Post-traumatic Stress Disorder and War: A Systematic Review
Bibliographic record
Abstract
PTSD has been linked in the literature to traumatic experiences of car accidents, natural disasters, sexual assaults and especially war. This is evidenced by the relevant literature research reported in the thesis. The research was guided by PRISMA 2020, which helped to ensure the quality of the research (Page et al., 2021a; 2020b). Initially, research was sought that addressed the association between this disorder and experiences of war. Of the found sources of material, a part was the category of previous similar type of research (N=7) on the relevant topic, from which the usefulness of the present study became apparent, with the limited Greek literature and the focus of the existing one on veteran soldiers. An important finding was the much higher prevalence of the general population and children and youth, compared to veterans. The association between PTSD and war, its intensity and prevalence, depends on other factors such as demographics, the type of trauma, the psychosocial make-up of the individual and his/her socio-cultural identity. There is a need for further research into this phenomenon, with the aim of formulating targeted policies for prevention, treatment-intervention and rehabilitation of people who have experienced the inhuman situations of war.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".