This is actually much worse than I thought These authors basically know nothing about factor modeling and have assumed they've found a substantially interpretable factor that represents a construct they're interested in But the model fits terribly and the loadings make no sense

Theoretically, what is this factor? It's not clear to me, to you, to the authors, or to anyone, that it actually represents "the accumulation of chronic stress experienced across the lifespan". How could it? It throws together everything, regardless of chronicity.

Also, how could it? It's assembled from a bunch of variables that make little sense together. And how could it? The choice to use a bifactor model means they're getting better-than-expected fit from modeling out residual variance, but the model STILL fits incredibly badly.

And how could it? The poor loadings indicate that a general factor is an unlikely description of cumulative lifetime stress, and that a strong enough positive manifold to substitute different composites successfully is unlikely to be the case for this data.

And how could their conclusions using this be relevant to what they argued? They cannot test measurement invariance with this model, as it is a bifactor model They also should not start testing MI because of the poor initial fit, and it's almost-certainly not supportable either!