The experience of head and neck cancer survivorship (including laryngectomy): an integrated biopsychosocial model
Bibliographic record
Abstract
PURPOSE OF REVIEW: The head and neck cancer (HNC) survivorship experience is unique among cancer populations. This review seeks to explore the HNC survivor experience associated with altered upper aerodigestive tract (UADT) function using principles of survivorship. RECENT FINDINGS: HNC survivors experience complex physical, functional, and psychosocial challenges related to UADT dysfunction. Interventions need to address all of these dimensions being mindful of the survivor experience. Studies reveal related unmet needs of both HNC survivors and their family members. An expose of the HNC survivorship experience is timely since 2016/2017 contains the release of landmark position papers and guidelines in the field. These address the unique challenges faced by the HNC population, their management, and the triad psychosocial, functional, and physical survivor burden. Such developments will drive future care. SUMMARY: The head and neck survivorship experience is characterized by complex changes with broad impact when examined in an experiential framework. HNC survivor care demands clinical excellence from multiple disciplines that are positioned to enact recent HNC guidelines and adopt survivorship principles. Future research in this population that explores experiential aspects of altered UADT function would be valuable in informing clinical practice. A biopsychosocial framework is presented for conceptualizing the HNC survivorship experience.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".