The Japanese version of the Fear of COVID-19 scale: Reliability, validity, and relation to coping behavior.

COVID-19 is spreading worldwide, causing various social problems. The aim of the present study was to verify the reliability and validity of the Japanese version of the Fear of COVID-19 Scale (FCV-19S) and to ascertain FCV-19S effects on assessment of Japanese people's coping behavior. After back-translation of the scale, 450 Japanese participants were recruited from a crowdsourcing platform. These participants responded to the Japanese FCV-19S, the Japanese versions of the Hospital Anxiety and Depression scale (HADS) and the Japanese versions of the Perceived Vulnerability to Disease (PVD), which assesses coping behaviors such as stockpiling and health monitoring, reasons for coping behaviors, and socio-demographic variables. Results indicated the factor structure of the Japanese FCV-19S as including seven items and one factor that were equivalent to those of the original FCV-19S. The scale showed adequate internal reliability (α = .87; ω = .92) and concurrent validity, as indicated by significantly positive correlations with the Hospital Anxiety and Depression Scale (HADS; anxiety, r = .56; depression, r = .29) and Perceived Vulnerability to Disease (PVD; perceived infectability, r = .32; germ aversion, r = .29). Additionally, the FCV-19S not only directly increased all coping behaviors (β = .21 - .36); it also indirectly increased stockpiling through conformity reason (indirect effect, β = .04; total effect, β = .31). These results suggest that the Japanese FCV-19S psychometric scale has equal reliability and validity to those of the original FCV-19S. These findings will contribute further to the investigation of various difficulties arising from fear about COVID-19 in Japan.

Introduction

As of September 2020, infectious disease caused by the novel coronavirus (coronavirus disease 2019, or COVID-19) continues to spread on a global scale. This most recently discovered coronavirus emerged in the city of Wuhan in Hubei Province of China in December 2019 [1]. As of September 9, 2020, approximately 27 million people (confirmed cases) have been infected worldwide; the number of deaths has risen to approximately 900,000 [2].

The first case of infection in Japan was confirmed on January 16, 2020: a Chinese man residing in Kanagawa Prefecture who had lived for some time in Wuhan. Subsequently, the spread of infection among local residents who had never visited Wuhan and cluster infections occurred in Japan, which led to a rapid rise in the number of infected people, particularly in Tokyo and Osaka. On April 16, 2020, the Japanese government declared a national state of emergency [3]. By September 9, 2020, the number of infected persons nationwide had risen to 72,726, leading to 1,393 deaths. Such a widespread social effect created confusion among the general public [4]. More specifically, reactions such as bulk purchases (stockpiling) of face masks and sanitizers soared, creating secondary disruptions [5].

Because fear of the COVID-19 epidemic can adversely affect disease management [6], fear of COVID-19 should be assessed appropriately. Some researchers have already conducted studies of people’s fear of infection with COVID-19 that is currently spreading worldwide [7-9]. The Fear of COVID-19 Scale (FCV-19S) was developed with the aim of quelling fear of COVID-19 and for other goals [10, 11]. The FCV-19S is positively associated with anxiety and depression, and with perceptions of vulnerability to infection.

The FCV-19S, based on the Protection Motivation Theory [12], has a unidimensional factor structure [10, 13]. The FCV-19S has been confirmed to have reliability and validity in various countries such as Bangladesh [14], Iran [10], Israel [15], Italy [16], New Zealand [17], Russia and Belarus [18], Saudi Arabia [19], Turkey [20], and Vietnam [21]. It has come to have more widespread use than other corona-related measures [13].

Results obtained using FCV-19S have been found to be associated with various factors including socio-demographic and residential environments. Being female, older, smoking, using health care services for COVID-19-related stress, and worries related to lockdown are factors associated with higher FCV-19S [14, 18, 21–23].

In addition, fear and anxiety can affect social behavior. Among the psychological responses and coping behaviors of people following the 2009 influenza A (H1N1) outbreak, those with less resistance to uncertainty were more likely to use coping behaviors aimed at releasing their emotions [24]. In the current context, fear of COVID-19 is not only positively associated with prevention behaviors [25, 26] and health-related behaviors such as increasing alcohol and tobacco use [21]; it is also associated with bulk buying behaviors [27].

However, these studies have not examined reasons underlying those behaviors. In Japan, where peer pressure is high, some people wear masks not only because it is necessary as a preventive behavior, but also because they are worried about how others will think of them if they do not wear a mask [28]. Therefore, reasons of two types are assumed for actions: self-determining reasons, by which a person decides to act independently out of a sense of need, and conformity reasons, by which a person attunes self-behavior to the actions of surrounding people out of fear or anxiety. This study therefore examines a model of the relation between fear of COVID-19 and coping behavior with reasons of two types mediating fear and coping behavior.

The purposes of this study were twofold. First, this study translates FCV-19S, established by Ahorsu et al. [10], into Japanese and assesses its reliability and validity in Japan based on a procedure equivalent to that used by Ahorsu et al. [10]. Secondly, this study develops a model of COVID-19 fear effects on coping behaviors, including reasons for the behaviors.

Materials and methods

Procedure

Data were collected in Japan. The participants were 450 residents of Japan (291 men and 159 women) aged 18 and older with average age of 48.13 years (SD = 14.04). They were recruited through an online service provided by Yahoo (https://crowdsourcing.yahoo.co.jp/), a major crowdsourcing service in Japan managed by Yahoo Japan Corp. The online service coordinates requests from clients with crowdsourcing workers. The current research was posted by the authors as a psychology research project in the "questionnaire" category on the Yahoo information board. The number of participants in the survey was set to be terminated when 450 participants had been recruited. The number of participants was determined based on the number of participants in another FCV-19S study [10] to exceed the minimum sample size required by CFA and SEM [29, 30]. The participants read the study descriptions and agreed to take part in it by opting into the study themselves. Participants who completed the survey were assigned 105 points (about one dollar) to be used at a specific store. The survey questionnaire was administered on April 18 and 19, 2020.

Survey description

Socio-demographic variable: The survey questionnaire asked for free answers from each respondent for sex, age, nationality, and residential area (city and prefecture). This item was followed by a multiple-choice question asking about the participants’ health condition at the time, which allowed for many responses such as 1 = “in normal condition,” 2 = “having a fever of 37.5°C or higher,” 3 = “having a sore throat,” 4 = “having deep fatigue,” 5 = “having a cough,” and 6 = “having other symptoms” [31]. The subsequent analysis combined answers that included at least one from choices 3 through 6 into one group, with three other groups including 1 = “in normal condition,” 2 = “having a fever of 37.5°C or higher,” and 3 = “having other symptoms.” The next question categorized the diseases being treated at the time into respiratory diseases, mental disorders (anxiety disorder, depression, and other mental disorders), and other diseases and asked the participants to indicate whether they had a disease, and if they did, to give the specific name(s) of the disease(s). The analysis combined the types of diseases into one group and divided the answers based on whether or not the participants had a disease being treated at the time. Subsequent questions asked all participants whether they smoked and asked female participants whether they were pregnant. All participants in this survey were Japanese citizens. For this study, the variables of sex, age, health condition at the time, diseases being treated, and smoking habits, which were expected to be associated with FCV in earlier studies [15, 18, 20–22], were used for the analysis.

Working status: The questionnaire asked whether the participants worked at a job at the time. If they did, the questionnaire asked them to describe their job. Participants were also asked whether they were able to work from home, how they commuted, and at what hierarchical level in the company their job was positioned. After combining responses indicating whether the participants worked at a job and whether they were able to work from home, three categories were created for analyses, including a group being able to work from home, one unable to work from home, and a group of participants not working at a job.

Family composition: Participants were asked about the number of family members living with them, their relation to the participant, their age, whether they had respiratory or other diseases, their smoking history, and their pregnancy status (only female family members residing with the participant). In addition, participants were asked about changes in the amount of conversations and conflict of opinions in the family living together in the last month. Only people living with family members who were expected to be associated with FCV in earlier studies [32, 33] were included in the analysis.

Sources of information about COVID-19: Participants were asked a multiple-choice question about media that they regarded as a valuable source of information about COVID-19. They were also asked to rank such information sources from first to the third based on their importance. Specific sources of information indicated in the answers were the following: 1 = newspaper; 2, news on TV; 3, talk shows on television; 4, websites of public organizations; 5, news on the internet; 6, Twitter; 7, Facebook; 8, Instagram; 9, other social networking services (“SNS”); and 10, other media. The analysis used only the most prioritized information sources and combined choices 6–9 into a single group called “SNS.”

Presence of persons infected with COVID-19 around the participant: Participants were asked whether anyone with whom they were acquainted had contracted COVID-19. Any respondent acquainted with an infected person was asked to describe their relation. To assess the status of COVID-19 infection for individuals around the participant, the survey asked about an infected person’s residence: 1, “in the same prefecture”; 2, “in the same municipality”; or 3, “in the same district” as the participant; or 4, no one was infected around the participant. The analysis combined responses for 1 through 3 into one group, designated as 1, “there is an infected person nearby” and the rest 2 “there is no infected person nearby.”

Measuring fear of COVID-19: The study used a Japanese translation of FCV-19S developed by Ahorsu et al. [8]. The following describes the procedure for translating the scale. First, permission to produce a Japanese translation of FCV-19S was obtained from Dr. Amir H. Pakpour, one author of the original article on FCV-19S. A translation agency performed the translation. The author of this report and the translation agency then modified Japanese expressions used for the items of the scale. A Korean psychologist fluent in Korean, English, and Japanese subsequently performed a reverse translation of the Japanese translation without seeing the original version. Finally, a native speaker of English compared this reverse translation and the original version of the scale and confirmed that they were fundamentally the same. The Japanese version was therefore finalized. The Japanese version of the scale that was completed consisted of seven items in the same manner as the original. These seven items were made a provisional Japanese version of the Fear of COVID-19 Scale (“FCV-19S-J”). FCV-19S-J asks questions to be answered on a scale of 1, “I am not afraid of COVID-19 at all” to 5, “I am most afraid of COVID-19.” A higher score reflects a greater fear of COVID-19 (S1 File).

Measuring anxiety and depression: The Japanese version of the Hospital Anxiety and Depression Scale (HADS) prepared by Hatta et al. [34] was used. Although the HADS [35] was designed originally for patients in nonpsychiatric hospital clinics, it has been found to be reliable and valid in general samples [34]. HADS was positively correlated with FCV-19S [10]. It comprises a total of 14 items, including seven that measure recent anxiety and another seven that measure recent depression. It seeks responses from four choices each. Higher scores denote severer anxiety or depression experienced recently. Both the measures of anxiety and depression are expected to show positive correlation with FCV-19S-J.

Measuring perception of vulnerability to infection: The study used the Japanese version of the perceived vulnerability to disease (PVD) scale developed by Fukukawa, Oda, Usami, and Kawahito [36]. The PVD scale [37], which has been demonstrated as positively correlated with FCV-19S [10], consists of 15 items comprising 7 items of susceptibility to infection and 8 items of germ aversion. The response to each item is selected from seven choices from 1 = “strongly disagree” to 7 = “strongly agree.” A high score represents high susceptibility to infection or high germ aversion. Both the measures of susceptibility to infection and germ aversion are expected to represent positive correlation with FCV-19S-J.

Behavior to cope with COVID-19: Participants were asked about their actions taken to cope with COVID-19. Items for coping behaviors were produced based on a report issued by the Ministry of Health, Labour and Welfare: "What we are doing to prevent new corona infection" of the "1st National Survey for Countermeasures against COVID-19" [38]. In addition, based on reports on social issues [39], items related to social behavior were added. Each of 19 items (e.g., “avoided places with large crowds”) was rated on a six-point Likert scale ranging from 1 (not at all) to 6 (very much) (S2 File).

Reason for behavior: We asked about reasons for the behaviors above to cope with COVID-19. We developed three items as proactive reasons (e.g., “I did it because I felt it was necessary for myself”) and four items as passive reasons (e.g., “I did it because other people told me to”). Each of 7 items was rated on a six-point scale ranging from 1 (not applicable at all) to 6 (highly applicable) (S2 File).

Ethical consideration

After the first section of the survey presented a statement of the survey purpose, the form stated that participation was voluntary and that the survey was anonymous: personal information would not be disclosed to third parties. Only those who agreed to cooperate in the survey would be able to proceed to the questionnaire. Additionally, the Tohoku University Graduate School of Education’s ethics committee granted ethical approval for this study (ID: 20-1-003).

Data analysis

Statistical operations were conducted using software (Mplus 8.1 [40]) and a computer program (R 3.6.3 [41]). Analyses examined the reliability and validity of the Japanese version of the FCV-19S and the effect of fear of COVID-19 on coping behavior.

To investigate the reliability and validity of the Japanese version of FCV-19S, confirmatory factor analysis, correlation analysis, and calculation of reliability coefficients were conducted. We also conducted t-tests and analysis of variance with the socio-demographic variable as the independent variable and FCV-19S as the dependent variable.

For confirmatory factor analysis (CFA), a robust maximum likelihood estimator (MLR) was applied in this study. To test goodness of fit, we conducted the following analyses: comparative fit index (CFI), root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), and Bayesian information criterion (BIC). The cut-off values for acceptable model fit used for this study were: RMSEA < .10 for acceptable fit and < .06 for good fit; CFI > .90 for acceptable fit and > .95 for good fit; and SRMR < .10 for acceptable fit and < .08 for good fit [29, 42]. Error correlation was assumed to be related to the modified index (MI) if the goodness of fit showed an inadequate value. An MI indicates the expected parameter change if a particular specification were included in the model. Reliability was calculated for Cronbach’s alpha coefficients (α) and McDonald’s omega coefficients (ω). Correlations between the FCV-19S-J and other measures were established by calculating Pearson’s correlation coefficients. A t-test was performed when examining the difference in means between the two groups. Analysis of variance was conducted when examining the difference in means among the three or more groups. Reported effect sizes are interpreted using Cohen’s d and η2, respectively including 95% confidence intervals.

To elucidate the effect of FCV-19S on coping behavior, an exploratory factor analysis of coping behavior and reasons for behavior was conducted. A structural equation model was tested.

In exploratory factor analyses (EFA), MLR and goemin rotation was applied for coping behavior and reason for behavior. We removed items with factor loadings lower than .35. In the structural equation model (SEM), a robust maximum likelihood estimator (MLR) was applied in this study. The same indices were used for testing goodness of fit as for confirmatory factor analysis. We assumed a direct path from FCV-19S to coping behavior and a path from FCV-19S to coping behavior by mediating the reason for behavior. Therefore, we examine not only the direct but also indirect effects of FCV-19S on coping behavior.

All statistical analyses used two-tailed tests. For all statistical evaluations, p values less than .05 were inferred as significant. Missing values were visible only for age. Therefore, pairwise deletion was used for missing data.

Results

Factor structure, reliability and validity of FCV-19S-J

Table 1 presents participants’ basic characteristics. The present study participants were 450 participants, mostly men (65%).

Table 1

Participants’ basic characteristics.

Variable	N = 450	%	FCV-19		t /F
			Mean (SD)
Sex
Men	291	(65%)	21.01	5.28	t(311.46) = 1.24 n.s.
Women	159	(35%)	21.68	5.55
Age (N = 448)
≤20s	35	(7.7%)	20.77	(5.73)	F(5, 442) = 0.46 n.s.
30s	116	(25.8%)	21.09	(5.86)
40s	104	(23.1%)	21.20	(5.57)
50s	49	(10.9%)	20.73	(5.43)
60s	117	(26.0%)	21.84	(4.59)
≥70s	27	(6.0%)	20.93	(5.40)
Health condition
In normal condition	415	(92.2%)	21.23	5.29	F(2, 447) = 0.52 n.s.
Having a fever of 37.5°C or higher	30	(6.7%)	21.80	6.29
Having other symptom	5	(1.1%)	19.20	7.89
Smoking habit
Smoker	165	(36.7%)	21.76	5.2	t(356.59) = 1.57 n.s.
Non-smoker	285	(63.3%)	20.95	5.47
Diseases being treated
Disease undergoing treatment	111	(24.7%)	21.68	6.08	t(164.31) = 0.88 n.s.
No disease undergoing treatment	339	(75.3%)	21.11	5.13
Work status
Able to work from home	109	(24.2%)	21.45	5.43	F(2, 447) = 0.47 n.s.
Unable to work from home	206	(45.8%)	21.39	5.33
Not working	135	(30.0%)	20.87	5.43
Living with family
Living with family	356	(79.1%)	21.44	5.33	t(141.66) = 1.40 n.s.
Not living with family	94	(20.9%)	20.54	5.54
Most important source of information
Newspaper	38	(8.4%)	19.47	5.00	F(6, 443) = 3.47**
News on TV	200	(44.4%)	22.08	5.01
Talk shows on television	20	(4.4%)	22.70	6.20
Websites of public organizations	50	(11.1%)	19.96	4.20
News on the internet	115	(25.6%)	21.17	5.86
SNS	15	(3.3%)	21.00	6.15
Other (e.g. radio, Youtube, No important source of information)	12	(2.7%)	17.17	6.49
Presence of persons infected
Someone I know has the corona virus.	8	(1.8%)	21.75	10.38	t(7.07) = 0.14 n.s.
No one I know has the corona virus.	442	(98.2%)	21.24	5.27

Notes: ** p< .01; sex, smoking habit, diseases being treated, living with family and presence of persons infected were subjected to t-tests. Analysis of variance was applied for age, health condition, work status, and sources of information.

Confirmatory factor analyses, as described by Ahorsu et al. [10], were used to examine the goodness of fit. Results show that the Japanese FCV-19S did not fit well (Table 2, Model 1). To improve the model fit, MI were used. The MI between items 1 and 4 (MI = 47.72) and between items 2 and 5 (MI = 35.30) were higher values. Therefore, a within factor error-covariance between items 1 and 4 (Model 2) and between items 2 and 5 (Model 3) was included. The model was modified. The model that includes error correlations of items 1 and 4 / items 2 and 5 is Model 4. Results indicate that the modified model (Model 4) was more acceptable (CFI = .943, RMSEA = .105, SRMR = .052) than Model 2 or 3. This was the final model.

Table 2

Factor loadings for the FCV-19S-J.

Items		Standardized loadings
		Model 1	Model 2	Model 3	Model 4
FCV-19S-J (α = .87 / ω = .92)
1	I am most afraid of coronavirus-19.	.590	.556	.562	.526
2	It makes me uncomfortable to think about coronavirus-19.	.744	.728	.688	.670
3	My hands become clammy when I think about coronavirus-19.	.737	.747	.759	.764
4	I am afraid of losing my life because of coronavirus-19.	.510	.471	.489	.449
5	When watching news and stories about coronavirus-19 on social media, I become nervous or anxious.	.743	.734	.691	.680
6	I cannot sleep because I’m worrying about getting coronavirus-19.	.740	.754	.770	.780
7	My heart races or palpitates when I think about getting coronavirus-19.	.819	.835	.843	.857
	Χ2	159.994***	113.398***	126.178***	71.068***
	df	14	13	13	12
	CFI	0.859	0.903	0.891	0.943
	RMSEA	0.152	0.131	0.139	0.105
	90 Percent C.I.	0.132–0.174	0.109–0.154	0.118–0.162	0.082–0.129
	SRMR	0.065	0.051	0.065	0.052
	BIC	7921.633	7864.521	7882.834	7817.045

Notes: ***p < .001; CFI, comparative fit index; RMSEA, root mean square error of approximation; SRMR, standardized root mean square residual; and BIC, Bayesian information criterion; α, Cronbach’s alpha; ω, McDonald’s omega.

The descriptive statistics of the Japanese FCV-19S and other scales are presented in Table 3. Internal consistency reliability was acceptable for FCV-19S scores (α = .87/ ω = .92). Correlations between the Japanese FCV-19S and the HADS and PVD were significant, ranging from r = .29 to r = .56, p < .01.

Table 3

Correlations between the Japanese FCV-19S-J and other scales.

		Mean (SD)	Min–max	Skewness	Kurtosis	FCV-19S-J
FCV-19S-J		21.25 (5.38)	7–35	.01	.06	-
HADS
anxiety (α = .87/ ω = .90)		6.83 (4.47)	0–21	.77	.35	.56***
Depression (α = .68/ ω = .76)		8.81 (3.84)	0–20	.31	-.11	.29***
PVD
perceived infectability (α = .84/ ω = .91)		27.06 (7.31)	7–49	.05	.40	.32***
germ aversion (α = .79/ ω = .85)		39.16 (8.26)	14–56	.01	-.25	.29***
Coping behavior
careful in daily life (α = .81/ ω = .85)		39.56 (5.95)	13–48	-.96	.99	.28***
Stockpiling (α = .93/ ω = .93)		6.34 (2.88)	2–12	.09	-.78	.30***
health monitoring (α = .64/ ω = .67)		11.11 (3.37)	3–18	-.39	-.07	.39***
Reason for behavior
Self-determining reason (α = .50/ ω = .50)		8.68 (1.66)	2–12	-.45	1.27	.11
conformity reason (α = .77/ ω = .80)		11.77 (3.69)	4–24	-.11	-.29	.21***

Notes: ***p < .001; α, Cronbach’s alpha; ω, McDonald’s omega

Differences based on relevant variables

Means and standard deviations of all compared groups are presented in Table 1. No significant difference was found among the variables other than the important source of information. Groups of the important source of information differed significantly with regard to the FCV-19S-J, F(6, 443) = 3.469, p< .01, η2 = .044, 95% CI [.006; .076]. Post-hoc tests revealed that the News on TV group scored higher on the FCV-19S-J than the Other groups, p = .04, d = .97, 95% CI [.38; 1.56].

Effects of fear of COVID-19 on coping behavior

Factor analysis was conducted of coping behaviors and the reasons for these behaviors. Results show that 13 items were extracted from three factors for coping behavior (Table 4); six items from two factors were extracted for reasons for the behavior (Table 5). The descriptive statistics of these scales are presented in Table 3. Structural equation modeling (SEM) was used to investigate the effect of fear of COVID-19 on coping behavior (Fig 1). The model had acceptable fit to the data, X2(42) = 179.934, p< .05, CFI = .905, RMSEA = .085, (90% CI .073 –.098), SRMR = .057. The path from FCV-19S-J to each coping behavior and conformity reason had a small and moderate effect (β = .206 –.358, p< .001). The path from conformity reason to stockpiling and from self-determining reason to daily attention had a small and moderate effect (β = .113 –.119, p< .05).

Table 4

Factor loadings for the coping behavior.

Items		Factor loadings
		F1	F2	F3
F1 Careful in daily life
2	Avoided places with large crowds	.855	-.057	-.007
3	Avoided having a conversation or utterance in proximity to another person	.763	-.001	-.075
1	Avoided places with poor ventilation	.739	-.003	.058
4	Washed hands, gargled, or sanitized hands and fingers using alcohol	.603	.020	.118
16	Refrained from eating out	.439	.098	.080
5	Covered the mouth with a mask or handkerchief when coughing or sneezing	.424	.016	.273
18	Intentionally blocked the inflow of information	.380	.000	.157
11	Received a test to determine whether you are infected with COVID-19	-.340	.205	.048
F2 Stockpiling
8	Purchased food in larger quantities than usual	-.015	.956	.010
7	Purchased commodities in larger quantities than usual	.027	.903	-.023
F3 Health monitoring
10	Monitored heath condition more carefully than before	.262	-.012	.658
9	Observed changes in your health condition by measuring body temperature, etc.	-.002	.155	.657
13	Did something to take your mind off of COVID-19	.002	.106	.362
	F1	-
	F2	.336	-
	F3	.384	.263	-

Table 5

Factor loadings for the reason for behavior.

Items		Factor loadings
		F1	F2
F1 Self-determining reason
1	I did it because I felt it was necessary for myself.	.736	.005
3	I did it based on my own decision.	.451	-.259
F2 Conformity reason
5	I did it because other people told me to.	.004	.829
6	I did it out of a fear of criticism that would be raised by other people.	-.020	.785
4	I followed other people.	.057	.722
2	I did it even though I did not actually think it was necessary.	-.193	.390
	F1	-
	F2	.02	-

Fig 1

Effect of fear of COVID-19 on coping behavior model.

Notes: **p< .01; ***p< .001.

An indirect effect was examined to ascertain whether the conformity reason significantly mediated the relation between FCV-19S-J and stockpiling. Results show that FCV-19S-J had a significant indirect effect on stockpiling, through the effect of conformity reason (β = .035, p< .05) for a modest total effect (β = .311, p< .01).

Discussion

The first purpose of this study was development of the Japanese version of FCV-19S. As described by Ahorsu et al. [10], the results of factor analysis indicated a single factor structure. The α coefficient and omega coefficient in FCV-19S-J returned sufficient values. HADS indicated a significant correlation between “depression” and “anxiety”; PVD revealed significant correlation between “perceived infectability” and “germ aversion,” which suggests adequate reliability and validity. In FCV-19S-J, the goodness of fit was made an acceptable value by assuming an error correlation between item 1 (“I am most afraid of coronavirus-19.”) and item 4 (“I am afraid of losing my life because of coronavirus-19.”) and between item 2 (“It makes me uncomfortable to think about coronavirus-19.”) and item 5 (“When watching news and stories about coronavirus-19 on social media, I become nervous or anxious.”). For the error correlations, the Saudi Arabian version [19] was on items 1 and 2, items 3 and 6, items 3 and 7, and items 6 and 7, whereas the Turkish version [20] was on items 3 and 6, items 3 and 7, and items 6 and 7. We found no study with reported error correlations between items 1 and 4, items 2 and 5 as in the results of this study. FCV-19S has a unidimensional structure. However items 3, 6, and 7 are regarded as somatic responses to COVID-19 fear; items 1, 2, 4, and 5 are regarded as representing the general level of fear [19, 43]. Therefore, the error correlations in this study are error correlations between items that indicate a general level of fear. In Japan, a state of emergency declaration was expanded to include all of Japan on April 16 [3]. This event was a couple of days before the participants in this study participated in the study. This social context might have influenced the association between items of general fear rather than somatic responses.

Results of t-tests and analysis of variance suggested that participants who prioritized news on television as an information source tended to have greater anxiety related to COVID-19 than others who prioritized other information sources. The FCV-19S scores, however, were not found to be significantly different based on other factors such as the sex, age, living with family, and presence of persons infected. Earlier studies indicated that risk factors which increase the fear of COVID-19 include being female, older, smoking, using health care services for COVID-19-related stress, worries related to lockdown, and not living with a family member [14, 18, 21–23, 32]. Differences between the results of this study and earlier studies are likely to be attributable to social conditions. Because a state of emergency was declared in Japan, it is likely that everyone living in Japan is almost equally fearful, irrespective of the demographic characteristics of the study participants. Therefore, we believe that these study participants did not differ significantly in terms of their fear of COVID-19 depending on their attributes.

The second purpose of this study was development of a model of COVID-19 fear effects on coping behaviors, including reasons for the behaviors. Results revealed that fear of COVID-19 encouraged measures taken to prevent infection such as care in daily life and health conditions. This result is consistent with results indicating that FCV-19S predicted positive behavioral change (e.g. hand washing, changed travel) [26] and that it was positively associated with adherence to New Zealand's lockdown rules (e.g. maintaining the two-meter rule when out in public) [17]. Particularly, Harper [26] examined behavioral change. Therefore, various behaviors such as hand-washing and stockpiling were combined into a single variable. However, this study not only categorized coping behaviors as being careful in daily life, stockpiling, and health monitoring; it also asked about reasons for the behaviors. Results of this study demonstrated that fear of COVID is associated with preventive behavior, and also that it is related directly to nuisance behaviors such as stockpiling. Furthermore, we have demonstrated that fear of COVID is associated with stockpiling via conformity.

The fear of COVID-19 did not affect self-determination of reasons. However, self-determination of reasons contributed to an increase in care in daily life. At least in Japan, the self-determination of reasons and fear of COVID-19 might be useful for encouraging caution in daily life.

Limitations

This study has some limitations. Study participants were solicited using the internet. The study was able to collect people in wide-ranging age groups, but those who were willing to participate in the survey were likely to have been mentally stable, with sufficient psychological capacity to contemplate COVID-19 effects. The survey must be expanded to include participants such as medical professionals and people who have been adversely affected financially through events such as a loss of work because of COVID-19.

Moreover, the analysis used for this study used cross-sectional data, which were inadequate to verify causal relations between anxiety about COVID-19 and coping behavior. Particularly, the cross-sectional survey does not enable us to ascertain whether anxiety and fear arouses preventive behavior or whether it is aroused by performance of preventive behavior. Subsequent studies must identify relations between coping behavior and a fear of COVID-19 using a longitudinal study.

Conclusions

Despite the limitations described above, this study has explained the factor structure of FCV-19S-J. This report is the first in Japan to describe a study identifying the relations between fear of COVID-19 and coping behavior. The environment surrounding COVID-19 changes day by day. Appropriately measuring people’s anxiety and fear of COVID-19 likely to contribute to an understanding of increasing anxiety experienced by many people and to prevention of difficulties associated with COVID-19.

The Japanese version of FCV-19S.

(DOCX)

Click here for additional data file.

The coping behavior and reason for behavior.

(DOCX)

Click here for additional data file.

Anonymized data set.

(XLSX)

Click here for additional data file.

24 Aug 2020

PONE-D-20-15563

Variables related to fear of novel coronavirus infection (COVID-19) and coping behavior

PLOS ONE

Dear Dr. Wakashima,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Oct 08 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Ali Montazeri

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Since one of the key outcomes of your study was the development of a translated version of the FCV-19S, you may wish to include this in the title of your manuscript.

3. PLOS ONE has specific requirements for studies that are presenting a new method or tool as the primary focus, including a newly developed or modified questionnaire or scale (https://journals.plos.org/plosone/s/submission-guidelines#loc-methods-software-databases-and-tools.) One requirement is that the questionnaire or scale must be openly available under a license no more restrictive than CC BY. In light of this, before we proceed, please include a copy of your questionnaire or scale as a Supporting Information file (in the original language) or provide a link if it is available through an online repository.

4. Thank you for stating the following financial disclosure:

"The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

At this time, please address the following queries:

Please clarify the sources of funding (financial or material support) for your study. List the grants or organizations that supported your study, including funding received from your institution.

State what role the funders took in the study. If the funders had no role in your study, please state: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.”

If any authors received a salary from any of your funders, please state which authors and which funders.

If you did not receive any funding for this study, please state: “The authors received no specific funding for this work.”

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

5. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Please see the following video for instructions on linking an ORCID iD to your Editorial Manager account: https://www.youtube.com/watch?v=_xcclfuvtxQ

6. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: No

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: N/A

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: No

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This is an interesting and timely study. I have some concerns that will help to improve the manuscript.

1- I would add Japanese or japan in the title

2- Abstract: sampling procedure is missing. Real results and statistics are not reported the abstract. I cannot understand what you really mean on “were relatively comparable to those of the original FCV-19S”? how did you assess coping behavior? Please clearly report mediation results rather than writing a vague interpretation.

3- Introduction is good but needs to improving by adding some information of the latest statistics on covid-19 in japan. Please also add the following references:

Pakpour, A. H., Griffiths, M. D., Chang, K. C., Chen, Y. P., Kuo, Y. J., & Lin, C. Y. (2020). Assessing the fear of COVID-19 among different populations: A response to Ransing et al.(2020). Brain, Behavior, and Immunity.

Pakpour, A. H., & Griffiths, M. D. (2020). The fear of COVID-19 and its role in preventive behaviors. Journal of Concurrent Disorders.

Lin, C. Y. (2020). Social reaction toward the 2019 novel coronavirus (COVID-19). Social Health and Behavior, 3(1), 1.

4- I think that the authors need to compare their results with previous validation version. Please see the following:

Nguyen, H.T.; Do, B.N.; Pham, K.M.; Kim, G.B.; Dam, H.T.; Nguyen, T.T.; Nguyen, T.T.; Nguyen, Y.H.; Sørensen, K.; Pleasant, A.; Duong, T.V. Fear of COVID-19 Scale—Associations of Its Scores with Health Literacy and Health-Related Behaviors among Medical Students. Int. J. Environ. Res. Public Health 2020, 17, 4164.

Soraci, P., Ferrari, A., Abbiati, F. A., Del Fante, E., De Pace, R., Urso, A., & Griffiths, M. D. (2020). Validation and psychometric evaluation of the Italian version of the Fear of COVID-19 Scale. International Journal of Mental Health and Addiction, 1-10.

Haktanir, A., Seki, T., & Dilmaç, B. (2020). Adaptation and evaluation of Turkish version of the fear of COVID-19 scale. Death Studies, 1-9.

Harper, C. A., Satchell, L. P., Fido, D., & Latzman, R. D. (2020). Functional fear predicts public health compliance in the COVID-19 pandemic. International journal of mental health and addiction.

Reznik, A., Gritsenko, V., Konstantinov, V., Khamenka, N., & Isralowitz, R. (2020). COVID-19 fear in Eastern Europe: Validation of the Fear of COVID-19 Scale. International journal of mental health and addiction, 1.

Alyami, Mohsen, Marcus Henning, Christian U. Krägeloh, and Hussain Alyami. "Psychometric evaluation of the Arabic version of the Fear of COVID-19 Scale." International journal of mental health and addiction (2020): 1.

Bitan, D. T., Grossman-Giron, A., Bloch, Y., Mayer, Y., Shiffman, N., & Mendlovic, S. (2020). Fear of COVID-19 scale: Psychometric characteristics, reliability and validity in the Israeli population. Psychiatry Research, 113100.

Winter, Taylor, Benjamin Riordan, Amir Pakpour, Mark Griffiths, Andre Mason, John Poulgrain, and Scarf Damian. "Evaluation of the English version of the Fear of COVID-19 Scale and its relationship with behavior change and political beliefs." (2020).

Sakib, N., Bhuiyan, A. I., Hossain, S., Al Mamun, F., Hosen, I., Abdullah, A. H., ... & Sikder, M. T. (2020). Psychometric validation of the Bangla Fear of COVID-19 Scale: Confirmatory factor analysis and Rasch analysis. International Journal of Mental Health and Addiction.

Reviewer #2: The introduction is not convincing. It fails to show the current literature gap. The aim of the study is not clear. The study should clearly specify the mentioned issues; whether you are validating FCV-19S or developing a model of COVID-19 fear effects…?

Method: how did you invite the participants to the study? How many were approached? What were the main reasons for non-participation? The rational for study sample size should be stated. The rationale behind selecting the variables included in the questionnaire should be stated.

The statistical analysis should be clearly explained. The conceptual model that guided the authors for analysis should be explained in details.

Table 1. please indicate which test was used for analysis.

Table 2: writing error, heart races!

Why did you select model 4 as the final model? Did you change any item in the scale? What modification/s was/were made in to the scale?

Why did you use HAD for structural validity among a community population?

What do you mean by (α= .93/ ω= .93) in table 3? These should be explained.

The main concern is that, could we use the same sample for both validation study and SEM?

What are the differences between table 4 and 5?

The discussion is highly poor. In this part you should compare the results obtained from your study with similar studies either confirming or rejecting the current results. Then, express your explanations or justifications.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Amir Pakpour

Reviewer #2: Yes: Marzieh Aaraban

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

1 Oct 2020

Reviewer #1 :

Comment 1 : Title

I would add Japanese or japan in the title.

Response:

We agree with your opinion. We have changed the title from “Variables related to fear of novel coronavirus infection (COVID-19) and coping behavior” to “The Japanese version of the Fear of COVID-19 scale: Reliability, validity, and relation to coping behavior”.

Comment 2 : Abstract

Sampling procedure is missing. Real results and statistics are not reported the abstract. I cannot understand what you really mean on “were relatively comparable to those of the original FCV-19S”? how did you assess coping behavior? Please clearly report mediation results rather than writing a vague interpretation.

Response:

We agree with the reviewer’s point. We have made the following modifications.

(1) We have added “450 Japanese participants were recruited from a crowdsourcing platform” to the Abstract as the sampling procedure (p.2 lines 21-22).

(2) We have added real results and statistics to the Abstract (p.2 lines 28–33).

(3) We have changed the sentence from “were relatively comparable to those of the original FCV-19S” to “These results suggest that the Japanese FCV-19S is a psychometric scale with the same reliability and validity as the original FCV-19S.”

Comment 3 : Introduction

Introduction is good but needs to improving by adding some information of the latest statistics on covid-19 in japan. Please also add the following references:

Response:

To page 3 of the revised manuscript, we have included the latest statistics on COVID-19 from the entire world and from Japan. We have added references to lines 53–54 (Lin, 2020), lines 56–57 (Pakpour and Griffiths, 2020), and lines 62–63 (Pakpour et al., 2020).

Comment 4 :

I think that the authors need to compare their results with previous validation version.

Response:

Thank you for introducing us to the many references. We have cited nine references to support the validation lines 60–73. These are the following: Sakib et al. (2020), Bitan et al. (2020), Soraci et al. (2020), Winter et al. (2020), Reznik et al. (2020), Alyami et al. (2020), Haktanir et al. (2020), Nguyen et al. (2020), and Harper et al. (2020).

Reviewer #2 :

Comment 1 : Introduction

The introduction is not convincing. It fails to show the current literature gap. The aim of the study is not clear. The study should clearly specify the mentioned issues; whether you are validating FCV-19S or developing a model of COVID-19 fear effects…?

Response:

The reviewer has commented on the lack of persuasiveness of the Introduction and the lack of clarity of purpose. We agree with the reviewer’s points. We have particularly cited the references introduced by Reviewer 1 (lines 60–73) and have described the purpose as follows: The purpose of this study was twofold. First, this study translates FCV-19S established by Ahorsu et al. [10] into Japanese and assesses reliability and validity in Japan based on a procedure equivalent to that used by Ahorsu et al. [10]. Secondly, this study develops a model of the effects of COVID-19 fear on coping behaviors, including the reasons for the behavior (p. 5 lines 82–85).

Comment 2 : Method

How did you invite the participants to the study? How many were approached? What were the main reasons for non-participation? The rational for study sample size should be stated.

Response:

The reviewer has commented on the lack of clarity related to data collection in the Materials and Methods section. We have specifically added information related to how we recruit participants and the reasonableness of our sample size (Page 5, lines 89–101). Because we used crowdsourcing and decided to end the study when the number of participants reached 450, we cannot state the reasons for non-participants.

Comment 3 :

The rationale behind selecting the variables included in the questionnaire should be stated.

Response:

We agree with the reviewer’s point. We have stated the rationale for our choice of variables by citing earlier studies (Page 6, lines 118–120; Page 7, lines 132–134).

Comment 4 :

The statistical analysis should be clearly explained. The conceptual model that guided the authors for analysis should be explained in details.

Response:

Thank you for your comment. We realized that our original explanation was unclear and revised as follows:

(1) The Data analysis section described all the analyses used for this study (lines 201–230).

(2) Regarding the conceptual model, we discussed the need to measure the reasons for behavior in the Introduction section and the relation between FCV-19S, coping behavior, and reasons for behavior, as assumed in this study (lines 74–81). In addition, the conceptual model was explained in the Data analysis section (lines 222–230).

Comment 5 :

Table 1. please indicate which test was used for analysis.

Response:

We have provided a brief description of the analysis of the Table 1 footnote of revised manuscript. Note: ** p<0.01, sex, smoking habit, diseases being treated, living with family and presence of persons infected were subjected to t-tests, and analysis of variance was performed for age, health condition, work status, and sources of information.

Comment 6 :

Table 2: writing error, heart races!

Response:

Thank you for pointing out this error. An earlier manuscript did not present all sentences in Item 7. We have therefore added all sentences to item 7. The original FCV-19S (Ahorsu et al., 2020) also uses the word "heart races".

Comment 7 :

Why did you select model 4 as the final model? Did you change any item in the scale? What modification/s was/were made in to the scale?

Response:

The reviewer has commented on the lack of clarity related to the final model decision. We decided to use Model 4 as the final model because it was an acceptable fit over the other two improved models (Model 2 and Model 3) (lines 242–243). We have added a description of MI to the Data analysis section to show that we have assumed error correlation related to MI (lines 213–215). Some other studies of FCV-19S have also assumed error correlations (Alyami et al., 2020; Haktanir et al., 2020) (lines 335–337). We did not change the items in the scale.

Comment 8 :

Why did you use HAD for structural validity among a community population?

Response:

HAD has been used in the validation of FCV-19S and has been found to be reliable and valid in studies of community samples. We have added the following explanation to lines 166–168 of the revised manuscript. Although the HADS [35] was designed originally for patients in nonpsychiatric hospital clinics, it has been found to be reliable and valid in general samples [34]. HADS was positively correlated with FCV-19S [10].

Comment 9 :

What do you mean by (α= .93/ ω= .93) in table 3? These should be explained.

Response:

We have provided a brief description of � and � in the Table 2 and Table 3 footnotes. We have also given the use of � and � as indicators of reliability in Data analysis section (lines 215–216).

Comment 10 :

The main concern is that, could we use the same sample for both validation study and SEM?

Response:

The reviewer has asked about the propriety of using the same sample for validation and SEM.

Many other studies have applied factor analysis and other analyses (including SEM) to the same samples. Therefore we believe there is no particular problem with their application here.

Comment 11 :

What are the differences between table 4 and 5?

Response:

Table 4 presents results of exploratory factor analysis for “coping behavior.” Table 5 shows the results of exploratory factor analysis for “reason for behavior.” For “reason for behavior,” we changed the factor names to clarify it that it is a reason (Previous manuscript: self-determination and conformity behavior. Revised manuscript: self-determining reason and conformity reason).

Comment 12 :

The discussion is highly poor. In this part, you should compare the results obtained from your study with similar studies either confirming or rejecting the current results. Then, express your explanations or justifications.

Response:

The reviewer is concerned about the lack of sufficient discussion. The reviewer is correct. We appreciate the chance to clarify our exposition. We have revised the paper as explained below.

(1) Results of the confirmatory factor analysis are discussed in comparison to results obtained for other countries (lines 335–346).

(2) The relation between sociodemographic variables and FCV-19S was discussed in comparison to the results of earlier studies (lines 349–358).

(3) Effects of FCV-19S on coping behaviors were discussed in comparison to Winter et al., 2020 and to Harper et al., 2020 (lines 359–375 ).

Other points to change

ERROR CORRECTED

p.6 line 103: “Socio-demographic variable” (previous manuscript: Attributes of the respondents)

p.6 line 108: “6 = having other symptoms” (previous manuscript: 9 = having other symptoms)

p.11 line 236: “FCV-19S-J” (previous manuscript: Japanese FCV-19S-J)

p.23 line 389: “longitudinal study” (previous manuscript: cross-sectional surveys)

Submitted filename: Response to Reviwers.docx

Click here for additional data file.

26 Oct 2020

The Japanese version of the Fear of COVID-19 scale: Reliability, validity, and relation to coping behavior

PONE-D-20-15563R1

Dear Dr. Wakashima,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Ali Montazeri

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors have addressed my comments. The paper can be published. Thank you so much for sending the paper for review in PLOS One.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

28 Oct 2020

PONE-D-20-15563R1

The Japanese version of the Fear of COVID-19 scale: Reliability, validity, and relation to coping behavior

Dear Dr. Wakashima:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Professor Ali Montazeri

Academic Editor

PLOS ONE