A Systematic Literature Review of the Impact of COVID-19 on the Health of LGBTQIA+ Older Adults: Identification of Risk and Protective Health Factors and Development of a Model of Health and Disease
Bibliographic record
Abstract
It is important to understand the differential impact of COVID-19 on the health of older lesbian, gay, bisexual, transgender, queer/questioning, intersex, asexual, and people with other sexual orientations and forms of gender expression (LGBTQIA+). The objective of this study is to systematically review the impact of COVID-19 on LGBTQIA+ older adults' health including risk and protective factors. We reviewed a total of 167 records including LGBTQIA+ older adults published since 2019. Two independent reviewers screened titles and abstracts and extracted information of 21 full-text records meeting inclusion criteria using COVIDENCE software. The results show that the negative health consequences are exacerbated by personal risk (e.g., perceived homo/transphobia and ageism in LGBTQIA+ communities) and environmental factors (e.g., heterosexism within health services). The negative impact seems to be reduced by personal protective (e.g., resilience, spirituality, and hobbies) and environmental factors (e.g., technology use to increase social participation and social rituals). In conclusion, the health of LGBTQIA+ older adults has been disproportionately affected during the pandemic associated to the latest coronavirus (COVID-19). The experiences of LGBTQIA+ older adults during the pandemic are integrated in a Model of Health and Disease for LGBTQIA+ older adults. Specific strategies to promote health and well-being in this community are provided.
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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 | 0.015 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.021 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".