Statistical analyses
REGRESSION, FLU, CHRONIC DISEASE
Continuous data were analyzed with the Mann–Whitney U test, or with the Kruskal–Wallis-test in case of comparing continuous data within three groups (three different media outlets). Binary, ordinal or nominal data were analyzed with the Chi-Square test. The outcome measure ‘improvement of vaccine willingness’ was defined as participants who answered ‘disagree’ to the question whether they were pro-influenza vaccination before watching the campaign video, and switched to ‘agree’ after watching the campaign video. Improvement of vaccine willingness, which means converted from against to pro-influenza vaccination, was coded by 1 and no improvement was coded by 0. Differences in improvement of vaccine willingness between participants who watched our campaign video with a Dutch versus Indian communicator or between different media outlets were analyzed with the Chi-Square test. A binary logistic regression was performed to analyze unadjusted and adjusted (with different predictors in the model) odds ratios concerning improvement of vaccine willingness. Within the adjusted regression model to predict improvement of vaccine willingness in the vaccine hesitant group, we controlled for media outlet, communicator, age, gender, migration background, education level, and chronic disease. We did not control for ‘flu shot each year’, because this relationship with vaccine willingness was too obvious. Overall, results are reported as frequencies (with percentages, and minimum and maximum) or medians (with quartiles 1 and 3, and minimum and maximum).