The Impact of Costaqda Features on Enhancing Qualitative Data Analysis for Reliable Outcomes Across Different Designs – A Qualitative Evidence Synthesis Protocol - Mfolo, Letlhogonolo; Costa, King (My University, 2024)
In this abstract, I present a comprehensive overview of the utilization of Qualitative Evidence Synthesis (QES) methodologies in informing policy-making across various sectors, including education, public health, management, and economic sciences. The rapid growth of QES is driven by the increasing demand among scholars and practitioners for distilled information on effective interventions. However, conducting rigorous QES studies necessitates expertise and adherence to international standards. Integrating QES projects with computer-assisted qualitative data analysis software (CAQDAS) further enhances reliability and dependability. I focus on the Collaborative Online Software Tool for Qualitative Data Analysis (COSTAQDA), a cloud-based platform designed to facilitate robust literature-based studies while upholding rigorous standards. COSTAQDA incorporates Inter-Coder Reliability Statistics, employing Cohen’s Kappa, to ensure methodological rigor. I delineate optimal methodologies for leveraging QES to support policy-makers and decision-makers with credible and trustworthy information. Advantages and disadvantages of QES methodologies are scrutinized, with attention to limitations. I explore opportunities for addressing methodological constraints through the proposed ENTREQ framework. Additionally, I introduce and demonstrate the COSTAQDA application, providing guidance from project inception to completion. In conclusion, this abstract provides insights into the symbiotic relationship between QES methodologies and CAQDAS applications like COSTAQDA, aiming to advance evidence-informed policy-making. By adopting rigorous methodologies and innovative tools, policy-makers and decision-makers can access reliable information crucial for addressing societal challenges.
Keywords: CAQDAS; COSTAQDA; Inter-Coder Reliability; Literature Review; Qualitative Data Analysis