Effects of Survey Mode on Results of a Patient Satisfaction Survey at the Observation Unit of an Acute Care Hospital in Singapore
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
INTRODUCTION: Over the years, surveys have become powerful tools for assessing a wide range of outcomes among patients. Healthcare managers and professionals now consider patient satisfaction as an outcome by itself. This study aims to determine if results of a patient satisfaction survey are affected by the manner by which the survey instrument is administered. MATERIALS AND METHODS: A patient satisfaction survey was conducted from May 2006 to October 2007 in a tertiary level acute care facility. All patients admitted to the observation unit during the study period were invited to participate. Using a contextualized version of the Consumer Assessment of Healthcare Providers and Systems (CAHPS) Hospital Survey, data was collected through either a phone interview, face to face interview or self-administered questionnaire. Each of these survey modes was administered during 3 different phases within the study period. RESULTS: Eight hundred thirty-two (832) patients were included in the survey. Based on results of univariate analysis, out of the 18 questions, responses to 11 (61.1%) were related to survey mode. Face-to-face interview resulted in the greatest proportion of socially desirable responses (72.7%), while phone interview yielded the highest proportion of socially undesirable responses (63.3%). After controlling for possible confounders, logistic regression results showed that responses to 55.6% of the questions were affected by survey mode. Variations in response between phone interview and self-administered questionnaire accounted for 87.5% of the observed differences. CONCLUSIONS: Researchers must be aware that the choice of survey method has serious implications on results of patient satisfaction surveys.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it