Adherence to COVID-19 Protective Behaviors among Iranian Adults: Survey of the Role of Health Literacy and Health Belief Model

DOI: https://doi.org/10.21203/rs.3.rs-1923899/v1

Abstract

Background

The coronavirus is one of the largest pandemics in the world that has occurred in recent years. The virus has so far killed millions of people around the world. To prevent the coronavirus, health behaviors are essential. Therefore, identifying the effective factors of coronavirus preventive behaviors can be effective in designing and implementing health interventions.

Methods

This study was a cross-sectional design that was implemented in Iran in 2021. Participants were recruited randomly from healthcare centers by medical records (n = 380, 64.7% female, mean age 32.14 years). The data collection included a demographic form, health literacy questionnaire, and Coronavirus disease (COVID-19) protective questionnaire. Analyses were adjusted for confounders using hierarchical regression analysis.

Results

According to the analysis, among participants COVID-19 preventive behaviors (CPBs) distributions, wearing masks was the highest and avoiding touching my face and do not leaving home were the lowest. Educational level, gender, perceive benefits, perceived barriers and self-efficacy trust were all significant predictors of COVID-19 protective behaviors. Also, among dimensions of the health literacy, all of them except decision-making were significant predictors of adherence to COVID-19 preventive behaviors. The most COVID-19 preventive behaviors distributions, among Iranian adults were wearing mask (66.3%) and covering mouth and nose while sneezing or coughing (44.2%) questions as “Always”.

Conclusions

this research shows health literacy and cognitive factors have a potential and determinative role in the health of patients with COVID-19. Wearing mask has been the highest preventive behavior in patients with COVID-19, which indicates the effect of educational level as demographic factors in these groups of patients. Therefore, these factors can be considered in prevention and treatment programs in health system.

Background

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus that in December, 2019, emerged in Wuhan, China. Most people infected with the COVID-19 virus will experience mild to moderate respiratory illness and recover without requiring special treatment [1]. During the interval between February 19 and 23, 2020, Iran reported its first 43 cases with eight deaths [2] and on 30th January 2020, the world health organization (WHO) declared the Chinese outbreak of COVID-19 to be a Public Health Emergency of International Concern posing a high risk to countries with vulnerable health systems [3].

Therefore, WHO recommended enhancing whole-of-society coordination mechanisms to support preparedness and response to prevention and control strategies for the disease [4, 5]. Also it recommended personal protective behaviors such as physical distancing, wearing a mask, keeping rooms well ventilated, avoiding crowds, cleaning your hands, and coughing into a bent elbow or tissue and checking local advice where people live and work [6, 7]. In other words, the compliance of the general public with the advice and regulations of the health authorities and the adoption of effective health behavior regimens are currently the only weapons to effectively cope with the disease [8].

Understanding the effective factors in engagement with health-protective behaviors can help inform public health strategies to encourage people to increase and sustain these behaviors. health literacy, knowledge, attitudes, reactions to stress, and motivation are important determinants of health behavior [9, 10].

Health literacy (HL) is the extent to which individuals attain, manage, and understand health information and apply that information in health decision-making [10]. HL is associated with self-care behaviors [11, 12], while low HL is associated with poorer health outcomes [13] and more likely to have health risk behaviors [14]. An acceptable level of health literacy makes people have a better understanding and interpretation of health conditions and challenges, and then they can have better decision-making, reaction and performance and look after themselves and those around them [15].

misconceptions about COVID-19 including uncertainty about whether people are likely to have natural or existing immunity to the virus, uncertainty around whether specific traditional and home remedies would offer protection and whether the virus was human-made and deliberately release are likely to cause concern for members of the public [16]. In this condition more accurate knowledge about how a virus is spread [17] and the perception that behaviors will be effective in reducing the risk of infection [18]. In health crisis like covid-19 pandemic that people are exposed with information excess from various information resources health literacy is important than ever [19]. Increasing awareness by giving correct information, and increasing health literacy are effective factors in adopting health-promoting behaviors [20].

The cognitive determinants are most strongly and consistently associated with behavior. A number of models integrating various cognitive determinants of health behavior have been developed and applied in this area [21]. Health Belief Model (HBM) is one of these models that has been used to explain the influence of the intrapersonal cognitive factors behavior in different populations [2224]. This model suggests, “If individuals regard themselves as susceptible to a condition, believe that condition would have potentially serious consequences, believe that a course of action available to them would be beneficial in reducing either their susceptibility to or severity of the condition, and believe the anticipated benefits of taking action outweigh the barriers to (or costs of) action, they are likely to take action that they believe will reduce their risks”.[25]. Bandura postulated that increased self-efficacy, perceived threat and perceived benefits, and decreased perceived barriers may increase the probability of health-related behaviors [22, 26, 27].

In other words, the psychological and behavioral responses of the general population play an important role in the control of the outbreak [28]. People who perceive greater risks are more willing to implement protective behaviors and more likely to prefer government policies designed to mitigate risk [29].

A broad understanding of some of the key factors for understanding behaviors and behavior change can provide a foundation for well-informed public health programs, help identify the most influential factors for a particular person or population, and enable program developers to focus on the most salient issue [30]. In order to well-control of Coronavirus, it is necessary a comprehensive understanding of the factors associated with personal protective behaviors, Therefore, our purpose in the current study was to determine the predicting effect of cognitive factors and HL on health-protective behaviors against Corona disease.

Methods

Study design and Participants

The present cross-sectional study was conducted in Sarab, a mountainous county in East Azerbaijan, the northwestern part of Iran. The population under study was the people 18-65 years of age covered by 4 the primary Health Care Services Centers (HCSCs) in urban and rural areas of the county. Multistage cluster sampling was employed to recruit 380 people from HCSCs. In the first stage of sampling, the 4 HCCs were considered as clusters and, then, in the second stage, the respondents were randomly selected from 4 HCCs. 380 people 18-65 years of age were selected via Morgan's table and Cochran's formula [31] with a N= 40000, d= 0.05, p=q=0.5 and Z= 1.96. Individuals were randomly selected from each HCSCs based on the health records of the population.

Ethical considerations

Ethical approval for the study was provided by Ethics Committee in Sarab Faculty of Medical Sciences.

Measures

Demographic information questionnaire

Data collection was conducted from November to February 2021 through face-to-face interviews, using a structured 3-sections questionnaire.

Socio-demographic characteristics questionnaire: This questionnaire included the variables of age, gender, marital status, educational status and monthly income.

Cognitive Factors Assessment Questionnaire

This was an HBM-based researcher-made questionnaire including: (1) risk perception to develop covid-19 (7 items) included. The questions such as "how likely do you think you will be contracting COVID-19" and personal belief regarding individuals suffering from the disease process and intensity of symptoms,(2) perceived barriers(4 items) consists of difficulties for protection against corona virus infection ("it cost me a lot to buy mask and …"),(3) perceived benefits (5 items) included benefits of protective behaviors for the individual and society (“Social quarantine and staying at home help us to avoid paying for unnecessary medications and …”), (4) self-efficacy (6 items) included a person’s confidence in adhering to protective behaviors (“social distancing, wearing a mask and …."), a five-point Likert-type scaling, ranging from one (strongly disagree) to five (strongly agree) was adopted. The sum of the respondents’ responses was used to measure each construct. (5) Cues to action: This dimension consists of participants’ information sources about corona virus disease (radio & television, social networks, health care workers and poster & banner). This scale included 4 items (yes, no and partly question) with scores ranging from 0 to 2.

The psychometric properties of the scales are documented [32]. For the current study, the estimates of internal consistency, as measured by Cronbach's Alpha, were 0.79 for perceived threat, 0.73 for perceived barriers, 0.75 for perceived benefits, 0.78 cues to action.

Self- Report Checklist: The checklist is used to investigate the health-protective behaviors (worn a mask or other face covering, coughing into a bent elbow or tissue g, avoiding contact with hands, face, and eyes, avoid going to crowded places and physical distancing) against developed covid-19 consisted of 5 items in a five-point Likert scale ranging from “never” (1) to “always” (5), ranging from 0 to 20 (Cronbach's Alpha 0.80).

Data analysis

We performed all the analyses using SPSS 16 (SPSS Inc, Chicago, IL, USA) and presented the data by mean (SD) and frequency (percent) for quantitative and qualitative variables, respectively. We also used the Kolmogorov-Smirnov test for testing the normality.

Two hierarchical logistic regression anal­yses were conducted to determine which variables can predict COVID-19 preventive behaviors. In Step 1, the covariates (i.e. age, gender, education level, marital status and income status) were entered into the models. In line with the COVID-19 preventive behaviors, the intention and CPBs were entered into Step 2 of the analyses. <0.05 was considered significant.

Results

Table 1 displays the demographics of the participants. The average age of the participants was 32.14 years (SD = 10.98), with the majority of them being under the age of 30 (55.3%), around 65 percent of the participants being female, and the majority of them having an academic degree. The majority of the samples were married couples.

Table 1

The relationship between demographical variable with COVID-19 protective behaviors (n = 380)

Variables

N (%)

Me ± SD

P-value

Age

Lower than 30

210 (55.3)

20.78 ± 30.07

0.098

30 to 39

130 (34.2)

20.51 ± 3.38

40 and higher

40 (10.5)

19.57 ± 3.67

Gender

Male

134 (35.3)

20.0 ± 3.47

0.013*

Female

246 (64.7)

20.86 ± 3.10

Level of education

Under diploma

115 (30.3)

19.24 ± 3.52

0.001*

Diploma

101 (26.6)

20.31 ± 3.22

College

164 (43.2)

21.56 ± 2.75

Marriage status

Married

262 (68.9)

20.41 ± 3.40

0.179

Single

118 (31.1)

20.89 ± 2.89

Income (month)

Less than 200 dollars

298 (78.4)

20.42 ± 3.31

0.119

200 dollars and higher

82 (21.6)

21.06 ± 30.01

*p<0.05


In Table 2 has been displayed percentage of response to covid-19 preventive behavior. Majority of the participants checked the wearing mask (66.3%) and covering mouth and nose while sneezing or coughing (44.2%) questions as “Always”.

Table 2

Frequency of COVID-19 protective behaviors among participants (n = 380)

Variables

Never

Seldom

Sometime

Mostly

Always

N (%)

N (%)

N (%)

N (%)

N (%)

When I leave the house, I always wear a mask.

2 (0.5)

2 (0.5)

24 (6.3)

100 (626.3)

252 (66.3)

I try to maintain a distance of at least 1.5 meters from other people.

2 (0.5)

9 (2.4)

82 (21.6)

171 (45.0)

116 (30.5)

I rarely leave my house unless absolutely necessary.

3 (0.8)

30 (7.9)

74 (19.5)

158 (41.6)

115 (30.3)

When I sneeze or cough, I put my hands over my mouth and nose.

5 (1.3)

16 (4.2)

65 (17.1)

126 (33.2)

168 (44.2)

I try not to touch my face (eyes, nose and mouth).

4 (1.1)

29 (7.6)

87 (22.9)

145 (38.2)

115 (30.3)

 

The bivariate associations for cognitive factors and HL with COVID-19 protective actions are shown in Table 3. We discovered that protective behaviors showed statistically significant relationships with all cognitive measures and HL (p-value 0.05) using the Pearson correlation coefficient test.

Table 3

Pearson correlation Coefficient of cognitive factors with COVID-19 preventive behaviors (n = 380)

Variables

1

2

3

4

5

6

7

1 = Risk perception

1

           

2 = Perceived benefits

0.109*

1

         

3 = Perceived barriers

0.135*

0.093

1

       

4 = cues to action

0.100

0.208*

-0.169*

1

     

5 = self-efficacy

0.124*

0.439*

-0.024

0.297*

1

   

6 = Health Literacy

0.981

0.512

0.145

0.437

0.237

1

 

6 = COVID-19 protective behaviors

0.119*

0.455*

0.101*

0.206*

.0542*

0.121*

1

*Correlation is significant at the 0.05 level (two-tailed).

 

The effects of demographic features, cognitive factors, and health literacy on COVID-19 protective behaviors were investigated using a hierarchical regression model (Table 4). In step 1, demographic features explained 11.9 percent of the variation in protective behaviors (F = 10.08; p-value > 0.05), implying that the demographic variable accounts for about 11.9 percent of the variation in protective behaviors. Table 3 shows that high protective behaviors were significantly associated with gender (ß=0.182; p-value = 0.001) and education level (ß=0.329; p-value = 0.001). An additional 30.4 percent of the variation in protective behaviors was explained by cognitive factors as predictor variables (step 2) (F = 38.77; p-value 0.05). Step 3 included the addition of health literacy factors, which explained an extra 2.8 percent of the variance.

Table 4

Hierarchical linear regression for prediction COVID-19 preventive behaviors through demographic characteristics, cognitive variables and health literacy (n = 380)

Variables

β

R2

R2 change

F change

SE

P-value

Step 1

0.119

0.133

10.08

 

Age

0.023

0.162

0.680

Gender

0.182

0.343

0.001*

Education level

0.329

0.207

0.001*

Marital status

0.022

0.396

0.693

Income status

0.046

0.046

0.349

Step 2

0.422

0.304

38.77

 

Age

0.059

0.134

0.209

Gender

0.089

0.290

0.037*

Education level

0.223

0.223

0.001*

Marital status

0.046

0.331

0.325

Income status

0.013

0.327

0.746

Risk perception

0.025

0.002

0.547

Perceived benefits

0.262

0.077

0.001*

Perceived barriers

0.142

0.044

0.001*

Cues to action

0.036

0.069

0.402

Self-efficacy

0.379

0.041

0.001*

Step 3

0.450

0.028

3.70

 

Age

0.052

0.132

0.266

Gender

0.073

0.288

0.085

Education level

0.235

0.172

0.001*

Marital status

0.031

0.328

0.507

Income status

0.014

0.324

0.739

Risk perception

0.016

0.002

0.690

Perceived benefits

0.266

0.076

0.001*

Perceived barriers

0.140

0.043

0.001*

cues to action

0.030

0.068

0.478

Self-efficacy

0.348

0.041

0.001*

Reading health information

0.091

0.014

0.024*

Ability to access health information

0.217

0.042

0.003*

Understanding health information

0.149

0.027

0.015*

Appraisal of health information

0.131

0.060

0.034*

Decision-making

0.041

0.024

0.397

*p < 0.05

Discussion

Determining of the effective factors related to health-protective behaviors is important in prevent of diseases, especially infectious diseases. So, this study was applied to determine the role of health literacy and cognitive factors on COVID-19 protective behaviors among adults.

Gender was recognized as one of the demographic characteristics affecting health-protective behaviors. This was consistent with the results showed by Shahnazi in Iran and Sánchez-Arenas in Mexico [33, 34]. In general, in the prevention of the disease, women perform better than men [35].

Also, higher education level led to COVID-19 protective behaviors among adults in this study. In Iran, COVID‑19 preventive behaviors was greater in urban area than rural [33]. According to this finding, better understanding and performing protective behaviors requires education level and health literacy. Therefore, among the demographic factors gender and education level should be addressing in educational programs.

The most COVID-19 preventive behaviors distributions, among Iranian adults were wearing mask (66.3%) and covering mouth and nose while sneezing or coughing (44.2%) questions as “Always”. Results of the other study in Iran demonstrated rate of adherence to preventive behaviors from COVID-19 among adult were good health performance and 61.2% of participants reported placing a tissue paper or bending elbow in front of my mouth and nose when coughing or sneezing questions as “Always” [33]. This founding indicates providing masks and training in terms of covering mouth and nose while sneezing or coughing has been effective two of the selected and successful preventive behaviors in during the COVID-19 pandemic.

The results of this study showed protective COVID-19 behaviors relationships with all cognitive factors and HL. These results were consistent with the other study in Norway that reported an association between health literacy and adoption of protective behaviors among adolescents in COVID-19 pandemic [36]. It means that people’s health literacy can impact COVID-19 protective behaviors. The finding of Shaukat et al. indicated the health literacy of university students was predictor health protective in these groups [37]. Despite the spread of rumors and misconceptions during the COVID-19 pandemic, the promotion of health literacy and appropriate health behaviors by health centers and national media is a necessity.

Cognitive factors of this study have included risk perception, perceived benefits, perceived barriers, cues to action and self-efficacy. Among these factors perceived benefits and cues to action were strongest association with COVID-19 protective behaviors. In contrast, self-efficacy had the least association with them. The more adult perceived benefits of COVID-19 protective behaviors, the more cues to action and the less ones perceived barriers to perform the behavior, the more probably to adopt the COVID-19 protective behaviors. This result was also supported by the findings of Shahnazi etal., in 2021 [33].

Risk perception was the other construct that associated with protective behaviors. Kwok et al., reported individuals had higher risk perception of COVID-19, mild anxiety, and adoption of health behavior, travel-avoidance and social distancing [38]. Risk perception can help promote health behavior in outbreak, but it should not be overemphasized, because it may affect inverse on people. Indeed, people perform more to health behaviors, when they believe they are at risk [39]. It is normal that people have some risk perception of COVID-19 disease, but it should modify to a positive factor in the performing protective behaviors such as wearing mask, keeping a social distance, staying home, not touching face and, etc. This finding appeared to be in line with that of Shmueli in 2021 who indicated that people who intended to be vaccinated had higher risk perception of suffering and complications of COVID-19 [40].

In this study, higher perceived benefits were predictor of COVID-19 protective behaviors. Health care providers and national media should can balance among perceived benefits and perceived barriers an individual. People probably hesitate in performing protective behaviors when they are more inform of the complications and mortality of COVID-19 disease against perceived benefits of protective behaviors, because they believe protective behaviors are futile. This finding confirms the results of Grinberg and Sela (2021) [41].

Regarding perceived barriers, performing to preventive behaviors increased by decreasing perceived barriers. One of the effective constructs of HBM is perceived barriers because people need to overcome barriers to health behavior in contrast internal tendency to adopt protective behavior [33]. Perceived barriers in this study was the lower the other constructs, except self-efficacy. It seems individuals tend to protective behavior adherence despite external and environmental barriers. This finding is related to the result of the Grinberg and Sela that reported the lower perceived barriers led to the more willing to administer the measles vaccine in mothers [41]. In this research, environmental barriers included lack of masks, disinfectants, etc. that were unavoidable.

Cues to action determined the second most important factor in COVID-19 protective behaviors. this result is in contraction to a study was conducted by Shahnazi that there are n’t relationship between cues to action and COVID-19 protective behaviors [33]. This may be because which in that research, cues to action was measured only two questions (TV and radio). There are several information resources in term of cues to action including Ministry of Health, national media or mass media (TV and radio), cyberspace, a doctor, health care providers and staff medical in Iran. This is where that health policy makers and health care providers, etc. can make the greatest roles. Result of our study was similar to finding of Kohpeima Jahromi and et al, (2021) [42]. In study of Shmueli showed cues to action was significant predictors of intention to vaccinate against COVID-19 in adults [40] .

Self-efficacy was the last predictor of COVID-19 protective behaviors from HBM constructs. This result was supported by the findings of the previous studies [33, 34, 42]. This result showed people with the high self-efficacy can better perform protective behavior and take care of their own against COVID-19 disease. Self-efficacy is the situation-specific confidence that people can cope with high-risk situations without relapsing to their former behaviors [25]. In HBM, individuals should have an acceptable level of self-efficacy to overcome barriers to behavior [25]. that it is a modifiable factor that can promote health behavior. Then, it is necessary to address this factor during outbreak of the disease.

Health literacy was the other determinant of COVID-19 protective behaviors in this research. This result was comparable with previous studies conducted in Pakistan [37] and Mexico City [34]. In situation of Covid-19 outbreak, have emphasized increasing the health literacy to prevent the spread of infection, because health literacy is important for the prevention of communicable diseases [43]. Results of a study in Australia appeared low health literacy in individuals led to held misinformation beliefs about COVID-19 and vaccinations than people who had appropriate health literacy [44]. The present study, 66.3% of participants never wear mask to protect the corona outdoors, 45% seldom keeping their social distance, just 0.8% of people staying in home, 44.2% of them never use their handkerchief or cover when cough or sneeze and 1.1% of ones not touching mouth, eyes, nose and other part of their face. These results were in contradict with a study in Mexico that reported 85.4% of participants worn mask, 80.8% covered their mouth with a sleeve when coughing, 72.7% kept at least 1.5 meters distance, 68.5% avoided face touching, 62.1% stayed home [34]. The rate of COVID-19 protective behaviors was low in Iran during the COVID-19 pandemic. The need for improving of COVID-19 protective behaviors is a crucial factor to address in Iran. The low understanding of COVID-19 symptoms, less recognizing COVID-19 protective behaviors, the more problem in term of research information and understanding policy maker massages about COVID-19 disease result from lower health literacy in people [44].

This present study has shown that the HBM was successful to predict COVID-19 preventive behaviors among adults in Iran. 45% of the variation in protective behaviors was explained by cognitive factors of HBM as predictor variables, demographic features and health literacy factors. In the study of Shmueli, 74% of the variance in intention to get COVID-19 vaccine explained by HBM constructs, demographic and health-related factors [40]. Then, using of this model is suggested to be applied in the other communicable diseases and also, designing intervention programs.

Limitations

This study had some limitations. The variables measured with self-report questioners, the risk of highly subjective biases among participants may arise. In addition, accessing to individuals was difficult during the COVID-19 pandemic.

Conclusions

The aim of the present study was predicting the role of health literacy and cognitive factors on COVID-19 protective behaviors among adults. In total, the findings of this study highlight that cognitive factors of HBM and health literacy were determinants of COVID-19 protective behaviors. Also rate of COVID-19 protective behaviors were low among adult in Iran. These findings can be useful for health policy makers and healthcare providers in order to prevent of the spread and mortality of COVID-19 disease.

Abbreviations

COVID-19: Coronavirus disease; CPBs: COVID-19 preventive behaviors; WHO: World Health Organization; HL: Health literacy; HBM: Health Belief Model; HCSCs: Health Care Services Centers; SD: Standard deviation

Declarations

Ethics approval and consent to participate

This study received ethical approval from the Sarab Faculty of Medical Sciences and conformed to the Declaration of Helsinki ethics guidelines. Following explanations of the study's goals and methodology, all participants signed a written informed consent form. At any stage during the study, participants were free to leave.

Consent for publication

Not applicable

Availability of data and materials

The dataset used for this research are available on request from the corresponding author.

Competing interests

The authors have no conflicts of interest to declare.

Funding

This work was supported by the Sarab Faculty of Medical Sciences.

Authors' contributions

TB conceptualized and designed the study, collected the data, drafted the initial manuscript. KHM carried out the statistical analysis and interpreted the data. SHSH drafted the initial manuscript, and reviewed the manuscript. SR was the supervisor of the study, developed the study, interpreted the results, wrote and edited the manuscript. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Acknowledgements

We gratefully acknowledge support for this work by Sarab Faculty of Medical Sciences.

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