Now research is being done on the passive monitoring of patients, Appelbaum says. A smartphone could be used to remotely track changes in someone’s speech or movement. People in the throes of mania, for example, often talk more quickly, and they sometimes roam about at all hours of the night. Conversely, depressed people sometimes stay too still, planting in bed or on the couch for days. “There are also many apps that have been developed that involve input from the patient: information about mood or thoughts or behavior, which can be monitored remotely for changes in their status,” Appelbaum says.
Birnbaum imagines a future in which his severely mentally ill patients might give him access to their digital footprint—including wearables, Facebook, and wherever else they live their lives online—so that he and his team could intervene if they begin to see signs of a psychotic relapse. “We know the earlier we intervene, the better the outcome,” Birnbaum says.
Anything involving doctors prying into their patients’ online lives could be done only with patient consent, most experts agree. Real, unresolved issues will come up if any of this ever comes to fruition, such as what happens if a patient revokes consent during a psychotic relapse, or how much social-media evidence can be weighed in hospitalization decisions, or even whether social media, with its jokes and memes and grandstanding, is a good mirror for anyone’s real mental state at all. Long before any of this happens, Birnbaum says, organizations such as the American Psychiatric Association should determine what the ethics and best practices are around monitoring patients’ social-media posts, so that patients’ rights can be protected even as their health is safeguarded.
That likely won’t be necessary for many years. Several experts I spoke with said they don’t know of any psychologists who monitor patients’ social-media data in a systematic way. And no one algorithm currently works well enough to accurately predict mental-health issues for an entire practice’s worth of patients based on social-media posts alone. (What would a hypothetical intervention even look like? A midnight drop-by with a sedative?)
One particularly cringeworthy example came in 2014, when an app made by a British charity meant to predict suicide risk from the use of phrases such as help me on Twitter was swiftly pulled after it was overrun by trolls and false positives (for example, “Someone help me understand why the bus is always late”). This type of technology, while promising, says Mike Conway, a professor at the University of Utah School of Medicine, “is not ready for prime time.”
The day that it is, our doctors might deduce a lot about our mental states from our random updates. And so will we. In fact, the most important beneficiary of this kind of technology could be the average social-media user. It’s rare that in any given tweet you’d admit, “I’m lonely.” Instead, looking at all of your online missives over time could provide clues to your deepest subconscious urges, like a modern-day Rorschach painted with your own words.