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Each conversation is guided by empathy, evidence, and structure. Volunteers listen to texters to help them feel valued, reflect, and find safe next steps. Every conversation is supported in real time by professional supervisors. By serving others, every responder becomes part of a growing social asset: a community of emotionally skilled people who carry greater resilience into their families, schools, workplaces, and communities. This dual impact of support for people in distress and skill-building for those who help is what makes the Crisis Text Line model so powerful. It’s not just crisis intervention; it’s community transformation at scale. The Crisis Text Line model operates through partnerships that extend reach, strengthen referral pathways, and disseminate insights to optimize impact across contexts. We collaborate with a broad network of community partners, public agencies, schools and universities, health and social service providers, governments, corporations, clinical and lived experience experts, all with the goal of strengthening mental health ecosystems. Insights that strengthen systems Crisis Text Line leverages powerful clinical research science and evaluation methods to deliver insights about wellbeing at scale. Collectively, each anonymized conversation contributes to our understanding of mental health in real time. Over the past decade, Crisis Text Line’s U.S. service has supported more than 11 million conversations. Each message represents a human story.
a crisis and an opportunity. Traditional systems cannot meet demand alone, and technology without humanity risks deepening loneliness and disconnection. What the world needs now are paradigms that rebuild brain health and social resilience while expanding access to care. Crisis Text Line operates at precisely this intersection. Its evidence-based, AI-enabled, volunteer-powered model uses technology to deliver rapid, clinically grounded support in moments of distress, while cultivating in thousands of everyday people the very skills that define a healthy brain economy. It is both a lifeline and a learning system, generating social and economic value by transforming crisis response into community strength. The model: technology meets humanity Launched in 2013, Crisis Text Line pioneered a new category of mental health support: real-time, text-based crisis response powered by trained volunteers, professional supervision, and aided by AI. It’s free, 24/7, confidential, and available by SMS, WhatsApp, or webchat in English and Spanish in the U.S. Anyone in distress can reach out to connect with a live, trained volunteer within minutes. Using AI-powered triage, the system instantly identifies the most urgent messages – those suggesting suicidal ideation or self-harm – and routes them to the top of the queue. It’s a simple but revolutionary formula: Technology for speed. People for connection. Science for wellbeing at scale.
Our insights reveal that our texters are diverse, often young, and frequently isolated from other forms of help. Nearly 45% of texters in the U.S. are under age 18, reflecting a generation that turns naturally to digital spaces for support. The issues that bring people to us are both universal and deeply personal. The most common reasons for reaching out include: • Relationships and family stress • Anxiety and stress
• Depression and sadness • Isolation and loneliness • Suicidal thoughts About one-quarter of all
conversations involve texters expressing suicidal ideation. Our volunteers and supervisors successfully de-escalate nearly all of these conversations: Fewer than one percent require emergency service intervention, a testament to the effectiveness of calm, compassionate human engagement in moments of acute crisis. Using AI, machine learning, and natural language processing, the organization’s clinical research team identifies emerging trends, risk patterns and effective conversational strategies. Recent models can: • Detect new planned suicide methods to inform public- health alerts. • Measure “emotional heat” to refine de-escalation training. • Analyze language patterns that convey genuine care to strengthen training. • Predict when a texter might disengage so supervisors can step in.
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