Faced with the challenges of storing, organizing, and sharing copies of individual studies, code sheets, and other study documents, among the research team members, we were compelled to design an efficient electronic working process. In this meta-analytic study, we examined relationships among 30 variables the code sheet used to extract data from each primary study contained 2,714 data fields we screened more than 26,000 articles, dissertations, and other research reports and we coded more than 600 studies. For our complex four-year model-testing meta-analysis, we chose to design an electronic system for storage of study documents and files and to enhance the efficiency, productivity, communication, file sharing, and work flexibility of the research team members. Managing hard copy study documents becomes unwieldy in meta-analyses, especially those of broad scope and complexity, requiring multiple coders and inclusion of large numbers of studies. The meta-analyst may develop paper code sheets on which to extract data from primary studies, guided by codebooks that contain theoretical and operational definitions of the study variables and detailed coding instructions for each variable on the code sheet. Recent conversations with leading meta-analysts have indicated that even today, meta-analysis continues to be mainly a paper-and-pencil process, with a research team member assigned to organize paper copies of the literature and coding documents. Health care providers need evidence-based guidelines on how behavioral change can be fostered in order to improve diabetes health outcomes and glycemia, because fewer than 30% of individuals with type 2 diabetes achieve nationally recommended goals for glucose control. Behavioral factors - adherence to diet, physical activity, medications, glucose self-monitoring, and appointment keeping - were examined as mediating variables because they are key targets for interventions. The primary aim of the meta-analysis was to examine a set of models that included psychological (e.g., depression, stress, anxiety), motivational (e.g., self-efficacy, health beliefs), and diabetes-related knowledge factors in predicting diabetes outcomes, such as glycemic control and quality of life. Key aspects of the electronic process are discussed below and include (a) locating studies that report relevant data among variables of interest, (b) extracting correlational data, or data that could be converted into correlations, from primary studies and pooling data across studies, (c) importing extracted data into data management software for analyses, and (d) gleaning meaningful, reliable, and clinically useful information from the synthesis of these data. We selected electronic tools that enabled us to organize and track the meta-analytic process, as well as to enhance communication among research team members. The purpose of this paper is to describe the electronic processes we designed, using commercially available software, for an extensive quantitative model-testing meta-analysis we conducted. ![]() ![]() The electronic process described here has been useful in streamlining the process of conducting this complex meta-analysis and enhancing communication and sharing documents among research team members. The major limitation in designing and implementing a fully electronic system for meta-analysis was the requisite upfront time to: decide on which electronic tools to use, determine how these tools would be employed, develop clear guidelines for their use, and train members of the research team. Specific electronic tools improved the efficiency of (a) locating and screening studies, (b) screening and organizing studies and other project documents, (c) extracting data from primary studies, (d) checking data accuracy and analyses, and (e) communication among team members. The purpose of this paper is to describe the electronic processes we designed, using commercially available software, for an extensive quantitative model-testing meta-analysis we are conducting. Commercially available electronic tools, e.g., EndNote, Adobe Acrobat Pro, Blackboard, Excel, and IBM SPSS Statistics (SPSS), are useful for organizing and tracking the meta-analytic process, as well as enhancing communication among research team members. ![]() Meta-analyses of broad scope and complexity require investigators to organize many study documents and manage communication among several research staff.
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