Study protocol: Addressing evidence and context to facilitate transfer and uptake of consultation recording use in oncology: A knowledge translation implementation study
Bibliographic record
Abstract
BACKGROUND: The time period from diagnosis to the end of treatment is challenging for newly diagnosed cancer patients. Patients have a substantial need for information, decision aids, and psychosocial support. Recordings of initial oncology consultations improve information recall, reduce anxiety, enhance patient satisfaction with communication, and increase patients' perceptions that the essential aspects of their disease and treatment have been addressed during the consultation. Despite the research evidence supporting the provision of consultation recordings, uptake of this intervention into oncology practice has been slow. The primary aim of this project is to conduct an implementation study to explicate the contextual factors, including use of evidence, that facilitate and impede the transfer and uptake of consultation-recording use in a sample of patients newly diagnosed with breast or prostate cancer. METHODS: Sixteen oncologists from cancer centres in three Canadian cities will participate in this three-phase study. The preimplementation phase will be used to identify and address those factors that are fundamental to facilitating the smooth adoption and delivery of the intervention during the implementation phase. During the implementation phase, breast and prostate cancer patients will receive a recording of their initial oncology consultation to take home. Patient interviews will be conducted in the days following the consultation to gather feedback on the benefits of the intervention. Patients will complete the Digital Recording Use Semi-Structured Interview (DRUSSI) and be invited to participate in focus groups in which their experiences with the consultation recording will be explored. Oncologists will receive a summary letter detailing the benefits voiced by their patients. The postimplementation phase includes a conceptual framework development meeting and a seven-point dissemination strategy. DISCUSSION: Consultation recording has been used in oncology, family medicine, and other medicine specialties, and despite affirming evidence and probable applications to a large number of diseases and a variety of clinical contexts, clinical adoption of this intervention has been slow. The proposed study findings will advance our conceptual knowledge of the ways to enhance uptake of consultation recordings in oncology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".