Emerging Interventions to Improve Health Outcomes for People Aging With HIV: Protocol for a Mixed Methods Implementation Science Evaluation
Bibliographic record
Abstract
BACKGROUND: In 2022, 54% of people with HIV were aged 50 years and older; however, clinical care for HIV in the United States often falls short of comprehensively integrating care for aging-related conditions. In response, the Health Resources and Services Administration HIV/AIDS Bureau Ryan White HIV/AIDS Program funded a new initiative comprising 10 demonstration sites to test emerging interventions to support people aging with HIV, as well as a capacity-building provider and an evaluation provider. NORC at the University of Chicago received an award for the evaluation provider. OBJECTIVE: This protocol aimed to describe the application of the Health Resources and Services Administration HIV/AIDS Bureau implementation science (IS) framework to a multisite evaluation, a related evaluation protocol, the technical assistance provided to support the evaluation, and the initiative's dissemination plan. METHODS: Using a theory-based approach, NORC developed a mixed methods evaluation plan using an IS hybrid type 2 study with two main aims: (1) to describe implementation outcomes and (2) to assess client-level outcomes. Implementation outcomes were assessed at the organizational level using tools including a survey of site characteristics, key informant interviews, and documentation of monthly monitoring calls and costs. Client-level outcomes were assessed through a survey and a medical chart abstraction tool. NORC also collected data on the sites' engagement with the capacity-building provider and their satisfaction with the services provided. RESULTS: The evaluation was funded in August 2022. Organizational-level data collection began upon institutional review board approval in April 2023. All sites were enrolling clients in the intervention and evaluation by September 2023, and 626 clients enrolled by December 2023. Data collection is expected to continue through December 2024. Analysis of the baseline results is currently underway, and comprehensive findings are expected by late 2025. CONCLUSIONS: To the best of our knowledge, this is the first national study to evaluate emerging clinical interventions for people aging with HIV using an IS framework. The findings will build an evidence base for advancing HIV clinical care to meet the needs of the aging population. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/72471.
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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 | 0.137 | 0.097 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.073 | 0.010 |
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".