Getting a Valid Survey Response From 662 Plastic Surgeons in the 21st Century
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: Web-based surveys save time and money. As electronic questionnaires have increased in popularity, telephone and mailed surveys have declined. With any survey, a response rate of 75% or greater is critical for the validity of any study. We wanted to determine which survey method achieved the highest response among academic plastic surgeons. METHODS: All American Association of Plastic Surgeons members were surveyed regarding authorship issues. They were randomly assigned to receive the questionnaire through 1 of 4 methods: (A) emailed with a link to an online survey; (B) regular mail; (C) regular mail + $1 bill, and (D) regular mail + $5 bill. Two weeks after the initial mailing, the number of responses was collected, and nonresponders were contacted to remind them to participate. The study was closed after 10 weeks. Survey costs were calculated based on the actual cost of sending the initial survey, including stationary, printing, postage (groups B-D), labor, and cost of any financial incentives. Cost of reminders to nonresponders was calculated at $5 per reminder, giving a total survey cost. RESULTS: Of 662 surveys sent, 54 were returned because of incorrect address/email, retirement, or death. Four hundred seventeen of the remaining 608 surveys were returned and analyzed. The response rate was lowest in the online group and highest in those mailed with a monetary incentive. CONCLUSIONS: Despite the convenience and low initial cost of web-based surveys, this generated the lowest response. We obtained statistically significant response rates (79% and 84%) only by using postal mail with monetary incentives and reminders. The inclusion of a $1 bill represented the greatest value and cost-effective survey method, based on cost per response.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.199 | 0.619 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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