Measuring patient satisfaction in complex continuing care/rehabilitation care
Bibliographic record
Abstract
Purpose - The purpose of this paper is to develop a psychometrically validated survey to assess satisfaction in complex continuing care (CCC)/rehabilitation patients. Design/methodology/approach - A paper or computer-based survey was administered to 252 CCC/rehabilitation patients (i.e. post-acute hospital care setting for people who require ongoing care before returning home) across two hospitals in Toronto, Ontario, Canada. Findings - Using factor analysis, five domains were identified with loadings above 0.4 for all but one item. Behavioral intention and information/communication showed the lowest patient satisfaction, while patient centredness the highest. Each domain correlated positively and significantly predicted overall satisfaction, with quality and safety showing the strongest predictive power and the healing environment the weakest. Gender made a significant contribution to predicting overall satisfaction, but age did not. Research limitations/implications - Results provide evidence of the survey's psychometric properties. Owing to a small sample, supplemental testing with a larger patient group is required to confirm the five-factor structure and to assess test-retest reliability. Originality/value - Improving the health system requires integrating patient perspectives. The patient experience, however, will vary depending on the population being served. This is the first psychometrically validated survey specific to a smaller specialty patient group receiving care at a CCC/rehabilitation facility in Canada.
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How this classification was reachedexpand
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".