Community Involvement in Development of Evidence-Informed Recommendations for Rehabilitation for Older Adults Living With HIV
Bibliographic record
Abstract
BACKGROUND: Involving community in development of clinical practice guidelines (CPGs) can decrease the gap between patient preferences and research evidence. OBJECTIVE: To incorporate meaningful participation of people living with human immunodeficiency virus (HIV; people living with HIV [PHAs]) in the development of evidence informed recommendations for rehabilitation practice. METHODS: PHAs were involved in a process to develop practice recommendations internally as members of a project team and externally through formal endorsement of the recommendations. LESSONS LEARNED: Lessons learned include 1) providing time to develop as a team and understand the roles, biases, and expertise of each member, 2) engaging community in initial discussions to determine the most meaningful involvement, 3) realizing that participation in research may trigger anxiety and stress in community members, 4) developing terms of reference to clarify roles and expectations, 5) providing opportunities for skill development, and 6) conducting formal evaluation of the process and satisfaction of community. CONCLUSION: Meaningful inclusion of community can improve the quality of practice guidelines.
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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 | 0.287 | 0.439 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.006 | 0.029 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".