Volume 11, Issue 2 (2023)
Health Educ Health Promot 2023, 11(2): 325-331 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Changizi M, Cheraghiyan B, Mohamadian H, Ghorbani Kalkhajeh S, Maghsoudi F, Salmanzadeh S. Effect of Applying Protection Motivation Theory in COVID-19 Information Channels on Preventive Behaviors in Southwest Iran. Health Educ Health Promot 2023; 11 (2) :325-331
URL: http://hehp.modares.ac.ir/article-5-68065-en.html
URL: http://hehp.modares.ac.ir/article-5-68065-en.html
M. Changizi * 
1, B. Cheraghiyan2, H. Mohamadian3, S. Ghorbani Kalkhajeh3, F. Maghsoudi3, Sh. Salmanzadeh4
1, B. Cheraghiyan2, H. Mohamadian3, S. Ghorbani Kalkhajeh3, F. Maghsoudi3, Sh. Salmanzadeh4
1- Department of Community Medicine, Faculty of Medicine, Abadan University of Medical Sciences, Abadan, Iran
2- “Hearing Research Center” and “Department of Biostatistics and Epidemiology, School of Public Health”, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
3- Department of Public Health, Faculty of Health, Abadan University of Medical Sciences, Abadan, Iran
4- Department of Infectious Diseases, Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
2- “Hearing Research Center” and “Department of Biostatistics and Epidemiology, School of Public Health”, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
3- Department of Public Health, Faculty of Health, Abadan University of Medical Sciences, Abadan, Iran
4- Department of Infectious Diseases, Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
Keywords: Motivation [MeSH], COVID-19 [MeSH], Health Behavior [MeSH], Information Sources [MeSH], Intention [MeSH], Fear [MeSH]
Full-Text [PDF 905 kb]
(677 Downloads)
| Abstract (HTML) (443 Views)
Full-Text: (68 Views)
Introduction
COVID-19 has devastated people's lives worldwide and has led to many deaths [1]. Iran has also been affected by COVID-19 in the Middle East and is one of the countries where this virus spread quickly [2]. Many Iranians lost their lives due to COVID-19 [3]. The World Health Organization (WHO) recommends preventive behaviors despite the approval of several vaccines to control the disease [4, 5]. Therefore, considering this issue, preventing transmission in society and public places includes health-protective behaviors such as using masks, social distancing, disinfection, regular and thorough handwashing, respiratory hygiene, etc. [6].
Gobi indicated that 99.7% of the general population wears a face mask when visiting wet markets in Malaysia [7]. In a study, 75% of the participants believed that using a mask can prevent contracting COVID-19. However, only 35% were willing to wear masks [8]. Rahimi showed the prevalence rate of face mask use was fairly low, especially in men and younger people, and the observed rates are unlikely to protect people from COVID-19 [9]. What distinguishes COVID-19 from other recent epidemics is its large-scale effect and duration the prolongation of the pandemic requires that investigations be updated [6]. The high percentage of face mask use among the general population is a good indicator of the strategy of public health measures [7]. However, proper operation and observance of these principles require sufficient awareness in this field [5]. The experiences of other infectious diseases, such as Sars and MERS, show that insufficient knowledge and negative attitudes towards this disease create a feeling of fear of the disease, which can complicate efforts to prevent the spread of the disease [10, 11].
Awareness of a disease may affect a person's attitude and intention, and the intention may turn into behavior [12]. One study found that participants had a relatively good level of knowledge, positive attitude, and good behavior about COVID-19 [10]. Another study showed that people had average knowledge about COVID-19 [13]. On the other hand, another study reported a favorable knowledge and attitude score [11]. At the same time as the spread of COVID-19, face-to-face contact was severely limited, knowledge transfer became popular online, and people had to rely on social media for news and information about COVID-19 [14]. As a result, social media quickly emerged as an important communication medium for producing, distributing, and using information [15]. Mass media and digital technologies also play an important role in addressing public health issues. A study showed that knowledge increases through social networks and the Internet, but this knowledge may be both useful and harmful [14]. The findings showed that social networks and mass media affect individual risk perception and preventive measures against Corona [11, 15]. However, actions such as improving awareness, attitude, and preventive behaviors of COVID-19 among preventive strategies are the first step in health planning [11]. The psychology of health behaviors has long examined individuals' motivation to adopt behavior changes in response to perceived threats to health. Motivating people to change their behavior to prevent the spread of the disease becomes a vital and conscientious matter [16]. Also, Experts believe that psycho-social models are an intellectual framework for educational planning [17]. The study of determinants of preventive behaviors with a clear and logical framework is very important [15].
In this regard, protection motivation theory (PMT) can be useful in identifying fears, beliefs, practices, and risk perceptions as important factors in people's responses to health behaviors [17]. PMT has been used in various studies to predict preventive behaviors [2, 18]. This theory focuses first on motivation and then on the development of adaptive skills [3]. The PMT and behavior explain the processes of cognitive mediation, threat assessment, coping assessment, and the construct of fear. Threat assessment includes the constructs of sensitivity, severity, and perceived rewards; coping assessment includes the constructs of self-efficacy, response efficacy, and perceived response costs. Fear is an intermediate variable between perceived sensitivity and threat assessment [17]. Protective motivation mediates the stages of threat assessment, coping assessment, and preventive behavior [17, 19]. Motivation is synonymous with behavioral intention. To evoke perceived protection motivation, perceived sensitivity and severity must overcome the rewards of maladaptive response (Lack of self-protection), and perceived self-efficacy must overcome the adaptive response costs ‘self-protection’ [11, 12]. In a study, it was reported that this model was able to predict 78% of the variance of disease-preventive behaviors [12]. In contrast, in another study, PMT could predict 5% of behavior [14]. It seems that to increase behavioral intention, the perceived severity of the infection should be highlighted and focus on the perception of people in performing protective behaviors. Also, at the beginning of the epidemic, fear predicted the adoption of preventive behavior, but over time, the perceived severity of the disease also showed stronger effects [20]. PMT affects individual behavior, vulnerable populations, and social distancing [21].
Considering that PMT has been validated in previous pandemic studies, the unique circumstances of COVID-19 should also lead to a critical examination of this theory in the context of a new pandemic. Therefore, it is critical to comprehensively examine PMT constructs concerning subsequent emotional reactivity and changes in behavioral patterns that have emerged during the COVID-19 outbreak. Hence, due to the prolongation of the pandemic, the importance of preventive behaviors against infectious diseases, and the lack of a study on the mediating role of theoretical constructs in protective behaviors and information sources of coronavirus, this research was conducted during the pandemic in southwestern Iran.
Instrument and Methods
In this cross-sectional descriptive study from July to August 2021, 255 patients participated. The sample size was determined based on estimating a proportion in the population (α=0.05; p=80%; z=1-α/2). The names of urban health centers of Abadan city were listed, and six were selected randomly. The list of names of subjects covered by each center was determined using the health care delivery system by a simple random method. Then, the subjects with at least a primary education level, inhabitants in the area covered by the urban health center, with no cognitive impairment were asked to come to the health center to answer the questionnaire. The participants who could not answer the questionnaire in person at the health center answered the questionnaire over the phone. Incomplete questionnaires were excluded.
The data collection tool was a researcher-made questionnaire based on PMT. The design of the protection motivation theory constructs questions was inspired by previous studies and in consultation with health education professors [18]. After designing the questions, the wording of each construct of the questionnaire according to the content validity review form was given to 8 experts (A health education professor and a PhD candidate in health education), and its content validity was checked. Its Content Validity Ratio was based on Lawshe (CVR=0.87) and the Content Validity Index according to Waltz and Bausell (CVI=0.79). Also, Cronbach's alpha test was used for reliability (α=0.880). This questionnaire included awareness questions (19 questions in the 19-57 score range), perceived sensitivity (6 questions in the 6-30 score range), perceived severity (5 questions in the 5-25 score range), internal and external rewards (6 questions in the 6-30 score range), response-cost (5 questions in the 5-25 score range), perceived response efficacy (7 questions in the 7-35 score range), self-efficacy (8 questions in the 8-40 score range), fear (7 questions in the 7-35 score range), protection motivation (10 questions in the 10-50 score range), behavior (10 questions in the 10-50 score range). The scale of awareness questions (yes-no-I do not know) was the scale of attitude (5-option Likert scale and score (1-5).
Data were analyzed by SPSS 24 software using Kruskal-Wallis, Pearson correlation, and linear regression analysis tests.
Findings
The participants were 146 (57.3%) men and 109 (42.7%) women. Diabetes was the most common disease among the subjects (Table 1).
Table 1) Some of the sociodemographic characteristics of the subjects
The knowledge scores of 32 subjects (12.5%) were moderate, and 223 (87.5%) were good. The mean score of preventive behavior was higher in women (35.36±7.48) compared to men (33.30±7.10) but was not statistically significant (p=0.593; Table 2).
Table 2) Mean and standard deviation structures of protection motivation theory
The age of the subjects was related to all constructs except perceived reward, cost and behavior. Subject education levels were associated with all constructs except cost (p<0.001). Also, marital status was related only to the perceived reward constructs (p=0.02; df=1; χ2=4.99). Subjects' jobs were associated with perceived reward, self-efficacy, protective behavior, awareness, and perceived threat (p<0.001). Economic status was related to all constructs except cost-response (p<0.001). Spearman correlation test showed that receiving news and information related to coronavirus was positively and significantly correlated with coping assessment (p<0.004; r=0.178), and motivation (p<0.001; r=0.222). There was a significant relationship between chronic disease and perceived fear and reward constructs (p<0.001). Spearman correlation test showed that protective behavior was associated with all constructs except fear and had a strong correlation with behavioral intention (p<0.001; r=0.579) and perceived response self-efficacy (p<0.001; r=0.470). Knowledge about COVID-19 was also associated with all constructs except fear and strongly correlated with perceived reward (p<0.001; r=0.405). Spearman correlation matrix of PMT constructs is shown in Table 3.
Table 3) Spearman correlation coefficient matrix of PMT theory constructs regarding COVID-19 protective behaviors
"Washing hands regularly with soap and water for 20 seconds" (51%), "covering the face with a paper towel or elbow or when sneezing or coughing" (39.2%), "keeping a distance of 1.5 meters with others" (33.3%), "referring for a corona test if you have symptoms" (18.4%), "disinfecting hand-contact surfaces at work" (14.1%), "using a mask when confronting a person suspected of having a corona" (55.7%), "opening of workplace windows for ventilation intermittently"(20%), "disinfecting personal items such as mobile phones, keys, bank cards, etc." (9%), "non-touching contaminated and disinfected hands with a mask" (22.4%) and "presence in crowded places "(28.2%) were the perpetual observance by individuals.
Knowledge predicted 11% (R=0.337; R2=0.113; p<0.001; CI=0.427-0.879) of protective behavior, and demographic parameters predicted 17.9% (R=0.423; R2=0.179; p<0.001) of PMT constructs variance. The subjects' education level was the strongest predictor of the structures of protection motivation theory (Table 4).
Table 4) Liner regression analysis of demographic variables as predictors of PMT constructs
All constructs of PMT, except perceived response cost, sensitivity, and perceived severity, predicted protective behavior (p<0.001; R=0.495; R2=0.487). In general, the constructs of this theory predicted 49.5% of the variance of protective behavior, and that protection motivation (behavioral intention) was the strongest predictor of behavior. Linear regression analysis also showed that in total, 37.5% of the model constructs predicted protective motivation (behavioral intention) against COVID-19 (p<0.001; R=0.375; R2=0.367) among which the evaluation of coping was a strong predictor of protection motivation (Table 5).
Table 5) The regression analysis of PMT structures as predictors of protective behaviorپ
Discussion
This study aimed to evaluate the constructs of the PMT model in preventive behaviors against COVID-19 and the effect of the media in receiving information related to COVID-19. The results of the present study showed that half of the patients had moderate preventive performance, and the other half had a good performance. However, few people have always practiced healthy behaviors. Our research findings are similar to other studies [11, 18]. This may be due to reduced restrictions and health messages, simplification, and mortality due to COVID-19.
In the present study, demographic variables were related to PMT model constructs. The present results showed that there is a significant relationship between age and some constructs of the PMT model. In other words, older people are more likely to understand perceived awareness and threats. In general, threat information can significantly influence people's threat appraisals and emotions (Fear and anxiety), which can also be influenced by people's personalities and previous experiences [22]. In addition, perceived severity is age-related and is higher among the elderly than the young [23]. Women also had better protective performance than men. The results of the Mortada study support the present study's findings [24]. This difference may be related to society, social norms, and women's responsibilities. From this perspective, programs are needed to fill this gap and strengthen preventive behavior [25, 5].
In the present study, participants received more corona-related news from mass media and social networks. People search and share information during epidemics. Also, the use of social media continues to increase its popularity due to the facilities provided by their platforms for exchanging information, opinions, and activities [26]. Liu reported that social media influences audience perceptions of threats and enhances self-efficacy in disseminating COVID-19 information [14]. Social media information can have positive and negative effects [26, 27]. Threat assessment is attractive in health messages and may affect people's attitudes [14, 28-30]. However, experimental results regarding the fear appeal's effectiveness are inconclusive [31]. The source of information also had a stronger correlation with motivation (Behavioral intention). The mass media has a large audience, and their training may affect people's intentions to change behavior. It is possible that emotional attitudes, along with perceiving the threat posed by trust in new media, can positively affect the intention to take protective measures during a health crisis [4, 24]. Media use seems to be associated with self-efficacy and preventive behaviors [4, 24, 27].
In the present study, demographic variables predicted the constructs of the protection motivation theory against COVID-19; among them, the level of education is the stronger predictor. Education seems to play a role in disease prevention to control disease transmission and empower individuals [32, 33]. protective behavior in this study was associated with all constructs except fear. Our results are inconsistent with Khazaei et al. [18].
In the present study, most subjects had good knowledge. Health education seems to have had a positive effect [32]. However, knowledge could predict protective behavior to some extent and had a high correlation with perceived reward. Further awareness seems to lead to a better understanding of the benefits of preventive behavior [33]. The present study's results showed a correlation between preventive behaviors against COVID-19 and all constructs except fear. Despite reporting a positive relationship between fear, attitude, and performance in other studies, the present study did not confirm this relationship [34].
In our study, behavioral intent showed a stronger association with behavior. The intention is considered a representative close to the behavior itself. As a person becomes more motivated to take preventive behavior against COVID-19, he or she is more likely to do so [2]. In the present study, fear, protective motivation, threat assessment, and coping assessment predicted approximately half the probability of preventive behavior occurring against COVID-19, with protective motivation (Intention) being the strongest predictor of behavior and similar to other studies [24, 35]. The role of coping assessment in this prediction was more than threat assessment. This means that people should feel threatened and feel they can do something about it. Theoretically, a high-threat assessment should lead to negative arousal, coping, and increased psychological symptoms. However, one study found that among individuals with low coping assessments, high-threat assessments could be interpreted as "unprotected" behaviors and inappropriate responses such as denial or avoidance [36]. In addition, the coping assessment had a strong effect on intention and, compared to other constructs, better-predicted protection motivation and was consistent with the study of others [23, 24, 28]. In general, Lin et al. [37] and Quandt et al. [38] identified self-efficacy and coping to perform a preventive behavior as the most critical construct in the context of appropriate behaviors against COVID-19. If the ability to fight the disease increases, the motivation and intention to take protective action against COVID-19 will also increase. It seems this research contributes to the public health crisis literature and its better management.
Although some studies have used the PMT model, the present study is the first to be conducted in southwestern Iran since the beginning of the COVID-19 pandemic to investigate different constructs affecting behavior and behavioral motivation. The present study also provides insights into the role of fear and self-efficacy and mass and social media in performing protective behavior against COVID-19. However, due to the self-reporting data collection tool, the answers may be exaggerated in some constructs, and the number of people with stable health behavior in this study was low. In our study, knowledge and behavior are in the same direction. Also, news sources may be able to influence the intent to perform protective behaviors and coping skills, and rewards of maladaptive behaviors and fear are negative predictors of protective behaviors against COVID-19. However, fear alone does not change behavior and can be a powerful tool to create fearsome campaigns. Protection motivation (Intent) also played an important role in observing the preventive behavior of COVID-19. In contrast, the coping assessment affected protection motivation. Finally, using appropriate coping techniques, strengthening news sources (Mass and social media) and, gaining people's trust, continuing to send educational materials until the end of the pandemic and the disappearance of coronavirus in the target population may help maintain conservative behavior and vaccination.
Conclusion
Protection motivation theory is effective in predicting protective behavior against COVID-19 infection.
Acknowledgment: We appreciate all the subjects and urban health center staff.
Ethical Permissions: Because data collection was through a questionnaire and there was no risk to life, informed consent was not obtained.
Conflicts of Interests: The authors have no conflicts of interest.
Authors’ Contribution: Changizi M (First Author), Introduction Writer/Main Researcher/Statistical Analyst/Discussion Writer (60%); Cheraghian B (Second Author), Assistant Researcher (10%); Mohamadian H (Third Author), Assistant Researcher (15%); Ghorbani Kalkhajeh S (Fourth Author), Assistant Researcher/Writer (5%); Maghsoudi F. (Fifth Author), Assistant Researcher/Statistical Analyst (5%); Salmanzadeh Sh (Sixth Author), Assistant Researcher (5%)
Funding/Support: This research was supported by the Deputy for Research Abadan University of Medical Sciences (No. 790).
COVID-19 has devastated people's lives worldwide and has led to many deaths [1]. Iran has also been affected by COVID-19 in the Middle East and is one of the countries where this virus spread quickly [2]. Many Iranians lost their lives due to COVID-19 [3]. The World Health Organization (WHO) recommends preventive behaviors despite the approval of several vaccines to control the disease [4, 5]. Therefore, considering this issue, preventing transmission in society and public places includes health-protective behaviors such as using masks, social distancing, disinfection, regular and thorough handwashing, respiratory hygiene, etc. [6].
Gobi indicated that 99.7% of the general population wears a face mask when visiting wet markets in Malaysia [7]. In a study, 75% of the participants believed that using a mask can prevent contracting COVID-19. However, only 35% were willing to wear masks [8]. Rahimi showed the prevalence rate of face mask use was fairly low, especially in men and younger people, and the observed rates are unlikely to protect people from COVID-19 [9]. What distinguishes COVID-19 from other recent epidemics is its large-scale effect and duration the prolongation of the pandemic requires that investigations be updated [6]. The high percentage of face mask use among the general population is a good indicator of the strategy of public health measures [7]. However, proper operation and observance of these principles require sufficient awareness in this field [5]. The experiences of other infectious diseases, such as Sars and MERS, show that insufficient knowledge and negative attitudes towards this disease create a feeling of fear of the disease, which can complicate efforts to prevent the spread of the disease [10, 11].
Awareness of a disease may affect a person's attitude and intention, and the intention may turn into behavior [12]. One study found that participants had a relatively good level of knowledge, positive attitude, and good behavior about COVID-19 [10]. Another study showed that people had average knowledge about COVID-19 [13]. On the other hand, another study reported a favorable knowledge and attitude score [11]. At the same time as the spread of COVID-19, face-to-face contact was severely limited, knowledge transfer became popular online, and people had to rely on social media for news and information about COVID-19 [14]. As a result, social media quickly emerged as an important communication medium for producing, distributing, and using information [15]. Mass media and digital technologies also play an important role in addressing public health issues. A study showed that knowledge increases through social networks and the Internet, but this knowledge may be both useful and harmful [14]. The findings showed that social networks and mass media affect individual risk perception and preventive measures against Corona [11, 15]. However, actions such as improving awareness, attitude, and preventive behaviors of COVID-19 among preventive strategies are the first step in health planning [11]. The psychology of health behaviors has long examined individuals' motivation to adopt behavior changes in response to perceived threats to health. Motivating people to change their behavior to prevent the spread of the disease becomes a vital and conscientious matter [16]. Also, Experts believe that psycho-social models are an intellectual framework for educational planning [17]. The study of determinants of preventive behaviors with a clear and logical framework is very important [15].
In this regard, protection motivation theory (PMT) can be useful in identifying fears, beliefs, practices, and risk perceptions as important factors in people's responses to health behaviors [17]. PMT has been used in various studies to predict preventive behaviors [2, 18]. This theory focuses first on motivation and then on the development of adaptive skills [3]. The PMT and behavior explain the processes of cognitive mediation, threat assessment, coping assessment, and the construct of fear. Threat assessment includes the constructs of sensitivity, severity, and perceived rewards; coping assessment includes the constructs of self-efficacy, response efficacy, and perceived response costs. Fear is an intermediate variable between perceived sensitivity and threat assessment [17]. Protective motivation mediates the stages of threat assessment, coping assessment, and preventive behavior [17, 19]. Motivation is synonymous with behavioral intention. To evoke perceived protection motivation, perceived sensitivity and severity must overcome the rewards of maladaptive response (Lack of self-protection), and perceived self-efficacy must overcome the adaptive response costs ‘self-protection’ [11, 12]. In a study, it was reported that this model was able to predict 78% of the variance of disease-preventive behaviors [12]. In contrast, in another study, PMT could predict 5% of behavior [14]. It seems that to increase behavioral intention, the perceived severity of the infection should be highlighted and focus on the perception of people in performing protective behaviors. Also, at the beginning of the epidemic, fear predicted the adoption of preventive behavior, but over time, the perceived severity of the disease also showed stronger effects [20]. PMT affects individual behavior, vulnerable populations, and social distancing [21].
Considering that PMT has been validated in previous pandemic studies, the unique circumstances of COVID-19 should also lead to a critical examination of this theory in the context of a new pandemic. Therefore, it is critical to comprehensively examine PMT constructs concerning subsequent emotional reactivity and changes in behavioral patterns that have emerged during the COVID-19 outbreak. Hence, due to the prolongation of the pandemic, the importance of preventive behaviors against infectious diseases, and the lack of a study on the mediating role of theoretical constructs in protective behaviors and information sources of coronavirus, this research was conducted during the pandemic in southwestern Iran.
Instrument and Methods
In this cross-sectional descriptive study from July to August 2021, 255 patients participated. The sample size was determined based on estimating a proportion in the population (α=0.05; p=80%; z=1-α/2). The names of urban health centers of Abadan city were listed, and six were selected randomly. The list of names of subjects covered by each center was determined using the health care delivery system by a simple random method. Then, the subjects with at least a primary education level, inhabitants in the area covered by the urban health center, with no cognitive impairment were asked to come to the health center to answer the questionnaire. The participants who could not answer the questionnaire in person at the health center answered the questionnaire over the phone. Incomplete questionnaires were excluded.
The data collection tool was a researcher-made questionnaire based on PMT. The design of the protection motivation theory constructs questions was inspired by previous studies and in consultation with health education professors [18]. After designing the questions, the wording of each construct of the questionnaire according to the content validity review form was given to 8 experts (A health education professor and a PhD candidate in health education), and its content validity was checked. Its Content Validity Ratio was based on Lawshe (CVR=0.87) and the Content Validity Index according to Waltz and Bausell (CVI=0.79). Also, Cronbach's alpha test was used for reliability (α=0.880). This questionnaire included awareness questions (19 questions in the 19-57 score range), perceived sensitivity (6 questions in the 6-30 score range), perceived severity (5 questions in the 5-25 score range), internal and external rewards (6 questions in the 6-30 score range), response-cost (5 questions in the 5-25 score range), perceived response efficacy (7 questions in the 7-35 score range), self-efficacy (8 questions in the 8-40 score range), fear (7 questions in the 7-35 score range), protection motivation (10 questions in the 10-50 score range), behavior (10 questions in the 10-50 score range). The scale of awareness questions (yes-no-I do not know) was the scale of attitude (5-option Likert scale and score (1-5).
Data were analyzed by SPSS 24 software using Kruskal-Wallis, Pearson correlation, and linear regression analysis tests.
Findings
The participants were 146 (57.3%) men and 109 (42.7%) women. Diabetes was the most common disease among the subjects (Table 1).
Table 1) Some of the sociodemographic characteristics of the subjects
The knowledge scores of 32 subjects (12.5%) were moderate, and 223 (87.5%) were good. The mean score of preventive behavior was higher in women (35.36±7.48) compared to men (33.30±7.10) but was not statistically significant (p=0.593; Table 2).
Table 2) Mean and standard deviation structures of protection motivation theory
The age of the subjects was related to all constructs except perceived reward, cost and behavior. Subject education levels were associated with all constructs except cost (p<0.001). Also, marital status was related only to the perceived reward constructs (p=0.02; df=1; χ2=4.99). Subjects' jobs were associated with perceived reward, self-efficacy, protective behavior, awareness, and perceived threat (p<0.001). Economic status was related to all constructs except cost-response (p<0.001). Spearman correlation test showed that receiving news and information related to coronavirus was positively and significantly correlated with coping assessment (p<0.004; r=0.178), and motivation (p<0.001; r=0.222). There was a significant relationship between chronic disease and perceived fear and reward constructs (p<0.001). Spearman correlation test showed that protective behavior was associated with all constructs except fear and had a strong correlation with behavioral intention (p<0.001; r=0.579) and perceived response self-efficacy (p<0.001; r=0.470). Knowledge about COVID-19 was also associated with all constructs except fear and strongly correlated with perceived reward (p<0.001; r=0.405). Spearman correlation matrix of PMT constructs is shown in Table 3.
Table 3) Spearman correlation coefficient matrix of PMT theory constructs regarding COVID-19 protective behaviors
"Washing hands regularly with soap and water for 20 seconds" (51%), "covering the face with a paper towel or elbow or when sneezing or coughing" (39.2%), "keeping a distance of 1.5 meters with others" (33.3%), "referring for a corona test if you have symptoms" (18.4%), "disinfecting hand-contact surfaces at work" (14.1%), "using a mask when confronting a person suspected of having a corona" (55.7%), "opening of workplace windows for ventilation intermittently"(20%), "disinfecting personal items such as mobile phones, keys, bank cards, etc." (9%), "non-touching contaminated and disinfected hands with a mask" (22.4%) and "presence in crowded places "(28.2%) were the perpetual observance by individuals.
Knowledge predicted 11% (R=0.337; R2=0.113; p<0.001; CI=0.427-0.879) of protective behavior, and demographic parameters predicted 17.9% (R=0.423; R2=0.179; p<0.001) of PMT constructs variance. The subjects' education level was the strongest predictor of the structures of protection motivation theory (Table 4).
Table 4) Liner regression analysis of demographic variables as predictors of PMT constructs
All constructs of PMT, except perceived response cost, sensitivity, and perceived severity, predicted protective behavior (p<0.001; R=0.495; R2=0.487). In general, the constructs of this theory predicted 49.5% of the variance of protective behavior, and that protection motivation (behavioral intention) was the strongest predictor of behavior. Linear regression analysis also showed that in total, 37.5% of the model constructs predicted protective motivation (behavioral intention) against COVID-19 (p<0.001; R=0.375; R2=0.367) among which the evaluation of coping was a strong predictor of protection motivation (Table 5).
Table 5) The regression analysis of PMT structures as predictors of protective behaviorپ
Discussion
This study aimed to evaluate the constructs of the PMT model in preventive behaviors against COVID-19 and the effect of the media in receiving information related to COVID-19. The results of the present study showed that half of the patients had moderate preventive performance, and the other half had a good performance. However, few people have always practiced healthy behaviors. Our research findings are similar to other studies [11, 18]. This may be due to reduced restrictions and health messages, simplification, and mortality due to COVID-19.
In the present study, demographic variables were related to PMT model constructs. The present results showed that there is a significant relationship between age and some constructs of the PMT model. In other words, older people are more likely to understand perceived awareness and threats. In general, threat information can significantly influence people's threat appraisals and emotions (Fear and anxiety), which can also be influenced by people's personalities and previous experiences [22]. In addition, perceived severity is age-related and is higher among the elderly than the young [23]. Women also had better protective performance than men. The results of the Mortada study support the present study's findings [24]. This difference may be related to society, social norms, and women's responsibilities. From this perspective, programs are needed to fill this gap and strengthen preventive behavior [25, 5].
In the present study, participants received more corona-related news from mass media and social networks. People search and share information during epidemics. Also, the use of social media continues to increase its popularity due to the facilities provided by their platforms for exchanging information, opinions, and activities [26]. Liu reported that social media influences audience perceptions of threats and enhances self-efficacy in disseminating COVID-19 information [14]. Social media information can have positive and negative effects [26, 27]. Threat assessment is attractive in health messages and may affect people's attitudes [14, 28-30]. However, experimental results regarding the fear appeal's effectiveness are inconclusive [31]. The source of information also had a stronger correlation with motivation (Behavioral intention). The mass media has a large audience, and their training may affect people's intentions to change behavior. It is possible that emotional attitudes, along with perceiving the threat posed by trust in new media, can positively affect the intention to take protective measures during a health crisis [4, 24]. Media use seems to be associated with self-efficacy and preventive behaviors [4, 24, 27].
In the present study, demographic variables predicted the constructs of the protection motivation theory against COVID-19; among them, the level of education is the stronger predictor. Education seems to play a role in disease prevention to control disease transmission and empower individuals [32, 33]. protective behavior in this study was associated with all constructs except fear. Our results are inconsistent with Khazaei et al. [18].
In the present study, most subjects had good knowledge. Health education seems to have had a positive effect [32]. However, knowledge could predict protective behavior to some extent and had a high correlation with perceived reward. Further awareness seems to lead to a better understanding of the benefits of preventive behavior [33]. The present study's results showed a correlation between preventive behaviors against COVID-19 and all constructs except fear. Despite reporting a positive relationship between fear, attitude, and performance in other studies, the present study did not confirm this relationship [34].
In our study, behavioral intent showed a stronger association with behavior. The intention is considered a representative close to the behavior itself. As a person becomes more motivated to take preventive behavior against COVID-19, he or she is more likely to do so [2]. In the present study, fear, protective motivation, threat assessment, and coping assessment predicted approximately half the probability of preventive behavior occurring against COVID-19, with protective motivation (Intention) being the strongest predictor of behavior and similar to other studies [24, 35]. The role of coping assessment in this prediction was more than threat assessment. This means that people should feel threatened and feel they can do something about it. Theoretically, a high-threat assessment should lead to negative arousal, coping, and increased psychological symptoms. However, one study found that among individuals with low coping assessments, high-threat assessments could be interpreted as "unprotected" behaviors and inappropriate responses such as denial or avoidance [36]. In addition, the coping assessment had a strong effect on intention and, compared to other constructs, better-predicted protection motivation and was consistent with the study of others [23, 24, 28]. In general, Lin et al. [37] and Quandt et al. [38] identified self-efficacy and coping to perform a preventive behavior as the most critical construct in the context of appropriate behaviors against COVID-19. If the ability to fight the disease increases, the motivation and intention to take protective action against COVID-19 will also increase. It seems this research contributes to the public health crisis literature and its better management.
Although some studies have used the PMT model, the present study is the first to be conducted in southwestern Iran since the beginning of the COVID-19 pandemic to investigate different constructs affecting behavior and behavioral motivation. The present study also provides insights into the role of fear and self-efficacy and mass and social media in performing protective behavior against COVID-19. However, due to the self-reporting data collection tool, the answers may be exaggerated in some constructs, and the number of people with stable health behavior in this study was low. In our study, knowledge and behavior are in the same direction. Also, news sources may be able to influence the intent to perform protective behaviors and coping skills, and rewards of maladaptive behaviors and fear are negative predictors of protective behaviors against COVID-19. However, fear alone does not change behavior and can be a powerful tool to create fearsome campaigns. Protection motivation (Intent) also played an important role in observing the preventive behavior of COVID-19. In contrast, the coping assessment affected protection motivation. Finally, using appropriate coping techniques, strengthening news sources (Mass and social media) and, gaining people's trust, continuing to send educational materials until the end of the pandemic and the disappearance of coronavirus in the target population may help maintain conservative behavior and vaccination.
Conclusion
Protection motivation theory is effective in predicting protective behavior against COVID-19 infection.
Acknowledgment: We appreciate all the subjects and urban health center staff.
Ethical Permissions: Because data collection was through a questionnaire and there was no risk to life, informed consent was not obtained.
Conflicts of Interests: The authors have no conflicts of interest.
Authors’ Contribution: Changizi M (First Author), Introduction Writer/Main Researcher/Statistical Analyst/Discussion Writer (60%); Cheraghian B (Second Author), Assistant Researcher (10%); Mohamadian H (Third Author), Assistant Researcher (15%); Ghorbani Kalkhajeh S (Fourth Author), Assistant Researcher/Writer (5%); Maghsoudi F. (Fifth Author), Assistant Researcher/Statistical Analyst (5%); Salmanzadeh Sh (Sixth Author), Assistant Researcher (5%)
Funding/Support: This research was supported by the Deputy for Research Abadan University of Medical Sciences (No. 790).
Article Type: Descriptive & Survey |
Subject:
Health Education and Health Behavior
Received: 2023/03/14 | Accepted: 2023/06/13 | Published: 2023/07/15
Received: 2023/03/14 | Accepted: 2023/06/13 | Published: 2023/07/15
References
1. Kuldeep D, Sharun KH, Ruchi T, Shubhankar S, Sudipta B, Yashpal Singh M, et al. Coronavirus Disease 2019-COVID-19. Clin Microbiol Revi. 2020;33(4):e00028-20. [Link] [DOI:10.1128/CMR.00028-20]
2. Bashirian S, Jenabi E, Khazaei S, Barati M, Karimi-Shahanjarini A, Zareian S, et al. Factors associated with preventive behaviours of COVID-19 among hospital staff in Iran in 2020: An application of the Protection Motivation Theory. J Hosp Infect. 2020;105(3):430-3. [Link] [DOI:10.1016/j.jhin.2020.04.035]
3. Chung JY, Thone MN, Kwon YJ. COVID-19 vaccines: The status and perspectives in delivery points of view. Adv Drug Deliv Rev. 2021;170:1-25. [Link] [DOI:10.1016/j.addr.2020.12.011]
4. Farooq A, Laato S, Islam AKMN, Isoaho J. Understanding the impact of information sources on COVID-19 related preventive measures in Finland. Technol Soc. 2021;65:101573. [Link] [DOI:10.1016/j.techsoc.2021.101573]
5. Azadeh MR, Ramezani T, Taheri kharameh Z. Investigating the factors affecting protective behaviors in the workplace of COVID-19 disease in employees of frequent departments in Qom: Application of protection motivation theory. Iran Occupational Health J. 2020;17(1):115-25. [Persian] [Link]
6. Duan Y, Shang B, Liang W, Lin Z, Hu C, Baker JS, et al. Predicting hand washing, mask wearing and social distancing behaviors among older adults during the COVID-19 pandemic: An integrated social cognition model. BMC Geriatr. 2022;22(1):91. [Link] [DOI:10.1186/s12877-022-02785-2]
7. Gobi Hariyanayagam G, Sera Selvanthansundram G, Shargunan Selvanthan G, Nur Syafina Insyirah Binti Z, Nor Amirah Binti Abdul H. Prevalence of facemask use among general public when visiting wet market during COVID-19 pandemic: An observational study. MedRxiv. 2020:2020. [Link] [DOI:10.2196/preprints.20555]
8. Hafeez A, Ahmad S, Siddqui SA, Ahmad M, Mishra S. A review of COVID-19 (Coronavirus Disease-2019) diagnosis, treatments and prevention. EJMO. 2020;4(2):116-25. [Link]
9. Rahimi Z, Shirali GA, Araban M, Mohammadi MJ, Cheraghian B. Mask use among pedestrians during the COVID-19 pandemic in Southwest Iran: An observational study on 10,440 people. BMC Public Health. 2021;21(1):133. [Link] [DOI:10.1186/s12889-020-10152-2]
10. Kim J, Yang K, Min J, White B. Hope, fear and consumer behavioral change amid COVID-19: Application of protection motivation theory. Int J Consum Stud. 2022;46(2):558-74 [Link] [DOI:10.1111/ijcs.12700]
11. Zhong BL, Luo W, Li HM, Zhang QQ, Liu XG, Li WT, et al. Knowledge, attitudes, and practices towards COVID-19 among Chinese residents during the rapid rise period of the COVID-19 outbreak: A quick online cross-sectional survey. Int J Biol Sci. 2020;16:1745-52. [Link] [DOI:10.7150/ijbs.45221]
12. McEachan R, Taylor N, Harrison R, Lawton R, Gardner P, Conner M. Meta-analysis of the reasoned action approach (RAA) to understanding health behaviors. Ann Behav Med. 2016;50(4):592-612. [Link] [DOI:10.1007/s12160-016-9798-4]
13. Kundu S, Al Banna MH, Sayeed A, Begum MR, Brazendale K, Hasan MT, et al. Knowledge, attitudes, and preventive practices toward the COVID-19 pandemic: an online survey among Bangladeshi residents. Z Gesundh Wiss. 2021:1-15. [Link] [DOI:10.1007/s10389-021-01636-5]
14. Liu P. COVID-19 information on social media and preventive behaviors: Managing the pandemic through personal responsibility. Soc Sci Med. 2021;277:113928. [Link] [DOI:10.1016/j.socscimed.2021.113928]
15. Gao J, Zheng P, Jia Y, Chen H, Mao Y, Chen S, et al. Mental health problems and social media exposure during COVID-19 outbreak. Plos one. 2020;15(4):e0231924. [Link] [DOI:10.1371/journal.pone.0231924]
16. Al-Rasheed M. Protective behavior against COVID-19 among the public in Kuwait: An examination of the protection motivation theory, trust in government and sociodemographic factors. Soc Work Public Health. 2020;35(7):546-56. [Link] [DOI:10.1080/19371918.2020.1806171]
17. Rogers WR. A protection motivation theory of fear appeals and attitude change1. J Psychol. 1975;91(1):93-114. [Link] [DOI:10.1080/00223980.1975.9915803]
18. Khazaee-Pool M, Naghibi M, Pashaei T, Chaleshgar Kordasiabi M. Use of protection motivation theory to assess preventive behaviors of COVID-19. J Mazandaran Univ Med Sci. 2021;31(195):19-29. [Persian] [Link]
19. Pothisa T, Ong-Artborirak P, Seangpraw K, Tonchoy P, Kantow S, Auttama N, et al. Knowledge of COVID-19 and its relationship with preventive behaviors and vaccination among adults in Northern Thailand's community. Int J Environ Res Public Health. 2022;19(3):1521. [Link] [DOI:10.3390/ijerph19031521]
20. Grano C, Singh Solorzano C, Di Pucchio A. Predictors of protective behaviours during the Italian COVID-19 pandemic: An application of protection motivation theory. Psychol Health. 2022;37(12):1584-604. [Link] [DOI:10.1080/08870446.2022.2062355]
21. Yeom M, Stewart F, Stewart A. The impact of social distancing on community case count in the United States: Testing the efficacy of protection motivation theory during early stages of the COVID-19 pandemic. Risk Hazards Crisis Public Policy. 2021;12(3):303-27. [Link] [DOI:10.1002/rhc3.12232]
22. Wu G, Deng X, Liu B. Using fear appeal theories to understand the effects of location information of patients on citizens during the COVID-19 pandemic. Curr Psychol. 2021:1-13. [Link] [DOI:10.1007/s12144-021-01953-8]
23. Ezati Rad R, Mohseni Sh, Kamalzadeh TH, Hassani Azad M, Shahabi N, Aghamolaei T, et al. Application of the protection motivation theory for predicting COVID-19 preventive behaviors in Hormozgan, Iran: A cross-sectional study. BMC Public Health. 2021;21(1):466. [Link] [DOI:10.1186/s12889-021-10500-w]
24. Mortada E, Abdel Azeem A, Al Showair A, Zalat MM. Preventive behaviors towards COVID-19 pandemic among healthcare providers in Saudi Arabia using the protection motivation theory. Risk Manag Healthc Policy. 2021;14:685-94. [Link] [DOI:10.2147/RMHP.S289837]
25. Moran KR, Valle SYD. A meta-analysis of the association between gender and protective behaviors in response to respiratory epidemics and pandemics. PLoS One. 2016;11(10):e0164541. [Link] [DOI:10.1371/journal.pone.0164541]
26. Eke PI. Using social media for research and public health surveillance. J Dental Res. 2011;90(9):1045. [Link] [DOI:10.1177/0022034511415277]
27. Mahmood QK, Jafree Razavi S, Mukhtar S, Fischer F. Social media use, self-efficacy, perceived threat, and preventive behavior in times of COVID-19: Results of a cross-sectional study in Pakistan. Front Psychol. 2021;12:12:562042. [Link] [DOI:10.3389/fpsyg.2021.562042]
28. Vai B, Cazzetta S, Ghiglino D, Parenti L, Saibene G, Toti M, et al. Risk perception and media in shaping protective behaviors: Insights from the early phase of COVID-19 Italian outbreak. Front Psychol. 2020;11:563426. [Link] [DOI:10.3389/fpsyg.2020.563426]
29. Hunt DM, Shehryar O. Integrating terror management theory into fear appeal research. Soc Pers Psychol Compass. 2011;5(6):372-82. [Link] [DOI:10.1111/j.1751-9004.2011.00354.x]
30. Diaz Quijano FA, Martínez Vega RA, Rodriguez Morales AJ, Rojas Calero RA, Luna González ML, Díaz Quijano RG. Association between the level of education and knowledge, attitudes and practices regarding dengue in the Caribbean region of Colombia. BMC Public Health. 2018;18(1):143. [Link] [DOI:10.1186/s12889-018-5055-z]
31. Wang PW, Ko N, Chang YP, Wu CF, Lu WH, Yen CF. Subjective deterioration of physical and psychological health during the COVID-19 pandemic in Taiwan: Their association with the adoption of protective behaviors and mental health problems. Int J Environ Res Public Health. 2020;17(18):6827. [Link] [DOI:10.3390/ijerph17186827]
32. Karijo E, Wamugi S, Lemanyishoe S, Njuki J, Boit F, Kibui V, et al. Knowledge, attitudes, practices, and the effects of COVID-19 among the youth in Kenya. BMC Public Health. 2021;21(1):1020. [Link] [DOI:10.1186/s12889-021-11067-2]
33. Nasirzadeh M, Aligol M. Assessment of Knowledge, Attitude, and Factors Associated with the Preventive Behaviors of COVID-19 in Qom, Iran, in 2020. Qom Univ Med Sci J. 2020;14(7):50-7. [Persian] [Link] [DOI:10.29252/qums.14.7.50]
34. Mohammadi Zeidi I, Mohammadi Zeidi B, Mirzaie S. Relationship between Fear, Attitude and Knowledge, and COVID-19 Preventive Behaviors in Dentists. J Babol Univ Med Sci. 2021;23(1):352-8. [Persian] [Link]
35. Chamroonsawasdi K, Chottanapund S, Pamungkas RA, Tunyasitthisundhorn P, Sornpaisarn B, Numpaisan O. Protection motivation theory to predict intention of healthy eating and sufficient physical activity to prevent Diabetes Mellitus in Thai population: A path analysis. Diabetes Metab Syndr. 2021;15(1):121-7. [Link] [DOI:10.1016/j.dsx.2020.12.017]
36. Oakley M, Himmelweit SM, Leinster P, Casado MR. Protection motivation theory: A proposed theoretical extension and moving beyond rationality- the case of flooding. Water. 2020;12(7):1848. [Link] [DOI:10.3390/w12071848]
37. Lin CY, Imani V, Rajabi Majd N, Ghasemi Z, Griffiths MD, Hamilton K, et al. Using an integrated social cognition model to predict COVID‐19 preventive behaviours. Br J Health Psychol. 2020;25(4):981-1005. [Link] [DOI:10.1111/bjhp.12465]
38. Quandt SA, LaMonto NJ, Mora DC, Talton JW, Laurienti Paul J, Arcury AT. COVID-19 pandemic among Latinx farmworker and nonfarmworker families in North Carolina: knowledge, risk perceptions, and preventive behaviors. Int J Environ Res Public Health. 2020;17(16):5786. [Link] [DOI:10.3390/ijerph17165786]
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |