Crisis Text Line was built from the ground up around technology and data. We've collected one of the largest health data sets in the world.
Ultimately, our goal is to use data to improve outcomes for people in crisis. To achieve this, we use data in two ways: (1) internally, to improve the quality of our service, and (2) externally, to improve the crisis space as a whole.
We find ways in which data can support our Crisis Responders. They are on the front line, talking with thousands of texters in crisis every day. We use data to help them focus on doing what they do best: talking to texters in crisis. Here are a few ways.
+ Continuous Improvement of Training
Every day, our data reveals new patterns in what it means to provide effective crisis intervention by text. For example, we’ve found that Crisis Responders who geniunely identify texter strengths (e.g., “you showed courage texting us.”) achieve higher satisfaction ratings from texters. Our data show that three most effective terms to use are brave, smart, and proud. (E.g., “That was brave of you to reach out to a friend.”)
+ Helping The Highest-Risk Texters First
Most crisis lines respond to texters in the order in which they arrive. We act more like a hospital emergency room, where a person with gun shot wound gets helped before a person with a broken leg. We call it texter triage. An algorithm runs in the background, and assesses a texter’s suicidal risk based on their first few messages. Texters at high risk get marked as “code orange” and move to #1 in the queue. During the Presidential Election, when we saw volume 8x our normal, we were still able to reach high risk texters in an average of 39 seconds. Shorter wait times mean lives saved.
+ Texter Feedback
After every conversation, we ask texters if they want to share a message with their Crisis Responder. These messages often confirm the impact the Crisis Responder has had on a texter’s life. Here’s an example: “Kindness is magic and you’re a magician.”
We share data to support smarter research, policy, and community organizing. Unlike other large-scale datasets on mental health and crisis, our data has incredible volume, velocity, and variety. We're excited to share aggregated, anonymized data as our Canadian dataset grows!