I am a junior in the medical field, and have been tasked with performing a propensity matched analysis of some data, using R-studio

I am looking at comparing the balance of my covariates (both before and after matching), and looking through the documentation for the cobalt package it says that continuous covariates will have the SMD shown, where as for binary variables the raw difference in proportion is automatically calculated.

I am aware I can change which I ask it to calculate, however I am after some guidance as to which I should use?

Looking through propensity-matched papers published in some of the higher-impact medical journals, as well as papers that report on how to report propensity scores and matching in the medical literature (eg. DOI: 10.1002/sim.3697; doi:10.1136/bmjopen-2020-036961; doi.org/10.1016/j.jtcvs.2007.07.021; and doi: 10.21037/atm.2018.12.10), they all seem to imply that the SMD is calculated and not the raw difference (or any mention of binary variables at all).

Looking through what has been documented in medical literature/medical statistics literature, I am unable to find any clear guidance on if I should use SMD or raw differnce.
As such, I have used SMD in my calculations so far