Understanding geriatric models of care for older adults living with HIV: A Scoping Review and Qualitative Analysis
Bibliographic record
Abstract
Abstract Background Advances in Human Immunodeficiency Virus (HIV) treatment have reduced mortality rates and consequently increased the number of individuals with HIV living into older age. Despite this, people aged 50 years and older have been left behind in recent HIV treatment and prevention campaigns, and a gold-standard model of care for this population has not yet been defined. Developing evidence-based geriatric HIV models of care can support an accessible, equitable, and sustainable HIV health care system that ensures older adults have access to care that meets their needs now and in the future. Methods Guided by Arksey & O’Malley (2005), a scoping review was conducted to determine the key components of, identify gaps in the literature about, and provide recommendations for future research into geriatric models of care for individuals with HIV. Five databases and the grey literature were systematically searched. The titles, abstracts and full texts of the search results were screened independently in duplicate. Data were analyzed using a qualitative case study and key component analysis approach to identify necessary model components. Results 5702 studies underwent title and abstract screening, with 154 entering full-text review. 13 peer-reviewed and 0 grey literature sources were included. Most articles were from North America. We identified three primary model of care components that may improve the successful delivery of geriatric care to people living with HIV: Collaboration and Integration; Organization of Geriatric Care; and Pillars of Holistic Care. Most articles included some aspects of all three components. Conclusion To provide effective geriatric care to older persons living with HIV, health services and systems are encouraged to use an evidence-based framework and should consider incorporating the distinct model of care characteristics that we have identified in the literature. However, there is limited data about models in developing countries and long-term care settings, and limited knowledge of the role of family, friends and peers in supporting the geriatric care of individuals living with HIV. Future evaluative research is encouraged to determine the impact of optimal components of geriatric models of care on patient outcomes.
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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 | 0.048 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.016 | 0.019 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 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".