Source: Ambro/FreeDigitalPhotos.net

Do you feel like your therapist is judging you? Or is he or she among the best listeners in your life? Empathy is at the foundation of , but that doesn't mean all therapists do it well. New science says that algorithms may be able to detect how your therapist is.

In research just published in PLOS One [1], scientists looked at transcripts of 1,000 therapy sessions. They used this to build an algorithm that analyzed the language to assign an empathy score. This let them classify therapists as high-empathy or low-empathy.

The process starts with human experts analyzing those transcripts and labeling the therapists as high- or low-empathy. The algorithm studies the language, learns from the human's labels, and builds a model of what empathetic dialogue looks like.

The algorithm looked for phrases that indicated empathy. Phrases like “it sounds like,” “do you think,” and “what I’m hearing,” signaled high empathy. Saying things like “next question,” “you need to” and “during the past” ended up being signals of low empathy.

The results were very good. Researchers compared the algorithm's output to the scores human experts gave to the therapists. In this kind of work, accuracy is computed with a value called an F1-score. (Here, we will get a little technical) Essentially, it's a combination of the precision (what percentage of therapists were correctly labeled high-empathy out of everyone labeled high-empathy) and recall (what percentage of therapists were correctly labeled high-empathy out of all the high-empathy therapists). That value was 0.85 out of a possible high score of 1 - a very good result.

The implications of this research for therapy could be significant. Right now, the only way to evaluate therapists is to have a third person sit in on the session or review a transcript. This is not great for the patient, who may not want to have personal discussions in front of a stranger or whose privacy concerns may keep a transcript from review. The review also affects the way therapists behave; if they know they are being observed, they may treat a patient differently. With this technology, sessions can be analyzed on a much larger scale since no humans need to be involved. Transcripts would be kept private from any other humans, but could be analyzed by the algorithms quickly and on a large scale. That, in turn, can help therapists learn to be more empathetic or flag a low-empathy therapist for deeper human-based review and training.

[1] "Rate My Therapist": Automated Detection of Empathy in Drug and via Speech and Language Processing

Bo Xiao, Zac E. Imel , Panayiotis . Georgiou, David C. Atkins, Shrikanth S. Narayananhttp://journals.plos.org/plosone/article?id=10.1371/journal.pone.0143055