Non-Clinical Interventions to Reduce Inequities in Palliative Care for 2SLGBTQ+ People: A Narrative Review
Bibliographic record
Abstract
Introduction: People who identify as Two-Spirit, lesbian, gay, bisexual, transgender, and/or queer (2SLGBTQ+) experience health disparities across the lifespan, including at end of life. Recently there has been recognition of the value of health promotion approaches to palliative care that address the social and structural determinants of a good death. Current reviews on 2SLGBTQ+ palliative care are primarily framed through a clinical, patient-provider level lens. Purpose: To understand how implemented and evaluated non-clinical interventions regarding palliative care for 2SLGBTQ+ people are described in the literature. Methods: A narrative review was conducted adhering to a systematic procedure. Six relevant databases were searched, and 1,547 records were screened by two independent reviewers. To be eligible for inclusion, studies had to describe one or more implemented and evaluated non-clinical intervention that addressed at least one inequity or barrier to palliative care for 2SLGBTQ+ people. Charted data was analyzed using inductive content analysis. The socio-ecological model (SEM) was used to critically examine findings. Results: Six studies were included for review. Examples of non-clinical interventions across various settings and multiple socio-ecological levels were noted. We identified four overarching themes to describe how non-clinical interventions reduce inequities in palliative care for 2SLGBTQ+ people. Conclusion: This review revealed gaps in interventions at organizational, community, and public policy levels. Future research should map efforts specific to the Canadian context and empower 2SLGBTQ+ communities to evaluate and report on the interventions they lead. A trauma-informed intersectional approach should be used in the design of interventions with and for 2SLGBTQ+ community members.
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.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".