No matter what you do, mutating a sparse array element-by-element is very slow (because the compressed column format needs to be re-packed each time you insert a new nonzero).
Here, your matrix isn’t very sparse, so I wouldn’t use a sparse matrix at all in this case. You could just do
R = rand([1,-1,0,0,0,0], n, m)
If you want you can convert this to a sparse matrix with sparse(R), but it’s generally not worth using a sparse-matrix data structure with a matrix that is only 2/3 sparse.
However, it is possible to generate such a sparse matrix directly, by calling sprand with a custom random-number generator. (This would be worth it if the probability p of a nonzero entry were much smaller than 1/3.) In particular, you could do:
p = 1/3 # probability of nonzero (±1) entry
R = sprand(n, m, p, N -> rand((-1,1), N))