The implementation of correctional nursing practice—Caring behind bars: A grounded theory study
Bibliographic record
Abstract
AIM: To understand how registered nurses implement their nursing practice in correctional institutions with healthcare governance by a health authority (e.g. Ministry of Health). DESIGN: Straussian grounded theory. METHODS: Simultaneous data collection and analysis were undertaken using theoretical sampling, constant comparison and memo writing. Thirteen registered nurses engaged in semi-structured telephone interviews about implementing their correctional nursing practice including, providing direct care to adult offenders. Data were collected (December 2018 to October 2019) until saturation occurred. Analytic coding (open, axial and final theoretical integration) was performed to identify the core category and subcategories around which the substantive theory was developed. RESULTS: The theory of Caring Behind Bars refers to the process of how registered nurses implemented their correctional nursing practice to care for offenders. The core category of Caring Behind Bars is comprised of five subcategories: tension between custody and caring, adaptability and advocacy, offender population, provision of care, and challenging and positive elements. CONCLUSION: Caring Behind Bars required registered nurses to address tension between custody and caring by adapting and advocating to access offenders. The provision of care required registered nurses to use assessment skills and numerous resources to provide a variety of patient focused care to offenders. The consequences of Caring Behind Bars had challenging and positive elements. IMPACT: The tension provides purposeful space to continue improving teamwork among correctional officers and registered nurses. More research is required about the impact of correctional healthcare governance models on professional practice and health outcomes. Frontline registered nurses can use the theory to make informed choices when providing care. Registered nurses practising in other domains of correctional nursing (i.e. administration, education and research) can also use this theory to advance and inform practice with the goal of promoting offender health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".