item factor analysis performance issues across R versions

I'll try to describe the problem briefly. Can try to provide reprex if this sounds novel.

I have some code based on this paper (https://doi.org/10.1007/s11136-021-02873-7) that fits item factor analysis models. With version R 3.6.2, OpenMx 2.17.2, Windows 10, the models were quick to estimate (e.g., 3 seconds). I can still run them in that environment. I recently revisited the code with R 4.5.1, OpenMx 2.22.10 on the same hardware and estimation is painfully slow (e.g., almost 4 minutes).

Wondering if anyone can point me in the right direction for figuring out why and/or if there are any known performance issues. Going back to older R versions on the same machine, this seems to be an issue with anything R 4.0 (e.g., 4.0.5) and later. I see something in release notes for OpenMx versions (e.g., 2.18) around that time about CSOLNP no longer being the default optimizer in part due to performance issues (changing the optimizer in this case does not seem to make a difference). I also understand that it might be that many on the development team are not using Windows. Though, if I install Ubuntu in a virtual machine and go with the latest R and OpenMx version, I seem to encounter the same performance issues.

Any advice is greatly appreciated. Understand if you folks would ask for more info.