Design patterns for digital products that handle sensitive content, evidence, or high-stakes investigations. Grounded in SAMHSA's six trauma-informed care principles and applied to interaction design.
These patterns are for designers, researchers, and product teams building tools in high-stakes investigation, content moderation, abuse reporting, healthcare, and crisis services.
This repository applies the six principles from SAMHSA's Trauma-Informed Care framework (TIP 57) to digital product design:
- Safety - Users feel physically and psychologically safe using the product
- Trustworthiness and Transparency - Actions and system behavior are clear and predictable
- Peer Support - Users are not isolated; support resources are accessible when needed
- Collaboration and Mutuality - The product works with users, not at them
- Empowerment, Voice, and Choice - Users have meaningful control over their experience
- Cultural, Historical, and Gender Issues - The product respects diverse identities and contexts
See /principles for how each maps to digital design.
| Pattern | Category | Risk |
|---|---|---|
| Content Gating | Safety and Emotional Load | High |
| Gradual Exposure | Safety and Emotional Load | High |
| Calm Visual Tone | Safety and Emotional Load | Medium |
| Pause, Exit, and Recovery | Safety and Emotional Load | High |
| Evidence Provenance | Trust, Transparency, and Provenance | High |
| Explainable AI Output | Trust, Transparency, and Provenance | High |
| Self-Paced Workflows | Control, Agency, and Pacing | Medium |
| Progressive Disclosure | Control, Agency, and Pacing | Medium |
| Annotation and Distance | Control, Agency, and Pacing | High |
| Reversibility and Safe Errors | Control, Agency, and Pacing | High |
| Neutral Microcopy | Language, Microcopy, and Inclusivity | Medium |
| Least-Privilege Access | Privacy, Security, and Ethical Safeguards | High |
| High-Exposure Content Review | Investigator Wellness | High |
/principles SAMHSA principles applied to digital product design
/patterns Individual design patterns with guidance and research grounding
/audit Scorable checklist for high-stakes and investigative UI review
references.md Full citation list
Principles establish the framework. Read these first to understand the why behind the patterns.
Patterns are the implementation layer. Each pattern addresses a specific problem, provides design guidance, and is tagged by risk level.
Audit is a structured checklist for evaluating an existing product against these patterns. Use it in design reviews, heuristic evaluations, or research planning.
Each pattern is tagged:
- High - Failure directly causes re-traumatization, harm, or loss of legal integrity
- Medium - Failure increases cognitive load or reduces user control
- Low - Failure reduces quality but is recoverable without harm
Each pattern follows this structure:
- Problem - What goes wrong without this pattern
- Design guidance - What to do
- Do / Don't - Concrete implementation examples
- Risk level - High / Medium / Low
- Principles - Which SAMHSA principles this pattern serves
- Sources - Research citations
See references.md for the full citation list.
- ai-accountability-design-patterns: 12 accountability concepts for AI-assisted products: traceability, chain of custody, explainability, integrity, and more. The Evidence Provenance and Explainable AI Output patterns here map directly to Provenance, Explainability, and Chain of Custody there.
- conversational-ai-patterns: interaction design patterns for conversational AI, including HITL handoff design, auditable AI output, and scale triage for regulated evidence review.