| dc.contributor.author |
Haenssgen MJ, Charoenboon N, Zanello G, Mayxay M, Reed-Tsochas F, Jones COH,Kosaikanont R, Praphattong P, Manohan P, Lubell Y, Newton PN, Keomany S, Wertheim HFL, Lienert J, Xayavong T, Warapikuptanun P, Khine Zaw Y, U-Thong P,Benjaroon P, Sangkham N, Wibunjak K, Chai-In P, Chailert S, Thavethanutthanawin P, Promsutt K, Thepkhamkong A, Sithongdeng N, Keovilayvanh M, Khamsoukthavong N, Phanthasomchit P, Phanthavong C, Boualaiseng S, Vongsavang S, Greer RC, Althaus T, Nedsuwan S, Intralawan D, Wangrangsimakul T, Limmathurotsakul D, Ariana P. |
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| dc.description.abstract |
Background: Antimicrobial resistance (AMR) is a global health priority. Leading UK
and global strategy papers to fight AMR recognise its social and behavioural dimensions,
but current policy responses to improve the popular use of antimicrobials (eg, antibiotics)
are limited to education and awareness-raising campaigns. In response to conceptual,
methodological and empirical weaknesses of this approach, we study people's antibioticrelated health behaviour through three research questions.RQ1: What are the
manifestations and determinants of problematic antibiotic use in patients' healthcareseeking pathways?RQ2: Will people's exposure to antibiotic awareness activities entail
changed behaviours that diffuse or dissipate within a network of competing healthcare
practices?RQ3: Which proxy indicators facilitate the detection of problematic antibiotic
behaviours across and within communities?
Methods: We apply an interdisciplinary analytical framework that draws on the public
health, medical anthropology, sociology and development economics literature. Our
research involves social surveys of treatment-seeking behaviour among rural dwellers in
northern Thailand (Chiang Rai) and southern Lao PDR (Salavan). We sample
approximately 4800 adults to produce district-level representative and social network
data. Additional 60 cognitive interviews facilitate survey instrument development and
data interpretation. Our survey data analysis techniques include event sequence analysis
(RQ1), multilevel regression (RQ1-3), social network analysis (RQ2) and latent class
analysis (RQ3).
Discussion: Social research in AMR is nascent, but our unprecedentedly detailed data on
microlevel treatment-seeking behaviour can contribute an understanding of behaviour
beyond awareness and free choice, highlighting, for example, decision-making
constraints, problems of marginalisation and lacking access to healthcare and competing
ideas about desirable behaviour. |
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