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Record W4396614873 · doi:10.2174/97898152237671240101

Trauma-informed Care for Nursing Education: Fostering a Caring Pedagogy, Resilience & Psychological Safety

2024· book· en· W4396614873 on OpenAlexaff
Kathleen Stephany

Bibliographic record

VenueBENTHAM SCIENCE PUBLISHERS eBooks · 2024
Typebook
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsDouglas College
Fundersnot available
KeywordsNursingResilience (materials science)PsychologyPsychological resilienceNurse educationMedicinePsychotherapist

Abstract

fetched live from OpenAlex

Trauma-informed care is designed to assist persons who have experienced adversity and focuses on change at the clinical and organizational level. Its goals center around prevention, intervention, and treatments that are evidence-based, encourage resilience, and enhance coping. This textbook is designed to give a comprehensive overview of trauma-informed care to students and faculty involved in nursing care programs. Key features: Explains the skill sets to assess and care for persons who have experienced trauma. Emphasizes key principles of trauma-informed care Includes the use of client-centered, person-centered, and resilience-based tools to deal with trauma Recommends trauma recovery from a positive psychology and post-traumatic growth perspective Utilizes a caring pedagogy intended to foster resilience and help offset the secondary traumatic stress and compassion fatigue experienced by student and practicing nurses. Communicates the value of fostering psychological safety, compassion satisfaction, and joy in work Includes narrative case studies and learning activities in all chapters to help the reader to actively engage with the subject matter. Presents self-care strategies to enhance physical and emotional well-being.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.849
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0020.000
Research integrity0.0010.001
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 head0.081
GPT teacher head0.468
Teacher spread0.387 · 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
GenreOther

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

Citations1
Published2024
Admission routes1
Has abstractyes

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