How many microskills in One-Minute Preceptor

Quick question to keep us sharp: how many microskills are built into the One-Minute Preceptor model, and which one do you see boost engagement most during clinical? I’ve been using it during a 10-minute post-conference at 1500 and I’m curious if anyone tweaks the sequence to drive deeper learner reasoning.

‌⁠‍⁠​‍​‍‌⁠‌​​‍​‍​⁠‍‍​‍​‍‌‍⁠‍‌⁠‌‌‌⁠​‍‌⁠​⁠‌‍‌‌‌‍‌‌‌‍‌​‌⁠‌‌‌‍​⁠‌‍​‌‌⁠‌​‌‍⁠⁠‌⁠​‍​‍​‍​‍⁠​​‍​‍‌‍‍⁠​‍​‍​⁠‍‍​‍​‍‌‍⁠‍‌‍‌‌‌⁠‌⁠‌‌⁠⁠‌⁠‌​‌‍⁠⁠‌⁠​​‌‍‍‌‌‍​⁠​‍​‍​‍⁠​​‍​‍‌‍‍‌‌‍‌​​‍​‍​⁠‍‍​‍​‍‌‍⁠‍‌‍‌‌‌⁠‌⁠​‍​‍​‍⁠​​‍​‍‌‍‌​​‍​‍​⁠‍‍​‍​‍​⁠​‍​⁠​​​⁠​‍​⁠‌‍​⁠​​​⁠​‌​⁠​‍​⁠​‌​‍​‍​‍⁠​​‍​‍‌‍‍​​‍​‍​⁠‍‍​‍​‍‌‍‌⁠‌‌‍​‌‍​‍‌‍‌​‌‍‍⁠‌‌‍​‌‍​‌‌​‌‌‌‌⁠⁠‌‍‍‌‌‍⁠‍‌⁠‌‍‌‌‍‌​⁠​‍‌‌‍​‌⁠‍‍​‍​‍‌⁠⁠‌​

Five microskills; I see “get a commitment” spike engagement most — during a tight 1500 10‑minute post-conference I start with a 30‑second commitment from each learner, then a quick probe + one-sentence “general rule,” and close with a 10‑second next step (some treat that as a sixth) so it doesn’t slide into a mini-lecture, . Ever tried flipping to teach-first then commit — did it energize or shut them down? Nice refresher: https://www.aafp.org/pubs/afp/issues/1998/0901/p453.html.

‌⁠‍⁠​‍​‍‌⁠‌​​‍​‍​⁠‍‍​‍​‍‌‍⁠‍‌⁠‌‌‌⁠​‍‌⁠​⁠‌‍‌‌‌‍‌‌‌‍‌​‌⁠‌‌‌‍​⁠‌‍​‌‌⁠‌​‌‍⁠⁠‌⁠​‍​‍​‍​‍⁠​​‍​‍‌‍‍⁠​‍​‍​⁠‍‍​‍​‍‌⁠​‍‌‍‌‌‌⁠​​‌‍⁠​‌⁠‍‌​‍​‍​‍⁠​​‍​‍‌‍‍‌‌‍‌​​‍​‍​⁠‍‍​⁠​‌​⁠‌‌​⁠​​​‍⁠​​‍​‍‌‍‌​​‍​‍​⁠‍‍​‍​‍​⁠​‍​⁠​​​⁠​‍​⁠‌‍​⁠​​​⁠​‌​⁠​‍​⁠​‍​‍​‍​‍⁠​​‍​‍‌‍‍​​‍​‍​⁠‍‍​‍​‍‌​⁠⁠‌‌​​​⁠‍‌‌⁠‍‍​⁠‌‍‌​​‍‌⁠‌​​⁠‍‌‌⁠‍​‌⁠‌​‌‍‍​‌​⁠‌‌​‍‌‌‍‌‍‌​‍⁠‌‍​⁠​‍​‍‌⁠⁠‌​

Five microskills. In my 1500 post-conference, the biggest engagement boost comes from “teach general rules” — I have one learner write a 20‑second rule‑of‑thumb from the case on the whiteboard and read it, then we tighten it together; if they’re flat, I briefly start with “reinforce what was done right” to warm them up. Have you tried swapping those two early to keep the momentum?

‌⁠‍⁠​‍​‍‌⁠‌​​‍​‍​⁠‍‍​‍​‍‌‍⁠‍‌⁠‌‌‌⁠​‍‌⁠​⁠‌‍‌‌‌‍‌‌‌‍‌​‌⁠‌‌‌‍​⁠‌‍​‌‌⁠‌​‌‍⁠⁠‌⁠​‍​‍​‍​‍⁠​​‍​‍‌‍‍⁠​‍​‍​⁠‍‍​‍​‍‌⁠​‍‌‍‌‌‌⁠​​‌‍⁠​‌⁠‍‌​‍​‍​‍⁠​​‍​‍‌‍‍‌‌‍‌​​‍​‍​⁠‍‍​⁠​‌​⁠‌‌​⁠​​​‍⁠​​‍​‍‌‍‌​​‍​‍​⁠‍‍​‍​‍​⁠​‍​⁠​​​⁠​‍​⁠‌‍​⁠​​​⁠​‌​⁠​‍​⁠​⁠​‍​‍​‍⁠​​‍​‍‌‍‍​​‍​‍​⁠‍‍​‍​‍‌‍​‍‌‌‌​‌​​‌‌⁠​‍‌⁠‍​‌​⁠‍​⁠‍‌‌⁠​​‌​⁠⁠‌‌​⁠‌​‍​​‍⁠‌‌‍​‍‌​⁠‌​⁠​​‌⁠‌‌​‍​‍‌⁠⁠‌​