Development and Validation of the Multidimensional COVID-19 Vaccine Hesitancy Scale

Figures & data

Table 1. Sociodemographics and medical characteristics of the sample (N = 1503)

Participant characteristics		N (%)
Age, Range (M± SD)		18–77 (36.88 ± 12.68)
Gender	Male	196 (13.0)
	Female	1307 (87.0)
Educational level	Grade 8 or less	3 (.2)
	Professional school/Grade 10	11 (.7)
	High school without baccalaureate	42 (2.8)
	Baccalaureate	449 (29.9)
	College, university	636 (42.3)
	Master’s degree	300 (20.0)
	PhD	46 (3.1)
	Other	16 (1.1)
Country	Ro	611 (40.7)
	Hu	824 (54.8)
	Other	68 (4.5)
Chronic disease	No	1192 (79.3)
	Yes	311 (20.7)
Flu vaccine past	No	1172 (78.0)
	Yes	331 (22.0)
Optional vaccine past	No	456 (30.3)
	Yes	1047 (69.7)
Diagnosed Covid-19	No	1073 (71.4)
	Yes	273 (18.2)
	Not sure	157 (10.4)
Vaccine intention	Do not consider	459 (30.5)
	Undecided	204 (13.6)
	Vaccinated	434 (28.9)
	Other	406 (27)
Vaccine type	Pfizer	430 (28.6)
	AstraZeneca	125 (8.3)
	Moderna	60 (4.0)
	Sinopharm	45 (3.0)
	Sputnik	70 (4.7)
	Johnson-Johnson	2 (.1)
	No answer	95 (6.3)
	Was not vaccinated	676 (45.0)

Values represent frequency and percentage, unless indicated otherwise.

Table 2. Summary of exploratory factor analysis for the Multidimensional COVID-19 Vaccine Hesitancy Scale/CoVaH (N = 1503)

Items		Component
		1. Skepticism	2. Risk	3. Fear
1.	A Covid-19 védőoltások beadatása jó mód arra, hogy megvédjem magam a Covid-19 betegségtől (R). (Getting Covid-19 vaccines is a good means to protect myself from the Covid-19 disease (R).)	.851	.383	.167
2.	A Covid-19 elleni védőoltások fontosak az egészségem szempontjából (R). (Covid-19 vaccines are important for my health (R).)	.850	.351	.147
3.	A védőoltás fontos a közösségem tagjainak egészsége szempontjából (R). (To be vaccinated is important for the health of others in my community (R).)	.837	.364	.177
4.	A Covid-19 elleni védőoltások hatékonyak (R). (Covid-19 vaccines are effective (R).)	.798	.417	.185
5.	Általában azt teszem, amit az orvosom javasol a Covid-19 védőoltásokkal kapcsolatban (R). (Generally, I do what my doctor or health care provider recommends about Covid −19 vaccines (R).)	.766	.206	.109
6.	A Covid-19 védőoltások súlyos allergiás reakciókat okozhatnak (anafilaxiás sokk). (Covid-19 vaccines can lead to severe allergic reactions (anaphylactic shock).)	.264	.783	.218
7.	A Covid-19 védőoltások kiválthatják azt a betegséget, amely ellen épp védelmet kellene nyújtaniuk. (Covid-19 vaccinations can cause the very illness they are designed to prevent.)	.379	.755	.207
8.	A Covid-19 elleni védőoltások vérrögöket és komplikációkat (pl. trombózis, embólia) okozhatnak. (Covid-19 vaccinations can cause blood clots and complications (ex. thrombosis, embolism).)	.238	.752	.220
9.	A Covid-19 védőoltások túlterhelik az immunrendszert. (Covid-19 vaccines overwhelm the immune system.)	.326	.734	.241
10.	Egyes újonnan megjelenő betegségeket (pl Covid-19-et is), stratégiailag hoztak létre és terjesztettek azért, hogy védőoltásokat dolgozhassanak ki. (Certain emerging diseases, like Covid-19 were strategically created and spread by the government in order to have the opportunity to develop vaccines.)	.271	.652	.146
11.	Óvatosan kell kezelnünk a Covid-19 védőoltással kapcsolatos ajánlásokat. (We have to be cautious about the recommendations that are given to the general public regarding the Covid-19 vaccine uptake.)	.357	.647	.167
12.	Kiráz a hideg (libabőrös leszek), amikor arra gondolok, hogy beoltanak valamelyik Covid-19 elleni védőoltással. (I have chills (goosebumps) when I think about being vaccinated with one of the Covid-19 vaccines.)	.197	.191	.869
13.	Felfordul a gyomrom (hányingerem, gyomoridegem van), amikor arra gondolok, hogy beoltanak valamelyik Covid-19 elleni védőoltással. (I have an upset stomach (nausea, butterflies) when I think about being vaccinated with one of the Covid-19 vaccines.)	.204	.204	.845
14.	A szívem gyorsabban ver (pulzusom megnő) amikor arra gondolok, hogy beoltanak valamelyik Covid-19 védőoltással. (My heart beats rapidly (change in heart rate) when I think about being vaccinated with one of the Covid-19 vaccines.)	.147	.251	.818
15.	Alvászavarom van, mert aggódom, hogy beoltanak az egyik Covid-19 elleni védőoltással (I have sleeping difficulties because I’m worrying about being vaccinated with one of the Covid-19 vaccines.)	.036	.155	.816
Eigenvalues		7.994	2.081	1.067
% of variance		53.3	13.9	7.1
Cumulative %		53.3	67.2	74.3
α subscales		.944	.895	.891
α total scale		.937

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Rotation converged in 5 iterations. 1,2,3,4,5 is reversed items (R).

Figure 1. Factor structure of the Multidimensional COVID-19 Vaccine Hesitancy Scale (CoVaH) .

Table 3. Model fit indices of Multidimensional COVID-19 Vaccine Hesitancy Scale

	χ2	df	p	χ^2/df	GFI	AGFI	NFI	IFI	TLI	CFI	RMSEA
3 factor structure/ 15 items	404.863	87	.000	4.654	.964	.950	.978	.983	.979	.983	.049

χ² = Chi-square statistic; GFI = Goodness of fit index; AGFI = Adjusted goodness of fit index; NFI = Normed fit index; IFI = Bollen’s incremental fit index; TLI = Tucker–Lewis index; CFI = Comparative fit index; RMSEA = Root mean square of error approximation; N = 1503.

Table 4. Group differences for criterion (concurrent) and validity

		Vaccine hesitancy	Skepticism	Risk	Fear
Vaccine intention	Do not consider	53.29 (10.12)	22.34 (3.21)	22.54 (5.48)	8.40 (5.09)
	Undecided	39.97 (9.56)	15.92 (4.50)	17.98 (5.27)	6.09 (3.42)
	Vaccinated	26.04 (8.67)	9.36 (4.39)	12.08 (4.85)	4.59 (1.93)
	df1, df2	3,691.90	3,664.26	3,691.17	3,647.86
	F/FWelch	691.76	1037.35	351.17	79.32
	p	≤.001	≤.001	≤.001	≤.001
	Cohen’s f	3.99	2.91	2.07	0.92
Flu vaccine past	No	39.32 (15.20)	15.72 (6.89)	17.22 (6.94)	6.37 (4.08)
	Yes	29.93 (12.13)	11.15 (5.64)	13.68 (5.80)	5.09 (2.83)
	df	651.37	635.55	622.42	755.87
	t/tWelch	11.71	12.37	9.34	6.49
	p	≤.001	≤.001	≤.001	≤.001
	Hedges’s g	0.64	0.69	0.53	0.33
Optional vaccine past	No	46.03 (14.30)	18.78 (6.16)	19.87 (6.51)	7.38 (4.86)
	Yes	33.43 (13.77)	12.95 (6.44)	14.95 (6.47)	5.52 (3.20)
	df	1501	1501	1501	633.04
	t/tWelch	16.12	16.33	13.51	7.46
	p	≤.001	≤.001	≤.001	≤.001
	Hedges’s g	0.90	0.92	0.76	0.49
Gender	Male	35.13 (14.23)	14.72 (7.00)	15.38 (7.08)	5.02 (2.60)
	Female	37.57 (15.19)	14.72 (6.89)	16.60 (6.82)	6.25 (4.01)
	df	1501	1501	1501	351.59
	t/tWelch	2.11	0.01	2.31	5.683*
	p	<.05	.992	<.05	≤.001
	Hedges’s g	0.16	0.00	0.18	0.32
Country	Romania	35.55 (13.69)	14.02 (6.46)	15.79 (6.37)	5.73 (3.33)
	Hungary	38.19 (15.81)	15.02 (7.10)	16.85 (7.09)	6.31 (4.19)
	df	1398.93	1374.58	1381.07	1426.05
	t/tWelch	3.37*	2.78*	2.96*	2.88*
	p	≤.001	≤.01	≤.01	≤.01
	Hedges’s g	0.18	0.15	0.16	0.15
Cronic disease	No	37.81 (14.93)	15.12 (6.84)	16.58 (6.79)	6.12 (3.88)
	Yes	35.09 (15.51)	16.18 (6.91)	15.92 (7.16)	6.00 (3.87)
	df	1501	1501	465.89	1501
	t/tWelch	2.83	4.43	1.469	0.482
	p	≤.001	≤.001	.142	.630
	Hedges’s g	0.18	0.28	−0.01	−0.031
Diagnosed Covid-19	No	37.06 (15.46)	14.62 (7.04)	16.32 (6.96)	6.11 (3.95)
	Yes	36.24 (14.21)	14.33 (6.64)	16.32 (6.83)	5.58 (3.33)
	df	450.123	440.936	1344	484.55
	t/tWelch	0.833	0.631	0.001	2.25*
	p	.405	.529	1.000	<.05
	Hedges’s g	−0.05	−0.04	0.00	0.14

*Welch statistic.

Data availability statement

The data that support the findings of this study are openly available in “figshare” at https://doi.org/10.6084/m9.figshare.15090891.v1.