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Record W3047508410 · doi:10.1177/2516103220942530

When it counts the most: Trauma-informed care and the COVID-19 global pandemic

2020· article· en· W3047508410 on OpenAlexaff
Delphine Collin‐Vézina, Denise Michelle Brend, Irene Beeman

Bibliographic record

VenueDevelopmental Child Welfare · 2020
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversité de SherbrookeMcGill UniversityOntario Centre of Excellence for Child and Youth Mental Health
Fundersnot available
KeywordsEmpowermentPandemicContext (archaeology)Mental healthPublic relationsPolitical sciencePsychologyTransparency (behavior)Health careMedicineCriminologyPsychiatryCoronavirus disease 2019 (COVID-19)LawGeography

Abstract

fetched live from OpenAlex

CONTEXT: Evidence from the COVID-19 crisis suggests that children and youth are more likely to be subjected to maltreatment and exposure to family violence, while experiencing limited access to the usual services that support vulnerable families and provide targeted services to meet their needs. The current global pandemic itself can also be experienced as a traumatic event. Trauma-informed care draws attention to the potential impacts, from the individual to the global, that myriad traumatic experiences can illicit and proposes using these understandings as foundational to the development and implementation of policy and practice. OBJECTIVE: The aim of this opinion paper is to offer insights to guide practices and policies during this unprecedented global crisis through a discussion of the Substance Abuse and Mental Health Services Administration (2014)’s six trauma-informed care principles: trustworthiness and transparency; safety; peer support; collaboration and mutuality; empowerment and choice; and cultural, historical and gender issues. FINDINGS: Specific recommendations based on these six principles and applied to the current situation are presented and discussed. These principles can serve both in the immediate crisis and as preventative measures against unforeseen future traumatic contexts. CONCLUSION: COVID-19 renews the imperative to maintain and strengthen trauma-informed practices and policies. We argue that never before has trauma-informed care been so important to promote the health and well-being of all and to protect our marginalized populations at greatest risk.

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)0.000
metaresearch head score (Gemma)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.826
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.030
GPT teacher head0.310
Teacher spread0.280 · 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 designNot applicable
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

Citations71
Published2020
Admission routes1
Has abstractyes

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