**Core Concept**
The p-value in a test of significance represents the probability of observing the study results, or more extreme, under the null hypothesis. It is a measure of the statistical significance of the observed difference.

**Why the Correct Answer is Right**
A p-value of 0.023 indicates that the probability of observing the study results, or more extreme, under the null hypothesis is less than 2.3%. This means that the observed difference is statistically significant, suggesting that the null hypothesis can be rejected. In other words, the observed difference is unlikely to occur by chance alone.

**Why Each Wrong Option is Incorrect**
**Option A:** This option is incorrect because a p-value of 0.023 does not indicate a non-significant result, which is typically considered as p > 0.05.
**Option B:** This option is incorrect because a p-value of 0.023 does not indicate a trend towards significance, which is typically considered as 0.05 < p < 0.1. **Option C:** This option is incorrect because a p-value of 0.023 does not indicate a highly significant result, which is typically considered as p < 0.01. **Clinical Pearl / High-Yield Fact** When interpreting p-values, it is essential to remember that a small p-value does not necessarily imply a large effect size. A small p-value can result from a large sample size, even if the effect size is small. **Correct Answer: C. Statistically significant.**