Can prosthodontic rehabilitation support social eating and return to work in head and neck cancer survivors? A scoping review
Bibliographic record
Abstract
PURPOSE: Oral dysfunction following head and neck cancer (HNC) treatment is a significant barrier for survivors attempting to return to work. Prosthodontic rehabilitation, including the replacement of missing teeth, plays a crucial role in restoring oral functions and addressing social eating, aesthetics, and functional limitations, potentially aiding survivors' re-entry into the workforce. This scoping review aims to map literature exploring the role of prosthodontic rehabilitation in facilitating social eating and return to work in HNC survivors. METHODS: We systematically searched MEDLINE, CINAHL, and PsycINFO databases up to February 15, 2024, for studies on return to work or social eating in HNC survivors, with a focus on tooth loss and prosthodontic rehabilitation post-treatment. An updated search was conducted on June 11, 2025. RESULTS: Thirteen studies were eligible, including four qualitative and nine quantitative works. Findings indicate a lack of studies directly linking prosthodontic rehabilitation to return to work and social eating. Limited quantitative data suggest that HNC survivors with dental prostheses, particularly implant-supported dentures, report fewer difficulties with social eating and employment compared to non-users. Qualitative data show that survivors value prosthodontic rehabilitation, particularly once their cancer is under control. CONCLUSIONS: While limited, available evidence suggests that prosthodontic rehabilitation improves HNC survivors' social eating, self-confidence, and quality of life, facilitating re-entry into the workforce. Implant-supported prostheses appear to offer better outcomes, enhancing social interactions and food choices. IMPLICATIONS FOR CANCER SURVIVORS: Functional dental prostheses enhance self-confidence in public eating and social interactions, highlighting their role in long-term well-being and survivorship.
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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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".