Coercion in psychiatric and mental health nursing: A conceptual analysis
Bibliographic record
Abstract
The use of coercion in psychiatric and mental health nursing is a major challenge, which can lead to negative consequences for nurses and patients, including rupture in the therapeutic relationship and risk of injury and trauma. The concept of coercion is complex to define and is used in different ways throughout the nursing literature. This concept is defined broadly, referring to both formal (seclusion, restraint, and forced hospitalization), informal (persuasion, threat, and inducement), and perceived coercion, without fully addressing its evolving conceptualizations and use in nursing practice. We conducted a concept analysis of coercion using Rodgers' evolutionary method to identify its antecedents, attributes, and associated consequences. We identified five main attributes of the concept: different forms of coercion; the contexts in which coercion is exercised; nurses' justification of its use; the ethical issues raised by the presence of coercion; and power dynamics. Our conceptual analysis shows the need for more nursing research in the field of coercion to achieve a better understanding of the power dynamics and ethical issues that arise in the presence of coercion.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".