995 Participant Responses on Media Exposure and AI Healthcare Attitudes

995 participants in an online experiment examined how media narratives shape public views of AI-assisted healthcare in China. The dataset includes experimental conditions, manipulation checks, pre-existing trust, attitudes, risk perceptions, and demographics. Fangzhou Zhou published the data on figshare in June 2026.

Use Cases

• Analyze persuasive effects of different positive media narratives based on manipulated media valence.
• Examine the influence of technical explanations on public evaluations based on the technical transparency variable.
• Assess how risk disclosure shapes perceived risk and attitudes based on the risk disclosure manipulation.
• Study demographic correlates of trust and attitudes toward AI-assisted healthcare.

Strengths

• Data from a controlled between-subjects experiment with 995 participants.
• Includes three manipulated media features: valence, technical transparency, and risk disclosure.
• Contains multiple measured variables: manipulation checks, pre-existing trust, attitudes, and risk perceptions.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect geographic bias inherent to its focus on China.

Provenance

Source

figshare

Collection Method

Online experiment (Study 2 of a two-study project).

Freshness

Last updated 2026-06-01 03:17:53; freshness should be verified.

Geography

China