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 doctors...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMJ Publishing Group
2019-08-01
|
| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/9/8/e026997.full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|---|
| ISSN: | 2044-6055 |