Patient experiences through head and neck cancer: Information delivery combatting psychological distress
Bibliographic record
Abstract
As part of a larger study investigating the utility of electronic decision support tools for patients with head and neck cancer (HNC), this article describes the patient experience of receiving cancer treatment in British Columbia, Canada. It aims to give voice to the patient experience and recommend a model of psychological adjustment for clinicians and clinical service management to consider to refine patient centric care pathways for HNC. Based in phenomenology, semi-structured interviews were conducted with 12 survivors of HNC, audio-video recorded, and thematically analyzed. Three themes were identified: (1) patients have high, though varying information needs; (2) an emotional experience; and (3) coping, strength, and resiliency. These themes arose from six concepts: (1) information needs; (2) fear of the unknown; (3) desire for personalized information; (4) varying degrees of information needs; (5) fear as a motivator versus stressor; and (6) high information needs on life after treatment. Conclusions: The patient experience must be considered through the full care trajectory and into survivorship to provide the right information to the correct patient at the optimal time. Patient journey mapping may be a novel approach to exploring the temporal relationship between information needs and the patient experience along the cancer continuum to uncover opportune moments, from the patient perspective, for knowledge and supportive care intervention. The model of psychological adjustment by Calver et al. (2019) can be considered to inform the delivery of cancer care information in a method recognizing the patient as the ultimate knowledge holder. Experience Framework This article is associated with the Patient, Family & Community Engagement lens of The Beryl Institute Experience Framework (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".