Using the Delphi Method to Elucidate Patient and Caregiver Experiences of Cancer Care
Bibliographic record
Abstract
Objective: Identify the most salient elements of the head and neck cancer (HNC) care experience described by patients and caregivers in focus group interviews. Methods: Three focus groups of patients and caregivers were facilitated by research assistants and clinicians. Open-ended guiding questions captured/elicited aspects of care that were appreciated, warranted improvement, or enhanced communication and information. A four-step Delphi process derived consensus among focus group facilitators (n = 5) regarding salient discussion points from focus group conversations. Results: Seven salient themes were identified: (1) information provision, (2) burden related to symptoms and treatment side effects, (3) importance of social support, (4) quality of care at both hospital and provider levels, (5) caring for the person, not just treating cancer, (6) social and emotional impact of HNC, and (7) stigma and insufficient information regarding human papillomavirus-related HNC. Conclusion: Participants reported varying needs and support preferences, a desire for individualized communication, and to feel cared for as both a person and a patient. Findings illuminate the intricate details underlying high-quality, compassionate, person-centered HNC cancer 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 | 0.047 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".