Effect of prenotification on the response rate of a postal survey of emergency physicians: a randomised, controlled, assessor-blind trial
Bibliographic record
Abstract
OBJECTIVES: Response rates to physician surveys are typically low. The objective of this study was to determine the effect of a prenotification letter on the response rate of a postal survey of emergency physicians. DESIGN: This was a substudy of a national, cross-sectional postal survey sent to emergency physicians in Canada. We randomised participants to either receive a postal prenotification letter prior to the survey, or to no prenotification letter. PARTICIPANTS: A random sample of 500 emergency physicians in Canada. Participants were selected from the Canadian Medical Directory, a national medical directory which lists more than 99% of practising physicians in Canada. INTERVENTIONS: Using computer-generated randomisation, physicians were randomised in a concealed fashion to receive a prenotification letter approximately 1 week prior to the survey, or to not receive a prenotification letter. All physicians received an unconditional incentive of a $3 coffee card with the survey instrument. In both groups, non-respondents were sent reminder surveys approximately every 14 days and a special contact using Xpresspost during the final contact attempt. OUTCOME: The primary outcome was the survey response rate. RESULTS: 201 of 447 eligible physicians returned the survey (45.0%). Of 231 eligible physicians contacted in the prenotification group, 80 (34.6%) returned the survey and among 237 eligible physicians contacted in the no-prenotification group, 121 (51.1%) returned the survey (absolute difference in proportions 16.5%, 95% CI 2.5 to 30.5, p=0.01). CONCLUSION: Inclusion of a prenotification letter resulted in a lower response rate in this postal survey of emergency physicians. Given the added costs, time and effort required to send a prenotification letter, this study suggests that it may be more effective to omit the prenotification letter in physician postal surveys.
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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 | 0.013 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".