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Determination Of Perceived Barriers And Benefits Of Adopting Health-Promoting Behaviors In Cardiovascular Diseases Prevention: Application Of Preventative Behavior Model 
Azar Tol, Sima Esmaeili Shahmirzadi, Davoud Shojaeizadeh, Mohamad Reza Eshraghian, Bahram Mohebbi,
Volume 6, Issue 3 (9-2012)
Abstract

Background and Aim: Cardiovascular diseases are the main cause of death and disabilities in the world. The purpose of the present study is to determine the perceived barriers and benefits of adopting health-promoting behaviors among individuals at risk of cardiovascular diseases referring to TUMS Teaching Hospitals in 2011.

Materials and Methods: This is a cross-sectional study in which 325 patients at risk of cardiovascular diseases were randomly selected. The data were collected using a self-made questionnaire having three parts: 14 items for demographic and health-related variables, 12 items for perceived barriers, and another 12 items for benefits. For data analysis, SPSS 18 was used.

Results: The mean age of patients was 53.56±11.27 about 47.7% of patients(n=155) were female and 52.3% (n=170) were male. There was a meaningful relationship between the mean of perceived benefits on the one hand and occupation, physical activity, type and frequency of physical activity, smoking and awareness of cardiovascular diseases on the other(p0.001). Moreover, the mean of perceived barriers showed a meaningful relationship with occupation, smoking and awareness of cardiovascular diseases(p0.05).

Conclusion: The findings of the present study revealed that demographic and health-related variables could affect the perception of barriers and benefits of adopting certain behaviors for the prevention of cardiovascular diseases. Therefore, using interventional and educational approaches appropriate for target group features can help us take effective steps towards health promotion.


Asthma Control Level Assessment by Moving from the Current Reactive Care Models into a Preventive Approach based on Fuzzy Clustering and Classification Algorithms
Roghaye Khasha, Mohammad Mahdi Sepehri, Nasrin Taherkhani,
Volume 14, Issue 3 (7-2020)
Abstract
Background and Aim: Asthma is a common and chronic disease of respiratory tracts. The best way to treat Asthma is to control it. Experts of this field suggest the continues monitoring on Asthma symptoms and adjustment of self-care plan with offering the preventive treatment program to have desired control over Asthma. Presenting these plans by the physician is set based on the control level in which the patient is. Therefore, successful recognition and classification of the disease control level can play an important role in presenting the treatment program to the patient and improves the self-care and strengthens the early interventions to alleviate the Asthma symptoms.  
Materials and Methods: Based on this objective, we collected the data of 96 Asthma patients within a 9-month period from a specialized hospital for pulmonary diseases in Tehran. Then we classified the Asthma control level by fuzzy clustering and different types of data mining method within a multivariate dataset with the multi-class response variable.
Results: Our best model resulting from the balancing operations and feature selection on data have yielded the accuracy of 88%.
Conclusion: Our proposed model can be applied in electronic Asthma self-care systems to support the decision in real time and personalized warnings on the possible deterioration of Asthma control. Such tools can centralize the Asthma treatment from the current reactive care models into a preventive approach in which the physician’s decisions and therapeutic actions are resulting from the personal patterns of chronic Asthma control and prevention of acute Asthma.

Factors Affecting the Acceptance of Personal Protection Measures among Patients before Having Covid-19
Fahimeh Hasanzadeh, Ali Aghajanloo, Dr Mohammadreza Dinmohammadi,
Volume 16, Issue 4 (10-2022)
Abstract
Background and Aim: The most recent threat to the global community is the ongoing outbreak of the disease known as Coronavirus Disease 2019 (COVID-19). Taking personal protection measures (PPM) is crucial to prevent the spread of COVID-19. This study aimed to determine the factors affecting the acceptance of PPM among patients before having COVID-19 admitted to hospitals in northwestern of Iran.
Materials and Methods: In this cross-sectional study, 560 eligible patients with a diagnosis of COVID-19 were selected by convenience sampling. Data were collected from January 6 to May 21, 2021, through a researcher-made questionnaire and were analyzed with descriptive statistics (number, percentage, mean, standard deviation), independent t-test, and multiple linear regression by SPSS. A significance level of 5% was selected.
Results: The average age of the participants was 60.1 (16.01) years with an age range of 21 to 95 years. Most of the participants were male (53.9%) and married (91.8%). The mean score of PPM acceptance among patients was 16.55 (2.59) out of 20 points. Multiple linear regression analysis determined employment status (β=0.29, P<0.001), residency (β=-0.19, P<0.001), education level (β=0.11, P=0.048), smoking (β=-0.10, P=0.03) and income level (β=0.13, P=0.01), as predictors of acceptance of PPM. Other personal and occupational variables, including age, gender, marriage, living status, having children, and history of influenza vaccination, were not found to be effective in predicting the acceptance of personal protection measures among participating patients.
Conclusion: The acceptance of personal protection measures among patients was relatively high. Acceptance of the unemployed, rural residents, illiterate, smokers, and those with low-income level was low. This study emphasizes the need to pay attention to the changes in the individual, social and economic characteristics of the community and their effects on preventive health behaviors, especially in vulnerable groups.

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