1. #SciComm is hard because it is hard to know what others don't know and express it in a way that they will *know* what you mean...you know what I mean? Good SciComm is REALLY important not only to make sure people "get" our stuff, but also in allowing them to trust us.

2. The advice "explain it so my grandma will understand" is good. When you tell my grandma about this super cool study you did, you are careful to explain why it's important. She gets that. Big pictures are really important. Why does everything you just told me matter?

3. But picture frames are equally important. Especially now. Be wary of what the NIH calls "overhyping" your findings (or others) and in the same way you explained everything else, also make it abundantly clear what you DON'T know. Maybe this means your data will change.

4. Express & own your limitation, place them in context. Your picture, your work, only exists within the context of these limitations, the frame. Tell grandma that even though your study drug looks AMAZING, it looks that way because we withdrew all the non-responders! Tell her

5. Grandma is not a rock. Grandma can understand and it is your job to make sure she does. Telling grandma upfront that there is room for limitations and uncertainty makes her more likely to remain engaged and trust you if and when these changes occur. Don't blindside gma.

6. As scientists, we are trained to be comfortable with uncertainty but it can be easy to forget how important it is to normalize that. It's actually not that normal. If grandma told you she baked you a dozen cookies for you & then fed them all to your brother, you'd be upset too

7. What if grandma had started off by saying I baked a dozen cookies and they're for you but then found out your brother had a really bad day and really needed cookies. An overly simple example, hopefully, the point is not lost.

8. Throughout this thread, I talk a lot about "your framing" or " when you communicate" I am referring to the science community at large, though all certainly applies at the individual level. As scientists, we have a responsibility to consume and conduct due diligence on others'

9. works. This includes translating those works. We need to normalize uncertainty and stop assuming that the general public doesn't want to hear it. The general feedback I am repeatedly seeing revolve around two main points (1) failure to provide a timeline of when this will end

10. I'll start there- we don't and never had a good answer, this was a difficult communication hurdle to start plagued by a separate war on misinformation that continues to deplete a lot of us mentally. To those of you fighting this, I see you and I admire you

11. I echo many of the thoughts already mentioned by far more talented researchers then I regarding statistical responsibility to express uncertainty behind models and very clearly state what exactly those models are saying.

12. The second point (2) the flip-flopping on rules and data, is mentioned in this thread, and is again influenced by rampant misinformation. To other SciCommers please continue to make yourselves available to media sources who ask for help and to your friends/family/communities

13. this helps ensure that information reaching mass volumes is accurate and from good sources. If it is outside of your wheelhouse don't be afraid to decline and suggest someone better suited. We need accurate information and we need it to convey that changes in info may occur.

14. Finally, when conveying info please dont forget there is no such thing as a bad question. People are scared. They are receiving info ranging from alarming to overly rosy. While it may feel like an uphill battle, I promise there are people who are still listening #epitwitter