The article "Consensual Qualitative Research: An Update" by Clara E. Hill, Sarah Knox, Barbara J. Thompson, Elizabeth Nutt Williams, Shirley A. Hess, and Nicholas Ladany reviews the application of consensual qualitative research (CQR) in 27 studies published between 1994 and 2003. CQR, introduced in 1997, integrates elements from phenomenological, grounded theory, and comprehensive process analysis approaches, emphasizing consensus among judges and the use of words to reflect data meaning. The authors describe the core components of CQR, including the consensus process, researcher biases, research team composition, data collection, data analysis, and writing up results and discussions. Key recommendations include: - Differentiating between expectations and biases, with a focus on addressing biases. - Ensuring team immersion in the data and rotating team members to foster diverse perspectives. - Training researchers in CQR methods, particularly in domain and core idea construction. - Using a balanced sample size and conducting pilot interviews to refine protocols. - Emphasizing open-ended questions and extensive probing in interviews. - Utilizing both telephone and face-to-face interviews, depending on the context. - Conducting a stability check to validate the cross-analysis. - Encouraging visual representation of results and member checking to enhance trustworthiness. - Writing results and discussions clearly, with rich examples and theoretical connections. The authors conclude that CQR is a viable qualitative method, suitable for in-depth studies of individual experiences and hidden or infrequent events, but suggest modifications to streamline the process.The article "Consensual Qualitative Research: An Update" by Clara E. Hill, Sarah Knox, Barbara J. Thompson, Elizabeth Nutt Williams, Shirley A. Hess, and Nicholas Ladany reviews the application of consensual qualitative research (CQR) in 27 studies published between 1994 and 2003. CQR, introduced in 1997, integrates elements from phenomenological, grounded theory, and comprehensive process analysis approaches, emphasizing consensus among judges and the use of words to reflect data meaning. The authors describe the core components of CQR, including the consensus process, researcher biases, research team composition, data collection, data analysis, and writing up results and discussions. Key recommendations include: - Differentiating between expectations and biases, with a focus on addressing biases. - Ensuring team immersion in the data and rotating team members to foster diverse perspectives. - Training researchers in CQR methods, particularly in domain and core idea construction. - Using a balanced sample size and conducting pilot interviews to refine protocols. - Emphasizing open-ended questions and extensive probing in interviews. - Utilizing both telephone and face-to-face interviews, depending on the context. - Conducting a stability check to validate the cross-analysis. - Encouraging visual representation of results and member checking to enhance trustworthiness. - Writing results and discussions clearly, with rich examples and theoretical connections. The authors conclude that CQR is a viable qualitative method, suitable for in-depth studies of individual experiences and hidden or infrequent events, but suggest modifications to streamline the process.