Impact of Natural Disasters on Mental Health: Evidence and Implications
Bibliographic record
Abstract
Natural disasters are large-scale catastrophic events, and they are increasing in frequency and severity. Converging evidence indicates that the mental health consequences of disasters are extensive and are often associated with trauma and the disruption of personal and socioeconomic factors in people's lives. Although most individuals experiencing disaster-related traumatic events do not develop mental illnesses, some experience adverse psychological effects of disasters. These mental health effects begin immediately following a disaster and may persist for extended periods. In this article, we summarize the literature findings to provide a narrative review that focuses on the mental health consequences of natural disasters. An overview of the disaster mental health research field is provided, and the findings are ordered into theoretical frameworks. Then, the development and course of psychopathology regarding disaster aftermath are described in a methodological context. Next, understanding a disaster as an event of transition is highlighted, and the impact of this disaster-specific transition is discussed. Lastly, a potential relationship between the transitional impact of a disaster and mental health consequences is speculated on, and the implications are discussed. The impact of disasters on mental health can be direct or indirect, short-term or long-term, and to some extent depends on the recovery process of the affected community. Also, we propose the possible merits of using the Transitional Impact Scale in the context of disaster mental health research by assessing the features of disaster-related transition and its effects on mental health. We conclude by suggesting a direction for future research in terms of measuring the disaster mental health effects in community settings (affected vs. non-affected) and also considering cross-cultural and cross-regional differences. In recent decades, a large amount of knowledge has been gathered from disaster mental health research, but, still, more research is needed to resolve some irregular findings through refining the methodological variations.
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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 | 0.009 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".