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Observational study to assess the effects of social networks on the seasonal influenza vaccine uptake by early career doctors

OBJECTIVES: To evaluate the effect of social network influences on seasonal influenza vaccination uptake by healthcare workers. DESIGN: Cross-sectional, observational study. SETTING: A large secondary care NHS Trust which includes four hospital sites in Greater Manchester. PARTICIPANTS: Foundation d...

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Autores principales: Edge, Rhiannon, Keegan, Thomas, Isba, Rachel, Diggle, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6720148/
https://www.ncbi.nlm.nih.gov/pubmed/31471430
http://dx.doi.org/10.1136/bmjopen-2018-026997
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author Edge, Rhiannon
Keegan, Thomas
Isba, Rachel
Diggle, Peter
author_facet Edge, Rhiannon
Keegan, Thomas
Isba, Rachel
Diggle, Peter
author_sort Edge, Rhiannon
collection PubMed
description OBJECTIVES: To evaluate the effect of social network influences on seasonal influenza vaccination uptake by healthcare workers. DESIGN: Cross-sectional, observational study. SETTING: A large secondary care NHS Trust which includes four hospital sites in Greater Manchester. PARTICIPANTS: Foundation doctors (FDs) working at the Pennine Acute Hospitals NHS Trust during the study period. Data collection took place during compulsory weekly teaching sessions, and there were no exclusions. Of the 200 eligible FDs, 138 (70%) provided complete data. PRIMARY OUTCOME MEASURES: Self-reported seasonal influenza vaccination status. RESULTS: Among participants, 100 (72%) reported that they had received a seasonal influenza vaccination. Statistical modelling demonstrated that having a higher proportion of vaccinated neighbours increased an individual’s likelihood of being vaccinated. The coefficient for γ, the social network parameter, was 0.965 (95% CI: 0.248 to 1.682; odds: 2.625 (95% CI: 1.281 to 5.376)), that is, a diffusion effect. Adjusting for year group, geographical area and sex did not account for this effect. CONCLUSIONS: This population exhibited higher than expected vaccination coverage levels–providing protection both in the workplace and for vulnerable patients. The modelling approach allowed covariate effects to be incorporated into social network analysis which gave us a better understanding of the network structure. These techniques have a range of applications in understanding the role of social networks on health behaviours.
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spelling pubmed-67201482019-09-17 Observational study to assess the effects of social networks on the seasonal influenza vaccine uptake by early career doctors Edge, Rhiannon Keegan, Thomas Isba, Rachel Diggle, Peter BMJ Open Occupational and Environmental Medicine OBJECTIVES: To evaluate the effect of social network influences on seasonal influenza vaccination uptake by healthcare workers. DESIGN: Cross-sectional, observational study. SETTING: A large secondary care NHS Trust which includes four hospital sites in Greater Manchester. PARTICIPANTS: Foundation doctors (FDs) working at the Pennine Acute Hospitals NHS Trust during the study period. Data collection took place during compulsory weekly teaching sessions, and there were no exclusions. Of the 200 eligible FDs, 138 (70%) provided complete data. PRIMARY OUTCOME MEASURES: Self-reported seasonal influenza vaccination status. RESULTS: Among participants, 100 (72%) reported that they had received a seasonal influenza vaccination. Statistical modelling demonstrated that having a higher proportion of vaccinated neighbours increased an individual’s likelihood of being vaccinated. The coefficient for γ, the social network parameter, was 0.965 (95% CI: 0.248 to 1.682; odds: 2.625 (95% CI: 1.281 to 5.376)), that is, a diffusion effect. Adjusting for year group, geographical area and sex did not account for this effect. CONCLUSIONS: This population exhibited higher than expected vaccination coverage levels–providing protection both in the workplace and for vulnerable patients. The modelling approach allowed covariate effects to be incorporated into social network analysis which gave us a better understanding of the network structure. These techniques have a range of applications in understanding the role of social networks on health behaviours. BMJ Publishing Group 2019-08-30 /pmc/articles/PMC6720148/ /pubmed/31471430 http://dx.doi.org/10.1136/bmjopen-2018-026997 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Occupational and Environmental Medicine
Edge, Rhiannon
Keegan, Thomas
Isba, Rachel
Diggle, Peter
Observational study to assess the effects of social networks on the seasonal influenza vaccine uptake by early career doctors
title Observational study to assess the effects of social networks on the seasonal influenza vaccine uptake by early career doctors
title_full Observational study to assess the effects of social networks on the seasonal influenza vaccine uptake by early career doctors
title_fullStr Observational study to assess the effects of social networks on the seasonal influenza vaccine uptake by early career doctors
title_full_unstemmed Observational study to assess the effects of social networks on the seasonal influenza vaccine uptake by early career doctors
title_short Observational study to assess the effects of social networks on the seasonal influenza vaccine uptake by early career doctors
title_sort observational study to assess the effects of social networks on the seasonal influenza vaccine uptake by early career doctors
topic Occupational and Environmental Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6720148/
https://www.ncbi.nlm.nih.gov/pubmed/31471430
http://dx.doi.org/10.1136/bmjopen-2018-026997
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