as small as a text that comes in at an unusual time—increases
the chance of relapse in the next few days. Triggr does not even
need to know whom that text comes from or what it says. The
interruption of routine is the critical clue.
Triggr is collecting every piece of data it can on how to help
people resist an urge as it swells and then drops o;, and has taken
on the tricky task of building a system designed to work with
minimal human input while producing a service customized to
each participant. While algorithms may determine that a slip is
coming, intervening to stop it isn’t necessarily suited to automation. “Our goal is to make it as human as possible,” says Haskell.
Still, clients do sometimes ask the recovery coaches if they are
robots. Tasha Hedstrom did; Triggr responded by asking if she
was a robot. Humor is one of the techniques the algorithm has
determined work well with some participants.
The coaches are always testing messages sent to clients in
response to di;erent types of issues. Those that resonate are
shared with the engineering team; when a similar call comes
in later, the system will know to suggest that e;ective response.
Once Triggr determines that a person is in danger of relapsing,
it’s time for the really hard part: intervention to stop the self-destructive behavior. Humans do oversee the interaction, but
when someone’s risk is rising, a member of the recovery team is
automatically alerted to the most e;ective way to reach out to
that client and the type of message to which he or she is most
likely to respond. This is as close to Haskell’s idea of digital intuition as Triggr has come so far.
A big focus for Haskell is developing connections to community
service organizations, and on a wet morning in January, he was
standing in a conference room in Framingham, Massachusetts,
excitedly explaining the app to a group of counselors from the
South Middlesex Opportunity Council (SMOC), a local nonprofit. SMOC had just launched Triggr as part of a program to
connect with drug users in the emergency room after they have
overdosed. Like many parts of the Northeast, the Midwest, and
Appalachia, Framingham is su;ering a rising number of opioid-related overdoses: they now average 10 a month.
Some counselors in the room worried that not all potential
clients have smartphones. Others wanted a service Triggr does
not o;er: alerts when a client has contacted a drug dealer or
used drugs again. Haskell had answers for every question, but a
month and a half after the presentation, Krystin Fraser, who is
running the grant, said that of the first eight people who signed
up, only one agreed to download Triggr. Some do not have a
smartphone, she explained, while others simply do not want
someone watching them. Over the next month, 13 more people
signed up for the app.
Most health apps are not regulated by the Food and Drug
Administration and the company has chosen not to publish
any clinical trials of its platform, something it is not required
to do. It is tracking the long-term outcomes for people who use
Triggr, and its decision does put the burden on the company to
show that it really has made something extraordinary. It is in a
crowded field. “There’s been a glut of mental-health apps, most
of questionable use and e;cacy,” says John Torous, a director of
the digital psychiatry program at Boston’s Beth Israel Deacon-
ess Medical Center. Torous is part of a study using passive phone
data to follow people su;ering from schizophrenia, a mental
disorder that is quite di;erent from addiction but can feature
similar underlying behavior, such as disrupted sleep. “People
underestimate how complex it is to work with this data,” says
Torous. “We’ve had mass-market smartphones for 10 years and
we still haven’t revolutionized mental-health care. If this were
as easy as building an app, in 10 years it would have been done.
People are complex. We can collect all this data, but how do we
analyze it in a valid way?”
Jukka-Pekka Onnela, a professor of biostatistics at Har-
vard’s T.H. Chan School of Public Health and Torous’s collabo-
rator on the schizophrenia study, is more optimistic. As people
use phones for more and more daily needs such as schedules,
navigation, and communication, the data from these devices
becomes “very, very powerful,” Onnela says. That’s especially so
for conditions where behavior is strongly influenced by a per-
son’s surroundings and recent history, as it is for people with
psychological disorders or addiction.
When they’re awake, people’s phone screens may be on more
than 20 times an hour. Onnela has found that frequency to be a
reliable indicator of sleep patterns, something essential to understanding psychological illness and treating it.
“In the past a lot of measurement has been confined to labs
or doctor’s o;ces,” says Onnela. “What we are trying to do is to
capture symptoms in the wild, the way people actually experience their lives.”
Nanette Byrnes is MIT Technology Review’s senior editor for