Exploring the Impact of Wildfires on Children’s Psychological Well-being: A Comprehensive Review of Recent Literature
Bibliographic record
Abstract
Introduction Wildfire disasters have become increasingly rampant. There is a critical need for all to fully understand the mechanism and impact of these disasters on humans, with a special emphasis on the mental health effects they pose on the affected individuals and communities. This article specifically presents a scoping review of the psychological reactions of children and adolescents post-wildfire disaster. Objectives This review aims to synthesize currently available literature regarding the impact of wildfire on mental health, specifically the psychological reactions of children to wildfires. Methods We identified 8 research articles using 6 databases for this review. Data extraction was performed using a qualitative descriptive approach. Results The results identified post-traumatic stress disorder (PTSD), anxiety, depression, stress, alcohol/substance misuse, hopelessness, low resilience, reduced quality of life, and self-esteem as the psychological conditions manifesting in children and adolescents post-wildfire disaster. PTSD was the most evaluated psychological reaction in the participants (7 out of eight studies). Conclusions This review highlights that deleterious mental health effects, such as PTSD, depression, anxiety, and suicidality, can persist in children for years post-wildfire disaster. Factors such as gender, direct exposure to the wildfire, re-traumatization, and resilience informed or ameliorated the severity of the impact of wildfire on children and adolescents. Our findings further emphasize the need for multi-year funding and programs to support children and adolescents’ mental health, including children with disabilities in the communities that have experienced wildfire disasters. Disclosure of Interest None Declared
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".