Beyond the Dichotomy: A Systematic Review of ELM in Health Information Elaboration
Abstract
The Elaboration Likelihood Model (ELM) is a foundational framework for understanding information processing and attitude change, yet its application within the complex domain of health information remains fragmented. This paper provides a comprehensive review to synthesize the extant literature on users’ health information elaboration. Through a systematic review of literature from major academic databases (including Web of Science, Scopus, EBSCO, and CNKI), this paper aims to (1) systematically map the conceptualization and operationalization of central and peripheral pathways, (2) integrate multidisciplinary research on information processing modes, and (3) identify critical gaps. The analysis reveals three primary findings: First, while ELM is widely adopted in health research to study outcomes like information adoption, the operationalization of central and peripheral routes is highly inconsistent. Second, research on information processing modes is siloed across psychology, information behavior, and computer science, lacking an integrated framework. Third, a critical gap exists wherein most studies treat the two processing routes as dichotomous extremes, neglecting their potential mixed use. This review synthesizes a fragmented field and highlights the need to move beyond a static, binary view of elaboration. The study proposes a research agenda focused on modeling the dynamic and mixed-use of pathways, examining the influence of user context (e.g., active search vs. passive browsing) on pathway selection, and employing more objective, real-world behavioral data to analyze users’ attention allocation and processing patterns.
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