MODELS
← Browse the encyclopedia

Guide · Free preview

Applicability

Check whether the evidence transports to your specific person, context, scale, and incentive environment.

A study shows a training protocol added impressive muscle in twelve weeks, and you're ready to adopt it wholesale. The subjects were 22-year-old male athletes on supervised programs with dialed-in sleep and nutrition. You are 47, sleep six hours, and train alone before work. The evidence is fine; the export license is the problem.

The move is to check whether the evidence transports to your specific person, context, scale, and incentive environment before acting on it. The cue is borrowing a conclusion generated on people or situations meaningfully unlike yours. Steps: list the differences between the source population and you (age, recovery capacity, supervision, adherence), judge which differences plausibly change the effect rather than just existing, then either discount the expected result, adjust the dose, or hunt for evidence closer to your own case, like studies on trainees over 40. When it works, you stop importing conclusions wholesale and start borrowing them with an honest discount, which saves you from programs built for bodies you don't have. Don't stall on demographic mismatch when the mechanism is近 general; some findings, like sleep helping recovery, transport to nearly everyone.

Keep exploring

Read the full page.

Create your free access to continue reading and explore the complete library.

Register free with ChatGPT →

Already registered? Use the same button to sign in.

Sign-in shares your email with Michael Simmons to create your site access. No payment required. Newsletter signup is separate. How your data is used