Introduction

Acute myocardial infarction (AMI) is a major health problem that results from having plaque in one or more coronary arteries. According to the literature, approximately one third of all deaths in the Eastern Mediterranean region result from cardiovascular disease including AMI [1]. Statistics about Jordan are rather more worrying with evidence showing that ischemic heart disease is the number one leading cause of death, and it is responsible for more than half of all deaths [2]. Even though its risk increases as age increases, AMI is considered prevalent among young people in Jordan [3]. Such prevalence of AMI in Jordan has detrimental and overwhelming consequences to the patients and entire healthcare system.

The consequences experienced by AMI patients could occur immediately after the AMI or later in life, and might affect the physiological, psychological, and/or financial well-being of the patients. The physiological consequences include such complications as chest pain due to coronary artery re-occlusion, cardiac dysrhythmias, and left ventricular free wall rupture [4,5,6,7]. In addition, psychological well-being is threatened post-AMI and patients are at increased risk for experiencing depression, behavioral changes, fear, and stress [8, 9]. AMI also has financial consequences secondary to the medical expenses of the disease and possible change in work status [10]. The combination of these complications negatively affects AMI patient’s quality of life. Therefore, it is necessary to establish proper, timely management of AMI.

While appropriate management of AMI remains challenging, there are certain factors that could assist in overcoming this obstacle. Health literacy is one of these key facilitators that plays a crucial role in achieving successful management of AMI during hospitalization and then after discharge [11,12,13]. Health literacy is the degree to which individuals can obtain, understand, process, appraise, and use basic health information and services needed to make appropriate health decisions [14, 15]. It is a multidimensional construct that is considered fundamental to patients’ understanding of discharge planning, and adherence to treatment post-discharge [11, 13]. In addition, health literacy enables individuals to utilize health information to make informed health-related decisions [13,14,15]. However, there are certain limitations and gaps in the literature pertinent to the role of health literacy in AMI management.

One of the main weaknesses in the literature is the limited number of studies that were conducted using comprehensive measurement tools of health literacy [11,12,13, 16]. Such tools might provide rapid evaluation of AMI patients’ level of health literacy. However, they fail to provide thorough measurement of this multifaceted concept that extends beyond individual patients’ ability to understand health-related information and their basic literacy and reading skills [14, 15, 17]. Another identified issue in the literature is the limited number of studies regarding the level of health literacy among Jordanian AMI patients, even though AMI is the leading cause of death in Jordan. More specifically, the strengths and needs of health literacy among Jordanian AMI patients have not been studied yet. Thus, this study was conducted to explore the health literacy strengths and needs of Jordanian AMI patients using cluster analysis.

Exploring the strengths and needs of health literacy allows for thorough understanding of AMI patients’ health needs. According to the Optimizing Health Literacy and Access (Ophelia) process, individuals could be grouped into clusters based on their health literacy profiles and sociodemographic characteristics [14]. In addition, the Ophelia process is a well-developed approach that relies on multidimensional measurement of health literacy [14]. Consequently, utilizing the Ophelia process not only helps the researchers to address the identified gaps in the literature but also facilitates taking future actions to address AMI patients’ needs. In other words, it helps researchers to design and implement evidence-based interventions to meet the actual needs of AMI patients.

Methods

Design and Setting

This study was conducted using a cross-sectional design at three hospitals in Jordan. The current study was conducted between October and December 2023.

Participants

AMI patients were recruited from three hospitals in Jordan using purposive sampling. Because this study was conducted to perform cluster analysis, the authors followed the recommendations of the Ophelia process guidelines to recruit more than 100 AMI patients [14]. The inclusion criteria in this study were: (1) AMI patients admitted for the first time into one of three hospitals, and (2) be at least 18 years old. Patients who have had AMI prior to their current admission were excluded from this study as their health literacy could have been affected by their previous experience and the discharge teaching they received previously. A total of 114 AMI patients agreed to participate in this study and completed the data collection tools.

Data Collection

The authors used a demographics questionnaire and the Health Literacy Questionnaire (HLQ) to collect the data from the participants. The demographics questionnaire was developed by the researchers and included items about the participants’ age, gender, marital status, smoking status, education, family size, and employment.

The HLQ was used to measure health literacy among AMI patients [18]. The HLQ consists of 44 items that are distributed to nine distinct scales. Scales one through five are Likert type with options ranging from one (= “strongly disagree”) to four (= “strongly agree”). The remaining four scales are also Likert type but with different options ranging from one (= “cannot do or always difficult”) to five (= “always easy”). There is no total score for the entire HLQ; instead, the total score for each scale is calculated as the mean. Hence, the total scores of the first five scales range from one to four and from one to five for the remaining four scales. The HLQ is a reliable, valid measure of health literacy that was developed based on a rigorous, validity driven approach [18]. The literature also supports the reliability and validity of the Arabic version of the HLQ [19].

Ethical Considerations

This study was approved by the institutional review board (IRB) committee at the host organization. Approvals were also obtained from the three hospitals where the data were collected. Each participant signed a paper-based informed consent after fully explaining the study to him/her. The participants were assured that their participation was entirely voluntary. The collected data were stored in a locked cabinet at the principal investigator’s office and were accessible only to the members of the research team.

Data Analysis

Data analysis was performed using SPSS (version 27). Descriptive statistics and frequencies were used to describe the participants’ sociodemographic characteristics. Hierarchical cluster analysis using Ward’s method was the main analysis in this study. The decision to use this analysis was based on the recommendations and steps of the Ophelia process where patients are grouped based on the similarities of health literacy patterns and sociodemographic characteristics [14]. SPSS (version 27) was used to run hierarchical cluster analysis. Then, the results were exported to a Microsoft Excel file to determine the optimal number of clusters that best represent the sample of AMI patients. The decision to choose the optimal solution was made based on: (1) careful examination of the agglomeration schedule and dendrogram in the SPSS output file; (2) the variation within the clusters which was determined by examining values of standard deviation (SD); SD of > 0.60 indicated that variation is still high within the cluster unless the size of the cluster was small; and (3) the patterns of the HLQ scales and the sociodemographic variables. The sociodemographic variables used were age, gender, marital status, smoking status, education, family size, and employment status.

The categorical variables were recoded before running the cluster analysis as follows: Gender was coded as Female = 1, Male = 0; Marital status was coded as married = 1, single and married = 0; Smoking status was coded as smoker = 1, non-smoker = 0; Education was coded as 4-year or graduate degree = 1, high school or less and 2 year college = 0; and Employment status was coded as Employed = 1, unemployed/retired = 0.

Results

Participants’ Characteristics

The results showed that the average age of the participants was 49.71 years (SD = 13.71). Fifty-eight participants were males, and most of AMI patients were married (70.2%). Regarding the scores of the HLQ scales, the highest mean for scales one through five was for “Social support for health” scale (mean = 3.08, SD = 0.49); and the “Ability to find good health information” had the highest mean among the scales six through nine (mean = 4.00, SD = 0.73). Table 1 provides more information about the participants’ characteristics.

Table 1 Participants’ characteristics (N = 114)
Full size table

Cluster Analysis Results

The results of cluster analysis revealed that the optimal solution has seven clusters. The clusters are presented in Table 2 and the following is a brief description of each cluster. The color coding used in the table is used to visually highlight the strengths and needs of health literacy among AMI patients. This coding ranges from green (strength) to red (need).

Table 2 Cluster analysis
Full size table

  • Cluster 1: AMI patients in this cluster had the lowest mean scores of the nine HLQ scales. The lowest score of the first five HLQ scales was observed in the “Actively managing my health” scale, and the lowest of the second group of HLQ was seen in the “Understand health information well enough to know what to do” scale. This was the oldest age cluster (mean age = 59.14 years) and had the largest family size. There was only one female (14.29%) AMI patient in this cluster and none of them had 4-year or graduate degree. Most participants in this cluster were smokers (71.43%).

  • Cluster 2: participants in this cluster also had low scores across the nine HLQ scales, but their mean scores were slightly higher than the mean scores in Cluster 1. The lowest HLQ scale mean scores were on the “Having sufficient information to manage my health” and “Actively managing my health” scales: 2.25 and 2.28, respectively. This cluster was the second oldest group with a mean age of 53.60 years and had the second largest family size. Most AMI patients in this cluster were unemployed and 50% of the cluster was female.

  • Cluster 3: there were 6 AMI patients in this cluster who had low scores on the nine HLQ scales. Notably, the lowest mean scores were observed on the “Navigating the healthcare system” and “Understand health information well enough to know what to do” scales. The average of age was 47.33 years, and most participants were females. One third of AMI patients in this cluster were employed, and the percentage of married participants was 50%.

  • Cluster 4: cluster analysis results showed that this cluster had high scores on the first group of HLQ scales compared to their low scores on the second group of scales (i.e., scales 6–9). The “Appraisal of health information” scale exhibited the highest mean score of all HLQ scales, whereas the lowest mean was for the “Navigating the healthcare system” scale (3.92). Regarding the sociodemographic characteristics, the mean of AMI patients’ age in this cluster was 48.97 years and smokers represented 29.03 of the participants.

  • Cluster 5: the participants in this cluster had a health literacy profile that is the opposite of the profile observed in Cluster 4. The scores on the first five HLQ scales were low compared to the high scores on the remaining four scales. The highest mean score was for the “Ability to find good health information” scale (4.60). The mean score of the “Having sufficient information to manage my health” scale was the lowest for participants in this cluster. Two thirds of AMI patients were females and the percentage of patients with 4-year or graduate degree was 55.6.

  • Cluster 6: this was the smallest cluster with only four (3.51%) participants. Similar to the participants in Cluster 5, AMI patients in this cluster also had higher scores on the HLQ scales six through nine. However, their mean scores on the first five HLQ scales were lower than the mean scores observed in Cluster 5. Female participants represented half of AMI patients in this cluster.

  • Cluster 7: The largest cluster in this study involved those AMI patients who had relatively higher scores on the nine HLQ scales compared to other clusters. “Appraisal of health information” and “Ability to find good health information” scales had the highest mean scores of the first and second group of HLQ scales, respectively. The participants in this group were young with a mean age of 48.26 years old. Twenty-six AMI patients in this cluster had a 4-year college or graduate degree. In addition, most AMI patients were females (53.19). The family size of AMI patients in this cluster was relatively small.

Discussion

AMI is common among Jordanians and is considered the top leading cause of death with detrimental complications to the patients and healthcare system. The pertinent literature shows that the prevalence of AMI is expected to increase in the upcoming years. This high prevalence suggests that the complications of AMI are also expected to correspondingly increase in the future. Therefore, it is essential to institute proper management of AMI. Health literacy is considered a key facilitator of appropriately managing AMI. However, research about the health literacy among AMI patients is still limited. This study was conducted to address a unique gap in the existing literature regarding the strengths and needs of health literacy among AMI patients. Cluster analysis was performed to identify the health literacy profiles while considering certain sociodemographic characteristics of AMI patients.

The study identified seven clusters of AMI patients, each characterized by unique health literacy profiles and sociodemographic characteristics. The largest cluster (Cluster 7) consisted of patients who generally had higher health literacy across all nine HLQ scales, suggesting a group well-equipped to manage their health. AMI patients in this cluster demonstrated strong profiles in the scales “Appraisal of health information” and “Ability to find good health information”. This indicates they can identify and use various health information sources [18]. In addition, they assume active roles in exploring health information from updated, reliable sources. Compared to AMI patients in the remaining clusters, those in Cluster 7 are considered advantageous for accessing, understanding, appraising, remembering, and using health information to improve their own health [14].

Contrary to Cluster 7, Clusters 1 and 2 represented patients with the lowest health literacy scores, highlighting significant needs in understanding and managing their health after experiencing AMI. The main challenges for patients in Cluster 1 were prominent in the “Actively managing my health” and “Understand health information well enough to know what to do” scales. In other words, they consider that their own healthcare is the responsibility of others, and they often have trouble understanding written health information and instructions [18]. These findings are consistent with a previous study that showed that active management of health was one of the main challenges experienced by AMI patients [20]. Addressing these challenges could significantly improve the health outcomes of AMI patients. For example, Aaby et al. [11] maintained that understanding health information has a central role in improving physical health of patients who have cardiovascular diseases.

Participants in Cluster 3 also had overall low scores on the nine HLQ scales, and the lowest score was on the “Navigating the healthcare system” scale. According to Osborne and colleagues [18], having low scores on this scale means that those patients have challenges in the ability to advocate on their own behalf and they only use available, obvious health information resources. Limited health literacy, as evident by low scores on the HLQ scales, is associated with unfavorable consequences for AMI patients. The risk for physical and psychological and/or mental complications increases as the level of health literacy decreases [4,5,6,7,8,9, 11]. In addition, AMI patients with limited health literacy are at higher risk for delaying timely seeking of medical care when needed [21]. Limited health literacy increases the likelihood for having inadequate engagement with healthcare providers which puts AMI patients at high risk for having less physical activity, unhealthy eating, and smoking [11].

Cluster 4 revealed that some AMI patients have high scores on the first five HLQ scales and weak scores on scales six to nine. The highest score was observed on the “Appraisal of health information” scale. Clusters 5 and 6 exhibited an opposite pattern of the health literacy profiles where the patients scored high on the last four scales of the HLQ and had low scores on the first five. In Cluster 5, “Having sufficient information to manage my health” had the lowest score indicating that those patients have many knowledge gaps about their health which prevents them from managing their own health [18]. For AMI patients in Cluster 6, the lowest score was on the scale “Feeling understood and supported by healthcare providers”. This means they have challenges in engaging with healthcare providers as a source of information.

This study highlights the influence of sociodemographic factors on health literacy. AMI patients who were current smokers represented more than two thirds of the participants in Cluster 1, whereas less than one third of the participants in Cluster 7 were smokers. In addition, older patients and those with lower educational attainment were more likely to have lower health literacy. On the other hand, those who were younger with 4-year college or graduate degrees demonstrated higher health literacy levels in most clusters. Looking closer at age revealed that the average age of AMI patients in Cluster 7 was about 11 years less than those in Cluster 1. Likewise, more than half of AMI patients in Cluster 7 had 4-year college or graduate degrees compared to no patients in Cluster 1. These findings are consistent with previous studies that showed that younger AMI patients tend to have higher levels of health literacy [16, 22,23,24,25]. In addition, lower education level was reported as the most significant sociodemographic predictor of limited health literacy in AMI patients [24, 26].

Gender differences were also notable in this study, with females generally exhibiting higher health literacy levels in certain clusters. As discussed earlier, Cluster 7 demonstrated the strongest health literacy profiles in this study with female AMI patients representing more than half of the cluster patients. In contrast, less than 15% of the AMI patients in Cluster 1 were females. Such findings are consistent with the existing literature where females tend to have higher levels of health literacy compared to males [16, 27, 28]. These insights are crucial for developing tailored health literacy interventions that consider the specific needs and characteristics of different patient groups.

Implications

The findings of this study and the identification of health literacy profiles have several important implications for healthcare providers, policymakers, and researchers aiming to improve the management and outcomes of AMI patients in Jordan. Healthcare providers should design and implement health literacy interventions that address the specific needs of each cluster. For instance, patients in Clusters 1 and 2, who have the lowest health literacy scores, require intensive support focusing on basic health literacy and self-management skills. Conversely, patients in Cluster 7, who exhibit high health literacy, might benefit more from empowerment strategies to maintain their engagement in health management. Cluster analysis provided important insights regarding the role of sociodemographic characteristics of AMI in health literacy. Male, older AMI patients, and those with lower educational attainment are more likely to have lower health literacy. Targeted efforts should be directed towards these vulnerable groups to mitigate health disparities.

The results also showed that AMI patients in certain clusters, 5 and 6 for example, demonstrated specific needs related to patient-healthcare provider interactions. Improving communication strategies between healthcare providers and patients, such as through clear and simple language and teach-back methods, can help patients feel more understood and supported. Training programs for healthcare providers to enhance their communication skills could significantly impact AMI patients’ health literacy and overall health outcomes. In addition, it was evident that identifying and utilizing reliable resources of health information was one of the challenges among AMI patients. Therefore, it is necessary to consider providing diverse health information resources to help AMI patients overcome this challenge.

Limitations

This study has several limitations that should be considered. The cross-sectional design limits the ability to generalize the findings. Additionally, the sample size, although adequate for cluster analysis, may not fully represent the larger population of AMI patients in Jordan. Future studies should aim to include larger samples and consider longitudinal designs to assess changes in health literacy over time.

Conclusion

The findings of this study highlight the critical role of health literacy in the management of AMI patients in Jordan. By identifying specific strengths and needs, this research provides a foundation for developing targeted health literacy interventions for AMI patients. Enhancing health literacy among AMI patients can improve health outcomes, reduce complications, and enhance their overall quality of life.