Crisis Detection & Intervention AI

Expert in detecting mental health crises and implementing safe, ethical intervention protocols.

⚠️ ETHICAL DISCLAIMER

This skill assists with crisis detection, NOT crisis response.

✅ Appropriate uses:

• Flagging concerning content for human review

• Connecting users to professional resources

• Escalating to crisis counselors

• Providing immediate hotline information

❌ NOT a substitute for:

• Licensed therapists

• Emergency services (911)

• Medical diagnosis

• Professional mental health treatment

Always provide crisis hotlines: National Suicide Prevention Lifeline: 988

When to Use

✅ Use for:

• Mental health journaling apps

• Recovery community platforms

• Support group monitoring

• Online therapy platforms

• Crisis text line integration

❌ NOT for:

• General sentiment analysis (use standard tools)

• Medical diagnosis (not qualified)

• Automated responses without human review

• Replacing professional crisis counselors

Quick Decision Tree

Detected concerning content? ├── Immediate danger? → Escalate to crisis counselor + show 988 ├── Suicidal ideation? → Flag for review + show resources ├── Substance relapse? → Connect to sponsor + resources ├── Self-harm mention? → Gentle check-in + resources └── General distress? → Supportive response + resources

Technology Selection

NLP Models for Mental Health (2024)

Model Best For Accuracy Latency

MentalBERT Mental health text 89% 50ms

GPT-4 + Few-shot Crisis detection 92% 200ms

RoBERTa-Mental Depression detection 87% 40ms

Custom Fine-tuned BERT Domain-specific 90%+ 60ms

Timeline:

• 2019: BERT fine-tuned for mental health

• 2021: MentalBERT released

• 2023: GPT-4 shows strong zero-shot crisis detection

• 2024: Specialized models for specific conditions

Common Anti-Patterns

Anti-Pattern 1: Using Generic Sentiment Analysis

Novice thinking: "Negative sentiment = crisis"

Problem: Mental health language is nuanced, context-dependent.

Wrong approach:

// ❌ Generic sentiment misses mental health signals const sentiment = analyzeSentiment(text);

if (sentiment.score < -0.5) { alertCrisis(); // Too broad! }

Why wrong: "I'm tired" vs "I'm tired of living" - different meanings, same sentiment.

Correct approach:

// ✅ Mental health-specific model import { pipeline } from '@huggingface/transformers';

const detector = await pipeline('text-classification', 'mental/bert-base-uncased');

const result = await detector(text, { labels: ['suicidal_ideation', 'self_harm', 'substance_relapse', 'safe'] });

if (result[0].label === 'suicidal_ideation' && result[0].score > 0.8) { await escalateToCrisisCounselor({ text, confidence: result[0].score, timestamp: Date.now() });

// IMMEDIATELY show crisis resources showCrisisResources({ phone: '988', text: 'Text "HELLO" to 741741', chat: 'https://988lifeline.org/chat' }); }

Timeline context:

• 2015: Rule-based keyword matching

• 2020: BERT fine-tuning for mental health

• 2024: Multi-label models with context understanding

Anti-Pattern 2: Automated Responses Without Human Review

Problem: AI cannot replace empathy, may escalate distress.

Wrong approach:

// ❌ AI auto-responds to crisis if (isCrisis(text)) { await sendMessage(userId, "I'm concerned about you. Are you okay?"); }

Why wrong:

• Feels robotic, invalidating

• May increase distress

• No human judgment

Correct approach:

// ✅ Flag for human review, show resources if (isCrisis(text)) { // 1. Flag for counselor review await flagForReview({ userId, text, severity: 'high', detectedAt: Date.now(), requiresImmediate: true });

// 2. Notify on-call counselor await notifyOnCallCounselor({ userId, summary: 'Suicidal ideation detected', urgency: 'immediate' });

// 3. Show resources (no AI message) await showInAppResources({ type: 'crisis_support', resources: [ { name: '988 Suicide & Crisis Lifeline', link: 'tel:988' }, { name: 'Crisis Text Line', link: 'sms:741741' }, { name: 'Chat Now', link: 'https://988lifeline.org/chat' } ] });

// 4. DO NOT send automated "are you okay" message }

Human review flow:

AI Detection → Flag → On-call counselor notified → Human reaches out

Anti-Pattern 3: Not Providing Immediate Resources

Problem: User in crisis needs help NOW, not later.

Wrong approach:

// ❌ Just flags, no immediate help if (isCrisis(text)) { await logCrisisEvent(userId, text); // User left with no resources }

Correct approach:

// ✅ Immediate resources + escalation if (isCrisis(text)) { // Show resources IMMEDIATELY (blocking modal) await showCrisisModal({ title: 'Resources Available', resources: [ { name: '988 Suicide & Crisis Lifeline', description: 'Free, confidential support 24/7', action: 'tel:988', type: 'phone' }, { name: 'Crisis Text Line', description: 'Text support with trained counselor', action: 'sms:741741', message: 'HELLO', type: 'text' }, { name: 'Chat with counselor', description: 'Online chat support', action: 'https://988lifeline.org/chat', type: 'web' } ], dismissible: true, // User can close, but resources shown first analytics: { event: 'crisis_resources_shown', source: 'ai_detection' } });

// Then flag for follow-up await flagForReview({ userId, text, severity: 'high' }); }

Anti-Pattern 4: Storing Crisis Data Insecurely

Problem: Crisis content is extremely sensitive PHI.

Wrong approach:

// ❌ Plain text storage await db.logs.insert({ userId: user.id, type: 'crisis', content: text, // Stored in plain text! timestamp: Date.now() });

Why wrong: Data breach exposes most vulnerable moments.

Correct approach:

// ✅ Encrypted, access-logged, auto-deleted import { encrypt, decrypt } from './encryption';

await db.crisisEvents.insert({ id: generateId(), userId: hashUserId(user.id), // Hash, not plain ID contentHash: hashContent(text), // For deduplication only encryptedContent: encrypt(text, process.env.CRISIS_DATA_KEY), detectedAt: Date.now(), reviewedAt: null, reviewedBy: null, autoDeleteAt: Date.now() + (30 * 24 * 60 * 60 * 1000), // 30 days accessLog: [] });

// Log all access await logAccess({ eventId: crisisEvent.id, accessedBy: counselorId, accessedAt: Date.now(), reason: 'Review for follow-up', ipAddress: hashedIp });

// Auto-delete after retention period schedule.daily(() => { db.crisisEvents.deleteMany({ autoDeleteAt: { $lt: Date.now() } }); });

HIPAA Requirements:

• Encryption at rest and in transit

• Access logging

• Auto-deletion after retention period

• Minimum necessary access

Anti-Pattern 5: No Escalation Protocol

Problem: No clear path from detection to human intervention.

Wrong approach:

// ❌ Flags crisis but no escalation process if (isCrisis(text)) { await db.flags.insert({ userId, text, flaggedAt: Date.now() }); // Now what? Who responds? }

Correct approach:

// ✅ Clear escalation protocol enum CrisisSeverity { LOW = 'low', // Distress, no immediate danger MEDIUM = 'medium', // Self-harm thoughts, no plan HIGH = 'high', // Suicidal ideation with plan IMMEDIATE = 'immediate' // Imminent danger }

async function escalateCrisis(detection: CrisisDetection): Promise<void> { const severity = assessSeverity(detection);

switch (severity) { case CrisisSeverity.IMMEDIATE: // Notify on-call counselor (push notification) await notifyOnCall({ userId: detection.userId, severity, requiresResponse: 'immediate', text: detection.text });

  // Send SMS to backup on-call if no response in 5 min
  setTimeout(async () => {
    if (!await hasResponded(detection.id)) {
      await notifyBackupOnCall(detection);
    }
  }, 5 * 60 * 1000);

  // Show 988 modal (blocking)
  await show988Modal(detection.userId);
  break;

case CrisisSeverity.HIGH:
  // Notify on-call counselor (email + push)
  await notifyOnCall({ severity, requiresResponse: '1 hour' });

  // Show crisis resources
  await showCrisisResources(detection.userId);
  break;

case CrisisSeverity.MEDIUM:
  // Add to review queue for next business day
  await addToReviewQueue({ priority: 'high' });

  // Suggest self-help resources
  await suggestResources(detection.userId, 'coping_strategies');
  break;

case CrisisSeverity.LOW:
  // Add to review queue
  await addToReviewQueue({ priority: 'normal' });
  break;

}

// Always log for audit await logEscalation({ detectionId: detection.id, severity, actions: ['notified_on_call', 'showed_resources'], timestamp: Date.now() }); }

Implementation Patterns

Pattern 1: Multi-Signal Detection

interface CrisisSignal { type: 'suicidal_ideation' | 'self_harm' | 'substance_relapse' | 'severe_distress'; confidence: number; evidence: string[]; }

async function detectCrisisSignals(text: string): Promise<CrisisSignal[]> { const signals: CrisisSignal[] = [];

// Signal 1: NLP model const nlpResult = await mentalHealthNLP(text); if (nlpResult.score > 0.75) { signals.push({ type: nlpResult.label, confidence: nlpResult.score, evidence: ['NLP model detection'] }); }

// Signal 2: Keyword matching (backup) const keywords = detectKeywords(text); if (keywords.length > 0) { signals.push({ type: 'suicidal_ideation', confidence: 0.6, evidence: keywords }); }

// Signal 3: Sentiment + context const sentiment = await sentimentAnalysis(text); const hasHopelessness = /no (hope|point|reason|future)/i.test(text);

if (sentiment.score < -0.8 && hasHopelessness) { signals.push({ type: 'severe_distress', confidence: 0.7, evidence: ['Extreme negative sentiment + hopelessness language'] }); }

return signals; }

Pattern 2: Safe Keyword Matching

const CRISIS_KEYWORDS = { suicidal_ideation: [ /\b(kill|end|take)\s+(my|own)\s+life\b/i, /\bsuicide\b/i, /\bdon'?t\s+want\s+to\s+(live|be here|exist)\b/i, /\bbetter off dead\b/i ], self_harm: [ /\b(cut|cutting|hurt)\s+(myself|me)\b/i, /\bself[- ]harm\b/i ], substance_relapse: [ /\b(relapsed|used|drank)\s+(again|today)\b/i, /\bback on\s+(drugs|alcohol)\b/i ] };

function detectKeywords(text: string): string[] { const matches: string[] = [];

for (const [type, patterns] of Object.entries(CRISIS_KEYWORDS)) { for (const pattern of patterns) { if (pattern.test(text)) { matches.push(type); } } }

return [...new Set(matches)]; // Deduplicate }

Pattern 3: GPT-4 Few-Shot Detection

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });

async function detectWithClaude(text: string): Promise<CrisisDetection> { const response = await client.messages.create({ model: 'claude-3-5-sonnet-20241022', max_tokens: 200, messages: [{ role: 'user', content: `You are a mental health crisis detection system. Analyze this text for crisis signals.

Text: "${text}"

Respond in JSON: { "is_crisis": boolean, "severity": "none" | "low" | "medium" | "high" | "immediate", "signals": ["suicidal_ideation" | "self_harm" | "substance_relapse"], "confidence": 0.0-1.0, "reasoning": "brief explanation" }

Examples:

• "I'm thinking about ending it all" → { "is_crisis": true, "severity": "high", "signals": ["suicidal_ideation"], "confidence": 0.95 }

• "I relapsed today, feeling ashamed" → { "is_crisis": true, "severity": "medium", "signals": ["substance_relapse"], "confidence": 0.9 }

• "Had a tough day at work" → { "is_crisis": false, "severity": "none", "signals": [], "confidence": 0.95 }` }] });

  const result = JSON.parse(response.content[0].text); return result; }

Production Checklist

□ Mental health-specific NLP model (not generic sentiment) □ Human review required before automated action □ Crisis resources shown IMMEDIATELY (988, text line) □ Clear escalation protocol (severity-based) □ Encrypted storage of crisis content □ Access logging for all crisis data access □ Auto-deletion after retention period (30 days) □ On-call counselor notification system □ Backup notification if no response □ False positive tracking (improve model) □ Regular model evaluation with experts □ Ethics review board approval

When to Use vs Avoid

Scenario Appropriate?

Journaling app for recovery ✅ Yes - monitor for relapses

Support group chat ✅ Yes - flag concerning posts

Therapy platform messages ✅ Yes - assist therapists

Public social media ❌ No - privacy concerns

Replace human counselors ❌ Never - AI assists, doesn't replace

Medical diagnosis ❌ Never - not qualified

References

• /references/mental-health-nlp.md

• NLP models for mental health

• /references/intervention-protocols.md

• Evidence-based intervention strategies

• /references/crisis-resources.md

• Hotlines, text lines, and support services

Scripts

• scripts/crisis_detector.ts

• Real-time crisis detection system

• scripts/model_evaluator.ts

• Evaluate detection accuracy with test cases

This skill guides: Crisis detection | Mental health NLP | Intervention protocols | Suicide prevention | HIPAA compliance | Ethical AI