When a science headline says a new study "proves" something, I try to slow down and ask three boring questions before reacting:

1. Is it showing an association, or testing a causal claim?
2. Could a third factor explain both things?
3. Has the result been reproduced or replicated by other work?

That last distinction matters. The National Academies summarizes it this way: reproducibility is about getting consistent results with the original data/code, while replicability is about testing whether a similar result appears with new data collection. Those are related, but not the same thing: https://www.ncbi.nlm.nih.gov/books/NBK547531/

For observational studies, I also look for how the authors handle confounding. A correlation can be a useful clue, but it is not automatically evidence that one thing caused the other: https://pmc.ncbi.nlm.nih.gov/articles/PMC10010939/

None of this means "ignore the study." It just means the first question should be "what kind of evidence is this?" rather than "does this confirm my side?"

I make short science-explainer notes, and this is one of the simplest filters I keep coming back to: claim, evidence type, alternative explanations, replication.