Shared Ethics Decision Making in Nursing Practice: A Systematic Review
Bibliographic record
Abstract
Background. Shared decision-making is a process by which healthcare professionals (HCPs’) and patients work together to make choices, taking into account the best clinical evidence and the patient's values. Currently, the level of shared decision-making (SDM) is still low. Some reasons were given such as time, knowlight, and skill but most of the reasons were not based on evidence and were often based on misconceptions. Most of the focus of decision-making is on the patient and physician, without involving the role of members. This study aims to analyze the act of involving shared ethical decision-making (SEDM) in nursing services. method. The database is systematically searched for the involvement of SEDM on data search engines, namely SCOPUS, PubMed, Mendeley, Scient Direct, and Google Scholar. Article reviews were by the inclusion criteria and extraction was carried out so that 25 articles were produced. Research studies use descriptive analysis that describes and explains research results that are explained in the literature. The risk of bias from the review results is identified to avoid cross-study bias. Results: Deep study approach SEDM in this systematic review, from 25 articles with qualitative study approaches (56%) and review studies (32%). Articles were written in America, Canada, Princess, the Netherlands, Norway, Sweden, Australia, and Korea. Respondents were family/parents with an average age of 37 years, HCPs respondents with an average age of 31 years with at least 5 years of work experience. The results of the study search were grouped based on two findings, namely the intervention of patient and family involvement and the involvement of health professionals in SEDM. Conclusions. Involving patients and families in SDM is very important, especially involvement in respecting the principle of patient autonomy. Patient autonomy is a benchmark in decision-making. Family or parents are sometimes more dominant in decisions. HCPs’ involvement as an informant in SEDM. The involvement of nurses in interprofessional discussions is very beneficial for patients. The nurse's observation of the patient's condition is important both in clinical and ethical considerations. Research recommendations in SEDM for nurses should dig up a lot of information about patients and discuss it with other health interprofessional. And the use of decision aids can increase the suitability of value treatments and reduce decision conflicts.
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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 | 0.028 | 0.090 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.018 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".