Is romantic partner betrayal a form of traumatic experience? A qualitative study
Bibliographic record
Abstract
According to a growing body of research, betrayal by a romantic partner is increasingly considered as a form of interpersonal trauma. Between 30% and 60% of betrayed individuals experience symptoms of post-traumatic stress disorder (PTSD), depression and anxiety to clinically meaningful levels. From a clinical perspective, this constellation of symptoms can be conceptualized as a stressor-related adjustment disorder. Yet, no qualitative research has examined the association between romantic betrayal and traumatic stress from the perspective of betrayed individuals. Face-to-face semi-structured interviews were conducted with 13 participants who had completed a clinical trial for a new treatment for adjustment disorder stemming from betrayal. Data were analysed using thematic content analysis. Although betrayal was experienced as a shocking and destabilizing event, and participants used trauma or 'feeling traumatized' as a metaphor to describe their experience, few had constructed their reaction as traumatic stress. In fact, participants reported experiencing difficulties understanding the intensity of their experience. However, when exposed to external sources (e.g., books and interviews by psychologists and researchers) that used a trauma and PTSD framework to explain the effects of betrayal, participants reported feeling clarity, validation and relief. Findings are discussed in the light of theoretical and clinical implications.
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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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".