Knowledge Gaps, Cognition and Media Learning: Designing Tailored Messages to Address COVID-19 Communication Inequalities

Figures & data

Table 1. Linear regression analyses: Demographic predictors of media learning, vaccine hesitancy, vaccine intentions, standardized regression coefficients for demographic predictors

Predictor	Model 1 (Media Learning)		Model 2 (Vaccine Hesitancy)	Model 3 (Vaccination Intentions)
	Recognition	Comprehension
Income	−.029	−.054	.023	.013
Education	.054	.045	−.022	−.037
Age	.256*	.206*	−.124*	−.048
Covid Experience	.085*	−.040	−.562	.051

*p<.05. **p<.01. ***p<.001.

Table 2. Anova results for mean comparisons by age in media learning

Media Learning Variables	Age	Mean	F (p)
Recognition	18–24	2.22	19.357 (.000)
	25–44	2.66
	45–65	3.16
Comprehension	18–24	2.05	13.439 (.000)
	25–44	2.47
	45–65	2.82

Table 3. Anova results for mean comparisons by age in vaccine hesitancy

Outcome variable	Age	Mean	F (p)
Vaccine Hesitancy	18–24	4.08	3.50(.03)
	25–44	3.81
	45–65	3.56

Table 4. Univariate message effects on elaboration, media learning

Dependent variables	F	df	p	Partial eta squared (η^2)	Mean scores by message types-sources**
					I-I(Gov)	S-C (Gov)	I-I(In)	S-C (In)
Elaboration*	3.45	3,608	.02	.02	6.14	6.84	6.51	6.33
Recognition	1.12	3,608	.34	.01	2.72	2.66	2.72	2.59
Comprehension	2.34	3,608	.07	.01	2.45	2.5	2.55	2.35

*Elaboration is measured with a 7-point scale

**I-I(Gov)= Informational-Instrumental message (Government source); S-C (Gov)= Social control-Communal message (Government source); I-I(In)= Informational-Instrumental message (Influencer source); S-C (In) Social control-Communal message(InfluencerSource).