What's the buzz about BUZZ? A workshop to enhance communication between patients and their health care teams
Bibliographic record
Abstract
Objective BUZZ is a workshop designed to enhance communication between patients and health care providers (HCPs) and results to date will be described. Background A study of HIV patients interviewed about their treatment, identified several barriers to communication with their health care teams. Another study called BEAHIV, demonstrated low levels of agreement between patients and HCPs surrounding bothersome symptoms of ARV treatment. With a grant from Janssen, a workshop was designed by a faculty of HIV clinicians from across Canada, in conjunction with a behavioural specialist. The workshop covered several topics: identifying barriers to communication for HIV patients, learning about one's own preferred communication style, how to determine a patient's communication style, and ways to uncover issues associated with the patient's treatment, such as ARV‐associated side effects. To date, 15 workshops have been conducted across the country. Results At the end of the workshop, 85% of participants said they would start or continue to identify barriers to communication. At the start of each workshop, several before/after questions were asked. Only 45% of HCPs felt comfortable in adapting their communication towards patients with different behavioural styles prior to participating in the workshop. This increased to 84% after the workshop. Prior to the workshop, 68% of HCPs said they currently engage patients in proactive discussions surrounding ARV‐associated side effects, increasing to 82% post‐workshop. Prior to the workshop, 60% proactively engaged patients on the impact of ARV side effects on quality of life, which increased to 80% post‐workshop. Several weeks after each workshop, a follow up with participants was conducted and it was found that many implemented changes in their practices as a result of what they learned. Conclusion A workshop designed to enhance communication may have a beneficial effect on reducing communication barriers and enhancing HIV patient care.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".