Ethical challenges in home-based care: A systematic literature review
Bibliographic record
Abstract
Because of the transfer of responsibility from hospitals to community-based settings, providers in home-based care have more responsibilities and a wider range of tasks and responsibilities than before, often with limited resources. The increased responsibilities and the complexity of tasks and patient groups may lead to several ethical challenges. A systematic search in the databases MEDLINE, CINAHL, and SveMed+ was carried out in February 2019 and August 2020. The research question was translated into a modified PICO (Population, Intervention, Comparison, and Outcome) worksheet. A total of 40 articles were included. The review is conducted according to the Vancouver Protocol. The main findings from the systematic literature review show that ethical challenges experienced by healthcare and social care providers in home-based care are related to autonomy and balancing ethical principles, decisions regarding intensity of care, challenges related to priority settings, truth-telling, and balancing the professional role. Findings regarding ethical challenges within home-based care are in line with findings from institutional healthcare and social care settings. However, some significant differences from the institutional context are also highlighted.
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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 | 0.111 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.020 | 0.019 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| 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".