Enhancing the quality and credibility of qualitative analysis.

TLDR

Qualitative research quality and credibility are influenced by diverse philosophical orientations, evolving debates, and a consensus that methods should be matched to empirical questions rather than universally prescribed. The overview seeks to improve qualitative analysis quality and credibility by addressing rigorous data techniques, researcher trustworthiness, and users’ philosophical preferences. It reviews rigorous data collection and analysis methods, validity and reliability practices, triangulation, researcher competence, and the influence of users’ beliefs about objectivity, subjectivity, truth, perspective, and generalization.

Abstract

Varying philosophical and theoretical orientations to qualitative inquiry remind us that issues of quality and credibility intersect with audience and intended research purposes. This overview examines ways of enhancing the quality and credibility of qualitative analysis by dealing with three distinct but related inquiry concerns: rigorous techniques and methods for gathering and analyzing qualitative data, including attention to validity, reliability, and triangulation; the credibility, competence, and perceived trustworthiness of the qualitative researcher; and the philosophical beliefs of evaluation users about such paradigm-based preferences as objectivity versus subjectivity, truth versus perspective, and generalizations versus extrapolations. Although this overview examines some general approaches to issues of credibility and data quality in qualitative analysis, it is important to acknowledge that particular philosophical underpinnings, specific paradigms, and special purposes for qualitative inquiry will typically include additional or substitute criteria for assuring and judging quality, validity, and credibility. Moreover, the context for these considerations has evolved. In early literature on evaluation methods the debate between qualitative and quantitative methodologists was often strident. In recent years the debate has softened. A consensus has gradually emerged that the important challenge is to match appropriately the methods to empirical questions and issues, and not to universally advocate any single methodological approach for all problems.