Theory of protective empowering for balancing patient safety and choices
Bibliographic record
Abstract
Registered nurses in psychiatric-mental health nursing continuously balance the ethical principles of duty to do good (beneficence) and no harm (non-maleficence) with the duty to respect patient choices (autonomy). However, the problem of nurses' level of control versus patients' choices remains a challenge. The aim of this article is to discuss how nurses accomplish their simultaneous responsibility for balancing patient safety (beneficence and non-maleficence) with patient choices (autonomy) through the theory of protective empowering. This is done by reflecting on interview excerpts about caring from 17 registered nurses taking part in a grounded theory study conducted in three acute urban psychiatric hospital settings in Canada. The interplay between the protective and empowering dimensions of the theory of protective empowering was found to correspond with international, national, and local nursing codes of ethics and standards. The overall core process of protective empowering, and its associated reflective questions, is offered as a new lens for balancing patient safety with choices.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".