POSTTRAUMATIC STRESS DISORDER AMONG PRESCHOOLERS EXPOSED TO ONGOING MISSILE ATTACKS IN THE GAZA WAR
Bibliographic record
Abstract
BACKGROUND: The prevalence and manifestation of posttraumatic stress symptoms in young children may differ from that observed in adults. This study examined sociodemographic, familial, and psychosomatic correlates of posttraumatic stress disorder (PTSD) among preschool children and their mothers who had been exposed to ongoing missile attacks in the Gaza war. METHODS: One hundred and sixty-seven mothers of preschoolers (aged 4.0-6.5 years) were interviewed regarding PTSD and psychosomatic symptomatology of their children, as well as their own reactions to trauma. RESULTS: Fourteen mothers (8.4%) and 35 children (21.0%) screened positive for PTSD. Sociodemographic characteristics were not associated with PTSD among mothers or children. Among children, the only significant risk factor was having a mother with PTSD (OR = 12.22, 95% CI 2.75-54.28). Compared to children who did not screen positive for PTSD, those who did screen positive displayed significantly higher rates of psychosomatic reactions to trauma, most notably constipation or diarrhea (OR = 4.36, 95% CI 1.64-11.60) and headaches (OR = 2.91, 95% CI 1.07-7.94). CONCLUSIONS: Results of this study add to the burgeoning literature on child PTSD, emphasizing the important role of maternal anxiety and the psychosomatic reactions associated with exposure to ongoing traumatic experiences in young children.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".