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Record W4313505689 · doi:10.1177/028072701703500104

Perceptions of Psychosocial Training on Behavioural Responses in Emergency Operations Centres

2017· article· en· W4313505689 on OpenAlexfundno aff
Alanna Thompson, Adam D. Vaughan, Laurie D. R. Pearce, Ciara B. Moran

Bibliographic record

VenueInternational Journal of Mass Emergencies & Disasters · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsnot available
FundersHealth Canada
KeywordsPsychosocialPerceptionEmergency responsePsychosocial supportTraining (meteorology)PsychologyApplied psychologyMedical educationMedical emergencyMedicinePsychiatry

Abstract

fetched live from OpenAlex

When a disaster strikes, the well-being of Emergency Operations Centre (EOC) personnel is often not the first priority for emergency managers working to help provide support to their local community and the incident command site. Through the development and testing of an iterative series of simulation exercises with EOC personnel, this study identified adverse psychosocial outcomes that may emerge within an EOC during an emergency. Having identified a number of practices which led to less than desired psychosocial outcomes, researchers developed a training and awareness video to identify the practices and demonstrate strategies to overcome negative impacts. A comparative analysis was undertaken to compare EOC actions pre- and post-exposure to the video. The results indicated a change in behaviour following the viewing of the video and supported training initiatives that stress the importance of strong leadership in an EOC, encouraging staff to take breaks, respecting diversity, and providing psychosocial support.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.064
GPT teacher head0.383
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2017
Admission routes1
Has abstractyes

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