The organization’s quantified approach, based on five million texts, has already produced a unique collection of mental-health data. C.T.L. has found that depression peaks at 8 p.m., anxiety at 11 p.m., self-harm at 4 a.m., and substance abuse at 5 a.m. The organization is working on predictive analysis, which would allow counsellors to determine with a high degree of accuracy whether a texter from a particular area, writing in at a particular time, using particular words, was, say, high on methamphetamine or the victim of sex trafficking. A texter who uses the word “Mormon” tends to be reaching out about L.G.B.T.Q. issues.Out of consideration for texters’ anonymity, Crisis Text Line displays its findings only by state. (Arkansas ranks highest for eating disorders, Vermont for depression; suicidal thoughts are most common in Montana and least common in New Hampshire.) But eventually there will be enough data to allow the organization to confidently reveal Zip codes and area codes without the risk of making any single texter identifiable. Such a wealth of data is new in the field of mental health. Isaac Kohane, a pediatrician who also has a Ph.D. in computer science and is the co-director of the Center for Biomedical Informatics at Harvard Medical School, told me, “You cannot have accountable care—financially or morally accountable care—if you cannot count, and until recently we literally could not count with any degree of acceptable accuracy.” He added, “It’s been mind-boggling, to those of us who knew what was available, that Amazon and Netflix were creating a far more customized, data-driven, evidence-based experience for their consumers than medicine has.” … Lublin hopes that the data will eventually be useful to school districts and police departments. “The corpus of data has the volume, velocity, and variety to really draw meaningful conclusions.
The New Yorker reports on the Crisis Text Line.
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