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Record W4405035408 · doi:10.1016/j.jad.2024.12.009

Cognitive control impairment in suicide behaviors: what do we know? A systematic review and meta-analysis of Stroop in suicide behaviors

2024· review· en· W4405035408 on OpenAlexafffund
Stéphane Richard‐Devantoy, Ayla Inja, Marina Dicker, Josie‐Anne Bertrand, Gustavo Turecki, Massimiliano Orri, John G. Keilp

Bibliographic record

VenueJournal of Affective Disorders · 2024
Typereview
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsComputer Research Institute of MontréalDouglas CollegeMcGill UniversityDouglas Mental Health University Institute
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchCanada Research ChairsMcGill UniversityAmerican Foundation for Suicide Prevention
KeywordsStroop effectPsychologyCognitionPoison controlMoodNeuropsychologyCognitive vulnerabilityClinical psychologyPopulationVulnerability (computing)Injury preventionPsychiatryMedicineMedical emergency

Abstract

fetched live from OpenAlex

BACKGROUND: Suicidal behavior results from a complex interplay between stressful events and vulnerability factors, including cognitive deficits. Poorer performance on the Stroop task, a measure of cognitive control, has been associated with suicidal behavior in numerous studies. The objective was to conduct an updated systematic review of the literature on the Stroop task as a neuropsychological test of vulnerability to suicidal acts in patients with mood and other psychiatric disorders, while also looking at how the type (classic versus emotional) or the version (paper or computerized) of the Stroop task, as well as the characteristics of the patient (clinical population, age, sex) moderated the Stroop effect. METHODS: A search on Medline, Embase, PsycInfo databases, and article references was performed. 53 studies (6781 participants) met the selection criteria. Interference time and errors of the Stroop Test were assessed in at least 3 studies to be analyzed. Moderators, such as the type (classic versus emotional) of the Stroop task and the characteristics of the patient (clinical population, age, sex) were also assessed. RESULTS: Interference time on Stroop performance was lower in suicide attempters than in patient controls (g = 0.20; 95%CI [0.10-0.30]) and healthy controls (g = 0.79; 95 % CI [0.29-1.29]), with patient controls scoring lower than healthy controls (g = -0.63; 95%CI [-1.01-0.25]). This was moderated by age and having a mood disorder. In terms of interference errors, suicide attempters performed worse than healthy controls (g = 0.57; 95%CI [0.01-1.15]) but did not perform differently from patient controls (g = 0.20; 95 % CI [-0.06-0.45]). Patient controls also did not score differently than healthy controls (g = -0.18; 95 % CI [-0.54-0.18]). There was a significant moderation effect for the type (i.e., original Stroop task) and version (i.e., paper format) of the Stroop task, and for some characteristics of the patient (i.e., older patients and having a mood disorder). CONCLUSIONS: Cognitive control impairment was associated with a history of suicidal behavior in patients, especially in older populations and those with mood disorders, however this result was moderated by outcome measure (interference time vs. errors), the type (i.e., original Stroop task) and the version (i.e., paper format) of the Stroop task. Cognitive control processes may be an important factor of suicidal vulnerability. Choosing the right neurocognitive test in the right population to detect suicide vulnerability is important direction for future research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.025
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.018
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.057
GPT teacher head0.414
Teacher spread0.358 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes2
Has abstractno

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