Skip to main navigation Skip to search Skip to main content

Integrating Models of Diffusion and Behavior to Predict Innovation Adoption, Maintenance, and Social Diffusion

  • Rachel A. Smith
  • , Youllee Kim
  • , Xun Zhu
  • , Dimi Théodore Doudou
  • , Eleanore D. Sternberg
  • , Matthew B. Thomas

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

This study documents an investigation into the adoption and diffusion of eave tubes, a novel mosquito vector control, during a large-scale scientific field trial in West Africa. The diffusion of innovations (DOI) and the integrated model of behavior (IMB) were integrated (i.e., innovation attributes with attitudes and social pressures with norms) to predict participants’ (N = 329) diffusion intentions. The findings showed that positive attitudes about the innovation’s attributes were a consistent positive predictor of diffusion intentions: adopting it, maintaining it, and talking with others about it. As expected by the DOI and the IMB, the social pressure created by a descriptive norm positively predicted intentions to adopt and maintain the innovation. Drawing upon sharing research, we argued that the descriptive norm may dampen future talk about the innovation, because it may no longer be seen as a novel, useful topic to discuss. As predicted, the results showed that as the descriptive norm increased, the intention to talk about the innovation decreased. These results provide broad support for integrating the DOI and the IMB to predict diffusion and for efforts to draw on other research to understand motivations for social diffusion.

Original languageEnglish
Pages (from-to)264-271
Number of pages8
JournalJournal of Health Communication
Volume23
Issue number3
DOIs
StatePublished - Mar 4 2018

Bibliographical note

Funding Information:
This work was supported by a grant to the Pennsylvania State University from the Bill & Melinda Gates foundation [grant number OPP1131603].

Publisher Copyright:
©, Published with license by Taylor & Francis.

Funding

This work was supported by a grant to the Pennsylvania State University from the Bill & Melinda Gates foundation [grant number OPP1131603].

FundersFunder number
Bill and Melinda Gates FoundationOPP1131603
The Pennsylvania State University

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    ASJC Scopus subject areas

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

    Fingerprint

    Dive into the research topics of 'Integrating Models of Diffusion and Behavior to Predict Innovation Adoption, Maintenance, and Social Diffusion'. Together they form a unique fingerprint.

    Cite this