The article "Generalization in Quantitative and Qualitative Research: Myths and Strategies" by Denise F. Polit and Cheryl Tatano Beck explores the concept of generalization in both quantitative and qualitative research. While generalization is a well-recognized quality standard in quantitative research, it is more controversial in qualitative research, where the primary goal is often to provide a rich, contextualized understanding of human experience through intensive study of specific cases. The authors discuss three models of generalization proposed by Firestone: classic sample-to-population (statistical) generalization, analytic generalization, and case-to-case transfer (transferability). They highlight common myths about these models and offer strategies to enhance the capacity for generalization, including planned replication, sampling strategies, systematic reviews, reflexivity, thick description, mixed methods research, and the RE-AIM framework within pragmatic trials. The article emphasizes the importance of both conceptual and reflexive thinking, as well as detailed and rich descriptions, to improve the generalizability of research findings.The article "Generalization in Quantitative and Qualitative Research: Myths and Strategies" by Denise F. Polit and Cheryl Tatano Beck explores the concept of generalization in both quantitative and qualitative research. While generalization is a well-recognized quality standard in quantitative research, it is more controversial in qualitative research, where the primary goal is often to provide a rich, contextualized understanding of human experience through intensive study of specific cases. The authors discuss three models of generalization proposed by Firestone: classic sample-to-population (statistical) generalization, analytic generalization, and case-to-case transfer (transferability). They highlight common myths about these models and offer strategies to enhance the capacity for generalization, including planned replication, sampling strategies, systematic reviews, reflexivity, thick description, mixed methods research, and the RE-AIM framework within pragmatic trials. The article emphasizes the importance of both conceptual and reflexive thinking, as well as detailed and rich descriptions, to improve the generalizability of research findings.