Item Response Theory Analysis of the Fear of COVID-19 Scale (FCV-19S): A Systematic Review

Figures & data

Figure 1 PRISMA flowchart.

Notes: Adapted from Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Annals of Internal Medicine. 2009;151(4):264–269.³¹ Creative Commons.

Table 1 Summary Characteristics of Included Studies

First Author	Year	Country	N	Age Group (Years)	Age (Mean)	Female (%)	Language	Type of Participant	IRT Method; Link Function Type	Assumptions Tested	Software
Al-Shannaq^Citation36	2021	Jordan	725	18–65	33.7	56.4	Jordanian	Adults	Graded Response Model; not report	No	IRTPRO™
de Medeiros^Citation37	2021	Brazil	230	18–71	35.33	76.1	Portuguese	General population	Graded Response Model; not report	No	Package mirt in R
Basit^Citation64	2021	Pakistan	380	NR	51.93	46.05	NR	Adult type 2 diabetes patients	Graded Response Model; not report	No	Test Analysis Modules package for R
Bellamkonda^Citation40	2021	India	572	NR	22.70	58.7	English	College students	Graded Response Model; not report	No	R software
Elemo^Citation42	2020	Ethiopia Amharic	307	NR	NR	81.1	Amharic	General population	Graded Response Model; not report	No	JASP 0.11.1
Caycho-Rodr ıguez^Citation43	2020	Argentina	1291	18–80	38.47	79.0	Spanish	General population	Graded Response Model; logit	No	“ltm” package R
Satici^Citation44	2020	Turkey	1304	18–64	29.47	70.3	Turkish	General population	Graded Response Model; not report	No	JASP 0.11.1
Han^Citation45	2021	Korea	300	19–65	NR	67.3	Korean	Adults	Rasch analysis; logit	No	jMETRIK 4.1.1
Giordani^Citation38	2021	Mozambique	387	18–70	34.5	51.7	Portuguese	General population	Rasch partial credit model; logit	No	R software
Chen^Citation46	2021	China	2445	NR	18.55	50.2	Chinese	General student population	Rasch analysis; logit	Yes	WINPEPS 3.74.0
Lin^Citation39	2021	Bangladesh, United Kingdom, Brazil, Taiwan, Italy, New Zealand, Iran, Cuba, Pakistan, Japan and France	15,663	10–92	29.64	53.4	Multi- language comparison	General student population	Rasch analysis; logit	No	WINPEPS 3.74.0
Winter^Citation41	2020	New Zealand	1397	18–88	47.5	40	English	General student population	Rasch analysis; logit	Yes	WINPEPS 3.74.0
Winter^Citation41	2020	New Zealand	1023	18–85	42	69.7	English	General student population	Rasch analysis; logit	Yes	WINPEPS 3.74.0
Pang^Citation47	2020	Malaysia	228	NR	26	71.1	Malay	General student population	Rasch analysis; logit	No	jMetrik 4.1.1
Sakib^Citation48,Citation49	2020	Bangladesh	8550	NR	26.5	44	Bangla	General student population	Rasch partial credit model; logit	Yes	WINSTEPS 4.3.0.
Ahorsu^Citation12	2020	Iran	717	<18	31.25	42	Persian	General student population	Rasch analysis; logit	No	WINSTEPS 3.75.0
Stănculescu^Citation50	2021	Romania	809	18 to 68	32.61	65.4	Romanian	General population	Graded Response Model; not report	No	ADANCO 2.2

Figure 2 Results of methodological quality assessment regarding Box A. Internal consistency.

Figure 3 Results of methodological quality assessment regarding Box E – structural validity.

Figure 4 Results of methodological quality assessment regarding Box G. Cross-cultural validity.

Figure 5 Results of methodological quality assessment regarding Box H. Criterion validity.

Figure 6 Results of methodological quality assessment regarding Box IRT.

Table 2 Summary Results of Rasch Analysis Properties

First Author	Year	FCV1			FCV2			FCV3			FCV4			FCV5			FCV6			FCV7
		Infit MnSq	Outfit MnSq	Difficulty	Infit MnSq	Outfit MnSq	Difficulty	Infit MnSq	Outfit MnSq	Difficulty	Infit MnSq	Outfit MnSq	Difficulty	Infit MnSq	Outfit MnSq	Difficulty	Infit MnSq	Outfit MnSq	Difficulty	Infit MnSq	Outfit MnSq	Difficulty
Han^Citation45	2021	1.08	1.14	−1.05	1.07	1.03	−1.50	0.76	0.68	0.63	0.88	0.89	0.37	0.91	0.90	−0.70	0.97	0.81	1.94	1.32	1.49	0.32
Giordani^Citation38	2021	0.85	0.90	‒0.417	0.91	0.87	‒0.003	0.91	0.85	1.718	0.90	0.87	‒0.031	0.78	0.84	0.84	0.85	0.83	1.903	0.83	0.82	1.166
Chen^Citation46	2021	1.25	1.23		0.87	0.89		0.73	0.69		1.31	1.24		1.12	1.07		0.87	0.88		0.82	0.81
Lin^Citation39	2021	1.07	1.13	−0.91	1.01	1.03	−0.74	0.91	0.9	1.01	1.13	1.1	−0.10	0.94	0.94	−0.63	0.88	0.86	0.98	1.02	1.01	0.39
Winter - Sample 1^Citation41	2020	1.11	1.17	− 1.04	0.94	0.98	− 0.86	0.87	0.72	0.96	1.36	1.25	− 0.06	1.13	1.12	− 0.64	1.07	0.92	0.78	1	0.8	0.87
Winter - Sample 2^Citation41	2020	1.11	1.12	− 1.11	0.93	0.91	− 0.95	0.84	0.69	1.11	1.3	1.29	0.1	1.16	1.19	− 0.81	0.97	0.87	0.82	1.06	0.89	0.85
Pang^Citation47	2020	0.87	0.89	−0.62	0.84	0.81	−0.44	1.38	1.3	0.99	0.83	0.76	−0.68	0.9	0.85	−0.16	1.1	1.05	0.55	1.07	1.02	0.36
Sakib^Citation48,Citation49	2020	0.99	0.99	− 1.04	1.12	1.16	− 0.84	0.82	0.84	1	0.94	0.95	0.25	0.93	0.87	− 0.86	0.91	0.93	1.16	1.2	1.26	0.33
Ahorsu^Citation12	2020	1.26	1.25	0.98	0.8	0.84	− 0.17	0.81	0.85	0.39	1.11	1	−0.77	1.01	1	0.85	0.9	0.94	− 0.43	0.81	0.91	− 0.83
Minimum		0.85	0.89	−1.05	0.8	0.81	−1.5	0.73	0.68	0.39	0.83	0.76	0.1	0.78	0.84	−0.7	0.85	0.81	0.55	0.81	0.8	0.32
Maximum		1.26	1.25	0.98	1.12	1.16	−0.003	1.38	1.3	1.718	1.36	1.29	0.37	1.16	1.19	0.85	1.1	1.05	1.94	1.32	1.49	1.166

Table 3 Summary of Items DIF Based on Age and Gender

First Author	Year	DIF Age							DIF Gender
		FCV 1	FCV 2	FCV 3	FCV 4	FCV 5	FCV 6	FCV 7	FCV 1	FCV 2	FCV 3	FCV 4	FCV 5	FCV 6	FCV 7
Giordani^Citation38	2021	‒0.38	‒0.01	0.14	0.31	0.24	0.14	0.31	‒0.01	0.06	‒0.05	‒0.08	‒0.04	‒0.20	‒0.03
Chen^Citation46	2021	0.1	0	0.15	0	−0.39	0.08	0	0.2	−0.23	−0.11	0.33	0.13	−0.21	−0.09
Lin^Citation39	2021	−0.67	−0.18	0.35	−1.05	0.28	0.66	0.76	0	0	−0.24	0.11	0.16	−0.06	−0.02
		0.30	−0.49	0.11	−0.40	0.00	0.73	0.50
		0.37	−0.32	−0.24	0.65	−0.28	0.08	−0.26
Winter - Sample 1^Citation41	2020	0.32	0.1	− 0.11	0.43	− 0.49	− 0.19	−0.36	− 0.06	0.06	− 0.12	− 0.25	0.18	− 0.02	0.22
Winter - Sample 2^Citation41	2020	0.32	0	− 0.08	0.42	− 0.43	− 0.08	− 0.24	−0.04	0.05	0	− 0.19	0.1	0	0.04
Pang^Citation47	2020								−0.07	−0.20	−0.11	−0.19	0.13	−0.22	−0.14
Sakib^Citation48,Citation49	2020	− 0.12	0	0	0.16	0.1	− 0.28	0.15	0.1	0.17	− 0.08	− 0.06	− 0.08	− 0.06	0.05
Ahorsu^Citation12	2020	− 0.05	− 0.22	0.25	0.21	0.3	− 0.31	− 0.23	− 0.10	− 0.33	− 0.29	0.29	0.48	− 0.24	0.21
Absolute Minimum		0.05	0	0	0	0	0.08	0	0	0	0	0.06	0.04	0	0.02
Absolute Maximum		0.67	0.49	0.35	1.05	0.49	0.73	0.76	0.2	0.33	0.29	0.33	0.48	0.24	0.22

Notes: Giordani: DIF contrast across gender=difficulty for males - difficulty for females; DIF contrast across age=difficulty for older (> 34.5 years) - difficulty for younger (≤ 34.5 years). Chen: DIF contrast across gender, Differential Item Functioning for females and males; DIF contrast across age groups, Differential Item Functioning for younger (ie, 18 years) and older (ie, >18 years) students. Lin: DIF gender (M versus F); Age: C=children aged below 18 years; A=adults aged between 18 and 60 years; E=elderly aged over 60 years. Rows respectively are related to C versus A, C versus E, A versus E. Winter: DIF contrast across gender: difficulty for males-difficulty for females; eDIF contrast across age: difficulty for participants with younger age -difficulty for participants with older ages. Pang: DIF contrast across gender=difficulty for males (reference group) – difficulty for females (focal group). Sakib: DIF contrast across gender=Difficulty for females − Difficulty for males; DIF contrast across age categories =Difficulty for participants with older age (ie, ≥ 26.53 years) – Difficulty for participants with younger age (ie, < 26.53 years). Ahorsu: DIF contrast across gender=difficulty for males-difficulty for females eDIF contrast across age groups=Difficulty for younger (ie, ≤ 31.25 years) - Difficulty for older (ie, > 31.25 years) patients.

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