Study protocol: the ILANA study – exploring optimal implementation strategies for long-acting antiretroviral therapy to ensure equity in clinical care and policy for women, racially minoritised people and older people living with HIV in the UK – a qualitative multiphase longitudinal study design
Bibliographic record
Abstract
INTRODUCTION: Cabotegravir and rilpivirine (CAB+RPV long-acting (LA)) is recommended as a treatment for HIV-1 allowing people living with HIV to receive 2 monthly injectable treatment, rather than daily pills. Providing injectable therapy in a system designed to provide and manage study participants on oral treatments poses logistical challenges namely how resources are used to accommodate patient preference within constrained health economies with capacity limitations. In this pragmatic multicentre study, we aim to understand the implementation of CAB-RPV-LA administration in two settings via mixed methods to explore perspectives of participants and the clinical team delivering CAB+RPV LA. METHODS AND ANALYSIS: Women, racially minoritised people and older people are chronically under-represented in HIV clinical trials so the ILANA trial has set recruitment caps to ensure recruitment of 50% women, 50% ethnically diverse people and 30% over 50 years of age to include a more representative study population. Using a mixed-methods approach, the primary objective is to identify and evaluate the critical implementation strategies for CAB+RPV LA in both hospital and community settings. Secondary objectives include evaluating feasibility and acceptability of CAB+RPV LA administration at UK clinics and community settings from the perspective of HIV care providers, nurses and representatives at community sites, evaluating barriers to implementation, the utility of implementation strategies and adherence. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the Health Research Authority Research Ethics Committee (REC reference: 22/PR/0318). The dissemination strategy has been formulated with the SHARE Collaborative Community Advisory Board to maximise the impact of this work on clinical care and policy. This strategy draws on and leverages existing resources within the participating organisations, such as their academic infrastructure, professional relationships and community networks. The strategy will leverage the Public Engagement Team and press office to support dissemination of findings. TRIAL REGISTRATION NUMBER: NCT05294159.
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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 | 0.070 | 0.070 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.082 | 0.018 |
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".