crisis-detection-intervention-ai

name	crisis-detection-intervention-ai
description	Detect crisis signals in user content using NLP, mental health sentiment analysis, and safe intervention protocols. Implements suicide ideation detection, automated escalation, and crisis resource integration. Use for mental health apps, recovery platforms, support communities. Activate on "crisis detection", "suicide prevention", "mental health NLP", "intervention protocol". NOT for general sentiment analysis, medical diagnosis, or replacing professional help.
allowed-tools	Read,Write,Edit,Bash(npm:*)
metadata	{"category":"Lifestyle & Personal","tags":["crisis","detection","intervention","crisis-detection","suicide-prevention"],"pairs-with":[{"skill":"crisis-response-protocol","reason":"Detection identifies the crisis; response protocol determines the safe intervention"},{"skill":"sober-addict-protector","reason":"Relapse crisis signals require the same NLP detection patterns as general crisis detection"},{"skill":"clinical-diagnostic-reasoning","reason":"Bias-aware clinical reasoning improves accuracy of crisis signal classification"}]}

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:  });
}

---

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.( {
  db..({
    : { : .() }
  });
});

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);
        }
      },  *  * );

      
       (detection.);
      ;

     .:
      
       ({ severity, :  });

      
       (detection.);
      ;

     .:
      
       ({ :  });

      
       (detection., );
      ;

     .:
      
       ({ :  });
      ;
  }

  
   ({
    : detection.,
    severity,
    : [, ],
    : .()
  });
}

---

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
   sentiment =  (text);
   hasHopelessness = .(text);

   (sentiment. < - && hasHopelessness) {
    signals.({
      : ,
      : ,
      : []
    });
  }

   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

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