Early Psychosocial Interventions for Individuals and Groups Affected by Disasters
Bibliographic record
Abstract
Abstract Throughout the world, individuals, groups, and communities are faced with major incidents, crises, and disasters. The impact of disasters can be wide-ranging, involving death, severe injury, the loss of home, shelter, liberty, security, and food, in addition to social dislocation and destroyed infrastructure and networks. Victims can experience distress, anger, grief, and fear together with symptoms of anxiety, depression, and post-traumatic stress. First responders and those delivering longer-term social and psychological support can be adversely affected by direct exposure to the disaster, by learning about the details of the disaster from the testimony of victims, or by viewing distressing images or artifacts connected to the disaster. To reduce the impact of disasters, communities and emergency services need to prepare plans to meet the physical, social, and psychological needs of those involved and undertake thorough testing of these plans to ensure they are fit for purpose. This planning needs to consider natural hazards such as forest fires, floods, drought, and biological hazards, including Covid-19, influenza, foot and mouth disease, and severe acute respiratory syndrome. Human and technological failings can also create hazards seen in transport crashes, the release of toxic substances, and armed conflict. Contingency planning is used to reduce exposure to a hazard by identifying and protecting those at most risk of harm. However, it is impossible to prevent crises and disasters from happening, making it essential to provide appropriate and timely support. Initial support ensures that disaster survivors are taken to a safe place where their immediate needs for food, drinks, and shelter are met. The aim of early psychosocial responses to disasters are fourfold: (a) to increase disaster preparedness to reduce the impact of hazards and vulnerabilities, (b) to respond to the immediate human needs for safety and survival, (c) to communicate care and provide psychological support, and (d) to provide an opportunity for survivors to process and create meaning from experiences. Ideally, all early psychosocial interventions would be evidence-based and delivered by trained and monitored practitioners; however, often, this is not the case. Despite the development of an abundance of disaster-related models, few have been evaluated; this failure is due to a lack of agreement on the aims, scope, measures, and training required to deliver evidence-based interventions. Humanitarian and emergency response organizations look toward psychologists to provide them with the evidence-based interventions, evaluation tools, and guidance they need for dealing with disasters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".