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Record W1989575373 · doi:10.1017/s1049023x14000259

The Need for a Systematic Approach to Disaster Psychosocial Response: A Suggested Competency Framework

2014· article· en· W1989575373 on OpenAlex
Robin S. Cox, Taryn Danford

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePrehospital and Disaster Medicine · 2014
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsPsychosocialPsychologyApplied psychologyJob analysisMedical educationMedicineJob satisfactionSocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

Competency models attempt to define what makes expert performers "experts." Successful disaster psychosocial planning and the institutionalizing of psychosocial response within emergency management require clearly-defined skill sets. This necessitates anticipating both the short- and long-term psychosocial implications of a disaster or health emergency (ie, pandemic) by developing effective and sustained working relationships among psychosocial providers, programs, and other planning partners. The following article outlines recommended competencies for psychosocial responders to enable communities and organizations to prepare for and effectively manage a disaster response. Competency-based models are founded on observable performance or behavioral indicators, attitudes, traits, or personalities related to effective performance in a specific role or job. After analyzing the literature regarding competency-based frameworks, a proposed competency framework that details 13 competency domains is suggested. Each domain describes a series of competencies and suggests behavioral indicators for each competency and, where relevant, associated training expectations. These domains have been organized under three distinct categories or types of competencies: general competency domains; disaster psychosocial intervention competency domains; and disaster psychosocial program leadership and coordination competency domains. Competencies do not replace job descriptions nor should they be confused with performance assessments. What they can do is update and revise job descriptions; orient existing and new employees to their disaster/emergency roles and responsibilities; target training needs; provide the basis for ongoing self-assessment by agencies and individuals as they evaluate their readiness to respond; and provide a job- or role-relevant basis for performance appraisal dimensions or standards and review discussions. Using a modular approach to psychosocial planning, service providers can improve their response capacity by utilizing differences in levels of expertise and training. The competencies outlined in this paper can thus be used to standardize expectations about levels of psychosocial support interventions. In addition this approach provides an adaptable framework that can be adjusted for various contexts.

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.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.372
Teacher spread0.345 · 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