Understanding Social Factors in the Context of Trauma: Implications for Measurement and Intervention
Bibliographic record
Abstract
One of the most important factors predicting the presence of posttraumatic stress disorder (PTSD) after trauma exposure is social support, yet the construct is theoretically complex and remains variably defined. To better inform the trauma literature on the impact of social factors, a theoretical review of social support and PTSD was conducted, and implications for measurement and intervention are outlined. Type of trauma, sex of participant, timing of social support, and support providers are described as significant moderators of the association between social factors and PTSD. The developmental trajectory of the association between social factors and PTSD occurrence is outlined, emphasizing the positive influence of social support initially following trauma, and the deterioration effect of PTSD symptoms on social support over the longer term. Possibilities for future research and intervention at multiple levels and at different time points are described.
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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 | 0.044 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".