The service quality dimensions and patient satisfaction relationships in South Korea: comparisons across gender, age and types of service
Bibliographic record
Abstract
Purpose Aims to investigate the structural relationships between out‐patient satisfaction and service quality dimensions under a South Korea health care system where patients have substantial freedom in choosing their medical service providers and to further study the causal relationship between service quality and satisfaction between out‐patient subgroups obtained on the basis of gender, age and types of services received. Design/methodology/approach After assessing the construct validity of the service quality dimensions based on confirmatory factor analysis, a path model specifying the relationships between service quality dimensions and patient satisfaction was estimated. The next analysis was a series of multi‐sample analyses. A multigroup LISREL analysis was used to test the invariance of structural paths between service quality dimensions and patient satisfaction. Findings Results indicated that the general causal relationship between service quality and patient satisfaction was well supported in the South Korean health‐care delivery system. An examination of the estimated path coefficients showed that the pattern of relationships between service quality and patient satisfaction was similar across the gender, age, and service type subgroups. Results also revealed that the level of satisfaction, on the other hand, was not the same for subgroups when divided by age and the types of services received. Originality/value Since the majority of the past studies have been geographically concentrated in the countries in North America and Western Europe, the findings of this study expand understanding of the relationships between service quality and patient satisfaction.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".