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According to an article recently published in The Atlantic, data science is the new frontier in psychotherapy. Feedback-Informed Treatment (FIT) is a system in which client surveys are collected before every therapy session, and provide an independent and private way of determining if a client is improving or deteriorating. Performance feedback and data collection allows therapists to adjust the tools or tone of sessions to provide the best treatment for their client, similar to how performance metrics are used in athletics. In addition, statistical algorithms, developed from data on thousands of cases, can predict which patients will deteriorate or are at risk of suicide (often with greater accuracy than a mental health professional), and can alert the psychotherapist.
While not yet widely used, these advances could prove critical for improving a field such as psychotherapy. Progress in psychotherapy is plagued by a lack of performance feedback for psychotherapists because of the private nature of their work, and by ‘whitewashing’, a term that describes when patients suggest to their psychotherapist that treatment is effective while in reality the patient may actually be deteriorating.
Although studies show that FIT improves the effectiveness of psychotherapy, psychotherapists tend to be resistant to the quantification of something as nuanced and delicate as mental health and interpersonal therapist-client relationships. And granted, the system can be improved; developer and researcher Michael Lambert noted that his system only significantly improves therapy outcomes for patients at risk of deterioration.
Like any facet of technology, the more it is used and implemented, the better it will become. The use of data science in psychotherapy is a burgeoning field, and suggests that, as data scientists, we will be able to improve the effectiveness with which professionals can identify and treat mental health problems.