A Unified Theoretical Framework of Learning Theories to Inform and Guide Public Health Continuing Medical Education Research and Practice

2021 
ABSTRACT Continuing medical education (CME) emerged at the start of the 20th century as a means of maintaining clinical competence among health care practitioners. However, evidence indicates that CME is often poorly developed and inappropriately used. Consequently, there has been increasing interest in the literature in evaluating wider contexts at play in CME development and delivery. In this article, the authors present a unified theoretical framework, grounded in learning theories, to explore the role of contextual factors in public health CME for health care practitioners. Discussion with pedagogical experts together with a narrative review of learning theories within medical and social science literature informed the framework's development. The need to consider sociocultural theories of learning within medical education restricted suitable theories to those that recognized contexts beyond the individual learner; adopted a systems approach to evaluate interactions between contexts and learner; and considered learning as more than mere acquisition of knowledge. Through a process of rigorous critical analysis, two theoretical models emerged as contextually appropriate: Biggs principle of constructive alignment and Bronfenbrenner bioecological model of human development. Biggs principle offers theoretical clarity surrounding interactive factors that encourage lifelong learning, whereas the Bronfenbrenner model expands on these factor's roles across multiple system levels. The authors explore how unification into a single framework complements each model while elaborating on its fundamental and practical applications. The unified theoretical framework presented in this article addresses the limitations of isolated frameworks and allows for the exploration of the applicability of wider learning theories in CME research.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    55
    References
    0
    Citations
    NaN
    KQI
    []