Abstract
Background: Omics-based biomarkers (OBMs) inform precision medicine (PM). As omics-based technologies gradually move into clinical settings, however, a co-occurrence of biomedical research and clinical practice is likely an important variable in the implementation of PM. Currently, little is known about the implications of such research-practice co-occurrence. Methods: This study used data collected from a pilot study designed to inform a full-scale PM implementation study through the validation of the measurement tool. It applied item response theory (IRT) methods to assess the tool’s reliability and measurement invariance across two study subgroups associated with research and practice settings. Results: The study sample consisted of 31 participants. Measurement invariance assessment was through differential item functioning (DIF) analysis with bootstrapping through Monte Carlo simulation. Overall, 13 out of 22 items that formed the PMI scale had DIF at significance level α=0.25. Item response functions (IRFs) revealed how each subgroup members responded to scale items and their attitudes towards factors that influence PM implementation. Conclusions: Attitudinal similarities and differences towards factors influencing PM implementation amongst those in biomedical research as compared with those in practice were established. Results indicated PM implementation knowledge that is unique and common to both groups. The study established the validity and reliability of the new PM implementation measurement tool for the two subgroups.
Highlights
Recent advances in omics technologies offer greater understandings of how gene-environment interactions affect health and pathological processes
item response theory (IRT) allowed for a critical examination of the information that was harvested from the manner study participants endorsed and ranked the various items associated with precision medicine (PM) implementation
In as much as public health and clinical practice through PM may benefit from advances in omics technologies and deeper gene-environment insights that flow from rigorous biomedical research, research benefits from being informed by practice problems and practical knowledge, leading to co-creation of solutions to broader PM issues in both spheres
Summary
Recent advances in omics technologies offer greater understandings of how gene-environment interactions affect health and pathological processes. Evidencebased medicine (EBM)[2], the widely applied and accepted approach to medicine, is mostly informed by systematic reviews, meta-analyses or group-level studies from which average recommendations for the “average person” are derived. In emphasizing individual uniqueness at the molecular level and tailored care based on uniqueness of genotype, PM enables advanced detection of pre-symptomatic conditions in the population and individuals, while improving surveillance and management of infectious diseases This results in better-adapted and personalized therapies, significantly delayed disease onset, as well as disease prevention. Methods: This study used data collected from a pilot study designed to inform a full-scale PM implementation study through the validation of the measurement tool It applied item response theory (IRT) methods to assess the tool’s reliability and measurement invariance across two study subgroups associated with research and practice settings. The study established the validity and reliability of the new PM implementation measurement tool for the two subgroups
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