Enhancing the delivery of comprehensive care for people living with HIV in Canada: insights from citizen panels and a national stakeholder dialogue
Bibliographic record
Abstract
BACKGROUND: People living with human immunodeficiency virus (HIV) are living longer with health-related disability associated with ageing, including complex conditions. However, health systems in Canada have not adapted to meet these comprehensive care needs. METHODS: We convened three citizen panels and a national stakeholder dialogue. The panels were informed by a plain-language citizen brief that outlined data and evidence about the challenge/problem, elements of an approach for addressing it and implementation considerations. The national dialogue was informed by a more detailed version of the same brief that included a thematic analysis of the findings from the panels. RESULTS: The 31 citizen panel participants emphasized the need for more prevention, testing and social supports, increased public education to address stigma and access to more timely data to inform system changes. The 21 system leaders emphasized the need to enhance person-centred care and for implementing learning and improvement across provinces, territories and Indigenous communities. Citizens and system leaders highlighted that policy actions need to acknowledge that HIV remains unique among conditions faced by Canadians. CONCLUSIONS: Action will require a national learning collaborative to support spread and scale of successful prevention, care and support initiatives. Such a collaborative should be grounded in a rapid-learning and improvement approach that is anchored on the needs, perspectives and aspirations of people living with HIV; driven by timely data and evidence; supported by appropriate decision supports and aligned governance, financial and delivery arrangements; and enabled with a culture of and competencies for rapid learning and improvement.
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 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 | 0.026 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.043 | 0.009 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".