POST-TRAUMATIC STRESS DISORDER IN CHILDREN FOLLOWING NATURAL DISASTERS: A SYSTEMATIC REVIEW OF THE LONG-TERM FOLLOW-UP STUDIES
Bibliographic record
Abstract
The objective of this article was to conduct a systematic review of long-term follow-up studies on Post-traumatic Stress Disorder (PTSD) symptoms in children and adolescents. The MEDLINE and PsycINFO databases were searched from 1980 through January 2014. Studies that examined PTSD symptoms in children for over three years after mass natural disasters were selected. Ten studies, including four cohort studies, four cross-sectional studies, one descriptive study, and one case-series study following disaster-exposed children, met all the selection criteria and thus were included in this review. The follow-up period ranged from three to 20 years after the disasters. Synthesized results regarding PTSD prevalence rate, changes over time, and influential factors on PTSD were summarized and discussed. The reviewed studies indicated that PTSD symptoms decrease rapidly during the first two years after a disaster; however, the long-term course is not yet clear. Several factors including gender and disaster experience appeared to be influential on PTSD symptoms; however, gender effect was possibly confounded by other factors. To examine moderating effects among those influential factors, as well as to avoid confounding, multivariate analytical methods would be beneficial and recommended in future research. Also, recovery patterns await further investigation for better understanding of the factors associated with chronic 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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".