Avoiding Bias without Defeating Hope

Working with human subjects can be a little tricky, especially when they have experienced a life altering event such as spinal cord injury. It is hard to explain to people that the chances they will walk again or navigate through day to day life independently are low. Presenting a non-invasive therapy that has encouraging results in some studies, but non-significant results in others, to this population of people can pose a serious challenge. On one hand you do not want to give them a false sense of hope that the intervention being used will " cure" their partial/full paralysis, but you also do not want to defeat their hopes of functional improvement. The placebo effect as well as natural recovery after spinal cord injury pose a big challenge and can bias the outcomes of the study. We should also consider our bias as scientists when we observe changes in our participants, which can also potentially skew our data.

The article https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2917255/ addresses some of these concerns. One way to avoid bias in clinical research studies is to design the experiment in such a way that accounts for placebo effects and natural recovery. This means including baseline periods in which the natural progression of the functional recovery is monitored. In order to account for placebo effects, the therapeutic intervention used should have a placebo condition. For a lot of non-invasive stimulation technologies a placebo setting is built in, however a lot of participants are able to tell the difference between the sham and active settings. Unfortunately, I do not know of a good way to address this other than hoping for improvements in newer models.

A major challenge I face is remaining objective when it comes to the outcomes of the participants that I work with. I sometimes have to catch myself when a thought crosses my mind of  "wow, that person is improving a lot" or " this intervention technology does not seem to work as well as the other". Fortunately, other people are blinded to the intervention that are assessing that subsection of the data, but I believe that it would be useful for me to practice being as objective as possible when it comes to participant outcome. I don't want to be too objective and become a robot, especially since I have to interact with the participants. I want to give them hope for the possible and not the impossible, I want to base the things I tell them in facts and not fantasies. When subjects ask me about unproven novel "miracle" treatments, I feel it is my duty as a scientist to encourage them to be a part of a safer and regulated study. However, what if the non-significant, sketchy, unregulated study would have helped them? It's an ethical dilemma that I am faced with on a day to day basis.
https://www.vox.com/2015/10/29/9637062/media-hype-cancer-drugs