Coercive Control and Intimate Partner Violence: Relationship With Personality Disorder Severity and Pathological Narcissism
Bibliographic record
Abstract
Intimate partner violence (IPV) is a global health concern, with increasing efforts focused on detection and prevention. Coercive control has been identified as a 'golden thread' linking risk profiles and violence perpetration. Narcissistic pathology is often implicated in control and violence, but research linking narcissism with aggression and abuse has been inconsistent. Most research on narcissism focuses on symptomatology, whereas contemporary diagnostic frameworks emphasise a dimensional approach to personality disorder 'severity'. No study has examined the association between pathological narcissism, violence and coercive control while accounting for overall personality pathology. Individuals in relationships with relatives high in narcissism (N = 135; 71% romantic partners, 22% family members; average relationship length = 20 years) completed informant measures of pathological narcissism and personality disorder severity, as well as self-report measures of abuse and coercive control. Relatives were rated highly in both grandiose and vulnerable narcissism features, as well as displaying prominent impairments in personality functioning. Correlation analysis indicated dimensional personality disorder severity was significantly and moderately associated with both abuse and coercive control. Pathological narcissism was significantly associated with coercive control but not abuse. Specific narcissism subfactors (exploitativeness, grandiose fantasy and entitlement rage) showed positive, weak associations with either coercive control or abuse. Within the context of high narcissistic symptomatology, personality disorder severity may be a risk factor for coercive control and IPV. Clinical implications suggest the relevance of incorporating a focus on personality in psychological interventions targeted at reducing IPV and coercive control.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".