Identifying and Analyzing Bot-Generated Responses in Online Health Care Surveys: Methodological Study

The findings underscore the necessity of implementing bot prevention and detection methods in online health care surveys to preserve data integrity. Failure to do so risks distorting research conclusions, particularly in health equity studies where demographic misclassification may bias results. The study highlights effective bot detection strategies, including open-text analysis, timestamp evaluation, and geographic validation, and recommends integrating these techniques into survey design. As bots continue to evolve, ongoing advancements in bot prevention and detection will be crucial to maintaining the reliability of digital health research.