Antibiotics and activity spaces: protocol of an exploratory study of behaviour, marginalisation and knowledge diffusion
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.
<jats:sec><jats:title>Background</jats:title><jats:p>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 antibiotic-related health behaviour through three research questions.</jats:p><jats:p>RQ1: What are the manifestations and determinants of problematic antibiotic use in patients’ healthcare-seeking pathways?</jats:p><jats:p>RQ2: Will people’s exposure to antibiotic awareness activities entail changed behaviours that diffuse or dissipate within a network of competing healthcare practices?</jats:p><jats:p>RQ3: Which proxy indicators facilitate the detection of problematic antibiotic behaviours across and within communities?</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>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).</jats:p></jats:sec><jats:sec><jats:title>Discussion</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Trial registration number</jats:title><jats:p><jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="NCT03241316" ext-link-type="clintrialgov" specific-use="clinicaltrial pre-results">NCT03241316</jats:ext-link>; Pre-results.</jats:p></jats:sec>