Report · AI & Tech

Half of Americans didn't turn to large language models for health questions in the past year

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A slim majority of Americans (51%) say they have not used a large language model such as ChatGPT, Gemini, or Claude for health-related information in the past year. The question went to a randomly assigned half sample, 510 U.S. adults, in a Verasight survey conducted June 25-30, 2025.

Another 20% say they have used one just once or twice in that span, 12% report using one once or twice a month, and 17% report at least weekly use, including 3% who say every day.

Topline

single choice

Topline distribution

Half of Americans didn't turn to large language models for health questions in the past year.

In the past year, how often have you used a large language model (e.g., ChatGPT, Gemini, Claude) to get health-related information?

  • Never 50.9%
  • Once or twice 20.0%
  • Once or twice a month 12.4%
  • Once or twice a week 8.5%
  • Many times a week 5.0%
  • Every day 3.1%

2025 · base n 510 · +/- 5.3%

ICA Conference Omnibus Survey #2025-058

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Methodology

Full methodology
Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting
Field dates
2025-06-25 → 2025-06-30
Base (unweighted)
510
Margin of error
+/- 5.3%
Module
ICA Conference Omnibus Survey #2025-058

Source

Citation

ICA Conference Omnibus Survey #2025-058, fielded June 25-30, 2025, N=510 US adults age 18+, +/- 5.3%.

https://verasight-ica-2025.tiiny.co

Verasight survey methodology

How Verasight conducts surveys.

This page describes the Verasight general survey contract, separate from how the Data Library packages it. When a wave report is published, its field dates, sample sizes, and module breakdown are listed in that report.

Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting.
Population
US adults age 18+.
Sample design
Surveys are run as omnibus or single-topic waves. Omnibus waves are split into modules with their own respondent set, typically around one thousand respondents per module.
Field window
Each wave specifies its own field dates. Most omnibus waves field across roughly two weeks.
Weighting
Per-module weighting to CPS targets including age, race and ethnicity, sex, income, education, region, and metropolitan status.
Partisanship benchmark
Pew Research Center's NPORS benchmarking surveys, three-year running average.
Vote benchmark
2024 presidential vote population benchmarks.
Margin of error
Typically about plus or minus 3.4 to 3.6 percent per module at standard module sizes. Question-level MoE is recomputed when a base shrinks materially below the module baseline.
Reporting
The canonical report hub is reports.verasight.io. Verified legacy reports remain on their original hosts, and unpublished reports are marked pending.
Transparency
Verasight is a member of the American Association for Public Opinion Research Transparency Initiative.

The canonical report hub is reports.verasight.io; older reports may remain on verified legacy hosts.