Ethical and culturally competent care of transgender patients: A scoping review
Bibliographic record
Abstract
BACKGROUND: Transgender individuals experience discrimination, stigmatization, and unethical and insensitive attitudes in healthcare settings. Therefore, healthcare professionals must be knowledgeable about the ways to deliver ethical and culturally competent care. ETHICAL CONSIDERATIONS: No formal ethical approval was required. AIM: To synthesize the literature and identify gaps about approaches to the provision of ethical and culturally competent care to transgender populations. DESIGN: A Scoping Review. LITERATURE SEARCH: Literature was searched within CINAHL, Science Direct, PubMed, Google Scholar, EMBASE, and Scopus databases using indexed keywords such as "transgender," "gender non-conforming," "ethically sensitive care," and "culturally sensitive care." In total, 30 articles, which included transgender patients and their families and nurses, doctors, and health professionals who provided care to transgender patients, were selected for review. Data were extracted and synthesized using tabular and narrative summaries and thematic synthesis. FINDINGS: Of 30 articles, 23 were discussion papers, 5 research articles, and 1 each case study and an integrative review. This indicates an apparent dearth of literature about ethical and culturally sensitive care of transgender individuals. The review identified that healthcare professionals should educate themselves about sensitive issues, become more self-aware, put transgender individual in charge during care interactions, and adhere to the principles of advocacy, confidentiality, autonomy, respect, and disclosure. CONCLUSIONS: The review identified broad approaches for the provision of ethical and culturally competent care. The identified approaches could be used as the baseline, and further research is warranted to develop and assess organizational and individual-level approaches.
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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 | 0.022 | 0.094 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".