Why Antimicrobial Resistance Messaging Fails: Qualitative Insights Through the Elaboration Likelihood Model Article Swipe

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Eva M. Krockow , David R. Jenkins , Samkele Mkumbuzi , Stephen J. Flusberg , Carolyn Tarrant ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.31234/osf.io/f8bev_v1

Objective: This study examined perceptions of current antimicrobial resistance (AMR) communications to improve future messaging, counter misinformation, and promote behaviour change. It extends previous research through focus groups with doctors and patients, analysed using the Elaboration Likelihood Model (ELM). Methods: We held 3 focus groups (n=15) with UK patients with recent experience of AMR and 4 (n=14) with hospital doctors experienced in AMR treatment and communication. Semi-structured questions explored perceptions of public AMR messaging. Data were analysed using reflexive thematic analysis. Results: Most participants found public AMR information difficult to access, overly technical, and unclear. They struggled to find personal and cultural relevance, described the tone as punitive and highlighted contradictory advice (e.g., discouraging antibiotic use while recommending full course completion), undermining argument quality. Some appreciated buzzwords like ‘superbugs’, but most felt that messages lacked impact and “punch”. When viewed through the ELM, the problematic tone and lack of personalisation reduced recipients’ motivation. The lack of readily available, clear information hindered their ability to engage in central route processing, reducing the likelihood of elaboration and subsequent persuasion. Attitude change from peripheral route information processing was equally questionable given the lack of persuasive message cues. Conclusions: Current AMR messaging is insufficient and risk communication theory could highlight areas for improvement. Our ELM analysis suggests a need to enhance motivation, capability, and argument quality while adding persuasive, peripheral cues. Personally and culturally tailored messages with a positive, solution-focused tone and simplified, engaging language may boost impact and promote lasting attitude change.

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Elaboration Elaboration likelihood model Resistance (ecology) Computer science Psychology Social psychology Biology Art Humanities Persuasion Ecology

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Type: preprint
Language: en
Landing Page: https://doi.org/10.31234/osf.io/f8bev_v1
OA Status: gold
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DOI: https://doi.org/10.31234/osf.io/f8bev_v1

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Title: Why Antimicrobial Resistance Messaging Fails: Qualitative Insights Through the Elaboration Likelihood Model

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Type: preprint

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Language: en

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Publication year: 2025

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Publication date: 2025-04-07

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Authors: Eva M. Krockow, David R. Jenkins, Samkele Mkumbuzi, Stephen J. Flusberg, Carolyn Tarrant

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Landing page: https://doi.org/10.31234/osf.io/f8bev_v1

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OA status: gold

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OA URL: https://doi.org/10.31234/osf.io/f8bev_v1

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Concepts: Elaboration, Elaboration likelihood model, Resistance (ecology), Computer science, Psychology, Social psychology, Biology, Art, Humanities, Persuasion, Ecology

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