방법 비교

	질적 증거 종합 방법	Trustworthiness Criteria in Qualitative Research
분야	질적 연구	질적 연구
계열	Process / pipeline	Process / pipeline
기원 연도	1988	1985
창시자	George Noblit and Dwight Hare	Yvonna Lincoln and Egon Guba
유형	Method	Framework
원전	Noblit, G. W., & Hare, R. D. (1988). Meta-ethnography: Synthesizing Qualitative Studies. SAGE Publications. ISBN: 978-0803931725	Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic Inquiry. SAGE Publications. ISBN: 978-0803924314
별칭	qualitative meta-synthesis, meta-ethnography, thematic synthesis, systematic review of qualitative studies	trustworthiness criteria, credibility, dependability, confirmability
관련	4	4
요약	Qualitative evidence synthesis (QES) is a systematic method for combining and interpreting findings from multiple qualitative research studies to generate higher-level understanding and theory. Different approaches—meta-ethnography, thematic synthesis, meta-narrative review, critical interpretive synthesis—each have distinct philosophical underpinnings and analytical procedures. Introduced by Noblit and Hare (1988) with meta-ethnography, qualitative synthesis has evolved alongside systematic reviews of quantitative research. Unlike quantitative meta-analysis, which pools numerical effect sizes, qualitative synthesis integrates concepts, themes, and interpretations from primary studies, identifying patterns, conflicts, and emergent theory. QES is increasingly used in health research, social sciences, and education to understand complex phenomena, translate research into practice, and identify gaps in evidence.	Trustworthiness is a framework for evaluating the quality and rigor of qualitative research, developed by Lincoln and Guba (1985) as an alternative to quantitative criteria (internal validity, external validity, reliability, objectivity). The framework comprises five criteria: credibility (findings are accurate and grounded in data), transferability (findings apply to other contexts), dependability (findings are consistent and defensible), confirmability (findings reflect the data and participants' perspectives, not researcher bias), and authenticity (research reflects diverse viewpoints and promotes understanding). This framework has become standard for assessing qualitative research across disciplines and guides researchers in designing and reporting rigorous qualitative studies.