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Record W4413930128 · doi:10.1177/02762366251374186

Psychopathy and Mental Imagery: The Role of Imagery in Social Dominance, Callousness, and Impulsivity

2025· article· en· W4413930128 on OpenAlexaff
Roshni Sohail, Adelle E. Forth

Bibliographic record

VenueImagination Cognition and Personality · 2025
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsCarleton University
Fundersnot available
KeywordsPsychopathyPsychologyImpulsivityMental imageDominance (genetics)Cognitive psychologyDevelopmental psychologyPersonalitySocial psychologyCognitionPsychiatry

Abstract

fetched live from OpenAlex

An inability to see mental images may contribute to the development of psychopathic traits. This study examined the relationship between trait vividness of mental imagery, spontaneous use of imagery, and psychopathic traits in undergraduates ( N = 836, 80.6% female). Results did not support that psychopathy is associated with imagery deficits. Vividness positively predicted total psychopathy and Boldness, and spontaneous use of imagery negatively predicted Meanness. Mediations revealed less vivid imagery associated with more impulsivity and therefore increased psychopathic traits. Findings suggest the generation of vivid images fuels the socially dominant elements of psychopathy, whereas a lack of generating or using imagery facilitates callousness and limits opportunities for behavioral control. Findings support the use of imagery-based cognitive behavioral therapy interventions that target the disparities in the generation of vivid images that fuel maladaptive attitudes and behaviors, which be key in mitigating the instrumental and reactive behaviors seen in this 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 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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.011
GPT teacher head0.321
Teacher spread0.310 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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