Trajectories of Depression, Post-Traumatic Stress, and Chronic Pain Among Women Who Have Separated From an Abusive Partner: A Longitudinal Analysis
Bibliographic record
Abstract
This longitudinal study explored changes in women's health after separation from an abusive partner by characterizing the trajectories of their mental health (depression and post-traumatic stress disorder [PTSD]) and physical health (chronic pain) over a 4-year period. We examined how the severity of intimate partner violence (IPV) affected these trajectories, controlling for selected baseline factors using 5 waves of data collected from a community sample of 309 English-speaking, Canadian women. IPV severity was measured using the Index of Spouse Abuse where women were asked to consider the entire period of their partner relationship up to present at wave 1 and to rate their IPV experiences in the previous 12 months at waves 2-5. Mental health was measured using established self-report measures of depression (CESD) and PTSD (Davidson Trauma Scale), while chronic pain was measured using the Chronic Pain Grade Scale. Trajectories were estimated using MLM techniques with severity of IPV and selected co-variates (time since separation, age, financial strain) included. Our results show that women's health improved significantly over time, although significant levels of depression, PTSD symptoms and disabling chronic pain remained at the end of wave 5. Regardless of time since separation, more severe IPV was associated with higher levels of depression, PTSD, and disabling chronic pain, with IPV having a stronger effect on these health outcomes over time, suggesting cumulative effects of IPV on health. The results of this study contribute to quantifying the continuing mental and physical health burdens experienced by women after separation from an abusive partner. Increased attention to the long-term effects of violence on women's health beyond the crisis of leaving is critically needed to strengthen health and social services and better support women's recovery and healing.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.132 | 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".