Polyvictimization and Cybervictimization Among College Students From France: The Mediation Role of Psychological Distress and Resilience
Bibliographic record
Abstract
Few studies have explored potential associations between polyvictimization and cybervictimization and even fewer have involved in college-age sample. As it has been shown in the literature, polyvictimization is associated with higher psychological distress and lower resilience. This study is aimed to model the association between polyvictimization and cybervictimization by testing the mediating role of psychological distress and resilience. The sample included 4,626 undergraduates from France. Participants completed questionnaires assessing cybervictimization, polyvictimization (emotional abuse from parents, exposure to interparental violence, parental neglect, unwanted sexual touching, and unwanted sexual intercourse), psychological distress, and resilience. Results show that each form of victimization considered was significantly associated with cybervictimization. Also, polyvictimized participants presented higher prevalence of cybervictimization. The association between polyvictimization and cybervictimization was partially mediated positively by psychological distress and negatively by resilience. In fact, more cybervictimization was observed among polyvictimized participants with a high score of psychological distress, whereas fewer cybervictimization was observed in those with a high score of resilience. This study provides a new understanding of the mechanisms involved in cybervictimization that can help to better prevent and intervene with victims. Our results suggest that mental health professionals should assess childhood experiences of victimization when they are working with cybervictims. They also suggest the need for mental health professionals to help both polyvictimized and cybervictimized youth to develop resilience skills and coping strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".