I'm a relatively non-technical clinician. And I recently came across an excellent paper paper (Schooling & Jones, 2018).The authors essentially implore biomedical researchers to use non-ambiguous language in describing their research questions (and to choose correspondingly appropriate methods to answer those questions). The ambiguity in question relates to the differences between predictive and causal modeling.
There is an excellent table, which summarizes much of the content. Under the “attribute” column you can find “interpretation” which includes several rows highlighting key distinctions.
My question is whether it would be appropriate to modify “predictors of risk” to “predictors of individual risk” for the predictive column, and modify “Effects on risk” to “Effects on population risk”? This was the only ambiguous aspect for me. Given how important it is as a consumer of scientific literature, and potentially as a future researcher, I want to make sure I get this right.