Older Adult Patients’ Experience of Care in a Dental School Clinic
Bibliographic record
Abstract
The aim of this study was to assess older adults' experience of care in an academic dental practice to identify opportunities to improve the patient experience for older adults. A cross-sectional descriptive survey design with a sample of adults aged 65 and older was conducted using the Consumer Assessment of Healthcare Providers and Systems Clinician and Group (CG-CAHPS) 12-month survey 2.0, with supplemental survey item sets addressing cultural competence and health literacy. A total of 850 older adults were invited to participate in the survey in fall 2016, and a 43% response rate was achieved. Overall, participants reported a positive experience of care and high ratings for their dental providers. Significant differences were found based on age, education level, race, and health status. A significantly more favorable experience of care was reported by patients aged 75 and older, as well as adults without any college education. Non-white patients were less likely to highly rate their dental providers and gave lower ratings for experiencing trust with their dental providers than white patients. Patients reporting good/fair/poor health were also less likely than those reporting very good/excellent health to highly rate their dental providers, and they gave lower ratings for patient-provider communication. This study demonstrated the feasibility of using the CG-CAHPS survey to assess the patient experience for older adults in an academic dental practice. Results identified opportunities for improving the dental practice and underscored the importance of enhancing dental curricula in areas of cultural competence, health literacy, and diversity.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".