Volume 17 - Special Issue: COVID-19
ioh 2020, 17 - Special Issue: COVID-19: 115-125 |
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Azadeh M, 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. ioh 2020; 17 (S1) :115-125
URL: http://ioh.iums.ac.ir/article-1-3115-en.html
URL: http://ioh.iums.ac.ir/article-1-3115-en.html
Spiritual Health Research Center, School of Paramedical Sciences, Qom University of Medical Sciences, Qom, Iran , ztaheri@muq.ac.ir
Abstract: (2818 Views)
Abstract
Background and aims: Nowadays, Covid-19 is considered as a pandemic. According to the World Health Organization (WHO), as of March 25, 2020, in more than 156 countries, about 664,731,000 new cases of the disease and 30,892 deaths were reported. Iran is one of the countries with the highest incidence. Although there is a possibility of occupational accident in all health care provision environments, the offices is the main dangerous health care provider in terms of occupational infections in health systems. Ensuring the safety of employees in offices is not only crucial in protecting them against the virus but also in preventing the transmission of the virus. Protective behaviors are effective in prevention of occurrence of the disease. Protection motivation theory (PMT) helps to understand preventive behaviors better and can be used in occupational injury training programs. Considering the importance of identifying the factors of the preventive behaviours of Covid-19 in the development and implementation of preventive programs, this study was conducted for predicting the preventive behaviour againt Covid-19 based on the PMT among employees in crowded offices in Qom, Iran.
Methods: In this cross sectional study, 232 employees in crowded offices in Qom, Iran have been selected using random clustering sampling method. Data collection instrument included demographic characteristics, protective behaviors against Covid-19, and PMT scale. The PMT constructs were assessed by questions composed and 7 subscales as follows: perceived vulnerability (2 items); perceived severity (2 items); perceived fear (2 items); self-efficacy (3 items); response efficacy (3 items); response cost (2 items); and protection motivation (1 items). The items were rated on a five-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). According to the theoretical assumptions, the threat appraisal score is the sum of the perceived susceptibility and severity scores. Also, the coping appraisal score is the sum of the self-efficacy and response efficacy scores minus the response cost score. Eight items scale by a three-point rated ‘always’, ‘sometimes’ and ‘never scored 2, 1 and 0, respectively measured Covid-19 preventive behaviours. The validity of the scale was confirmed using the viewpoints of health-education experts. The reliability of the scale was investigated by calculating internal consistency. Data have been analyzed via descriptive statistics and structural equations through SmartPLS statistical software. In the structural model, path coefficient, and R square were used to measure relationships among constructs. The predictive power of the model was examined by calculating Q2 indexes of behavior. Finally, a goodness of fit (GoF) index was calculated to display the model fit to the model.
Results: Mean and standard deviation of participants’ age has been 39.8
8.7; and, 90.1% of them have been male. More than half of participants (53.8%) have shown protective behaviors higher than average. There has been a significant relationship between coping appraisal and protection motivation ( 
=0.297 and p-value˂0.05). However, there has been no significant relationship between threat appraisal and fear constructs and protection motivation ( =0.060 and p-value>0.05). Also, there has been significant positive relationship between protection motivation and protective behaviors ( =0.214 and p-value˂0.05). Fit indices of the model have been desirable and the model could predict overall 5% of changes in performing protective behaviors. GoF was 0.503, indicating the model good fit.
Conclusion: According to the results, coping appraisals were identified to be the significant positive associations with protection motivation. Contrary to the expectations based on the PMT, it is generally seen that none of the threat appraisals (severity, vulnerability, and fear) predicted protection motivation and preventive behaviour against Covid-19. Protection motivation is predictor factor of the protective behaviors. The results can be used in formulating training programs to optimize protective behaviors among employees working in offices.
Keywords: Protective Behaviors, Covid-19, Protective Motivation, Employees
Background and aims: Nowadays, Covid-19 is considered as a pandemic. According to the World Health Organization (WHO), as of March 25, 2020, in more than 156 countries, about 664,731,000 new cases of the disease and 30,892 deaths were reported. Iran is one of the countries with the highest incidence. Although there is a possibility of occupational accident in all health care provision environments, the offices is the main dangerous health care provider in terms of occupational infections in health systems. Ensuring the safety of employees in offices is not only crucial in protecting them against the virus but also in preventing the transmission of the virus. Protective behaviors are effective in prevention of occurrence of the disease. Protection motivation theory (PMT) helps to understand preventive behaviors better and can be used in occupational injury training programs. Considering the importance of identifying the factors of the preventive behaviours of Covid-19 in the development and implementation of preventive programs, this study was conducted for predicting the preventive behaviour againt Covid-19 based on the PMT among employees in crowded offices in Qom, Iran.
Methods: In this cross sectional study, 232 employees in crowded offices in Qom, Iran have been selected using random clustering sampling method. Data collection instrument included demographic characteristics, protective behaviors against Covid-19, and PMT scale. The PMT constructs were assessed by questions composed and 7 subscales as follows: perceived vulnerability (2 items); perceived severity (2 items); perceived fear (2 items); self-efficacy (3 items); response efficacy (3 items); response cost (2 items); and protection motivation (1 items). The items were rated on a five-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). According to the theoretical assumptions, the threat appraisal score is the sum of the perceived susceptibility and severity scores. Also, the coping appraisal score is the sum of the self-efficacy and response efficacy scores minus the response cost score. Eight items scale by a three-point rated ‘always’, ‘sometimes’ and ‘never scored 2, 1 and 0, respectively measured Covid-19 preventive behaviours. The validity of the scale was confirmed using the viewpoints of health-education experts. The reliability of the scale was investigated by calculating internal consistency. Data have been analyzed via descriptive statistics and structural equations through SmartPLS statistical software. In the structural model, path coefficient, and R square were used to measure relationships among constructs. The predictive power of the model was examined by calculating Q2 indexes of behavior. Finally, a goodness of fit (GoF) index was calculated to display the model fit to the model.
Results: Mean and standard deviation of participants’ age has been 39.8
8.7; and, 90.1% of them have been male. More than half of participants (53.8%) have shown protective behaviors higher than average. There has been a significant relationship between coping appraisal and protection motivation ( =0.297 and p-value˂0.05). However, there has been no significant relationship between threat appraisal and fear constructs and protection motivation ( =0.060 and p-value>0.05). Also, there has been significant positive relationship between protection motivation and protective behaviors ( =0.214 and p-value˂0.05). Fit indices of the model have been desirable and the model could predict overall 5% of changes in performing protective behaviors. GoF was 0.503, indicating the model good fit.Conclusion: According to the results, coping appraisals were identified to be the significant positive associations with protection motivation. Contrary to the expectations based on the PMT, it is generally seen that none of the threat appraisals (severity, vulnerability, and fear) predicted protection motivation and preventive behaviour against Covid-19. Protection motivation is predictor factor of the protective behaviors. The results can be used in formulating training programs to optimize protective behaviors among employees working in offices.
Keywords: Protective Behaviors, Covid-19, Protective Motivation, Employees
Type of Study: Research |
Subject:
Respiratory disease
Received: 2020/05/26 | Accepted: 2020/12/11 | Published: 2020/11/30
Received: 2020/05/26 | Accepted: 2020/12/11 | Published: 2020/11/30
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