Impact of Incentives on Physician Participation in Research Surveys: Randomized Experiment
Bibliographic record
Abstract
BACKGROUND: Web-based surveys can be effective data collection instruments; however, participation is notoriously low, particularly among professionals such as physicians. Few studies have explored the impact of varying amounts of monetary incentives on survey completion. OBJECTIVE: This study aims to conduct a randomized study to assess how different incentive amounts influenced survey participation among neurologists in the United States. METHODS: We distributed a web-based survey using standardized email text to 21,753 individuals randomly divided into 5 equal groups (≈4351 per group). In phase 1, each group was assigned to receive either nothing or a gift card for US $10, $20, $50, or $75, which was noted in the email subject and text. After 4 reminders, phase 2 began and each remaining individual was offered a US $75 gift card to complete the survey. We calculated and compared the proportions who completed the survey by phase 1 arm, both before and after the incentive change, using a chi-square test. As a secondary outcome, we also looked at survey participation as opposed to completion. RESULTS: For the 20,820 emails delivered, 879 (4.2%) recipients completed the survey; of the 879 recipients, 622 (70.8%) were neurologists. Among the neurologists, most were male (412/622, 66.2%), White (430/622, 69.1%), non-Hispanic (592/622, 95.2%), graduates of American medical schools (465/622, 74.8%), and board certified (598/622, 96.1%). A total of 39.7% (247/622) completed their neurology residency more than 20 years ago, and 62.4% (388/622) practiced in an urban setting. For phase 1, the proportions of respondents completing the survey increased as the incentive amount increased (46/4185, 1.1%; 76/4165, 1.8%; 86/4160, 2.1%; 104/4162, 2.5%; and 119/4148, 2.9%, for US $0, $10, $20, $50, and $75, respectively; P<.001). In phase 2, the survey completion rate for the former US $0 arm increased to 3% (116/3928). Those originally offered US $10, $20, $50, and $75 who had not yet participated were less likely to participate compared with the former US $0 arm (116/3928, 3%; 90/3936, 2.3%; 80/3902, 2.1%; 88/3845, 2.3%; and 74/3878, 1.9%, for US $0, $10, $20, $50, and $75, respectively; P=.03). For our secondary outcome of survey participation, a trend similar to that of survey completion was observed in phase 1 (55/4185, 1.3%; 85/4165, 2%; 96/4160, 2.3%; 118/4162, 2.8%; and 135/4148, 3.3%, for US $0, $10, $20, $50, and $75, respectively; P<.001) and phase 2 (116/3928, 3%; 90/3936, 2.3%; 80/3902, 2.1%; 88/3845, 2.3%; and 86/3845, 2.2%, for US $0, $10, $20, $50, and $75, respectively; P=.10). CONCLUSIONS: As expected, monetary incentives can boost physician survey participation and completion, with a positive correlation between the amount offered and participation.
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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 | 0.283 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".