Understanding the Experiences and Impact in Intimate Partners of Psychopathic Individuals
Bibliographic record
Abstract
Psychopathic individuals comprise approximately 1% of the population and display maladaptive personality traits that have significant negative impacts on society. Intimate partner violence (IPV) perpetrated by individuals with psychopathic traits has been documented to be severe, versatile, and result in substantial harm to survivors. This study builds on previous findings that examine key constructs such as harms due to abuse, distress, coping, social support and posttraumatic growth. In Study 1, a scale to measure financial harm (Financial Harm Inventory; FHI) was developed and psychometrically validated in a mixed sample of current and former partners of psychopathic individuals, as well as those with friends, family or acquaintances of individuals with psychopathic traits (n = 827). The finalized 12-item scale demonstrated a unidimensional structure, with good reliability (α =.93) and excellent ability to discriminate across levels of the latent trait. The FHI demonstrated good convergent validity with measures of psychological harm (r = .32 - .35), while discriminant validity demonstrated mixed results. Study 2 surveyed respondents (n = 542) who self-identified as having previously been in a relationship with an intimate partner who has psychopathic traits. Participants reported high levels of emotional, sexual, financial, and physical harm in their relationship as well as high levels of depression, trauma symptoms and anxiety. Relationships between psychopathy, distress, coping, social support were structurally modelled. The majority of the hypothesized relationships were supported. Unexpected findings suggest ways that coping may impact distress and experiences of posttraumatic growth. Study 3 sought to better understand the experiences of survivors in a qualitative study using the Enhanced Critical Incident Technique (ECIT). Interviews (n = 15) were conducted with individuals who self-identified as being in a romantic relationship with a partner who had psychopathic traits. Themes included harmful aspects of the relationship (16 themes) and helpful or positive aspects of the relationship (11 themes). Participants also shared what resources wished they had available to them during their abusive relationship (4 themes). Themes supported previous findings of extensive harm due to the psychopathic traits of the partners and uncovered aspects of intimate partner relationships that have not been previously examined.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".