Quality of life and social support in relation to trauma and posttraumatic stress disorder
Bibliographic record
Abstract
Research in the areas of quality of life and social support suggests a complex relationship with trauma. Most studies have found inverse relationships between both quality of life and social support posttrauma. However, it remains unclear how these findings apply to individuals with a current or past diagnosis of posttraumatic stress disorder (PTSD), or to individuals who do not meet the criteria for PTSD. Furthermore, previous research has been limited to global index outcomes, which overlook specific domains that could reveal more information, obtained from convenience samples. We seek here to address these limitations by analysing data from a large community-based epidemiological catchment area study conducted in the south west of Montreal (N = 2399) broken down according to current PTSD diagnostic status: (i) Current PTSD, (ii) Past PTSD, (iii) No lifetime PTSD in spite of trauma exposure, and (iv) No lifetime trauma exposure. The inverse relationship of decreased quality of life posttrauma, specifically as PTSD severity increases, was replicated within our sample. In contrast to many previous studies, we show that social support was not significantly different between PTSD and No PTSD groups. Subscale scores were examined in depth for both quality of life and social support, with outcomes showing that even after PTSD remits, the gap between PTSD and No PTSD groups widens. This research allows for a much needed broadening of our understanding of quality of life for individuals with current and remitted PTSD.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".