[josinalvo]

If you are testing A vs notA, and you exclude some scenarios in which A is true (and dont exclude anything else), that is (by definition) evidence for notA and against A. (at least by a bayesian definition)

Now, might be that the priors for A were very large, and A is still the most likely hypothesis. But the evidence just received reduced those priors

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(I know that the case in point does not fit the rather strict requirements of the first paragraph. But I think the affirmation "the hypothesis that reducing the workload improves the life of the worker, while still very likely, is now a bit less likely" is true in this case.)

(The phrase in " " sounds odd to me. If I knew numbers, it would be much better to say P(A) was 95% and now is 90%)