Analysis of evidence appraisals for interventional studies in family medicine using an informatics approach

Abstract

Abstract This study reports the first assessment of published comments in the family medicine literature using structured codes, which produced commentary annotations that will be the foundation of a knowledge base of appraisals of family medicine trials. Evidence appraisal occurs in a variety of formats and serves to shed light on the quality of research. However, scientific discourse generally and evidence appraisal in particular has not itself been analyzed for insights. A search strategy was devised to identify all journal comments indexed in PubMed linked to controlled intervention studies published in a recent 15-year period in major family medicine journals. A previously developed structured representation in the form of a list of appraisal concepts was used to formally annotate and categorize the journal comments through an iterative process. Trends in family medicine evidence appraisal were then analyzed. A total of 93 comments on studies from five journals over 15 years were included in the analysis. Two thirds of extracted appraisals were negative criticisms. All appraisals of measurement instruments were negative (100%). The participants baseline characteristics, the author discussions, and the design of the interventions were also criticized (respectively 91.7%, 84.6% and 83.3% negative). In contrast, appraisals of the scientific basis of the studies were positive (81.8%). The categories with the most appraisals were, most generally, those focused on the study design, and most specifically, those focused on the scientific basis. This study provides a new data-driven approach to review scientific discourse regarding the strengths and limitations of research within academic family medicine. This methodology can potentially generalize to other medical domains. Structured appraisal data generated here will enable future clinical, scientific, and policy decision-making and broader meta-research in family medicine.