Using Eye Movement Desensitization and Reprocessing (EMDR) and Compassion-Focused Therapy (CFT) to Support Persons Experiencing Intimate Partner Violence
Bibliographic record
Abstract
A high prevalence of intimate partner violence (IPV) amongst individuals in Canada, a variety of mental health consequences, and lower quality of life requires a need for effective treatments. This research aims to explore how EMDR and compassion-focused therapy (CFT) together can support and treat individuals who have experienced IPV. A literature review is conducted to examine current and past literature examining the effectiveness of EMDR and CFT for individuals who have experienced IPV. Findings from the literature review show that EMDR is helpful in treating PTSD symptoms and that CFT is helpful in treating components of PTSD and shame in those who have suffered from IPV. A framework is proposed that integrates both compassion- focused and EMDR principles into a single model aimed at treating IPV by targeting PTSD symptoms through EMDR and utilizing a compassion-focused lens and techniques to target shame and guilt. By targeting these two areas, EMDR along with CFT could help in reducing mental health issues after IPV and may increase quality of life.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".