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Record W3011224736 · doi:10.1007/s11469-020-00259-3

Impulsivity and Impulsivity-Related Endophenotypes in Suicidal Patients with Substance Use Disorders: an Exploratory Study

2020· article· en· W3011224736 on OpenAlexaff
Alessandra Costanza, Stéphane Rothen, Sophia Achab, Gabriel Thorens, Marc Baertschi, Kerstin Weber, Alessandra Canuto, Hélène Richard-Lepouriel, Nader Perroud, Daniele Zullino

Bibliographic record

VenueInternational Journal of Mental Health and Addiction · 2020
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsImpulsivityEndophenotypePsychologyClinical psychologyAggressionAngerPsychiatryCannabisTraitPoison controlSuicidal ideationSubstance abuseHealth psychologyInjury preventionMedicinePublic healthCognitionMedical emergency

Abstract

fetched live from OpenAlex

Abstract Suicidal behavior (SB) is a major problem in patients with substance use disorders (SUDs). However, little is known about specific SB risk factors in this population, and pathogenetic hypotheses are difficult to disentangle. This study investigated some SB and SUD-related endophenotypes, such as impulsivity, aggression, trait anger, and risk-taking behaviors (RTBs), in forty-eight patients with SUDs in relation to lifetime history of suicide attempts (SAs). Disorders related to alcohol, cannabis, cocaine, opiates, and hallucinogenic drugs were included. Lifetime SAs was significantly associated with both higher impulsivity and higher aggression, but not with trait anger. A higher number of RTBs were associated with lifetime SAs and higher impulsivity, but not with aggression and trait anger. Assessing these endophenotypes could refine clinical SB risk evaluation in SUDs patients by detecting higher-risk subgroups. An important limitation of this study is exiguity of its sample size. Its primary contribution is inclusion of all SUD types.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.307
Teacher spread0.285 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations63
Published2020
Admission routes1
Has abstractyes

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