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Record W2022701704 · doi:10.3109/01612840903506444

Forensic Psychiatric/Mental Health Nursing: Responsive to Social Need

2010· review· en· W2022701704 on OpenAlexaff
Arlene Kent‐Wilkinson

Bibliographic record

VenueIssues in Mental Health Nursing · 2010
Typereview
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsForensic nursingNursingForensic psychiatrySpecialtyMental healthMental health nursingIntervention (counseling)MedicineNurse educationPsychologyForensic sciencePsychiatry

Abstract

fetched live from OpenAlex

Forensic nursing is an emerging global nursing specialty, with subspecialties that focus on nursing practice at the clinical-legal interface of tending to victims and offenders, living and deceased. An integrated review of the literature provides an overview of the role development of forensic nursing subspecialties. The subspecialties of forensic nursing that deal with the mental health care of victims and offenders are the focus of this paper. Forensic nursing, like all forensic specialties, developed from a need in society for a medico-legal role. This paper discusses the global role of forensic nursing and argues that role development has been both proactive and responsive to vital needs of victims and offenders in society. Advanced practice forensic nurses have taken leadership roles in the role development of this nursing specialty. A future challenge for forensic psychiatric/mental health nurses with advanced education is to take leadership roles in all areas of psychiatric assessment, intervention, and evaluation of clients.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.822
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.062
GPT teacher head0.499
Teacher spread0.437 · 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 designOther design
Domainnot available
GenreReview

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

Citations15
Published2010
Admission routes1
Has abstractyes

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