It's not clear who the audience is. It sounds like most people who complain about them are software people and not researchers/scientists.
For someone like me, who once did computational research using MATLAB, and later analyzed data for my job, Jupyter is not worse, and is in most ways superior. Let's take your points one by one:
> Participants stated they often downloaded data outside of the notebook from various data sources since interfacing with them programmatically was too much hassle.
This was the norm with MATLAB, Excel and JMP as well, unless someone wrote code to autodownload (extremely rare - less than 1% of people did that). And if you are going to write code to get the data from somewhere, it's much nicer in Jupyter than in these other tools.
> Not only that, but notebooks often crash with large data sets (possibly due to the notebooks running in a web browser).
I honestly have not seen this, and the reason makes no sense. Your browser is not handling the data. The kernel is. I mean yes, if you try to load several GB of data in pandas, it's possible you will have problems if you run out of RAM, but this has nothing to do with notebooks.
> Once the data is loaded, it then has to be cleaned, which participants complained is a repetitive and time consuming task
This was as much a problem prior to notebooks as it is now. Notebooks did not make this any worse.
> Explore and analyze. Modeling and visualizing data are common tasks but can become frustrating. For example, we observed one participant tweak the parameters of a plot more than 20 times in less than 5 minutes.
It was even worse with MATLAB. Ditto for Excel. JMP is a bit nicer for visualization, though.
> Notebooks do not have all of the features of an IDE, like integrated documentation or sophisticated autocomplete, so participants often switch back and forth between an IDE (e.g., VS Code) and their notebook.
It may be better now, but this was a problem in MATLAB as well.
> While it is easy to share the notebook file, it is often not easy to share the data.
This is as true with MATLAB, JMP, etc. A lot of the complaints about it being hard to reuse notebooks is because notebooks at least attempt to be reproducible, and thus many more people attempt it. Prior to notebooks, I know almost no one who tried to share MATLAB analyses, because it was such a pain to do so.
> Notebooks as products. If a large data set is used, as one might expect in production, then the notebook will lose the interactivity while it is executing. Also, notebooks encourage "quick and dirty" code that may require rewriting before it is production quality.
I suppose some people are trying to make products out of notebooks, and this is where all the recent grief I see is coming from. I do not think it was the primary goal of notebooks, though. They were meant for data analyses and prototyping, not for production use.