The COVID-19 global vaccination campaign was justified as a necessary exit strategy from an unprecedented public health, social, and economic crisis. However, concerns about adverse effects post-vaccination—particularly autoimmune reactions—have received comparatively less attention in the peer-reviewed literature. This protocol outlines a two-phase qualitative coding study that builds on a completed scoping review of 109 peer-reviewed articles to evaluate how associations between COVID-19 vaccination and autoimmune disorders are interpreted and framed. Accordingly, rather than adjudicating the scientific truth of vaccine-related claims, the study will examine whether interpretations are proportionate to the evidence presented and internally consistent. Phase 1 will focus on biological plausibility by extracting mechanistic explanations, such as molecular mimicry, bystander activation, and cytokine dysregulation, and assessing whether the mechanistic evidence reported aligns with authors' conclusions. Phase 2 will focus on epistemic integrity by applying a typology to analyze the evidentiary consistency between claims about vaccine-related harms and benefits within studies. Quotations will be extracted and analyzed for causal reasoning, rhetorical framing, and evidentiary symmetry. Articles will be double-coded, with inter-rater reliability assessed and adjudicated through discussion. By integrating mechanistic and epistemic analyses, the planned study will provide a framework for evaluating the interpretive standards applied to vaccine safety claims. Rather than reaffirming or rejecting specific biomedical positions, it will document how scientific knowledge is framed, qualified, or selectively emphasized—highlighting interpretive practices that have shaped evidence-based discourse within a climate of perceived urgency and institutional consensus.
No takes yet. Share an insight, caveat, or question.
Claudia Chaufan (2025) studied this question.
Synapse has enriched 5 related papers. Consider them for comparative context: