Factors influencing data saturation in qualitative studies

Abstract

This study aims to evaluate the factors that influence data saturation in qualitative studies. The study adopted a systematic literature review of 24 journal articles published between 2018 and 2022. The articles were obtained from a Google scholar database.  The findings point to five factors that affect data saturation namely, pre-determined codes and themes, sample size, relevancy of research subjects (respondents), number of research methods, and length of data collection sessions. It is argued in this paper, therefore, that in order to attain data saturation, researchers should consider multiple factors that may affect data saturation in order to increase the validity of qualitative studies.