The p-value tells you the same thing no matter where you encounter it, be it in a t-test, ANOVA, regression, experiment, etc. That’s the beauty of it…It you have a p-value, you have a hypothesis. If you have a hypothesis, you have some statement you are trying to dissprove. You can’t determine the direction or magnitude of some value using the p-value, only if something is or isnt. The key is to always know what that something is (null) and what it isnt (alternative). The p-value is then measured against the level of significance you selected to determine if you are rejecting or accepting the null – “If the p-value is low (p-value < alpha value), the null must go. (practically, not statistically speaking).
Hence, you are determining, “This thing is what my null says it is, or it isn’t”. I find it highly useful to always write your null and alternative hypothesis when you are first starting out.
I am a fetal practicianer, so confirm this explanation. Research under “hypothesis testing, alpha, type I or II, probability statistics, etc”. All relate directly to your question. Good luck.
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