Application of Health Belief Model for the assessment of COVID-19 preventive behavior and its determinants among students: A structural equation modeling analysis.

BACKGROUND: COVID-19 is a new pandemic that poses a threat to people globally. In Ethiopia, where classrooms are limited, students are at higher risk for COVID-19 unless they take consistent preventative actions. However, there is a lack of evidence in the study area regarding student compliance with COVID-19 preventive behavior (CPB) and its predictors.
OBJECTIVE: This study aimed to assess CPB and its predictors among students based on the perspective of the Health Belief Model (HBM). METHOD AND MATERIALS: A school-based cross-sectional survey was conducted from November to December 2020 to evaluate the determinants of CPB among high school students using a self-administered structured questionnaire. 370 participants were selected using stratified simple random sampling. Descriptive statistics were used to summarize data, and partial least squares structural equation modeling (PLS-SEM) analyses to evaluate the measurement and structural models proposed by the HBM and to identify associations between HBM variables. A T-value of > 1.96 with 95% CI and a P-value of < 0.05 were used to declare the statistical significance of path coefficients. RESULT: A total of 370 students participated with a response rate of 92%. The median (interquartile range) age of the participants (51.9% females) was 18 (2) years. Only 97 (26.2%), 121 (32.7%), and 108 (29.2%) of the students had good practice in keeping physical distance, frequent hand washing, and facemask use respectively. The HBM explained 43% of the variance in CPB. Perceived barrier (β = - 0.15, p < 0.001) and self-efficacy (β = 0.51, p <0.001) were significant predictors of student compliance to CPB. Moreover, the measurement model demonstrated that the instrument had acceptable reliability and validity. CONCLUSION AND RECOMMENDATIONS: COVID-19 prevention practice is quite low among students. HBM demonstrated adequate predictive utility in predicting CPBs among students, where perceived barriers and self-efficacy emerged as significant predictors of CPBs. According to the findings of this study, theory-based behavioral change interventions are urgently required for students to improve their prevention practice. Furthermore, these interventions will be effective if they are designed to remove barriers to CPBs and improve students' self-efficacy in taking preventive measures.

Introduction

The global outbreak of the COVID-19 pandemic has spread worldwide, affecting almost all countries and territories [1]. The pandemic is highly contagious that has been spread to different countries within a few months of its occurrence and it was declared as a pandemic by the World Health Organization (WHO) making it the concern of the global population [1, 2].

In addition to causing morbidities and mortalities, the pandemic affects all aspects of human life [3, 4]. Education is one of the most affected systems worldwide by the pandemic [5]. Consequently, schools were locked down for months by which students were obliged to stay at home with no education. Its effect on education is disproportionately higher in developing countries like Ethiopia due to the poor technological infrastructures that could support online education [6, 7].

The federal government of Ethiopia declared school reopening after six months of lock down so that students have started face to face leaning [8]. Students learn in a crowded environment because of the limited number of classrooms in schools, which can increase the risk of COVID-19 transmission unless appropriate preventive measures are taken [9]. Given this, the involvement of students in COVID-19 preventive activities is crucial to contain the spread of the pandemic among themselves and their community at large.

Even though there is no a proven drug to treat COVID-19 [10], there are various nonpharmaceutical interventions such as hand-washing, wearing a facemask, and physical distancing have established their relevance in preventing the spread of the infection [1]. On the contrary, schools are institutions where students are gathered together to learn, which makes physical distancing difficult and in turn imposes an increased risk of COVID-19 infection unless adequate precaution measures are taken by the schools and the students too [11].

Studies from various parts of the world have shown that student’s engagement in COVID-19 preventive behaviors is highly variable across countries. For example, 74.5% of students wear a facemask and 85% of students washed their hands frequently in Bangladesh [12], 80.0% of students adopted social isolation strategies, regular hand washing, and enhanced personal hygiene measures in Jordan [13] and more than 94% of students were following the recommended preventive health behaviors in Iran [14]. On the other hand, few studies among Ethiopian university students have shown unsatisfactory compliance behavior of students towards COVID 19 preventive measures, where only 56% of students keep their physical distance, 74% wash their hands frequently [15, 16].

COVID-19 is not only a health threat, but it is also a threat to the socio-economic aspect of human life [17].

The extent to which a disaster like the COVID-19 pandemic could impact people’s lives depends on how they perceive the disaster [18, 19]. For example, a study done by Mahmoud AB and his colleagues claimed that individuals’ job insecurity was highly dependent on their perceptions of the pandemic in which employees with an intense perception of COVID-19 were more likely to be exposed to job insecurity [19].

Risk reduction measures such as social distancing, hand washing, and wearing a facemask can rarely be enforced entirely by coercion unless students must understand what is expected of them and feel strongly about the importance of compliance. In this regard, Health Belief Model (HBM) is the most appropriate fit behavioral framework to understand why students are /aren’t participating in COVID-19 preventive measures [20].

The HBM was developed in the 1950s for the purpose to explain why people do/don’t take a certain preventive measure if they face the risk of being ill [20-22]. According to this model, students are most likely to take COVID-19 preventative measures if they perceive the threat of contracting the infection is to be serious, feel they are personally susceptible to the infection, have the confidence of executing the recommended preventive actions, and perceive that there are fewer costs than benefits to engaging in preventive measures [23].

HBM has shown an adequate utility in the prediction of the various spectrum of health behaviors [21, 22, 24]. For instance, studies from India [25], Iran [26], Iraq [27], and Ethiopia [28, 29] have shown the predictive utility of the model in the prediction of COVID-19 preventive health behaviors among the various population.

Theory, research, and practice are interrelated concepts that are essential to understanding health behavior and health behavior change. The best theory is informed by practice and the best practice should be grounded in theory [30]. The HBM is one of the various health behavior models that has been demonstrated its importance in guiding behavior change intervention in various settings [31, 32]. This model also could help us to understand why students do/don’t take COVID-19 preventive measures by taking their perception of the pandemic and the recommended measures into account.

Moreover, identifying important cognitive factors that drive the students’ compliance to the preventive measures of COVID-19 would have greater importance to design appropriate health communication programs that influence students to take the recommended preventive measures of COVID-19. Furthermore, students are at higher risk of getting COVID-19 infection due to the large class size, a common phenomenon in resource-limited countries like Ethiopia. In this case, following the recommended measures for COVID-19 infection is of great importance. However, students’ COVID-19 prevention practice and associated factors have remained unstudied in the academia. Therefore, this study aimed to assess COVID-19 preventive health behavior (CPB) and associated factors among secondary school students in Gondar City, North West Ethiopia based on the Health Belief Model [S1 Fig]. Furthermore, the authors believe that the study generated a shred of preliminary evidence that could have paramount importance to design contextual behavior change interventions among students in the study area to improve student’s COVID-19 prevention practice.

Methods

Study participants

An institution based crossectional study was conducted from November to December 2020 among secondary school students (Grade 9th to 12th) attending their class during the academic year of 2020/2021in Gondar city. According to the Ethiopian education system, secondary school students refer to students who attend their class at high school (9th to 10th) and preparatory schools (11th to 12th). All secondary school students who were attending their class at Gondar city were included in the present study. Students who are out of school during the data collection period after home checkups (A family call to check whether students unavailable at school during data collection were available at home and able to fill a questionnaire) were excluded from the study. In addition to this, students who were transferred out and/or transferred in from schools out of Gondar in the 2020/2021 academic year were also excluded.

Sample size determination and procedure

The sample size was determined for another study which is submitted to BMC Journal of Psychiatry that aimed to assess COVID-19 associated anxiety among students. Moreover, the sample size was also above the minimum required sample size for PLS-SEM analysis based on the ten times rule of thumb [33]. Our final model consisted of a total of 32 (5 in the inner model and 27 in the outer model) paths indicated that at least 320 (10 times 32) observations are required for PLS-SEM estimations. Fortunately, our pre-calculated sample was 370 which was adequate to proceed with PLS-SEM. Furthermore, we conducted a post hoc power analysis to verify that the sample was adequate to detect the required estimates precisely based on the following assumption: the amount of explained variance in the endogenous variable (0.43), number of predictor (exogenous) variables (5), significance level (0.05), and sample size (370). Based on that, the observed power was calculated to be 1.0, which is acceptable (> 0.8) [34-36].

We employed a stratified simple random sampling technique. First, stratification was done based on school ownership into private and governmental schools, which resulted in 5 and 12 schools respectively, and then the sample was allocated proportionally. Then, three governmental (Fasiledess preparatory school, Azezo secondary school, and Hidar 11 secondary school) and two private (Debre Selam St. Mary secondary school and Waliya secondary school) schools were selected on a random basis. Finally, study participants were selected using a simple random sampling technique based on their merged class roaster using Microsoft excel random number generator.

Study variables

In a multivariate analysis, variables are classified into four categories involving endogenous (independent), exogenous (dependent), latent (unobserved), and observed (manifest) variables. In this regard, the endogenous (dependent) variable of this study was CPB. Whereas, perceived severity, perceived susceptibility, perceived barriers, perceived benefits, self-efficacy, and cues to action were the exogenous (independent) latent variables. A total of 27 manifests (observed) variables were used to measure the latent variables included in the final model. Moreover, sociodemographic attributes of students (age, sex, religion, parental education, parental occupation, family income, living arrangement) were also measured.

Data collection and measurement

Data collection

Data were collected using a structured self-disinterred questionnaire. The self-administered technique was selected over the interviewer-administered method for the following reasons: a) all of the study participants were literate, b) it can reduce social desirability bias, and c) this approach is resource efficient [37, 38]. Four BSc nurses and two public health professionals were participated in the data collection process as a data collector and supervisor respectively after they received a one-day training on the purpose of the study, the data collection process, the ethical considerations, and the precautions that should be taken during the data collection process. The data were collected at school from Monday to Friday.

The data collectors used hand sanitizers, gloves, and facemasks during the data collection. At the same time, students were also obliged to wear facemasks and clean their hands with hand sanitizer/alcohol. Moreover, each participant was asked for the symptoms of the coronavirus infection by the data collectors before starting any data collection [39].

Measurements

The questionnaire used for this study was adapted from different literature by the research team [20, 25, 28, 40, 41]. The instrument was initially prepared in English and then translated into the local language (Amharic). Back translation to English was done to check its consistency. Content validity test and pre-test of the instrument were done based on 10 experts and 21 secondary school students respectively. The content validity was assessed based on six health behavior, two infectious diseases, and two COVID-19 pandemic response team experts’ judgment. The final questionnaire used for this study was composed of 51 items with two sections measuring sociodemographic, and HBM variables (perceived severity, perceived susceptibility, perceived barriers, perceived benefits, self-efficacy, cues to action, and CPB).

Perceived susceptibility. It was defined as a student’s perception of the risk of contracting COVID-19 infection and it was measured by six items having a five-point Likert scale. Its score ranged from 6–30. The higher score indicated higher perceived susceptibility towards COVID-19 [25].

Perceived severity. It was defined as a student’s perception of the seriousness of having COVID-19 infection and it was measured by 5 items having a five-point Likert scale. Its score ranged from 5–25. The higher score indicated higher perceived severity towards COVID-19 [41, 42].

Perceived benefit. It was defined as a student’s perception of the benefits of wearing a facemask, keeping physical distance, and washing hands frequently for the prevention of COVID-19 and it was measured by five items having a five-point Likert scale. Its score ranged from 5–25. The higher score indicated higher perceived benefits of performing recommended preventive COVID-19 behaviors [25, 41, 42].

Perceived barriers. It was defined as a student’s perception of the factors that restrict an individual to do COVID-19 preventive measures and it was measured by four items having a five-point Likert scale. Its score ranged from 4–20. The higher score indicated higher perceived barriers to avoid behavioral risk behaviors of COVID-19 [25].

Self-efficacy. It was defined as a student’s confidence to execute recommended preventive measures of COVID-19 and it was measured by four items having a five-point Likert scale. Its score ranged from 4 to 20. A higher score indicated the student’s higher self-efficacy/confidence to execute the recommended measures [25, 41, 42].

Cues to action. It refers to the impact of triggering media, bodily testimonials on student’s compliance behavior to the preventive measures of COVID-19. It was measured by three items having a five-point Likert scale. Its score ranged from 3 to 15. The higher score indicates the higher impact of cues to execute preventive behaviors [25, 41, 42].

Preventive health behaviors. Refers to the student’s practice concerning handwashing, physical distancing, and facemask wearing to prevent COVID-19 infection. It was measured by seven items having a five-point response rate ranging from 1 (Never) to 5 (always). The composite score of the preventive behaviors ranged from 8 to 40. The higher score indicates student’s better engagement COVID-19 preventive behaviors [25, 28].

The psychometric properties of each construct are depicted in detail in the result section of this manuscript [Tables 5 and 6].

Table 5

The reliability and convergent validity tests results of the instrument used to assess students CPB based on the Health Belief Model in Gondar city, Northwest Ethiopia, 2020 (n = 370).

Construct domain		Initial Model				Final Model
	Indicator	loading	Alpha	CR	AVE	Loading	Alpha	CR	AVE
Cues to action	CA1	0.66	0.76	0.77	0.52	0.66	0.76	0.78	0.52
	CA2	0.83				0.84
	CA3	0.66				0.66
CPB	CPB1	0.79	0.89	0.89	0.51	0.78	0.88	0.88	0.52
	CPB2	0.67				0.65
	CPB3	0.72				0.70
	CPB4	0.71				0.69
	CPB5	0.74				0.73
	CPB6	0.55				Omitted
	CPB7	0.74				0.73
	CPB8	0.75				0.74
Perceived barrier	PBA1	0.82	0.86	0.86	0.62	0.74	0.84	0.85	0.56
	PBA2	0.76				0.69
	PBA3	0.93				0.89
	PBA4	0.51				Omitted
	PBA5	0.47				Omitted
	PBA6	0.24				Omitted
	PBA7	0.71				0.65
Perceived benefit	PBE1	0.79	0.87	0.85	0.48	0.76	0.86	0.86	0.54
	PBE2	0.80				0.77
	PBE3	0.74				0.68
	PBE4	0.76				0.72
	BEN 5	0.60				Omitted
	PBE6	0.76				0.75
Perceived severity	PSE1	0.78				0.79	0.86	0.87	0.62
	PSE2	0.78				0.78
	PSE3	0.68				0.67
	PSE4	0.89				0.89
Self-efficacy	SEF1	0.72	0.82	0.82	0.54	0.72	0.82	0.83	0.53
	SEF2	0.67				0.67
	SEF3	0.69				0.70
	SEF4	0.84				0.83
Perceived susceptibility	PSU1	0.52	0.78	0.72	0.42
	PSU2	0.82
	PSU3	0.77
	PSU4	0.87
	PSU5	-0.30
	PSU6	0.34

Note: AVE = Average Variance Extracted, CR = Composite Reliability, CA = Cues to action, CBM = COVID-19 preventive behaviors, PBA = Perceived barrier, PBE = Perceived benefit, PSE = Perceived severity, SEF = Self efficacy, “Initial model” is a seven-factor with all HBM variables, “Final model” is a six-factor model with all HBM variables except perceived susceptibility.

Table 6

Heterotrait-Monotrait (HTMT) discriminant validity test result of the instrument used to assess students COVID-19 preventive behavior based on the Health Belief Model in Gondar city, Northwest Ethiopia, 2020 (n = 370).

Construct Domains	CPB	CA	PBA	PBE	PSE	SEF
COVID-19 preventive behavior (CPB)
Cues to action (CA)	0.49
Perceived barrier (PBA)	0.25	0.25
Perceived benefit (PBE)	0.31	0.55	0.15
Perceived susceptibility (PSE)	0.23	0.27	0.06	0.40
Self-Efficacy (SEF)	0.62	0.61	0.14	0.34	0.18

Data processing and analysis

The data were entered into EpiData version 4.6 and transferred into STATA version 14 and SMART-PLS version 3.2 statistical software for further data cleaning, coding and analysis. Descriptive statistics such as medians, interquartile ranges, frequencies, and proportions were computed. A structural equation modeling analysis was employed to assess relationships among the latent variables (HBM constructs) and the convergent and discriminate validity of the instrument. Structural equation modeling is a multivariate analytical approach used to simultaneously test and estimate complex causal relationships among variables. It can also be used to assess whether a hypothesized model is consistent with the data collected to reflect a theory [43]. There are two major approaches to structural equation modeling–covariance-based SEM (CB-SEM) and variance-based/partial least squares SEM (PLS-SEM). Even though both approaches are used for the same purpose, to assess cause-effect relations between latent constructs, they differ in their basic assumptions and estimation procedures [44]. PLS-SEM uses a regression-based ordinary least squares (OLS) estimation method intending to explain the latent constructs’ variance by minimizing the error terms and maximizing the R2 values of the target endogenous constructs [45]. On the other hand, the CB-SEM estimation procedure aims at reproducing the covariance matrix i.e., minimizing the difference between the observed and estimated covariance matrix, without focusing on explained variance [43]. CB-SEM requires normally distributed data and larger sample size, particularly when the data didn’t meet multivariate normality assumption, to produce precise estimates than PLS-SEM which can produce precise estimate with smaller sample size regardless of multivariate normality of the [33, 45, 46]. In the present study, the multivariate normality assumption was assessed and it was markedly departed from the multivariate normality assumption with a Mardia coefficient of 14.8 [47]. Therefore, we preferred to use PLS-SEM since it is an appropriate approach with a smaller sample size regardless of the multivariate assumptions.

The PLS-SEM analysis was done in two steps. In the first step reliability, convergent, and discriminant validity of the instrument were judged based on the assessment of the outer model (a model which shows the relationship between the latent variable and its indicators) by constructing a seven-factor model (initial model) based on the health belief model. The reliability of items within a construct was assessed using Cronbach’s coefficient (α) composite reliability of > 0.7 [48].

The discriminant validity was assessed using Hetro-Trait Mono-Trait (HTMT) criterion and all the HBM constructs achieved the discriminant validity, HTMT<0.85 [49]. Whereas, convergent validity was assessed using average variance extracted (AVE), where all HBM constructs except perceived severity achieved (AVE> 0.5) [43]. Moreover, perceived benefit, perceived barrier and CPB achieved convergent validity, AVE > 0.5 following the removal of 1, 3, and 1 poorly loaded items respectively. However, perceived susceptibility failed to achieve construct validity at all because of poor factor loading values of its indicators [Table 5]. Furthermore, the presence of multicollinearity among constructs was assessed using variance inflation factor (VIF). The VIF value of each construct was ranged from 1.43 to 2.95 which laid within the acceptable range, less than five [50].

At the second stage, we constructed a six-factor model (final model) based on the HBM model by excluding perceived susceptibility (because it didn’t achieve convergent validity). The bootstrapping procedure was employed to evaluate the structural model empirically and to calculate significant values for all paths [51]. We calculated the amount of variance (R2) in CPB explained by the model and the path coefficients, including the T-value and P-value. The R2 criterion value was evaluated based on the previous recommendations: 0.02 as small, 0.13 as a medium, and 0.26 as large. To evaluate our hypotheses, we considered path coefficients with a T-value >1.96 and a P-value <0.05 as significant. Moreover, coefficient of determination (R-Square) and predictive relevance (Q2) were computed through the Blindfolding procedure to assess the final model predictive utility. Accordingly, the final model demonstrated acceptable predictive utility. All PLS-SEM analyses were performed using SmartPLS 3 software.

Ethical consideration

For this study, ethical clearance was obtained from the Institute Review Board (IRB) of the University of Gondar with an approval number of V/PRCS/05/548/2020. Written consent was obtained from participants aged 18 and above. For participants with the age of less than 18, parental/guardian consent and assent from themselves were obtained. Moreover, permission letters and oral permissions were obtained from the city education office and selected school principals respectively. Each of the participants was included voluntarily and the data were analyzed anonymously. Indeed, the study was conducted following the Declaration of Helsinki [52].

Result

Sociodemographic characteristics

A total of 370 students participated in this study with a response rate of 92%. The median age of the participants was 18 with an interquartile age range of 2 years. More than half (51.9%) of the participants were females. The majority of the participants (76.2%) were from private schools (Table 1).

Table 1

Socio-demographic characteristics of Gondar city secondary school students, North West Ethiopia, 2020 (n = 370).

Variable	Response category	Frequency	Percent
Age	< 18	149	40.3
	≥ 18	221	59.7
Sex	Male	178	48.1
	Female	192	51.9
Marital Status	Single	328	88.7
	Married	33	8.9
	Engaged	9	2.4
Educational status of the participants	Grade 9	11	3.0
	Grade 10	146	39.5
	Grade 11	93	25.1
	Grade 12	120	32.4
Religion	Orthodox	331	89.5
	Muslim	39	10.5
Mother’s occupation	Housewife	262	70.8
	Government employee	47	12.7
	Merchant	33	8.9
	NGO employee	13	3.5
	Other	15	4.1
Father’s occupation	Government employee	92	24.9
	NGO employee	42	11.3
	Merchant	93	25.1
	Farmer	121	32.7
	Other	22	6.0
Mother’s educational status	Unable to read and write	131	35.4
	Able to read and write	89	24.0
	Primary	59	16.0
	Secondary	59	16.0
	Tertiary	32	8.6
Father’s educational status	Unable to read and write	64	17.3
	Able to read and write	116	31.4
	Primary	59	16.0
	Secondary	70	18.9
	Tertiary	61	16.4
To whom do you live?	With my parents	237	64.0
	With my siblings	49	13.2
	With my relatives	31	8.4
	Alone	43	11.6
	Other	10	2.7
School type	Government School	272	76.2
	Private School	88	23.8

COVID-19 preventive behaviors

About 80 (21.6%), 62 (16.76%), 81 (21.89) of students reported that they never keep their physical distance, never wash their hands frequently for at least 20 seconds, and never wear facemask respectively. On the other hand, only 97 (26.2%), 121 (32.7%), and 108 (29.2%) of the students reported that they consistently keep their physical distance, wash their hands frequently for at least 20 minutes, and wear facemask respectively [Table 2].

Table 2

COVID-19 preventive behaviors among secondary school students in Gondar city, Northwest Ethiopia 2020 (n = 370).

Items	Response categories
	Poor practice			Good practice
	Never	Rarely	Some times	Many times	Always
I keep my physical distance	80 (21.62)	103 (27.84	90 (24.32)	55 (14.86)	42 (11.35)
I bend my elbow in front of my mouth and nose when I cough or sneeze	46 (12.43)	76 (20.54)	82 (22.16)	74 (20)	92 (24.86)
I don’t shake hands/ kiss others	64 (17.3)	120 (32.4)	92 (24.86)	41 (11.08)	53 (14.32)
I don’t leave the house unless necessary	92 (24.86)	87 (23.51)	99 (26.76)	48 (12.97)	44 (11.89)
I wash my hands frequently for at least 20 minutes	62 (16.76)	83 (22.43)	104 (28.11)	68 (18.38)	53 (14.32)
I don’t touch my nose, face, and mouth without washing my hands	76 (20.54)	66 (17.84)	83 (22.43)	60 (16.22)	85 (22.97)
I wear facemask	81 (21.89)	86 (23.4)	95 (25.68)	57 (15.41)	51 (13.78)

Health Belief Model variables

The composite score for each construct of HBM was computed by adding indicators value of the same construct. Then, the composite score was divided by the number of indicators for each construct to produce a standardized score to make a comparison across constructs. Only two construct’s median score were higher than the neutral score of the Likert scale. The lowest median score was observed in students’ perceived severity of the pandemic, whereas the highest score was observed in their perceived benefit of taking preventive measures and cues to action to take preventive measures. The median score of perceived severity was significantly higher among females at a p-value < 0.05. However, there was no significant difference in the median score of all other constructs across gender [Table 3].

Table 3

Descriptive summary results of Health Belief Model variables.

Construct domain	Total			Male		Female
	Score range	Median	IQR	Median	IQR	Median	IQR
Perceived susceptibility	1–5	2.9	1.8	3.2	1.6	2.8	1.7
Perceived severity*	1–5	2.75	2	2.5	1.5	3	1.25
Perceived benefit	1–5	4	1.2	4	1.2	4	1
Perceived barrier	1–5	2.85	1.6	3	1.6	2.85	1.6
Cues to action	1–5	4	1.3	4	1	4	1.3
Self-efficacy n	1–5	3	1.75	3	0.93	2.99	1.03
CPB	1–5	2.88	1.4	2.75	1.37	2.94	1.4

* Shown significant difference across gender at p-value <0.05, CPB = COVID-19 Preventive Behavior

Mean and standard deviation are reported instead of median and interquartile ranges respectively because the construct’s score was normally distributed, IQR = Interquartile range.

Correlation among Health Belief Model variable

Since the score of most of constructs didn’t meet the normality assumption, we employed a Spearman’s correlation analysis to assess the relationship between HBM variables [53]. The result revealed that perceived severity (r = 0.2, p < 0.05), perceived benefit (r = 0.27, p < 0,05), self-efficacy (r = 0.52, p < 0,05) and cues to action (r = 0.40, p < 0,05) were positively and significantly correlated with CPB. On the other hand, perceived barrier (r = -0.22, p < 0,05) was negatively correlated with CPB whereas perceived susceptibility didn’t show significant correlation with COVID-19 preventive behavior [Table 4].

Table 4

Spearman correlation among Health Belief Model variables.

Constructs	PSU	PSE	PBE	PBA	CA	SEF	CPB
PSU	1.00
PSE	0.26 (<0.001)	1.00
PBE	0.13 (0.02)	0.34 (<0.001)	1.00
PBA	0.08(0.62)	0.04 (0.28)	-0.12 (0.06)	1.00
CA	0.14(0.01)	0.23(<0.001)	0.44 (<0.001)	-0.20(0.01)	1.00
SEF	0.09(0.07)	0.15(0.01)	0.29 (<0.001)	-0.12(0.01)	0.48(<0.001)	1.00
CPB	0.10 (0.11)	0.20(<0.001)	0.27(<0.001)	-0.22(0.002)	0.40(<0.001)	0.52(<0.001)	1.00

Note: values in the bracket in each cell represents a p-value and values out of the bracket are correlation coefficients (r), PSU = Perceived susceptibility, PSE = Perceived severity, PBE = Perceived benefit, PBA = Perceived barrier, CA = Cues to action, SEF = Self-efficacy, and CPB = COVID-19 preventive behavior.

Structural equation modeling analysis

Structural equation modeling analysis involves two important model assessments, each has its objectives. These models are measurement model (outer model) assessment and structural model (inner model) assessment. The first one was done to evaluate the psychometric properties of the instrument whereas the second was employed to test the hypothesis that was proposed by the HBM in predicting a CPB.

Concerning the measurement model assessment, all of the HBM constructs shown adequate reliability and convergent validity except perceived susceptibility. The results indicated that all of the HBM model constructs were measured adequately, where each of the constructs captured 50% of the variance in its indicators [Table 5].

Discriminant validity

Discriminant validity ensures that a constructed measure is empirically unique and represents phenomena of interest that other measures in a structural equation model do not capture [54]. This was assessed by using heterotrait-monotrait ratio of correlations (HTMT); a new method for assessing discriminant validity in partial least squares structural equation modeling [49]. The HTMT value of 0.85 was used to declare convergent validity. As it is depicted in the table below all of the HBM constructs showed acceptable discriminant validity [Table 6].

Structural model assessment

The structural model assessment was done to test the hypothesis proposed by the health belief model. In this regard, a six-factor model was fitted to assess the associations among the HBM variables. In the final model, perceived severity, perceived benefit, perceived barrier, self-efficacy, and cues to action were fitted as exogenous latent variables to predict the endogenous (independent) variable (CPB) as proposed by the HBM. The final model explained 43% of the variance in CPB, indicated that the model showed an adequate predictive utility [Fig 1].

Fig 1

Structural equation model of determinants of CPB among secondary school students in Gondar city, Northwest Ethiopia, 2020.

CA = Cues to action, CBM = COVID-19 preventive behaviors, PBA = Perceived barrier, PBE = Perceived benefit, PSE = Perceived severity, SEF = Self efficacy, Path coefficients shown in red color were not statistically significant.

The structural equation modeling analysis revealed that perceived barriers (β = - 0.15, p = <0.001) and self-efficacy to execute the recommended COVID-19 measures (β = 0.51, p = <0.001) were significantly linked to CPB positively and negatively respectively. This indicated that students were more likely to engage in COVID-19 preventive behaviors if their perception of barriers to take the recommended measures was lower or their confidence to execute those recommended measures were high. Perceived benefit, perceived severity, and cues to action were linked positively to CPB. However, none of them were statistically significant. Moreover, self-efficacy was a powerful predictor of CPB [Table 7].

Table 7

Path coefficient of the structural equation modeling analysis of CPB among secondary school students in Gondar city, Northwest Ethiopia, 2020 (n = 370).

Hypothesis	Path coefficients	95% CI		T-Value	P Values
		Lower Bound	Upper bound
Cues to action → CPB	0.11	-0.04	0.27	1.29	0.20
Perceived barrier → CPB	-0.15	-0.24	-0.06	3.17	<0.001
Perceived benefit → CPB	0.02	-0.13	0.15	0.30	0.77
Perceived severity → CPB	0.10	-0.02	0.20	1.76	0.08
Self-efficacy → CPB	0.51	0.36	0.64	7.19	<0.001

R2 = 0.43, CBM COVID-19 Preventive Behavior.

Discussion

This research uses the health belief model to assess predictors of COVID-19 preventive behavior (CPB) of secondary school students in Gondar city. The model explained a 43% variance in the CPB of students. This indicates the model was adequate in predicting the CPB and it may be used to guide behavior change interventions among students in the study area [55]. The result of this study is higher than that of a study conducted in Iran [26] and lower than that of a study conducted in Egypt [42], where the HBM explained 26% and 58% of the variance in CPB respectively. This difference may be due to the different methods of analysis between the current and previous studies. Previous studies have used ordinary regression analysis that may affect the predictive utility of the model because these analysis approaches don’t account for measurement errors. In contrast, this study used a multivariate analysis approach that provides a precise estimate against ordinary regression analyses because it takes measurement errors into account.

Only 97 (26.2%), 121 (32.7%), and 108 (29.2%) of students had good practice regarding physical distance, frequent hand washing, and facemask use respectively. These results are lower than the findings reported by different previous studies [15, 16, 26, 29]. The discrepancy may be explained by the fact that previous studies were conducted at the beginning of the introduction of COVID-19 when everybody was scared and had taken preventive measures aggressively.

As time goes by, the risk perception of individuals may be reduced because they have received a great deal of information about the nature of the pandemic. As a result, people’s engagement in preventive practices may be reduced. Moreover, the results indicate that most students were not performing the recommended preventive measures for COVID-19. This requires urgent measures, such as school health communications on COVID-19 prevention, to improve students’ COVID-19 prevention practice. Besides, students come to school from different villages, which can increase the risk of pandemic transmission in their communities if they become infected. As such, there is a need to encourage students to follow recommended COVID-19 prevention measures for their benefit and the benefit of their community as well.

Among the HBM constructs, perceived barriers and self-efficacy were found to be significant predictors of CPB in the present study. Various HBM -studies conducted based on the HBM have also identified perceived barriers as a significant determinant of poor adherence to CPB [26, 28, 29, 42]. In our study, perceived barriers had a significant negative association with COVID-19 preventive behavior. This indicated that students were more likely to adopt COVID-19 preventive behaviors if their perceived barriers (lack of soap, lack of sanitizers/alcohol, the impact of COVID-19 preventive measures on daily activities, and poor economic status) were eliminated. In addition to this, our PLS-SEM analysis also revealed that self-efficacy was another significant predictor of COVID-19 preventive behaviors. This result indicated that student engagement with COVID-19 preventive behavior was dependent on their perceived self-efficacy/confidence to take the recommended measures. These results are consistent with various studies conducted previously elsewhere based on the health belief model [26, 28, 29, 40–42]. In the present study, perceived self-efficacy was the most powerful predictor of students’ COVID-19 preventive behaviors, identified the need to focus on improving student self-efficacy (confidence) to adopt COVID-19 preventative behavior for students to follow recommended actions. This finding is contradictory with a systematic review of HBM-based studies that claimed that perceived barrier was the strongest predictor of preventive health behaviors [30]. However, it is consistent with some other studies that were done using the health belief model to predict COVID-19 preventive behaviors [28, 40, 41].

In the present study, perceived benefit, perceived severity, and cues to action showed a positive correlation with the COVID-19 preventive behaviors as proposed by the HBM. However, none of them showed any significant association in the structural equation modeling analysis. These findings were contradictory in other studies. On the other hand, the results are consistent with various previous studies based on HBM that indicated that perceived severity was not an important predictor of COVID-19-related preventative behaviors, where perceived benefit [26, 29] and cues to action [28] were significant predictors of COVID-19 preventive behaviors. On the other hand, the results of this study are consistent with various previous HBM based studies which claimed that perceived severity was not a significant predictor of COVID-19 preventive behaviors [26, 28, 42].

The present study has several limitations including: it was solely based on self-reported responses of students that may be liable to social desirability bias, and the study was based on the intrapersonal level model, (HBM) where other environmental and interpersonal factors were not considered. Withstanding the aforementioned limitation, the study applied a structural equation modeling analysis which is supposed to produce a precise estimate in analyses involving latent variables, because this analysis technique takes measurement errors into account unlike the ordinary regression analysis [56].

Conclusion and recommendations

COVID-19 prevention practice is quite low among students. The Health Belief Model demonstrated adequate predictive utility in predicting preventive behaviors related to COVID-19. Perceived barrier and self-efficacy were found to be the significant predictors of COVID-19 preventive behavior. Thus, to contain the spread of the COVID-19 virus, schools should design and implement behavioral change programs to enhance protective behavior amongst students, by issuing warnings and recommendations about the pandemic, or by imposing legal restrictions accordingly. Moreover, such interventions should focus on the reduction of barriers (providing facemasks, hand sanitizers, and soaps for those who are in financial hardship) and enhancing students’ self-efficacy in adopting COVID-19 preventative behavior. Furthermore, the health belief model can also be used to guide behavior change interventions and other researches on the area of interest in the study area.

The authors believed that the present study generated a shred of preliminary evidence for COVID-19 prevention programs in schools in the study area. As we observed, most students have not implemented the recommended COVID-19 prevention measures. This could also lead to an increased risk of COVID-19 transmission in the community if they get infected, as long as students are expected to return to their homes. From this perspective, designing and implementing school-based behavioral change programs to enable students to follow recommended preventive measures will be of direct importance to the entire community.

Conceptual framework adapted based on the Health Belief Model and review of different literatures [20, 26, 28, 40, 41].

(TIF)

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17 Mar 2021

PONE-D-21-05732

Application of Health Belief Model for the Assessment of COVID-19 Preventive Behavior and its Determinants among Students: A Structural Equation Modeling Analysis

PLOS ONE

Dear Dr. Shitu,

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.

On receipt and processing, your manuscript was sent to two reviewers for assessment. I am now in receipt of the recommendation from the two reviewers, which you will find at the bottom of this email. I have also now had the opportunity to re-read the manuscript myself, and I have two additional observations which I wish to offer in conjunction with the reviewers’ reports.

Your work ignores a substantial research body where COVID-19/Pandemic/wartime perceptions were conceptualised, and this work needs to be consulted with. See Mahmoud et al. [1] and Mahmoud and Reisel [2]

Please, whilst revising, offer your manuscript proper proofreading.

References

1.            Mahmoud AB, Grigoriou N, Fuxman L, Reisel WD, Hack-Polay D, Mohr I: A generational study of employees’ customer orientation: a motivational viewpoint in pandemic time. Journal of Strategic Marketing 2020:1-18.

2.            Mahmoud AB, Reisel WD: Exploring Personal Experience of Wartime Crisis Effects on Job Insecurity in Syria. Psihologia Resurselor Umane 2015, 13(2):245–256.

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We look forward to receiving your revised manuscript.

Kind regards,

Ali B. Mahmoud, Ph.D.

Academic Editor

PLOS ONE

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: The strongest contribution of this study is the findings. This is because the results show that students in the Ethiopian city of Gondar do not have good practice of Covid-19 preventive measures. Methodology is sound and well executed. However, post-hoc power analysis should be conducted to ascertain statistical power for sample size adequacy (Refer to lines 123 – 130). The conclusion is logically derived from the analysis of data. However, this reviewer recommends the author/s to improve on the practical recommendations based on the findings of the study. Some thought should be given to what measures should be in place to improve the adoption of good practices of Covid-19 preventive measures among students. This is the weakest part of the article. Some typos (in the Table as well) exist in the manuscript. For example, expression like “pandemic that eats many lives" (line 66). This article requires editorial work to improve the written quality. Furthermore, the referencing style needs to conform to the standard expected by the Journal.

Reviewer #2: The effort invested in the crafting of this paper is apparent. However, the paper in its current form needs the suggested improvements in order to overcome the listed limitations and produce a stronger contribution to the state of existing knowledge within a reasonable timeframe. As a result, I am recommending a resubmit addressing the recommended changes for this paper prior to its acceptance in journal. I hope that the review comments will help further improve the work, or reframe it in such a way that a revised submission would be strengthened.

(1) In the abstract and introduction section, the rationale for and the aim/motivation of the study has not been stated, the rationale (academic underpinning) for conducting this study is not strong and is currently weak. E.g. What is the originality of this study?

(2) The paper provides a satisfactory literature review demonstrating an understanding of the relevant literature in the field with the appropriate up-to-date literature sources.

(3) Although the research methodology applied for the study is appropriate, this section lacks academic justifications to support your methodology choices – some of the statements/claims made sounds more arbitrary. There is a need to discuss the alternatives and justification of methods selected for data collection and data analysis, supported by appropriate references needs to be provided.

(4) An interesting area of research and the results provide significant theoretical and practical contributions but the discussions section could better relate the findings to entries information management applications.

(5) The current conclusion section needs to answer the following questions:

• How does the paper bridge the gap between theory and practice?

• What is the impact upon society?

(6) Overall, paper is well-written and structured, which does much for its readability and comprehensibility.

Best Wishes for revision

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Submitted filename: Remarks by Reviewer.pdf

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10 Apr 2021

Dear Ali B. Mahmoud, Ph.D., editor and reviewers:

Hereby, we resubmit the enclosed –revised- manuscript ID PONE-D-21-05732-[ EMID:15744fc9849b3e3d], which is entitled “Application of Health Belief Model for the Assessment of COVID-19 Preventive Behavior and its Determinants among Students: A Structural Equation Modeling Analysis” to your journal.

We have read the comments carefully and we were able to implement all of them (see the manuscript with track changes). While reading the manuscript critically, we spotted English grammar errors, which we and a language expert have corrected too. We hope that our revision will be felt like an improvement. We certainly feel this manuscript has improved thanks to the suggestions of the reviewers. The datasets generated and/or analyzed in the current study are available publicly with no restriction at https://www.kaggle.com/kegnieshitu/determinants-of-covid19-preventive-behaviors

Response to the Editor’s Comment and suggestions

On receipt and processing, your manuscript was sent to two reviewers for assessment. I am now in receipt of the recommendation from the two reviewers, which you will find at the bottom of this email. I have also now had the opportunity to re-read the manuscript myself, and I have two additional observations which I wish to offer in conjunction with the reviewers’ reports.

Your work ignores a substantial research body where COVID-19/Pandemic/wartime perceptions were conceptualised, and this work needs to be consulted with. See Mahmoud et al. [1] and Mahmoud and Reisel [2]

Please, whilst revising, offer your manuscript proper proofreading.

References

1. Mahmoud AB, Grigoriou N, Fuxman L, Reisel WD, Hack-Polay D, Mohr I: A generational study of employees’ customer orientation: a motivational viewpoint in pandemic time. Journal of Strategic Marketing 2020:1-18.

2. Mahmoud AB, Reisel WD: Exploring Personal Experience of Wartime Crisis Effects on Job Insecurity in Syria. Psihologia Resurselor Umane 2015, 13(2):245–256.

Response: Thank you very much, Dr. Ali B. Mahmoud, for your input and comments. I looked at two of the documents and found them both interesting. I tried to incorporate the findings of the first article in the background section of our manuscript (See page 5, line 93-97 in the manuscript). However, the second article is not related to the present study. While its primary focus is not related to COVID-19, the paper attempted to provide an overview of how job insecurity was in the Syrian war crisis. On the other hand, the present study attempted to provide an overview of how students are implementing the recommended preventive actions for COVID-19. Because of this, we could not consult the second article.

Response to Journal requirements:

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

Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found athttps://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf andhttps://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Response: We have prepared the manuscript in accordance with the guidelines presented at the aforementioned web addresses..

Please provide additional details regarding participant consent. In the ethics statement in the Methods and online submission information, please ensure that you have specified whether consent was informed.

Response: We referred to the ethics statement and stated that we have obtained ethical approval from the University of Gondar. As well, we obtained consent from each participant >=18 years of age and participants <18 years of age from their parents/guardians and their assent (See page 14, line 292-300 in the manuscript).

Please include your actual numerical p-values in Table 4.

Response: P-values are included for each correlation coefficient (See table 4 on page 19 in manuscript)

Please revise your tables to replace p-values of "0.000" to "<0.001".

Response: Correction was made accordingly (see Table 7 on page 23 in the manuscript)

Please provide the names of the five schools were participants were recruited from.

Response: We described the list of selected schools (See line 169-171 on page 8 in the manuscript)

Please include additional information regarding the survey or questionnaire used in the study and ensure that you have provided sufficient details that others could replicate the analyses. For instance, if you developed the survey or questionnaire as part of this study and it is not under a copyright more restrictive than CC-BY, please include a copy, in both the original language and English, as Supporting Information. If the questionnaire is published, please provide a citation to the (1) questionnaire and/or (2) original publication associated with the questionnaire.

Response: The tool was prepared by adapting instruments from various studies and that we provided an appropriate citation to the studies associated with the questionnaire. (See line 197-198 on page 10 in the manuscript)

7. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

Response: We made our dataset publicly available at:

https://www.kaggle.com/kegnieshitu/determinants-of-covid19-preventive-behaviors

8. We note you have included a table to which you do not refer in the text of your manuscript. Please ensure that you refer to Table 1 in your text; if accepted, production will need this reference to link the reader to the Table.

Response: Sorry for the mistake. We cited the table in its appropriate place (See line 304 on page 14 in the manuscript)

Response to reviewer 1 comments and suggestions

The strongest contribution of this study is the findings. This is because the results show that students in the Ethiopian city of Gondar do not have good practice of Covid-19 preventive measures. Methodology is sound and well executed. However, post-hoc power analysis should be conducted to ascertain statistical power for sample size adequacy (Refer to lines 123 – 130). The conclusion is logically derived from the analysis of data. However, this reviewer recommends the author/s to improve on the practical recommendations based on the findings of the study. Some thought should be given to what measures should be in place to improve the adoption of good practices of Covid-19 preventive measures among students. This is the weakest part of the article. Some typos (in the Table as well) exist in the manuscript. For example, expression like “pandemic that eats many lives" (line 66). This article requires editorial work to improve the written quality. Furthermore, the referencing style needs to conform to the standard expected by the Journal.

Response: Thank you for your comment. We did a post hoc power analysis based on assumptions including, the amount of examining variable in the endogenous variable (COVID-19 preventive behavior=0.43), the number of predictors (exogenous variables=5), significant level=0.05, and sample size=370. The computation was done using an online statistical calculator which was developed by an American professor, Daniel Soper (1) (See line 160-164 on page 8 in the manuscript).

1. Soper, D.S. (2021). Post-hoc Statistical Power Calculator for Multiple Regression [Software]. Available from https://www.danielsoper.com/statcalc

Moreover, we gave this manuscript to an English language expert, Mr. Fikadie, for an English language edition. Then the entire manuscript was edited for grammatical and typographic errors based on his suggestion and comments. We checked our referencing style whether it is per the journal requirement and made corrections. In addition to this, we tried to correct contextual errors we had noted in our proofreading and emotional expressions like “pandemic that eats many lives” were revised (see line 75-76 on page 4 in the manuscript).

Response to reviewer 2 comments and suggestions

Reviewer #2: The effort invested in the crafting of this paper is apparent. However, the paper in its current form needs the suggested improvements to overcome the listed limitations and produce a stronger contribution to the state of existing knowledge within a reasonable timeframe. As a result, I am recommending a resubmit addressing the recommended changes for this paper prior to its acceptance in journal. I hope that the review comments will help further improve the work, or reframe it in such a way that a revised submission would be strengthened.

(1) In the abstract and introduction section, the rationale for and the aim/motivation of the study has not been stated, the rationale (academic underpinning) for conducting this study is not strong and is currently weak. E.g. What is the originality of this study?

Response: Thank you for your valuable suggestions and comments. We tried to further describe the rationale and its originality in the introduction sections, (see line 113-132 on page 6 in the manuscript)

(2) The paper provides a satisfactory literature review demonstrating an understanding of the relevant literature in the field with the appropriate up-to-date literature sources.

Response: Thank you for your feedback.

(3) Although the research methodology applied for the study is appropriate, this section lacks academic justifications to support your methodology choices – some of the statements/claims made sounds more arbitrary. There is a need to discuss the alternatives and justification of methods selected for data collection and data analysis, supported by appropriate references need to be provided.

Response: We discussed the justifications for the data collection and analysis methodology we had used in this study. For instance, we followed a self-administered approach to collect our data for the following reasons; a) all of our participants were literates, b) the self-administered technique is better in reducing social desirability bias over the interviewer-administered approach, and c) the self-administered technique saves time and resource (see in line 185-188 at page 9 in the manuscript)

Regarding the analysis technique, we employed a structural equation modeling analysis which has been widely used by health behavior researchers investigating complex relationships between latent constructs such as perceived susceptibility, COVID-19 preventive behaviors, and so on. There are two approaches of structural equation modeling approaches; covariance-based SEM (CB-SEM) and variance-based same the so-called partial least squares SEM(PLS-SEM). Even though these approaches have the same purpose, they differ in their basic assumptions. The former is based on the maximum likelihood estimation technique that requires data that meets the multivariate normality assumption. Whereas the latter computes estimates using ordinary least squares estimation techniques regardless normality of the data. Moreover, the PLS-SEM is effective over CB-SEM with a small sample size and/or data that violate multivariate assumptions. In our case, we preferred to use PLS-SEM because our data didn’t meet the multivariate normality assumption (the details of comparison of these methods and supporting articles are presented in the manuscript, see in line 245-363 on page 12).

(4) An interesting area of research and the results provide significant theoretical and practical contributions but the discussions section could better relate the findings to entries information management applications.

Response: We made revisions to the discussion part by further discussing the impact of the findings on actual practice. (see the discussion part in the revised manuscript)

(5) The current conclusion section needs to answer the following questions:

• How does the paper bridge the gap between theory and practice?

• What is the impact upon society?

Response: We tried to mention how the current study findings could brig the gap b/n the theory and practice and its implication of on the society (See the conclusion part in the revised manuscript and see line 455-471 from page 26-27 in the manuscript)

(6) Overall, the paper is well-written and structured, which does much for its readability and comprehensibility.

Response: Thank you so much!

Submitted filename: Response to editor and reviewers OHBI PLOS ONE.docx

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15 Apr 2021

PONE-D-21-05732R1

Application of Health Belief Model for the Assessment of COVID-19 Preventive Behavior and its Determinants among Students: A Structural Equation Modeling Analysis

PLOS ONE

Dear Dr. Shitu,

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.

Outstanding from the previous review: AB Mahmoud and WD Reisel [1] conceptualise wartime perceptions which can form the theoretical premise for COVID-19 perceptions since the latter has triggered a war-like context— therefore, it has to be cited. While revising and addressing Reviewer 1 comments, make sure an English native speaker proofreads the whole text.

References

1.            Mahmoud AB, Reisel WD: Exploring Personal Experience of Wartime Crisis Effects on Job Insecurity in Syria. Psihologia Resurselor Umane 2015, 13(2):245–256.

Please submit your revised manuscript by May 30 2021 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 . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at  https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Ali B. Mahmoud, Ph.D.

Academic Editor

PLOS ONE

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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

Reviewer #2: 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

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: 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

Reviewer #2: 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: No

Reviewer #2: 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: In my first review of this article, I made comments on the need for post-hoc power analysis. This was included. Furthermore, I commended the authors of the important contribution of the article related to children and Covid-19 prevention behaviors and recommended authors to add relevant practical recommendations. What is unclear is the phrase "behavior change barograms" (line 488). Lastly, this revised submission still requires professional proofreading and editing to improve English expressions and grammar.

Reviewer #2: I am pleased to see that that the authors have taken the previous review comments on board and have set out to deal with every one of them. There has clearly been a great deal of additional work undertaken to address each of the reviewers' concerns, which is duly noted and appreciated. This has made a significant impact on the quality of the paper. Thank you.

**********

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: Yes: Dr Seong-Yuen Toh

Reviewer #2: No

[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.

26 Apr 2021

Dear Ali B. Mahmoud, Ph.D., editor and reviewers:

Hereby, we resubmit the enclosed –revised- manuscript ID PONE-D-21-05732-[ EMID:15744fc9849b3e3d], which is entitled “Application of Health Belief Model for the Assessment of COVID-19 Preventive Behavior and its Determinants among Students: A Structural Equation Modeling Analysis” to your journal.

We have read the comments carefully and we were able to implement all of them (see the manuscript with track changes). While reading the manuscript critically, we spotted English grammar errors, which we and a language expert have corrected too. We hope that our revision will be felt like an improvement. We certainly feel this manuscript has improved thanks to the suggestions of the reviewers.

Response to the Editor’s Comment and suggestions

Outstanding from the previous review: AB Mahmoud and WD Reisel [1] conceptualise wartime perceptions which can form the theoretical premise for COVID-19 perceptions since the latter has triggered a war-like context— therefore, it has to be cited. While revising and addressing Reviewer 1 comments, make sure an English native speaker proofreads the whole text.

References

1. Mahmoud AB, Reisel WD: Exploring Personal Experience of Wartime Crisis Effects on Job Insecurity in Syria. Psihologia Resurselor Umane 2015, 13(2):245–256.

Response: Thank you very much, Dr. Ali B. Mahmoud, for your input and comments. Initially, I was thought that the second manuscript is not related to ours. Now, I realized that the article is contextually related to our study under the umbrella of disaster (COVID-19 vs Wartime). I incorporated the article into my manuscript. (See line 94-98 in the manuscript). In addition to this, the whole manuscript was given to English experts in the University for proofreading, and amendments were made based on their feedback (see the revised manuscript with track changes)

Response to reviewer 1 comments and suggestions

In my first review of this article, I made comments on the need for post-hoc power analysis. This was included. Furthermore, I commended the authors of the important contribution of the article related to children and Covid-19 prevention behaviors and recommended authors to add relevant practical recommendations. What is unclear is the phrase "behavior change barograms" (line 488). Lastly, this revised submission still requires professional proofreading and editing to improve English expressions and grammar.

Response: Thank you Dr. Seong-Yuen Toh for your valuable comments and suggestions. Sorry for the error. We said "behavior change barograms" just to say "behavior change programs", it was a typographical error. We made corrections accordingly (See line 461 in the manuscript). In addition to this proofreading of the whole manuscript was done by the research team and English language experts. Moreover, our study findings claimed that the COVID-19 preventive practice among students was quite low. Based on these findings, we recommended schools design and implement behavior change interventions to enhance their pupil’s COVID-19 prevention practice. We also suggest some important focus of intervention based on our finding including reduction of barriers through the provision of facemasks, hand sanitizers, and soaps for those who are in financial hardship and enhancing students' self-efficacy to improve their prevention practice (see the conclusion and recommendation section of the manuscript).

Response to reviewer 2 comments and suggestions

I am pleased to see that that the authors have taken the previous review comments on board and have set out to deal with every one of them. There has clearly been a great deal of additional work undertaken to address each of the reviewers' concerns, which is duly noted and appreciated. This has made a significant impact on the quality of the paper. Thank you

Response: Thank you very much for your valuable contribution to the improvement of the manuscript.

Submitted filename: Response to editor and reviewers PLOS ONE.docx

Click here for additional data file.

9 Jul 2021

PONE-D-21-05732R2

Application of Health Belief Model for the Assessment of COVID-19 Preventive Behavior and its Determinants among Students: A Structural Equation Modeling Analysis

PLOS ONE

Dear Dr. Shitu,

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 Aug 23 2021 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 . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at  https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Ali B. Mahmoud, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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

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

Reviewer #3: 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

Reviewer #3: Yes

**********

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

Reviewer #1: Yes

Reviewer #3: 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

Reviewer #3: 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

Reviewer #3: 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: Acceptable standard of English after the amendments and improvements.

Please accept this paper for publication.

Reviewer #3: This revision is an improved one. The paper needs detailed proof reading to reconcile English discrepancies. Please see my suggested modifications in the attached file.

**********

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

Reviewer #3: No

[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.

Submitted filename: Review Plos One Ethiopia Study.docx

Click here for additional data file.

4 Aug 2021

Dear Ali B. Mahmoud, Ph.D., editor and reviewers:

Hereby, we resubmit the enclosed –revised- manuscript ID PONE-D-21-05732-[ EMID:15744fc9849b3e3d], which is entitled “Application of Health Belief Model for the Assessment of COVID-19 Preventive Behavior and its Determinants among Students: A Structural Equation Modeling Analysis” to your journal. We have read the comments carefully and we were able to implement all of them (see the manuscript with track changes). While reading the manuscript critically, we spotted English grammar errors, which we corrected. We hope that our revision will be felt like an improvement. Furthermore, we assessed our reference list for retracted papers and we didn’t cite any retracted article. Thank you!

Response to reviewers and editors

1) Suggestion to improve paper’s structure:

I suggest removing the first paragraph that introduces Covid-19. I find it to be too medically focused. There is no need to speculate on the origins of the virus (particularly since it is not established definitively) since it is irrelevant for the purpose of this paper. Alternatively, authors could replace medical wording with simple reference to Covid-19 pandemic. Everyone knows and understands what this is.

I would suggest instead to incorporate some of the already established early research studies on negative effects of Covid-19 as applicable to either the same settings (such as educational environment), or the same demographics (such as kids). For example, the following paper summarizes the up-to-date research finding based on kids at-home eating habits during Covid:

“The Janus-faced effects of COVID-19 perceptions on family healthy eating behavior: Parent’s negative experience as a mediator and gender as a moderator” by Ali B. Mahmoud, Dieu Hack-Polay, Leonora Fuxman, Maria Nicoletti https://onlinelibrary.wiley.com/doi/10.1111/sjop.12742

Giving the reader the summary of findings about Covid related impacts within similar context would present a better introductory background to the current study.

Response: Correction has been made accordingly (See line 67-82 on page 4 in the manuscript).

2) I suggest deleting the entire section “Study Period and Setting”. The only immediately relevant information in this section are the dates of the study, which authors can easily incorporate into the next section.

Response: Correction has been made accordingly (See line 156-165 at page 5 in the revised manuscript with track changes).

This revision is an improved one. The paper needs detailed proof reading to reconcile English discrepancies. Please see my suggested modifications in the attached file.

Response: Thank you for taking time to review our work for the language details. Proofreading and language review have been made throughout the manuscript (See the revised manuscript with a track change).

3) Here are some suggestions to correct language throughout the manuscript

Line 73: remove end of sentence punctuation (See line 69-70 on page 4 in the manuscript).

Response: Correction has been made accordingly

Lines 75-78 (third paragraph): I don’t see the need to re-state mortality statistics as those do change rather quickly and are widely accessible online. This paper is about students in University setting and as such the focus of the introduction should be on the specifics of the environment under consideration.

Line 88-89: grammar correction : “more than 94% of students were following the recommended preventive health behaviors in Iran

Response: Correction has been made accordingly (See line 93-94 on page 5 in the manuscript).

Line 106: correct punctuation – remove “; ”

Response: Correction has been made accordingly (See line 112 on page 6 in the manuscript).

Line 116: grammar correction – “The HBM is one of the various health behavior models that has been…”

Response: Correction has been made accordingly (See line 122 on page 6 in the manuscript).

Lie 127: replace “study area” with academia.

Response: Correction has been made accordingly (See line 134 on page 7 in the manuscript).

Line 136: replace “administration” with administered.

Response: Correction has been made accordingly

Line 147: replace “refers” with refer.

Response: Correction has been made accordingly (See line 145 on page 7 in the manuscript).

Line 151: and/or

Response: Correction has been made accordingly (See line 149 on page 7 in the manuscript).

Line 156: capitalize the title of the journal

Response: Correction has been made accordingly (See line 153 on page 7 in the manuscript).

Line 162: replace punctuation “;” with :

Response: Correction has been made accordingly (See line 159 on page 8 in the manuscript).

Line 163: coma needed ” … variable (0.43),”

Response: Correction has been made accordingly (See line 160 on page 8 in the manuscript).

Line 167: “governmental schools, which resulted…”

Response: Correction has been made accordingly (See line 164 on page 8 in the manuscript).

Line 188: replace punctuation “;” with :

Response: Correction has been made accordingly (See line 183 on page 9 in the manuscript).

Line 190: insert “is resource efficient”

Response: Correction has been made accordingly (See line 185 on page 9 in the manuscript).

Line 235: delete coma - “practice concerning handwashing, …”

Response: Correction has been made accordingly (See line 235 on page 11 in the manuscript).

Line 244: add coma – “cleaning, coding…”

Response: Correction has been made accordingly (See line 239 on page 11 in the manuscript).

Line 262: insert “ produce precise estimate with smaller…”

Response: Correction has been made accordingly (See line 257 on page 12 in the manuscript).

Line 276: add coma – “perceived benefit, perceived barrier…”

Response: Correction has been made accordingly (See line 271 on page 13 in the manuscript).

Lin 301: add reference for Declaration of Helsinki.

Response: The reference has been added ((See line 296 on page 14 in the manuscript).

Line 312: replace “kept” with keep for grammatical consistency.

Response: Correction has been made accordingly (See line 307 on page 16 in the manuscript).

Line 324: correct - “…scores were higher than the neutral score…”

Response: Correction has been made accordingly (See line 319 on page 18 in the manuscript).

Line 337: add coma and lower case – “perceived severity (r = 0.2, p < 0.05), perceived benefit…”

Response: Correction has been made accordingly (See line 332 on page 18 in the manuscript).

All statistical techniques, new and old, should have reference. For example, line 336 and 365

Response: Correction has been made accordingly (See line 331 and 361 on page 18 and 361 in the manuscript, respectively).

Line 407-408: poor choice of wording “These results are results lower than the result reported by various previous studies…” Please rewrite this sentence

Response: Correction has been made accordingly (See line 402-403 on page 24 in the manuscript).

Line 420: lower case “perceived barriers”

Response: Correction has been made accordingly (See line 415 on page 25 in the manuscript).

Line 437: “…studies that were done using the health belief model…”

Response: Correction has been made accordingly (See line 432 on page 25 in the manuscript).

Line 440: use abbreviation HBM instead of health belief model.

Response: Correction has been made accordingly (See line 435 on page 25 in the manuscript).

Line 446: remove “is” or add our results “… the results are consistent…”

Response: Correction has been made accordingly (See line 441 on page 26 in the manuscript).

Line 449: replace punctuation “;” with:

Response: Correction has been made accordingly (See line 444 on page 26 in the manuscript).

Line 457: capitalize the name of the model to keep consistent “Health Belief Model”

Response: Correction has been made accordingly (See line 452 on page 26 in the manuscript).

Submitted filename: Response to edditor and reviewers.docx

Click here for additional data file.

24 Jan 2022

Application of Health Belief Model for the Assessment of COVID-19 Preventive Behavior and its Determinants among Students: A Structural Equation Modeling Analysis

PONE-D-21-05732R3

Dear Dr. Shitu,

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. Please, ensure the final version of your manuscript addresses the minor syntax edits suggested by Reviewer 3 and has undergone top-down proofreading.

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 B. Mahmoud, Ph.D.

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 #3: 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 #3: Yes

**********

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

Reviewer #3: 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 #3: 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 #3: 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 #3: please make corrections in lines:

73: "Schools"– sentence case

147: what is “after home checkups”?

201: extra parenthesis

**********

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 #3: No

11 Mar 2022

PONE-D-21-05732R3

Application of Health Belief Model for the Assessment of COVID-19 Preventive Behavior and its Determinants among Students: A Structural Equation Modeling Analysis

Dear Dr. Shitu:

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

Dr. Ali B. Mahmoud

Academic Editor

PLOS ONE