Determining the Cutoff Points of the 5C Scale for Assessment of COVID-19 Vaccines Psychological Antecedents among the Arab Population: A Multinational Study

Abstract

Background

One of the newly faced challenges during the COVID-19 is vaccine hesitancy (VH). The validated 5C scale, that assesses 5 psychological antecedents of vaccination, could be effective in exploring COVID-19 VH. This study aimed to determine a statistically valid cutoff points for the 5C sub-scales among the Arab population.

Methods

A cross-sectional study was conducted among 446 subjects from 3 Arab countries (Egypt, United Arab Emirates (UAE), and Jordan). Information regarding sociodemographics, clinical history, COVID-19 infection and vaccination history, and 5C scale were collected online. The 5C scores were analyzed to define the cutoff points using the receiver operating characteristic curve (ROC) and to verify the capability of the questionnaire to differentiate whether responders are hesitant or non-hesitant to accept vaccination. ROC curve analysis was conducted for previous vaccine administration as a response, with the predictors being the main 5 domains of the 5C questionnaire. The mean score of each sub-scale was compared with COVID-19 vaccine intake.

Results

The mean age of the studied population was 37 ± 11, 42.9% were males, 44.8% from Egypt, 21.1% from Jordan, and 33.6% from the UAE. Statistically significant differences between vaccinated and unvaccinated participants, respectively, were detected in the median score of confidence [6.0(1.3) versus 4.7(2.0)], complacency [(2.7(2.0) versus 3.0(2.0)], constraints [1.7(1.7) versus 3.7(2.3)], and collective responsibility [6.7(1.7) versus 5.7(1.7)]. The area under the curve of the 5 scales was 0.72, 0.60, 0.76, 0.66, 0.66 for confidence, complacency, constraints, calculation, and collective responsibility at cutoff values of 5.7, 4.7, 6.0, 6.3, and 6.2, respectively.

Conclusion

The Arabic validated version of the 5C scale has a good discriminatory power to predict COVID-19 vaccines antecedent.

Keywords

Arab COVID-19 psychological antecedents vaccine hesitancy 5C AUC ROC SARS-CoV-2

Introduction

More than 146 million people have been affected by the 2019 coronavirus disease (COVID-19), with about 3.1 million worldwide deaths.¹ Disease containment measures should be continued until herd immunity is achieved and COVID-19 can no longer circulate. Herd immunity is acquired if at least 60% of the population are vaccinated or get infected. As an emergency response to contain the pandemic and its related burden(s), non-pharmaceutical intervention measures were globally implemented. These included physical distancing and curfews.^2,3 Mass vaccination could be the only way to build herd immunity and reduce disease burden(s).⁴ With the recent introduction of several effective vaccinations, many countries scheduled mass immunization programs utilizing most emergency-approved vaccines.^4,5

Currently, about 13 vaccines have been approved and licensed for general use.⁶ Many Arab countries caught up with the global community importing and rolling out vaccines among its populations. The United Arab of Emirates (UAE) was among the first countries to roll out vaccines with priority for the elderly, frontline workers, and patients with chronic diseases. Egypt and Jordan have begun COVID-19 vaccination among health care workers and launched a governmental website for registration. On March 26, more than 78% of the targeted population living in UAE received at least a single dose, while more 7% of Jordanians were vaccinated.⁷ The difference in percentages between 3 aforementioned countries could be due to the time difference in starting vaccination campaigns but, most importantly, due to hesitancy toward vaccination. Vaccine Hesitancy (VH) and reluctance among people in these countries and around the word is incited by lots of misinformation and dis-information circulating about vaccine side effects, lack of trust, and conspiracy theories.⁸ Accordingly, exploring the prevalence of VH and its determinants is crucial using culturally adapted tools that can distinguish between hesitant and non-hesitant populations.

COVID-19 VH is part of a long-standing debate about vaccination dynamics. VH was declared as a global health,⁹ and, with the emergence of the pandemic, it is taking a toll and seems to persist as a global problem.¹⁰ VH simply refers to a person’s refusal, or hesitation, to be vaccinated or to have their children vaccinated against a disease, even though the vaccine has been shown to be safe and efficient.¹¹ VH raises concerns at the individual and community levels as exposure to an infectious disease increases the risk of disease transmission among the community where effective vaccination programs are not established.¹² COVID-19 infodemic has impacted people’s perceptions and trust with offered vaccines leading to an increase in VH even among different groups who were never known to be hesitant toward any vaccination. Moreover, intention to vaccinate is argued to be higher than the actual vaccination uptake in some countries, hence, it is essential to identify risks, intentions, and antecedents to vaccination.¹³

Previous models^11,14 were proposed to synthesize and expand on VH by measuring the 5 psychological antecedents of vaccination. An antecedent is a psychological cause or determinant inside an individual that influences whether or not a person gets vaccinated. Confidence, complacency, constraints, calculation, and collective responsibility are the 5 sub-scales of this tool. The 5C scale evaluates 5 psychological antecedents to vaccination and offers insight into human mental representations, attitudes, and behavioral patterns that are influenced by the respondent’s environment and background.¹⁵ Evidence from few Arabic countries demonstrated the existence of COVID-19 VH.¹⁶ With the emergence of COVID-19 and the distribution and manufacturing of the vaccine, the need to explore the existing resistance and potential hesitancy utilizing validated tools seems eminent.

To the best of the authors’ knowledge, no study has addressed the cutoff values for COVID-19 psychological antecedents (confidence, complacency, constraints, calculation, and collective responsibility) using the 5C scale. Estimating such cutoff points will provide insights into the COVID-19 vaccination-related individual and psychological antecedents and will help in identifying important predictors of COVID-19 vaccination intention and behavior. In this research, we aimed at identifying the cutoff point for each of the 5C sub-scale to be used in determining the psychological antecedent of the COVID-19 vaccine among the Arab population.

Methods

The data for this study were derived from a preexisting cross-sectional study conducted from January to March, 2021 to assess the prevalence of psychological antecedents for COVID-19 vaccines among the general population in the Arab world. Based on the assumptions of AUC = 0.5 for the null hypothesis and AUC =v0.6 for the alternative hypothesis, allocation ratio between vaccinated and non-vaccinated population was estimated to be 1 to 2, power = 0.80, and α = 0.05, the minimum sample size required was estimated at 219 participants using MedCalc software application (version 19.6.3). We duplicated the sample size to allow for the comparative analysis and to compensate potential missing data.

The questionnaire was composed of 3 sections. The first section collects data on sociodemographic: age, sex, education, marital status, occupation (health care worker or not), and comorbidities (asthma, diabetes mellitus, hypertension, ischemic heart diseases). The second section included questions on COVID-19 infection: history of previous COVID-19 infection, family history of COVID-19 infection, mortality among relatives due to COVID-19, history of vaccination against influenza, knowledge about different types of COVID-19 vaccine, and searching the web for information about COVID-19 vaccine. The third section is the validated Arabic 5C questionnaire, which is composed of 15 questions covering 5 main domains or subscales: confidence (Q1-Q3), complacency (Q4-Q6), constraints (Q7-Q9), calculation (Q10-Q12), and collective responsibility (Q13-Q15).

The results are presented as means and standard deviations (SD) in case of normally distributed data, median and interquartile range (IQR) for non-normally distributed data, or as percentages for categorical data. Continuous variables were compared using t-test or Mann-Whitney test while chi-square was used to compare categorical variables.

The cutoff points for the different subscales of the Arabic version of the 5C questionnaire were determined using the receiver operating characteristic curve (ROC) based on the self-report of receiving COVID-19 vaccines. Responses to the question “history of COVID-19 vaccine intake” was coded as a binary variable (“not vaccinated” and “vaccinated”), to distinguish between individuals who received and those who did not receive the vaccine. The ROC curve is a graphical plot of sensitivity against 1—specificity at various discrimination cutoff points. The best cutoff point is the one that represents the best compromise between sensitivity and specificity. It will be identified using the Youden index.

The study was approved by the Ethics Committee of the Faculty of Medicine/Alexandria University/Egypt (00012098). All research activities were in accordance with the International Ethical Guidelines for Epidemiological studies.¹⁷ Participants were consented online before taking the survey.

Results

A total of 460 participants participated in the study. Of which, 14 were excluded due to missing data (more than 20%). Of the total 446 participants included in the analysis (Table 1), 27.6% reported a history of COVID-19 vaccine intake. The mean ± SD age was 37 ± 11 years, 42.9% were males, 67% were married, 44.8% from Egypt, 33.6% from UAE, 40.3% had a university degree, and 35.4% were healthcare workers. More than half (63%) of participants reported a history of chronic comorbidities, 27.8% got infected with COVID-19, 35.2% gave family history of COVID-19 infection, and 21.8% had influenza vaccine, and 72.9% were aware of availability of several vaccines.

Table 1.

Participants’ Demographics and Clinical Characteristics.

Sociodemographic criteria	Total (n = 446)	Vaccinated (n = 119)	Unvaccinated (n = 327)	P-value
Gender				<.001
Male	191 (42.9)	43 (36.8)	148 (45.3)
Female	255 (57.1)	76 (64.8)	179 (45.7)
Age, mean ± SD	36.76 ± 10.84	36.63 ± 10.41	36.81 ± 11.00	.89
Country				<.001
Egypt	200 (44.8)	15 (12.6)	185 (56.6)
Jordan	94 (21.1)	7 (5.8)	87 (26.6)
UAE	150 (33.6)	97 (81.5)	53 (16.2)
Education				<.001
Pre university	21 (4.7)	12 (10.1)	9 (2.8)
Technical/vocational	23 (5.2)	5 (4.2)	18 (5.5)
University degree	179 (40.13)	52 (43.7)	127 (39)
Postgraduate degree	169 (37.9)	49 (41.2)	120 (36.7)
Others	54 (12.1)	1 (0.8)	53 (16.2)
Marital status				.07
Single	101 (22.7)	31 (26.1)	70 (21.4)
Married	301 (67.5)	82 (68.9)	219 (67.0)
Divorced	28 (6.3)	6 (5.0)	22 (6.7)
Widow	16 (3.6)	0 (0)	16 (4.9)
Healthcare workers	158 (35.4)	58 (48.7)	90 (27.5)	<.001
Chronic comorbidities	282 (63%)	31 (26.1)	251 (76.8)	<.001
Responders getting yearly Influenza vaccination	97 (21.8)	17 (41.5)	80 (24.5)	.02
History of COVID-19 infection				.03
Yes	123 (27.6)	25 (21)	98 (30)
No	159 (60.3)	84 (70.6)	185 (56.6)
Do not know	54 (12.1)	10 (8.4)	44 (13.5)
Family history of COVID-19 infection				.27
Yes	157 (35.2)	59 (49.6)	139 (42.5)
No	240 (53.8)	55 (46.2)	161 (49.2)
Do not know	499 (11.0)	5 (4.2)	27 (8.3)
Family history of death due to COVID-19 infection				<.001
Yes	143 (32.1)	31 (26.1)	112 (34.3)
No	252 (56.5)	85 (71.4)	167 (51.1)
Do not know	51 (11.3)	3 (2.5)	48 (14.7)
knowledge about the availability of different vaccines (yes)	325 (72.9)	112 (94.1)	213 (65.1)	<.001
History of COVID-19 infection after vaccination among family and friends (yes)	48 (10.8)	40 (33.9)	8 (8.2)	<.001
knowledge about the indications and contraindications for different types of COVID-19 vaccines	123 (27.6)	97 (82.2)	26 (26.8)	<.001
knowledge about the different information related to COVID-19 vaccine through searching the web	133 (29.8)	83 (70.3)	50 (51.5)	<.001

Participants who reported receiving the COVID-19 vaccine were mainly females (57.1% vs 42.9%), aged 36.63 ± 10.41, from UAE (64.7%), had achieved higher education (41.2% vs 36.7%), healthcare workers (48.7% vs 27.5%), did not report a history of chronic conditions (73.9 vs 23.2%), reported a history of receiving influenza vaccine yearly (41.5% vs 24.5%), did not contract COVID-19 infection (70.3% vs 56.6%), did not give a family history of COVID-19 related deaths (71.4% vs 51.1%), knew about the presence of different types of COVID-19 vaccine (82.2% vs 26.8%), and searched the web for more information about COVID-19 (70.3% vs 51.5%).

The median and IQR were calculated for each question and sub-scale. The estimated median (IQR) values for confidence (5.0(2.0)), complacency (3.0(2.0)), constrains (3.0(2.67)), calculation (6.0(1.33)), and collective responsibility (5.66(1.67)) are presented in Table 2. The median score of each items was significantly different between vaccinated and unvaccinated except for questions 5 and 12. There was a statistically significant difference between vaccinated and unvaccinated, respectively, in the median scores of confidence [6.0(1.3) versus 4.7(2.0)], complacency [(2.7(2.0) versus 3.0(2.0)], constraints [1.7(1.7) versus 3.7(2.3)], and collective responsibility [6.7(1.7) versus 5.7(1.7)].

Table 2.

Median and IQR of the 5C Subscales in Arabic Version.

The subscale	Total	Vaccinated (n = 119)	Unvaccinated (n = 327)	P -value
Confidence	5.0 (2.0)	6.0 (1.3)	4.66 (1.7)	<.001
Q1: I am completely confident that vaccines are safe	5.0 (2.0)	6.0 (3.0)	5.0 (2.0)
Q2: Vaccinations are effective	5.0 (2.0)	6.0 (2.0)	5.0 (2.0)
Q3: Regarding vaccines, I am confident that public authorities decide in the best interest of the community	5.0 (2.0)	7.0 (1.0)	5.0 (3.0)
Complacency	3.0 (2.0)	2.7 (2.0)	3.0 (2.0)	<.001
Q4: Vaccination is unnecessary because vaccine-preventable diseases are not common anymore	2.0 (3.0)	1.0 (2.0)	3.0 (3.0)
Q5: My immune system is so strong; it also protects me against diseases	3.0 (3.0)	4.0 (3.0)	3.0 (3.0)
Q6: Vaccine-preventable diseases are not so severe that I should be vaccinated	3.0 (3.0)	1.0 (2.0)	3.0 (3.0)
Constrains	3.0 (2.67)	1.7 (1.7)	3.7 (2.3)	<.001
Q7: Everyday stress prevents me from being vaccinated	3.0 (3.0)	2.0 (2.0)	3.0 (3.0)
Q8: For me, it is inconvenient to be vaccinated	3.0 (4.0)	1.0 (1.0)	4.0 (3.0)
Q9: Visiting the doctor makes me feel uncomfortable; this keeps me from being vaccinated	3.0 (3.0)	1.0 (1.0)	3.0 (3.0)
Calculation	6.0 (1.33)	6.00 (2.0)	6.00 (1.3)	.321
Q10: When I think about being vaccinated, I weigh its benefits and risks to make the best decision possible	6.0 (2.0)	6.0 (3.0)	6.0 (2.0)
Q11: For each and every vaccination, I closely consider whether it is useful for me	6.0 (2.0)	6.0 (2.0)	6.0 (2.0)
Q12: It is important for me to fully understand the topic of vaccination before I get vaccinated	7.0 (1.25)	7.0 (2.0)	7.0 (2.0)
Collective responsibility	5.6 (1.6)	6.7 (1.7)	5.7 (1.7)	<.001
Q13: When everyone else is vaccinated, I don’t have to be vaccinated, too.	5.0 (3.0)	7.0 (2.0)	5.0 (3.0)
Q14: I get vaccinated because I can also protect people with a weaker immune system	6.0 (2.0)	7.0 (1.0)	6.0 (2.0)
Q15: Vaccination is a collective action to prevent the spread of diseases	7.0 (2.0)	7.0 (1.0)	7.0 (2.0)

Table 3 showed the cutoff points of the different sub-scales. The cutoff points were based on responses to the question “Did you get the COVID-19 vaccine?.” One cutoff point was identified from ROC analysis for each subscale. Some responses were reverse-coded and higher scale values indicate a positive (favorable) response. These cutoff points were used to classify respondents into:

Table 3.

The Cutoff Values, Sensitivity, and Specificity of the 5C Subscales.

Subscale	Cutoff points	AUC (95% CI)	Sensitivity (95% CI)	Specificity (95% CI)
Confidence	5.7	0.72 (0.65-0.78)	0.68 (0.59-0.76)	0.71 (0.65-0.77)
Complacency	4.7	0.59 (0.53-0.66)	0.74 (0.65-0.82)	0.41 (0.35-0.47)
Constraints	6.0	0.76 (0.71-0.81)	0.70 (0.61-0.78)	0.75 (0.69-0.81)
Calculation	6.3	0.66 (0.60-0.72)	0.61 (0.51-0.61)	0.64 (0.58-0.73)
Collective responsibility	6.2	0.66 (0.59-0.72)	0.61 (0.51-0.69)	0.66 (0.60-0.72)

Abbreviations: AUC, area under the curve; CI, confidence intervals.

Not confident: when confidence subscale score was <5.6, and confident when subscale score was ≥5.6.

Not complacent: when complacency score was <4.7, and complacent when subscale score was ≥4.7.

Did not have constraints against COVID-19 vaccine when the subscale score was <6.0, and had constraints when the sub-scale score was ≥6.0.

Did not assess different calculation for receiving COVID-19 vaccine when the sub-scale score was <6.3, and assessed calculation when the subscale score was ≥6.3.

Lacking (absence of) collective responsibility when the sub-score was <6.2, and having (feeling) collective responsibility when the subscale score was ≥6.2.

Discussion

With the fast pace of COVID-19, researchers are becoming dependent on universal scales without evidence of effectiveness and efficacy within local population subgroups. This is critical as VH, being a global public health issue, needs addressing for better controlling COVID-19 spread. This research was conducted to estimate a cutoff point at which each of the 5C domains can be assessed negatively or positively toward the COVID-19 vaccine’s attitude and behavior. Results indicated valuable cutoff points for which each domain could be utilized using proper test characteristics measures. As such, utilizing the Arabic version of the questionnaire is an asset as it discriminates against COVID-19 hesitancy utilizing a set of validated questions.

Developers of the 5C scale did not report clear cutoff points for its domains but rather recommended each implementer estimates cutoff point of each sub-scale according to the study context.¹⁵ As it is clear from the stated definitions of the 5 subscales no umbrella concept embraces all antecedents. Thus, our results support the notion that calculating a uniform total score across all antecedents is not actually practical and that the sub-domains are of better use for presenting the dimensions of the scale. One of the major advantages of 5C scale is that it can assess the 5 antecedents is to explain vaccination behavior and to assess the need for interventional programs. Once such hesitancy is explored, the role of intervention to improve vaccine acceptance is easily established and properly formulated.¹⁸

No previous study tried to estimate the cutoff points for the 5C sub-scale. However, the 5C psychological antecedent sub-scales were associated with different outcome variables to assess vaccination antecedent among different population for different vaccines. Kowk et al¹⁹ used the 5C scale to explore the intension to receive COVID-19 vaccine and correlated it with influenza vaccination among health care workers in Hong Kong. COVID-19 vaccination intention was associated with higher confidence and collective responsibility scores, and lower complacency score. Barriers against vaccination were investigated against the 5C to assess the psychological antecedents among German family physicians toward hepatitis B, Influenza, and pertussis vaccines. It was concluded that increased confidence in vaccine was associated with vaccination and recommending vaccine for others. Complacency, constrains, and collective responsibility were associated with own vaccination.²⁰ Eitze et al²¹ used the 5C psychological antecedent to measure response to vaccination before and after implementation of an interventional program on influenza and pneumococcal infection. Of interest is the fact that all previously stated studies have utilized the 5C sub-scales as a continuous variable and did not attempt to identify a cutoff point for each domain. This adds value to our results as they clearly tried to categorize participants into hesitant or not using each of the cutoff points estimated for each domain. These estimates were provided with good sensitivity and specificity. These estimates are helpful when designing vaccination campaigns.

It is worth noting that one of the benefits of the 5C scale is its ability to detect early warning signs of VH, consequently, guiding policymakers and stakeholders to provide evidence-based public health programs. The scale can be considered an effective tool in the fight against COVID-19 considering that effective non-pharmaceutical interventions are creating serious burdens on mental health status at the global level. Assessing and addressing VH using tested cutoff point among Arab populations is necessary and, given our results, more appropriate. The testing characteristics reported in the current study will be useful for future public health surveys that measure and explore COVID-19 VH. Determining the cutoff point will be highly useful in identifying populations with higher hesitancy, hence, interventions could be easily directed toward them. Moreover, the result of this study will help in directing resources toward clear targets allowing for more effective VH interventions.

Our results indicated that a higher proportion of those who reported that they were not vaccinated had at least one chronic disease. We speculate that this category’s refusal or hesitancy to get vaccinated may be due to the fear of the vaccine side effects that may extend beyond his fear from the infection itself and, possibly, due to the poor awareness about the need to get vaccinated being a vulnerable group. Another issue to be noticed was that a higher proportion of vaccinated participants have had relatives who were infected with COVID-19 even after being vaccinated. Although there was a higher presentation of health care workers among the vaccinated participants, we expect that they may receive the vaccine in the near future even after their colleagues and friends got the infection based on the WHO, Centers for Diseases Prevention and Control (CDC) and local public health department’s recommendations.²²

Responses to the 5C scale determine what respondents think and feel about COVID-19 vaccines and being vaccinated. In this work, the cutoff point of the confidence scale was estimated at 5.7. Indicating that if the median score of the 3 items of this domain exceeded 5.7, then the respondent is more likely to be trusting the efficacy and safety of the vaccine, the system of vaccine delivery, and the policymakers. For the complacency, if subjects scored above 4.7, then they probably thinks that vaccine is not necessary to prevent COVID-19 infection. In fact, a higher complacency score donates a lower perceived risk of COVID-19 diseases. Risk perception is a critical point to define when dealing with COVID-19 vaccination and for the development of proper communication messages that engage the general population against improper risk perception.

For constraints, higher values indicate poor access to health services and weak perception of self-efficacy and behavioral control. The structural and psychological barriers (access, a lack of self-control) are “gate-keepers” against impeding the implementation of vaccination intentions into behavior. Travel time or inconvenient procedures may also act as barriers. Perceiving constraints should therefore be related to a lack of perceived behavioral control.²³ For calculation, individuals with a score above 6.3 indicate higher perceived risk of COVID-19 infection. This donates that individuals weighted the risk of infection to that of vaccination. Depending on the information sources that are used, a high calculation can lead to non-vaccination due to the high availability of anti-vaccination sources, for instance, on the internet.²⁴ COVID-19 infodemic, therefore, could play a significant role in this item. Information shared over social media platforms is critical in defining this domain and should be considered when responses are higher than expected.

Collective responsibility, which determines respondent’s behavior toward protecting others through self-vaccination. The respondent feels that he can protect others from contracting infection when they become vaccinated as it enhances herd immunity. A higher collective responsibility score usually correlates with empathy and collectivism of the respondents, while a lower score donates that the respondent doesn’t care about others and doesn’t know enough about herd immunity.²⁵ Social responsibility is a critical point to consider when dealing with COVID-19 vaccination hesitancy as it shows how responsible each individual to his community, the elderly, and those at higher risk. This domain deals with protective factors at the community levels as it may reflect how people behave during social gatherings.

This is the first study that identifies a threshold for the 5C among Arabs. Due to time restrictions, this survey was conducted only in 3 different Arab countries where vaccine delivery already started. Therefore, generalizability to all Arab states may be limited. This survey was conducted using an online, which further limits generalizability. Still, pandemic restrictions and limitations did not facilitate better sampling. When feasible, future research should focus on a random sample to further validate the results.

Conclusion

The results suggest that the Arabic validated version of the 5C subscales have a good discriminatory power to predict COVID-19 vaccines psychological antecedent and provided valuable cutoff points for the 5C subscales; namely confidence, complacency, constraints, calculation, and collective responsibility. Each subscale had proper test characteristics measures. Utilizing the Arabic version of the questionnaire is an asset as it discriminates against COVID-19 hesitancy utilizing a set of validated measures. Future research should utilize these cutoff points to dichotomize research participants by each subscale to better understand their COVID-19 hesitancy attributes.

Footnotes

Acknowledgements

Many thanks to all study participants and staff from participating universities who assisted in the conduct of this study.

Author Contribution

RG, SA, RS conceptualized the study idea, designed the survey tools, assisted in data collection, and composed the initial manuscript draft. AR performed the statistical analysis, data interpretation, and visualization and participated in manuscript writing up. KK assisted in data collection, interpretation, and visualization, edited the initial manuscript. IE assisted in data collection, reviewing, and editing the manuscript. MS assisted in data collection and reviewing the manuscript.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Ramy Mohamed Ghazy

Khalid A. Kheirallah

Data Availability

Data are available upon request by mailing the first author.

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