An-Najah National University Faculty of Graduate Studies The Impact of Medications on Daily Lives of Patients with Cardiovascular Diseases: A Cross Sectional Study By Rasha Yousef Tirhi Supervisors Dr. Samah Al-Jabi Co-Supervisor Dr. Sa'ed Zyoud This Thesis is Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Clinical Pharmacy, Faculty of Graduate Studies, An-Najah National University, Nablus-Palestine. 0202 ii The Impact of Medications on Daily Lives of Patients with Cardiovascular Diseases: A Cross Sectional Study By Rasha Yousef Tirhi This thesis was defended Successfully on 1/8/2021 and approved by: Defense Committee Members Signature 1. Dr. Samah W. Al-Jabi / Supervisor 2. Dr. Sa'ed Zyoud / Co-Supervisor 3. Dr. Maher Khdour / External Examiner 4. Dr. Rowa Al-Ramahi / Internal Examiner iii Dedication This work is dedicated to the soul of my father, who would have been thrilled to see this work come to life, whose love and care inspire me in every single step in my life; I will always do my best just to make you proud. (May GOD rest your soul in peace) It is dedicated to my mother for her endless love, support, encouragement, who taught me perseverance in setting my objectives and achieving them and gave me the strength to face all challenges. And it is dedicated to my beloved sisters and brothers who shared their words of advice and encouragement to complete this thesis. iv Acknowledgment At the very beginning, I would like to express my deepest gratitude to Almighty Allah, without whom nothing is possible, for giving me the strength, endurance, skills, power of the mind, and the willpower to complete my thesis and prepare it within the scheduled time. I would like to express my deepest thanks, gratitude, and respect to my supervisors, Dr. Samah Al- Jabi and Dr. Sa’ed Zyoud, for their helpful guidance, insightful comments, considerable encouragement, and patience to complete this thesis. Without their valuable opinions and ideas, this work would not have been accomplished I wish to express my special thanks to all my lecturers at An-Najah National University for their precious assistance, scholarly knowledge, and enthusiasm. I would like to express my indebtedness to my family and my friends who have given me constant support and love during the completion of the thesis v vi Table of Contents No. Content Page Dedication iii Acknowledgment iv Declaration v Table of Contents vi List of Tables viii List of Appendices ix List of Symbols and Abbreviations x Abstract xi Chapter One: Introduction 1 1.1 Background 1 1.1.1 Cardiovascular Disease and its impact on patient’s life 4 1.1.2 Pathophysiology of the Cardiovascular Disease 5 1.1.3 Diagnosis of Cardiovascular Disease 6 1.1.4 Common test used in diagnosis CVD 7 1.1.5 Cardiovascular Disease treatment 8 1.2 Literature Review 9 1.3 Statement of the problem and rationale of the study 21 1.4 The objectives of the study 22 1.4.1 General Objective 22 1.4.2 Specific Objectives 22 1.5 Significance of the study 23 Chapter Two: Methodology 24 2.1 Study design and settings 24 2.2 Sample size 24 2.3 Data collection 25 2.3.1 Tools used in data collection 25 2.4 Inclusion and exclusion criteria 28 2.4.1 Inclusion criteria 28 2.4.2 Exclusion criteria 28 2.5 Statistical data analysis 28 2.6 Ethical approval 29 Chapter Three: Results 30 3.1 Sociodemographic characteristics of the study patients 30 3.2 Cardiovascular diseases and other comorbidities among the patients of the study 31 3.3 Chronic medication used by the study sample 32 3.4 Medications-related characteristics 34 3.5 Assessment of Medication-Related Burden Using LMQ-3 35 vii Chapter Four: Discussion 55 4.1 Discussion 55 4.2 Strengths and limitations 63 Chapter Five: Conclusion 64 5.1 Conclusion 64 5.2 Recommendations 65 References 66 Appendices 81 ب الملخص viii List of Tables No. Tittle Page 3.1 Socio-demographic characteristics of the study patients (N=380) 30 3.2 Chronic diseases among the study sample 31 3.3 The most commonly prescribed medications 32 3.4 Medications-related characteristics 34 3.5 Patients response to Living with Medicines Questionnaire (LMQ‐3) n=380 38 3.6 Response to LMQ arranged according to the eight domains 43 3.7 Differences in proportions of patients agreeing with 41 LMQ items 49 3.8 Effect of demographic and medication-related characteristics of respondents on individual domains of Living with medicine Questionnaire version-3 LMQ-3 (n=380) 52 3.9 Perceived medication-related burden measured using Living with Medicines Questionnaire version-3 (LMQ-3) and VAS (n=380) 54 ix List of Appendices No. Tittle Page 1 Data Collection Form 81 2 Scoring of LMQ-3 items and subscales/domains 86 3 Institutional Review Board Approval Letter 87 4 Faculty of Graduate Study Approval 88 x List of Symbols and Abbreviations ACE-I Angiotensin Converting Enzyme Inhibitors BNP Brain Natriuretic Peptide CCB Calcium Channel Blockers CRP C-Reactive Protein CSE Cardiac Self Efficacy CVD Cardiovascular Disease DRP Drug Related Problems ECG Electrocardiogram HF Heart Failure ISPOR International Society for Pharmacoeconomics and Outcomes Research LMQ Living with Medicine Questionnaire MRB Medication Related Burden NCD Non Communicable Diseases PRN As Needed QOL Quality Of Life SPSS Statistical Package for Social Sciences VAS Visual Analogue Scale xi The Impact of Medications on Daily Lives of Patients with Cardiovascular Diseases: A Cross Sectional Study By Rasha Yousef Tirhi Supervisor Dr. Samah Al-Jabi Co-Supervisor Dr. Sa'ed Zyoud Abstract Background: Multiple long-term cardiovascular medication use affects different aspects of patients’ daily lives and quality of life, which creates a burden for patients. The burden of medications critically affects their medication beliefs, behaviours, and disease outcomes. Evaluating medicines’ burden from the patients’ perspectives is a crucial endeavour to identify barriers that may hinder achieving optimal health outcomes. The present study aimed to exploit the Arabic version of Living with Medicines Questionnaire-3 (LMQ-3) to quantify the medicine burden among cardiovascular patients, assess the effect of chronic cardiovascular medication use on different aspects of patients’ daily lives, and to examine the relationship between demographic and clinical characteristics of the patients’ daily life score. Methods: The study was a cross-sectional observational study; patients were included from community pharmacies who used cardiovascular medication in Jerusalem, Palestine, from January to October 2019. The data collection form consisted of demographic and clinical information about the patients, Living with Medicines Questionnaire version-3 (LMQ-3), which measures the impact of medicine use on patients’ daily lives and a xii visual analogue scale (VAS), allowed the patient to express his or her overall perceived medication burden which is a scale from 1–10 that measures global burden, with anchors indicating no burden at all to extremely burdensome. Results: A total of 380 patients were included in this study. Their mean age (±SD) was 58±12.2 years, the majority of patients have health insurance (292, (76.8%)), 227 (59.7%) were living in urban areas, and 259 (68.2%) patients had hypertension. According to our present research, the LMQ domain score revealed a significant burden among the female gender, living in urban areas in comparison to rural or camps, without insurance, with one or two diseases, using 1–4 medicines, using solid oral dose with other non-oral formulations for some domains in which level of significance was determined at P < 0.05. The vast majority (96.3%) of respondents self-reported suffering from a minimum (39.2%) to moderate (57.1%) degree of burden. The median (IQR) LMQ overall score was 108 (19.8), which is considered a moderate burden. Furthermore, the present research indicated that the evaluation mean ± SD of the global burden by the VAS score was 5.2 ± 2.3, which indicates medium burden. Conclusion: Healthcare providers should acknowledge the impact of multiple long-term medicines on patients’ daily lives and make an effort to diminish patients’ medication-related burden by using LMQ- 3 personally to provide individual tailored therapeutic care plans to achieve the best possible benefits for patients. Additionally, expanding pharmacists’ roles, xiii especially clinical pharmacists, can assist doctors in estimating a patient’s medication related burden through the implementation of pharmaceutical care. Keywords: cardiovascular medication; medication-related burden; medication adherence; patient experience; Living with Medicine Questionnaire; daily lives. 1 Chapter One Introduction 1.1 Background Multiple medication prescriptions for patients with chronic disease usually impact their cognition and function and raise the possibility of drug interactions and adverse events (Runganga et al., 2014). Chronic diseases are the most significant cause of death globally, with the majority of deaths being from cardiovascular disease (CVD) (mainly from ischaemic heart disease and stroke), followed by cancer (Yach et al., 2004). In 2015 an estimated 17.9 million people died from CVD, 31% of all global death (Fuller et al., 2018). Cardiovascular diseases (CVDs) are disorders of the heart and blood vessels, consisting of heart failure, stroke, ischaemic heart disease, and other cardiac and vascular disorders. Patients’ quality of life is significantly reduced by these diseases, and noticed an increasing in the probability of disability. More time, resources and energy are spent by patients to stay well (Hajar, 2016, Mensah et al., 2019, Eton et al., 2012). Burden experienced by patients with these chronic health diseases is not only related to the illness itself, but also linked to the regimens of the healthcare that are ever-expanding, comprising keeping medical appointments, monitoring health, diet, medication-taking and exercise. A spiral of negative consequences can be triggered by excessive healthcare burden. Non-compliance with recommended medications and care will 2 result in more hospitalizations, more intensive therapy and a higher mortality rate (Eton et al., 2012). These chronic conditions usually require complex self-management of both medical interventions and disease symptoms, which involve essential demands on patients’ time, effort and finances (Katusiime et al., 2016). Multiple medications are prescribed to treat and prevent CVD. Usually, these treatment regimens are complex and used until the end of patients’ lives, which creates a burden for patients (Gallacher et al., 2011). Polypharmacy use enhances the risk of drug-related problems (DRPs) – for instance, drug interaction, hospitalization, non-adherence and adverse drug events (Salazar et al., 2007). Medication-related burden is classified into five dimensions: burden related to adverse effects; the healthcare system; medication routines; social aspects; and medication characteristics (Mohammed et al., 2016). Patients with a large number of medication-related burdens may find an increase in the negative impact on their quality of life and daily lives (Eton et al., 2012), with a fundamental problem with prescribed regimen adherence (Demain et al., 2015). Several studies measure the knowledge of and adherence to medication in Palestinian society, but to the best of my knowledge there has been no research on the burden of using the drugs, whereby the treatment burden results in poor clinical outcome, increased mortality and morbidity, more hospitalization, fractures, demand for 3 nursing home care and an increase in healthcare costs (Demain et al., 2015). To optimize medicine utilization in these patients, there is a considerable requirement to realize their difficulties, attitudes, experiences and concerns (Katusiime et al., 2018). However, most published research concentrates on the biomedical perspective, ignoring the patients’ viewpoint (Krska et al., 2014). Furthermore, patient experience is a crucial element to the measuring of the quality of healthcare and also to improve healthcare safety, and patient outcome (Institute of Medicine, 2001), especially because some patients with polypharmacy prefer not to take medicines or to stop some or all of their medications (Krska et al., 2017b). Medicine-related burden is a relatively new concept (Mohammed et al., 2016); this makes the need not only to understand that burden but also to measure it (Katusiime et al., 2016), especially in patients with CVDs on whom limited research has been performed (van der Laan et al., 2018). One of the recent questionnaires developed for measuring overall medicine burden is the Living with Medicines Questionnaire (LMQ) (Krska et al., 2014, Krska et al., 2017b), which investigates numerous parts of the burden of medication utilization from the patient’s perspective. In addition, the value of this questionnaire comes from assessing several issues, such as adherence to the treatment plan, patient relationship with healthcare professionals and also adverse drug reaction (Krska et al., 2014). This will assist in determining patients’ views of drug therapy and its effects on their 4 lives (Zidan et al., 2016). This questionnaire differs from other instruments that are used to measure patient experience with medicine use because it covers more domains. This questionnaire deals with eight interrelated dimensions of medicine use experience: perception about medication effectiveness; concerns about medicine utilization; patient–providers relationship and communication concerning medicine; practical complexity; intervention with their daily life; autonomy/control over medicine ,side effects and cost burden. (Krska et al., 2017b). 1.1.1 Cardiovascular disease and its impact on the patient’s life CVDs are a group of heart and blood vessel disorders, including coronary heart disease, peripheral arterial disease, rheumatic heart, and cerebrovascular disease (Hajar, 2016). It is a major contributor to disability (World Health Organization, 2004). CVDs are the number one cause of death – the number of deaths from CVD is 17.9 million people each year – and CVD ranks top of ten killer non-communicable diseases (NCDs) (Collier and Kienzler, 2018). CVDs are one of the leading causes of morbidity and mortality in the occupied Palestinian territory. In Palestine, CVD is the leading cause of death. (Abu-Rmeileh et al., 2012). Various emotional and physical symptoms are usually experienced by sufferer with a history of CVD, such as sleep difficulties, fatigue and edema limiting their social and physical activity, resulting in poor life quality (Komalasari et al., 2019). Many patients experienced functional and productivity loss as a result of CVD; additionally, a lack of insurance and reduced income were 5 linked to this loss (Calcagno et al., 2016). The effect of the consequence of CVD and the therapy itself can be positive or negative; symptoms may decrease, with the enhancement of function and sense of well-being; or the treatment may be deleterious, causing new symptoms, side effects, or a reduced sense of well-being and ability to function (Wenger et al., 1984). Many factors, such as good medication adherence, daily physical activity, and controlling risk factors, have a positive impact on the quality of life of patients with CVD (Ludt et al., 2011). 1.1.2 Pathophysiology of the cardiovascular disease The major cause of CVD is atherosclerosis; multiple risk factors contribute to forming atherosclerosis blocks, such as dyslipidaemia, hypertension, cigarette smoking, immunological phenomena, inflammation, and endothelial dysfunction. These risk factors contribute to multiple processes, including oxidation and inflammation in the artery wall, which contribute to the development of fatty-fibrous lesions over time. Heart attacks and strokes may be caused by inflammation, lesion rupture or physical trauma (Scott, 2004). C-reactive protein (CRP), an inflammatory marker, is used to monitor disease progression, inflammatory marker CD40 and the cardiac myofilament protein troponin, the early warning signs of heart attack. Cardiovascular hypertrophy occurs as a consequence of neuro–humoral and biomechanical processes seen in hypertension, which predisposes to heart failure via apoptosis. In addition, coronary artery disease is a common cause of heart failure (Scott, 2004, Davies et al., 1988). 6 The hallmark of ageing hearts is increases production of pro-inflammatory markers, including high-levels of IL-6, TNF, and CRP (Curtis et al., 2018). CVD prevalence is linked to increased overall myocardial degeneration and deterioration, apoptosis, inflammation and oxidative distress (Davies et al., 1988). Heart failure, arterial fibrillation, and other CVD are common as a result of functional and electrical defects in the heart (Steenman and Lande, 2017). Cardiac damage results in permanent loss of cells because the heart cannot regenerate (Scott, 2004). 1.1.3 Diagnosis of cardiovascular disease Patients with CVD suffer from several symptoms, which include trouble breathing, chest pain and tightness, discomfort, especially when they are highly active, pain, numbness, and weakness in arms or legs if blood vessels there are narrowed (Jin, 2018). The methods that doctors use in diagnosing cardiovascular disease usually depend on the heart disease that the patient has. General methods for diagnosis of CVD depend on a number of laboratory tests and imaging studies, the patient’s medical and family history, physical examination, risk factors, and the integration of these results with the tests are the most crucial elements of diagnosis. 7 1.1.4 Common test used in diagnosis CVD  Blood test: TroponinT-Test which measure the level of cardiac specific troponin, the marker of choice to detect heart attack; other biomarkers that also appear include fibrinogen and PAI-1, elevated asymmetric dimethyl arginine, high level of homocysteine, and elevated brain natriuretic peptide (BNP).  Electrocardiogram (ECG): records the electrical signals of the heart (its rhythm and how fast the heart is beating), the strength, and timing of the electrical signal, which identifies conduction disturbances, that assists in the diagnosis of heart disease, including myocardial ischaemia, arrhythmias, and angina. Infarction or ischaemia is indicated by ST- segment elevation or depression. Chamber hypertrophy is characterized by large voltage QRS complexes, downward-sloping ST segments, and T-wave inversion. Exercise stress testing is a proven diagnostic test for symptomatic coronary artery disease that is also used to evaluate individuals with established cardiac illness. (Garner et al., 2017). Other tests that also contribute to diagnosis are cardiac computerized tomography, echocardiography, coronary angiography chest X-ray, myocardial perfusion scan (MPS), cardiac magnetic resonance imaging (Wedro and Davis, 2020). 8 1.1.5 Cardiovascular disease treatment Maximizing patients’ quality and quantity of life and preventing more deterioration in their status are the main goals of treating cardiovascular disease. Generally, once the plaque has begun, limiting its progression is possible by using appropriate medicine and preserving a healthy lifestyle with regular exercise and healthy food (Palmiero et al., 2019). The major drugs that are used in treating and preventing CVD are:  Aspirin, which makes platelets less sticky with its activity as an antiplatelet, which minimizes the risk of heart attack, the present of other risk factors for heart disease, determine its routine use.  Beta-blocker: helps in inhibiting the activity of adrenaline on the heart, decreases the heart muscles’ oxygen demand, helps the heart beat more efficiently and slows the heart rate.  Calcium channel blockers (CCBs) assist the myocardium contraction and pumping to be more effective.  Nitrates: dilate arteries so that they increase blood flow to the cardiac muscle (Wedro and Davis, 2020). 9 1.2 Literature Review In 2018, a study was conducted by van der Laan et al. (2018) to measure the impact of cardiovascular medication use on patients’ daily lives by using LMQ; 196 patients from the Netherlands with long-term medicine use participated. A serious proportion of these patients experienced MRB in their everyday life, especially due to the intervention of medicines with daily and social live and lack of communication with healthcare professionals. In 2015, Shareef et al. (2015) conducted a study among Indian patients to identify drug-related issues in cardiovascular disease patients. A total of 112 patient cases were examined in this report. Drug interaction was the most common drug-related issue (49.05%), followed by adverse drug reactions (18.86%) and failure to receive the drug (9.43% ). This research demonstrated the value of a pharmacist in a multidisciplinary team who reviews drug therapy on a regular basis so as to identify and address drug- related problems, achieve better therapeutic outcomes and improve patient care. Furthermore, in 2011, Gallacher et al. (2011) performed a secondary analysis of qualitative interview data for 47 patients with chronic HF in Britain to understand the treatment burden in these patients. They discovered that the healthcare burden in those patients included the large number of medicines and appointments, obstacles to obtaining services, 10 inconsistent and poorly structured care, a lack of continuity, and insufficient coordination between health professionals. In 2013, Janet Krska et al. conducted a study on patients taking long-term medicines to measure the effect on their day-to-day living, especially the influence on the quality of life (QOL). The majority of the patients’ had established routines for using multiple medications. Some required great effort; some had unpleasant experiences of discussing concerns with their doctor, and the social activities of patients were restricted. On the other hand, in a cross-sectional study conducted by Sav et al. (2016) on 581 participants with various chronic diseases, patients were asked about treatment burden by concentrating on five dimensions: social life; medication; financial burden; time and administrative; and lifestyle change. In this study, the risk of treatment burden was observed more in young patients with chronic disease, metabolic disorders (diabetes), endocrine disease and those with unpaid careers. In 2017, a study that was undertaken by Singh (2017) in India explained that half of cardiovascular patients did not use their medicine as directed. Several factors contributed to their non-adherence. Some were related to patients, such as a low ability to read and write and a shortage of participation in the process of treatment decision-making. In addition, those factors related to the physicians included complicated regimen and lack of communication with patients, and those related to the healthcare systems included hard access to care. 11 In 2015 a research that was performed by Bansilal et al. (2015) regarding the prevention of cardiovascular disease showed that compliance to cardiovascular treatment was very low in patients with chronic disease, particularly with patients who used many pharmacological agents, which resulted in direct and indirect healthcare costs. Furthermore, in 2013, Reeve et al. performed a study among Australian older patients taking ten medicines. The study found that 60% of patients reported using a large number of medications, discontinuation willingly of one or more of their medicine was seen in 92% of patients, and cessation of medication use was largely accepted by older adults. In 2016 Zidan et al. (2016) performed a translation and cultural adaptation of the LMQ into the Arabic language, by obtaining permission from the original developers (Krska et al., 2014), which was done by using the guidelines of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) for the translation and cultural adaptation of patient-reported outcome measures. This translation generates a culturally suitable translation of the LMQ, identical to the original English tool, to be used in Arabic countries in clinical practice and research. In 2008 Wu et al. (2008) performed a study to explore medicine adherence among patients with HF and which factors influence them, through an in- depth interview for seven women and nine men with HF. They found that education and explanation from healthcare providers help patients 12 comprehend their disease, symptoms, and how medicines effectively decrease their symptoms and greatly benefit adherence. Another new study that was performed by Van Der Laan et al., (2018), who identified the main factors that were linked to non-adherence to cardiovascular medications, the study collected information on 255 patients from 23 community pharmacies regarding patient medications, demographics, illness characteristics, quality of life, knowledge, behaviour toward medicines, and satisfaction with knowledge. This study explains that forgetting, having insufficient cognizance on what to do if the dose is missed, having a hesitating attitude towards medications, are the primary factors associated with patients’ non-adherence. Many intervention strategies must be used to improve cardiovascular medication adherence by using tools to prevent forgetting; also, patients’ beliefs about medicines should be addressed. In 2019 Bahall (2019) performed a study using a questionnaire to gather information about medical background, socio-demographic traits, social support, and reasons for medication non-adherence in the cardiac clinic, to identify reasons for medication non-adherence and its related causes. In this study, carelessness, ceasing medication use when feeling well, forgetfulness, and ceasing medications when feeling worse were the main causes for non-adherence, followed by cost and the unpleasant effects of medication. According to this study, there is a strong need for productive communication between patients and healthcare professionals with regard 13 to patients’ concerns and potential adverse drug effects in order to promote greater adherence. In 2006, a study conducted by Kulkurini et al. (2006) assessed the adherence to evidence-based cardiovascular medicine prescribed when discharged from hospital by studying 1326 patients who suffered from coronary artery disease and their adherence to B-blockers, statins, and angiotensin-converting enzyme (ACE) inhibitors. Patients who were using these medications from one year were considered adherent; only 54% of patients were adherent to the medication. Discontinuation of medication was seen in elderly, women, unmarried, less educated, and patients with a larger number of prescribed medicines. In contrast, better adherence was seen with strong mental health, elevated educational level, married marital status, and non-user of antidepressant. Neither physical function nor insurance coverage correlated with adherence. There is a massive need for healthcare professionals’ awareness of patients’ factors that influence adherence. Furthermore, in 2014 Caldeira et al. (2014) performed a random meta- analysis study on patients with chronic cardiovascular disease by comparing variant dosing regimens (once-daily use versus twice or more daily administration) and evaluated adherence to treatment. They found that a dosing regimen with once-daily use was linked with a 56% reduction in the risk of non-adherence to the medicine. So taking medications once per day decreases the possibility of non-adherence to 50%. 14 In 2006, Ho et al. (2006) identified factors linked to medication therapy cessation and the impact of medication cessation after myocardial infarction. The study of 1521 patients found that discontinuation of their medication early after discharge from the hospital was associated with higher mortality risk than those who continued taking medicine. Patients who discontinued all medicines at one month had lower one-year survival than those who continued. In 2010, Dragomir et al. estimated the impact of low adherence to antihypertensive drugs on cardiovascular outcomes and the cost of hospitalization in a cohort study of 59,647 patients with essential hypertension. Poor adherence to antihypertensive drugs was related significantly to a higher risk of vascular events, hospitalization and higher cost of medical treatments, according to the findings, by increasing the level of adherence; we can provide a better health status and net financial gain. In 2014, Al Ameri et al. (2014) performed a study for 237 elderly patients in a tertiary hospital in the United Arab Emirates to see whether there was a correlation between polypharmacy and factors such as age, gender, level of education, number of medications, and comorbidities. The results revealed a clear relationship between these factors and polypharmacy, in which co-morbidities and drug interaction increase with increasing medications taken by patients. Male subjects were more frequently exposed to polypharmacy and had more significant co-morbidities than women. 15 Consequently, educational programmes targeting healthcare providers and patients must be developed in the hospital settings. Another study was conducted by Demain et al. (2015), who identified treatment disruptions experienced by patients with chronic disease and treatment and tried to put strategies in place to minimize these treatment- generated disruptions. Data were collected from 294 patients. Primary results show that treatment generates adverse physical and emotional side effects; patients try to reduce these disruptions by non-adherence or additional adaptive work, which has a huge impact on physical outcome and care relationships. Clinicians must communicate with patients by having an honest and constructive discussion about therapy disruptions and the ability to follow prescribed regimens by putting plans that result in optimizing outcomes and minimizing disruptions. In 2010 van Mourik et al. performed a global study to check the availability, price and affordability of cardiovascular medications in some developing countries, using the standardized data which were collected according to the WHO/Health Action International methodology. Data were analysed from 36 countries, which include the following medicines: atenolol, captopril, hydrochlorothiazide, nifedipine and losartan. The outcome measures were percentage availability, price ratios to the international reference price. Results show that cardiovascular medicines’ overall availability was poor; patients’ prices were higher than international reference prices. Also, chronic treatment with antihypertensive medicine 16 costs more than payments in many countries; also, when single therapy is inadequate, therapy becomes unaffordable. This confirms the need for concerted attention and financing to make medicines for chronic disease accessible, so various policy options should be recommended to reach this goal. A retrospective cohort observation of patients made by Sokol et al. (Sokol et al., 2005) assessed the impact of medication adherence on healthcare utilization and cost for four chronic diseases: diabetes mellitus; hypercholesterolaemia; essential hypertension; and congestive cardiac failure. Results explained that for hypercholesterolaemia and diabetes, since high drug adherence was linked to lower disease-related healthcare costs, higher treatment costs were more than offset by lower medical costs, resulting in a significant reduction in overall healthcare costs. For hypertension, dyslipidaemia and diabetes, cost offsets were noticed for all- cause medical costs at high medication adherence degrees. An increase in medication adherence linked with lower hospitalization rates was observed in four diseases, so increasing drug utilization provides a net financial return driven via a higher rate of adherence to treatment with guidelines- based therapy. A retrospective database study performed by Lynch et al. (2009) determined the adherence to antihypertensive medication and its association with decreased medical and drug costs, work absence days, and medical service utilization among employees with hypertension. Results 17 proved that adherence to antihypertensive medication was correlated with improvements in short-term utilization measures, healthcare costs, emergency service utilization, and work absence days among high prior- cost employees, but not among low prior-cost employees. In 1995, a cross-sectional study was performed by Lin et al. (2007) to measure the medication adherence rate and investigate its associated factor among patients in Tainan who were diagnosed with hypertension. The results showed that drug adherence among elderly using antihypertensive medication was 57.6%, and that many factors aided in better adherence, such as decreased daily dose frequency, trust in the efficacy of antihypertensive medication, health examination, low incidence of adverse drug effects, and more explanation from physicians about adverse drug reactions. To improve adherence, doctors should prescribe long-acting medications, confirm the medications’ efficacy and reduce the probability of adverse effect occurrence. A recent cross-sectional study was conducted by Krska et al., (2019) in south-east England, which measured the complexity of the regimen and specified how burden is influenced. In a total of 492 patients who completed the Living with Medicines Questionnaire (LMQ), complexity was correlated firmly with the number of medications, the number of therapeutic classes and the number of formulations. The highest complexity scores were observed for patients using medications for eyes, respiratory disease, and skin. By increasing the frequency of dosing, the 18 number of medicines, number of different therapeutics groups all increased the medication burden. Sixty per cent of patients used cardiovascular medicine, but a high burden is linked more to neurological, psychiatric and gastrointestinal conditions. Another recent study performed by Tordoff et al. (2019b), using the Living with Medicines Questionnaire (LMQ), identified any subpopulations with a huge medicine burden among 472 New Zealand adults from a community pharmacies’ using more than one medicine for at least three months. From the LMQ scores it appears that 30.5% had a high burden. Elevated scores were connected with unemployed. Patients use at least five medicines, using medicines at least three times a day, aged 18–29 years;. Therefore these patients should be the objective of interventions aimed at reducing drug burden. Zolnierek and DiMatteo, (2009) did a meta-analysis that estimated the relationship between doctor communication and patient adherence, which proves that physician communication is positively associated with patients’ adherence, so training doctors in communication skills will generate essential improvements in patients’ medication adherence. Communication in healthcare centres is strongly correlated with better patient adherence. A survey was performed by Roshan et al. (2010) on 313 CVD patients to inspect whether different types of prognostic information connected with the prescription of a specific drug by doctors can impact patients to use the medicine as recommended and to check whether patients need this type of 19 information. The highest self-estimated probability of not taking the medication was seen when the cardiologist prescribed the drug without explaining the absolute and risk-lowering figure. Most patients (85%) wanted to get information about the cardiovascular risk reduction linked with cardiovascular medication. Van der Wal et al. (2010) performed a qualitative descriptive study to identify reasons for compliance, hindrances to compliance, and the intervention that may help heart failure patients. Primary reasons that improve adherence were fear of hospitalization and the annoying symptoms of heart failure, while negative aspects and misunderstandings of a regimen were the hindrances for compliance. So healthcare professionals need to confirm the advantages of compliance, encourage patients to adhere, and concentrate on individual hindrance to compliance, knowledge shortage, and misunderstanding regarding the regimen, and give more accurate information about the need for a healthy diet. A randomized controlled trial conducted by Murray et al. (2007) determined whether pharmacist intervention leads to efficient drug adherence and a positive health effect for heart failure patients. The authors showed that pharmacist intervention for outpatients with HF disease can significantly enhance adherence to cardiovascular drugs, decreasing healthcare utilization and costs. Constant pharmacist interventions are the cornerstone because it appears that the effect dissipates when the intervention ceases. 20 A retrospective longitudinal cohort study conducted by Fitzgerald et al. (2011) assessed the relationship between adherence (with angiotensin II receptor blockers (ARBs) angiotensin-converting enzyme inhibitors (ACEIs), aldosterone antagonists, beta-blockers (B-blockers) and primary results of all-cause mortality and cardiovascular hospitalizations for 557 patients with HF for a period of follow-up of 1.1 years. This study clarified a strong relationship between non-adherence and increased risk of all-cause hospitalization and mortality for heart failure populations, so systems of care are required to optimize adherence for heart failure patients. Another study in Palestine conducted by Jamous et al., (2014) on 187 patients investigated medicine adherence and beliefs about medications and whether beliefs affect medication adherence. This study was carried out in Nablus, Palestine at a primary healthcare clinic of the Palestinian Medical Military Services, using the beliefs about medicines questionnaire to estimate beliefs and the Morisky medication adherence scale to evaluate adherence. The study clarified that 79.6% of patients agreed that their medications were essential, 58.2% were worried about taking medications on a regular basis, and 57.8% were worried about becoming dependent on their medications. The study also explained that patients with a higher level of beliefs about medications had higher adherence, however patients who had higher worried beliefs had lower adherence. So beliefs about medicines are a significant element in improving adherence. 21 1.3 Statement of the Problem and Rationale of the Study Multiple long-term cardiovascular medicine use can affect the different aspects of patients’ daily lives (van der Laan et al., 2018). In addition, the medication burden has an apparent adverse effect on patients’ lives and is linked with adverse drug events (Zidan et al., 2016). Adverse drug reactions (ADRs) have considerable economic and clinical costs as they often lead to hospital admission, prolongation of hospital stay, and emergency department visits(Sultana et al., 2013). Furthermore, the burden and complexity of multiple medication use are associated with worse patient outcomes, including reduced adherence and increased costs, hospitalizations, mortality rates(Boye et al., 2020). So treatment burden can negatively impact on quality of life and adherence to treatments. Moreover, patients’ beliefs about medicines are probably affected by their own experiences, which can affect their adherence to using medications, so poor adherence could compromise their health and life (Tordoff et al., 2019a). Few studies have been performed to evaluate cardiovascular medications’ impact on patients’ lives and quality of life. No research has been conducted in Palestine focusing on these issues using the LMQ scale, which is considered an instrument that quantifies medicine burden, which helps us recognize specific burden challenges that may need to be addressed, resulting in prevention or/and reduction of medicine burden. 22 This study may optimize cardiovascular medication use by quantifying patients’ thoughts, feelings, and experiences using long-term medicine, and resolving drug-related problems. This can improve clinical outcomes, decrease mortality and morbidity, decrease hospitalization, the demand for nursing home care and lower healthcare costs (Demain et al., 2015). The results of this study can help us design interventions to minimize medication burden, assist patients in gaining better use of their medicine, and improve medication adherence and health system costs. 1.4 The Objectives of the Study 1.4.1 General objective The main objective of the current study was to assess the impact of chronic cardiovascular medication use on patients’ daily lives. 1.4.2 Specific objectives  To quantify the medicine burden among cardiovascular patients by using LMQ-3.  To assess the effect of chronic cardiovascular medication use on different aspects of patients’ daily lives.  To examine the relationship between demographic and clinical characteristics of the patients’ daily life score. 23 1.5 Significance of the Study This is the first study in Palestine to measure cardiovascular medications’ impact on patients’ lives by using the LMQ. The study measured the burden of using these medications, which may improve patient quality of life by making an endeavour to reduce the medication-related burden on patients. Furthermore, collecting information about cardiovascular patients’ experience using their medicine will give in-depth a knowledge for healthcare providers about this impact, which encourages them to make a significant effort to decrease patients’ medication-related burden by facilitating a combination of long-term medication use in the daily lives of patients. In addition, this study provides us with appropriate information about the most prominent factors that are influencing medication-related burden that should be taken into consideration when starting to design tailored interventions to minimize this burden, which result in improving patients’ outcome and quality of life, increase medication effectiveness, decrease mortality and morbidity, decrease hospitalization, demand for nursing home care and reduce healthcare costs. 24 Chapter Two Methodology 2.1 Study Design and Settings A cross-sectional study design was used to address the research goals in community pharmacies, Participants were recruited from many pharmacies in the capital city Jerusalem. These pharmacies were private pharmacy or pharmacies in clinic. Recruitment took place over several visits, lasting around three hours each, via face-to-face appointment, between January 2019 and October 2019. In agreement with the pharmacist, approached customers after they had dispensed a prescription or made a purchase. I introduced myself by name, the University I'm studying at. I explained to them the Questionnaire Objectives, and asked if they agree to participate, People who agreed included in this study. Participants were patients who used cardiovascular medication in Jerusalem, Palestine. 2.2 Sample Size The population was chosen from public pharmacies in Jerusalem. The approximated sample size that was obtained was 380 patients. Since the exact number of patients with cardiovascular medications in the study setting is unknown, it is assumed that the population is less than 20,000 patients. This number was used to calculate the sample size needed in this study. By considering a response distribution to be 50% and allowing a 5% margin of error at a 95% confidence interval, the study’s required sample size was determined using the Raosoft sample size calculator 25 (http://www.raosoft.com/samplesize.html). The minimum adequate sample size was 377. In addition, to minimize erroneous results and increase the study’s reliability, the target sample size was increased by 5% to 10%. Furthermore, a pilot study of 10 - 20 patients was done before beginning the actual study. 2.3 Data Collection Data were collected by a pharmacist in community pharmacies familiar with the pharmacies’ work system. Data were collected from January to October 2019. 2.3.1 Tools used in data collection The data collection form (Appendix 1) that was used in this study consists of four parts: 1. Patient’s demographic information: age, gender, locality (urban, rural, camp), health insurance. 2. Clinical information about disease history and comorbidities, including the presence of comorbidities and the name of medications used. 3. Medication information’s: name of medications used, Medications- Related Characteristics, number of medicines used, formulation used, and medication frequency. 4. LMQ-3 scale (Arabic version used): a multi-item survey tool, was developed in the UK, specifically to explore people’s medicine burden. http://www.raosoft.com/samplesize.html 26 It has been validated, refined and revised, and is now known as LMQ-3 and has been translated into many languages. This questionnaire contains 41 statements positively or negatively worded on a 5-point Likert-type scale (strongly agree to strongly disagree), reverse scoring used for negatively worded questions, so that higher scores indicate a higher burden/worse experience of medicine utilization. So the degree of medication-related burden (MRB) is classified based on the LMQ overall score: (41–73) no burden at all; (74–106) minimum burden; (107–139) moderate burden; (140–172) high burden; (173–205) extremely high burden. 5. Based on data from cardiovascular patients. The LMQ-3 also consists of a visual analogue scale (VAS), that allowed the patient to express his or her overall perceived medication burden, a scale from 1–10 that measures global burden, with anchors indicating (no burden at all, to extremely burdensome. LMQ total scores were compared to scores from the VAS, “Overall, how much of a burden do you feel your medicines are to you, by measuring the mean of VAS, and notice if there is a positive correlation between LMQ total scores and VAS burden scores. And an optional free-text question. (Tordoff et al., 2019a, Zidan et al., 2018b). Subscale/domain score was the summation of item scores per domain, which are related to interferences with day-to-day life, side effects, general concerns about medicines, practical difficulties, lack of effectiveness, patient-physician relationship/ communication issues, cost-related burden, 27 and absence of autonomy /control over medicines’ use as represented in Appendix 2. Thus the LMQ-3 total score is the summation of all subscale scores (Krska et al., 2017a). In this study, we use LMQ-3 to measure the treatment burden among patients with cardiovascular disease. This questionnaire is a reliable, valid instrument, has an acceptable construct, criterion-related and known-groups validity, and is internally consistent as a measure of medicine burden. A culturally suitable translation of the LMQ was generated for potential research and clinical practice in Arabic-speaking countries. Further validation of the developed Arabic version is recommended and required. This Questionnaire covers practical difficulties, general concerns about medication, patient–health professionals communication and relationships about medicines, interference with everyday life, lack of effectiveness, cost-related burden, shortage of autonomy/control of medicine use, and side effects. The LMQ-3 has a 5-point rating scale to measure the extent of agreement with each statement, in addition to a free-text box to enable patients to add any further issues not covered by the questionnaire or to explain their responses (Zidan et al., 2016). Permission to use this instrument was obtained from both the original developer of the scale and the group that translated it to the Arabic language (Katusiime et al., 2018). 28 2.4 Inclusion and Exclusion Criteria 2.4.1 Inclusion criteria 1. Residents aged 18 years and above. 2. Patients have cardiovascular disease and using cardiovascular medication. 3. Patients who agreed to participate. 2.4.2 Exclusion criteria 1. Patients were unable to understand the questions. 2. Patients have cancer or are receiving chemotherapy. 2.5 Statistical Data Analysis All data were analysed using the Statistical Package for Social Sciences (SPSS) (SPSS Inc., Chicago, IL, USA) program version 16. The descriptive analysis presented the normally distributed continuous variables as means ± standard deviations (SD), the not normally distributed continuous variables as medians (lower-upper quartiles), and the categorical variables as frequencies and percentages. Kolmogorov–Smirnov test was used to assess data normality. Differences in score results were evaluated using the t-test for continuous variables (normally distributed). The Mann–Whitney U test or Kruskal–Wallis was performed appropriately for not normally distributed ones. Either the chi-square or the Fisher exact test was used, as 29 appropriate, to test the significance between categorical variables. The level of significance was determined at P < 0.05. Also, scores of LMQ-3 were calculated from the responses to the statements of the questionnaire, using reversed scoring as required. The scores were then categorized into a low, moderate, or high burden (Katusiime et al., 2018). 2.6 Ethical Approval Before the start of the research, approval of Institutional Review Board (IRB) (Appendix 3--), and agreement of Faculty of Graduate Studies at An- Najah National University were received to ascertain patients’ rights, and facilitate the research progression. Only patients who agreed to participate were included in the study after discussing the research objectives and protocols with each one and obtaining a verbal agreement. 30 Chapter Three Results 3.1 Sociodemographic Characteristics of the Study Patients A total number of 380 patients with cardiovascular diseases were included in this study. The data were collected from the community pharmacies in Jerusalem, Palestine. Table 3.1 shows the socio-demographic characteristics of the patients. The mean age (±SD) of patients was 58±12.2 years, ranging from 20 to 85 years; 53% were between 30 and 60 years, and 46% were above 60 years old. In addition, 195 (51.3%) patients were females, and 185 (48.7) were males giving a female:male ratio of 1.55:1. The majority of patients, 227 (59.7%) were living in urban areas, 125 (32.9%) and 28 (7.4%) patients were living in rural and camp areas, respectively. The majority of patients have health insurance (292, (76.8%)). Table 3.1: Socio-demographic characteristics of the study patients (N=380). Characteristic Total (n=380) Age (years) Mean ± SD Range 58 ± 12.2 20-85 Age category (years) <60 >60 205 (53.9) 175 (46.1) Gender, n% Male Female 185(48.7) 195 (51.3) Locality, n% Urban Rural Refugee camp 227 (59.7) 125 (32.9) 28 (7.4) Insurance, n% Yes No 292 (76.8) 88 (23.2) 31 3.2 Cardiovascular Diseases and Other Comorbidities among the Patients of the Study The study patients had a mean ± SD of 2.68 ± 1.17 and median (interquartile range) of 3 (2-–3) illnesses with a maximum of 8. Regarding cardiovascular diseases, 259 (68.2%) of patients had hypertension, followed by 102 (26.8%) with ischaemic heart diseases, 64 (16.8%) with heart failure, and 12 (3.2%) with atrial fibrillation (Table 3.2). Regarding other co-morbid diseases, Table 3.2 shows that the majority of patients suffered from diabetes mellitus (n=178, 46.8%), followed by dyslipidaemia (n=158, 41.6%). Table 3.2: Chronic diseases among the study sample. Chronic disease Total (n=380) Frequency (%) Hypertension 259 (68.2) Diabetes mellitus 178 (46.8) Dyslipidaemia 158 (41.6) Ischaemic heart diseases 152 (26.8) Peptic ulcer 88 (23.2) Heart failure 64 (16.8) Hypoparathyroidism 32 (8.4) Anaemia 17 (4.5) Arterial fibrillation 12 (3.2) Vit. D deficiency 10 (2.6) Osteoporosis 9 (2.4) Stroke 8 (2.1) Neuropathic pain 7 (1.8) Gout 4 (1.1) Rheumatoid arthritis 4 (1.1) Renal failure 3 (0.8) Urinary stone 3 (0.8) Depression 3 (0.8) Glaucoma 3 (0.8) Allergic rhinitis 3 (0.8) Insomnia 3 (0.8) Benign prostatic hyperplasia 3 (0.8) Asthma 3 (0.8) 32 3.3 Chronic Medications Used by the Study Sample Regarding medications used, the number of medications used among patients ranged from 1–13, with a mean (±SD) of 4 ± 1.71 and median (interquartile range) of 4 (3–5). As shown in Table 3.3, according to patients’ medications; aspirin (n=181, 47.6%), atorvastatin (n=134, 35.5%), metformin (n=104, 27.4%) and bisoprolol (n=90, 23.7%) were the most commonly used medications. Table 3.3: The most commonly prescribed medications. Medication Name Total (n=380) Frequency (%) Aspirin 181 (47.6) Atorvastatin 134 (35.5) Metformin 104 (27.4) Bisoprolol 90 (23.7) Ramipril 83 (21.8) Clopidoxcel 80 (21.1) Amiodarone 19 (5) Furosemide 44 (11.6) Omeprazole 42 (11.1) Enalapril 41 (10.8) Insulin 41 (10.8) Valsartan/ Hydrochlorothiazide 40 (10.5) Amlodipine 37 (9.7) Atenolol 36 (9.5) Levothyroxine 32 (8.4) Glimepiride 30 (7.9) Losartan 22 (5.8) Rosuvastatin 22 (5.8) Sitagliptin/Metformin 22 (5.8) Simvastatin 21 (5.5) Esomeprazole 20 (5.3) Valsartan/Amlodipine 20 (5.3) Calcium+vitD 16 (4.2) Spironolactone 16 (4.2) Lercadipine 15 (3.9) Metoprolol 14 (3.7) Iron 13 (3.4) Vitamin B12 13 (3.4) Pregabalin 12 (3.2) Empagliflozin 11 (2.9) 33 Lansoprazole 11 (2.9) Liraglutide 11 (2.9) Vitamin D 10 (2.6) Metformin/Pioglitazone 9 (2.3) Bezafibrate 8 (2.1) Nitrate 8 (2.1) Prasugrel 8 (2.1) Ramipril/Hydrochlorothiazide 8 (2.1) Apixaban 7 (1.8) Glibenclamide 7 (8.1) Propranolol 7 (1.8) Ranitidine 7 (1.8) Vidogliptin 7 (1.8) Candesartan/Hydrochlorothiazide 6 (1.6) Empagliflozin/Metformin 6 (1.6) Nifedipine 6 (1.6) Digoxin 5 (1.3) Doxazocin 5 (1.3) Metformin/Pioglitazone 5 (1.3) Dulaglutide 5 (1.3) Allopuranol 4 (1.1) Alfacalcidol 4 (1.1) Dapagliflozin/Metformin 4 (1.1) Hydrochlorothiazide 4 (1.1) Pantoprazole 4 (1.1) Rivaroxaban 4 (1.1) Warfarin 4 (1.1) Amitriptyline 4 (1.1) Alendronate 3 (0.8) Dabigatran 3 (0.8) Pravastatin 3 (0.8) Prednisolone 3 (0.8) Tamsulosin 3 (0.8) Brotiazolam 2 (0.5) Carvedilol 2 (0.5) Escitalopram 2 (0.5) Losartan/Hydrochlorothiazide 2 (0.5) Propylthiouracil 2 (0.5) Acetazolamide 1 (0.3) Cilazapril/Hydrochlorothiazide 1 (0.3) Colchicine 1 (0.3) Duloxetine 1 (0.3) Dutasteride 1 (0.3) Famotidine 1 (0.3) Fexofenadine 1 (0.3) Fingolimod 1 (0.3) Flecainide 1 (0.3) Gabapentin 1 (0.3) Ivabradine 1 (0.3) Hydroxycarbamide 1 (0.3) Letrozole 1 (0.3) Lorazepam 1 (0.3) 34 Methotrexate 1 (0.3) Oxcarbazepine 1 (0.3) Potassium Chloride 1 (0.3) Repaglinide 1 (0.3) Risedronate 1 (0.3) Saxagliptin 1 (0.3) Sitagliptin 1 (0.3) Sulfasalazine 1 (0.3) Terazosin 1 (0.3) Teriflunomide 1 (0.3) Ticagrelor 1 (0.3) Verapamil 1 (0.3) Citalopram 1 (0.3) Diazepam 1 (0.3) 3.4 Medications-Related Characteristics Two hundred and fifty-one patients (66.1%) used 1–4 medicines, and 122 (32.1%) patients used 5–9 medicines. On the other hand, nearly all patients used formulations that are oral solid formulations, with 314 (82.6%) using tablets or capsules, while 17.4% of patients used tablets or capsules with other formulations. More than half of the patients reported using medicines once daily, and 34% reported using them twice daily (Table 3.4). Table 3.4: Medication-related characteristics. Medication-related characteristics Total (n=380) Frequency (%) Number of medicines 1–4 5–9 10 or more 251 (66.1%) 122 (32.1%) 7 (1.8%) Formulation used Tablet/capsule Tablet/capsule with other formulation 314 (82.6%) 66 (17.4%) Medication Frequency Once daily Twice daily Three times daily More than three times daily Other times* 200 (52.6%) 131 (34.5%) 39 (10.3%) 1 (0.3%) 9 (2.4%) * Includes medications used when needed (prn), different days of the week, every two weeks, once a month, weekly, every three months, or every half-year. 35 3.5 Assessment of Medication-Related Burden Using LMQ-3 Concerning communication/relationships with healthcare providers about medications, 299 (78.6%) of respondents trusted their physicians’ judgement in choosing their medication. About three-quarters of participants 294 (77.4%) judged that physician listen to their personal opinions,306 (85%) take their worries about side effects seriously, 297 (78.2%) explained that they get enough information about medications from their physician and that healthcare providers know enough about them and their medications 289 (76.1%), (Tables 3.5 ,3.6 ,3.7). In this domain, remarkably higher scores indicated poorer quality relationships among female participants (P-value 0.046), urban locality (P-value 0.00), without health insurance (P-value 0.015). (Table 3.8) Over 60% of participants did not find it a struggle to receive prescriptions from their physicians or medicines from pharmacists. Eighty-three percent (317) feel that the times for taking their medicines are appropriate, 276 (72.6%) were worried about forgetting to take their medications, and it is easy for them to keep to their medication schedule 289 (76%), (Tables 3.5, 3.6, 3.7). Putting a lot of thought and planning into using medications is seen only in 109 (30%) of participants, and 99 (26%) feel that using their medicines is hard. Remarkable higher scores, indicating more practical difficulties, were found among patients without health insurance ( P-value 0.003). (Table 3.8) 36 The price of prescribed medications was troublesome for approximately half of the respondents (Tables 3.5, 3.6, 3.7). Significant high scores indicating a greater price-related burden were found in patients suffering from one disease (P-value 0.031). (Table 3.8). Concerning the side effects,218 (57.4%) of participants strongly agree/agreed that side effects were much worse than the disease for which they were taking medications and 275( 72.4%) of respondents feel that the side effects of medications intervene in their daily lives (Tables 3.5, 3.6, 3.7). Significant higher scores indicating greater side effect-related burdens were found in participants’ who had one or two diseases (P- value 0.02). (Table 3.8). With regard to the perceived effectiveness of medicines,301( 79.3%) of participants felt that their medications are actually working, 294 (77.4% ) live up to their expectations, 313( 82.4%) agree that medicines prevent their conditions from getting worse, about fourth-fifths of respondents reported the advantages and expressed satisfaction (Tables 3.5, 3.6, 3.7). The assessment of attitudes/ concerns about medicines finds that 300 (79%) of participants felt they require more information about their medications, 221 (58.2%) were worried about long-term effects of using medications, potential drug–drug interactions 273 (71.8%), and potential drug–beverage interaction 234(61.6%). Three-quarters of them were worried about using several medicines at the same time, and 209 (55%) were worried about being too dependent on their medications. Two-thirds of participants would 37 prefer to have more say in the brands of medications used (Tables 3.5, 3.6, 3.7). In terms of the impact/ interference of medications with daily life,251 (66.1%) of respondents referred that their lives revolved around using their medications, approximately half of respondents see that their medications intervene with leisure or social activities,198 (52.1%) feel that taking medicines affects their driving, and 269 (70.8%) that their medicines did not interfere with their social relationships. Half of the respondents see that taking medicines causes problems with daily tasks; 242 (63.7%) deny medicines’ interference with their sexual life (Table 3.5, 3.6, 3.7). Significantly higher scores elucidating greater interference with daily life were observed among patients with one disease (P-value 0.013) and those were using 1–4 medicines (P-value 0.008). (Table 3.8) Over half of the patients reported minimal empowerment to change their medication regimens to accommodate their lifestyles, according to an evaluation of their control/autonomy over their medication regimens; 95(25%) felt they could change their medicine dose, 172 (45.3%) thought they had the option of using or not using their medications. In contrast, one-third felt they could change the administration times (Tables 3.5, 3.6, 3.7). Patients who used tablets/capsules with other formulations had significantly higher scores (P-value 0.027), and those who uses 1-4 medicine or 5-9 medicine (P-value 0.006) suggesting a lack of control (Table 3.8). 38 Gender, locality and formulation affected one domain; health insurance and medication number affected two domains; the number of diseases affected three domains. (Table 3.8) Table 3.5: Patients’ response to Living with Medicines Questionnaire (LMQ‐3) n=380. Question Total (n = 380) n (%) 1- I find getting my prescriptions from the physician hard Strongly Agree Agree Neutral Disagree Strongly Disagree 42 (11.1) 84 (22.1) 24 (6.3) 173 (45.5) 57 (15) 2- I find getting my medications from the pharmacist hard Strongly Agree Agree Neutral Disagree Strongly Disagree 34 (8.9) 72 (18.9) 17 (4.5) 193 (50.8) 64 (16.8) 3-I am delighted with the effectiveness of the medications Strongly Agree Agree Neutral Disagree Strongly Disagree 87 (22.9) 223 (58.7) 17 (4.5) 50 (13.2) 3 (8) 4- I am satisfied with the times I should take my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 115 (30.3) 202 (53.2) 15 (3.9) 40 (10.5) 8 (2.1) 5- I am concerned about paying for my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 69 (18.2) 97 (25.5) 24 (6.3) 157 (41.3) 33 (8.7) 6- I am concerned that I have to take several medications at the same time Strongly Agree Agree Neutral Disagree Strongly Disagree 90 (23.7) 188 (49.5) 22 (5.8) 62 (16.3) 18 (4.7) 7- I trust the decision of my physician(s) in choosing medications for me Strongly Agree Agree 126 (33.2) 173 (45.5) 39 Neutral Disagree Strongly Disagree 29 (7.6) 44 (11.6) 8 (2.1) 8- I would like more say in the brands of medications I utilize Strongly Agree Agree Neutral Disagree Strongly Disagree 79 (20.8) 175 (46.1) 32 (8.4) 79 (20.8) 15 (3.9) 9- I feel I need more information about my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 138 (36.3) 162 (42.6) 19 (5) 51 (13.4) 10 (2.6) 10- I am worried that I may forget to take my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 81 (21.3) 195 (51.3) 26 (6.8) 69 (18.2) 9 (2.4) 11- I can change the dose of the medications I take Strongly Agree Agree Neutral Disagree Strongly Disagree 31 (8.2) 64 (16.8) 20 (5.3) 201 (52.9) 64 (16.8) 12- I am worried about possible damaging long-term effects of taking medications Strongly Agree Agree Neutral Disagree Strongly Disagree 83 (21.8) 138 (36.3) 30 (7.9) 108 (28.4) 21 (5.5) 13- I can decide whether or not to take my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 51 (13.4) 121 (31.8) 16 (4.2) 119 (31.3) 73 (19.2) 14- My physician(s) listen to my opinions about my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 71 (18.7) 223 (58.7) 29 (7.6) 46 (12.1) 11 (2.9) 15- My medications prevent my condition from getting worse Strongly Agree Agree Neutral Disagree Strongly Disagree 80 (21.1) 233 (61.3) 17 (4.5) 37 (9.7) 13 (3.4) 40 16- I am worried that I am too dependent on my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 76 (20) 133 (35) 27 (7.1) 110 (28.9) 34 (8.9) 17- I am worried that my medications interact with foods, alcohol Strongly Agree Agree Neutral Disagree Strongly Disagree 87 (22.9) 147 (38.7) 22 (5.8) 104 (27.4) 20 (5.3) 18- I am concerned that my medicines may interact with each other Strongly Agree Agree Neutral Disagree Strongly Disagree 92 (24.2) 181 (47.6) 23 (6.1) 77 (20.3) 7 (1.8) 19- My medications interfere with my social or leisure activities Strongly Agree Agree Neutral Disagree Strongly Disagree 88 (23.2) 93 (24.5) 16 (4.2) 148 (38.9) 35 (9.2) 20- My physician takes my worries about side effects seriously Strongly Agree Agree Neutral Disagree Strongly Disagree 127 (33.4) 179 (47.1) 25 (6.6) 45 (11.8) 4 (1.1) 21- The side effects I get are sometimes worse than the disease for which I take medications Strongly Agree Agree Neutral Disagree Strongly Disagree 70 (18.4) 148 (38.9) 20 (5.3) 117 (30.8) 25 (6.6) 22- The side effects I get from my medications interfere with my daily life (e.g., work, housework, sleep) Strongly Agree Agree Neutral Disagree Strongly Disagree 87 (22.9) 188 (49.5) 13 (3.4) 86 (22.6) 6 (1.6) 23- I have to put a lot of planning and thought into taking my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 33 (8.7) 76 (20) 26 (6.8) 182 (47.9) 63 (16.6) 41 24- I get enough information about my medications from my physician(s) Strongly Agree Agree Neutral Disagree Strongly Disagree 124 (32.6) 173 (45.5) 25 (6.6) 48 (12.6) 10 (2.6) 25- My medications live up to my expectations Strongly Agree Agree Neutral Disagree Strongly Disagree 101 (26.6) 200 (52.6) 32 (8.4) 43 (11.3) 4 (1.1) 26- I can change the times I take my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 31 (8.2) 107 (28.2) 17 (4.5) 168 (44.2) 57 (15) 27- It is easy to keep to my medications routine Strongly Agree Agree Neutral Disagree Strongly Disagree 99 (26.1) 190 (50) 20 (5.3) 54 (14.2) 17 (4.5) 28- Taking medications affects my driving abilities Strongly Agree Agree Neutral Disagree Strongly Disagree 50 (13.2) 148 (38.9) 37 (9.7) 108 (28.4) 37 (9.7) 29- I find using my medications difficult Strongly Agree Agree Neutral Disagree Strongly Disagree 27 (7.1) 72 (18.9) 18 (4.7) 179 (47.1) 84 (22.1) 30- The side effects I get from my medications are annoying Strongly Agree Agree Neutral Disagree Strongly Disagree 79 (20.8) 124 (32.6) 23 (6.1) 123 (32.4) 31 (8.2) 31- I sometimes have to decide between buying basic essentials or medications Strongly Agree Agree Neutral Disagree Strongly Disagree 84 (22.1) 153 (40.3) 25 (6.6) 86 (22.6) 32 (8.4) 42 32- My medications allow me to live my life as I want to Strongly Agree Agree Neutral Disagree Strongly Disagree 83 (21.8) 211 (55.5) 17 (4.5) 50 (13.2) 19 (5) 33- I have to pay more for my drugs than I can afford Strongly Agree Agree Neutral Disagree Strongly Disagree 69 (18.2) 85 (22.4) 22 (5.8) 171 (45) 33 (8.7) 34-The healthcare professionals providing my care know enough about me and my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 108 (28.4) 181 (47.6) 25 (6.6) 57 (15) 9 (2.4) 35- My medications interfere with my social relationships Strongly Agree Agree Neutral Disagree Strongly Disagree 22 (5.8) 69 (18.2) 20 (5.3) 200 (52.6) 69 (18.2) 36- Taking medications makes it difficult for me to complete daily activities (such as work, housework, hobbies) Strongly Agree Agree Neutral Disagree Strongly Disagree 68 (17.9) 125 (32.9) 16 (4.2) 146 (38.4) 25 (6.6) 37- My medications have a negative impact on my sexual life Strongly Agree Agree Neutral Disagree Strongly Disagree 15 (3.9) 64 (16.8) 59 (15.5) 165 (43.4) 77 (20.3) 38- My drugs’ side effects have a negative impact on my health Strongly Agree Agree Neutral Disagree Strongly Disagree 25 (6.6) 99 (26.1) 26 (6.8) 183 (48.2) 47 (12.4) 39- My medications are working Strongly Agree Agree Neutral Disagree Strongly Disagree 94 (24.7) 207 (54.5) 26 (6.8) 42 (11.1) 11 (2.9) 40- The side effects are worth it for the benefits I get from my medications Strongly Agree Agree 106 (27.9) 192 (50.5) 43 Neutral Disagree Strongly Disagree 30 (7.9) 47 (12.4) 5 (1.3) 41- My life revolves around using my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 76 (20) 175(46.1) 26 (6.8) 79 (20.8) 24 (6.3) Table 3.6: Response to LMQ arranged according to the eight domains. Relationships Domain Questions I trust the decision of my physician(s) in choosing medications for me Strongly Agree Agree Neutral Disagree Strongly Disagree 126 (33.2) 173 (45.5) 29 (7.6) 44 (11.6) 8 (2.1) My physician(s) listens to my opinions about my medicines Strongly Agree Agree Neutral Disagree Strongly Disagree 71 (18.7) 223 (58.7) 29 (7.6) 46 (12.1) 11 (2.9) My physician takes my concerns about side effects seriously Strongly Agree Agree Neutral Disagree Strongly Disagree 127 (33.4) 179 (47.1) 25 (6.6) 45 (11.8) 4 (1.1) I get enough information about my medications from my physician(s) Strongly Agree Agree Neutral Disagree Strongly Disagree 124 (32.6) 173 (45.5) 25 (6.6) 48 (12.6) 10 (2.6) The healthcare professionals providing my care know enough about me and my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 108 (28.4) 181 (47.6) 25 (6.6) 57 (15) 9 (2.4) Practicalities Domain Questions I find getting my prescriptions from the physician hard Strongly Agree Agree 42 (11.1) 84 (22.1) 44 Neutral Disagree Strongly Disagree 24 (6.3) 173 (45.5) 57 (15) I find getting my medications from the pharmacist hard Strongly Agree Agree Neutral Disagree Strongly Disagree 34 (8.9) 72 (18.9) 17 (4.5) 193 (50.8) 64 (16.8) I am satisfied with the times I should take my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 115 (30.3) 202 (53.2) 15 (3.9) 40 (10.5) 8 (2.1) I am worried that I may forget to take my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 81 (21.3) 195 (51.3) 26 (6.8) 69 (18.2) 9 (2.4) I have to put a lot of planning and thought into taking my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 33 (8.7) 76 (20) 26 (6.8) 182 (47.9) 63 (16.6) It is easy to keep to my medications routine Strongly Agree Agree Neutral Disagree Strongly Disagree 99 (26.1) 190 (50) 20 (5.3) 54 (14.2) 17 (4.5) I find using my medications hard Strongly Agree Agree Neutral Disagree Strongly Disagree 27 (7.1) 72 (18.9) 18 (4.7) 179 (47.1) 84 (22.1) Cost Domain Questions I am concerned about paying for my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 69 (18.2) 97 (25.5) 24 (6.3) 157 (41.3) 33 (8.7) I sometimes have to choose between buying basic essentials or medications Strongly Agree Agree 84 (22.1) 153 (40.3) 45 Neutral Disagree Strongly Disagree 25 (6.6) 86 (22.6) 32 (8.4) I have to pay more for my drugs than I can afford. Strongly Agree Agree Neutral Disagree Strongly Disagree 69 (18.2) 85 (22.4) 22 (5.8) 171 (45) 33 (8.7) Side effects Domain Questions The side effects I get are sometimes worse than the disease for which I take medications Strongly Agree Agree Neutral Disagree Strongly Disagree 70 (18.4) 148 (38.9) 20 (5.3) 117 (30.8) 25 (6.6) The side effects I get from my medications interfere with my daily life (e.g., work, housework, sleep) Strongly Agree Agree Neutral Disagree Strongly Disagree 87 (22.9) 188 (49.5) 13 (3.4) 86 (22.6) 6 (1.6) The side effects I get from my medications are annoying Strongly Agree Agree Neutral Disagree Strongly Disagree 79 (20.8) 124 (32.6) 23 (6.1) 123 (32.4) 31 (8.2) The side effects I get from my medications adversely affect my well-being Strongly Agree Agree Neutral Disagree Strongly Disagree 25 (6.6) 99 (26.1) 26 (6.8) 183 (48.2) 47 (12.4) Lack of effects Domain Questions I am delighted with the effectiveness of the medications. Strongly Agree Agree Neutral Disagree Strongly Disagree 87 (22.9) 223 (58.7) 17 (4.5) 50 (13.2) 3 (8) My medications prevent my condition from getting worse. Strongly Agree Agree Neutral Disagree Strongly Disagree 80 (21.1) 233 (61.3) 17 (4.5) 37 (9.7) 13 (3.4) 46 -My medications live up to my expectations. Strongly Agree Agree Neutral Disagree Strongly Disagree 101 (26.6) 200 (52.6) 32 (8.4) 43 (11.3) 4 (1.1) My medications allow me to live my life as I want to Strongly Agree Agree Neutral Disagree Strongly Disagree 83 (21.8) 211 (55.5) 17 (4.5) 50 (13.2) 19 (5) -My medications are working. Strongly Agree Agree Neutral Disagree Strongly Disagree 94 (24.7) 207 (54.5) 26 (6.8) 42 (11.1) 11 (2.9) The side effects are worth it for the benefits I get from my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 106 (27.9) 192 (50.5) 30 (7.9) 47 (12.4) 5 (1.3) Concerns Domain Questions I am concerned that I have to take several medications at the same time Strongly Agree Agree Neutral Disagree Strongly Disagree 90 (23.7) 188 (49.5) 22 (5.8) 62 (16.3) 18 (4.7) I would like to have more say in the brands of medications I use Strongly Agree Agree Neutral Disagree Strongly Disagree 79 (20.8) 175 (46.1) 32 (8.4) 79 (20.8) 15 (3.9) I feel I need more information about my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 138 (36.3) 162 (42.6) 19 (5) 51 (13.4) 10 (2.6) I am worried about possible damaging long-term effects of taking medications Strongly Agree Agree Neutral Disagree Strongly Disagree 83 (21.8) 138 (36.3) 30 (7.9) 108 (28.4) 21 (5.5) 47 I am worried that I am too dependent on my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 76 (20) 133 (35) 27 (7.1) 110 (28.9) 34 (8.9) I am worried that my medications interact with foods, alcohol Strongly Agree Agree Neutral Disagree Strongly Disagree 87 (22.9) 147 (38.7) 22 (5.8) 104 (27.4) 20 (5.3) -I am concerned that my medications may interact with each other Strongly Agree Agree Neutral Disagree Strongly Disagree 92 (24.2) 181 (47.6) 23 (6.1) 77 (20.3) 7 (1.8) Interference Domain Questions My medications interfere with my social or leisure activities Strongly Agree Agree Neutral Disagree Strongly Disagree 88 (23.2) 93 (24.5) 16 (4.2) 148 (38.9) 35 (9.2) Taking medications affect my driving abilities Strongly Agree Agree Neutral Disagree Strongly Disagree 50 (13.2) 148 (38.9) 37 (9.7) 108 (28.4) 37 (9.7) My medications interfere with my social relationships Strongly Agree Agree Neutral Disagree Strongly Disagree 22 (5.8) 69 (18.2) 20 (5.3) 200 (52.6) 69 (18.2) Taking medicines makes it difficult for me to complete daily activities (such as work, housework, hobbies) Strongly Agree Agree Neutral Disagree Strongly Disagree 68 (17.9) 125 (32.9) 16 (4.2) 146 (38.4) 25 (6.6) My medication has a negative impact on my sexual life. Strongly Agree Agree 15 (3.9) 64 (16.8) 48 Neutral Disagree Strongly Disagree 59 (15.5) 165 (43.4) 77 (20.3) My life revolves around using my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 76 (20) 175(46.1) 26 (6.8) 79 (20.8) 24 (6.3) Autonomy Domain Questions I can change the dose of the medication I take Strongly Agree Agree Neutral Disagree Strongly Disagree 31 (8.2) 64 (16.8) 20 (5.3) 201 (52.9) 64 (16.8) I can decide whether or not to take my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 51 (13.4) 121 (31.8) 16 (4.2) 119 (31.3) 73 (19.2) I can change the times I take my medications Strongly Agree Agree Neutral Disagree Strongly Disagree 31 (8.2) 107 (28.2) 17 (4.5) 168 (44.2) 57 (15) 49 Table 3.7: Differences in proportions of patients agreeing with 41 LMQ items. Statements Agree/Strong Agree, N (%) Strongly Disagree/ Disagree, N (%) Neutral, N (%) 1- Relationships (items=5 ;Mean (SD)=10.5 (3.6) I trust the decision of my physician(s) in choosing medication for me My physician(s) listens to my opinions about my medications My physician takes my concerns about side effects seriously I get enough information about my medications from my doctor(s) The healthcare professionals providing my care know enough about me and my medications 299(78.6%) 294(77.4%) 306(85%) 297(78.2%) 289(76.1%) 52(13.6) 57(15%) 49(12.9%) 58(15.2%) 66(17.3%) 29(7.6) 29(7.6%) 25(6.6%) 25(6.6%) 25(6.6) 2- Practicalities (Items= 7 , Mean (SD)=20.3 (3.5) I find getting my prescriptions from the doctor hard I find getting my medications from the pharmacist hard I am satisfied with the times I should take my medications I am worried that I may forget to take my medications I have to put a lot of planning and thought into taking my medications It is easy to keep to my medication routine I find using my medications difficult 126(33.2%) 106(27.9%) 317(83.4%) 276(72.6%) 109(28.7%) 289(76.1%) 99(26.1%) 230(60.5%) 257(67.6%) 48(12.6%) 78(20.5%) 245(64.5%) 71(18.7%) 263(69.2%) 24(6.3%) 17(4.5%) 15(3.9%) 26(6.8%) 26(6.8%) 20(5.3%) 18(4.7%) 3- Cost (Items=3, Mean (SD)=8.6 (3) I am concerned about paying for my medications 166(43.7%) 190(50%) 24(6.3%) 50 I sometimes have to choose between buying basic essentials or medications I have to pay more for my drugs than I can afford 237(62.4%) 154(40.5%) 89(23.4%) 204(53.7%) 25(6.6%) 22(5.8%) 4- Side effects (Items=4, Mean (SD)= 11.1 (3.4) The side effects I get are sometimes worse than the disease for which I take medications The side effects I get from my medications interfere with my daily life (e.g., work, housework, sleep) The side effects I get from my medications are annoying My drug side effects have a negative impact on my health 218(57.4%) 275(72.4%) 203(53.4%) 124(32.6%) 142(37.4%) 92(24.2%) 118(31%) 230(60.1%) 20(5.3%) 13(3.4%) 25(6.6%) 26(6.8%) Statements Agree/Strong Agree, N (%) Strongly Disagree/ Disagree, N (%) Neutral, N (%) 5- Lack of effect (Items=6, Mean (SD)=12.8 (3.7) I am delighted with the effectiveness of my medications My medications prevent my condition from getting worse My medications live up to my expectations My medications allow me to live my life as I want to My medications are working The side effects are worth it for the benefits I get from my medications 310(81.6%) 313(82.4%) 301(79.2%) 294(77.4%) 301(79.3%) 298(78.4%) 53(13.9%) 50(13.2%) 47(12.4%) 69(18.1%) 53(13.9%) 52(13.7%) 17(4.5%) 17(4.5%) 32(8.4%) 17(4.5%) 26(6.8%) 30(7.9%) 6- Concerns (Items=7, Mean (SD)=16.8 (4.9) I worry that I have to take several medications at the same time 278(73.2%) 80(21%) 22(5.8%) 51 I would like to have more say in the brands of medications I use I feel I need more information about my medications I am concerned about possible damaging long-term effects of taking medications I am worried that I am too dependent on my medications I am worried that my medications interact with alcohol I am concerned that my medications may interact with each other 254(66.8%) 300(79%) 221(58.2%) 209(55%) 234(61.6%) 273(71.8%) 94(24.7%) 61(16%) 129(33.9%) 144(37.9%) 124(32.6%) 84(22.1%) 32(8.6%) 19(5%) 30(7.9%) 27(7.1%) 22(5.8%) 23(6.1%) 7- Interference (Items=6, Mean (SD)=18.2 (4.7) My medications interfere with my social or leisure activities Taking medications affects my driving abilities My medications interfere with my social relationships Taking medications causes me problems with daily tasks (such as work, housework, hobbies). My medications have a negative impact on my sexual life My life revolves around using my medications 181(47.6%) 198(52.1%) 91(23.92%) 193(50.8%) 79(20.8%) 251(66.1%) 183(48.2%) 145(38.2%) 269(70.8%) 171(45%) 242(63.7%) 103(27.1%) 16(4.2%) 37(9.7%) 20(5.3%) 16(4.2%) 59(15.5% 26(6.8%) 8- Autonomy (Items=3, Mean (SD)= 9.9 (2.6) I can change the dose of the medications I take I can decide whether or not to take my medications I can change the times I take my medications 95(25%) 172(45.3%) 138(36.3%) 265(69.7%) 192(50.5%) 225(59.2%) 20(5.3%) 16(4.2%) 17(4.5%) 52 Table 3.8: Effect of demographic and medication-related characteristics of respondents on individual domains of Living with Medicines Questionnaire version-3 LMQ-3 (n=380). Median (IQR) domain score (^Maximum possible score) Characteristics Relationships (^25) Practicalities (^35) Cost (^15) Side effects (^20) Effectiveness (^30) Concerns (^35) Interference (^30) Autonomy (^15) Gender Male Female P-value 10(7–12) 10(8–13) 0.046 21(19–22) 21(19–22) 0.793 10(6–10) 9(6–10) 0.231 10(8–14) 11(9–14) 0.219 18(14–20) 17(12–20) 0.11 18(14–20) 17(12–20) 0.110 18(15–22) 18(15–22) 0.523 10(8–12) 10(8–12) 0.692 Age <50 50–64 >65 P-value 10(8–13( 10(8–13) 10(7–12) 0.113 21(17–22.5) 21(18–22) 21(19–22) 0.808 9(6–10.5) 9(6–10) 10(7–10.75) 0.168 10(8–14) 11(9–14) 11(8–14) 0.537 16(12–19) 18(12–21) 18(15–20) 0.068 16(12–19) 18(12–21) 18(15–20) 0.068 16(12–19) 18(12–21) 18(15–20) 0.068 10(8–12) 10(8–12) 10(8–12) 0.110 Locality Urban Rural Refugee camp P-value 10(8–13) 9(7–11) 9(8–11) 0.001 21(18–22) 21(19–22) 20.5(18.25-2.75) 0.694 9(6–11) 10(7–10) 7.5(6–9) 0.080 10(8–14) 11(9–14) 111(8–13) 0.210 17(12–2) 18(14.5–19) 16(12.5–20.5) 0.312 17(12–21) 18(14.5–19) 16(12.25–20.5) 0.312 18(14–21) 19(16–22) 20.5(14–23) 0.061 10(8–12) 10(8–12) 10(9–12) 0.293 Health Insurance No Yes P-value 11(9–13) 10(7–12) 0.015 21(19–22) 20(17–23) 0.003 9(7–11) 9(6–10) 0.518 10(8–14) 11(8–14) 0.550 18(14–20) 17(13–20) 0.696 18(14–20) 17(13–20) 0.696 17(14–21.75) 19(15–22) 0.094 10(7–12) 10(8–12) 0.270 No. of Diseases One Disease Two Diseases Three Diseases Four Diseases Five Diseases & More P-value 10(8–13) 10(8–13) 9(7–11) 10(7–14) 10(7.25–12.5) 0.146 21(19–22.25) 21(19–22) 21(19–22) 20(18–22) 20.5(17.25–22) 0.744 10(8.75–12) 9(6–10) 9(6–10) 9(5–10) 8.5(4.25–10) 0.031 12(10–14) 12(9–14) 10(8–14) 10(8–13) 10(9-11.75) 0.020 18.5(16–21.25) 18(13–21) 17(12–18.25) 16(12.5–19.5) 15.5(12–20.5) 0.080 18.5(16–21.25) 18(13–21) 17(12–19.25) 16(12.5–19.5) 15.5(12–20.5) 0.080 20(17–23) 19(15–22) 18(14–22) 17(13.5–21) 17.5(13.5–20) 0.013 10(8–12) 10(8–12) 10(8–12) 10(8–12) 10(8–12) 0.651 53 CO-morbidity CVD without como CVD with como P-value 10(7–13) 10(8–13) 0.253 21(19–22) 21(18–22) 0.568 10(8–10) 9(5.75–10) 0.007 12(9–14) 10(8–14) 0.136 18(16–21) 16(12–20) 0.00 18(16–21) 16(12–20) 0.00 20(16–22) 18–14–22) 0.021 10)8–12) 10(8–12) 0.137 #Of medications 1–4 5–9 >10 P-value 10(8–13) 10(8–13) 10(9–20) 0.258 21(19–22) 21(18–22) 19(20–17) 0.163 9(6–10) 9(6–10) 5(5–12) 0.569 11(9–14) 10(8–14) 9(7–14) 0.128 18(13–20) 17(13–20) 13(9–26) 0.651 18(13–20) 17(13–20) 13(9–26) 0.651 19(15–22) 17(14–21) 15(11–20) 0.008 10(8–12) 10(7.75–12) 12(12–12) 0.006 Formulation used Tablet/capsule Tablet/Capsule with other formulations P-value 10(8–12) 10(8–15) 0.105 21(19–22) 21(18–23) 0.259 9(6–10) 9(5.75–9) 0.970 11(8–14) 11.5(8–14.25) 0.507 18(13–20) 16(13–22) 0.806 18(13–20) 16(13–22) 0.806 18(15–22) 18(14–22) 0.542 10(8–12) 11(8–12) 0.027 Medication Frequency Once daily Twice daily Three times daily More than 3 Times P-value 10(8–13) 10(8–13) 10(9–15) 8(6.5–12) 0.431 21(19–22) 21(18–22) 20(18–22) 20(17–22) 0.533 10(6–10) 9(6–10) 10(6–12) 6(3.5–10) 0.114 11(9–14) 11(8–14) 10(7–14) 8(7–9.5) 0.071 18(14–20) 17(12–20) 16(12–21) 13(10–17) 0.053 18(14–20) 17(12–20) 16(12–21) 13(10–17) 0.053 19(15–22) 18(15–22) 17(14–21) 15(12–18) 0.055 10(8–12) 10(8–12) 11(9–12) 13(7.5–14.5) 0.131 IQR interquartile Range, p-value<0.05 mean significant, Higher score indicating a greater burden 54 Table 3.9: Perceived medication-related burden measured using Living with Medicines Questionnaire version-3 (LMQ-3) and VAS (n=380). Variable Range Mean (SD) Median (IQR) Frequency (%) LMQ overall score No burden at all Minimum burden Moderate burden High burden Theme 1: Communication/relationships with healthcare professionals about medicines Theme 2: Practical difficulties Theme 3: Cost-related burden Theme 4: Side-effects burden Theme 5: Perceived effectiveness of medicines Theme 6: Attitudes/concerns about medicine use Theme 7:Impact/interferences with day-to-day life Theme 8: Control/autonomy of medicine use VAS: Global burden (41–205) (41–73) (74–106) (107–139) (140–172) (5–25) (7–35) (3–15) (4–20) (6–30) (7–35) (6–30) (3–15) (0–10) 108.2(16) 10.5(3.6) 20.3(3.5) 8.6(3) 11.1(3.4) 16.8(4.9) 16.9(5.4) 18.2(4.9) 9.9(2.6) 5.2(2.3) 108(19.8) 10(5) 21(3) 9(4) 14(6) 17.5(7) 17.5(7) 18(7) 10(4) 5.0(3) 7(1.8%) 149(39.2%) 217(57.1%) 7(1.8%) Table 3.9 presents the perceived medication-related burden (MRB) measured using LMQ-3 and VAS. The vast majority of the study populations are perceived to suffer from minimum to moderate degrees of burden. 55 Chapter Four Discussion 4.1 Discussion The present study appears to be the first in Palestine and probably in Jerusalem that measures the burden of using cardiovascular medications from the perspective of patients’ living by using the LMQ. The first study conducted using this questionnaire in the Arab world was in Qatar for diabetic patients (Zidan et al., 2018a). A second new study was carried out in Kuwait among geriatric patients (Awad et al., 2020). Another study in Palestine quantified the level of knowledge and medication adherence among Palestinian geriatrics with chronic diseases and looked at potential associations with socio-demographic factors (Najjar et al., 2015). Socio-demographic findings of the current study were relatively close to the results of a descriptive cross-sectional survey that was implemented on 450 hypertensive patients from government primary healthcare centres’ outpatient clinics and a group of private clinics and pharmacies in West Bank, Palestine, in 2011. The aim of that study was to evaluate the Palestinian hypertensive patients’ adherence to therapy and the influence of a variety of demographic and psychosocial factors on medication adherence (Al-Ramahi, 2015). In that study, the majority of patients were female (253(56.2%)) with an average age of 59.1(±12.2) years, living in the city, and had health insurance. Similar results were detected in the current study in which the female patients accounted for 195(51.3%), with an average 56 age ± SD of 58 ±12.2, most of them living in urban areas and with health insurance. The patients of the current study had some chronic diseases with a mean ± SD of 2.68 ± 1.17 and median (interquartile range) of 3 (2–3) illnesses with a maximum of 8 diseases. Similar findings were observed in a study that was done to evaluate the factors that influence coronary heart disease (CHD) patients’ quality of life (QoL) and to assess the patterns of cardiac self-efficacy (CSE) and quality of life (QoL) among CHD patients., in which 30% of the patient have two chronic diseases (Barham et al., 2019). Regarding CVDs, 259 (68.2%) of this study’ patients had hypertension, followed by 102 (26.8%) with ischaemic heart diseases, 64 (16.8%) with heart failure, and 12 (3.2%) with atrial fibrillation. Similar findings were observed in a research that was done to classify the incidence of medication therapy problems among hospitalized patients with cardiovascular disorders in Felege Hiwot Referral Hospital, where the most common CVDs encountered were hypertensive heart disease (32.9%), rheumatic heart disease (31.6%), functional heart failure, and cor pulmonale (18.4%) (Tegegne et al., 2014). On the other hand, regarding other co-morbid diseases, most of the patients in this present study suffered from diabetes mellitus (n=178, 46.8%), followed by dyslipidaemia (n=158, 41.6). A similar finding was observed in a study done to assess the prevalence, types and factors linked to the possibility of drug–drug interactions among patients with cardiovascular 57 disease, in which the most common co-morbid disease was diabetes mellitus affecting 205 (51.2%) patients, followed by chronic kidney disease in 56 (14%) patients (Aldabe et al., 2016). With regard to medications used, the number of medications used among patients ranged from 1–13, with a mean (±SD) of 4 ± 1.71 and median (interquartile range) of 4 (3–5). A similar finding was observed in the study investigating the factors that influence antihypertensive medication adherence in hypertensive patients, as well as the correlation between treatment satisfaction and adherence. As a result, 42% of patients took 6 or more drugs, with a median (interquartile range) of 6.8. (4.8–8.0) (Zyoud et al., 2013). In the current study, with regard to patients’ medications, aspirin (n=181, 47.6%), atorvastatin (n=134, 35.5%), metformin (n=104, 27.4%), and bisoprolol (n=90, 23.7%) were the most commonly used medications. Similar findings were observed in (Aldabe et al., 2016) study in which aspirin was the most frequently prescribed medication for cardiovascular patients. On the other hand, nearly all of the patients took an oral solid-dose formulation, with 314 (82.6%) using tablets or capsules, while 17.4% of patients used tablets or capsules with other formulations. In a previous study, similar results were reported whereby 325(76.7%) used tablets or capsules, while 99 (23.3%) used tablets or capsules with other formulations (Awad et al., 2020). 58 More than 50% of the patients in the current study reported using medicines once daily, and 34% reported using twice daily; while in the previous survey that was done on geriatric patients, 46.9% of patients used drugs three times, and in 31.6% the frequency of daily dose was twice daily (Awad et al., 2020). Since evaluating MRB using the LMQ-3 is still relatively recent, there are few studies with which to compare the present research. The current results are best compared to previous LMQ-3 studies conducted in Qatar, England, and Kuwait. We quantify MRB by using LMQ and VAS. According to our present research, the great majority (96.3%) of respondents self-reported suffering from a minimum (39.2%) to moderate (57.1%) degree of burden. Similar findings were observed in a previous study (Awad et al., 2020), in which the majority (97.4%) of geriatric participants self-reported suffering from a minimum (35.4%) to moderate (62.0%) degree of burden. Also, another study (Krska et al., 2019) found that most patients were suffering from a minimal (33.1%) to moderate (53.6%) degree of burden. On the other hand, the study by (Zidan et al., 2018b) in Qatar showed different findings, whereby the majority of the participants experienced minimal (66.8%) to moderate (24.1%) degrees of burden; this may be due to the differences among the study population. In the present study, the median (IQR) LMQ overall score was 108(19.8), which is a moderate burden. This is similar to (Awad et al., 2020) in Kuwait, in which the score was 112(21), and greater than the minimum 59 burden in the study conducted in Qatar (95%) (Zidan et al., 2018a) and in England (99.7%) (Krska et al., 2018). Furthermore, the present research indicates that the evaluation mean of the global burden by the VAS score was 5.2, which is similar to (Awad et al., 2020) that equals to 5; and higher than the score of 3 reported in Qatar (Zidan et al., 2018a). These variations may be related to the fact that both studies had a lower percentage of geriatric patients (Zidan et al., 2018b). In the Qatari study, 37 (12.6%) patients were geriatrics, and in the English study, 277 (41.9%) patients were geriatrics, compared with 175 (46%) geriatric patients in our study. Also, this may be related to cultural differences between countries. Demographic and medication-related characteristics affected scores among some domains in the questionnaire: female gender gave a higher score of burden related to relationships with healthcare providers. A similar finding was observed in a higher level of MRB among females (Zidan et al., 2018a, Sav et al., 2013, Sav et al., 2015), while disagreement with previous studies was seen in Kuwait (Awad et al., 2020), in which males had a higher level of burden and non-significant difference dependent on gender (Krska et al., 2018). Female respondents had significantly higher scores of a burden in communication/relationships with healthcare providers in terms of medications and perceived efficacy of medicines, which may be attributed to culture and feeling the burden of communication with healthcare professionals. 60 There was no significant correlation between patient age and LMQ domain score in this study; similar results were observed in Qatari and England research, which found that burden score was not strongly linked to age (Katusiime et al., 2018, Zidan et al., 2018a), in contrast to the study by (Awad et al., 2020) where there was a significant association among patients >75 years in which scores of burden were higher than for those aged less than 75. The current results showed that patients resident in the urban region had a higher level of burden than those living in