Measures of retention in HIV care: A protocol for a mixed methods study
Bibliographic record
Abstract
Abstract Introduction Retention in HIV care is necessary to achieve adherence to antiretroviral therapy, viral load suppression, and optimal health outcomes. There is no standard definition for retention in HIV care, which compromises consistent and reliable reporting and comparison of retention across facilities, jurisdictions, and studies. Objective The objective of this study is to explore how stakeholders involved in HIV care define retention in HIV care and their preferences on measuring retention. Methods We will use an exploratory sequential mixed methods design involving HIV stakeholder groups such as people living with HIV, people involved in providing care for PLHIV, and people involved in decision-making about PLHIV. In the qualitative phase of the study, we with conduct 20-25 in-depth interviews to collect perspectives of HIV stakeholders on using their preferred retention measures. The interview guide has being provided as an online Supplementary Appendix 1.The findings from the qualitative phase will inform the development of survey items for the quantitative phase. Survey participants (n=385) will be invited to rate the importance of each approach to measuring retention on a seven-point Likert scale. We will merge the findings from the qualitative and quantitative findings phase to inform a consensus-building framework for a standard definition of retention in care. Ethical Issues and Dissemination This study has received ethics approval from the Hamilton Integrated Research Ethics Board. The findings will be disseminated through peer-reviewed publications, conference presentations, and among stakeholder groups. Limitations 1. This study has limitation, we won’t be able to arrive at a standard definition, a Delphi technique amongst the stakeholders will be utilized using the framework to reach a consensus globally accepted definition.
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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 | 0.176 | 0.135 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.092 | 0.021 |
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".