In qualitative research, what is a potential pitfall that can occur if researchers do not achieve data saturation, particularly affecting the validity of their data interpretation?

If researchers stop collecting data before reaching saturation, they may miss important themes that appear only later in the study, so the findings are incomplete and may misrepresent the phenomenon. Because the sample does not cover all relevant perspectives, the analysis can overemphasize the few patterns that emerged early, making the conclusions seem more definitive than they truly are. This lack of depth can lead to false generalizations and weaken the study’s credibility. For example, interviewing only three people about a new community program might miss a critical barrier that appears only in the fourth or fifth interview, causing the researchers to overlook a key obstacle and report a misleadingly positive outcome. Thus, failing to achieve saturation risks producing invalid or overly narrow interpretations.