Annual index · lawful aggregate data · AI and mental health
World AI & Mental Health Index by MentalCraft
An annual report on AI literacy, AI agent readiness, reflection load, and health-advice trust, interpreted with legal data collection and local context.
Publication gate
Embargoed
Annual reports should be generated as private drafts first, then released only after paper timing and owner approval are clear.
Data source Aggregate only
Privacy threshold Required
Owner approval Required before publication
Annual report modules
Yearly reports can be generated automatically from aggregate data, but stay private until the owner approves release after any paper embargo.
Data collection
Lawful data collection
Ordinary screening is not enrollment in a study. Optional analytics and saved history are governed by the privacy notice, consent where required, data minimization, and access or deletion paths.
Commercial model
Sustainable business model
Self-checks stay accessible without checkout, while revenue can come from optional guides, transparent post-result referral partners, annual aggregate index reports, and institutional tools without ad surveillance.
Free self-checks with optional paid guides
Transparent referral or affiliate partners after results
Annual aggregate index reports with owner release approval
Institutional tools with rights-preserving data practices
No dark patterns or ad surveillance
Start with AI literacy baseline
The AI literacy self-check is the cleanest baseline before the annual index work expands.