Preparing for Antibiotic Resistance Campaigns: A Person-Centered Approach to Audience Segmentation

Rachel A. Smith, Madisen Quesnell, Lydia Glick, Nicole Hackman, Nkuchia M. M'Ikanatha

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Antibiotic resistance is a growing threat to public health that calls for urgent attention. However, creating campaigns to slow the emergence and spread of drug-resistant pathogens is challenging because the goal - antibiotic stewardship - encompasses multiple behaviors. This study provided a novel approach to audience segmentation for a multifaceted goal, by using a person-centered approach to identify profiles of U.S. adults based on shared stewardship intentions. The latent class analysis identified three groups: stewards, stockers, and demanders. The findings suggest campaigns with goals aimed at encouraging stewards to follow through on their intentions, encouraging stockers to dispose of their leftover antibiotics, and convincing demanders to accept providers' evidence-based judgment when a prescription for antibiotics is not indicated. Covariate analysis showed that people who held more inaccurate beliefs about what antibiotics can treat had higher odds of being demanders and stockers instead of stewards. People with stronger health mavenism also had higher odds of being stockers instead of stewards. The covariate analysis provided theoretical insight into the strategies to pursue in campaigns targeting these 3 groups.

Original languageEnglish (US)
Pages (from-to)1433-1440
Number of pages8
JournalJournal of Health Communication
Volume20
Issue number12
DOIs
StatePublished - Dec 2 2015

All Science Journal Classification (ASJC) codes

  • Health(social science)
  • Communication
  • Public Health, Environmental and Occupational Health
  • Library and Information Sciences

Fingerprint

Dive into the research topics of 'Preparing for Antibiotic Resistance Campaigns: A Person-Centered Approach to Audience Segmentation'. Together they form a unique fingerprint.

Cite this