Evidence map›Paper›PMID 37588775›Full record

ArticleNature reviews psychology2023

The use of advanced technology and statistical methods to predict and prevent suicide.

Evan M Kleiman, Catherine R Glenn, Richard T Liu

Open access · greenAbstract read
In one paragraph

Article in Nature reviews psychology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
14.7field-weighted citation impact, top 1% of its field
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

30 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
  2. Article
  3. Predicting Next-Day Passive Suicidal Ideation in At-Risk Youth.Suicide & life-threatening behavior · 2026
    Article
  4. Review
  5. Article
  6. Understanding sleep and smartphone use in diverse adolescents through passive digital monitoring.Journal of research on adolescence : the official journal of the Society for Research on Adolescence · 2026
    Article
  7. Article
  8. Observational
  9. Article
  10. Article
  11. Article
  12. Longitudinal User Engagement with Microinteraction Ecological Momentary Assessment (μEMA).Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2025
    Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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 at 3 institutions in 1 country.

Evan M KleimanDepartment of Psychology, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.ORCID 0000-0001-8002-1167
Catherine R GlennDepartment of Psychology, Old Dominion University, Norfolk, VA, USA.ORCID 0000-0003-2497-6000
Richard T LiuDepartment of Psychiatry, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-1367-9716
Harvard University · USOld Dominion University · USRutgers, The State University of New Jersey · US

Funding

Clarifying proximal mechanisms linking interpersonal stressors to suicidal behavior in youth: A multi-informant real-time monitoring studyR01MH124899 · NIMH · RUTGERS, THE STATE UNIV OF N.J. · PI GLENN, CATHERINE ROSE, KLEIMAN, EVAN · 2021 to 2025
$2.9M
NIMH NIH HHS R01 MH124899
6 · The paper itself

Abstract

In the past decade, two themes have emerged across suicide research. First, according to meta-analyses, the ability to predict and prevent suicidal thoughts and behaviours is weaker than would be expected for the size of the field. Second, review and commentary papers propose that technological and statistical methods (such as smartphones, wearables, digital phenotyping and machine learning) might become solutions to this problem. In this Review, we aim to strike a balance between the pessimistic picture presented by these meta-analyses and the optimistic picture presented by review and commentary papers about the promise of advanced technological and statistical methods to improve the ability to understand, predict and prevent suicide. We divide our discussion into two broad categories. First, we discuss the research aimed at assessment, with the goal of better understanding or more accurately predicting suicidal thoughts and behaviours. Second, we discuss the literature that focuses on prevention of suicidal thoughts and behaviours. Ecological momentary assessment, wearables and other technological and statistical advances hold great promise for predicting and preventing suicide, but there is much yet to do.

Identifiers

PMID37588775
PMCPMC10426769
OpenAlexW4362663179

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.