There is a great dissonance between research and reality and it is getting wider by the minute. Don’t get me wrong, there are forces that are trying to counteract the effects but the causes of the dissonance remain.
Before I design any study, I have a picture in my head of a doctor and a patient, often an elderly woman. I think I project myself in to the future subconsciously.
The patient is nervous and the doctor is stressed. The paient is not literate in the field of medicine and the doctor does not have time to keep up with the debates in medical research, perhaps even being naive to its downsides.
They are there to solve a problem. To make the best of a tricky situation called disease.
My job is to make sure to provide them with accurate and broad information that will help them to make a choice for the first line of treatment or even to diagnose the condition. I do my job in aims to give the doctor at the clinic the best chance to find a good solution and to provide the patient a tool that will help her to fight against a hinder in her longevity.
It may seem somewhat romantic, but that is how we must think within the medical sciences as even the most hard core lab rat with the most narrow biomechanistic subject is a puzzle whose purpose is to maintain someones ability to feel and enjoy health.
At this point in time, common research practice is to exclude any individual that isn’t optimal. This is a particularly visible problem in neuroimagine studies as most studies performed, particularly on individuals aged 70 and over, sample individuals that are physically and mentally beyond the mean of the population hence lacking common comorbidities (e.g. prior head traumas, high blood pressure, type 2 diabetes, depression etc.)
We want to see a clear head with optimal volume and perfect correlations coefficients.
And for research purposes it is important to isolate the effects, thus removing any potential patients that may complicate the picture. However, harsh exclusion criteria do have their cost.
Reality is complex and no patient will ever come in to e.g. a memory clinic solely having one comorbidity and being of optimal health.
The conclusions drawn upon our analyses, with individuals who are optimally chosen for a singular research question, are used in a clinical setting as a potential treatment strategy in a population that resembles nothing to the research population.
This means, per fact that the patient in the doctors office, if he/she isn’t a young male (as predominantly pharmacological research is based on this population) or someone without more than one comorbidity, has much much worse chances of successful treatment.
We need to start picturing the target audience of our research more often, and put more effort in developing strategies in which we can do research while including “non-optimal” patients as they are the core consumer of our results.
The ethics have to debated not only how to avoid harming non-optimal voluntary research participants e.g. elderly or women, but also the consequences of excluding them completely while subjecting them to treatment and diagnostic strategies in which they were not tested for.