Social support over time for men and women veterans with and without complex trauma histories.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Social support is closely linked to health, but little is known about United States (U.S.) veterans' social support over time and factors that may influence their support trajectories. This study investigates social support over time for U.S. men and women Post-9/11 veterans in relation to trauma history and gender. A secondary analysis of longitudinal cohort data from the Survey of Experiences of Returning Veterans (SERV), which employed a repeated-measures longitudinal design using five waves of data (baseline, 3, 6, 9, 12 months) with 672 combat veterans. Results from random intercept multilevel models found no significant gender differences in social support over time. Veterans with complex trauma histories were at risk for lower social support across waves. A stability trend was also observed; specifically, at baseline, veterans who started with high support maintained their level over time whereas veterans who started with deficits in social support remained low over time. Veterans identifying as African American or Latinx, and those with lower annual incomes, reported lower support compared to White and higher-income veterans. Furthermore, low social support was significantly associated with severe posttraumatic stress symptoms and active suicidal ideation across 12 months. SERV utilized a nonrandom sampling method that may reduce generalizability of findings. There is also potential for residual confounding by factors related to both social support levels and time since discharge that were not available in this data set. Findings have implications for developing clinical and community interventions intended to support veterans as they transition back to the community. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.002 | 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) | 0.005 | 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 it