How to boost the boosters? A survey-experiment on the effectiveness of different policies aimed at enhancing acceptance of a “Seasonal” vaccination against COVID-19

Table 2 Logistic regression with periodical vaccination strong-acceptance as a dependent variable

	Model 1			Model 2			Model 3
	B	SE	Exp(B)	B	SE	Exp(B)	B	SE	Exp(B)
Constant	−2.446***	0.397	0.087	−5.901***	1.362	0.003	−5.756***	1.406	0.003
Gender	0.181	0.176	1.198	− 0.271	0.241	1.011	− 0.246	0.245	0.782
Age	0.028***	0.006	1.028	0.011	0.008	1.022	0.012	0.008	1.012
Parenthood	− 0.132	0.183	0.876	0.022	0.242	1.000	0.027	0.247	1.027
Income	0.128	0.080	1.137	0.000	0.105	0.875	− 0.014	0.107	0.986
Education	− 0.087	0.069	0.916	− 0.134	0.091	1.280	− 0.148	0.092	0.862
Sector-UO^ab	0.047	0.420	1.048	0.247	0.630	2.107	0.089	0.634	1.093
Sector-Arab^b	0.147	0.288	1.158	0.745	0.420	0.770	0.716	0.434	2.047
Past COVID vaccination				− 0.261	0.889	2.662	− 0.248	0.925	0.780
Perceived benefits				0.979***	0.176	0.401	1.027***	0.180	2.793
Perceived barriers				− 0.914***	0.144	1.049	− 0.912***	0.146	0.402
Severity				0.048	0.160	1.382	0.077	0.163	1.080
Susceptibility				0.324*	0.171	1.364	0.280	0.173	1.323
Self-efficacy				0.311*	0.176	0.995	0.311*	0.179	1.365
Trust in Government				− 0.005	0.005	1.021	− 0.005	0.005	0.995
Social norms				0.021**	0.007	1.053	0.023**	0.007	1.023
Had COVID				0.052	0.389	0.917	0.126	0.389	1.134
Relatives had COVID				− 0.087	0.258	1.011	− 0.033	0.262	0.967
Mandate v. negative incentive							− 0.694*	0.324	0.500
Positive Incentive v. negative incentive							− 0.340	0.321	0.712
Information v. negative incentive							−1.113**	0.332	0.328
-2 Log likelihood	809.810			495.106			482.395
Nagelkerke R²	0.052			0.537			0.552

N = 799; *p < 0.05; **p < 0.01; ***p < 0.001; ^aUO—Ultra-orthodox; ^bReference group: General Jewish population

ISSN: 2045-4015