Systematic Review of Questionnaires Measuring Patient Satisfaction in Ambulatory Anesthesia
Bibliographic record
Abstract
BACKGROUND: Patient satisfaction has become an important component of quality improvement in ambulatory anesthesia services. However, it is difficult to measure due to its subjective and complex psychological construct. Psychometric methodology has been successfully used to evaluate this outcome. The authors conducted a systematic review to evaluate questionnaires to measure patient satisfaction with ambulatory anesthesia. METHODS: A systematic literature search of The Cochrane Library, MEDLINE, EMBASE, CINAHL, HAPI, PsycINFO, and Dissertation Abstracts was performed to identify studies on questionnaires evaluating patient satisfaction after ambulatory anesthesia. The authors included the articles that used multiple-item questionnaires, and the questionnaires were assessed with the strategy of psychometric questionnaire construction, validity, reliability, and acceptability. RESULTS: The authors scanned 131 articles yielded by our search strategy. Eleven articles were included in the study. Two questionnaires, IOWA Satisfaction with Anesthesia Scale and Evaluation du Vecu de I'Anesthesie Generale, fulfilled the criteria, but the latter was not developed specifically for ambulatory anesthesia, whereas Iowa Satisfaction with Anesthesia Scale was designed only for monitored anesthesia patients. CONCLUSIONS: In a large number of trials, patient satisfaction has been evaluated using overall satisfaction or nonvalidated questionnaires. Only a few studies have developed questionnaires with rigorous psychometric methods to measure patient satisfaction with anesthesia care. At this time, there is still no valid or reliable questionnaire for measuring patient satisfaction in ambulatory anesthesia. Further study should be conducted to develop standardized instruments to measure this outcome.
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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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".