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Volume 13, Issue 3 (2025)
Health Educ Health Promot 2025, 13(3): 413-419 |
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History
Received: 2025/07/1 | Accepted: 2025/08/15 | Published: 2025/08/19
Received: 2025/07/1 | Accepted: 2025/08/15 | Published: 2025/08/19
How to cite this article
Karimi M, Motori P, Mohammadi A, Etebari M. Relationship Between Predictors of Hypertension Self-Care Behaviors Based on Protection Motivation Theory and Demographic Factors. Health Educ Health Promot 2025; 13 (3) :413-419
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1- Department of Health Promotion, Faculty of Health, Shiraz University of Medical Sciences, Shiraz, Iran
2- Department of Community Education in the Health System, Faculty of Health, Shiraz University of Medical Sciences, Shiraz, Iran
3- “Student Research Committee†and “Department of Health Promotion, School of Healthâ€, Shiraz University of Medical Sciences, Shiraz, Iran
2- Department of Community Education in the Health System, Faculty of Health, Shiraz University of Medical Sciences, Shiraz, Iran
3- “Student Research Committee†and “Department of Health Promotion, School of Healthâ€, Shiraz University of Medical Sciences, Shiraz, Iran
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Introduction
Hypertension refers to a condition in which a person’s blood pressure remains consistently above the normal range [1]. This condition can lead to vascular damage and harm vital organs such as the heart, brain, and kidneys over time [2]. According to the World Health Organization’s 2023 report, it is estimated that around 1.28 billion adults aged 30 to 79 are affected by hypertension, with two-thirds of them living in low- and middle-income countries. Despite its widespread prevalence, about 46% of those with hypertension are unaware of their condition, and less than half (42%) have been diagnosed and received adequate treatment [3]. A study conducted in Iran in 2024 showed that the prevalence of high blood pressure is 21.44% among men and 33.53% among women [4].
Hypertension significantly increases the risk of developing cardiovascular diseases, stroke, and kidney failure [5]. One of the primary strategies for managing hypertension and maintaining blood pressure within a healthy range is engaging in self-care behaviors [6]. These behaviors include adherence to a proper diet, regular physical activity, weight management, compliance with prescribed medications, and reducing the intake of salt and fats [7].
Behavioral change models provide valuable frameworks for understanding the factors influencing self-care behaviors among patients. One of the key models in this field is the protection motivation theory (PMT), introduced by Rogers in 1975 [8]. This theory explains how individuals adopt protective behaviors in response to health threats and identifies the factors that influence their motivation to safeguard their health. PMT consists of five main components, including perceived threat, which includes two subscales—perceived susceptibility (the likelihood of developing a disease or its complications) and perceived severity (the seriousness of the disease’s consequences), perceived rewards, which refers to the potential benefits of engaging in unhealthy behaviors, such as the pleasure of consuming unhealthy foods or the time saved by avoiding physical activity, perceived response efficacy, which reflects an individual’s belief in the effectiveness of a healthy behavior in reducing the risk of disease, self-efficacy, defined as the individual’s belief in their ability to succeed in accomplishing preventive behaviors, response costs, which include barriers such as financial costs, time, effort, and medication side effects that may prevent individuals from engaging in healthy behaviors, and finally, protection motivation, which represents the individual’s willingness and commitment to adopting healthy behaviors [9, 10].
On the other hand, understanding the relationship between demographic factors (such as age, gender, education level, and economic status) and predictors of self-care behaviors can facilitate the design of effective interventions for improving hypertension management [11]. Various studies have demonstrated that certain demographic factors (such as sex, education, income level, and marital status) directly influence patients’ adherence to self-care behaviors [12-14]. However, the authors did not find any studies that examined the relationship between these demographic factors and the constructs of behavior change models, particularly PMT. Therefore, this study aimed to investigate the relationship between demographic factors and self-care behaviors and to identify their predictors based on PMT in patients with hypertension.
Instrument and Methods
Study design and sample
This cross-sectional study was conducted among patients with hypertension at eight urban and rural comprehensive health service centers in Omidieh, a city in Khuzestan Province, southern Iran, in 2022. Participants were selected using stratified random sampling, ensuring an equal distribution of men and women in the study. The sample size of 420 was determined based on a study by Ghanei Gheshlagh et al. [15], using IBM PASS 15 software, and considering a significance level (α=0.05), a margin of error (d=0.05), and a 10% non-response rate. To select and recruit the participants, an equal number of 25 men and 25 women were randomly chosen from each comprehensive health center using the lists of patients in Iran’s Integrated Health System (SIB).
Hypertensive patients who were 30 years old or older, diagnosed with primary hypertension for at least six months, had no severe complications related to hypertension, and had no history of chronic diseases or acute physical or mental illnesses were included in the study. Participants who did not fully respond to the questionnaire were excluded from the analysis.
Research tools
The questionnaire used for data collection in this study consisted of three sections.
- Demographic information form: This form collected information, such as sex, age, education level, marital status, and job status.
- Protection motivation theory (PMT) constructs: The constructs assessed were perceived severity (5 items, 5-point Likert scale: very high/high/moderate/low/very low), perceived susceptibility (5 items, 5-point Likert scale: very high/high/moderate/low/very low), intrinsic and extrinsic rewards (14 items, 5-point Likert scale: strongly agree/agree/neutral/disagree/strongly disagree), response costs (11 items, 5-point Likert scale: strongly agree/agree/neutral/disagree/strongly disagree), Self-efficacy (9 items, 5-point Likert scale: very high/high/moderate/low/very low), response efficacy (9 items, 5-point Likert scale: very high/high/moderate/low/very low).
Face and content validity of the questionnaire were assessed and confirmed by a panel of 10 experts in health education and promotion, nutrition, and cardiology. Content validity ratios (CVR>0.75) and content validity indices (CVI>0.79) were obtained, which were deemed appropriate based on the criteria set by Lawshe [16] and Waltz et al. [17]. The Cronbach’s alpha values were within the acceptable range of 0.7 to 0.90 for the constructs. In pilot research with 30 participants conducted over a two-week interval, the questionnaire’s external reliability was evaluated using intra-class correlation (ICC), which revealed good reliability (ICC>0.75, p=0.01).
- Self-Care Questionnaire for High Blood Pressure: This scale, developed by Han et al., includes 20 items rated on a 4-point scale (always-never) [18]. Ghanei Gheshlagh et al. assessed the reliability of the Persian version of this questionnaire and discovered that eliminating a specific alcohol-related item leads to a Cronbach’s alpha of 0.86 [15].
Data collection procedure
After receiving permission from the Shiraz University of Medical Sciences Ethics Committee, participants were informed about the goals of the study and signed a consent form. They were then given questionnaires to complete. The researcher stayed with the participants as they filled out the questionnaires, providing answers and clarifying any uncertainties. On average, it took approximately 20 minutes to finish the surveys. The study was conducted according to the principles of the Declaration of Helsinki.
Data analysis
The data were analyzed using SPSS 24 software. The normal distribution of the data was assessed and confirmed using the Kolmogorov-Smirnov test (p>0.01). Independent t-tests and ANOVA were used to examine differences in quantitative parameters between different demographic subgroups. The significance level was set at <0.05.
Findings
A total of 420 questionnaires were administered to the participants, and 397 individuals (198 women and 199 men) completed the questionnaires (response rate=94.5%). The respondents’ mean age was 56.20 (9.26) years, ranging from 30 to 87 years (Table 1).
Table 1. Frequency of study participants’ demographic parameters
![src=./files/hehp/images/HTML_Publish/82094/1.png]()
Individuals with higher education levels, particularly university graduates, tended to have statistically significantly higher mean scores in self-efficacy (p=0.033) and response cost (p=0.009). While perceived threat (p=0.052) was close to statistical significance, other parameters, such as self-care behaviors, perceived reward, and response efficacy, did not show significant differences (Table 2).
Table 2. Comparing the participants’ mean scores of self-care behaviors and protection motivation theory constructs by education levels
![src=./files/hehp/images/HTML_Publish/82094/2.png]()
There was a significant difference between men and women in perceived threat (higher in men, p=0.015) and perceived reward (higher in men, p<0.001), while other parameters did not show statistically significant differences. Regarding marital status, there were no significant statistical differences in the mean scores of the parameters between married and single individuals (Table 3).
Table 3. Comparing mean scores of self-care behaviors and protection motivation theory constructs by sex and marital status
![src=./files/hehp/images/HTML_Publish/82094/3.png]()
Perceived reward score was significantly higher among the part-time worker group compared to the other groups (p=0.006). However, no significant differences were observed across different employment groups for self-care behaviors, perceived threat, response cost, response efficacy, and self-efficacy (Table 4).
Table 4. Comparing mean scores of self-care behaviors and protection motivation theory constructs by employment status
![src=./files/hehp/images/HTML_Publish/82094/4.png]()
Individuals with excellent economic status had significantly higher self-care behaviors and self-efficacy scores. Additionally, perceived threat was significantly higher among individuals with poor economic status. Response cost was also highest in the group with poor economic status, while perceived rewards peaked in the group with excellent economic status. However, response efficacy did not show any significant differences across the various economic groups (Table 5).
Table 5. Analysis of protective motivation theory constructs by economic status
![src=./files/hehp/images/HTML_Publish/82094/5.png]()
Discussion
This study assessed the perspectives of 397 hypertensive patients at eight urban and rural comprehensive health service centers and eight health posts in Omidiyeh city. The aim was to investigate the relationship between demographic factors and self-care behaviors in patients with hypertension, as well as to assess the impact of these factors on predicting the PTM.
Response cost and self-efficacy showed significant differences across different educational levels. Specifically, as individuals’ educational levels increased, their mean scores for self-efficacy and response cost also increased. However, no significant differences were observed in the other parameters studied across educational levels. This finding may be explained by the fact that higher education equips individuals with more information and greater awareness about health, thereby enhancing their sense of efficacy. The significant differences in response cost and self-efficacy clearly demonstrate the positive impact of education on individuals’ capacity to cope with health threats. Consistent with our study, Bağ & Mollaoğlu also indicated that self-efficacy levels increase with higher educational attainment [19]. Rahaei et al. found that there is no significant difference between different education levels in performing proactive self-care behaviors for cancer prevention [20]. The results of some studies are also inconsistent with our findings. For example, Simbar et al. showed that self-care among postmenopausal women is positively correlated with the educational levels of both the women and their spouses [21]. In the study by Keshavarz et al., no significant difference is observed between literate and illiterate individuals in response cost and response efficacy [22]. These results can be considered in planning educational interventions, as patients with lower levels of education may need additional training to enhance their sense of self-efficacy.
There were significant differences between men and women in perceived threat and perceived reward, indicating that sex plays an important role in individuals’ perceptions of threats and rewards. Perceived threats and perceived rewards in men were significantly higher than in women. These differences may be attributed to cultural, social, and even biological distinctions between men and women. While self-care behaviors and self-efficacy did not show significant differences between genders, it appears that gender has a greater impact on certain psychological parameters, such as threat and reward. Consistent with our findings, Qian & Yuan also report no difference in self-efficacy and self-care based on gender [23]. In the study by Yan et al. regarding the intention to quit smoking, men perceive greater rewards from smoking compared to women [24]. However, contrary to our findings, in the study by Hu et al., women adhere better to self-care behaviors [25]. Similarly, in the study by Bağ & Mollaoğlu on hemodialysis patients, male participants have higher self-efficacy compared to female participants [19]. In another study by Yan et al. on the intention to quit smoking, female participants have higher self-efficacy for quitting smoking than males and also perceive higher response costs [24]. Furthermore, in the study by Keshavarz et al., which is inconsistent with our results, no significant difference in perceived threat is observed between men and women, and response efficacy is reported to be higher in women than in men. However, regarding response cost, consistent with our findings, no significant sex difference is observed [22].
The inconsistency in some findings may be due to the fact that the sample size in certain studies was not representative of the entire population, or differences in the research topics may have contributed to these discrepancies. Given that there are relatively few studies investigating the predictive role of demographic factors based on behavior change models, we were compelled to use articles with topics outside the domain of hypertension for comparison. Considering the influence of sex on the perception of certain constructs, it is recommended that healthcare providers take sex into account during their counseling on hypertension self-care and focus on aspects that are of greater importance to each sex.
In terms of marital status, our study found no significant differences between the studied parameters and individuals’ marital status. Consistent with our findings, Bağ & Mollaoğlu also reported that marital status has no effect on self-care or self-efficacy [19]. Similarly, in the study by Zare Sakhvidi et al., no significant differences were found in cancer preventive behaviors based on marital status [26]. In the study by Rahaei et al. on cancer preventive behaviors, there are no significant differences in self-care behaviors between married and single individuals [20]. These findings may suggest that being married or single alone cannot account for differences in these parameters. This may indicate that both married and single individuals act similarly in various aspects of motivation and self-care. However, given the complexities of social relationships and the different impacts that married life or single living may have on individuals, future studies should explore this issue more thoroughly and consider factors such as lifestyle and social support in this context.
Among different employment groups, a significant difference existed only in perceived reward. Part-time employees perceived significantly greater rewards compared to the other groups. Consistent with our findings, Bağ & Mollaoğlu indicated that employed individuals score higher in self-care and self-efficacy [19]. Similarly, Simbar et al. reported that self-care among employed postmenopausal women is significantly higher than that of housewives, and women whose husbands are employed also score higher than those whose husbands are unemployed [21]. In the study by Qian & Yuan, unemployed cancer patients have lower self-efficacy scores compared to retired participants or those employed full-time [23]. However, in the study by Afshar et al., there is no significant difference in perceived threat between employed and unemployed individuals [27]. These findings may be valuable for those working in occupational health or workplace health promotion, as they can inform the planning of targeted interventions for individuals in different employment situations.
Economic status can be one of the most important factors influencing self-care behaviors and health-related motivations [28]. Individuals with good economic status had significantly higher levels of self-care and self-efficacy. Moreover, perceived threat and perceived rewards were significantly higher among those with excellent economic status compared to other economic levels. Conversely, response cost was significantly higher among individuals with poor economic status. Similarly, in the study by Bağ & Mollaoğlu, individuals with higher income levels and access to health insurance report higher self-care and self-efficacy scores [19]. Simbar et al. also demonstrate a positive correlation between menopausal women’s self-care and family income level [21]. In the study by Afshar et al., perceived severity scores are higher among individuals with poor economic status compared to those with better economic status [27]. However, in the study by Qian & Yuan, there are no differences in self-efficacy for self-care based on insurance coverage and household income [23]. These findings may reflect fundamental differences in individuals’ access to resources, information, and financial and social capabilities. Therefore, individuals with lower economic status may face greater challenges in adopting self-care behaviors. Overall, these results can inform health policy and strategies to support socioeconomically disadvantaged groups.
The sample was drawn from a single geographic region, which may restrict the diversity of the target population and limit the applicability of the findings to broader communities. Since cultural factors and health-related behaviors vary across different regions of the country, the findings of this study cannot be generalized to all adults with hypertension in Iran. Therefore, similar studies should be conducted in other provinces, and the results should be compared. One of the strengths of this study is that it was conducted on a reasonably large sample of patients with hypertension. Additionally, a valid and reliable questionnaire was developed and validated during the study to assess the constructs of the Protection Motivation Model.
Demographic characteristics play a significant role in shaping self-care behaviors and protective motivation. These findings highlight the need for tailored health education programs and targeted interventions that consider individual and social determinants of health. By recognizing and addressing these differences, public health initiatives can be more effective in promoting sustainable health behaviors and improving overall community well-being. Future studies should employ longitudinal designs to examine long-term behavioral changes and protective motivation. Additionally, incorporating parameters, such as social support, healthcare accessibility, and cultural factors, can provide a more comprehensive understanding of the determinants of health behaviors. Furthermore, sampling from diverse geographic and economic backgrounds would enhance the generalizability of the results and help identify varied behavioral patterns across different communities.
Conclusion
Education level, gender, employment status, and economic status play a significant role in shaping self-care behaviors and protective motivation.
Acknowledgments: We express our gratitude to everyone who participated in this research. The authors are thankful to Shiraz University of Medical Sciences. The authors acknowledge Ms. Motori for her significant and impactful role in the research process.
Ethical Permissions: Ethics approval and consent to participate in the study mentioned above were obtained from the ethics board committee of Shiraz University of Medical Sciences (IR.SUMS.SCHEANUT.REC.1401.008).
Conflicts of Interests: The authors declared no competing interests.
Hypertension refers to a condition in which a person’s blood pressure remains consistently above the normal range [1]. This condition can lead to vascular damage and harm vital organs such as the heart, brain, and kidneys over time [2]. According to the World Health Organization’s 2023 report, it is estimated that around 1.28 billion adults aged 30 to 79 are affected by hypertension, with two-thirds of them living in low- and middle-income countries. Despite its widespread prevalence, about 46% of those with hypertension are unaware of their condition, and less than half (42%) have been diagnosed and received adequate treatment [3]. A study conducted in Iran in 2024 showed that the prevalence of high blood pressure is 21.44% among men and 33.53% among women [4].
Hypertension significantly increases the risk of developing cardiovascular diseases, stroke, and kidney failure [5]. One of the primary strategies for managing hypertension and maintaining blood pressure within a healthy range is engaging in self-care behaviors [6]. These behaviors include adherence to a proper diet, regular physical activity, weight management, compliance with prescribed medications, and reducing the intake of salt and fats [7].
Behavioral change models provide valuable frameworks for understanding the factors influencing self-care behaviors among patients. One of the key models in this field is the protection motivation theory (PMT), introduced by Rogers in 1975 [8]. This theory explains how individuals adopt protective behaviors in response to health threats and identifies the factors that influence their motivation to safeguard their health. PMT consists of five main components, including perceived threat, which includes two subscales—perceived susceptibility (the likelihood of developing a disease or its complications) and perceived severity (the seriousness of the disease’s consequences), perceived rewards, which refers to the potential benefits of engaging in unhealthy behaviors, such as the pleasure of consuming unhealthy foods or the time saved by avoiding physical activity, perceived response efficacy, which reflects an individual’s belief in the effectiveness of a healthy behavior in reducing the risk of disease, self-efficacy, defined as the individual’s belief in their ability to succeed in accomplishing preventive behaviors, response costs, which include barriers such as financial costs, time, effort, and medication side effects that may prevent individuals from engaging in healthy behaviors, and finally, protection motivation, which represents the individual’s willingness and commitment to adopting healthy behaviors [9, 10].
On the other hand, understanding the relationship between demographic factors (such as age, gender, education level, and economic status) and predictors of self-care behaviors can facilitate the design of effective interventions for improving hypertension management [11]. Various studies have demonstrated that certain demographic factors (such as sex, education, income level, and marital status) directly influence patients’ adherence to self-care behaviors [12-14]. However, the authors did not find any studies that examined the relationship between these demographic factors and the constructs of behavior change models, particularly PMT. Therefore, this study aimed to investigate the relationship between demographic factors and self-care behaviors and to identify their predictors based on PMT in patients with hypertension.
Instrument and Methods
Study design and sample
This cross-sectional study was conducted among patients with hypertension at eight urban and rural comprehensive health service centers in Omidieh, a city in Khuzestan Province, southern Iran, in 2022. Participants were selected using stratified random sampling, ensuring an equal distribution of men and women in the study. The sample size of 420 was determined based on a study by Ghanei Gheshlagh et al. [15], using IBM PASS 15 software, and considering a significance level (α=0.05), a margin of error (d=0.05), and a 10% non-response rate. To select and recruit the participants, an equal number of 25 men and 25 women were randomly chosen from each comprehensive health center using the lists of patients in Iran’s Integrated Health System (SIB).
Hypertensive patients who were 30 years old or older, diagnosed with primary hypertension for at least six months, had no severe complications related to hypertension, and had no history of chronic diseases or acute physical or mental illnesses were included in the study. Participants who did not fully respond to the questionnaire were excluded from the analysis.
Research tools
The questionnaire used for data collection in this study consisted of three sections.
- Demographic information form: This form collected information, such as sex, age, education level, marital status, and job status.
- Protection motivation theory (PMT) constructs: The constructs assessed were perceived severity (5 items, 5-point Likert scale: very high/high/moderate/low/very low), perceived susceptibility (5 items, 5-point Likert scale: very high/high/moderate/low/very low), intrinsic and extrinsic rewards (14 items, 5-point Likert scale: strongly agree/agree/neutral/disagree/strongly disagree), response costs (11 items, 5-point Likert scale: strongly agree/agree/neutral/disagree/strongly disagree), Self-efficacy (9 items, 5-point Likert scale: very high/high/moderate/low/very low), response efficacy (9 items, 5-point Likert scale: very high/high/moderate/low/very low).
Face and content validity of the questionnaire were assessed and confirmed by a panel of 10 experts in health education and promotion, nutrition, and cardiology. Content validity ratios (CVR>0.75) and content validity indices (CVI>0.79) were obtained, which were deemed appropriate based on the criteria set by Lawshe [16] and Waltz et al. [17]. The Cronbach’s alpha values were within the acceptable range of 0.7 to 0.90 for the constructs. In pilot research with 30 participants conducted over a two-week interval, the questionnaire’s external reliability was evaluated using intra-class correlation (ICC), which revealed good reliability (ICC>0.75, p=0.01).
- Self-Care Questionnaire for High Blood Pressure: This scale, developed by Han et al., includes 20 items rated on a 4-point scale (always-never) [18]. Ghanei Gheshlagh et al. assessed the reliability of the Persian version of this questionnaire and discovered that eliminating a specific alcohol-related item leads to a Cronbach’s alpha of 0.86 [15].
Data collection procedure
After receiving permission from the Shiraz University of Medical Sciences Ethics Committee, participants were informed about the goals of the study and signed a consent form. They were then given questionnaires to complete. The researcher stayed with the participants as they filled out the questionnaires, providing answers and clarifying any uncertainties. On average, it took approximately 20 minutes to finish the surveys. The study was conducted according to the principles of the Declaration of Helsinki.
Data analysis
The data were analyzed using SPSS 24 software. The normal distribution of the data was assessed and confirmed using the Kolmogorov-Smirnov test (p>0.01). Independent t-tests and ANOVA were used to examine differences in quantitative parameters between different demographic subgroups. The significance level was set at <0.05.
Findings
A total of 420 questionnaires were administered to the participants, and 397 individuals (198 women and 199 men) completed the questionnaires (response rate=94.5%). The respondents’ mean age was 56.20 (9.26) years, ranging from 30 to 87 years (Table 1).
Table 1. Frequency of study participants’ demographic parameters
Individuals with higher education levels, particularly university graduates, tended to have statistically significantly higher mean scores in self-efficacy (p=0.033) and response cost (p=0.009). While perceived threat (p=0.052) was close to statistical significance, other parameters, such as self-care behaviors, perceived reward, and response efficacy, did not show significant differences (Table 2).
Table 2. Comparing the participants’ mean scores of self-care behaviors and protection motivation theory constructs by education levels
There was a significant difference between men and women in perceived threat (higher in men, p=0.015) and perceived reward (higher in men, p<0.001), while other parameters did not show statistically significant differences. Regarding marital status, there were no significant statistical differences in the mean scores of the parameters between married and single individuals (Table 3).
Table 3. Comparing mean scores of self-care behaviors and protection motivation theory constructs by sex and marital status
Perceived reward score was significantly higher among the part-time worker group compared to the other groups (p=0.006). However, no significant differences were observed across different employment groups for self-care behaviors, perceived threat, response cost, response efficacy, and self-efficacy (Table 4).
Table 4. Comparing mean scores of self-care behaviors and protection motivation theory constructs by employment status
Individuals with excellent economic status had significantly higher self-care behaviors and self-efficacy scores. Additionally, perceived threat was significantly higher among individuals with poor economic status. Response cost was also highest in the group with poor economic status, while perceived rewards peaked in the group with excellent economic status. However, response efficacy did not show any significant differences across the various economic groups (Table 5).
Table 5. Analysis of protective motivation theory constructs by economic status
Discussion
This study assessed the perspectives of 397 hypertensive patients at eight urban and rural comprehensive health service centers and eight health posts in Omidiyeh city. The aim was to investigate the relationship between demographic factors and self-care behaviors in patients with hypertension, as well as to assess the impact of these factors on predicting the PTM.
Response cost and self-efficacy showed significant differences across different educational levels. Specifically, as individuals’ educational levels increased, their mean scores for self-efficacy and response cost also increased. However, no significant differences were observed in the other parameters studied across educational levels. This finding may be explained by the fact that higher education equips individuals with more information and greater awareness about health, thereby enhancing their sense of efficacy. The significant differences in response cost and self-efficacy clearly demonstrate the positive impact of education on individuals’ capacity to cope with health threats. Consistent with our study, Bağ & Mollaoğlu also indicated that self-efficacy levels increase with higher educational attainment [19]. Rahaei et al. found that there is no significant difference between different education levels in performing proactive self-care behaviors for cancer prevention [20]. The results of some studies are also inconsistent with our findings. For example, Simbar et al. showed that self-care among postmenopausal women is positively correlated with the educational levels of both the women and their spouses [21]. In the study by Keshavarz et al., no significant difference is observed between literate and illiterate individuals in response cost and response efficacy [22]. These results can be considered in planning educational interventions, as patients with lower levels of education may need additional training to enhance their sense of self-efficacy.
There were significant differences between men and women in perceived threat and perceived reward, indicating that sex plays an important role in individuals’ perceptions of threats and rewards. Perceived threats and perceived rewards in men were significantly higher than in women. These differences may be attributed to cultural, social, and even biological distinctions between men and women. While self-care behaviors and self-efficacy did not show significant differences between genders, it appears that gender has a greater impact on certain psychological parameters, such as threat and reward. Consistent with our findings, Qian & Yuan also report no difference in self-efficacy and self-care based on gender [23]. In the study by Yan et al. regarding the intention to quit smoking, men perceive greater rewards from smoking compared to women [24]. However, contrary to our findings, in the study by Hu et al., women adhere better to self-care behaviors [25]. Similarly, in the study by Bağ & Mollaoğlu on hemodialysis patients, male participants have higher self-efficacy compared to female participants [19]. In another study by Yan et al. on the intention to quit smoking, female participants have higher self-efficacy for quitting smoking than males and also perceive higher response costs [24]. Furthermore, in the study by Keshavarz et al., which is inconsistent with our results, no significant difference in perceived threat is observed between men and women, and response efficacy is reported to be higher in women than in men. However, regarding response cost, consistent with our findings, no significant sex difference is observed [22].
The inconsistency in some findings may be due to the fact that the sample size in certain studies was not representative of the entire population, or differences in the research topics may have contributed to these discrepancies. Given that there are relatively few studies investigating the predictive role of demographic factors based on behavior change models, we were compelled to use articles with topics outside the domain of hypertension for comparison. Considering the influence of sex on the perception of certain constructs, it is recommended that healthcare providers take sex into account during their counseling on hypertension self-care and focus on aspects that are of greater importance to each sex.
In terms of marital status, our study found no significant differences between the studied parameters and individuals’ marital status. Consistent with our findings, Bağ & Mollaoğlu also reported that marital status has no effect on self-care or self-efficacy [19]. Similarly, in the study by Zare Sakhvidi et al., no significant differences were found in cancer preventive behaviors based on marital status [26]. In the study by Rahaei et al. on cancer preventive behaviors, there are no significant differences in self-care behaviors between married and single individuals [20]. These findings may suggest that being married or single alone cannot account for differences in these parameters. This may indicate that both married and single individuals act similarly in various aspects of motivation and self-care. However, given the complexities of social relationships and the different impacts that married life or single living may have on individuals, future studies should explore this issue more thoroughly and consider factors such as lifestyle and social support in this context.
Among different employment groups, a significant difference existed only in perceived reward. Part-time employees perceived significantly greater rewards compared to the other groups. Consistent with our findings, Bağ & Mollaoğlu indicated that employed individuals score higher in self-care and self-efficacy [19]. Similarly, Simbar et al. reported that self-care among employed postmenopausal women is significantly higher than that of housewives, and women whose husbands are employed also score higher than those whose husbands are unemployed [21]. In the study by Qian & Yuan, unemployed cancer patients have lower self-efficacy scores compared to retired participants or those employed full-time [23]. However, in the study by Afshar et al., there is no significant difference in perceived threat between employed and unemployed individuals [27]. These findings may be valuable for those working in occupational health or workplace health promotion, as they can inform the planning of targeted interventions for individuals in different employment situations.
Economic status can be one of the most important factors influencing self-care behaviors and health-related motivations [28]. Individuals with good economic status had significantly higher levels of self-care and self-efficacy. Moreover, perceived threat and perceived rewards were significantly higher among those with excellent economic status compared to other economic levels. Conversely, response cost was significantly higher among individuals with poor economic status. Similarly, in the study by Bağ & Mollaoğlu, individuals with higher income levels and access to health insurance report higher self-care and self-efficacy scores [19]. Simbar et al. also demonstrate a positive correlation between menopausal women’s self-care and family income level [21]. In the study by Afshar et al., perceived severity scores are higher among individuals with poor economic status compared to those with better economic status [27]. However, in the study by Qian & Yuan, there are no differences in self-efficacy for self-care based on insurance coverage and household income [23]. These findings may reflect fundamental differences in individuals’ access to resources, information, and financial and social capabilities. Therefore, individuals with lower economic status may face greater challenges in adopting self-care behaviors. Overall, these results can inform health policy and strategies to support socioeconomically disadvantaged groups.
The sample was drawn from a single geographic region, which may restrict the diversity of the target population and limit the applicability of the findings to broader communities. Since cultural factors and health-related behaviors vary across different regions of the country, the findings of this study cannot be generalized to all adults with hypertension in Iran. Therefore, similar studies should be conducted in other provinces, and the results should be compared. One of the strengths of this study is that it was conducted on a reasonably large sample of patients with hypertension. Additionally, a valid and reliable questionnaire was developed and validated during the study to assess the constructs of the Protection Motivation Model.
Demographic characteristics play a significant role in shaping self-care behaviors and protective motivation. These findings highlight the need for tailored health education programs and targeted interventions that consider individual and social determinants of health. By recognizing and addressing these differences, public health initiatives can be more effective in promoting sustainable health behaviors and improving overall community well-being. Future studies should employ longitudinal designs to examine long-term behavioral changes and protective motivation. Additionally, incorporating parameters, such as social support, healthcare accessibility, and cultural factors, can provide a more comprehensive understanding of the determinants of health behaviors. Furthermore, sampling from diverse geographic and economic backgrounds would enhance the generalizability of the results and help identify varied behavioral patterns across different communities.
Conclusion
Education level, gender, employment status, and economic status play a significant role in shaping self-care behaviors and protective motivation.
Acknowledgments: We express our gratitude to everyone who participated in this research. The authors are thankful to Shiraz University of Medical Sciences. The authors acknowledge Ms. Motori for her significant and impactful role in the research process.
Ethical Permissions: Ethics approval and consent to participate in the study mentioned above were obtained from the ethics board committee of Shiraz University of Medical Sciences (IR.SUMS.SCHEANUT.REC.1401.008).
Conflicts of Interests: The authors declared no competing interests.