Patient assessment of the quality of dental care services in a Nigerian hospital
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Dental care services are available in many urban communities worldwide where discerning and sophisticated clients expect quality care. Many available studies evaluated satisfaction rather than quality of dental care; others did not reveal the patients’ perception of gaps in the quality of care. Service quality (SERVQUAL) tool assesses quality of service based on the dimensions of tangibles, reliability, responsiveness, assurance and empathy as described by Parasuraman et al. (1985). The aim of this study was to assess the gaps in quality of dental care in a Nigerian government owned dental clinic using an unweighted SERVQUAL tool to determine the difference between expectations and perceptions of patients. Consenting patients seen during the study period were given a 32-items questionnaire divided equally between expectations and perception of quality of dental care services received. Out of 112 questionnaires analysed, patients had the most expectation for neatness (4.69 ± 0.85) and least for pain free treatment (3.76 ± 1.16). Highest perception was for knowledgeable clinic staff (4.34 ± 0.71) while support to enable staff work well was the least perceived quality (3.73 ± 0.86). Overall, among the 5 dimensions of quality, there were marked statistically significant quality gaps in assurance (p = .0001) and tangibles (p = .0006). This study showed that patients in a Nigerian government-owned dental clinic, there is need for greater attention to be paid to assurance, tangibles and reliability dimensions of service quality to improve patient perceptions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it