Impact of Incentives on Physician Participation in Research Surveys: Randomized Experiment
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,088 | 0,130 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,004 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,005 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».