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Record W6921730922 · doi:10.7939/r3-34fs-2q35

A Focused Ethnography of Correctional Nurses Who Care for Incarcerated Women with Mental Health Concerns in Canada

2023· dissertation· en· W6921730922 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2023
Typedissertation
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisMental healthPsychological interventionHealth careQualitative researchEthnographyMental health careMental illness

Abstract

fetched live from OpenAlex

Background: Worldwide, the number of incarcerated women has been grown by more than 50% in the past twenty years. In Canada, when women are incarcerated, they make up 15% of the provincial/territorial admissions, and 8% of federal admissions. Within the correctional system, women remain disproportionally burdened with higher prevalence rates for chronic and infectious diseases, mental health concerns and substance use. Once incarcerated, research has identified that opportunities do exist to improve the physical and mental health of women. For women who are incarcerated, their regular and consistent point of contact with healthcare is through their interactions with nursing staff as they are the principal providers of healthcare in correctional facilities. The literature notes that interventions by nurses in correctional facilities have the potential to improve the lives of women beyond incarceration, and at the heart of this potential is the nurse-patient relationship which is a core component of nursing practice. For incarcerated women to undergo an improvement in their health it was worthwhile to look at how the nurse-patient relationship was perceived and enacted, more specifically by examining the experiences of the nurses working with incarcerated women. Purpose: The purpose of this study was to explore nurses’ experiences working with incarcerated women with mental health concerns to bring greater understanding to the practice of correctional healthcare professionals. Method: A focused ethnography was used. Eighteen correctional nurses from three provinces participated in individual semi-structured interviews. The participants worked in federal and provincial/territorial centres, including sentenced and remand facilities. Data analysis consisted of thematic analysis. Data were managed with Quirkos, a qualitative data analysis software. Results: Data analysis developed seven themes: jack of all trades; seeing beyond the clinical task; being an expert; moments of opportunity; building the patient up; complex relationships, and culturally safe correctional nursing care. Complex relationships revealed that the nurse-patient relationship should be better described as a triad that includes the correctional officer. Culturally safe care was evident throughout the themes but also developed into a separate theme. Conclusion: This study revealed that nurses were drawn to working in correctional facilities because of the intersection of complex patients, healthcare and the criminal justice system. The study also found that nurses experienced the pressure to acculturate into the correctional culture from when they first were employed and throughout their correctional career. Finally, it learned that the therapeutic nurse-patient relationship includes the correctional officers and can be thought of as a triad. Limitations of the study include sample diversity. Several recommendations were identified for future research, as well as for correctional nursing clinical practice and educational institutions.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
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
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.251
Teacher spread0.239 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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