This is what's meant by an instrumentation threat. Perhaps part or all of any pre-post gain is attributable to the change in instrument, not to your program. The observers may get tired over time or bored with the observations. Conversely, they might get better at making the observations as they practice more. In either event, it's the change in instrumentation, not the program, that leads to the outcome.
Mortality is used metaphorically here.
Usually, it means that they are dropping out of the study. Let's assume that in our compensatory math tutoring program we have a nontrivial dropout rate between pretest and posttest. And, assume that the kids who are dropping out are the low pretest math achievement test scorers. If you look at the average gain from pretest to posttest using all of the scores available to you at each occasion, you would include these low pretest subsequent dropouts in the pretest and not in the posttest. You'd be dropping out the potential low scorers from the posttest, or, you'd be artificially inflating the posttest average over what it would have been if no students had dropped out.