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The Prevalence and Impact of Trauma and Why Trauma-informed Care is Needed in Nursing Education

2024· book-chapter· en· W4396614994 on OpenAlexaff
Kathleen Stephany

Bibliographic record

VenueBENTHAM SCIENCE PUBLISHERS eBooks · 2024
Typebook-chapter
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsDouglas College
Fundersnot available
KeywordsNursingMedicineTrauma carePsychologyMedical emergency

Abstract

fetched live from OpenAlex

Chapter one explores the reasons why student nurses need to be educated in trauma-informed care. Trauma-informed care endeavours to help people who have experienced trauma and targets change at the organizational and clinical level with the aim of improving client/patient outcomes. Various forms of adversity that exist are presented, and we are informed that trauma is not merely a childhood occurrence but may occur at any point across the lifespan. Stereotypical biases and racial stigma experienced by the following special populations are explored, those with differing sexual orientation or gender identity, older adults, refugees and immigrants, people of colour, and Indigenous people. The role that bias and implicit bias play in structural trauma aimed at specific populations is explained. An overview is given of the following specific trauma-related responses, trauma triggers, acute stress disorder, post-traumatic stress disorder, secondary traumatic stress, vicarious traumatization, and compassion fatigue. The Four Core Assumptions of Trauma-informed Care as recommended by the Substance Abuse and Mental Health Services Administration (SAMHSA are explored, because they are foundational for providing traumaresponsive care, and consist of realizing, recognizing, responding, and resisting retraumatization. Healthcare professionals are strongly encouraged to practice in a trauma-responsive and trauma-sensitive manner. Incorporating trauma-informed approaches into the Nursing School curriculum is recommended for the following reasons. Adversity is prevalent in society, and high number of people who access health services have experienced trauma. Student nurses are not currently learning these skills in a comprehensive way in all schools. Student nurses may have a history of trauma, and they are exposed to adverse and stressful events in clinical training. Two Narrative Case Studies are presented. The first shares the story of a Counsellor who developed compassion fatigue, and the second one reveals the complexity of the trigger response. The following learning activities are suggested: connecting with the goodness in life; changing prejudices and stigma; and participating in a trauma-sensitive practice challenge. A self-care strategy that promotes self-compassion is included at the end of the chapter.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.702
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0010.001
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 head0.024
GPT teacher head0.353
Teacher spread0.329 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations0
Published2024
Admission routes1
Has abstractyes

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