Comparing the characteristics of people living with and without HIV in long-term care and home care in Ontario, Canada
Bibliographic record
Abstract
Population aging and successful drug therapy in human immunodeficiency virus (HIV) management mean that more people are living longer with HIV. As these individuals age, they become more at risk of developing other chronic health conditions which will have many implications for disease management and choice of care setting. As people living with HIV turn to home care and long-term care (LTC) settings for care, understanding the particular needs of this population is becoming increasingly important. This study sought to describe the sociodemographic, clinical, and social attributes of people living with HIV in the home care and institutional environments. This work involved secondary analysis of data collected from both the international Resident Assessment Instruments (interRAI) home care and minimum data set instruments in the Canadian province of Ontario. Descriptive analysis was used to describe key attributes of people living with and without HIV in LTC, complex continuing care, and home care settings. A comparison of differences between people living with HIV across the three environments was also done using Chi-square analysis. People living with HIV were often younger, male and unmarried than other populations in the care settings studied. Together with specific health needs associated with issues like mental health and social isolation, people living with HIV represent a population with complex and distinctive health needs. Finding ways to better understand the needs of this vulnerable population will help to develop strategies to provide better formal and informal care and improve the quality of life of this group. interRAI standardized assessment instruments may be important tools for meeting this challenge.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".