Literature DB >> 33122922

Predictors of Coronavirus Disease 2019 (COVID-19) Prevention Practices Using Health Belief Model Among Employees in Addis Ababa, Ethiopia, 2020.

Trhas Tadesse1, Tadesse Alemu2, Getasew Amogne3, Getabalew Endazenaw1, Ephrem Mamo1.   

Abstract

BACKGROUND: Ethiopia has taken strict preventive measures against COVID-19 to control its spread, to protect citizens, and ensure their wellbeing. Employee's adherence to preventive measures is influenced by their knowledge, perceived susceptibility, severity, benefit, barrier, cues to action, and self-efficacy. Therefore, this study investigated the predictors of COVID-19 prevention practice using the Health Belief Model among employees in Addis Ababa, Ethiopia, 2020.
METHODS: Multicentre cross-sectional study design was used. A total of 628 employees selected by systematic sampling method were included in this study. Data were collected using a pretested self-administered questionnaire. Summary statistics of a given data for each variable were calculated. Logistic regression model was used to measure the association between the outcome and the predictor variable. Statistical significance was declared at p-value<0.05. Direction and strength of association were expressed using OR and 95% CI.
RESULTS: From a total of 628 respondents, 432 (68.8%) of them had poor COVID-19 prevention practice. Three hundred ninety-one (62.3%), 337 (53.7%), 312 (49.7), 497 (79.1%), 303 (48.2%) and 299 (52.4%) of the respondents had high perceived susceptibility, severity, benefit, barrier, cues to action and self-efficacy to COVID-19 prevention practice, respectively. Employees with a low level of perceived barriers were less likely to have a poor practice of COVID-19 prevention compared to employees with a high level of perceived barrier [AOR = 0.03, 95% CI (0.01,0.05)]. Similarly, employees with low cues to action and employees with a low level of self-efficacy were practiced COVID prevention measures to a lesser extent compared those with high cues to action and high level of self-efficacy [AOR = 0.05, 95% CI (0.026,0.10)] and [AOR = 0.08, 95% CI (0.04,0.14)], respectively.
CONCLUSION: The proportion of employees with poor COVID-19 prevention was high. Income, perceived barrier, cues to action, and self-efficacy were significantly associated with COVID-19 prevention practice.
© 2020 Tadesse et al.

Entities:  

Keywords:  COVID-19; Health Belief Model; employees; predictor

Year:  2020        PMID: 33122922      PMCID: PMC7588498          DOI: 10.2147/IDR.S275933

Source DB:  PubMed          Journal:  Infect Drug Resist        ISSN: 1178-6973            Impact factor:   4.003


Introduction

The globe is facing an extremely bizarre time struggling to fight an enemy it never saw before; the novel coronavirus disease (COVID)-19. SARS-CoV-2 or COVID-19 was first reported in December 2019, as a cluster of acute respiratory illness in Wuhan (pneumonia of unknown cause), Hubei Province, China, from where it spread rapidly around the globe involving more than 190 countries. The World Health Organization (WHO) declared the outbreak a Public Health Emergency of International Concern (PHEIC) on 30 January 2020 and a global pandemic on 11 March 2020.1,2 As of 22 April 2020, more than 2.57 million cases have been reported across 185 countries and territories, resulting in more than 178,558 deaths. About three-fourth (701,838) the people with COVID-19 have recovered while about 52, 262 of them are in a serious or critical condition.3,4 There are now more than 24,600 confirmed cases of coronavirus infection across the continent Africa, resulting in more than 1190 mortalities. Similarly, about 116 cases and 3 death of COVID-19 are reported in Ethiopia as of 22 April 2020.5 COVID-19 causes a range of respiratory symptoms including fever, fatigue, dry cough, and difficulty of breathing. It may result in serious complications like ARDS and death especially among elderly patients and patients with underlying medical conditions like heart disease, diabetes, hypertension, and asthma. A study done in China shows those patients with a severe form of COVID 9 developed ARDS and required ICU admission and oxygen therapy. At this stage of the diseases, the mortality rate is high (15%).6,7 For five decades, the Health Belief Model (HBM) has been one of the most widely used conceptual frameworks in health behavior. The HBM has been used both to explain change and maintenance of health-related behaviors and as a guiding framework for health behavior intervention.8 It is now believed that people will take action to prevent or control ill-health conditions like COVID-19 if they regard themselves as susceptible to the COVID-19; if they believe it would have potentially serious consequences; if they believe that a course of action like stay home, keep social distance, wear face mask, etc available to them would help reduce either their susceptibility to the disease or the severity of the condition; and if they think that the likely barriers (or cost) of taking the actions outweighed by its benefits.9 Given that health motivation is it’s a central focus, the Health Belief Model is an ideal option for addressing behavioral problems that evoke health concerns. The model has been tested repeatedly in western countries that it fits best for health behavior change studies as well as a planning model together with other health education and planning models, such as the PRECEDE–PROCEDE model. To date, a vaccine and effective treatment are not available for COVID-19. In a situation like this, basic hygiene principles and aggressive public health measures are virtually important for preventing the spread of the disease and hence reducing its impact in the community. Therefore, this study was aimed at assessing predictors of COVID-19 prevention practice among Higher Education employees in Addis Ababa Ethiopia using a Health Belief Model.

Methods and Materials

Study Area and Period

The study was conducted to determine the predictors of COVID-19 prevention practice among employees working in Addis, Ethiopia, May 2020. Addis Ababa is the capital city of Ethiopia with a population of around 4.7 million. Addis Ababa has 109 administrative sub-cities and a total of 99 Kebeles. The study was done among employees selected from four organizations in Addis Ababa (Ethiopian Airlines, Commercial Bank of Ethiopia, Black Lion Hospital, and Ethiopian Telecommunication Corporation). The study was done from May to June 2020.

Study Design

A multicentered cross-sectional study design was used to assess predictors of COVID-19 prevention practices using a Health Belief Model among employees in Addis Ababa, Ethiopia, 2020.

Inclusion and Exclusion Criteria

Employees from the four stated organizations and who are willing to participate were included in this study. Employees with hearing and visual impairment were excluded from this study.

Sample Size

The sample size for the study was calculated using a single proportion formula by assuming 95% CL, 4% marginal error, and 50% proportion of COVID-19 prevention practice. Therefore, by adding a 10% non-response rate, the final sample size for this study was 628.

Sampling Method

The sample size was proportionally allocated to each of the four organizations. Then, a systematic sampling method was used to select the study participants from each of the four organizations. According to the available data during the study period, a total of 4396 active workers were available in the four selected organizations in Addis Ababa. Hence, by dividing the total active employees during the study period (4396) with the total sample size (628), (N/n), the sampling interval (K) of 7 was obtained. The first employee was selected at random from each organization and consecutive participants were selected every seventh employee. Participants were approached in their working area.

Variables

COVID-19 prevention practice was the dependent variable. Demographic variables, knowledge about COVID-19, and the HBM constructs (perceived susceptibility, perceived severity, perceived benefit, perceived barrier, cues to action, and self-efficacy) were the independent variables.

Data Collection Method and Instrument

The questionnaire was developed by reviewing previous different literature conducted on prevention practice of COVID-19 and in consultation with experts from different fields to check the relevance and make necessary changes according to the study requirements. The questions were modified according to the suggestions received from the expert panel and output from the pre-test. Guidelines for layout, question design, formatting, and pretesting testing were followed. The questionnaire was used to gather employees’ demographic data, knowledge about COVID-19 and its prevention, Health Belief Model constructs (perceived susceptibility, perceived severity, perceived benefit, perceived barrier, and cues to action self-efficacy), and practice of COVID-19 prevention.

Data Analysis

SPSS version 23 computer software package was used to analyze the data. The collected data were entered into SPSS and data cleaning was undertaken before data analysis. Summary statistics like frequency, percent, mean, and standard deviation of a given data for each variable were calculated. A logistic regression model was used to measure the association between the outcome (COVID-19 prevention practice) and the predictor variables (socio-demographic variables, knowledge, and the HBM constructs). Statistical significance was declared at p-value<0.05. Direction and strength of association was expressed using OR and 95% CI.

Data Quality Assurance

A preliminary phase was conducted to assess the validity and reliability of the questionnaire before its use. Initially, three Ethiopian experts in the field of epidemiology and research in Ethiopian universities were asked to assess the degree to which items in the questionnaires were relevant and can correctly measure predictors of COVID-19 prevention practice using the Health Belief Model, and a correction was made accordingly. Then, the questionnaire was pretested on 30 participants who were excluded later from the study sample. Data were used to assess internal consistency reliability using Cronbach’s alpha. The results showed adequate internal consistency reliability (with Cronbach’s alpha= 0.915 or perceived susceptibility, 0.773 for perceived severity, 0.954 for the perceived benefit, 0.869 for the perceived barrier, 0.806 for cues to action, and 0.986for self-efficacy questions).

Ethics Approval and Consent to Participants

Approval and ethical clearance was obtained from the Institution Review Board (IRB) of Universal Medical and Business College (UMBC) which was in accordance with the principles embodied in the Declaration of Helsinki. Official permission was also obtained from the principals of the four selected organizations before approaching the study participants. The objective and purpose of the study was clearly explained to the study subjects to obtain written informed consent before data collection. Participants were also informed that they can discontinue or decline to participate in the study at any time. Confidentiality of the information was maintained and the data were recorded anonymously throughout the study.

Operational Definition and Its Measurements

Knowledge of COVID-19: knowledge of COVID-19 was measured using 12 questions. Each correct response was scored 1, and each incorrect response was scored 0. A total score of ≥9 (≥80%) out of 12 was considered as having good knowledge whereas a score <9 (<80%) was considered as poor knowledge towards COVID-19 and its prevention. COVID-19 prevention practices: Practice of COVID-19 prevention was measured using eleven questions. Each correct response in the practice category was scored 1, and each incorrect response was scored 0. A total score of ≥8 (≥80%) out of eleven was considered as having good practice whereas a score <8 (<80%) was considered as having a poor practice of COVID-19 prevention.10 Perceived susceptibility: one’s belief regarding the chance of getting COVID-19. Respondents will be asked eight7 questions (eg I am not afraid of getting Coronavirus infection) to describe their level of agreement in a five-scale response format from “strongly disagree” to “strongly agree”. The 5-point Likert scale response options, scored from 1 to 5, were strongly disagree, disagree, neutral, agree, and strongly agree. Subscale scores were obtained by summing item scores and dividing by the total number of items. If it is above or equal to the average score, it was indicative of high perceived susceptibility.11 Perceived severity: one’s belief of how serious COVID-19 and its squeal are. Respondents were asked six6 questions (eg Becoming Corona virus-infected is the worst thing that could happen to me) to describe their level of agreement in a five scale response format from “strongly disagree” to “strongly agree”. The 5-point Likert scale response options, scored from 1 to 5, were strongly disagree, disagree, neutral, agree, and strongly agree. Subscale scores were obtained by summing item scores and dividing by the total number of items. If it is above or equal to the average score, it was indicative of high perceived severity.12 Perceived benefit: one’s beliefs in the efficacy of COVID-19 prevention practice like hand washing, social distancing, etc. to reduce the risk of getting COVID-19. Respondents were asked 109 questions (eg Washing hands frequently with soap and water or using alcohol-based hand rub kills the virus that causes COVID-19) to describe their level of agreement in a five-scale response format from “strongly disagree” to “strongly agree”. The 5-point Likert scale response options, scored from 1 to 5, were strongly disagree, disagree, neutral, agree, and strongly agree. Subscale scores were obtained by summing item scores and dividing by the total number of items. If it is above or equal to the average score, it was indicative of a high perceived benefit.13 Perceived barrier: one’s belief about the tangible and psychological costs of practicing COVID-19 prevention mechanisms like staying at home. Respondents were asked six6 questions (eg Face mask is hard to get) to describe their level of agreement in a five-scale response format from “strongly disagree” to “strongly agree”. The 5-point Likert scale response options, scored from 1 to 5, were strongly disagree, disagree, neutral, agree, and strongly agree. Subscale scores were obtained by summing item scores and dividing it by the total number of items. If it is above or equal to the average score, it was indicative of a low level of perceived barrier.14 Cues to action: strategies to activate one’s “readiness” to use COVID-19 prevention practices. Based on prior research (Wilson et al, 1991), a 6-item yes/no scale was used to assess participant’s exposure to cues that could influence them to engage in COVID-19 practice. The scale was developed. Typical items as follows: “Do you know someone with COVID-19?” The sum of the score ranged from 6 to 12; higher scores indicated exposure to more COVID-19 information. Scale score was obtained by summing item scores and dividing by the total number of items.15 Self-efficacy: one’s confidence in one’s ability to use or apply prevention of COVID-19 practices recommended by WHO in a different situation. Respondents were asked five5 questions (eg feel confident that I could talk to any person to using a face mask) to describe their level of agreement in a five-scale response format from “strongly disagree” to “strongly agree”. The 5-point Likert scale response options, scored from 1 to 5, were strongly disagree, disagree, neutral, agree, and strongly agree. Subscale scores were obtained by summing item scores and dividing by the total number of items. If it was above or equal to the average score, it was indicative of a high level of self-efficacy.16

Result

Socio-Demographic Characteristics of the Respondents

A total of 628 employees working in four organizations in Addis Ababa were included in this study. More than half of the study subjects 414 (65.9%) were in the age category of 24–28 years with a mean ± SD of 28.76 ± 5.10 years. The majority of the respondent 434 (69.1%) were males and more than half 361 (57.5%) of them were single. The majority 376 (59.9%) and 402 (64.0%) of them were degree holders by educational level and earn a monthly income of 2500–7499 birr, respectively. Most 247 (39.3%) of them were bank workers, while 131 (20.9%) of them were health workers (Table 1).
Table 1

Socio-Demographic Characteristics of the Respondents, Employees in Addis Ababa, Ethiopia, May 2020

VariablesCategoryNumberPercent
Age (years)24–2841465.9
≥2921434.1
SexMale43469.1
Female19430.9
Marital statusSingle36157.5
Married26742.5
Educational levelCertificate9014.3
Degree37659.9
Masters14122.5
PhD213.3
OccupationHealth workers13120.9
Airline workers8213.1
Bank workers24739.3
Telecommunication workers16826.8
Income (birr)2500–749940264.0
7500–12,4998513.5
≥12,50014122.5
Socio-Demographic Characteristics of the Respondents, Employees in Addis Ababa, Ethiopia, May 2020

Knowledge of the Respondents About COVID-19

Of the total of 628 respondents, 248 (39.5%) of them had poor knowledge about COVID-19 (Figure 1). All of the respondents heard about the disease. More than half 337 (53.7%) of them were not aware of the call center service number to seek information about COVID-19 and half 309 (49.2%) of the employees were aware of the main symptoms of COVID-19 like fever, dry cough, and difficulty of breathing. Two hundred ninety-seven (47.3%) of them believed that persons infected with COVID-19, but has no symptoms cannot transmit the virus to others. Close to half 297 (47.3%) of them said children and young adults do not need to take measures to prevent COVID-19, and people who have contact with someone infected with the COVID-19 should be immediately quarantined. Only 261 (41.6%) of them said the length of quarantine of people who have contact with COVID-19 cases is 14 days (Table 2).
Figure 1

Level of knowledge of the respondents about COVID-19, employees in Addis Ababa, Ethiopia, May 2020.

Table 2

Knowledge of the Respondents About COVID-19, Employees in Addis Ababa, Ethiopia, May 2020

VariablesCategoryNumberPercent
Know the call center service number to seek information about COVID-19Yes29146.3
No33753.7
Know the main symptoms of COVID-19 (fever, dry cough, difficulty of breathing)Yes30949.2
No31950.8
Supportive treatment can help most patients recover from the COVID-19 infectionYes13221.0
No49679.0
Patients who have chronic illnesses, elderly and obese are more likely to develop a severe form of COVID-19Yes29747.3
No33152.7
Persons infected with COVID-19, but has no symptoms cannot transmit the virus to othersYes29747.3
No33152.7
It is not necessary for children and young adults to take measures to prevent COVID-19Yes29747.3
No33152.7
People who have contact with someone infected with the COVID-19 virus should be immediately quarantinedYes29747.3
No33152.7
Length (in days) of quarantine of people who have contact with COVID-19 cases517127.2
1011217.8
1426141.6
218413.4
Knowledge of the Respondents About COVID-19, Employees in Addis Ababa, Ethiopia, May 2020 Level of knowledge of the respondents about COVID-19, employees in Addis Ababa, Ethiopia, May 2020.

Sources Information About COVID-19

The major sources of information about COVID-19 for the study subjects were government media (TV/Radio) (69.6%), social media (67.7%), local sources like posters, banners (59.1%), national sources (MOH/EPHI) (55.4%) and private medias TV/Radio (52.7%) (Figure 2).
Figure 2

Trusted sources information about COVID-19, employees in Addis Ababa, Ethiopia, May 2020.

Trusted sources information about COVID-19, employees in Addis Ababa, Ethiopia, May 2020.

Factors Affecting Knowledge of the Respondents About COVID-19

Bivariate and multivariate logistic regression models were carried out to determine the factors affecting the employees’ knowledge of COVID-19. Only variables with a p-value ≤0.2 (age, level of education, occupation, income) were included in the multivariate regression. After adjusting for possible confounding factors with multivariate regression; age, level of education, and income were significantly associated with knowledge about COVID-19 with a p-value <0.05. Employees in the age category of 24–28 years were 2.75 times [AOR = 2.75, 95% CI (1.72, 4.41)] more likely to have a poor level of knowledge about COVID-19 compared to employees whose age was greater than 28 years. Similarly, employees with an educational level of the certificate were 10.02 times [AOR = 10.02, 95% CI (5.02, 19.99)] more likely to have a poor level of knowledge about COVID-19 than employees with an educational level of degree an above. Employees with a monthly income of 7500–12,499 birr were less likely to have a poor level of knowledge about COVID-19 (Table 3).
Table 3

Factors Affecting Knowledge of the Respondents About COVID-19, Employees in Addis Ababa, Ethiopia, May 2020

VariablesCategoryKnowledge of COVID-19COR (95% CI)AOR (95% CI)P-value
Poor, N%)Good, N(%)
Age (years)24–28150(60.5)264(69.5)1.49(1.06, 2.08)*2.75(1.72, 4.41)0.000
≥2898(39.5)116(30.5)11
Level of educationCertificate21(8.5)110(28.9)4.09(2.47, 6.78)*10.02(5.02, 19.99)0.000
Degree45(18.1)37(9.7)0.64(0.40,1.03)1.41(0.78, 2.53)0.255
Master and above182(73.4)233(61.3)11
OccupationNon-health workers227(91.5%)270(71.1)0.23(0.14, 0.37)*0.85(0.48, 1.51)0.581
Health workers21(8.5%)110(28.9)11
Income (birr)2500–7499139(56.0)263(69.2)0.89(0.59, 1.34)0.70(0.46, 1.08)0.106
7500–12,49964(25.8)21(5.5)0.15(0.08, 028)*0.10(0.05, 0.20)0.000
≥12,50045(18.1)96(25.3)11

Note: *p-value < 0.05.

Factors Affecting Knowledge of the Respondents About COVID-19, Employees in Addis Ababa, Ethiopia, May 2020 Note: *p-value < 0.05.

Constructs of the HBM About COVID-19 Prevention Practice

Three hundred ninety-one (62.3%) of the respondents had high perceived susceptibility to COVID-19 while the rest 237 (37.7%) had low perceived susceptibility to Coronavirus infection with a mean score ± SD of 14.65±8.5 and a median value of 11. Concerning the perceived severity of the disease, 337 (53.7%) of the respondents had high perceived severity to coronavirus infection while the rest 291 (46.3%) had low perceived severity and the mean score for perceived severity was 22.34 with a standard deviation ±7.8 and median value 24. Concerning the third component of the Health Belief Model, half 316 (50.3%) of the respondents had low perceptions about the benefit of coronavirus infection prevention practice. But 312 (49.7%) of the participants had high perceived benefit with a mean ± SD score of 34.0± 12.7 with a median value of 39. Three hundred twenty-five (51.8%) of the respondents were exposed to low triggering factors for coronavirus infection prevention with a mean ± SD score of 8.9±2.3 and median value 8. Four hundred ninety-seven (79.1%) of the respondents had a high perceived barrier and the rest 131 (20.9%) of the participants had low perceived barrier with a mean ± SD score of 18.02 ± 7.3 with a median value of 21. About 329 (52.4%) had low self-efficacy towards coronavirus infection prevention with a mean ± SD score of 15.6 ± 7.5 with and a median value of 15 (Table 4).
Table 4

Opinions of the Constructs of Health Belief Model About COVID-19 Prevention Practice, Employees in Addis Ababa, Ethiopia, May 2020 (N=628)

ItemsFrequencyPercent
Perceived susceptibility
 High39162.3
 Low23737.7
Perceived severity
 High29146.3
 Low33753.7
Perceived benefit
 High31249.7
 Low31650.3
Perceived barrier
 High49779.1
 Low13120.9
Cues to action
 High30348.2
 Low32551.8
Self-efficacy
 High29952.4
 Low32947.6
Opinions of the Constructs of Health Belief Model About COVID-19 Prevention Practice, Employees in Addis Ababa, Ethiopia, May 2020 (N=628)

Practice of COVID-19 Prevention

Of the total of 628 respondents, 432 (68.8%) of them had a poor practice of COVID-19 prevention. More than half 58.3% of them did not clean surfaces. Only 39.8% of them cover their mouth and nose while sneezing and coughing while 42.4% of them disposed used tissues properly after coughing and sneezing. The majority of 60.8% of them washed their hands frequently with soap and water for 20 seconds and 58.9% of them cleaned their hands with alcohol-based sanitizer if water is not available. More than half 55.7% of them wear masks in public areas and none of them kept their distance. More than two-thirds of 68.85% of them avoided groups and all of them stayed at home if they feel sick (Figures 3 and 4).
Figure 3

Overall practice of COVID-19 prevention, employees in Addis Ababa, Ethiopia, May 2020.

Figure 4

Practice of COVID-19 prevention, employees in Addis Ababa, Ethiopia, May 2020.

Overall practice of COVID-19 prevention, employees in Addis Ababa, Ethiopia, May 2020. Practice of COVID-19 prevention, employees in Addis Ababa, Ethiopia, May 2020.

Factors Associated with COVID-19 Prevention Practice

A bivariate and a multivariate logistic regression model was carried out to determine the factors affecting the employees’ knowledge of COVID-19. Only variables with a p-value ≤0.2 (sex, knowledge, perceived severity) were included in the multivariate regression. After adjusting for possible confounding factors with multivariate regression; income, perceived barrier, cues to action, and self-efficacy were significantly associated with prevention practice of COVID-19 with a p-value <0.05. Employees with a monthly income of 7500–12,499 birr and 7500–12,499 birr were more likely to practice the prevention of COVID-19 compared to employees with a monthly income of ≥12,500 birr [AOR = 3.67, 95% CI (1.09,12.42)] and [AOR = 4.25, 955CI (1.23,14.65)], respectively. Employees with low level of perceived barriers were less likely to have a poor practice of COVID-19 prevention compared to employees with a high level of perceived barrier [AOR = 0.03, 95% CI (0.01,0.05)]. Similarly, employees with low cues to action and employees with a low level of self-efficacy were practiced COVID prevention measures to a lesser extent compared those with high cues to action and high level of self-efficacy [AOR = 0.05, 95% CI (0.026, 0.10)] and [AOR = 0.08, 95% CI (0.04, 0.14)], respectively (Table 5).
Table 5

Factors Associated with COVID-19 Prevention Practice, Employees in Addis Ababa, Ethiopia, May 2020 (N=628)

VariablesCategoryPracticeCOR, 95% CIAOR, 95% CIP-value
PoorGood
SexMale3081260.73(0.51,1.04)
Female124701
Age (years)24–282981160.65(0.46,0.93)*1.53(0.79,0.299)0.210
>281348011
Marital statusSingle2191422.56(1.77,3.69)*1.96(0.93,4.13)0.770
Married2135411
Educational statusCertificate461425.50(3.02,10.01)*2.91(0.86,9.79)0.085
Degree248542.97(1.83,4.81)*1.43(0.55,3.69)0.463
Masters and above13819611
Occupational statusNon-health workers3631340.41(0.28,0.61)*0.56(0.267,1.19)0.563
Health workers696211
Income (birr)2500–74992481544.85(2.78,8.48)*3.67(1.09,12.42)0.036
7500–12,49959263.44(1.72,6.90)*4.25(1.23,14.65)0.022
≥12,5001251611
KnowledgePoor knowledge180680.74(0.52,1.06)
Good knowledge2521281
Perceived susceptibilityLow2811100.69(0.49,0.97)*1.24(0.68,2.24)0.482
High1518611
Perceived severityLow2361010.88(0.63,1.24)
High196951
Perceived benefitLow231850.67(0.47,0.94)*1.34(0.75,2.39)0.324
High20111111
Perceived barrierLow406910.06(0.03,0.09)*0.03(0.01,0.05)0.000
High261051
Cues to actionLow280450.16(0.11,0.24)*0.05(0.026,0.10)0.000
High15215111
Self-efficacyLow280490.18(0.12,0.26)*0.08(0.04,0.14)0.000
High15214711

Note: *P-value < 0.05.

Factors Associated with COVID-19 Prevention Practice, Employees in Addis Ababa, Ethiopia, May 2020 (N=628) Note: *P-value < 0.05.

Discussion

COVID-19 is an emerging infectious disease that poses a significant threat to public health.17 Given the severe threats imposed by COVID-19 and the lack of a COVID-19 vaccine, preventive measures play a vital role in decreasing infection rates and halting the spread of the disease.18 This indicates the necessity of employees to practice the preventive and control measures, which is affected by socio-demographic characteristics, level of knowledge, perceived susceptibility, severity, benefit, barrier, cues to action, and self-efficacy. Therefore, this study was the first study to assess the predictors of coronavirus infection prevention practice among employees of Addis Ababa, Ethiopia using the Health Belief Model. In this study, the level of COVID-19 prevention practice was 196 (31.2%). This was similar to a study conducted in residents of Ethiopia.19 However, this was lower when compared to the previous study done among health professionals in Ethiopia which were 63%,20,21 and with the study conducted among the high-risk group of Addis Ababa Ethiopia which was 49%22 with the study conducted in the Kingdom of Saudi Arabia.23 And with the study conducted in Hong Kong which was 77% of the participants reported good health performance for COVID–19.24 This discrepancy might be due to the difference in the study population. A perceived barrier is one of the components of HBM that deals with the perception of barriers that do not allow the performance of coronavirus infection prevention (ie availability and accessibility of water, home environment, and the availability of electricity and internet connection).25 The present study finds out that employees with low level of perceived barriers were less likely to have a poor practice of COVID-19 prevention compared to employees with a high level of perceived barrier [AOR = 0.03, 95% CI (0.01,0.05)]. This might be due to the finding proportion of households with soap and water for hand-washing was 13% and current levels of access to water and hand-washing facilities, and characteristics of the home environment are not conducive for effective implementation of basic prevention measures, including social distancing26 and limited access to electricity and internet connection discourages work from home.27 Self-efficacy is one of the components of HBM that refers to the level of a person’s confidence in his or her ability to successfully perform the prevention mechanism of COVID-19.8 The current study identified that employees with low cues to action and employees with a low level of self-efficacy were practice COVID prevention measures to a lesser extent compared with those with high cues to action and high level of cues to action [AOR = 0.05, 95% CI (0.026,0.10)] and [AOR = 0.08, 95% CI (0.04,0.14)], respectively. This was in line with the study conducted in Turkish adults28 and with the study conducted in Iran among hospital staff.29 Individuals who believe they are at low risk of developing a COVID-19 are more likely to engage in unhealthy, or risky, behaviors like not wearing a face mask, unable to keep social distancing, etc.,30 and the combination of Perceived severity and Perceived susceptibility is referred to as perceived threat31 which depend on knowledge about the COVID-19 situation.32 The HBM predicts that higher perceived threat leads to a higher likelihood of engagement in health-promoting behaviors like keeping social distancing, properly wearing a face mask, hand hygiene, etc. But the current study failed to show the significant association between COVID-19 prevention practice and perceived severity and perceived susceptibility. This might be due to the knowledge gap that was found among the employees towards the COVID-19 situation was 40%. A study conducted in Sudan to determine the Sudanese perceptions of COVID-19 using the Health Belief Model showed that low perceived susceptibility (beliefs about the likelihood of getting COVID-19) and severity (beliefs about the seriousness of contracting COVID-19, including consequences) was 45% and 40%, respectively.33 This is slightly higher compared to the current study, which was 37.7% of the employee had low perceived susceptibility. But the perceived severity was slightly lower which 53.7% of the employees had low perceived severity. This difference might be due to the difference in the study area.and the source of the population. In the current study of a total of 628 respondents, 380 (60.5%) of them had good knowledge about COVID-19. This was higher when it compared with the study that was done in Ethiopia which was 52% of the participants had good knowledge on transmission of COVID-1922 and with the study conducted in India which was 39% of the participants have good perceived knowledge for preventive measures.34

Limitation

This study has some limitations. One of the limitations is bias occurred as a result of the study design (cross-sectional) since the study took the information at specified time-points and cause and effect association cannot be studied. Different mechanisms were used to reduce potential bias in the study. In addition to this, a lack of sufficient similar study limited comparison to this study finding with other studies. However, identifying knowledge gaps, perceived susceptibility, severity, benefit, barrier, cues to action, self-efficacy, and practice can be used to develop effective interventions and establish baseline levels to set priorities for program managers.

Conclusions

This study examined the predictors of COVID-19 prevention practice using the Health Belief Model among employees of Addis Ababa, Ethiopia. A significant number of employees had poor knowledge about COVID-19 and its prevention. The proportion of poor prevention practice of COVID-19 was also high. Income, perceived barrier, cues to action, and self-efficacy were significantly associated with the prevention practice of COVID-19 with a p-value<0.05. Hence, policymakers and other concerned bodies should focus on those areas to improve the prevention practice of COVID-19.
  16 in total

Review 1.  Using social and behavioural science to support COVID-19 pandemic response.

Authors:  Jay J Van Bavel; Katherine Baicker; Paulo S Boggio; Valerio Capraro; Aleksandra Cichocka; Mina Cikara; Molly J Crockett; Alia J Crum; Karen M Douglas; James N Druckman; John Drury; Oeindrila Dube; Naomi Ellemers; Eli J Finkel; James H Fowler; Michele Gelfand; Shihui Han; S Alexander Haslam; Jolanda Jetten; Shinobu Kitayama; Dean Mobbs; Lucy E Napper; Dominic J Packer; Gordon Pennycook; Ellen Peters; Richard E Petty; David G Rand; Stephen D Reicher; Simone Schnall; Azim Shariff; Linda J Skitka; Sandra Susan Smith; Cass R Sunstein; Nassim Tabri; Joshua A Tucker; Sander van der Linden; Paul van Lange; Kim A Weeden; Michael J A Wohl; Jamil Zaki; Sean R Zion; Robb Willer
Journal:  Nat Hum Behav       Date:  2020-04-30

2.  The Health Belief Model as an explanatory framework in communication research: exploring parallel, serial, and moderated mediation.

Authors:  Christina L Jones; Jakob D Jensen; Courtney L Scherr; Natasha R Brown; Katheryn Christy; Jeremy Weaver
Journal:  Health Commun       Date:  2014-07-10

3.  Perceived susceptibility to illness and perceived benefits of preventive care: an exploration of behavioral theory constructs in a transcultural context.

Authors:  Galen Joseph; Nancy J Burke; Noe Tuason; Judith C Barker; Rena J Pasick
Journal:  Health Educ Behav       Date:  2009-10

4.  Towards an effective health interventions design: an extension of the health belief model.

Authors:  Rita Orji; Julita Vassileva; Regan Mandryk
Journal:  Online J Public Health Inform       Date:  2012-12-19

5.  The perceived severity of a disease and the impact of the vocabulary used to convey information: using Rasch scaling in a simulated oncological scenario.

Authors:  Roberto Burro; Ugo Savardi; Maria Antonietta Annunziata; Paolo De Paoli; Ivana Bianchi
Journal:  Patient Prefer Adherence       Date:  2018-12-03       Impact factor: 2.711

6.  Clustering of lifestyle risk behaviours and its determinants among school-going adolescents in a middle-income country: a cross-sectional study.

Authors:  Chien Huey Teh; Ming Woey Teh; Kuang Hock Lim; Chee Cheong Kee; Mohd Ghazali Sumarni; Pei Pei Heng; Tajul Hassan Mohd Zahari; Ying Ying Chan; Md Iderus Nuur Hafiza; Eng Ong Tee; Kamaludin Fadzilah
Journal:  BMC Public Health       Date:  2019-08-27       Impact factor: 3.295

7.  Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.

Authors:  Chaolin Huang; Yeming Wang; Xingwang Li; Lili Ren; Jianping Zhao; Yi Hu; Li Zhang; Guohui Fan; Jiuyang Xu; Xiaoying Gu; Zhenshun Cheng; Ting Yu; Jiaan Xia; Yuan Wei; Wenjuan Wu; Xuelei Xie; Wen Yin; Hui Li; Min Liu; Yan Xiao; Hong Gao; Li Guo; Jungang Xie; Guangfa Wang; Rongmeng Jiang; Zhancheng Gao; Qi Jin; Jianwei Wang; Bin Cao
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

8.  The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study.

Authors:  Kiesha Prem; Yang Liu; Timothy W Russell; Adam J Kucharski; Rosalind M Eggo; Nicholas Davies; Mark Jit; Petra Klepac
Journal:  Lancet Public Health       Date:  2020-03-25

9.  Mental health and emotional impact of COVID-19: Applying Health Belief Model for medical staff to general public of Pakistan.

Authors:  Sonia Mukhtar
Journal:  Brain Behav Immun       Date:  2020-04-10       Impact factor: 7.217

10.  Short report on implications of Covid-19 and emerging zoonotic infectious diseases for pastoralists and Africa.

Authors:  Anthony Egeru; Sintayehu W Dejene; Aggrey Siya
Journal:  Pastoralism       Date:  2020-06-09
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  15 in total

1.  Community responses to COVID-19 pandemic first wave containment measures: a multinational study.

Authors:  Myo Nyein Aung; Claire Stein; Wei-Ti Chen; Vandana Garg; Monika Saraswati Sitepu; Nguyen Thi Dang Thu; Carlos Primero D Gundran; Mohd Rohaizat Hassan; Unyaporn Suthutvoravut; Aung Naing Soe; Magde Nour; Khin Khin Gyi; Rainer Brandl; Motoyuki Yuasa
Journal:  J Infect Dev Ctries       Date:  2021-08-31       Impact factor: 2.552

2.  Using the Health Belief Model to examine travelers' willingness to vaccinate and support for vaccination requirements prior to travel.

Authors:  Courtney Suess; Jason Maddock; Tarik Dogru; Makarand Mody; Seunghoon Lee
Journal:  Tour Manag       Date:  2021-08-22

3.  Awareness, perception and the practice of COVID-19 prevention among residents of a state in the South-South region of Nigeria: implications for public health control efforts.

Authors:  Golden Owhonda; Omosivie Maduka; Ifeoma Nwadiuto; Charles Tobin-West; Esther Azi; Chibianotu Ojimah; Datonye Alasia; Ayo-Maria Olofinuka; Vetty Agala; John Nwolim Paul; Doris Nria; Chinenye Okafor; Ifeoma Ndekwu; Chikezie Opara; Chris Newsom
Journal:  Int Health       Date:  2022-05-02       Impact factor: 3.131

4.  Perceived Susceptibility and Severity of COVID-19 on Prevention Practices, Early in the Pandemic in the State of Florida.

Authors:  M A DeDonno; J Longo; X Levy; J D Morris
Journal:  J Community Health       Date:  2022-04-22

5.  Health Communication, Knowledge, Perception and Behavioral Responses to COVID-19 Outbreak in Dessie, Kombolcha and Kemissie Towns, Amhara Region, Northeast Ethiopia: A Mixed-Method Study.

Authors:  Zemen Mengesha Yalew; Yibeltal Asmamaw Yitayew; Ebrahim Seid Mohammed; Tesfaye Bezabih Gezihagne
Journal:  J Multidiscip Healthc       Date:  2021-05-11

6.  COVID-19 Prevention Practices and Associated Factors among Diabetes and HIV/AIDS Clients in South-Wollo Zone, Ethiopia: A Health Facility-Based Cross-Sectional Study.

Authors:  Ayechew Ademas; Metadel Adane; Awoke Keleb; Gete Berihun; Mistir Lingerew; Tadesse Sisay; Seada Hassen; Melaku Getachew; Getu Tesfaw; Dejen Getaneh Feleke; Elsabeth Addisu; Leykun Berhanu; Masresha Abebe; Adinew Gizeyatu; Habtemariam Abate; Atimen Derso
Journal:  J Multidiscip Healthc       Date:  2021-08-04

7.  Testing the Effectiveness of the Health Belief Model in Predicting Preventive Behavior During the COVID-19 Pandemic: The Case of Romania and Italy.

Authors:  Johannes Alfons Karl; Ronald Fischer; Elena Druică; Fabio Musso; Anastasia Stan
Journal:  Front Psychol       Date:  2022-01-12

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

Authors:  Kegnie Shitu; Asmamaw Adugna; Ayenew Kassie; Simegnew Handebo
Journal:  PLoS One       Date:  2022-03-21       Impact factor: 3.240

9.  Perception of COVID-19 Prevention Methods Efficacy and Intention to Use Among Patients with Chronic Disease in Dessie Town, Northeast Ethiopia: A Multicentered Cross-sectional Study.

Authors:  Abebe Dires; Sisay Gedamu; Yemiamrew Getachew
Journal:  J Multidiscip Healthc       Date:  2021-06-04

10.  Perceived Susceptibility to and Seriousness of COVID-19: Associations of Risk Perceptions with Changes in Smoking Behavior.

Authors:  Erin A Vogel; Lisa Henriksen; Nina C Schleicher; Judith J Prochaska
Journal:  Int J Environ Res Public Health       Date:  2021-07-17       Impact factor: 4.614

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