Evidence & trust
Evidence should become more useful without becoming less true.
The P4L Evidence and Trust Standard sets the public rules for claims, uncertainty, disclosure, AI use, correction, and how decision-oriented impact is measured.
Scope: This is a public communications and evidence-governance standard. It is not product certification, clinical validation, legal advice, regulatory clearance, or medical advice.
Truth before promotion. Evidence proportionality. Uncertainty visible. Humans accountable.
Why this standard exists
Healthspan and prevention innovation can move faster than shared language, trust, and institutional pathways. P4L uses this standard to govern how evidence is represented, uncertainty disclosed, relationships identified, AI used, errors corrected, and impact measured.
Twelve commitments
- Truth before promotion.
- Evidence proportionality.
- Review express and implied public meaning.
- Do not translate preclinical or mechanistic evidence into unproven human benefit.
- Distinguish biomarkers from meaningful functional and clinical outcomes.
- Keep material uncertainty visible.
- Match claims to the population and conditions studied.
- State regulatory, trial, peer-review, and investigational status accurately.
- Disclose relevant interests.
- Keep humans accountable for AI-assisted work.
- Correct material errors promptly and visibly.
- Measure decisions, adoption, and public value—not publicity volume alone.
Evidence labels
Established evidenceStrong human evidencePromising human evidencePreliminary human evidenceObservational / mechanisticPreclinical evidenceExpert hypothesisEvidence insufficient for the claim
Public invitation
P4L welcomes substantive proposals to improve its evidence, uncertainty, correction, and AI-governance practices. Material changes should be versioned and visible.