I have two scales with 7 binary items. The simple raw scores from these scales (summing the item responses of 0 or 1) are very skewed with about 56% of the sample having a scale score of 0. This is not unexpected as the scale measures behavioral problems with higher scale scores indicating more problems. A scale score of 0 indicates no problems. I am interested in looking at the relationship of these scale scores to binary outcomes variables. Given the nature of the scale and positive skew, I am inclined to dichotomized the scale scores into those with a score of 0 and those with a non-zero score (i.e., 1-7). Effectively creating a "no problems" / "problems" dichotomy. This way when I use logistic regression the coefficients will be easily interpretable. I know that there are issues with dichotomizing a continuous variable and was curious what you all think of this approach. I was also curious what other analytical paths you would consider.

Thank you very much for you thoughtful consideration!