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Developing a logic model for communication-based interventions on antimicrobial resistance (AMR).

Publication ,  Journal Article
Virhia, J; Laurie, E; Lembo, T; Seni, J; Pollack, R; Davis, A; Mapunjo, S; Mshana, SE; Mmbaga, BT; Hilton, S
Published in: PLOS global public health
January 2024

The importance of communication in enhancing people's awareness and understanding of antimicrobial resistance (AMR) is consistently recognised in global and national action plans (NAPs). Despite this, there have been relatively few national AMR communication campaigns which use a structured approach to take account of the local context, encompass co-design with the target audience and use a logic model to help inform its design, implementation and evaluation. Designing a logic model for communication-based interventions can help map out the planning, resources, messaging, assumptions and intended outcomes of the campaign to maximise its impact, ensure it is fit for context and minimise any unintended consequences on individuals and society. Building on an AMR research project in Tanzania, Supporting the National Action Plan for AMR (SNAP-AMR), we co-designed the SNAP-AMR Logic Model with key stakeholders to implement AMR communication campaigns and related legacy materials to be employed in support of the Tanzanian NAP, but with broader relevance to a range of contexts. In developing the SNAP-AMR Logic Model, we reviewed relevant communication theories to create and target messages, and we considered behavioural change theories. We defined all key elements of the SNAP-AMR Logic Model as follows: (1) resources (inputs) required to enable the design and implementation of campaigns, e.g. funding, expertise and facilities; (2) activities, e.g. co-design of workshops (to define audience, content, messages and means of delivery), developing and testing of materials and data collection for evaluation purposes; (3) immediate deliverables (outputs) such as the production of legacy materials and toolkits; and (4) changes (outcomes) the campaigns aim to deliver, e.g. in social cognition and behaviours. The SNAP-AMR Logic Model efficiently captures all the elements required to design, deliver and evaluate AMR communication-based interventions, hence providing government and advocacy stakeholders with a valuable tool to implement their own campaigns. The model has potential to be rolled out to other countries with similar AMR socio-cultural, epidemiological and economic contexts.

Published In

PLOS global public health

DOI

EISSN

2767-3375

ISSN

2767-3375

Publication Date

January 2024

Volume

4

Issue

6

Start / End Page

e0002965
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Virhia, J., Laurie, E., Lembo, T., Seni, J., Pollack, R., Davis, A., … Hilton, S. (2024). Developing a logic model for communication-based interventions on antimicrobial resistance (AMR). PLOS Global Public Health, 4(6), e0002965. https://doi.org/10.1371/journal.pgph.0002965
Virhia, Jennika, Emma Laurie, Tiziana Lembo, Jeremiah Seni, Roxana Pollack, Alicia Davis, Siana Mapunjo, Stephen E. Mshana, Blandina T. Mmbaga, and Shona Hilton. “Developing a logic model for communication-based interventions on antimicrobial resistance (AMR).PLOS Global Public Health 4, no. 6 (January 2024): e0002965. https://doi.org/10.1371/journal.pgph.0002965.
Virhia J, Laurie E, Lembo T, Seni J, Pollack R, Davis A, et al. Developing a logic model for communication-based interventions on antimicrobial resistance (AMR). PLOS global public health. 2024 Jan;4(6):e0002965.
Virhia, Jennika, et al. “Developing a logic model for communication-based interventions on antimicrobial resistance (AMR).PLOS Global Public Health, vol. 4, no. 6, Jan. 2024, p. e0002965. Epmc, doi:10.1371/journal.pgph.0002965.
Virhia J, Laurie E, Lembo T, Seni J, Pollack R, Davis A, Mapunjo S, Mshana SE, Mmbaga BT, Hilton S. Developing a logic model for communication-based interventions on antimicrobial resistance (AMR). PLOS global public health. 2024 Jan;4(6):e0002965.

Published In

PLOS global public health

DOI

EISSN

2767-3375

ISSN

2767-3375

Publication Date

January 2024

Volume

4

Issue

6

Start / End Page

e0002965