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Volume 12, Issue 4 (2024)
Health Educ Health Promot 2024, 12(4): 695-702 |
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Received: 2024/11/1 | Accepted: 2024/12/12 | Published: 2024/12/18
Received: 2024/11/1 | Accepted: 2024/12/12 | Published: 2024/12/18
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Malekzadeh F, Tahmasebi R, Noroozi A. Role of Cardio-Vascular Risk Assessment in Educational Intervention Based on Health Belief Model for Medical Adherence in Patients with Hypertension. Health Educ Health Promot 2024; 12 (4) :695-702
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1- Student Research Committee, Bushehr University of Medical Sciences, Bushehr, Iran
2- Department of Epidemiology and Biostatistics, Faculty of Health, Bushehr University of Medical Sciences, Bushehr, Iran
3- Department of Health Education and Promotion, Faculty of Health, Bushehr University of Medical Sciences, Bushehr, Iran
2- Department of Epidemiology and Biostatistics, Faculty of Health, Bushehr University of Medical Sciences, Bushehr, Iran
3- Department of Health Education and Promotion, Faculty of Health, Bushehr University of Medical Sciences, Bushehr, Iran
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Introduction
Hypertension is a non-communicable disease that affects millions of people worldwide [1]. Approximately 1.28 billion adults aged 30-79 years suffer from hypertension, with two-thirds living in low- and middle-income countries [2, 3]. Alarmingly, around 700 million people with high blood pressure are not receiving any treatment [4]. In Iran, around 6.6 million people individuals aged 25 to 64 have hypertension [5]. This condition is a leading cause of heart attacks and stroke deaths, estimated to cause 9.5 million deaths annually. It is predicted to account for a quarter of all deaths by 2030 [2].
With the increasing prevalence of cardiovascular diseases [6, 7], it is crucial to prevent complications and effectively treat these conditions. This necessitates proactive measures, such as ensuring patients adhere to prescribed medications [8]. However, maintaining medical adherence poses a significant challenge. The World Health Organization recognizes non-compliance as a critical issue that can result in increased mortality [9]. Medical adherence refers to a person's conformity with recommendations provided by healthcare providers [10]. Non-compliance with hypertension treatments can lead to a heightened risk of cardiovascular diseases, heart attacks, and stroke. It can also diminish the quality of life, contributing to depression and escalating treatment costs due to frequent doctor visits and side effects [11].
An essential aspect of medical adherence is patients' understanding of their disease and its treatment, alongside their beliefs about their health conditions [12]. Educating patients plays a crucial role in enhancing awareness and changing these beliefs [13]. Health education experts employ behavior change theories and models to promote awareness, modify health beliefs, and encourage appropriate health behaviors [14]. One such model is the Health Belief Model (HBM), which posits that individuals are more likely to respond positively to health messages when they perceive themselves at risk (perceived sensitivity), and believe the threat is serious (perceived severity). Additionally, they must perceive that behavior change offers significant benefits (perceived benefits), and they can overcome barriers to these changes (perceived barriers). In this context, educational programs are likely to be effective [15, 16].
One of the reasons that people continue to practice unhealthy behaviors is due to inaccurate perceptions of risk and susceptibility called unrealistic optimism. People show a selective focus on health behavior. In selective focus, individuals ignore their own risk-increasing behavior and focus on their own risk-reducing behavior; Instead, individuals ignore others’ risk-decreasing behavior and focus on others’ risk-increasing behavior. Accordingly, individuals perceive others as susceptible to disease, not themselves [17]. Perceived susceptibility and severity, as indicators of perceived threat, are vital factors in health behavior [17, 18], and when individuals believe that they are at a high risk of experiencing adverse health consequences, they are more likely to take preventive measures. One manipulation method of perceived susceptibility for increasing behavior is risk personalized based on a person’s characteristics or behavior [19, 20]. Cardiovascular risk assessment by Framingham risk score considering several factors including age, sex, smoking status, total cholesterol levels, HDL cholesterol levels, and blood pressure estimates an individual's risk of developing cardiovascular disease within the next ten years [21]. Therefore, it seems that risk assessment increases medical adherence in two ways; First, according to the theory of unrealistic optimism, risk assessment can increase individuals' perception of their susceptibility to disease and directly lead to medical adherence, and second, by considering demographic factors such as age, gender, smoking status, etc. (as a set of modifying factors), it can have an indirect effect on treatment adherence.
Various studies based on the HBM show that appropriate interventions rooted in the model can improve medical adherence [22, 23]. Conversely, previous studies have emphasized the importance of risk assessment in planning preventive strategies [24], and enhancing risk perception [18]. However, in none of the interventions based on the HBM, the intervention method on the perceived susceptibility construct was based on personalizing risk (reducing unrealistic optimism), and the role of risk assessment as a factor that may affect other beliefs and medical adherence behavior was not identified. Therefore, the research aims for this study were as follows:
This study aims to determine whether risk assessment combined with Health Belief Model (HBM)-based education is as effective as risk assessment alone in improving knowledge, beliefs about medical adherence, medical adherence, and treatment compatibility.
Materials and Methods
Study design and participants
This semi-experimental research was conducted with hypertensive participants from October 2023 to June 2024 in Bushehr city. The study population consisted of individuals diagnosed with hypertension for over one year, characterized by a systolic blood pressure exceeding 140 mmHg or diastolic blood pressure above 90 mmHg.
The inclusion criteria were as follows: Participants must be receiving treatment with antihypertensive medication, must not adhere regularly to their prescribed treatment (as reported by themselves), must have a ratio of prescribed to consumed medications of less than 80% over a week, and must express a willingness to participate. The exclusion criteria included a history of heart surgery or angioplasty, a previous heart attack, unwillingness to continue participation, failure to read the training booklet after three follow-ups, and incomplete questionnaire responses.
Sample size
Drawing from the findings of the Zamani et al. study [25], and with a significance level (α) of 0.05 and the test’s power of 90%, the minimum sample size required for each group was calculated to be 33, using the below formula:
![src=./files/hehp/images/HTML_Publish/78149/n.png]()
Considering a potential attrition rate of 20%, the final sample size for each group was set at 40 patients, totaling 120 patients in three groups.
Six comprehensive health service centers in Bushehr were selected randomly through a lottery process. Two centers were assigned to each group. In these centers, a list of all people with high blood pressure who met the inclusion criteria was compiled. From this list, participants were randomly selected using EXCEL software based on the number of covered patients and the desired group sizes. Selected participants were then contacted, and the objectives of the study, as well as the inclusion criteria (including medication usage patterns) were confirmed. In total, 40 patients were included in the risk assessment and education (based on the HBM) group, 40 patients in the risk assessment group, and 40 patients in the control group.
Intervention
Before starting the study, the total cholesterol and HDL cholesterol levels of the patients were measured. After preparing the blood test results, the patients completed the questionnaires. For patients in the risk assessment group with education based on the HBM (risk assessment and education group), risk assessment was initially performed using the Framingham model (detailed explanations are provided in the educational content section). The results indicated each patient's probability of developing cardiovascular diseases within the next 10 years compared to similar individuals based on age, as well as the type of risk a person (low risk, moderate risk, or high risk) was interpreted. Subsequently, a booklet based on the HBM’s constructs was provided, and they were asked to read it and follow their doctor's recommendations regarding medication.
One week after receiving the booklet, a follow-up phone call was made to check whether they had read it. In cases where they had not, an additional week was provided to complete the reading. This follow-up process was repeated three times, and those who did not read the booklet by the end of this period were excluded from the study.
In the risk assessment group, the Framingham Model was also used to determine patients' probabilities of developing cardiovascular diseases over the next 10 years, with categorizations as low, moderate, or high risk. Participants were asked to adhere to their doctor's medication recommendations. For both intervention groups (risk assessment and education, as well as the risk assessment group) two text messages were sent each month to monitor their treatment plans.
The control group did not receive any training until the end of the study period. To maintain ethical consideration, their 10-year risk levels were assessed and explained to them at the conclusion of the study. After three months, participants were invited to complete a follow-up questionnaire.
Educational content
Risk assessment is calculated based on several factors, including age, sex, smoking status, total cholesterol levels, HDL cholesterol levels, untreated systolic blood pressure and treated systolic blood pressure. The scoring related to these parameters differs by gender. For instance, in women, scores for age range from -7 for ages 20 to 34 years to 16 for the ages of 75 to 79 years; In men, scores range from -9 to 13 for the same age brackets.
Based on the scores calculated, the risk percentage was determined. Patients with a risk assessment of 10% or less fall into the low-risk group, those with a risk of 10% to 20% were categorized as medium risk, and patients with a score over 20% are considered high risk for cardiovascular diseases. For further information about the scoring system, please refer to the provided reference [26].
The booklet contained information about the prevalence of cardiovascular diseases (perceived sensitivity), the severity of complications and consequences of cardiovascular diseases (perceived severity), the benefits of adhering to treatment (perceived benefits), and the barriers to following through with treatment (perceived barriers). Additionally, the booklet recommended strategies to improve medical adherence, such as saving reminders on mobile phones and using daily and weekly medication reminder boxes, to enhance patients' confidence in their ability to comply with treatment (perceived self-efficacy).
Data collection
In this study, a questionnaire served as the data collection tool, consisting of four parts; Demographic information, knowledge, constructs of the Health Belief Model (HBM), including perceived self-efficacy, barriers, benefits, susceptibility and severity. The final section assessed medical adherence and treatment compatibility to measure participant behavior. Explanations of each part are provided below:
1. Demographic information questionnaire: This questionnaire comprised 15 questions, covering aspects such as age, gender, education level, occupation, marital status, family income, health insurance, hypertension duration, drug use duration, history of chronic diseases and family history of hypertension.
2. Knowledge questionnaire: A portion of the HK-LS standard questionnaire comprising 12 questions, assessed participants’ knowledge about hypertension definitions, lifestyle factors, treatment considerations, drug therapy, dietary practices, and potential complications of hypertension. Each question contained a true or false statement, rated on a three-point scale: True, false and I don't know. Correct answers received a score of 1, while incorrect answers and 'I don't know' received a score of 0, yielding a total score range from 0 to 12. In Erkoc et al.’s study, the reliability of this instrument was reported at 0.82 [27], while this study found the reliability for this section to be 0.80.
3. HBM constructs questionnaire including:
- Self-efficacy: This construct was measured using the standard HIV medical adherence self-efficacy questionnaire. It included 12 questions rated on an 11-point scale from 0 (I can't do it at all) to 10 (I can do it completely). One question, I will continue to take my medication even if the CD4 cells decrease significantly in the next 3 months, was excluded due to its specificity to HIV [28]. Scores ranged from 0 to 100, where higher scores indicate a greater belief in the ability to adhere to treatment. The content validity, construct validity and internal consistency of this tool have been confirmed [28]. In this study, Cronbach's coefficient was estimated at 0.87.
- Perceived barriers: The PMAQ (Patient Medication Adherence Questionnaire), designed by Lingran, included 61 questions, of which 20 were utilized in this study. Responses were measured using a 5-level Likert scale from strongly agree (score 5) to strongly disagree (score 1), with higher scores indicating more perceived barriers [29]. The total score range was from 20 to 100, with a Cronbach's coefficient of 0.79.
- Perceived benefits, sensitivity, and severity: These constructs included five questions about perceived benefits, four about perceived sensitivity, and six about perceived severity, using a tool developed by the researcher based on HBM principles. Each was rated using a 5-point Likert scale. Scores ranged from 0 to 25 for perceived benefits, 0 to 20 for perceived sensitivity, and 0 to 30 for perceived severity. Higher scores reflect a better understanding of each construct, with Cronbach’s alpha coefficients of 0.92, 0.88, and 0.79 respectively for these constructs.
4. Medical adherence questionnaire: To assess medical adherence, the researcher employed Morisky's standard medical adherence questionnaire, which consists of 8 questions [30]. This questionnaire included seven binary (yes/no) questions and one rated on a 5-point Likert scale. Scoring ranged from 0 to 8, with a score of 1 for a yes answer, and a score of 0 for a no. In the 8th question, scoring was based on these classifications: Never (1), rarely (0.75), sometimes (0.5), usually (0.25), and always (0). A lower score indicates higher medical adherence. In Morisky et al.’s study, Cronbach's alpha coefficient was reported at 0.83 [30], while this study’s coefficient was 0.79.
5. Treatment compliance: To evaluate treatment compatibility, the number of drugs prescribed and taken during the current week was assessed, and the ratio of consumed to prescribed drugs was calculated. A compliance rate of 80% or higher was considered adequate.
The prepared questionnaires were reviewed by 10 health education experts. For assessing the experts’ agreement on the questions, the content validity ratio (CVR) was measured and scores of 0.62 or higher indicated good content validity [31]. In this study, CVR for each question was higher than 0.67.
Before data collection, the questionnaire reliability was tested in a sample of 30 hypertensive patients. The Cronbach’s alpha coefficients were 0.82, 0.90, 0.71, 0.82, 0.78, 0.71, and 0.83 for knowledge, perceived self-efficacy, severity, benefits, barriers, susceptibility, and medical adherence, respectively. All the questionnaires were reliable.
Statistical analysis
During the study, one patient from the risk assessment and education group was excluded from the study due to not reading the booklet; During the follow-up, two patients from the risk assessment group and 2 patients from the control group were excluded from the study due to their unwillingness to continue participation. Therefore, out of 106 participants, 35 were included in the risk assessment and education group, 34 in the risk assessment group, and 37 in the control group. Data analysis was conducted using SPSS software, version 23.0. Descriptive statistics, Chi-square test, ANOVA, paired t-tests, and repeated measurement ANOVA were employed to analyze the data.
Ethical considerations
All patients provided written informed consent. To uphold ethical standards in the research, patients could withdraw from the study at any time. The collected data were managed confidentially. The present study was approved by the Institutional Review Board of the Bushehr University of Medical Sciences with ethics number IR.BPUMS.REC.1402.164.
Findings
In this research, an analysis of demographic data indicated that the three groups were homogeneous in terms of demographic information, except for education level. Ages were 50.81±10.17 years in the risk assessment and education group, 51.14±9.41 years in the risk assessment group, and 50.08±10.54 years in the control group (p=0.896; Table 1).
Before the study, most participants in both intervention groups were at a low-risk level for cardiovascular disease (17 of our results suggest that, or 47.2%, in the risk assessment and education group, and 18 patients, or 50%, in the risk assessment group; p=0.965).
Significant differences were observed between the risk assessment and education group and the risk group for perceived sensitivity (p=0.001), perceived severity (p<0.001), perceived barriers (p=0.007), and perceived self-efficacy (p=0.001), indicating that risk assessment with education was more effective in changing beliefs. Both groups showed similar effects for perceived benefits (p=0.405; Table 2). The average change in the risk and education group's knowledge score was significantly higher than in the risk group (p=0.024; Table 2).
There was no statistically significant difference in medical adherence among the three groups at the beginning of the study (p=0.318). However, after the intervention, both the risk and education group and risk group demonstrated increased medical adherence scores, with the risk and education group showing a significantly higher medical adherence rate than the risk group (p=0.001; Table 2). Additionally, at the beginning of the study, patients in all three groups had less than 80% treatment compliance. After the intervention, 24 participants (68.6%) in the risk assessment and education group, 17 participants in the risk assessment group (50%), and one patient (2.7%) in the control group were compatible with the treatment. A significant difference in treatment compliance was noted among the three groups (p<0.001). However, no significant difference was found in compliance between the risk assessment and education group and the risk assessment group (p=0.116).
Table 1. Comparison of demographic factors between risk assessment and education group (n=35), risk assessment group (n=34), and control groups (n=37) among patients with hypertension
![src=./files/hehp/images/HTML_Publish/78149/1.png]()
Table 2. Comparing the mean of HBM’s constructs and medical adherence during the intervention in risk assessment and education (n=35), risk assessment (n=34), and control (n=37) groups among patients with hypertension (p<0.001)
![src=./files/hehp/images/HTML_Publish/78149/2.png]()
Discussion
This research confirmed the effectiveness of educational content based on the HBM and risk assessment of cardiovascular diseases in enhancing medical adherence among patients with high blood pressure. Risk assessment combined with education, not only increased knowledge but also positively modified patients' beliefs regarding all constructs of the HBM, thereby improving medical adherence. In the risk assessment group, both patients' knowledge and beliefs about perceived benefits and self-efficacy increased while the perceived barriers decreased. Consequently, the risk assessment led to a significant enhancement in treatment compliance and medical adherence. Importantly, risk assessment coupled with education proved to be more effective than risk assessment alone in transforming patients' beliefs and knowledge, except regarding their understanding of the benefits of medical adherence.
In terms of med
Hypertension is a non-communicable disease that affects millions of people worldwide [1]. Approximately 1.28 billion adults aged 30-79 years suffer from hypertension, with two-thirds living in low- and middle-income countries [2, 3]. Alarmingly, around 700 million people with high blood pressure are not receiving any treatment [4]. In Iran, around 6.6 million people individuals aged 25 to 64 have hypertension [5]. This condition is a leading cause of heart attacks and stroke deaths, estimated to cause 9.5 million deaths annually. It is predicted to account for a quarter of all deaths by 2030 [2].
With the increasing prevalence of cardiovascular diseases [6, 7], it is crucial to prevent complications and effectively treat these conditions. This necessitates proactive measures, such as ensuring patients adhere to prescribed medications [8]. However, maintaining medical adherence poses a significant challenge. The World Health Organization recognizes non-compliance as a critical issue that can result in increased mortality [9]. Medical adherence refers to a person's conformity with recommendations provided by healthcare providers [10]. Non-compliance with hypertension treatments can lead to a heightened risk of cardiovascular diseases, heart attacks, and stroke. It can also diminish the quality of life, contributing to depression and escalating treatment costs due to frequent doctor visits and side effects [11].
An essential aspect of medical adherence is patients' understanding of their disease and its treatment, alongside their beliefs about their health conditions [12]. Educating patients plays a crucial role in enhancing awareness and changing these beliefs [13]. Health education experts employ behavior change theories and models to promote awareness, modify health beliefs, and encourage appropriate health behaviors [14]. One such model is the Health Belief Model (HBM), which posits that individuals are more likely to respond positively to health messages when they perceive themselves at risk (perceived sensitivity), and believe the threat is serious (perceived severity). Additionally, they must perceive that behavior change offers significant benefits (perceived benefits), and they can overcome barriers to these changes (perceived barriers). In this context, educational programs are likely to be effective [15, 16].
One of the reasons that people continue to practice unhealthy behaviors is due to inaccurate perceptions of risk and susceptibility called unrealistic optimism. People show a selective focus on health behavior. In selective focus, individuals ignore their own risk-increasing behavior and focus on their own risk-reducing behavior; Instead, individuals ignore others’ risk-decreasing behavior and focus on others’ risk-increasing behavior. Accordingly, individuals perceive others as susceptible to disease, not themselves [17]. Perceived susceptibility and severity, as indicators of perceived threat, are vital factors in health behavior [17, 18], and when individuals believe that they are at a high risk of experiencing adverse health consequences, they are more likely to take preventive measures. One manipulation method of perceived susceptibility for increasing behavior is risk personalized based on a person’s characteristics or behavior [19, 20]. Cardiovascular risk assessment by Framingham risk score considering several factors including age, sex, smoking status, total cholesterol levels, HDL cholesterol levels, and blood pressure estimates an individual's risk of developing cardiovascular disease within the next ten years [21]. Therefore, it seems that risk assessment increases medical adherence in two ways; First, according to the theory of unrealistic optimism, risk assessment can increase individuals' perception of their susceptibility to disease and directly lead to medical adherence, and second, by considering demographic factors such as age, gender, smoking status, etc. (as a set of modifying factors), it can have an indirect effect on treatment adherence.
Various studies based on the HBM show that appropriate interventions rooted in the model can improve medical adherence [22, 23]. Conversely, previous studies have emphasized the importance of risk assessment in planning preventive strategies [24], and enhancing risk perception [18]. However, in none of the interventions based on the HBM, the intervention method on the perceived susceptibility construct was based on personalizing risk (reducing unrealistic optimism), and the role of risk assessment as a factor that may affect other beliefs and medical adherence behavior was not identified. Therefore, the research aims for this study were as follows:
This study aims to determine whether risk assessment combined with Health Belief Model (HBM)-based education is as effective as risk assessment alone in improving knowledge, beliefs about medical adherence, medical adherence, and treatment compatibility.
Materials and Methods
Study design and participants
This semi-experimental research was conducted with hypertensive participants from October 2023 to June 2024 in Bushehr city. The study population consisted of individuals diagnosed with hypertension for over one year, characterized by a systolic blood pressure exceeding 140 mmHg or diastolic blood pressure above 90 mmHg.
The inclusion criteria were as follows: Participants must be receiving treatment with antihypertensive medication, must not adhere regularly to their prescribed treatment (as reported by themselves), must have a ratio of prescribed to consumed medications of less than 80% over a week, and must express a willingness to participate. The exclusion criteria included a history of heart surgery or angioplasty, a previous heart attack, unwillingness to continue participation, failure to read the training booklet after three follow-ups, and incomplete questionnaire responses.
Sample size
Drawing from the findings of the Zamani et al. study [25], and with a significance level (α) of 0.05 and the test’s power of 90%, the minimum sample size required for each group was calculated to be 33, using the below formula:
Considering a potential attrition rate of 20%, the final sample size for each group was set at 40 patients, totaling 120 patients in three groups.
Six comprehensive health service centers in Bushehr were selected randomly through a lottery process. Two centers were assigned to each group. In these centers, a list of all people with high blood pressure who met the inclusion criteria was compiled. From this list, participants were randomly selected using EXCEL software based on the number of covered patients and the desired group sizes. Selected participants were then contacted, and the objectives of the study, as well as the inclusion criteria (including medication usage patterns) were confirmed. In total, 40 patients were included in the risk assessment and education (based on the HBM) group, 40 patients in the risk assessment group, and 40 patients in the control group.
Intervention
Before starting the study, the total cholesterol and HDL cholesterol levels of the patients were measured. After preparing the blood test results, the patients completed the questionnaires. For patients in the risk assessment group with education based on the HBM (risk assessment and education group), risk assessment was initially performed using the Framingham model (detailed explanations are provided in the educational content section). The results indicated each patient's probability of developing cardiovascular diseases within the next 10 years compared to similar individuals based on age, as well as the type of risk a person (low risk, moderate risk, or high risk) was interpreted. Subsequently, a booklet based on the HBM’s constructs was provided, and they were asked to read it and follow their doctor's recommendations regarding medication.
One week after receiving the booklet, a follow-up phone call was made to check whether they had read it. In cases where they had not, an additional week was provided to complete the reading. This follow-up process was repeated three times, and those who did not read the booklet by the end of this period were excluded from the study.
In the risk assessment group, the Framingham Model was also used to determine patients' probabilities of developing cardiovascular diseases over the next 10 years, with categorizations as low, moderate, or high risk. Participants were asked to adhere to their doctor's medication recommendations. For both intervention groups (risk assessment and education, as well as the risk assessment group) two text messages were sent each month to monitor their treatment plans.
The control group did not receive any training until the end of the study period. To maintain ethical consideration, their 10-year risk levels were assessed and explained to them at the conclusion of the study. After three months, participants were invited to complete a follow-up questionnaire.
Educational content
Risk assessment is calculated based on several factors, including age, sex, smoking status, total cholesterol levels, HDL cholesterol levels, untreated systolic blood pressure and treated systolic blood pressure. The scoring related to these parameters differs by gender. For instance, in women, scores for age range from -7 for ages 20 to 34 years to 16 for the ages of 75 to 79 years; In men, scores range from -9 to 13 for the same age brackets.
Based on the scores calculated, the risk percentage was determined. Patients with a risk assessment of 10% or less fall into the low-risk group, those with a risk of 10% to 20% were categorized as medium risk, and patients with a score over 20% are considered high risk for cardiovascular diseases. For further information about the scoring system, please refer to the provided reference [26].
The booklet contained information about the prevalence of cardiovascular diseases (perceived sensitivity), the severity of complications and consequences of cardiovascular diseases (perceived severity), the benefits of adhering to treatment (perceived benefits), and the barriers to following through with treatment (perceived barriers). Additionally, the booklet recommended strategies to improve medical adherence, such as saving reminders on mobile phones and using daily and weekly medication reminder boxes, to enhance patients' confidence in their ability to comply with treatment (perceived self-efficacy).
Data collection
In this study, a questionnaire served as the data collection tool, consisting of four parts; Demographic information, knowledge, constructs of the Health Belief Model (HBM), including perceived self-efficacy, barriers, benefits, susceptibility and severity. The final section assessed medical adherence and treatment compatibility to measure participant behavior. Explanations of each part are provided below:
1. Demographic information questionnaire: This questionnaire comprised 15 questions, covering aspects such as age, gender, education level, occupation, marital status, family income, health insurance, hypertension duration, drug use duration, history of chronic diseases and family history of hypertension.
2. Knowledge questionnaire: A portion of the HK-LS standard questionnaire comprising 12 questions, assessed participants’ knowledge about hypertension definitions, lifestyle factors, treatment considerations, drug therapy, dietary practices, and potential complications of hypertension. Each question contained a true or false statement, rated on a three-point scale: True, false and I don't know. Correct answers received a score of 1, while incorrect answers and 'I don't know' received a score of 0, yielding a total score range from 0 to 12. In Erkoc et al.’s study, the reliability of this instrument was reported at 0.82 [27], while this study found the reliability for this section to be 0.80.
3. HBM constructs questionnaire including:
- Self-efficacy: This construct was measured using the standard HIV medical adherence self-efficacy questionnaire. It included 12 questions rated on an 11-point scale from 0 (I can't do it at all) to 10 (I can do it completely). One question, I will continue to take my medication even if the CD4 cells decrease significantly in the next 3 months, was excluded due to its specificity to HIV [28]. Scores ranged from 0 to 100, where higher scores indicate a greater belief in the ability to adhere to treatment. The content validity, construct validity and internal consistency of this tool have been confirmed [28]. In this study, Cronbach's coefficient was estimated at 0.87.
- Perceived barriers: The PMAQ (Patient Medication Adherence Questionnaire), designed by Lingran, included 61 questions, of which 20 were utilized in this study. Responses were measured using a 5-level Likert scale from strongly agree (score 5) to strongly disagree (score 1), with higher scores indicating more perceived barriers [29]. The total score range was from 20 to 100, with a Cronbach's coefficient of 0.79.
- Perceived benefits, sensitivity, and severity: These constructs included five questions about perceived benefits, four about perceived sensitivity, and six about perceived severity, using a tool developed by the researcher based on HBM principles. Each was rated using a 5-point Likert scale. Scores ranged from 0 to 25 for perceived benefits, 0 to 20 for perceived sensitivity, and 0 to 30 for perceived severity. Higher scores reflect a better understanding of each construct, with Cronbach’s alpha coefficients of 0.92, 0.88, and 0.79 respectively for these constructs.
4. Medical adherence questionnaire: To assess medical adherence, the researcher employed Morisky's standard medical adherence questionnaire, which consists of 8 questions [30]. This questionnaire included seven binary (yes/no) questions and one rated on a 5-point Likert scale. Scoring ranged from 0 to 8, with a score of 1 for a yes answer, and a score of 0 for a no. In the 8th question, scoring was based on these classifications: Never (1), rarely (0.75), sometimes (0.5), usually (0.25), and always (0). A lower score indicates higher medical adherence. In Morisky et al.’s study, Cronbach's alpha coefficient was reported at 0.83 [30], while this study’s coefficient was 0.79.
5. Treatment compliance: To evaluate treatment compatibility, the number of drugs prescribed and taken during the current week was assessed, and the ratio of consumed to prescribed drugs was calculated. A compliance rate of 80% or higher was considered adequate.
The prepared questionnaires were reviewed by 10 health education experts. For assessing the experts’ agreement on the questions, the content validity ratio (CVR) was measured and scores of 0.62 or higher indicated good content validity [31]. In this study, CVR for each question was higher than 0.67.
Before data collection, the questionnaire reliability was tested in a sample of 30 hypertensive patients. The Cronbach’s alpha coefficients were 0.82, 0.90, 0.71, 0.82, 0.78, 0.71, and 0.83 for knowledge, perceived self-efficacy, severity, benefits, barriers, susceptibility, and medical adherence, respectively. All the questionnaires were reliable.
Statistical analysis
During the study, one patient from the risk assessment and education group was excluded from the study due to not reading the booklet; During the follow-up, two patients from the risk assessment group and 2 patients from the control group were excluded from the study due to their unwillingness to continue participation. Therefore, out of 106 participants, 35 were included in the risk assessment and education group, 34 in the risk assessment group, and 37 in the control group. Data analysis was conducted using SPSS software, version 23.0. Descriptive statistics, Chi-square test, ANOVA, paired t-tests, and repeated measurement ANOVA were employed to analyze the data.
Ethical considerations
All patients provided written informed consent. To uphold ethical standards in the research, patients could withdraw from the study at any time. The collected data were managed confidentially. The present study was approved by the Institutional Review Board of the Bushehr University of Medical Sciences with ethics number IR.BPUMS.REC.1402.164.
Findings
In this research, an analysis of demographic data indicated that the three groups were homogeneous in terms of demographic information, except for education level. Ages were 50.81±10.17 years in the risk assessment and education group, 51.14±9.41 years in the risk assessment group, and 50.08±10.54 years in the control group (p=0.896; Table 1).
Before the study, most participants in both intervention groups were at a low-risk level for cardiovascular disease (17 of our results suggest that, or 47.2%, in the risk assessment and education group, and 18 patients, or 50%, in the risk assessment group; p=0.965).
Significant differences were observed between the risk assessment and education group and the risk group for perceived sensitivity (p=0.001), perceived severity (p<0.001), perceived barriers (p=0.007), and perceived self-efficacy (p=0.001), indicating that risk assessment with education was more effective in changing beliefs. Both groups showed similar effects for perceived benefits (p=0.405; Table 2). The average change in the risk and education group's knowledge score was significantly higher than in the risk group (p=0.024; Table 2).
There was no statistically significant difference in medical adherence among the three groups at the beginning of the study (p=0.318). However, after the intervention, both the risk and education group and risk group demonstrated increased medical adherence scores, with the risk and education group showing a significantly higher medical adherence rate than the risk group (p=0.001; Table 2). Additionally, at the beginning of the study, patients in all three groups had less than 80% treatment compliance. After the intervention, 24 participants (68.6%) in the risk assessment and education group, 17 participants in the risk assessment group (50%), and one patient (2.7%) in the control group were compatible with the treatment. A significant difference in treatment compliance was noted among the three groups (p<0.001). However, no significant difference was found in compliance between the risk assessment and education group and the risk assessment group (p=0.116).
Table 1. Comparison of demographic factors between risk assessment and education group (n=35), risk assessment group (n=34), and control groups (n=37) among patients with hypertension
Table 2. Comparing the mean of HBM’s constructs and medical adherence during the intervention in risk assessment and education (n=35), risk assessment (n=34), and control (n=37) groups among patients with hypertension (p<0.001)
Discussion
This research confirmed the effectiveness of educational content based on the HBM and risk assessment of cardiovascular diseases in enhancing medical adherence among patients with high blood pressure. Risk assessment combined with education, not only increased knowledge but also positively modified patients' beliefs regarding all constructs of the HBM, thereby improving medical adherence. In the risk assessment group, both patients' knowledge and beliefs about perceived benefits and self-efficacy increased while the perceived barriers decreased. Consequently, the risk assessment led to a significant enhancement in treatment compliance and medical adherence. Importantly, risk assessment coupled with education proved to be more effective than risk assessment alone in transforming patients' beliefs and knowledge, except regarding their understanding of the benefits of medical adherence.
In terms of med