Clasp survey finds over 70% of healthcare students use betting platforms weekly

The poll of 1,000 respondents found many students are turning to betting, content creation and other non-traditional income sources as new federal loan caps tighten financing options.

Summary

More than 70% of healthcare students who use prediction markets or betting platforms do so at least a few times a week, a Clasp survey found, underscoring how financial strain is pushing some students toward non-traditional ways to fund tuition and living expenses. The survey of 1,000 U.S. healthcare students, fielded by Pollfish from June 16 to 28, showed that 27% had used a betting or prediction market platform and that 73% of those bettors used them at least a few times a week, including 15% who bet daily. About two-thirds of student bettors said winnings were real or potential school money, with 24% saying winnings were part of their plan to pay for school and 43% saying they could help. The report said 69% started using the platforms to make extra money for school or living expenses, while only 40% said they were net positive and half said they roughly broke even. DraftKings, Kalshi, FanDuel and Polymarket were among the main platforms cited. Clasp also found that 56% of respondents relied on at least one other non-traditional income source, including heavy credit card use, content creation on platforms such as TikTok, YouTube, OnlyFans or Substack, AI data labeling, and sperm or egg donation. The findings were released as new federal graduate loan caps took effect on July 1, limiting annual borrowing for nursing and allied health students to $20,500, versus up to $50,000 for students in professional programs such as law and medicine. The survey found 52% had never heard of the new caps and only 32% knew their programs faced lower borrowing limits. Clasp CEO Tess Michaels said students are not treating betting as entertainment but as part of their tuition strategy, even though most are barely breaking even.

Terms & Concepts
  • prediction markets: Event-based trading venues where people speculate on future outcomes.
  • AI data labeling: Work that involves tagging or sorting data used to train artificial intelligence models.
  • borrowing limits: Caps on the amount students can borrow through loan programs.