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Record W4403795131 · doi:10.1097/jfn.0000000000000518

A Canadian Sexual Assault Nurse Examiner’s Personal Reflection and Ongoing Questioning of Vicarious Trauma

2024· article· en· W4403795131 on OpenAlexaffabout
Diana Rose Caporiccio, Arlene Kent‐Wilkinson, Cindy Peternelj‐Taylor

Bibliographic record

VenueJournal of Forensic Nursing · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCompassion fatigueMedicineCLARITYPersonal narrativeNursingPsychologyBurnoutNarrativeClinical psychology

Abstract

fetched live from OpenAlex

ABSTRACT Vicarious trauma (VT) is a concept that has been recognized in nursing. Although research has extensively explored signs, symptoms, and risks associated with VT, there is a notable gap in the literature concerning the personal lived experiences of sexual assault nurse examiners (SANEs). Objective The objective of this article was to provide a first-person account of the vulnerable aspects of my life where I questioned if VT had influenced my thought processes and to uncover the potential health risks associated with exposure to patients' repeated stories of trauma. I questioned whether I was experiencing VT or other disorders such as burnout, posttraumatic stress disorder, or compassion fatigue. The scholarly literature was reviewed after my personal reflection to analyze my personal experiences and to gain clarity on how VT and/or other related concepts may impact the professional and personal lives of SANEs. Methods Methods used to produce my personal stories have been done via self-reflection and journaling. Three stories that I believe may resemble VT are shared and analyzed vis-à-vis the literature. My personal vignettes are compared with signs and symptoms of VT and illustrate how they may manifest in the daily lives of SANEs. Implications To date, researchers have neglected to explore concrete examples of the personal depth VT may exhibit in an individual's life. By disclosing and synthesizing my personal stories, I hope to encourage SANEs to be open about their experiences, spread awareness and prevention strategies regarding VT, and, ultimately, further enhance well-being and promote increased longevity in their careers.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.030
GPT teacher head0.354
Teacher spread0.323 · 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 designQualitative
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

Citations2
Published2024
Admission routes2
Has abstractyes

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