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Record W2027545156 · doi:10.1177/0969733015576357

Ethical issues experienced by healthcare workers in nursing homes

2015· review· en· W2027545156 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNursing Ethics · 2015
Typereview
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsHamilton Health Sciences
Fundersnot available
KeywordsNursingEthical issuesBurnoutNursing ethicsHealth careWork (physics)PsychologyMedicineEngineering ethicsPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Ethical issues are increasingly being reported by care-providers; however, little is known about the nature of these issues within the nursing home. Ethical issues are unavoidable in healthcare and can result in opportunities for improving work and care conditions; however, they are also associated with detrimental outcomes including staff burnout and moral distress. OBJECTIVES: The purpose of this review was to identify prior research which focuses on ethical issues in the nursing home and to explore staffs' experiences of ethical issues. METHODS: Using a systematic approach based on Aveyard (2014), a literature review was conducted which focused on ethical and moral issues, nurses and nursing assistants, and the nursing home. FINDINGS: The most salient themes identified in the review included clashing ethical principles, issues related to communication, lack of resources and quality of care provision. The review also identified solutions for overcoming the ethical issues that were identified and revealed the definitional challenges that permeate this area of work. CONCLUSIONS: The review highlighted a need for improved ethics education for care-providers.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.679
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0100.022
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.357
GPT teacher head0.619
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it