Oral Health in Adult Patients Receiving Palliative Care: A Mixed Method Study
Bibliographic record
Abstract
BACKGROUND: Oral disease is highly prevalent in persons receiving palliative care (PRPC). Yet, little is known about how PRPC perceive their oral health status and related treatment needs. METHODS: This mixed-method study included 49 English-speaking PRPC (age≥18) recruited from the University of Iowa Palliative Care Clinic. Participants first completed a structured review of oral symptoms, followed by an oral exam. A nested sample of 11 participants also completed a semi-structured, in-depth interview querying their perceived oral health concerns and related treatment needs. Quantitative and qualitative data was analyzed and integrated for interpretation. RESULTS: Participants averaged 58.4 years. Nearly 70% had terminal cancer and 25% had advanced organ failure. Eighty-six percent of participants reported at least one oral symptom, including dry mouth (83.7%), a pain-related symptom (40.8%), or oral function difficulties (51.0%). Among the 31 dentate participants, 52% had untreated decayed/broken teeth and 33.3% had oral soft tissue lesions. Ill-fitting dentures and denture sores were common among denture users. About 40% of participants reported compromised health and/or quality of life due to oral conditions; however, the perceived impacts were modest. With the exception of painful conditions, oral treatment was not a priority for most of the participants. CONCLUSION: Oral disease was highly prevalent in PRPC, yet its overall impact was modest. In the absence of painful symptoms, most participants reported limited desire to seek treatment for oral health conditions. However, given the serious impacts of untreated oral diseases, oral healthcare decision should not be based solely on self-reported symptoms or distress.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".