Building a New Science of Recovery

One question I often get from treatment providers and recovery organization is “What type of data should we be tracking on our populations?” Before we jump into this, we should take a look at why we need evidence of recovery.

This is the RSRC consensus definition of recovery. It is purposefully broad, and casts a wide net. The reason for the broad scope of the definition is that in order to understand the variety of recovery trajectories, we must first define the parameters of what we are talking about, then, collectively, we must track different trajectories in specific ways. Over time and in aggregate, recovery will define itself.

in si·tu (in ˈsīto͞o,ˌin ˈsēto͞o) adverb · adjective
in the original place.

For example, to have a broader understanding of whether someone is appropropriate for pharmacotherapy, we must weigh several factors and the risk and benefits. Most importantly, we must identify the goals of the individual seeking care. However, lacking data to compare one trajectory (pharmacotherapy) to another (say CBT counselling + 12 Steps), we have no way of knowing which path will best help the client because we cannot compare them directly. This is why using the same frameworks for the study of recovery is important. We need to generate organic data from recovery in situ, in order to compare it across different modalities. Over time, and with collaboration, we can build a rich compendium of evidence for various “pathways” of recovery.

If we do not begin to measure recovery ourselves and define it through science, other forces outside of recovery will do so without our input.

So what should we measure? If we take a Recovery-informed Theory approach (RIT) see here:

Recovery-informed Theory states, “Successful long-term recovery is self-evident, and consists of a fundamentally emancipatory set of procceses.

We see with an RIT approach, we must deconstruct sucessful recovery trajectories in order to figure out what is best to measure. However, we do know some basic facts already.

1.) Recovery is a radical process of change (and therefore should be easy to measure)

2.) Recovery is a largely relational process. Individuals and those around them know they are getting better because their relationships to people, institutions, ideas, norms, and behavioral expectations become more bi-directional, mutually beneficial, and overall their relational spheres becomes more healthy.

3.) Recovery involves the person-in-environment. Other people, systems, and relationships are always involved.

4.) Recovery is a process, and therefore, is best measured longitudinally. Change is the measure of differences over time. One of the great failings of addiction science, and treatment outcome research, is that it fails to offer a robust conceptualization of recovery over the long term.

5.) In summary, we need to capture variables regarding the relationship to the self (intrapersonal), the relationship to others (interpersonal), and the ecological improvements in the life of the individual (the conditions of their lives).

Taken together, we can see a rough outline of the best ways to measure and study recovery. Some commonly used metrics can be found below. When we capture all three conditions over time, we see a relatively robust field in which recovery change occurs over time. A good way to remember the social equation for the study of recovery is {(In+Ip)E x T}, or Intrapersonal + Interpersonal, factored into the develocological environment over time.

Develocology : .

Some useful measures to start with:
The Rosenberge Self-Esteem Scale
The General Self-Efficacy Scale
The Brief Resiliency Scale
The Hoping and Coping in Recovery Scale
The Measure of Percieved Social Support Scale
The Recovery Capital Scale (BARC-10 or ARCS)
The Social Well Being Scale (SWBS)
The WHO Quality of Life Scale (WHO-QOL, WHOQOL-Brief)

There are several ways to measure develocological improvements, however, there is no one way to do so. It will be up to us as clinicians, providers, and scientists to decide how we are to proceed. I encourage you, the reader, to begin to think about how you see recovery, and ask questions of those who have recovered. However, to return to the the orginal question:

“What should we be measuring about recovery?”

I will say this: Ask people who have recovered to describe what factors made the biggest differences in their journey. I guarantee that a quick Google Scholar search will set you on a psychometric journey to figure out how to best capture the features they illuminate.

We are, after all, creating a whole new science of recovery. We are getting out from under the pathological shadow of addiction science. This is a collaborative endeavor, whose ownership is collectively held. We each have a part in walking the tightrope of skepticism and openess to new knowledge that science dictates. This new science is meant to be debated, it is meant to create new knowledge, and it is meant to seek truth about recovery. Not from a lofty perch in the ivory tower, but organically measured from the ground in which it grows. That means that you, me, and everyone else in this field has an obligation to formulate and test our ideas about successfull recovery.

These are pioneering times for recovery science. Mistakes will be made, people will be angry, bitter, elated, enlightened, and relieved at various points of the journey. What’s most important is this: if we all contribute to developing this new science of recovery, then the grassroots nature of recovery will also provide the source of knowledge for recovery science. So rather than national agencies, advocacy groups, pharmaceutical companies, and insurance profiteers deciding what consitutes recovery, we must do it ourselves- we must collectively define the whole science of recovery. Why? Because in the days of data-driven models and RCTs, we must respond with science, and empricism, lest we lose all control over the destiny of the field, and over the fate of those we help.

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