Cambridge, Massachusetts-based HealthRhythms has received a $2.1 million grant from the NIH to continue investigating smartphone-based behavioral health interventions.

By passively collecting various areas of users’ daily patterns, such as physical activity, sleep, and frequency of social interactions, the company aims to combat users’ depression or anxiety with behavioral suggestions customized to the individual and their routines.

"Many [digital mental health interventions] provide pretty generic information, things like ‘try to sleep between seven and nine hours a night,’” Mark Matthews, chief technology officer at HealthRhythms, told MobiHealthNews. “So, it’s on the patient to improvise the intervention with the information they are receiving so that it is relevant to them and actionable, and unless you have access to psychotherapists or a particularly observant psychiatrist, that process itself might never even happen.”

Starting from diet and physical research conducted at HealthRhythms CEO Tandem Choudhury’s lab at Cornell, Matthews said that the company now has a developed a behavior-focused algorithm and platform called Measure that is currently being fine-tuned through testing at the University of Utah. The grant money, he explained, will be primarily funding a randomized controlled trial of the refined companion product, called Cue. This study will enroll depression patients into a 14 week program, and will also be conducted at the University of Utah.

What Matthews said sets HealthRhythms’ platform apart from the other lifestyle suggestions, passive monitoring services, and mental health apps on mobile marketplaces is its adaptiveness. After observing a user’s behavior, HealthRhythms' platform will offer unique suggestions that take previous behavior or symptoms of mental illness into consideration.

“[The algorithm] will look at your lifestyle that you’re engaging in and suggests small changes based on what you’re already doing,” he explained. “So, instead of 10,000 steps a day, which is generic, we would go ‘Look, based on what we’re seeing you do right now and the degree of physical activity that you engage in when you’re in a better place, we suggest 8,400 steps.’”

The platform will also try to unobtrusively fit these suggestions into a users’ daily routine, Matthews said. For instance, if a user is taking a bus to work, the platform might suggest exiting a stop early to work toward an activity goal.

While not all of the platform’s suggestions will be specifically fitness-based, Matthews said that the bus example is a good way to illustrate how a clearly defined behavior suggestion, customized for the individual, could be more effective for users.

“For this kind of thing, having examples really makes a difference,” he said. “Personalization of the health information makes it significantly different on how people process information that’s been given and how they act on it, even going so far as to the level of whether someone would trust this information, or think it’s even relevant.”

After testing their platform, the NIH funding will also be used to bring HealthRhythms’ platform to commercial markets. Once ready, Matthews said that he hopes it can be implemented within multiple levels of care, and for patients with varying forms of mental illness.

“Obviously there’s a huge variation when it comes to depression, different kinds of depression, it affects from all walks of life regardless of socioeconomic background,” he said. “Ultimately we see that we are trying to develop tools that make a difference in day to day life.”