Using Machine Learning To Transform Therapy

May 30, 2023   |   Mental Health Professionals

In an age of AI and algorithms, finding a therapist typically still means searching online directories and making calls.

Megan Rozanski and Aditi Gaur, co-founders of Mind & Match, are determined to change that. 

“Netflix can recommend the best-fit content for me, and Tik Tok can learn my preferences. Yet the process of finding a therapist still feels like we’re in the Yellow Pages era,” says Rozanski.

Rozanski moved to five states in six years. Gaur’s journey was similar. With every move to a new college or job, they had to search for a new therapist. Telehealth was rare, and most therapists weren’t licensed in multiple states. 

The co-founders met at Stanford grad school and knew their therapy journeys mirrored the experience of most of their transient GenZ and Millennial peers.

Depression and anxiety rates in the U.S. were already increasing prior to the pandemic, disproportionately impacting the younger generations of GenZ and Millennials.

The exhaustion from repeatedly finding available new therapists, the right insurance and a good fit propelled Rozanski and Gaur to launch a better way to match clients with therapists. 

“We wanted to create a more recommendation-based platform that leverages existing research on what creates a good fit between a patient and therapist,” says Megan.


How online therapy matching works

Today, Mind & Match helps connect users each month with therapists from every state.

Users create a profile based on demographics and therapy preferences. The platform’s simple survey includes questions like: 

  • Individual or group therapy preference
  • Length of therapy
  • Method preferences about emotional intensity, therapist reactions and past or future-oriented
  • Likes and dislikes
  • Therapist identity
  • Finance and insurance

Questions are based on research from clinical psychologist John Norcross, PhD, on what categories of preferences contribute to the therapeutic alliance, improving therapy outcomes.

Clinicians set up a profile on the Mind & Match platform, answering their survey questions about therapy style and preferences. The platform uses client and therapist survey responses to facilitate matches. Within seconds, users are served six therapist matches they can contact through the app. Adjusting responses to any of the questions resets the matches.

The algorithm incorporates feedback from users who self-report satisfaction with their recommended matches, which will be used to continuously enrich the algorithm over time. “Our long-term vision is to create an unprecedented algorithm that learns about you and people like you over time. In the future, if someone with a similar profile joins the platform, we will know who might be best suited to help them,” says Gaur.

Therapists on the platform receive a summary of those users who choose to share it, which can be a solid starting point for determining if the match is a mutual fit.

Changes in therapy enable innovation

Two changes in the therapy landscape make Mind & Match possible: telehealth and the advancement of interstate compacts. The pandemic led to the widespread adoption of teletherapy, which made up
63 percent of all telehealth visits in 2022. 

Interstate licensure compacts allow clinicians to work in many more states without obtaining multiple licenses. For example, PSYPACT covers psychologists in 35 states, with more states enacting legislation to join. Psychologists who join the compact can practice interjurisdictional telepsychology across compact states. This enables clients who move often to continue therapy with the clinician they’ve come to know and trust, and also expands access.

Gaur and Rozanski realized clinicians targeting multiple geographic areas could not reach prospects in other states. Online directories are still location-based and oriented by state. Even searching for a therapist on Google is location-based.

“How do they find the best-fit clients when their catchment area is so much larger? We’re building this infrastructure to support that,” says Rozanski.


Algorithm-based therapy platform benefits clients and therapists

By making the process of finding a therapist easier, both Gaur and Rozanski hope to significantly minimize barriers to getting care. They also hope that making better therapy matches will allow more people to stay in treatment and achieve better outcomes.

In user interviews with mental health professionals, Gaur and Rozanski found that therapists were excited by the potential of improved matchmaking. “We’ve interviewed hundreds of psychologists, and the theme of wanting to specialize in treating a certain population or treatment area continues to come up as a pain point,” says Gaur.

Mind & Match helps therapists build their niche by matching them with their best-fit referrals.

As monthly users on Mind & Match grow, Gaur says the algorithm will continue to improve. Rozanski says that progress is key to reducing the barriers to access much-needed mental healthcare. “Frankly, 18 to 29-year-olds don’t want to pick up the phone. They prefer to tailor their preferences and see them in real time. We must help support this demographic that has consistently reported the highest rates of anxiety and depression and the greatest unmet need for counseling or therapy.”

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