The Level of utilization and Satisfaction of Complete Denture Treatment Provided in Fiji from 2010-2016
Bibliographic record
Abstract
BACKGROUND: Wearing dentures helps rehabilitate the oral health status for the older people. Due to lack of previous data, this objective of this study was to determine the level of utilization and satisfaction of complete denture treatment at dental clinics in Fiji. MATERIALS & METHODS: A cross sectional descriptive study was conducted on 85 edentulous patients and dentures at the Fiji National University (FNU) teaching dental clinic from 2010-2016.Patients who utilized the dentures fabricated at FNU and identified as complete denture patients from 2010-2016 were included in this study. Data was collected using the denture assessment form and Oral Health Impact Profile for Edentulous Patients (OHIP-EDENT) questionnaire. Correlation test was done and p less than 0.05 was considered as level of significance. RESULTS: Participants were between the age range of 40-79 years with majority being male (54%). Greater level of satisfaction noted among 60-69 years male participants and those wearing the dentures for 3-4 years than other groups. Difficulty in chewing (40%) and food catching underneath the denture (33%) were common denture related complains. One thirds of participants reported of uncomfortable dentures while 24% had sore spots due to their dentures. More than two thirds of them, (71%) were unable to eat and enjoy food and for most patients, the vertical dimension (94%), esthetics assessment (94%), tooth selection (91%), boarder extension (78%), posterior seal (99%) and centric relation (99%) were acceptable. Patients with acceptable vertical dimension (46.1±7.6), acceptable esthetics (45.8±7.9) and boarder extension (48.0±7.2) showed greater satisfaction level compared to those with unacceptable denture characteristics. CONCLUSION: This study highlighted that satisfaction among recent denture wearers was low and majority participants portrayed poor understanding regarding denture aftercare and hygiene. It can be recommended for the teaching institutes and dental clinics to evaluate the quality of treatments and help to improve the quality of services being provided to the patients. Further study is needed to determine the in- depth perceptions of denture wearers. It also can be recommended for the patients to take heed of the post operative denture hygiene instructions being given.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".