How Does One Design a Study around the use of “Gorilla-Feet” Shoes? (Blog #3 continued...)

A scientific study design is part of this assignment. With the above topic in mind, how would one develop, or design, a study with these barefoot-like shoes?

If my hypothesis were “Running while wearing shoes such as the “Vibram-Five-Fingers” (shoes that simulate being barefoot), causes fewer injuries to feet, ankles, and joints than while using “traditional running shoes”, how would I set up a design to test it?

In this instance, my exposure would be wearing these “barefoot shoes” while running.

My disease (or desired outcome) would be fewer injuries associated with running.

Study Type

Choosing a study type is crucial, in that it should be appropriate for the situation. In this particular instance, I would want to compare an exposed (wearing the “barefoot-type” shoes while running) group, to an unexposed group (wearing traditional running shoes while running). Then, I would be monitoring each group over time to see if there is a difference in running-related injury rates between the two groups.

The study type that seems to be a “best fit” for this situation is a prospective cohort study (other names are concurrent cohort or longitudinal study (Gordis, chap 9, p 170). For even better evidence of causality, randomly assigning participants to the exposed & unexposed groups helps to decrease chances of other confounding factors (other factors that might secretly influence the outcome).

Why? A prospective study follows the exposed and unexposed samples over time to see if they develop the disease/outcome being monitored. In my fictional study, I would want to monitor my groups over a period of time that allows for the injuries to potentially develop. Not being an expert on sports injuries, I would do a literature review, and consult sports trainers and physicians that treat sports injuries, for narrowing this study time-frame down to something manageable. Challenges with prospective studies can be that, with following groups over long time periods, they can become expensive, and because of the longer time-frame, participants can be lost to drop-out, or attrition. This loss to follow-up can bias, or slant the results of, the study, potentially confusing interpretation (Gordis, chap 9, p 174).