Ways of Knowing: From Subjective Judgment to Objective Data

I have supervised psychology students in training programs and have been disturbed by the range of competency that I witnessed. Some have been smart and empathic, every bit as good at helping people as I imagined myself to be. I saw evidence for the idea that some people are natural-born healers.

I also saw people who were so inept as to be alarming. In one instance, I explored whether I could provide a recommendation to block an individual from receiving a doctoral degree upon completing a final training program. I could not, in large part because I had entered the organization too late in the training year.

However, the question should be raised as to what would give my judgment weight at such an important juncture in a person’s life. My opinion may not have been shared by other previous supervisors. What would be the basis for letting my judgment determine the issue? Was my position based on my subjective experience, my gut, or on any objective data about this person’s performance? It was all gut.

I can also recall that in my own professional training, there was never any objective data intruding on a purely subjective discussion of my therapy sessions. I played tape recordings of my sessions with supervisors and we discussed my degree of empathy and the accuracy of my interpretations. We discussed my formulation of a case and how I was approaching treatment. We had all sorts of discussion, but no measurement of anything.

Clinical research depends on measurement

Clinical practice is very different from clinical research. You cannot research what you cannot measure. Clinical practice and clinical research are different worlds, but one must wonder why. The people within each realm are pursuing different career paths, shaped by different cultures, in pursuit of different short-term goals. Yet the people conducting both endeavors are committed to the ultimate goals of eradicating suffering and increasing wellbeing for all.

Clinical research uses validated patient self-report measures, and so in a sense, objective research is largely subjective in that it involves quantifying thoughts and feelings. While it would be ideal to draw blood to test whether someone is depressed, we have no such capability today. We instead rely on rating measures which objectify the subjective. They are scientific and valuable. Just ask the people who have chosen a research career over a clinical practice career.

Research goes nowhere without measurement. Clinical practice pays homage to research, but usually just to a body of randomized controlled trials connected with a preferred clinical model. Clinical practice then goes on to ignore measurement. There seems to be a core fallacy that once a clinical model has been validated through rigorous research, it is fine to then use it at will with no further measurement of results. Shouldn’t we be measuring results at the individual level after the clinical trials?

What and how we measure

Clinicians and program directors should follow the lead of our research colleagues and measure clinical progress to augment clinical judgment about how treatment is proceeding. But the question quickly becomes: What do we measure? Should we measure symptoms, functioning, quality of life, or some combination of these? We have several well-validated measures for these domains, but one might ask whether we have any outcome measurements that don’t rely on self-report scales.

We do, and the best example is that a chemical dependency program may insist on measuring clean urines as an outcome measure. Given that chemically dependent people often relapse due to mood disorders, should we not also be monitoring how their moods have been trending? Perhaps the best decision might be to measure subjective experience with available objective measures.

One of my main proposals here is to foster a measurement culture within clinical practice, but we must find ways to make measurement a low burden for clinicians. Patients are happy to complete any assessment tool that their treatment provider recommends, and so the barrier is the burden and potential resistance of the clinician. I have implemented outcome-informed treatment in large systems of care, and I know that clinicians embrace this enhancement to care once they understand it and fit it comfortably into their practice routine. However, convenience is paramount.

I have been consulting in the past several years with companies that provide digital behavioral health platforms and video/telephonic psychotherapy, and I can bear witness to the fact that patients complete assessments without any concern when the measurement process is embedded into the experience without any role for a clinician. We are used to rating restaurants, movies, and many other experiences, and so no consumer today should be shocked to have a symptom rating scale sent their way.

The royal road not found

There will never be a royal road to truth. For those unfamiliar with the concept of a “royal road” in Freud’s work, please note that he argued dreams were the royal road to knowing the unconscious mind. It seems that royalty can become plebian, if not quite ridiculous, over time. There is no single path to knowledge, but instead many winding roads going in unpredictable directions.

We are often left to our best judgment in complicated endeavors like healthcare. We are fortunate to be able to measure aspects of a clinical problem, but we will long encounter problems with no available measurements. Judgment and measurement inform one another under the best circumstances. The critical point is to give each its due and to recognize that we will always need both ways of knowing.

While there is no reliable royal road to the truth, we might be able to grasp the spirit of the next closest thing – a humble openness to all perspectives and available data. I would add that the tension between subjectivity and objectivity is important beyond the lofty levels of clinical theories and models. It also plays out at the individual level.

We should be gathering all available data on how an individual patient is progressing. We should also be assessing how clinicians in training are performing. The simplest recommendation I would make is that all clinical training programs begin to require students to use patient self-report measures in their work. The clinician then knows how the patient is progressing. The supervisor then knows, based on aggregated data for all of one’s patients, how the clinician is progressing.

Ed Jones, PhD, is senior vice president for the Institute for Health and Productivity Management.