Evidence map›Paper›PMID 38700375›Full record

ArticleSuicide & life-threatening behavior2024

Do people know how suicidal they will be? Understanding suicidal prospection.

Daniel D L Coppersmith, Adam C Jaroszewski, Samuel J Gershman, Christine B Cha, Alexander J Millner, Rebecca G Fortgang, Evan M Kleiman, Matthew K Nock

Abstract read
In one paragraph

Article in Suicide & life-threatening behavior, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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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

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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

1 citing paper in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Daniel D L CoppersmithDepartment of Psychology, Harvard University, Cambridge, Massachusetts, USA.ORCID 0000-0002-9397-3228
Adam C JaroszewskiDepartment of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA.
Samuel J GershmanDepartment of Psychology, Harvard University, Cambridge, Massachusetts, USA.
Christine B ChaCounseling & Clinical Psychology Department, Teachers College, Columbia University, New York, New York, USA.
Alexander J MillnerDepartment of Psychology, Harvard University, Cambridge, Massachusetts, USA.ORCID 0000-0001-6092-2857
Rebecca G FortgangDepartment of Psychology, Harvard University, Cambridge, Massachusetts, USA.
Evan M KleimanDepartment of Psychology, Rutgers University, New Brunswick, New Jersey, USA.
Matthew K NockDepartment of Psychology, Harvard University, Cambridge, Massachusetts, USA.

Funding

Capturing the Structure and Dynamics of Suicidal ThinkingF31MH130055 · NIMH · HARVARD UNIVERSITY · PI COPPERSMITH, DANIEL · 2022 to 2023
$65k
National Science Foundation DGE-1745303NIMH NIH HHS F31 MH130055NIMH NIH HHS F31MH130055
6 · The paper itself

Abstract

introductionLittle research has been done on how people mentally simulate future suicidal thoughts and urges, a process we term suicidal prospection.

methodsParticipants were 94 adults with recent suicidal thoughts. Participants completed a 42-day real-time monitoring study and then a follow-up survey 28 days later. Each night, participants provided predictions for the severity of their suicidal thoughts the next day and ratings of the severity of suicidal thoughts over the past day. We measured three aspects of suicidal prospection: predicted levels of desire to kill self, urge to kill self, and intent to kill self. We generated prediction errors by subtracting participants' predictions of the severity of their suicidal thoughts from their experienced severity.

resultsParticipants tended to overestimate (although the average magnitude was small and the modal error was zero) the severity of their future suicidal thoughts. The best fitting models suggested that participants used both their current suicidal thinking and previous predictions of their suicidal thinking to generate predictions of their future suicidal thinking. Finally, the average severity of predicted future suicidal thoughts predicted the number of days participants thought about suicide during the follow-up period.

conclusionsThis study highlights prospection as a psychological process to better understand suicidal thoughts and behaviors.

Indexed as

Suicidal IdeationAdultFemaleHumansMaleYoung Adultprospectionsuicidal ideationsuicide

Identifiers

PMID38700375
PMCPMC11305949

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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.