Two theoretical/statistical questions about directions of correlations, forgive my statistical ignorance, I really need help!

1. When I search for relevant articles to support my arguments, I often come across correlational studies. Often, the correlations found from regression models seem non-directional (e.g. life satisfaction and self-esteem can influence each other bidirectionally) but the articles often base their discussion on one direction of the correlation (e.g. life satisfaction can be predicted from self-esteem). Would it still be appropriate to cite the same study in support of "self-esteem can be predicted from life satisfaction"?
2. Can a longitudinal design really eliminate the plausibility of having a correlational conclusion in a direction opposite to your prediction? This is what I found in one article, but it seems like most people assume the directions of certain correlations without doubt, especially if it is based on longitudinal studies. "On a more general level we believe that there are three common, important and less widely recognized misunderstandings with respect to longitudinal study designs in occupational health psychology. The first of these is that we can prove causality by using longitudinal study designs. The extent to which causal inferences can be made depends on the following four conditions: temporal ordering of the focal variables, the strength of the statistical association between them, theoretical plausibility of the presumed causal relationship, and exclusion of plausible rival hypotheses for this relationship (2, unpublished manuscript by de Lange et al). While the first three conditions are relatively easy to satisfy with a longitudinal design, it is impossible to exclude the possibility that particular associations are due to variables that were not measured in the study design. Thus we can never prove causal relationships; the best we can do is argue that it is plausible that certain statistical associations can be understood in causal terms."