DAG: how descendant, collider and mediator most likely affect the effect between exposure and outcome? I made a very simple scenario:

Let's assume 'total work time' has a positive association with 'income' (more you work, more you earn).
But when I adjust to one of the following DAG's members, what should most likely happen with the association between exposure and outcome?
a) work time job1 (mediator)
b) colleagues visited at job1 (descendant)
c) quality time (collider)
My own understanding is that the effect of the exposure on the outcome most likely decreases in all three cases. Is this correct? Is this the reason why adjusting to them is bad, meaning that we will get biased estimates?

Adjusting on the mediator will get you biased results, if your goal is to get the total effect. If you just want the direct effect, you should condition on that mediator and on nothing else (well, technically, conditioning on the descendant of the mediator shouldn't hurt anything).
Conditioning only on the descendant shouldn't change anything much.
Conditioning on the collider will open up the collider and allow causal information to flow from the cause to the effect along another path. However, the collider is not a confounder, because the arrow is from the cause to the collider, not the other way around. I would still be hesitant to condition on the collider: I think you might introduce collider bias. It's not confounder bias, but it is collider bias.
