This study explores the use of visual joint displays to integrate qualitative and quantitative data in mixed methods research, particularly in health sciences. The authors searched for empirical articles in three high-impact journals that published state-of-the-art mixed methods research. They analyzed 19 joint displays to identify their types, design, purpose, rationale, data sources, integration approaches, and analytic strategies. The most common types of joint displays were statistics-by-themes and side-by-side comparisons. Innovative displays connected findings to theoretical frameworks or recommendations. Researchers used joint displays for convergent, explanatory sequential, exploratory sequential, and intervention designs. The study identified exemplars for each design, demonstrating how joint displays enhance the interpretation of integrated results and yield new insights. The authors recommend that researchers use joint displays to integrate and represent mixed methods analysis, emphasizing the value of this approach in advancing mixed methods research.This study explores the use of visual joint displays to integrate qualitative and quantitative data in mixed methods research, particularly in health sciences. The authors searched for empirical articles in three high-impact journals that published state-of-the-art mixed methods research. They analyzed 19 joint displays to identify their types, design, purpose, rationale, data sources, integration approaches, and analytic strategies. The most common types of joint displays were statistics-by-themes and side-by-side comparisons. Innovative displays connected findings to theoretical frameworks or recommendations. Researchers used joint displays for convergent, explanatory sequential, exploratory sequential, and intervention designs. The study identified exemplars for each design, demonstrating how joint displays enhance the interpretation of integrated results and yield new insights. The authors recommend that researchers use joint displays to integrate and represent mixed methods analysis, emphasizing the value of this approach in advancing mixed methods research.