To determine when a cause-and-effect conclusion about the relationship between two variables in an experiment has been reached, the most relevant element from your list would be "random selection of participants."
Random selection helps to eliminate bias and ensures that the sample is representative of the larger population, which is crucial for establishing a causal relationship. While factors like study design also play a role, random selection is essential for supporting strong causal inferences in experimental research.