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

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 ?, 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.

SUBMITTER: Edge R

PROVIDER: S-EPMC6720148 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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

Edge Rhiannon R Keegan Thomas T Isba Rachel R Diggle Peter P

BMJ open 20190830 8

<h4>Objectives</h4>To evaluate the effect of social network influences on seasonal influenza vaccination uptake by healthcare workers.<h4>Design</h4>Cross-sectional, observational study.<h4>Setting</h4>A large secondary care NHS Trust which includes four hospital sites in Greater Manchester.<h4>Participants</h4>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 ...[more]

PMID: 31471430

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Project description:BackgroundPredicting vaccination behaviors accurately could provide insights for health care professionals to develop targeted interventions.ObjectiveThe aim of this study was to develop predictive models for influenza vaccination behavior among children in China.MethodsWe obtained data from a prospective observational study in Wuxi, eastern China. The predicted outcome was individual-level vaccine uptake and covariates included sociodemographics of the child and parent, parental vaccine hesitancy, perceptions of convenience to the clinic, satisfaction with clinic services, and willingness to vaccinate. Bayesian networks, logistic regression, least absolute shrinkage and selection operator (LASSO) regression, support vector machine (SVM), naive Bayes (NB), random forest (RF), and decision tree classifiers were used to construct prediction models. Various performance metrics, including area under the receiver operating characteristic curve (AUC), were used to evaluate the predictive performance of the different models. Receiver operating characteristic curves and calibration plots were used to assess model performance.ResultsA total of 2383 participants were included in the study; 83.2% of these children (n=1982) were <5 years old and 6.6% (n=158) had previously received an influenza vaccine. More than half (1356/2383, 56.9%) the parents indicated a willingness to vaccinate their child against influenza. Among the 2383 children, 26.3% (n=627) received influenza vaccination during the 2020-2021 season. Within the training set, the RF model showed the best performance across all metrics. In the validation set, the logistic regression model and NB model had the highest AUC values; the SVM model had the highest precision; the NB model had the highest recall; and the logistic regression model had the highest accuracy, F1 score, and Cohen κ value. The LASSO and logistic regression models were well-calibrated.ConclusionsThe developed prediction model can be used to quantify the uptake of seasonal influenza vaccination for children in China. The stepwise logistic regression model may be better suited for prediction purposes.

Project description:ObjectiveStudies indicate that initial career intentions and personal characteristics (eg, gender) can influence medical career decision-making. However, little is known about how personal characteristics and intention interact with career decision-making. To address this gap, we examined the link between career intention at the start of the 2-year UK Foundation Programme (FP) and career intentions on its completion.MethodsData came from the 2017 UK National Career Destination Survey, a cross-sectional study completed by all second year foundation doctors. We included respondents' demographics (gender, graduate status on entry to medical school, career intention on starting the FP) and career intention as an outcome measure (eg, specialty (residency) training (UK), NHS non-training posts/further study, career break, working abroad). Multinomial regression was used to assess the independent relationship between background characteristics and career intention.ResultsThere were 6890 participants and 5570 usable responses. 55.9% of respondents were female and 43.1% were male, 77.1% were non-graduates and 22.9% were graduate entrants to medical school. Approximately two-thirds (62.3%, n=2170) of doctors who had an original intention to pursue specialty training after F2, still intended to do so on completion. Most of those who stated at the start of F2 that they did not want to pursue specialty indicated at the end of F2 they would be undertaking other employment opportunities outwith formal training. However, 37.7% of respondents who originally intended to pursue specialty training on FP completion did something different. Graduate entrants to medicine were more likely to immediately progress into specialty training compared with their peers who did medicine as a primary first degree.ConclusionOriginal intention is a strong predictor of career intentions at the end of the FP. However, a considerable proportion of doctors changed their mind during the FP. Further research is needed to understand this behaviour.

Project description:OBJECTIVE:To actively solicit adverse events experienced in the days following immunisation with quadrivalent inactivated influenza vaccine using Australia's near real-time, participant-based vaccine safety surveillance system, AusVaxSafety. DESIGN AND SETTING:Observational cohort study conducted in 194 sentinel surveillance immunisation sites (primary care, hospital and community-based clinics) across Australia. PARTICIPANTS:Individuals aged ?6 months who received a routine seasonal influenza vaccine at a participating site (n=102?911) and responded to a survey (via short message service or email) sent 3 days after vaccination about adverse events experienced (n=73?892; 71.8%). MAIN OUTCOME MEASURE:Near real-time and cumulative participant-reported rates of any adverse event, fever or medical attendance experienced within 3 days after vaccination overall, by brand, age, pregnancy status and concomitant vaccine receipt. RESULTS:Participant median age was 57 years (range: 6 months to 102 years); 58.1% (n=42?869) were female and 2.7% (n=2018) were pregnant. Near real-time fast initial response cumulative summation and Bayesian analyses of weekly event rates did not demonstrate a safety signal. Children aged 6 months to 4 years had higher event rates (522/6180; 8.4%) compared with older ages; participants aged ?65 years reported fewer events (1695/28 154; 6.0%). There were no clinically significant differences in safety between brands, by age group or overall. Cumulative data analysis demonstrated that concomitant vaccination was associated with increased rates of fever (2.1% vs 0.8%) and medical attendance (0.8% vs 0.4%), although all rates were low and did not exceed expected levels. CONCLUSIONS:Novel, postmarketing AusVaxSafety surveillance demonstrated comparable and expected safety outcomes for the 2017 quadrivalent inactivated influenza vaccine brands used in Australia. These near real-time, participant-reported data are expected to encourage confidence in vaccine safety and promote uptake.

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

Publications

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

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