logistic regression, model performance

Question

I am interested to understand in which scenarios person should use sensitivity, specificity, and when should person opt for precision recall.

On a high level I understand for a balanced data set we should use precision, recall and if dataset is imbalanced we should use sensitivity and specificity. but I am not sure why they say it. If you people have different perspective, pls throw some light on how to perceive these.

Thanks