COVID-19 Preventive behaviors based on social cognitive integrative model among medical students

COVID-19 Preventive behaviors based on social cognitive integrative model among medical students | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report COVID-19 Preventive behaviors based on social cognitive integrative model among medical students Arman Mirzaie, Zeinab Gholamnia-Shirvani, Mohammad- Ali Jahani, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4149386/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Jul, 2025 Read the published version in BMC Research Notes → Version 1 posted 10 You are reading this latest preprint version Abstract Objective : The COVID-19 outbreak in Iran prompted the investigation of preventive behaviors in vulnerable and key groups. This descriptive and analytical cross-sectional study aimed to determine COVID-19 prevention behaviors among medical students using an integrated social cognition model and identified influencing factors. Results : The results of the study of 650 medical students with a mean age of 24.37±3.78 years showed that the total score of the integrated social cognition model was at a medium level (85.44±8.70). The constructs of attitude (16.14±2.66), subjective norms (5.33±1.30), perceived behavioral control (8.18±1.76), action self-efficacy (8.60±1.66), maintenance self-efficacy (12.29±2.25), intention (8.05±1.55), action planning (8.00±1.62), coping planning (8.08±1.62), and COVID‐19 preventive behaviors (10.78±1.99) were at a medium level. There was a good correlation between the constructs of the integrated model (r = 0.42-0.64, p<0.001). Students who were older, unmarried, had a mother or father with a university education, were nondormitory, were native, at the basic science level obtained higher scores for the model constructs (p<0.001). These findings should be considered to improve health education interventions and encourage COVID-19 preventive behaviors in students. COVID-19 preventive behavior social cognition model Figures Figure 1 Introduction Coronavirus spread rapidly throughout the world in 2019 due to its high degree of contagion. This is the reason why approximately 200 countries were infected with this virus in less than a few months. According to the official report in March 2024, 704,000,253 people were infected with this virus worldwide, and the number of deaths caused by this virus was more than 7,004,732. In Iran, 7,626,527 cases of COVID-19 and 146,799 related deaths have been reported [1]. During this time, behaviors such as maintaining an appropriate social distance, wearing a mask, and not leaving the house except when necessary are less common than other behaviors [2]. In vulnerable and key target groups of society, such as medical students, there is also a lack of COVID-19 preventive behaviors [3]. Planning and preparing to address the COVID-19 crisis is a national and international necessity, and the adoption of preventive behaviors at the community level should be strongly considered by policymakers and health officials [4]. Health education models and theories help identify potentially modifiable factors related to behavior and ultimately design interventions that promote preventive behaviors [5]. The Theory of Planned Behavior (TPB) has been used in many studies to teach and apply protective behaviors [6-8]. Although TPB-based studies have shown that the construct of intention always predicts health behavior and is the link between the influence of social cognition constructs on behavior [9, 10], the relationship between intention and behavior is imperfect [11, 12]. Therefore, dual-phase models of behavior such as the Health Action Process Approach (HAPA), which has two motivational and volitional phases [13], suggest a postintentional volition phase. According to the HAPA, there are two types of planning: action planning and coping planning [14]. Action planning is a task-facilitating strategy and relates to how individuals prepare themselves for performing a behavior. This includes making plans for when, where and how to perform the specific behavior. Coping planning is a strategy to foresee barriers and obstacles and find solutions to overcome them [15]. Self-efficacy is another important determinant of behavior according to the HAPA. Several types of self-efficacy can be distinguished: action self-efficacy (an optimistic belief about personal agency during the preactional, motivational phase) and maintenance self-efficacy (an optimistic belief about personal agency during the postactional, volitional phase). Previous research has also shown that intention, planning, and self-efficacy predict health-preventive behaviors more specifically [16-18]. The integrated social cognition model (Fig. 1) is one of the frameworks used in research related to COVID-19 preventive behaviors. According to this model, contextual influences and behavior have a two-way relationship with each other [19]. Previous studies have used the integrated social cognition model in different populations and groups, and the results have been satisfactory (19, 20). Considering the outbreak of COVID-19 in Iran as well as Mazandaran Province and its consequences, there is a need to investigate COVID-19 prevention behaviors according to a successful theoretical framework such as the integrated social cognition model in vulnerable and key groups such as medical students. Therefore, this study aimed to determine COVID-19 prevention behaviors based on an integrated social cognition model and the factors affecting these behaviors among medical students at the Babol University of Medical Sciences. The results of the present study can guide future research, especially theory-based health education interventions to promote COVID-19 preventive behaviors in this key target population. Methods This cross-sectional study (descriptive-analytical) was conducted in 2022 on 650 medical students at Babol University of Medical Sciences. The participants were selected using the available sampling method. To perform multivariate regression analysis, the sample size was calculated using Analytics Calculators online software to identify the expected effect size of 0.17 [20], for eight predictor variables, a 99% confidence level, and 90% test power. The participants included medical students from different stages of basic sciences, clinical preparation, internships and clerkships. Exclusion criteria included unwillingness. The data collection tools included a demographic questionnaire and a valid and reliable questionnaire of integrated social cognition model constructs in the field of COVID-19 preventive behaviors [20]. This questionnaire [20] included 31 items and 9 constructs: a. Attitude, 6 questions (alpha=0.88); b. Subjective norms, 2 questions (alpha=0.77); c. Perceived behavioral control, 3 questions (alpha=0.90); d. Intention, 3 questions (alpha=0.90); e. Action self-efficacy, 3 questions (alpha=0.88); f. Maintenance self-efficacy, 4 questions (alpha=0.90); g. Action planning, 3 questions (alpha=0.83); h. Coping planning, 3 questions (alpha=0.89); and i. COVID‐19 preventive behaviors, 4 questions (alpha=0.80). The answer options were in the form of a 5-point Likert scale, and the score range of the questionnaire was 31 to 155. Univariate and multivariate regression analyses were used to investigate the relationships between demographic and contextual variables and the constructs of the integrated social cognition model. Pearson's correlation coefficient was used to check the correlation of the integrated social cognition model constructs. The collected data were analyzed by SPSS 22 software at a significance level of P<0.05. Results This cross-sectional study (descriptive-analytical) was conducted in 2022 on 650 medical students at Babol University of Medical Sciences. The participants were selected using the available sampling method. To perform multivariate regression analysis, the sample size was calculated using Analytics Calculators online software to identify the expected effect size of 0.17 [20], for eight predictor variables, a 99% confidence level, and 90% test power. The participants included medical students from different stages of basic sciences, clinical preparation, internships and clerkships. Exclusion criteria included unwillingness. The data collection tools included a demographic questionnaire and a valid and reliable questionnaire of integrated social cognition model constructs in the field of COVID-19 preventive behaviors [20]. This questionnaire [20] included 31 items and 9 constructs: a. Attitude, 6 questions (alpha=0.88); b. Subjective norms, 2 questions (alpha=0.77); c. Perceived behavioral control, 3 questions (alpha=0.90); d. Intention, 3 questions (alpha=0.90); e. Action self-efficacy, 3 questions (alpha=0.88); f. Maintenance self-efficacy, 4 questions (alpha=0.90); g. Action planning, 3 questions (alpha=0.83); h. Coping planning, 3 questions (alpha=0.89); and i. COVID‐19 preventive behaviors, 4 questions (alpha=0.80). The answer options were in the form of a 5-point Likert scale, and the score range of the questionnaire was 31 to 155. Univariate and multivariate regression analyses were used to investigate the relationships between demographic and contextual variables and the constructs of the integrated social cognition model. Pearson's correlation coefficient was used to check the correlation of the integrated social cognition model constructs. The collected data were analyzed by SPSS 22 software at a significance level of P<0.05. Results The average age of the participants was 24.37 ± 3.78 years, of which 333 (51.23%) were male, 451 (69.38%) were single, 421 (64.76%) lived in a dormitory, 504 (77.54%) were natives, 196 (30.15%) were at the basic sciences level, 644 (99.07%) used social media, 498 (76.62%) had a history of COVID-19, and 628 (96.61%) had been vaccinated against COVID-19 (Table 1). Table 1- Demographic characteristics of medical students (n=650) Percentage (Frequency) Subgroups of Variables Variables 333 (51.23) Male Gender 317 (48.77) Female 451 (69.39) Single Marital status 190 (29.23) Married 9 (1.38) Divorced. Widowed 57 (8.76) Illiterate Father's education 419 (64.45) Primary, secondary and high-school 174 (26.76) University 63 (9.68) Illiterate Mother's education 426 (65.56) Primary, secondary and high-school 161 (24.76) University 421 (64.77) Dormitory Place of residence 69 (10.61) Rental house 35 (5.39) Private home 125 (19.23) Home with family 146 (22.46) No Being a native 504 (77.54) Yes 196 (30.15) Basic Sciences Education level 139 (21.39) Clinical preparations 126 (19.38) Internship 189 (29.08) Clerkship 152 (23.38) No History of COVID-19 498 (76.62) Yes 22 (3.38) No COVID-19 Vaccination 628 (96.62) Yes 6 (0.92) No Using social media 644 (99.07) Yes Table 2 shows the average, median, and maximum-minimum scores of the questionnaire for COVID-19 preventive behaviors based on the integrated social cognition model for medical students. The total average of the integrated social cognition model constructs was 85.44±8.70, and the model constructs for COVID-19 preventive behaviors were at the "medium" level. Table 2- Constructs of the integrated model for preventing COVID‐19 among medical students (n=650) Maximum score Max-Min Median (IQR) Mean (SD) Variables 30 27-11 16 (14-18) 16.14±2.66 Attitude 10 10-2 5 (4-6) 5.33±1.30 Subjective norms 15 15-5 8 (7-9) 8.18±1.76 Perceived behavior control 15 15-3 8 (7-9) 8.50±1.55 Intention 20 20-7 10.50 (9-12) 10.78±1.99 Preventive behavior 15 13-5 8 (7-9) 8.00±1.62 Action planning 15 14-3 8 (7-9) 8.08±1.62 Coping planning 15 13-5 8 (7-10) 8.60±1.66 Action self-efficacy 20 20-7 12 (11-14) 12.29±2.25 Maintenance self-efficacy 155 139-69 84 (80-88) 85.44±8.70 Total The results of univariate and multivariate regression analysis showed that the variables of marriage, mother's and father's education, place of residence, being a native of Mazandaran, and level of education had a significant relationship with the total score of the model constructs. These variables were identified as strong independent predictors for the total score of the constructs of the integrated social cognition model. In multivariate analysis, the age variable showed a significant relationship with the total score of the constructs. Single students with mothers and fathers who had a university education, who were nondormitory, who were native, and who were at the basic sciences level obtained higher total scores in the model constructs (Table 3). Table 3- Regression analysis of the relationship between the integrated model of preventive behavior against COVID-19 and the demographic characteristics of medical students (n=650) Demographic variables Univariate analysis (raw effects) Multivariate analysis (adjusted effects) β(SE) 95% (CI) P Value β(SE) 95% (CI) P Value Age -0.01(0.09) -0.01 to 0.16 0.916 0.24 (0.09) 0.05 - 0.43 0.011 Gender 0.51 (0.68) -0.83 to 1.85 0.455 -0.22 (0.64) -1.49 -1.04 0.729 Occupation -1.14 (0.78) -2.68 to 0.39 0.145 -0.95 (0.72) -2.38 to 0.47 0.190 Marital status -2.45 (0.74) -3.91to -0.99 0.001 -1.95 (0.72) -3.36 to -0.53 0.007 Mother’s education 4.78 (0.76) 3.26 to 6.29 < 0.001 2.59 (0.82) 0.96 to 4.21 0.002 Father’s education 4.27 (0.75) 2.79 to 5.75 < 0.001 2.47 (0.80) 0.89 to 4.04 0.002 Place of residence 4.35 (0.69) 2.99 to 5.71 < 0.001 3.46 (0.67) 2.14 to 4.79 < 0.001 Being a native 2.38 (0.81) 0.78 to 3.97 0.004 1.70 (0.75) 0.21 to 3.19 0.025 Education level -3.42 (0.67) -4.75 to -2.09 < 0.001 -3.16 (0.77) -4.68 to-1.64 < 0.001 History of COVID-19 -0.19 (0.80) -1.78 to 1.38 0.808 -0.93 (0.78) -0.46 to 0.59 0.230 Using social media 4.65 (3.57) -2.35 to 11.66 0.193 4.62 (3.32) -1.89 to11.15 0.164 According to the Pearson test results, there was a good correlation between the integrated social cognition model and COVID-19 preventive behaviors in medical students. Attitude had the strongest correlation with the total constructs of the integrated model (r=0.64 and p<0.001), followed by perceived behavioral control (r=0.61 and p<0.001) and COVID-19 preventive behaviors (r=0.58 and p<0.001) (Table 4). Table 4- Correlation matrix of the integrated model for preventing COVID‐19 among medical students (n=650) Constructs Attitude Subjective norms Perceived behavior control Intention Preventive behavior Action planning Coping planning Action self-efficacy Maintenance self-efficacy Total Attitude 1 Subjective norms r=0.18 p<0.001 1 Perceived behavioral control r=0.34 p<0.001 r= 0.26 p<0.001 1 Intention r=0.14 p<0.001 r=0.15 p<0.001 r=0.25 p<0.001 1 Preventive behavior r=0.30 p<0.001 r=0.20 p<0.001 r=0.25 p<0.001 r=0.21 p<0.001 1 Action planning r=0.13 P=0.001 r=0.12 P=0.001 r=0.20 p<0.001 r=0.12 P=0.001 r=0.16 p<0.001 1 Coping planning r=0.23 p<0.001 r=0.26 p<0.001 r=0.20 p<0.001 r=0.12 P=0.002 r=0.19 p<0.001 r=0.32 p<0.001 1 Action self-efficacy r=0.23 p<0.001 r=0.23 p<0.001 r=0.27 p<0.001 r=0.18 p<0.001 r=0.20 p<0.001 r=0.17 p<0.001 r=0.21 p<0.001 1 Maintenance self-efficacy r=0.13 p<0.001 r=0.84 P=0.031 r=0.14 p<0.001 r=0.10 P=0.006 r=0.15 p<0.001 r=0.09 P=0.029 r=0.08 P=0.029 r=0.11 P=0.005 1 Total r=0.64 p<0.001 r=0.47 p<0.001 r=0.61 p<0.001 r=0.42 p<0.001 r=0.58 p<0.001 r=0.43 p<0.001 r=0.52 p<0.001 r=0.50 p<0.001 r=0.45 p<0.001 1 Discussion The results of the present study showed that the constructs of the integrated social cognition model for preventing COVID-19 were at a medium level for medical students at Babol University of Medical Sciences. There was a good correlation between the constructs of the model. Demographic variables showed a significant relationship with the total score of the constructs of the model. The present study showed that the total score and the score of the constructs of the integrated social cognition model for COVID-19 preventive behaviors were at a medium level for medical students. It seems that the high prevalence of COVID-19 in society and widespread information, especially in the mass media, have affected the level of COVID-19 preventive behaviors. On the other hand, studying in an academic environment with easy and quick access to social media provides them with better knowledge and attitudes toward COVID-19 and ways to prevent it [21]. Thus, there is a need to design programs to improve the constructs of this preventive behavior to a greater extent. In the study of Rahmanian et al. [22] the scores for knowledge, attitudes, and practices of medical students in Jahrom regarding COVID-19 were greater than average. In fact, medical students seemed to have acceptable insight into the disease as individuals who are at the forefront of the fight against coronavirus. However, the results of the study by Khazaee et al. [23] in the field of COVID-19 showed that the average score of the behavior construct and the perceived sensitivity were greater than those of other constructs. Lin et al's [20] findings also showed that perceived behavioral control, intention, action planning, and maintenance self-efficacy had the highest scores for COVID-19 preventive behaviors based on the integrated social cognition model. Delshad-Noqabi et al. [24] showed that the average score of the constructs of perceived sensitivity and perceived intensity was greater than that of other constructs. It seems that the difference in the theoretical frameworks used in the mentioned studies justifies the differences in scores for COVID-19 preventive behaviors in different populations. There was a high correlation between the constructs of the integrated social cognition model. Lin et al. [20] also reported that all the proposed relationships between the constructs of the integrated social cognition model in the context of COVID-19 preventive behaviors were statistically significant. The attitude construct had the strongest correlation with the total constructs in the integrated model, followed by perceived behavioral control and COVID-19 preventive behaviors. The construct of attitude is the first determinant of behavioral intention, which refers to the general feeling of liking or disliking any particular behavior. The more favorable a person's attitude toward a behavior is, the more likely a person is to intend to perform that behavior [25]. Additionally, the perceived behavioral control over a preventive behavior and the ability to perform it among medical students showed a strong correlation with the constructs of the integrated social cognition model. Nasirzadeh et al's [26] study also revealed a direct and significant relationship between preventive behaviors and attitudes and reported that attitude was the strongest predictor of behavior. Duan et al. [27] reported a correlation between maintenance self-efficacy and subjective norms with intention and maintenance self-efficacy and between action planning and preventive behavior. However, Khazaee et al [23] reported a positive and significant correlation between the constructs of sensitivity, benefits, obstacles, and self-efficacy, among which self-efficacy was the strongest predictor. In Mahindarathne's study, self-efficacy also had a significant positive effect on COVID-19 preventive behaviors. This may be because if people identify their strengths and potentials (self-efficacy) in fighting a disease, they will be more optimistic about performing preventive behaviors [28]. Parents' education level, being a native of Mazandaran, place of residence, marital status, age, and educational level were effective in predicting COVID-19 among medical students based on the integrated social cognition model. In fact, students with mothers and fathers with a university education who were native, nondormitory, single, older, or at the basic sciences level had better scores on the constructs of the integrated model of preventive behavior. The results of Adriani et al's [29] study showed that there is a significant relationship between the level of education and the constructs of the health belief model, so people with a higher level of education had greater perceived sensitivity, perceived severity, perceived benefits, self-efficacy, and preventive behaviors. Khazaee et al. [23] reported that people with a higher level of education have better COVID-19 preventive behaviors. The students who were natives of Mazandaran province and lived at home showed a better status in the constructs of the integrated social cognition model due to the possibility of living in healthier conditions. Xiang et al. [30] reported a relationship between acute respiratory tract infection prevention behaviors and place of residence. In the present study, students who were single had higher scores on the constructs of the integrated model. Older students also had higher scores on the integrated model constructs. In a study by Haischer et al. [31] there was also a significant relationship between the gender, age, place of residence, and marital status of people with preventive behavior. In fact, the investigation of the relationship between people's age and maintenance self-efficacy, or belief in the ability to maintain and continue preventive behaviors, revealed that preventive behavior scores increase with age. Consistent with this result, the results of a study showed that the younger people are, the lower their COVID-19 preventive behaviors [32]. Students at the basic sciences level showed better scores in the constructs of the integrated model than did clinical students. A study evaluated the level of anxiety and working conditions of health care workers during the COVID-19 outbreak and showed that service providers for patients diagnosed with COVID-19 had better personal protective measures [33]. However, a study by Rahmanian et al. indicated that the performance of administrative staff was better than that of medical staff (22). In fact, students at the basic sciences level had better preventive behavior despite having less clinical exposure to the coronavirus due to their strong motivation and more favorable attitude. The results of this study showed the average level of the constructs of the integrated social cognition model for preventing COVID-19 and the factors affecting them in medical students at Babol University of Medical Sciences. The results of this study could be helpful for evaluating, designing, and implementing better health education interventions to improve social cognitive constructs related to COVID-19 preventive behaviors among medical students. Limitations This study has several limitations that should be considered, such as the use of self-report scales, the use of available samples, the cross-sectional nature of the study design, and the indeterminacy of causal relationships in the model under study. Abbreviations TBP: Theory of Planned Behavior HAPA: Health Action Process Approach Declarations Ethics approval and consent to participate The code of ethics (IR.MUBABOL.HRI.REC.1400.144) was obtained from the Ethics Committee of Babol University of Medical Sciences, and informed consent was obtained from the participants. Consent for publication Not applicable Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was funded by the Research and Technology Vice-Chancellor of Babol University of Medical Sciences. Authors' contributions Conceptualization: Z.Gh, MA. J and A.P Methodology: Z.Gh, MA. J, HA.N and A.P Project administration: A.M, Z.Gh, MA.J Formal analysis: HA.N Writing Original Draft: A.M, Z.Gh, MA.J Writing Review & Editing: A.M, Z.Gh, MA.J All authors reviewed the manuscript. Acknowledgements We thank all the medical students who participated in this study. References Worldometer. Countries where COVID-19 has spread. [updated March 12, 2024. Available from: https://www.worldometers.info/coronavirus/countries-where-coronavirus-has-spread/. Nakhaeizadeh A, Mohammadi S. Assessing the Level of Engagement in Preventive Behaviors and COVID-19 Related Anxiety in Iranian Adults. Avicenna J Nurs Midwifery Care. 2021;29(2):160-70. nmj.umsha.ac.ir/article-1-2237-en.html. Haque A, Mumtaz S, Khattak O, Mumtaz R, Ahmed A. Comparing the preventive behavior of medical students and physicians in the era of COVID-19: Novel medical problems demand novel curricular interventions. 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The Journal of Tolooebehdasht 2023;22(1):32-46. doi.org/10.18502/tbj.v22i1.2778 Xiang N, Shi Y, Wu J, Zhang S, Ye M, Peng Z, et al. Knowledge, attitudes and practices (KAP) relating to avian influenza in urban and rural areas of China. BMC Infect Dis. 2010;10:34. doi: 10.1186/471-2334-10-34. Haischer MH, Beilfuss R, Hart MR, Opielinski L, Wrucke D, Zirgaitis G, et al. Who is wearing a mask? Gender-, age-, and location-related differences during the COVID-19 pandemic. PloS one. 2020;15(10):e0240785. doi.org/10.1371/journal.pone. . Ezati-Rad R, Mohseni S, Kamalzadeh Takhti H, 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;21:466. doi.org/10.1186/s12889-021-0500-w Bostan S, Akbolat M, Kaya A, Ozata M, Gunes D. Assessments of anxiety levels and working conditions of health employees working in COVİD-19 pandemic hospitals. Electron J Gen Med. 2020;17(5):em246. https://doi.org/10.1186/s12889-021-0500-w Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 15 Jul, 2025 Read the published version in BMC Research Notes → Version 1 posted Editorial decision: Revision requested 28 Jun, 2024 Reviews received at journal 27 May, 2024 Reviewers agreed at journal 27 May, 2024 Reviewers agreed at journal 19 Apr, 2024 Reviewers agreed at journal 16 Apr, 2024 Reviewers invited by journal 15 Apr, 2024 Editor invited by journal 04 Apr, 2024 Submission checks completed at journal 31 Mar, 2024 Editor assigned by journal 31 Mar, 2024 First submitted to journal 22 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4149386","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":285980192,"identity":"ef07a5d5-fddb-4c9f-bf0f-19f7247c68a8","order_by":0,"name":"Arman Mirzaie","email":"","orcid":"","institution":"Babol University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Arman","middleName":"","lastName":"Mirzaie","suffix":""},{"id":285980193,"identity":"9db4bf7a-1b17-4718-bbbe-09fcc1e5d977","order_by":1,"name":"Zeinab Gholamnia-Shirvani","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYHACNgaGAiDFzMD4gIHhALFaDMBamA1I1AJkSBClRb6B/dqDDwZ20ebszM+qeWruyPEzMD98dAOPFsYGnnLDGQbJuTub2cxu8xx7ZizZwGZsnINHCzMDT5o0jwFz7obDDEAtbIcTNxzgYZPGp4UNoqUeqIX9WzHPPyK08DCwHwNqOQzUwmPGzNtGhBYJZh42yRkGx0FaiiXn9h02lmwm4Bf59vZnEh8qqnM3nD++8cObb4fl+NmbHz7Gp4WBmccAzmbiAYvgUw4G7A/gTMYfBFWPglEwCkbBSAQAIUBGaSmM6t0AAAAASUVORK5CYII=","orcid":"","institution":"Babol University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Zeinab","middleName":"","lastName":"Gholamnia-Shirvani","suffix":""},{"id":285980194,"identity":"3899ee58-9350-4d9e-9bca-a6935a8815fd","order_by":2,"name":"Mohammad- Ali Jahani","email":"","orcid":"","institution":"Babol University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mohammad-","middleName":"Ali","lastName":"Jahani","suffix":""},{"id":285980195,"identity":"5db828b3-5a58-4dae-b815-26b05c3c2846","order_by":3,"name":"Hossein-Ali Nikbakht","email":"","orcid":"","institution":"Babol University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Hossein-Ali","middleName":"","lastName":"Nikbakht","suffix":""},{"id":285980196,"identity":"b66f50c2-599c-4166-81c7-b4fff5ff14ec","order_by":4,"name":"Amir Pakpour","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Amir","middleName":"","lastName":"Pakpour","suffix":""}],"badges":[],"createdAt":"2024-03-22 11:30:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4149386/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4149386/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13104-025-07377-y","type":"published","date":"2025-07-15T15:57:27+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":54088159,"identity":"828d1556-fbf6-4b0d-8ce7-b8c30dea45b4","added_by":"auto","created_at":"2024-04-04 12:05:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":84276,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIntegrated social cognition model for COVID-19 preventive behaviors\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4149386/v1/29915507dbddcdbffdd72cfe.png"},{"id":87219465,"identity":"6d174c9e-0fb3-40f2-a98f-564570aefcbe","added_by":"auto","created_at":"2025-07-21 16:05:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1052606,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4149386/v1/2de5bb3c-ba2d-4037-b9b4-9b24ae5fb60e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":" COVID-19 Preventive behaviors based on social cognitive integrative model among medical students","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCoronavirus spread rapidly throughout the world in 2019 due to its high\u0026nbsp;degree of contagion. This is the reason why\u0026nbsp;approximately\u0026nbsp;200 countries were infected with this virus in less than a few months. According to the official report in March 2024, 704,000,253 people\u0026nbsp;were\u0026nbsp;infected with this virus worldwide, and the number of deaths caused by this virus was more than 7,004,732. In Iran, 7,626,527 cases of COVID-19 and 146,799\u0026nbsp;related\u0026nbsp;deaths have been reported\u0026nbsp;[1].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDuring this time, behaviors such as\u0026nbsp;maintaining\u0026nbsp;an appropriate social distance, wearing a mask, and not leaving the house except when necessary are less\u0026nbsp;common\u0026nbsp;than other behaviors\u0026nbsp;[2].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eIn vulnerable and key target groups of society, such as medical students, there is also a lack of COVID-19 preventive behaviors\u0026nbsp;[3].\u003csup\u003e\u0026nbsp;\u003c/sup\u003ePlanning and preparing to\u0026nbsp;address\u0026nbsp;the COVID-19 crisis is\u0026nbsp;a\u0026nbsp;national and international\u0026nbsp;necessity, and the adoption of preventive behaviors at the community level should be strongly considered by policymakers and health officials\u0026nbsp;[4].\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Health education models and theories help identify potentially modifiable factors related to behavior and ultimately design interventions that promote preventive behaviors [5].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eThe Theory\u0026nbsp;of Planned Behavior\u0026nbsp;(TPB) has been used in many studies to teach and apply protective behaviors\u0026nbsp;[6-8].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eAlthough TPB-based studies have shown that the construct of intention always predicts health behavior and is the link between the influence of social cognition constructs on behavior\u0026nbsp;[9, 10],\u003csup\u003e\u0026nbsp;\u003c/sup\u003ethe relationship between intention and behavior is imperfect\u0026nbsp;[11, 12].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eTherefore, dual-phase models of behavior such as the Health Action Process Approach (HAPA), which\u0026nbsp;has\u0026nbsp;two motivational and volitional phases\u0026nbsp;[13],\u003csup\u003e\u0026nbsp;\u003c/sup\u003esuggest a\u0026nbsp;postintentional\u0026nbsp;volition phase. According to\u0026nbsp;the\u0026nbsp;HAPA, there are two types of planning: action planning and coping planning\u0026nbsp;[14].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eAction planning is a task-facilitating strategy and relates to how individuals prepare themselves for performing a behavior. This includes making plans for when, where and how to perform the specific behavior. Coping planning is a strategy to foresee barriers and obstacles and find solutions to overcome them\u0026nbsp;[15].\u0026nbsp;Self-efficacy is another\u0026nbsp;important determinant of behavior according to\u0026nbsp;the HAPA. Several types of self-efficacy can be distinguished: action self-efficacy (an optimistic belief about personal agency during the preactional, motivational phase) and maintenance self-efficacy (an optimistic belief about personal agency during the postactional, volitional phase). Previous research has also shown\u0026nbsp;that\u0026nbsp;intention, planning, and self-efficacy predict health-preventive behaviors more specifically\u0026nbsp;[16-18].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eThe integrated social cognition model \u003cstrong\u003e(Fig. 1)\u003c/strong\u003e is one of the frameworks used in research related to COVID-19 preventive behaviors. According to this model, contextual influences and behavior have a two-way relationship with each other [19].\u003csup\u003e\u0026nbsp;\u003c/sup\u003ePrevious studies have used the integrated social cognition model in different populations and groups, and the results have been satisfactory (19, 20).\u003c/p\u003e\n\u003cp\u003eConsidering the outbreak of COVID-19 in Iran as well as Mazandaran Province and its consequences, there is a need to investigate COVID-19 prevention behaviors according to a successful theoretical framework such as the integrated social cognition model in vulnerable and key groups such as medical students. Therefore, this study aimed to determine COVID-19 prevention behaviors based on an integrated social cognition model and the factors affecting these behaviors among medical students at the Babol University of Medical Sciences. The results of the present study can guide future research, especially theory-based health education interventions to promote COVID-19 preventive behaviors in this key target population.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis cross-sectional study (descriptive-analytical) was conducted in 2022 on 650 medical students at Babol University of Medical Sciences. The participants were selected using the available sampling method. To perform multivariate regression analysis, the sample size was calculated using Analytics Calculators online software to identify the expected effect size of 0.17\u0026nbsp;[20],\u0026nbsp;for\u0026nbsp;eight predictor variables, a 99% confidence level, and 90% test power. The participants included medical students from different stages of basic sciences, clinical preparation,\u0026nbsp;internships and clerkships. Exclusion criteria included unwillingness.\u003c/p\u003e\n\u003cp\u003eThe data collection tools included a demographic questionnaire and a valid and reliable questionnaire of integrated social cognition model constructs in the field of COVID-19 preventive behaviors\u0026nbsp;[20].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eThis questionnaire\u0026nbsp;[20]\u0026nbsp;included 31 items and 9 constructs: a. Attitude, 6 questions (alpha=0.88); b. Subjective norms, 2 questions (alpha=0.77); c. Perceived behavioral control, 3 questions (alpha=0.90); d. Intention, 3 questions (alpha=0.90); e. Action self-efficacy, 3 questions (alpha=0.88); f. Maintenance self-efficacy, 4 questions (alpha=0.90); g. Action planning, 3 questions (alpha=0.83); h. Coping planning, 3 questions (alpha=0.89); and i. COVID‐19 preventive behaviors, 4 questions (alpha=0.80). The answer options were in the form of a 5-point Likert scale, and the score range of the questionnaire was 31 to 155.\u003c/p\u003e\n\u003cp\u003eUnivariate and multivariate regression analyses were used to investigate the relationships between demographic and contextual variables and the constructs of the integrated social cognition model. Pearson\u0026apos;s correlation coefficient was used to check the correlation of the integrated social cognition model constructs. The collected data were analyzed by SPSS 22 software at a significance level of P\u0026lt;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThis cross-sectional study (descriptive-analytical) was conducted in 2022 on 650 medical students at Babol University of Medical Sciences. The participants were selected using the available sampling method. To perform multivariate regression analysis, the sample size was calculated using Analytics Calculators online software to identify the expected effect size of 0.17\u0026nbsp;[20],\u0026nbsp;for\u0026nbsp;eight predictor variables, a 99% confidence level, and 90% test power. The participants included medical students from different stages of basic sciences, clinical preparation,\u0026nbsp;internships and clerkships. Exclusion criteria included unwillingness.\u003c/p\u003e\n\u003cp\u003eThe data collection tools included a demographic questionnaire and a valid and reliable questionnaire of integrated social cognition model constructs in the field of COVID-19 preventive behaviors\u0026nbsp;[20].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eThis questionnaire\u0026nbsp;[20]\u0026nbsp;included 31 items and 9 constructs: a. Attitude, 6 questions (alpha=0.88); b. Subjective norms, 2 questions (alpha=0.77); c. Perceived behavioral control, 3 questions (alpha=0.90); d. Intention, 3 questions (alpha=0.90); e. Action self-efficacy, 3 questions (alpha=0.88); f. Maintenance self-efficacy, 4 questions (alpha=0.90); g. Action planning, 3 questions (alpha=0.83); h. Coping planning, 3 questions (alpha=0.89); and i. COVID‐19 preventive behaviors, 4 questions (alpha=0.80). The answer options were in the form of a 5-point Likert scale, and the score range of the questionnaire was 31 to 155.\u003c/p\u003e\n\u003cp\u003eUnivariate and multivariate regression\u0026nbsp;analyses\u0026nbsp;were used to investigate the\u0026nbsp;relationships\u0026nbsp;between demographic and contextual variables and the constructs of the integrated social cognition model. Pearson\u0026apos;s correlation coefficient was used to check the correlation of\u0026nbsp;the\u0026nbsp;integrated social cognition model constructs. The collected data were analyzed by SPSS 22 software at a significance level of P\u0026lt;0.05.\u003c/p\u003e\n\u003ch2\u003eResults\u003c/h2\u003e\n\u003cp\u003eThe average age of\u0026nbsp;the\u0026nbsp;participants was 24.37 \u0026plusmn; 3.78 years, of which 333 (51.23%) were male,\u0026nbsp;451 (69.38%) were single,\u0026nbsp;421 (64.76%) lived in\u0026nbsp;a\u0026nbsp;dormitory,\u0026nbsp;504 (77.54%) were natives,\u0026nbsp;196 (30.15%) were at the basic sciences level,\u0026nbsp;644 (99.07%) used social media,\u0026nbsp;498 (76.62%) had a history of COVID-19,\u0026nbsp;and 628 (96.61%) had been vaccinated against COVID-19 (Table 1).\u003c/p\u003e\n\u003cp\u003eTable 1- Demographic characteristics of medical students (n=650)\u003c/p\u003e\n\u003ctable dir=\"rtl\" border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"525\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.24334600760456%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003e(Frequency)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.29657794676806%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eSubgroups of Variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.460076045627375%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.24334600760456%\"\u003e\n \u003cp dir=\"LTR\"\u003e333 (51.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.29657794676806%\"\u003e\n \u003cp dir=\"LTR\"\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.460076045627375%\" rowspan=\"2\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e317 (48.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\"\u003e\n \u003cp dir=\"LTR\"\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.24334600760456%\"\u003e\n \u003cp dir=\"LTR\"\u003e451 (69.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.29657794676806%\"\u003e\n \u003cp dir=\"LTR\"\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.460076045627375%\" rowspan=\"3\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e190 (29.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\"\u003e\n \u003cp dir=\"LTR\"\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e9 (1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\"\u003e\n \u003cp dir=\"LTR\"\u003eDivorced. Widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.24334600760456%\"\u003e\n \u003cp dir=\"LTR\"\u003e57 (8.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.29657794676806%\"\u003e\n \u003cp dir=\"LTR\"\u003eIlliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.460076045627375%\" rowspan=\"3\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eFather\u0026apos;s education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e419 (64.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\"\u003e\n \u003cp dir=\"LTR\"\u003ePrimary, secondary and high-school\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e174 (26.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\"\u003e\n \u003cp dir=\"LTR\"\u003eUniversity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.24334600760456%\"\u003e\n \u003cp dir=\"LTR\"\u003e63 (9.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.29657794676806%\"\u003e\n \u003cp dir=\"LTR\"\u003eIlliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.460076045627375%\" rowspan=\"3\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eMother\u0026apos;s education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e426 (65.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\"\u003e\n \u003cp dir=\"LTR\"\u003ePrimary, secondary and high-school\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e161 (24.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\"\u003e\n \u003cp dir=\"LTR\"\u003eUniversity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.24334600760456%\"\u003e\n \u003cp dir=\"LTR\"\u003e421 (64.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.29657794676806%\"\u003e\n \u003cp dir=\"LTR\"\u003eDormitory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.460076045627375%\" rowspan=\"4\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003ePlace of residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e69 (10.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\"\u003e\n \u003cp dir=\"LTR\"\u003eRental house\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e35 (5.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\"\u003e\n \u003cp dir=\"LTR\"\u003ePrivate home\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e125 (19.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\"\u003e\n \u003cp dir=\"LTR\"\u003eHome with family\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.24334600760456%\"\u003e\n \u003cp dir=\"LTR\"\u003e146 (22.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.29657794676806%\"\u003e\n \u003cp dir=\"LTR\"\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.460076045627375%\" rowspan=\"2\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eBeing a native\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e504 (77.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\"\u003e\n \u003cp dir=\"LTR\"\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.24334600760456%\"\u003e\n \u003cp dir=\"LTR\"\u003e196 (30.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.29657794676806%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eBasic Sciences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.460076045627375%\" rowspan=\"4\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e139 (21.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eClinical preparations\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e126 (19.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eInternship\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e189 (29.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eClerkship\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.24334600760456%\"\u003e\n \u003cp dir=\"LTR\"\u003e152 (23.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.29657794676806%\"\u003e\n \u003cp dir=\"LTR\"\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.460076045627375%\" rowspan=\"2\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eHistory of COVID-19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e498 (76.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\"\u003e\n \u003cp dir=\"LTR\"\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.24334600760456%\"\u003e\n \u003cp dir=\"LTR\"\u003e22 (3.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.29657794676806%\"\u003e\n \u003cp dir=\"LTR\"\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.460076045627375%\" rowspan=\"2\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eCOVID-19 Vaccination\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e628 (96.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\"\u003e\n \u003cp dir=\"LTR\"\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.24334600760456%\"\u003e\n \u003cp dir=\"LTR\"\u003e6 (0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.29657794676806%\"\u003e\n \u003cp dir=\"LTR\"\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.460076045627375%\" rowspan=\"2\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eUsing social media\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.42857142857143%\"\u003e\n \u003cp dir=\"LTR\"\u003e644 (99.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.57142857142857%\"\u003e\n \u003cp dir=\"LTR\"\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2 shows the average, median, and maximum-minimum scores of the questionnaire for COVID-19 preventive behaviors based on the integrated social cognition model\u0026nbsp;for\u0026nbsp;medical students. The total average of\u0026nbsp;the\u0026nbsp;integrated social cognition model constructs was 85.44\u0026plusmn;8.70, and the model constructs for COVID-19 preventive behaviors were at the \u0026quot;medium\u0026quot; level.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2- Constructs of\u0026nbsp;the\u0026nbsp;integrated model for\u0026nbsp;preventing\u0026nbsp;COVID‐19\u0026nbsp;among\u0026nbsp;medical students (n=650)\u003c/p\u003e\n\u003ctable dir=\"rtl\" border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"677\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eMaximum score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eMax-Min\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eMedian (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.46381093057607%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eMean (SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.474150664697195%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e27-11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e16 (14-18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.46381093057607%\"\u003e\n \u003cp dir=\"LTR\"\u003e16.14\u0026plusmn;2.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.474150664697195%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eAttitude\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e10-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e5 (4-6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.46381093057607%\"\u003e\n \u003cp dir=\"LTR\"\u003e5.33\u0026plusmn;1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.474150664697195%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eSubjective norms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e15-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e8 (7-9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.46381093057607%\"\u003e\n \u003cp dir=\"LTR\"\u003e8.18\u0026plusmn;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.474150664697195%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003ePerceived behavior control\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e15-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e8 (7-9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.46381093057607%\"\u003e\n \u003cp dir=\"LTR\"\u003e8.50\u0026plusmn;1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.474150664697195%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eIntention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e20-7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e10.50 (9-12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.46381093057607%\"\u003e\n \u003cp dir=\"LTR\"\u003e10.78\u0026plusmn;1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.474150664697195%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003ePreventive behavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e13-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e8 (7-9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.46381093057607%\"\u003e\n \u003cp dir=\"LTR\"\u003e8.00\u0026plusmn;1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.474150664697195%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eAction planning\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e14-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e8 (7-9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.46381093057607%\"\u003e\n \u003cp dir=\"LTR\"\u003e8.08\u0026plusmn;1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.474150664697195%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eCoping planning\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e13-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e8 (7-10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.46381093057607%\"\u003e\n \u003cp dir=\"LTR\"\u003e8.60\u0026plusmn;1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.474150664697195%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eAction self-efficacy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e20-7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e12 (11-14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.46381093057607%\"\u003e\n \u003cp dir=\"LTR\"\u003e12.29\u0026plusmn;2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.474150664697195%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eMaintenance self-efficacy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e139-69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.020679468242246%\"\u003e\n \u003cp dir=\"LTR\"\u003e84 (80-88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.46381093057607%\"\u003e\n \u003cp dir=\"LTR\"\u003e85.44\u0026plusmn;8.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.474150664697195%\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eThe results of univariate and multivariate regression analysis showed that the variables of marriage, mother\u0026apos;s and father\u0026apos;s education, place of residence, being a native of Mazandaran, and level of education had a significant relationship with the total score of the model constructs. These variables were identified as strong independent predictors for the total score of the constructs of the integrated social cognition model. In multivariate analysis, the age variable showed a significant relationship with the total score of the constructs. Single students with mothers and fathers who had a university education, who were nondormitory, who were native, and who were at the basic sciences level obtained higher total scores in the model constructs (Table 3).\u003c/p\u003e\n\u003cp\u003eTable 3- Regression analysis of the relationship between the integrated model of preventive behavior against COVID-19 and the demographic characteristics of medical students (n=650)\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"648\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.376543209876544%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.58024691358025%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate analysis (raw effects)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"39.04320987654321%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate analysis (adjusted effects)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.898608349900595%\"\u003e\n \u003cp\u003e\u0026beta;(SE)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.681908548707753%\"\u003e\n \u003cp\u003e95% (CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.121272365805169%\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.898608349900595%\"\u003e\n \u003cp\u003e\u0026beta;(SE)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.681908548707753%\"\u003e\n \u003cp\u003e95% (CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.717693836978132%\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.376543209876544%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e-0.01(0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e-0.01 to 0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.185185185185185%\"\u003e\n \u003cp\u003e0.916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e0.24 (0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e0.05 - 0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.648148148148149%\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.376543209876544%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e0.51 (0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e-0.83 to 1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.185185185185185%\"\u003e\n \u003cp\u003e0.455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e-0.22 (0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e-1.49 -1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.648148148148149%\"\u003e\n \u003cp\u003e0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.376543209876544%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e-1.14 (0.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e-2.68 to 0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.185185185185185%\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e-0.95 (0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e-2.38 to 0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.648148148148149%\"\u003e\n \u003cp\u003e0.190\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.376543209876544%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e-2.45 (0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e-3.91to -0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.185185185185185%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e-1.95 (0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e-3.36 to -0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.648148148148149%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.376543209876544%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMother\u0026rsquo;s education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e4.78 (0.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e3.26 to 6.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.185185185185185%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e2.59 (0.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e0.96 to 4.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.648148148148149%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.376543209876544%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFather\u0026rsquo;s education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e4.27 (0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e2.79 to 5.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.185185185185185%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e2.47 (0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e0.89 to 4.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.648148148148149%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.376543209876544%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e4.35 (0.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e2.99 to 5.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.185185185185185%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e3.46 (0.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e2.14 to 4.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.648148148148149%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.376543209876544%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBeing a native\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e2.38 (0.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e0.78 to 3.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.185185185185185%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e1.70 (0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e0.21 to 3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.648148148148149%\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.376543209876544%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e-3.42 (0.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e-4.75 to -2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.185185185185185%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e-3.16 (0.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e-4.68 to-1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.648148148148149%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.376543209876544%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of COVID-19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e-0.19 (0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e-1.78 to 1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.185185185185185%\"\u003e\n \u003cp\u003e0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e-0.93 (0.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e-0.46 to 0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.648148148148149%\"\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.376543209876544%\"\u003e\n \u003cp\u003e\u003cstrong\u003eUsing social media\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e4.65 (3.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e-2.35 to 11.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.185185185185185%\"\u003e\n \u003cp\u003e0.193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.117283950617283%\"\u003e\n \u003cp\u003e4.62 (3.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.277777777777779%\"\u003e\n \u003cp\u003e-1.89 to11.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.648148148148149%\"\u003e\n \u003cp\u003e0.164\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAccording to the Pearson test results, there was a good correlation between the integrated social cognition model\u0026nbsp;and\u0026nbsp;COVID-19 preventive behaviors in medical students.\u0026nbsp;Attitude\u0026nbsp;had the\u0026nbsp;strongest\u0026nbsp;correlation with the total constructs of the integrated model (r=0.64 and p\u0026lt;0.001), followed by perceived behavioral control (r=0.61 and p\u0026lt;0.001) and COVID-19 preventive behaviors (r=0.58 and p\u0026lt;0.001) (Table 4).\u003c/p\u003e\n\u003cp\u003eTable 4- Correlation matrix of\u0026nbsp;the\u0026nbsp;integrated model for\u0026nbsp;preventing\u0026nbsp;COVID‐19\u0026nbsp;among\u0026nbsp;medical students (n=650)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"774\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.728682170542635%\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstructs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.852713178294573%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAttitude\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.077519379844961%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubjective norms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePerceived behavior control\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreventive behavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAction planning\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoping planning\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAction self-efficacy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaintenance self-efficacy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.10077519379845%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.728682170542635%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAttitude\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.852713178294573%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.077519379844961%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.10077519379845%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.728682170542635%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubjective norms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.852713178294573%\"\u003e\n \u003cp\u003er=0.18 p\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.077519379844961%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.10077519379845%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.728682170542635%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePerceived behavioral control\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.852713178294573%\"\u003e\n \u003cp\u003er=0.34 p\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.077519379844961%\"\u003e\n \u003cp\u003er= 0.26\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.10077519379845%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.728682170542635%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.852713178294573%\"\u003e\n \u003cp\u003er=0.14\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.077519379844961%\"\u003e\n \u003cp\u003er=0.15\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.25\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.10077519379845%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.728682170542635%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreventive behavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.852713178294573%\"\u003e\n \u003cp\u003er=0.30\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.077519379844961%\"\u003e\n \u003cp\u003er=0.20\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.25\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.21\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.10077519379845%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.728682170542635%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAction planning\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.852713178294573%\"\u003e\n \u003cp\u003er=0.13\u003c/p\u003e\n \u003cp\u003eP=0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.077519379844961%\"\u003e\n \u003cp\u003er=0.12\u003c/p\u003e\n \u003cp\u003eP=0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.20\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.12\u003c/p\u003e\n \u003cp\u003eP=0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.16\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.10077519379845%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.728682170542635%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoping planning\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.852713178294573%\"\u003e\n \u003cp\u003er=0.23\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.077519379844961%\"\u003e\n \u003cp\u003er=0.26\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.20\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.12\u003c/p\u003e\n \u003cp\u003eP=0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.19\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003er=0.32\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.10077519379845%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.728682170542635%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAction\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eself-efficacy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.852713178294573%\"\u003e\n \u003cp\u003er=0.23\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.077519379844961%\"\u003e\n \u003cp\u003er=0.23\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.27\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.18\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.20\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003er=0.17\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003er=0.21\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.10077519379845%\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.728682170542635%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaintenance self-efficacy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.852713178294573%\"\u003e\n \u003cp\u003er=0.13\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.077519379844961%\"\u003e\n \u003cp\u003er=0.84\u003c/p\u003e\n \u003cp\u003eP=0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.14\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.10\u003c/p\u003e\n \u003cp\u003eP=0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.15\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003er=0.09\u003c/p\u003e\n \u003cp\u003eP=0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003er=0.08\u003c/p\u003e\n \u003cp\u003eP=0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.11\u003c/p\u003e\n \u003cp\u003eP=0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.10077519379845%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.728682170542635%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.852713178294573%\"\u003e\n \u003cp\u003er=0.64\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.077519379844961%\"\u003e\n \u003cp\u003er=0.47\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.61\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.42\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.58\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003er=0.43\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\"\u003e\n \u003cp\u003er=0.52\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.50\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\"\u003e\n \u003cp\u003er=0.45\u003c/p\u003e\n \u003cp\u003ep\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.10077519379845%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results of the present study showed that the constructs of\u0026nbsp;the\u0026nbsp;integrated social cognition model\u0026nbsp;for\u0026nbsp;preventing\u0026nbsp;COVID-19 were at a medium level\u0026nbsp;for\u0026nbsp;medical students\u0026nbsp;at\u0026nbsp;Babol University of Medical Sciences. There was a good correlation between the constructs of the model. Demographic variables showed a significant relationship with the total score of the constructs of the model.\u003c/p\u003e\n\u003cp\u003eThe present study showed that the total score and the score of the constructs of the integrated social cognition model for COVID-19 preventive behaviors were at a medium level\u0026nbsp;for\u0026nbsp;medical students. It seems that the high prevalence of COVID-19 in society and widespread information, especially in the mass media, have\u0026nbsp;affected\u0026nbsp;the level of COVID-19 preventive behaviors. On the other hand, studying in an academic environment with easy and quick access to social media\u0026nbsp;provides\u0026nbsp;them\u0026nbsp;with\u0026nbsp;better knowledge and attitudes toward COVID-19 and ways to prevent it\u0026nbsp;[21].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eThus, there is a need to design\u0026nbsp;programs to improve the constructs of this preventive behavior to a\u0026nbsp;greater extent.\u003c/p\u003e\n\u003cp\u003eIn the study of Rahmanian et al.\u0026nbsp;[22]\u0026nbsp;the\u0026nbsp;scores for\u0026nbsp;knowledge,\u0026nbsp;attitudes, and\u0026nbsp;practices\u0026nbsp;of medical students in Jahrom regarding COVID-19\u0026nbsp;were greater\u0026nbsp;than average. In fact, medical students seemed to have acceptable insight into the disease as individuals who are at the forefront of the fight against coronavirus.\u003csup\u003e\u0026nbsp;\u003c/sup\u003eHowever, the results of the study by Khazaee et al.\u0026nbsp;[23]\u0026nbsp;in the field of COVID-19 showed that the average score of the behavior construct and the perceived sensitivity were\u0026nbsp;greater\u0026nbsp;than\u0026nbsp;those of\u0026nbsp;other constructs.\u003c/p\u003e\n\u003cp\u003eLin et al\u0026apos;s\u0026nbsp;[20]\u0026nbsp;findings also showed that perceived behavioral control, intention, action planning, and maintenance self-efficacy had the highest scores\u0026nbsp;for\u0026nbsp;COVID-19 preventive behaviors based on the integrated social cognition model.\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDelshad-Noqabi et\u0026nbsp;al.\u0026nbsp;[24]\u003csup\u003e\u0026nbsp;\u003c/sup\u003eshowed that the average score of the constructs of perceived sensitivity and perceived intensity was\u0026nbsp;greater\u0026nbsp;than\u0026nbsp;that of\u0026nbsp;other constructs. It seems that the difference in the theoretical frameworks used in the mentioned studies justifies the differences in scores for COVID-19 preventive behaviors in different populations.\u003c/p\u003e\n\u003cp\u003eThere was a high correlation between the constructs of the integrated social cognition model. Lin et al.\u0026nbsp;[20]\u0026nbsp;also reported that all the proposed relationships between the constructs of the integrated social cognition model in the context of COVID-19 preventive behaviors were statistically significant.\u003c/p\u003e\n\u003cp\u003eThe attitude construct had the\u0026nbsp;strongest\u0026nbsp;correlation with the total constructs in the integrated model, followed by perceived behavioral control and COVID-19 preventive behaviors. The construct of attitude is the first determinant of behavioral intention, which refers to the general feeling of liking or disliking any particular behavior. The more favorable a person\u0026apos;s attitude toward a behavior is, the more likely a person\u0026nbsp;is\u0026nbsp;to\u0026nbsp;intend to\u0026nbsp;perform that behavior\u0026nbsp;[25].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eAdditionally, the perceived behavioral control over a preventive behavior and the ability to perform it\u0026nbsp;among\u0026nbsp;medical students showed a\u0026nbsp;strong\u0026nbsp;correlation with the constructs of the integrated social cognition model. Nasirzadeh et\u0026nbsp;al\u0026apos;s\u0026nbsp;[26]\u0026nbsp;study also\u0026nbsp;revealed\u0026nbsp;a direct and significant relationship between preventive behaviors and\u0026nbsp;attitudes\u0026nbsp;and reported\u0026nbsp;that\u0026nbsp;attitude\u0026nbsp;was\u0026nbsp;the strongest predictor of behavior.\u003c/p\u003e\n\u003cp\u003eDuan et al.\u0026nbsp;[27]\u0026nbsp;reported a correlation between maintenance self-efficacy and subjective norms with intention and maintenance self-efficacy and\u0026nbsp;between\u0026nbsp;action planning\u0026nbsp;and\u0026nbsp;preventive behavior.\u003csup\u003e\u0026nbsp;\u003c/sup\u003eHowever,\u0026nbsp;Khazaee et al\u0026nbsp;[23]\u0026nbsp;reported a positive and significant correlation between the constructs of sensitivity, benefits, obstacles, and self-efficacy, among which self-efficacy was the strongest predictor.\u003csup\u003e\u0026nbsp;\u003c/sup\u003eIn Mahindarathne\u0026apos;s study, self-efficacy also had a significant positive effect on COVID-19 preventive behaviors.\u0026nbsp;This may be\u0026nbsp;because if people identify their strengths and potentials (self-efficacy) in fighting a disease, they will be more optimistic about performing preventive behaviors\u0026nbsp;[28].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Parents\u0026apos; education level, being a native of Mazandaran, place of residence, marital status, age, and educational level were effective\u0026nbsp;in predicting\u0026nbsp;COVID-19\u0026nbsp;among\u0026nbsp;medical students based on the integrated social cognition model. In fact, students with mothers and fathers with\u0026nbsp;a\u0026nbsp;university education who were native, nondormitory, single, older,\u0026nbsp;or\u0026nbsp;at the basic sciences level had better\u0026nbsp;scores on\u0026nbsp;the constructs of the integrated model of preventive behavior. The results of Adriani et al\u0026apos;s\u0026nbsp;[29]\u0026nbsp;study showed that there is a significant relationship between the level of education and the constructs of the health belief model, so people with a higher level of education had\u0026nbsp;greater\u0026nbsp;perceived sensitivity, perceived severity, perceived benefits, self-efficacy, and preventive behaviors.\u003csup\u003e\u0026nbsp;\u003c/sup\u003eKhazaee et al.\u0026nbsp;[23]\u003csup\u003e\u0026nbsp;\u003c/sup\u003ereported\u0026nbsp;that people with a higher level of education have better COVID-19 preventive behaviors.\u003c/p\u003e\n\u003cp\u003eThe students who were natives of Mazandaran province and lived at home showed a better status in the constructs of the integrated social cognition model due to the possibility of living in healthier conditions. Xiang et\u0026nbsp;al.\u0026nbsp;[30]\u0026nbsp;reported\u0026nbsp;a relationship between acute respiratory tract infection\u0026nbsp;prevention\u0026nbsp;behaviors and place of residence.\u003csup\u003e\u0026nbsp;\u003c/sup\u003eIn the present study, students who were single had higher\u0026nbsp;scores on\u0026nbsp;the constructs of the integrated model.\u0026nbsp;Older students\u0026nbsp;also had higher scores\u0026nbsp;on the\u0026nbsp;integrated model constructs. In a study by Haischer et al.\u0026nbsp;[31]\u0026nbsp;there was also a significant relationship between\u0026nbsp;the\u0026nbsp;gender, age, place of residence, and marital status of people with preventive behavior. In fact, the investigation of the relationship between people\u0026apos;s age and maintenance self-efficacy, or belief in the ability to maintain and continue preventive behaviors,\u0026nbsp;revealed\u0026nbsp;that preventive\u0026nbsp;behavior scores increase\u0026nbsp;with age. Consistent with this result, the results of a study showed that the younger people are, the lower their COVID-19 preventive behaviors\u0026nbsp;[32].\u003c/p\u003e\n\u003cp\u003eStudents at the basic sciences level showed better scores in the constructs of the integrated model than\u0026nbsp;did\u0026nbsp;clinical students. A study evaluated the level of anxiety and working conditions of health care workers\u0026nbsp;during\u0026nbsp;the COVID-19\u0026nbsp;outbreak\u0026nbsp;and showed that service providers\u0026nbsp;for\u0026nbsp;patients diagnosed with COVID-19 had better personal protective measures\u0026nbsp;[33].\u003csup\u003e\u0026nbsp;\u003c/sup\u003eHowever,\u0026nbsp;a\u0026nbsp;study by Rahmanian et al. indicated that the performance of administrative staff was better than that of medical staff\u0026nbsp;(22).\u003csup\u003e\u0026nbsp;\u003c/sup\u003eIn fact, students at the basic sciences level had better preventive behavior despite having less clinical exposure to the coronavirus due to their strong motivation and more favorable attitude. The results of this study showed the average level of the constructs of the integrated social cognition model for\u0026nbsp;preventing\u0026nbsp;COVID-19 and the factors affecting them in medical students at Babol University of Medical Sciences. The results of this study could be helpful\u0026nbsp;for evaluating, designing, and implementing\u0026nbsp;better health education interventions to improve social cognitive constructs\u0026nbsp;related to\u0026nbsp;COVID-19 preventive behaviors among medical students.\u003c/p\u003e\n\u003ch1\u003eLimitations\u003c/h1\u003e\n\u003cp\u003eThis study has several limitations that should be considered, such as the use of self-report scales, the use of available samples, the cross-sectional nature of the study design, and the indeterminacy of causal relationships in the model under study.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eTBP: Theory of Planned Behavior\u003c/p\u003e\n\u003cp\u003eHAPA: Health Action Process Approach\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe code of ethics (IR.MUBABOL.HRI.REC.1400.144) was obtained from the Ethics Committee of Babol University of Medical Sciences, and informed consent was obtained from the participants.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Research and Technology Vice-Chancellor of Babol University of Medical Sciences.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions\u003c/p\u003e\n\u003cp\u003eConceptualization: Z.Gh, MA. J and A.P\u003c/p\u003e\n\u003cp\u003eMethodology: Z.Gh, MA. J, HA.N and A.P\u003c/p\u003e\n\u003cp\u003eProject administration: A.M, Z.Gh, MA.J\u003c/p\u003e\n\u003cp\u003eFormal analysis: HA.N\u003c/p\u003e\n\u003cp\u003eWriting Original Draft: A.M, Z.Gh, MA.J\u003c/p\u003e\n\u003cp\u003eWriting Review \u0026amp; Editing: A.M, Z.Gh, MA.J\u003c/p\u003e\n\u003cp\u003eAll authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe thank all the medical students who participated in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorldometer. Countries where COVID-19 has spread. [updated March 12, 2024. Available from: https://www.worldometers.info/coronavirus/countries-where-coronavirus-has-spread/.\u003c/li\u003e\n\u003cli\u003eNakhaeizadeh A, Mohammadi S. Assessing the Level of Engagement in Preventive Behaviors and COVID-19 Related Anxiety in Iranian Adults. 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International journal of environmental research and public health. 2019;17(1):64. doi: 10.3390/ijerph17010064 \u003c/li\u003e\n\u003cli\u003eHagger MS, Smith SR, Keech JJ, Moyers SA, Hamilton K. Predicting social distancing intention and behavior during the COVID-19 pandemic: An integrated social cognition model. Ann Behav Med. 2020;54(10):713-27. doi: 10.1093/abm/kaaa073.\u003c/li\u003e\n\u003cli\u003eLin CY, Imani V, Majd NR, Ghasemi Z, Griffiths MD, Hamilton K, et al. Using an integrated social cognition model to predict COVID‐19 preventive behaviours. British journal of health psychology. 2020;25(4):981-1005. doi: 10.111/bjhp.12465.\u003c/li\u003e\n\u003cli\u003eAlsoghair M, Almazyad M, Alburaykan T, Alsultan A, Alnughaymishi A, Almazyad S, et al. Medical students and COVID-19: knowledge, preventive behaviors, and risk perception. International journal of environmental research and public health. 2021;18(2):842. doi: 10.3390/ijerph18020842 \u003c/li\u003e\n\u003cli\u003eRahmanian M, Dorodchi A, Zarenezhad M, Hatami N, Javdani F, Kalani N. Knowledge, Attitude and Practice of Students of Jahrom University of medical sciences to the new coronavirus (Covid-19). Med J Mashhad Univ Med Sci. 2020;63(3):2359-69. 10.22038/MJMS.2020.16937 \u003c/li\u003e\n\u003cli\u003eKhazaee-Pool M, Shahrousvand S, Naghibi SA. Predicting Covid-19 preventive behaviors based on health belief model: An Internet-based study in Mazandaran province, Iran. J Maz Univ Med. 2020;30(190):56-66. jmums.mazums.ac.ir/article-1-15530-en.html.\u003c/li\u003e\n\u003cli\u003eDelshad Noghabi A, Yoshany N, Mohammadzadeh F, Javanbakht S. Predictors of COVID-19 preventive behaviors in Iranian population over 15 years old: an application of health belief model. J Maz Univ Med. 2020;30(191):13-21. jmums.mazums.ac.ir/article-1-15215-en.html.\u003c/li\u003e\n\u003cli\u003eHagger MS, Hamilton K. Social cognition theories and behavior change in COVID-19: A conceptual review. Behav Res Ther. 2022;154:104095. doi: 10.1016/j.brat.2022. .\u003c/li\u003e\n\u003cli\u003eNasirzadeh M, Aligol M. Assessmentof 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.\u003c/li\u003e\n\u003cli\u003eDuan 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. doi.org/10.1186/s12877-022-02785-2 \u003c/li\u003e\n\u003cli\u003eMahindarathne PP. Assessing COVID-19 preventive behaviours using the health belief model: A Sri Lankan study. J Taibah Univ Med Sci. 2021;16(6):914-9. doi: 10.1016/j.jtumed.2021.07.006 \u003c/li\u003e\n\u003cli\u003eRezaee-Aderiani E, Soltani T, Mazloumi Mahmoud Abad SS, Madidizadeh F, Sharif Yazdi M. Preventive Covid-19 behavior among Youth using the health belief model in Khomeyni Shahr, Isfahan. The Journal of Tolooebehdasht 2023;22(1):32-46. doi.org/10.18502/tbj.v22i1.2778 \u003c/li\u003e\n\u003cli\u003eXiang N, Shi Y, Wu J, Zhang S, Ye M, Peng Z, et al. Knowledge, attitudes and practices (KAP) relating to avian influenza in urban and rural areas of China. BMC Infect Dis. 2010;10:34. doi: 10.1186/471-2334-10-34.\u003c/li\u003e\n\u003cli\u003eHaischer MH, Beilfuss R, Hart MR, Opielinski L, Wrucke D, Zirgaitis G, et al. Who is wearing a mask? Gender-, age-, and location-related differences during the COVID-19 pandemic. PloS one. 2020;15(10):e0240785. doi.org/10.1371/journal.pone. .\u003c/li\u003e\n\u003cli\u003eEzati-Rad R, Mohseni S, Kamalzadeh Takhti H, 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;21:466. doi.org/10.1186/s12889-021-0500-w \u003c/li\u003e\n\u003cli\u003eBostan S, Akbolat M, Kaya A, Ozata M, Gunes D. Assessments of anxiety levels and working conditions of health employees working in COVİD-19 pandemic hospitals. Electron J Gen Med. 2020;17(5):em246. https://doi.org/10.1186/s12889-021-0500-w \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-research-notes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resn","sideBox":"Learn more about [BMC Research Notes](http://bmcresnotes.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/resn/default.aspx","title":"BMC Research Notes","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, preventive behavior, social cognition model","lastPublishedDoi":"10.21203/rs.3.rs-4149386/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4149386/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e: The COVID-19 outbreak in Iran prompted the investigation of preventive behaviors in vulnerable and key groups. This descriptive and analytical cross-sectional study aimed to determine COVID-19 prevention behaviors among medical students using an integrated social cognition model and identified influencing factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The results of the study of 650 medical students with a mean age of 24.37±3.78 years showed that the total score of the integrated social cognition model was at a medium level (85.44±8.70). The constructs of attitude (16.14±2.66), subjective norms (5.33±1.30), perceived behavioral control (8.18±1.76), action self-efficacy (8.60±1.66), maintenance self-efficacy (12.29±2.25), intention (8.05±1.55), action planning (8.00±1.62), coping planning (8.08±1.62), and COVID‐19 preventive behaviors (10.78±1.99) were at a medium level. There was a good correlation between the constructs of the integrated model (r = 0.42-0.64, p\u0026lt;0.001). Students who were older, unmarried, had a mother or father with a university education, were nondormitory, were native, at the basic science level obtained higher scores for the model constructs (p\u0026lt;0.001). These findings should be considered to improve health education interventions and encourage COVID-19 preventive behaviors in students.\u003c/p\u003e","manuscriptTitle":" COVID-19 Preventive behaviors based on social cognitive integrative model among medical students","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-04 12:05:05","doi":"10.21203/rs.3.rs-4149386/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-28T10:00:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-27T15:33:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"225140805027103428629328375783850001896","date":"2024-05-27T14:00:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"31b3d876-857e-47d1-8681-536c21fa2494","date":"2024-04-19T13:24:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"916b20b5-1897-45aa-af3d-133a10f54509","date":"2024-04-16T05:15:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-15T13:55:11+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-04-04T09:45:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-01T03:37:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-01T03:37:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Research Notes","date":"2024-03-22T11:28:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-research-notes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resn","sideBox":"Learn more about [BMC Research Notes](http://bmcresnotes.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/resn/default.aspx","title":"BMC Research Notes","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0a579475-ba25-4e29-a5d7-554ce540149e","owner":[],"postedDate":"April 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-21T16:03:57+00:00","versionOfRecord":{"articleIdentity":"rs-4149386","link":"https://doi.org/10.1186/s13104-025-07377-y","journal":{"identity":"bmc-research-notes","isVorOnly":false,"title":"BMC Research Notes"},"publishedOn":"2025-07-15 15:57:27","publishedOnDateReadable":"July 15th, 2025"},"versionCreatedAt":"2024-04-04 12:05:05","video":"","vorDoi":"10.1186/s13104-025-07377-y","vorDoiUrl":"https://doi.org/10.1186/s13104-025-07377-y","workflowStages":[]},"version":"v1","identity":"rs-4149386","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4149386","identity":"rs-4149386","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}