Abstracts from the 43rd Annual Scientific Meeting of the Canadian Geriatrics Society
Bibliographic record
Abstract
Background: Transgender older adults (TOA) are a vulnerable population who have and continue to face mistreatment, stigma, and discrimination when accessing healthcare.Evidence is needed to understand how to best support TOA navigating aging and end of life.Methods: A scoping review was conducted to consolidate and summarize current evidence and to identify areas for future study.Results: 63 articles were identified with 38 representing the lived experience of TOA, 22 pertaining to provision of care to TOA, and 3 involving both.Evidence synthesis resulted in the development of three major themes: health, mistreatment, and social connection/autonomy.TOA were found to be disproportionately burdened by multiple chronic conditions including a higher prevalence of depression and suicide.Preventative care such as vaccination and routine disease screening was disproportionally missed.TOA faced challenges with loneliness, mistreatment, and social resources.TOA feared non-affirming care in dependent living including the inability to live in the truth of their chosen gender.Gender affirming care in the TOA population improved quality of life.Care providers endorse a lack of knowledge regarding care of TOA and an interest in learning more.Discussion: Despite this focus on transgender individuals 65+, no articles meeting our inclusion criteria represented the lived experience of TOA in dependent living.Further, a lack of research with regards to gender affirming care and older bodies was raised by TOA and supported by this review.Research is needed to identify how to best support TOA in healthcare settings.Conclusions: Care providers must consider chronic disease burden, routine preventative care, and the benefits of gender affirming care when serving TOA.Research is needed to establish best practices for care providers and to facilitate TOA informed decision making.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.120 | 0.038 |
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".