martínez-Alés, Katherine M Keyes

Abstract readReview
In one paragraph

Review in Current psychiatry reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

2 authors.

Gonzalo Martínez-AlésColumbia Mailman School of Public Health, 722W 168th St, Suite 1030, New York, NY, 10032, USA. gm2792@cumc.columbia.edu.
Katherine M KeyesColumbia Mailman School of Public Health, 722W 168th St, Suite 1030, New York, NY, 10032, USA.

Funding

Suicide as a contagion: modeling and forecasting emergent outbreaksR01MH121410 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI KEYES, KATHERINE M., SHAMAN, JEFFREY L · 2020 to 2024
$3.2M
NIMH NIH HHS R01 MH121410
6 · The paper itself

Abstract

purpose of reviewTo examine current trends in suicide and self-injury in the USA, as well as potential contributors to their change over time, and to reflect on innovations in prevention and intervention that can guide policies and programs to reduce the burden of suicide and self-injury in the USA. RECENT

findingsSuicide and non-fatal self-injury are on the rise in the USA. Reasons for such trends over time remain speculative, although they seem linked to coincident increases in mood disorders and drug use and overdose. Promising innovative prevention and intervention programs that engage new technologies, such as machine learning-derived prediction tools and computerized ecologic momentary assessments, are currently in development and require additional evidence. Recent increases in fatal and non-fatal self-harm in the USA raise questions about the causes, interventions, and preventive measures that should be taken. Most innovative prevention efforts target individuals seeking to improve risk prediction and access to evidence-based care. However, as Durkheim pointed out over 100 years ago, suicide rates vary enormously between societal groups, suggesting that certain causal factors of suicide act and, hence, should be targeted at an ecological level. In the next generation of suicide research, it is critical to examine factors beyond the proximal and clinical to allow for a reimagining of prevention that is life course and socially focused.

Indexed as

Suicide PreventionDrug OverdoseHumansMachine LearningMood DisordersSelf-Injurious BehaviorSubstance-Related DisordersSuicideUnited StatesBrief contact interventionsEcologic momentary assessmentMachine learningMultilevel epidemiologySuicide predictionSuicide prevention

Identifiers

PMID31522256
PMCPMC7027360

What OpenQuestion holds

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Registered trials

None linked

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.