Nurses’ perspectives on human rights when coercion is used in psychiatry: a systematic review protocol of qualitative evidence
Bibliographic record
Abstract
BACKGROUND: The World Health Organization describes the perpetuation of human rights violations against people with mental health problems as a global emergency. Despite this observation, recent studies suggest that coercive measures, such as seclusion, restraints, involuntary hospitalization, or involuntary treatment, are steadily or increasingly being used without proof of their effectiveness. In nursing, several literature reviews have focused on understanding nurses' perspectives on the use of seclusion and restraints. Although many studies describe the ethical dilemmas faced by nurses in this context, to this date, their perspectives on patient's rights when a broad variety of coercive measures are used are not well understood. The aim of this review is to produce a qualitative synthesis of how human rights are actually integrated into psychiatric and mental health nursing practice in the context of coercive work. METHODS: Noblit and Hare's meta-ethnographic approach will be used to conduct this systematic review. The search will be conducted in CINAHL, Medline, PsycINFO, ERIC, and Scopus databases, using the PICo model (Population, phenomenon of Interest, Context) and a combination of keywords and descriptors. It will be complemented by a manual search of non-indexed articles, gray literature, and other applicable data sources, such as human rights related documents. Qualitative and mixed-method study designs will be included in this review. Empirical and peer-reviewed articles published between 2008 and 2019 will be selected. Articles will be evaluated independently by two reviewers to determine their inclusion against eligibility criteria. The quality of the selected papers will then be independently evaluated by two reviewers, using the Joanna Briggs Institute's Checklist for Qualitative Research. Data extraction and content analysis will focus on first- and second-order constructs, that is, the extraction of research participants' narratives and their interpretation. DISCUSSION: This review will provide a synthesis of how psychiatric and mental health nurses integrate human rights principles into their practice, as well as it will identify research gaps in this area. The results of this review will then provide qualitative evidence to better understand how nurses can contribute to the recognition, protection, and advocate for human rights in a psychiatric context. SYSTEMATIC REVIEW REGISTRATION: PROSPERO, CRD42019116862.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.155 | 0.124 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.014 | 0.009 |
| Bibliometrics | 0.025 | 0.019 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.033 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".