The psychosocial impacts of wildland fires on children, adolescents and family functioning: a scoping review
Bibliographic record
Abstract
Disasters have become increasingly common, calling for the need to more fully understand the impacts of such events. This article presents a scoping review of the psychosocial impacts of wildland fires on children, adolescents and family functioning. We identified 19 research articles and reviewed them according to the following characteristics: date and location of the fire, study time period, study design, instrument(s), sample and findings. The studies were primarily conducted within Australia, the US and Canada. The results identified factors that are linked to the impact of wildfires on children, adolescents and families. Age, gender, time, and proximity to the wildfire can impact both children and adolescents while behaviours of family members and home and property loss are important among families. Our understanding of the topic is limited because of the low number of studies, small sample sizes and inconsistent use of age groups and instruments. Future investigations would benefit by being placed within a disaster framework. Other recommendations include focusing specifically on family units, children and adolescents as the primary participants to generate more information about the aftermath of the fire event and conducting longitudinal studies with established scales to allow for comparisons.
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.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".