Which of the following is NOT a main concern when working with small samples?

The notion of high confidence intervals primarily refers to the degree of certainty associated with an estimated range of values. In statistical terms, confidence intervals are calculated based on the sample data, and smaller samples generally lead to wider confidence intervals. This indicates greater uncertainty rather than "very high confidence" regarding the estimates derived from such data.

In the context of small samples, one of the significant challenges is that they can reduce the generalizability and reliability of findings. Small sample sizes are more prone to sampling error, which can misrepresent the true population parameters. As a result, researchers may struggle with reinforcing their findings as robust and reliable, which ties into the concerns outlined in other options.

Furthermore, small samples can increase the chances of Type I errors (false positives), where researchers might reject the null hypothesis when it is actually true. Thus, the impact of working with smaller samples presents several challenges, while the concept of "very high confidence intervals" does not pertain to typical concerns associated with small sample sizes.