How Big Data is Changing Psychotherapy

The digital age ushered in an unprecedented amount of data, generating analytical possibilities never before imagined. Dubbed big data, these data sets are massive, complex and require computer power to surpass traditional statistical approaches and instead identify interactions among sets of variables. Opportunities to leverage big data, from patient records data to social media platforms, stand to impact the psychotherapy field.

Rich Ivry, Chair of the Psychology Department at the University of California, Berkley, suggests in the Association for Psychological Science that the field will move to a data-driven approach, despite its roots as a theory-driven discipline. Ivry cites numerous areas contributing to big data in psychology. MRI studies generate data on mental activity, requiring analytics that interpret mental activity. We’ve deciphered the human genome, unveiling countless opportunities to examine how genes influence behavior.

At its core, big data presents an opportunity to better understand human behavior without the challenges traditional research poses, like self-reporting errors from research participants or substantial time investments from researchers for manual work. Here are a few specific ways big data can revolutionize therapy and counseling.

Feedback-Informed Treatment

At the forefront of big data is the opportunity to truly improve practicing professionals – without compromising the heavy regulations protecting privacy through laws and norms. Tony Rousmaniere notes in The Atlantic that because of the deeply personal – and sensitive – nature of psychotherapy, “therapists function largely in private, sheltered from objective feedback.” Without metrics to measure against, psychotherapists are left to rely on client feedback, which is largely misleading. Columbia University found in a recent survey that 70% of patients reported giving a rose-colored view to therapists whom they really didn’t find effective.

Enter feedback-informed-treatment (FIT), where with algorithms developed from big data patterns, computer-based surveys of patients can flag at-risk patients based on predicted outcomes – and eliminate the human error imposed by a patient’s desire to avoid disappointing a therapist, or a therapists’ “natural overconfidence and clinical blind spots,” Rousemaniere explains. What began 20 years ago as a single system from a Brigham Young University researcher has expanded today to more than 50 systems. In practice, this can be the difference between letting a deteriorating patient walk out the door, or continuing to probe until the truth is found.

Therapy Outcome Management System

Perhaps one of the biggest drivers of big data is the ever-present smartphone. In his Doctor of Psychology thesis for George Fox University, Timofey S. Galuza notes the Therapy Outcome Management System (TOMS) capitalizes on this with smartphone apps that collect effectiveness data in real-time, as opposed to relying on traditionally retrospective effectiveness studies that require participants to evaluate sessions after the fact. Through the TOMS app, patients provide real-time feedback on psychotherapy outcome and sessions on an iPhone or iPad.

Because of the adaptability, relative ease and prevalence of a smartphone app, previous issues like small sample size, are overcome with more public distribution – data could potentially be collected at the end of each session, by any professional with an iPhone or iPad, and is then anonymized and stored for further study.

With this ease of access also come questions of security (is de-identification occurring), ethics (how to handle the data), and validity (is the use widespread enough that data is reliable?). Ultimately, Galuza concludes, this technology fosters large, global sample sizes, and marries research and expertise in psychology.

Substance Abuse Counseling and Rehabilitation

In the rehabilitation sphere, big data provides the opportunity for predictive analytics, which forecast possible future outcomes from current and historic patient data. This can create national averages as benchmarks for therapists to measure patient process – and confirm if the patient is on track.

myPTsolutions, a therapist recruiting organization, argues this stands to help clinics estimate time frames for program completion, assess therapists’ professional skills against national averages, and ultimately, create measurable outcomes for the field. With data to back plans, therapists can better communicate expectations, and measure not only the progress of their patients, but their own expertise.

Suicide Prevention

In an area where potentially affected individuals are often excluded from clinic trials, big data stands to aid suicide prevention by aggregating medical history – and social media posts – to isolate patterns that may raise flags. Since  “the suicidal phenotype is characterized by extreme heterogeneity,” as Dr. Nicola Davies writes in Psychiatry Advisor, this type of large-scale measurement and analysis possesses enormous potential to revolutionize suicide prevention.

Measuring Depression

Big data can also correct problematic approaches to depression, which traditionally requires patients to report (and understand) their feelings and risks simplifying depression into a static state. On the other hand, aggregating data from social media, smartphones and wearable technology can revolutionize this approach by, for example, connecting a social media behavior to postpartum depression.

Even if big data overhauls the psychology field, Ivry advises students pursue training that will equip them to use the technology – but still ground themselves in psychological theory. Big data stands to eliminate human error and improve treatment rates and feedback with computer-assisted algorithms, but also raises ethical, legal and moral issues that require human decision-making skills. And ultimately, the field will still need experts to respond to the predictions and implement effective, new procedures aimed at improving patients’ treatment.

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