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Record W7162003148 · doi:10.82308/44904

Impulsivity in men and women: A general population study in the Southwest of Montreal

2012· dissertation· en· W7162003148 on OpenAlexaboutno aff
Andrea Reyes Ayllon

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsImpulsivityBarratt Impulsiveness ScalePopulationAggressionMental healthSocioeconomic statusPersonalityPoison controlLogistic regression

Abstract

fetched live from OpenAlex

Impulsivity is considered a major contributor to various antisocial behaviours (Nofziger, 2010) and is present in many mental and personality disorders (American Psychiatric Association, 2000). Given that clear sex differences have been observed in such behaviours and disorders (Nofziger, 2010; Struber, et al., 2008), it is of interest to explore whether similar sex differences are observed in impulsivity. This thesis explores sex differences in impulsivity and its sub factors, as well as the potential role of impulsivity in explaining sex differences in antisocial behaviours and affective disorders. Using the Barratt Impulsiveness Scale, 11a version (BIS-11a; Barratt, 1994), a self report measure of impulsivity, we compared men and women on their total BIS total scores and factor scores, and examined whether sex moderated the association between impulsivity and criminal justice involvement, aggression, substance dependence, depression and mania.The analyses were conducted using data gathered through a large Epidemiological Catchment Area study of mental health in Montreal, Canada. The sample was randomly selected among residents living in the southwest of the city and consisted of 2,419 participants, between the ages of 15 and 69. Each participant was administered a variety of assessment measures including the BIS-11a, the Composite International Diagnostic Interview, a self report version of the Modified Overt Aggression Scale and a self-report criminal justice involvement scale. One-way analyses of covariance revealed no sex differences in impulsivity, even after controlling for age and socioeconomic status. In terms of the factors of impulsivity, both careful planning and coping stability were marginally higher in men. Additionally, logistic regression analyses showed that impulsivity was a predictor of criminal justice involvement, aggression and substance dependence but not of depression and mania and that sex was predictive of criminality, self-aggression and substance dependence (both alcohol and drug) in the past twelve months. Sex, however did not moderate the relation between impulsivity and any of the other variables, as was originally anticipated. In conclusion, if men were more prone than women to engage in such behaviours, their propensity is probably due to other factors such as heightened opportunity to engage in antisocial behaviours. Alternatively, the BIS-11a might not measure all components of impulsivity such a sensation seeking trait which may be directly linked to sex differences in antisocial behaviours and affective disorders. Future studies should include additional measures of impulsivity in order to get a clearer picture of the role sex might play in the association between antisocial behaviours, affective disorders and impulsivity as a whole.This large scale epidemiological study is the first to our knowledge in North America to look at sex differences and similarities in the measurement of impulsivity as well as the correlates of the latter. This study will allow us to make inferences about the relation between impulsivity and sex in the general population.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.105
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.371
Teacher spread0.343 · 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 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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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