In a recent conversation, a colleague in the field told me they are attempting to “Catalog the biases at work among many of the scientific and medical experts in the field.” And they said to me, “I’d like to hear what biases you observe.”
This blog post serves as my attempt to respond to that request. What biases do you observe?
My current list of those biases is as follows:
- The idea that knowing the list of diagnostic criteria is the same as understanding the disorder
- Ignoring signs and symptoms of the illness that come from non-research sources
- Transforming each of the diagnostic criteria into a simple yes/no question
- Not including psychological struggles or improvements when determining remission
- Forgetting the complexity of real-world clinical implementation
- Conducting research with simple and compliant subjects, then doing clinical reasoning based on results of that work
- Understanding the illness by emphasizing the clinical discipline they were trained in
- Working to suppress symptoms and then conflating that with sufficient improvement
I’ll say more about each one of those in order, below.
Biases At Work
- In my experience, scientific experts in the field tend to use the criteria that are meant to be used to diagnose the presence of a substance use disorder as their main way of understanding the illness.
One trend inside the doing of that error is setting aside the phenomenological characteristics of addiction illness that are not found in the diagnostic criteria.
But people with addiction illness, those in recovery, and their family members – if they read over that diagnostic criteria list – would know that the simple list of diagnostic criteria falls far short of a sufficient quantitative and qualitative description of any one person’s addiction illness. Further, people who are maintaining recovery know all too well the signs and symptoms of their illness that are not found on the list of diagnostic criteria, and that tend to re-emerge at times over the years.
There are a variety of documented sources of that kind of information. My two favorite sources are older ones:
- The “Jellinek Chart” shows common signs of alcoholic disease progression.
- Gorski lists relapse warning signs that show up before going to back to using (during the early, middle, and later stages of regression out of recovery).
Both of those sources describe what it is like to have or to witness the illness. Lists like these can help someone understand addiction illness in its various forms and stages.
Here’s my favorite example of limiting one’s understanding of an illness to the list of its diagnostic signs and symptoms or objective research targets:
- Someone I know was present when a neurological bench scientist working in Parkinson’s research met a person with Parkinson’s for the first time. They were delighted to meet each other. But when the scientist explained what they were working on (movement problems, naturally) the person with Parkinson’s asked if they ever worked on gut motility. The person with Parkinson’s had to explain to the researcher that there are whole sets of problems not visible to others. The bench scientist was very grateful to hear of a whole new array of research targets – from a person who knew in a whole different way.
2. The bias listed as #1 above leads naturally into this next one. In my experience, empirical scientists/researchers are largely unaware of, or are quick to ignore or dismiss, objective signs that are universally accepted by clinicians and the people that experience the illness.
- But meanwhile, clinicians are expected by research scientists and medical experts to work with and not set aside the objective signs that are identified by researchers.
3. When they use the list of diagnostic criteria, they tend to turn each of the diagnostic criteria into a simple and straightforward question and ask the person if they ever experienced that or not. They generally do not first immerse themselves in the case history, then obtain information from data sources other than the person’s self-report, and last of all make a judgement from all the information gathered as compared to the diagnostic criteria.
4. In my experience they view the illness as being in remission if use of the substance stops or if the countable number of diagnostic criteria that are currently present shrinks to a small enough number.
- But quitting is diagnostic, not prognostic. And a simple elimination or reversal of the facts or information needed to identify the illness is not the same as the person healing or the same as full recovery. Or that the illness is not still in operation in other ways not listed in the diagnostic criteria.
5. In my experience research scientists or medical experts far from clinical work tend to make flawed assumptions (based on the logic of their training) about clinical implementation. For example, clinicians know we provide treatment based on practice guidelines. And clinicians tend to ask about adjusting the use of a guideline based on the facts or circumstances of the individual patient. And in my experience, most academics or researchers would answer such a question by saying something like, “Take a closer look at the guideline”. They believe most of the important individual differences from one patient to another are covered in the practice guideline for that disorder.
- But working clinicians know that patients have multiple disorders or divergent needs. And therapists might need to commonly use multiple practice guidelines simultaneously or have to attempt to blend them.
At that point, if that was explained to the research scientist or medical expert, their response would be to say something like, “Oh”, and the topic of the real world would be discussed.
6. Survivorship bias. Studies evaluate those that enter a study. They do not study those who can’t or won’t enter the study. And they study those that complete the study, not those that can’t or won’t complete the study. And studies only let in those who are healthy enough and uncomplicated enough to be studied in the first place (such as having only one disorder, and having no cognitive impairment, etc.).
- Should we only study the survivors of our protocol? Shouldn’t we also study the drop-outs, no-shows, and those that didn’t make it? Clinicians generally see complicated and ambivalent real-world patients in real-world clinical and community settings.
7. In my experience, their understanding comes right from their individual clinical discipline. They limit themselves to looking for things their specific tools are geared to find and tend to have little recognition of this as a self-limiting process.
- For example, physicians generally see addiction as a brain illness with bio-psycho-social manifestations. They do not tend to see addiction as a bio-psycho-social-spiritual illness.
In my experience this error becomes more rare or smaller when they are working as a member of a team. For example, when such a person is one member of a team (composed of staff from clinical psychology, primary health, nursing, spiritual care, addiction counseling, marital and family therapy, wellness/recreation therapy, and psychiatry) their information is added to that from the other disciplines, is contextualized, and in that way their understanding improves.
8. In my experience, they view improvement in a person as nothing more or less than suppressing symptoms (reducing the number or intensity of problem indicators). Working to suppress symptoms is the focus.
- They work toward obtaining statistically significant differences and lose focus on clinically significant differences.
- Working toward health and wellbeing is forgotten. That is to say, the focus is on the course of illness, not the course of recovery.
I’ll close with a quote to consider from Thomas Payte, MD:
The majority of the population prefer the certainty of illogical conviction to the uncertainty of logical doubt.
It seems to me this applies to all of us as people, including we professionals, and not to our patients only.
Recommended Reading
Haun, N., Hooper-Lane, C. & Safdar, N. (2016). Healthcare Personnel Attire and Devices as Fomites: A Systematic Review. Infection Control & Hospital Epidemiology. 37:1367–1373.
Ioannidis, J. P. A. (2005). Why Most Published Research Findings Are False. PLOS Medicine. 2(8): e124. 696-701. DOI: 10.1371/journal.pmed.0020124
James L. (2016). Carl Jung and Alcoholics Anonymous: is a Theistic Psychopathology Feasible? Acta Psychopathol. 2:1.
Petrilli, C.M., Saint, S., Jennings, J.J., Caruso, A., Kuhn, L., Snyder, A., & 2 Vineet Chopra, V. (2018). Understanding Patient Preference for Physician Attire: A cross-sectional observational study of 10 academic medical centres in the USA. BMJ Open. doi:10.1136/ bmjopen-2017-021239.
Twerski, A. (1997). Addictive Thinking: Understanding Self-Deception. Hazelden.
Weiss, D., Tilin, F. & Morgan, M. (2018). The Interprofessional Health Care Team: Leadership and Development, Second Edition. Jones & Bartlett Learning: Burlington, MA.