**Core Concept:**
The p-value is a statistical measure used to determine the likelihood of observing the results obtained from a hypothesis test due to chance alone, thus indicating the strength of evidence against the null hypothesis. It ranges from 0 to 1, with lower values (closer to 0) indicating stronger evidence against the null hypothesis.

**Why the Correct Answer is Right:**
The correct answer, **D**, states that a p-value less than 0.05 is generally considered significant. This is because a p-value of 0.05 is conventionally used as the threshold to decide if the observed results are significant or not. If the p-value is less than 0.05, it indicates that the results are highly unlikely to occur by chance, and the null hypothesis is rejected, leading to acceptance of the alternative hypothesis.

**Why Each Wrong Option is Incorrect:**
A) A p-value of 0.1 is often considered as the threshold for significant results, which is incorrect as a more stringent threshold is used to maintain the probability of making type II errors (missing true effects) at a minimum.
B) A p-value of 0.01 is considered significant, which is incorrect because the choice of 0.05 is more commonly used and provides a balance between rejecting the null hypothesis when it is false (type I error) and failing to reject when it is true (type II error).
C) A p-value of 0.07 is considered significant, which is incorrect, as the threshold is set at 0.05 to strike a balance between type I and type II errors.

**Clinical Pearl:**
When making clinical decisions, it is essential to remember that the significance threshold is not a fixed value, but a subjective choice depending on the research question, sample size, and the desired balance between type I and type II errors. This choice is often determined by the researcher or the institution conducting the study. However, a p-value of 0.05 is commonly used as a benchmark for clinical significance.