I am conducting a study looking at attitudes of a group to the use of music as a form of therapy for people with dementia. I want to see if they are positive, neutral or negative (at least negative or positive) in my sample (N=92). My hypothesis based on previous studies is that the majority of the group will have positive attitudes.

In order to do that, I have constructed a scale and done the usual reliability and validity checks. The scale (SAMD) ranges from 19 to 95 (continuous), with highest scores reflecting more positive attitudes.

I am stuck as to how to classify negative attitudes, neutral and positive attitudes (at least negative or positive). My supervisor suggested ROC but I cannot see for the life of me how that makes any sense. (Correct me if I'm wrong) ROC curves are used to determine cut off scores - he is presuming that a cut off score of let's say 50 (which I am supposed to calculate so that it has the best specificity and sensitivity) would determine negative from positive attitudes. But when it comes down to it, I still don't know who has positive and who has negative attitudes so dichotomise the variable SAM-D.

I chose to split the distribution of the range of scores into three sections and categorized negative, neutral and positive attitudes accordingly (frequency statistics for the 33rd and the 66th percentile ) but that seems ad-hoc.

I have also administered two other scales (continuous variables as well) to the sample alongside them, one looking at attitudes to dementia and another looking at stress. My supervisor suggests that I do ROC with the attitudes to dementia scale (ADQ) and the SAMD.

I am trying to work out if ROC is the best way to find if my sample has positive attitudes. If so, I would appreciate it if someone explained it to me! If ROC is not the way, I would be grateful of any other methods.

Many thanks in advance

Almitra