You are here

  • Home
  • Archive
  • Volume 9, Issue 8
  • Observational study to assess the effects of social networks on the seasonal influenza vaccine uptake by early career doctors

Article Text

Article menu

Download PDFPDF

XML
Occupational and environmental medicine
Research
Observational study to assess the effects of social networks on the seasonal influenza vaccine uptake by early career doctors
  1. Rhiannon Edge1,
  2. Thomas Keegan1,
  3. Rachel Isba1,
  4. Peter Diggle1,2
  1. 1Lancaster Medical School, Lancaster University, Lancaster, UK
  2. 2Epidemiology and Population Health, University of Liverpool, Liverpool, UK
  1. Correspondence to Dr Rhiannon Edge; r.edge{at}lancs.ac.uk

Abstract

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.

  • social network analysis
  • influenza vaccination
  • auto-logistic regression
  • occupational health

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/.

https://doi.org/10.1136/bmjopen-2018-026997

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    View Full Text

    Footnotes

    • Contributors RE wrote the manuscript with input from all other authors all of which have approved the final version. RE collected the data. PJD advised on the statistical methodology which was implemented by RE. TJK guided the initial data collection and SN analysis. All authors contributed to the conception of the project. This study is part of a larger programme of work devised by RI.

    • Funding This work was supported by the Colt Foundation.

    • Competing interests None declared.

    • Patient consent for publication Not required.

    • Ethics approval Prospective ethical approval was obtained (15RECNA17) from Lancaster University Research Ethics Committee and the Pennine Acute Hospitals NHS Trust.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data availability statement Data are available in a public, open access repository.