THE RELATIONSHIP OF PERCEIVED BASIC PSYCHOLOGICAL NEEDS FOR
HEALTH BEHAVIORS AND MEDICATION ADHERENCE IN SAUDI ARABIAN
PATIENTS WITH CORONARY ARTERY DISEASE
A Dissertation
Presented to
The Graduate Faculty of The University of Akron
In Partial Fulfillment
of the Requirements for the Degree
Doctor of Philosophy
Abdulaziz Almarwani
December 2019
THE RELATIONSHIP OF PERCEIVED BASIC PSYCHOLOGICAL NEEDS FOR
HEALTH BEHAVIORS AND MEDICATION ADHERENCE IN SAUDI ARABIAN
PATIENTS WITH CORONARY ARTERY DISEASE.
Abdulaziz Almarwani
Dissertation
Approved: Accepted:
______Advisor Department Chair Dr. Linda Shanks Dr. Marlene Huff
______Committee Member Interim Dean of the College Dr. Sheau-Huey Chiu Dr. Elizabeth A. Kennedy
______Committee Member Dean of the Graduate School Dr. Marlene Huff Dr. Marnie Saunders
______Committee Member Date Dr. Patricia Vermeersch
______Committee Member Judith A. Juvancic-Heltzel
ii
ABSTRACT
Coronary Artery Disease (CAD) is one of the major causes of morbidity and mortality in Saudi Arabia. Health behaviors contributing to CAD are inactivity, diet, smoking, and medication nonadherence. In Saudi Arabia, these health behaviors were not examined through the lens of the self-determination theory, which emphasizes on patients' perceived psychological needs (PPN) (autonomy, competence, and relatedness).
Therefore, this study aimed to explore the levels of PPN for health behaviors and medication adherence as well as assess the relationships among these needs and medication adherence.
A cross-sectional descriptive exploratory correlational design was conducted on
121 CAD patients at Madinah Cardiac Center. The majority of study participants were men with an average age of 58 years. The levels of perceived autonomy in physical activity (PA-PA), diet (PA-Diet), and smoking (PA-Smoking), were relatively high with the means ranging from 5.6 to 6.4 out of 7. The level of perceived competence in not smoking (PC-Smoking) was higher (� = 5.8) than both perceived competence in physical activity (PC-PA) (� = 3.9) and perceived competence in diet (PC-Diet) (�= 4.3). Level of perceived relatedness in physical activity was medium with a mean of 4.2. Nearly half of the study participants reported high medication adherence, while 52.9% reported medium medication and low medication adherence. The result of Spearman’s rho and Pearson’s r test showed weak positive correlations between medication adherence and PA-PA, PA- diet, PC-PA, and PC-Diet. Perceived autonomy and perceived competence in health
iii behaviors did not explain the variance in the medication adherence using multiple regression. All translated study instruments were reliable with Cronbach’s alpha of 0.86 or higher except for the MGL (4 items), where Cronbach’s alpha was 0.58.
This study is the first study to provide information about the levels of PPN as well as the level of medication adherence among Saudi patients with CAD. Despite the limitations, the results of this study provide a starting point for Saudi healthcare policymakers to learn about the relationship among PPN in health behaviors. This study may also serve as the basis for future researchers to study other populations with chronic illnesses.
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ACKNOWLEDGEMENTS
There are many people who deserve to be thanked for their support throughout my educational journey. I would like to thank my dissertation advisors Dr. Linda Shanks and Dr. Sheau-Huey Chiu for their immense amount of support and direction throughout the entire process of writing this dissertation. Without their guidance and support, this would not have been possible, and I would not be where I am today. I would also like to express my appreciation to my committee members. Dr. Marlene Huff, Dr. Patricia
Vermeersch, and Dr. Judith A. Juvancic-Heltzel for their guidance and support. Also, I would like to thank the nursing faculty at The University of Akron and Kent State
University for the valuable education I have received.
I would like to thank the Saudi Arabian Cultural Mission (SACM) in Washington
D.C and Taibah University for the support and guidance they provided to me during this governmental scholarship.
I would like to thank the research department at the Madinah Cardiac Center
(MCC) for their immense amount of support and direction throughout the process of data collection. I would like to thank the research office coordinator Ms. Aisha Alharbai and the head of nursing education Ms. Amira Ibrahim for their support. I would also like to thank the nursing research assistant Mr. Fahad Mousa Almarwani for his assistance during the data collection phase
A special thanks to my family, my mother Fatemah Al Johani who has been always encouraging me toward the best, my father Mofdy Almarwani, and my wife Dr.
v
Bayan Almarwani for their endless support and continuous encouragement to strive towards my goal of becoming a successful person.
My appreciation also extends to Dr. Gibran Mancus who has been a true brother to me in the USA. Finally, I would like to thank all my friends, colleagues and people who helped me throughout my academic and personal life.
ءاﺪھا( ﻰـــﻟا يﺪــﻟاو ﻲﻟﺎﻐﻟا وو ا ﻟ ـ ﺪ ﻲﺗ ﺔﯿﻟﺎــﻐﻟا ﺟوزو ﺘ ـ ﻲـ ﺔﯿﻟﺎــﻐﻟا او ﻔط ﺎ ﻲﻟ ﻟ ﻦﯿ ﻓو ﻞﺼﯿ ﯿﻟﺎــﻐﻟا ﻦ)
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DEDICATION
I'd like to dedicate this work to King Abdullah bin Abdulaziz Al Saud.
يﺪھأ اﺬھ ا ﻌﻟ ﻞﻤ ا ﻰﻟ ﻚﻠﻤﻠﻟ ﺪﺒﻋ ﷲ ﻦﺑ ﺪﺒﻋ ﺰﯾﺰﻌﻟا لآ ﻮﻌﺳ د “ ﻤﺣر ﮫ "ﷲ ﮫ ﻤﺣر
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TABLE OF CONTENTS
Page
LIST OF FIGURES ...... xiv
LIST OF TABLES ...... xv
CHAPTER
I. INTRODUCTION ...... 1
Background ...... 1
Cardiovascular Disease ...... 1
Coronary artery Disease ...... 2
Coronary Artery Disease in Saudi Arabia ...... 3
Health Behaviors Contributing to Coronary Artery Disease ...... 4
Medication Adherence ...... 5
Health Behaviors and Medication Adherence ...... 7
Self-Determination Theory ...... 10
Application of Self-determination Theory to Study ...... 12
Significance to Nursing ...... 15
Summary ...... 16
Research Purpose ...... 17
Research Questions ...... 18
II. LITERATURE REVIEW ...... 19
viii
Cardiovascular Diseases ...... 19
Worldwide Cardiovascular Disease ...... 19
Cardiovascular Disease in the United States ...... 20
Coronary Artery Disease in the United States ...... 20
Cardiovascular Disease in Saudi Arabia ...... 21
Coronary Artery Disease in Saudi Arabia ...... 22
Health Behaviors Contributing to Cardiovascular Disease ...... 23
Health Behaviors Contributing to Coronary Artery Disease ...... 25
Health Behaviors and Coronary Artery Disease ...... 26
Coronary Artery Disease and Physical Inactivity ...... 26
Coronary Artery Disease and Diet/Obesity ...... 27
Coronary Artery Disease and Smoking ...... 29
Medication Adherence ...... 30
Health Behaviors and Medication Adherence ...... 31
Physical Activity and Medication Adherence ...... 32
Diet and Medication Adherence ...... 33
Smoking and Medication Adherence ...... 34
Physical Activity, Diet, Smoking and Medication Adherence ...... 35
Self Determination Theory ...... 36
Basic Psychological Needs and Behaviors Contributing to Coronary Artery ...... 38
ix
Gaps ...... 40
Conclusion ...... 41
III. RESEARCH DESIGN AND METHODS ...... 43
Research Design ...... 44
Research Setting ...... 44
Sampling ...... 44
Determination of Sample Size ...... 45
Inclusion and Exclusion Criteria ...... 46
Selections of Study Participants ...... 47
Data Collection Procedure ...... 48
Electronic Tablet-Based Data Collection ...... 49
Data Collection Instruments ...... 50
Treatment Self-Regulation Questionnaire (TSRQ) ...... 51
Perceived Competence Scale (PCS) ...... 53
Relatedness to Others in Physical Activity Scale (ROPAS) ...... 54
Four Item MGL Medication Adherence Scale (MGL) ...... 54
Instrument Translation Process ...... 55
Protection of Human Subjects ...... 56
Maintaining Confidentiality and Anonymity ...... 57
Rights and Privacy ...... 57
Summary ...... 57
IV. RESULTS ...... 59
Data Management ...... 60
x
Data Entry ...... 60
Data Screening ...... 60
Characteristics of Study Sample ...... 60
Demographic Data ...... 60
iPads Vs Paper Demographic Characteristics ...... 62
Reliability of Study Instruments ...... 64
Reliability of iPad Vs Paper Surveys ...... 65
Analysis of the Research Questions ...... 66
Research Question 1 ...... 66
Research Question 2 ...... 67
Research Question 3 ...... 67
Research Question 4 ...... 68
Research Question 5 ...... 69
Research Hypotheses ...... 69
Statistical Assumptions ...... 69
Normality ...... 70
Linearity ...... 71
Homoscedasticity ...... 72
The Correlation Between Study Variables ...... 72
Pearson’s r Correlation ...... 72
Spearman’s rho Correlation ...... 73
Research Question 6 ...... 74
Statistical Assumptions ...... 74
xi
Multicollinearity ...... 75
Independent Errors ...... 75
Multiple Linear Regression Analysis ...... 76
Multiple Regression Result of the Original Variables and the MGL (4 Items) ...... 76
Multiple Regression Result of the Original Variables and the MGL (3 Items) ...... 77
Multiple Regression Result for the Transformed Variables and the MGL (4 Items) ...... 78
Multiple Regression Result for the Transformed Variables and the MGL (3 Items) 79
Summary ...... 80
V DISSCUSSION ...... 82
Review and Discussion of Findings ...... 82
Demographics ...... 82
Levels of Perceived Psychological Needs for Health Behaviors ...... 84
Levels of Perceived Autonomy in Health Behaviors ...... 85
Level of Perceived Competence in Health Behaviors ...... 88
Level of Perceived Relatedness in Physical Activity ...... 92
The Relationships Among the PPN For Health Behaviors ...... 94
The Relationships Among Independent Variables ...... 94
The Relationship Between the Independent Variables (PPN In Health Behaviors) and Dependent Variable (Medication Adherence) ...... 98
The Level of Medication Adherence ...... 101
Strengths of The Study ...... 104
Study Limitations ...... 105
xii
Implication for Future Research ...... 107
Conclusion ...... 109
REFERENCES ...... 111
APPENDICES ...... 142
APPENDIX A: IRB APPROVAL FROM THE UNIVERSITY OF AKRON ..143
APPENDIX B: IRB APPROVAL FROM MADINAH CARDIAC CENTER (MCC) ...... 144
APPENDIX C: SCRIPT FOR RECRUITMENT ...... 145
APPENDIX D: OPEN LETTER TO STUDY PARTICIPANTS ...... 147
APPENDIX E: INFORMED CONSENT ...... 149
APPENDIX F: ARABIC STUDY SURVEY ...... 152
APPENDIX G: DEMOGRAPHIC DATA ...... 159
APPENDIX H: TREATMENT SELF-REGULATION QUESTIONNAIRE (TSRQ) ...... 160
APPENDIX I: PERCEIVED COMPETENCE SCALE ...... 162
APPENDIX J: RELATEDNESS TO OTHERS IN PHYSICAL ACTIVITY SCALE ...... 164
APPENDIX K: FOUR ITEM MGL MEDICATION ADHERENCE SCALE ..165
xiii
LIST OF FIGURES
Figure Page
1. Study Model ...... 15
2. Selections of Study Participants ...... 47
xiv
LIST OF TABLES
Table Page
Table 1. Study Variables ...... 13
Table 2. Multiple Regression Power Analysis ...... 45
Table 3. Data Collection Instruments ...... 51
Table 4. Demographic Characteristics ...... 61
Table 5. Demographic Characteristics of Survey Types ...... 63
Table 6. Reliability Test Table ...... 65
Table 7. Reliability Test of iPad And Paper Surveys ...... 66
Table 8. Level of Medication Adherence ...... 69
Table 9.1. Z-Score of Skewness and Kurtosis (Non-Transformed Variables) ...... 70
Table 9.2. Z-Score of Skewness and Kurtosis (Transformed Variables) ...... 71
Table 10.1. Pearson R Correlations ...... 73
Table 10.2. Spearman's Rho Correlation ...... 74
Table 11. Predictors of Medication Adherence ...... 76
Table 12 Predictors of Medication Adherence ...... 77
Table 13 Predictors of Medication Adherence ...... 78
Table 14 Predictors of Medication Adherence ...... 79
xv
CHAPTER I
INTRODUCTION
Coronary artery disease (CAD) is a serious disease that contributes to increasing rates of worldwide mortality and morbidity (Kovel et al., 2016). This study aims to understand health behaviors/medication adherence from the perspective of the psychological needs of self-determination theory (SDT) in CAD patients in Saudi Arabia.
Specifically, this study will explore perceived psychological needs (autonomy, competence, and relatedness) for health behaviors and their relationships to medication adherence in Saudi patients with CAD. The background, SDT, and significance of the study will be discussed in the following sections.
Background
Cardiovascular Disease
Cardiovascular disease (CVD) is a serious life-threatening disease with high morbidity and mortality rates worldwide (Tolmie et al., 2009). Cardiovascular disease is a term used to identify many heart problems, including hypertension (HTN), CAD, arrhythmia, congenital heart disease, and heart failure (WHO, 2017d). According to the World Health
Organization (WHO), in 2016 worldwide death due to CVD was 17.9 million (WHO,
2017a). Saudi Arabia is one of the largest countries in the Middle East, with a population of more than 32 million individuals (General Authority of Statistics, 2017). With the country’s socioeconomic growth, several lifestyle changes have occurred, “such as an increased consumption of poor-quality foods and the adoption of a sedentary lifestyle”
1
(Aljefree & Ahmed, 2015, p. 1). All these changes have resulted in an increase in the rates of CVD and its associated risk factors among Gulf countries, including Saudi
Arabia (Aljefree & Ahmed, 2015)
The WHO in 2002 reported that the mortality rate of CVD in Saudi Arabia was
35%, which increased to 46% in 2014 (WHO, 2014) and 37% in 2016 (WHO, 2018a).
The most recent annual health statistics report released by the Saudi Ministry of Health
(MOH) in 2016 showed an increase in visits to health centers and outpatient clinics in
MOH hospitals took place due to CVD. The rates of death due to CVD in Saudi Arabia at times exceed those of developed countries, such as Australia, where 30% of reported deaths in 2016 were due to CVD (“Heart disease in Australia,” n.d.). Still, the above
CVD statistics highlight the need to conduct research studies to examine, evaluate, and contribute to improving patient’s holistic health status, as well as reduce and minimize
CVD risk factors in this country.
Coronary Artery Disease
Coronary artery disease (CAD) is a partial or complete blockage of the coronary arteries that provide oxygen and nutrients to the heart muscle (Mayo Clinic, 2018).
Coronary artery disease is one of the most common cardiovascular diseases worldwide
(Benjamin et al., 2017). The American Heart Association (AHA) reported one in seven deaths in the United States (U.S.) results from CAD, which kills more than 360,000 people each year (Benjamin et al., 2017). “The estimated annual incidence rate of heart attacks in the U.S. is 580,000 new attacks and 210,000 recurrent attacks” (Benjamin et al., 2017, p. 2).
2
The AHA also reported that between 2004 and 2014, the annual death rate caused by
CAD decreased to 35.5 %; however, healthcare expenses and health risk factors are still high
(Benjamin et al., 2017). Between 2012 and 2013, the U.S government estimated the cost of heart disease treatment, which was $199.6 billion. According the AHA, the treatment of heart attacks cost around $11.5 and 10.4 billion for the treatment of CAD (Benjamin et al., 2017).
In the U.S. both heart attacks and CAD “ranked among the ten most expensive hospital principal discharge diagnoses” (Benjamin et al., 2017, p. 2). Finally, the AHA suggested that between 2013 and 2030, treatment costs of CAD would increase by approximately 100% in the United States (Benjamin et al., 2017).
Coronary Artery Disease in Saudi Arabia
In the past two decades, CAD has grown as a common health issue in Saudi
Arabia, and it is currently the third most common cause of mortality and adult
hospitalization, after road traffic accidents and senility in Saudi Arabia (Taha, Nabil, &
Iyer, 2011). The first national statistic about CAD in Saudi Arabia was published in 2004.
At that time the prevalence of CAD among Saudis was 5.5% (approximately 858,000
patients), with higher rates for men and in urban areas (Al-Nozha et al., 2004). In 2005,
Myocardial Infarction (MI), which is a type of CAD, “was one of the leading causes of
death (30.9%) among CVD patients in Saudi Arabia” (Osman, Alsultan, & Al-Mutairi,
2011, p.1280). The data from the WHO in 2008 ranked Saudi Arabia 13th in mortalities
caused by CAD (20,900) (Finegold, Asaria, & Francis, 2013). In 2017, deaths attributed
to CAD remain high. According to the World Health Rankings, in 2017, death due to
CAD reached 23,624 (24.25%) of total deaths in Saudi Arabia (World Health Rankings,
3
2017). Saquib, Zaghloul, Mazrou and Saquib (2017) reported that the most common type of CVD in Saudi Arabia is CAD (18%).
These death statistics are considered high by Saudi officials when compared to those of other countries in the region such as Oman (22%), Yemen (21%), and Jordan
(19%) (World Health Rankings, 2017). Thus, these numbers highlight the great need for researchers to study patients diagnosed with CAD in Saudi Arabia to establish effective plans to reduce CAD mortalities and risk factors. This study will therefore focus on patients with CAD in Saudi Arabia, because it is the most prevalent diagnosis among
CVD patients in Saudi Arabia (Ahmed et al., 2017; Al-Nozha et al., 2004; Al-Qahtani,
Taha, Aljoudi, & Bahnassy, 2014; Saquib et al., 2017; Taha et al., 2011).
Health Behaviors Contributing to Coronary Artery Disease
Many health behavior factors for CAD have been identified in the literature
(Ahmed et al., 2017; Aljefree & Ahmed, 2015; Al-Qahtani et al., 2014; Capewell et al.,
2010; Saad & Latif, 2017). The WHO defines health behavior risk factors as “any attribute, characteristic, or exposure of an individual that might increase the likelihood of developing a disease or injury” (WHO, 2017c, p. 1). The WHO listed examples of these behavioral factors associated with CAD, including poor diet, obesity, tobacco use, extensive use of alcohol, and physical inactivity (Capewell et al., 2010; Ministry of
Health, 2017; Ram & Trivedi, 2012; WHO, 2017d). These same health behaviors have also been identified as contributing factors in increasing incidences of CAD in Saudi
Arabia and the Gulf countries (Aljefree & Ahmed, 2015; Ministry of Health, 2017;
Nohair et al., 2017).
4
According to the Saudi Project for Assessment of Coronary Events (SPACE), one pilot study carried out at eight hospitals in Saudi Arabia found that acute coronary syndrome (ACS), which includes unstable angina, non-ST-elevation MI, ST-elevation MI and sudden cardiac death, occurred more frequently in men (77%) than in women (23%) among the Saudi population (Al-Habib et al., 2009), Other related health issues included
“diabetes (56%), HTN (48%), being a current smoker (39%), ischemic heart disease
(32%), and hyperlipidemia (31%)” (Al-Habib et al., 2009, p. 255). Moreover, high prevalence of obesity was observed among patients diagnosed with ACS (72%)
(Mobeirek et al., 2014). The level of physical activity among Saudi females is considered to be low (72.9 % not active) compared to other nations (Al-Zalaban, Al-Hamdan, &
Saeed, 2015). Similarly, the majority of Saudi males (66.6%) were also found to be not physically active (Al-Zalaban et al., 2015).
In Saudi Arabia, in addition to these health behavioral factors, poor medication adherence was found to be associated with CAD complications. Research suggests that medication adherence is low among the Saudi population with heart disease (Altuwairqi,
2016; Patel, Shetty, & Rasras, 2015; Shaik et al., 2016). The cause of poor medication adherence is not clearly understood, which increases the need for research on this issue that affects mortality, morbidity, and increased the cost of health care services
(Altuwairqi, 2016).
Medication Adherence
Treatment of chronic diseases such as CAD requires a high level of self- management such as taking medication, changing dietary habits, and improving physical activity. Medication adherence is one of the most important factors in improving patients’
5 health (Lourenço et al., 2014; Patel et al., 2015). In order for medication to be effective for patients’ treatment, patients must adhere to their prescribed medications (Lourenço et al., 2014). Medication adherence is the degree to which patients follow the instructions given by their healthcare provider about their prescribed medication (Lourenço et al.,
2014). Poor adherence is defined as “taking less than 80% of prescribed doses and can also include taking too many doses” (Al-Ganmi, Perry, Gholizadeh & Alotaibi 2016, p.
3002). Non-adherence has been linked to decreased patient’s health and increased rates of hospitalization as well as an increased healthcare costs and increased mortality rates
(Lourenço et al., 2014; Patel et al., 2015; Polonsky & Henry, 2016).
Saudi patients with CAD are at high risk of recurrent CAD events due to poor health behaviors and the absence of proper health education (Al Shammeri et al., 2014).
One study aimed to estimate the rate of achieving optimal medical therapy (OMT), which was defined as adherence to medication therapy (antiplatelet therapy, statins, beta blockers, and angiotensin-converting enzyme inhibitors), maintenance of physical activities (daily exercise for 30 minutes), and minimization of tobacco consumption, in
CAD patients in Saudi Arabia (Al Shammeri et al., 2014). The results of this study found that only 10.4% of CAD participants (n = 207) achieved the desired OMT. The researchers concluded that OMT was poorly achieved in CAD patients in the Saudi population, which would increase patients’ re-hospitalization and mortality rates (Al
Shammeri et al., 2014).
It is important to provide patients appropriate information regarding their medication to encourage adherence and in order to achieve better treatment goals (Patel et al., 2015). For example, the chance of having second MI is high after a first MI
6 especially if patients are not adhering to their medical plans (Thune et al., 2011;
Lourenço et al., 2014). The most common prescribed medications for patients with CAD are “antiplatelet agents, beta-blockers, angiotensin-converting enzyme inhibitors, and lipid-lowering therapy” (Sanal, & Aronow, 2003, p. 1046). The use of these medications is recommended to prevent a secondary CAD attack (Al Shammeri et al., 2014; Fleg et al., 2013; Thune et al., 2011).
As previously stated, however, medication adherence is low among the Saudi population (Altuwairqi, 2016; Patel et al., 2015; Shaik et al., 2016). In the past decade, the number of studies on medication adherence has increased in Saudi Arabia, and many studies have aimed to identify the level of medication adherence among people with chronic conditions, such as heart disease (Altuwairqi, 2016; Khayyat et al., 2017; Shaik et al., 2016; Patel et al., 2015). For example, Shaik et al. (2016) conducted a cross- sectional study with 282 hypertensive patients to identify the level of medication adherence, as well as to understand the factors associated with poor adherence among these patients at King Khalid University Hospital in Riyadh, Saudi Arabia. The researchers found that more than half of patients (55%) had low adherence to their medications. Age, income, and health perception comprised the three factors most associated with poor adherence. These factors could be used to identity patients for counseling and education sessions to improve medication adherence (Shaik et al., 2016).
Health Behaviors and Medication Adherence
Improving health behaviors is linked to positive health outcomes, which leads to increased disease control (WHO, 2017d). The relationships between health behaviors and medication adherence are very important in achieving satisfactory treatment outcomes
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(Han et al., 2017). There have been studies that examined the relationships between health behaviors and medication adherence. The most recent study that examined the relationship between health behaviors and medication adherence is a study conducted by
Lee et al. (2018). The study found significant association between health behaviors
(physical activity, diet, smoking) and medication adherence among patients with CAD.
Patients who showed unhealthy lifestyles were more likely to have poor medication adherence, which raised the risk of cardiovascular complications. Moreover, most patients with CAD experienced difficulties in lifestyle modification and medication adherence. Recent research in Jordan found that most patients with CAD did not follow healthy behaviors, such as physical activity, healthy diet, smoking cessation, and medication adherence, to reduce disease risk factors, which put them at a higher risk of hospital readmission (Mosleh & Darawad, 2015). The results indicated when patients have poor health behaviors they are more likely to have poor medication adherence
(Mosleh & Darawad, 2015).
In comparison, Han et al. (2017) conducted a study to examine the relationships between several health behaviors and medication adherence in patients diagnosed with hypertension, hyperlipidemia, and diabetes. Their results found that patients who reported following mild physical activity showed better medication adherence; patients who were not obese and were controlling their diet showed better medication adherence; and patients who were smokers had low medication adherence (Han et al., 2017). These positive health behaviors are possible predictors of improved medical adherence, which in turn is associated with improved health outcomes (Han et al., 2017).
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Similarly, Hempler et al. (2012) conducted a study to examine the relationship between long-term changes in dietary habits and physical activity behaviors and the initiation of preventive medications among patients with CAD. The study focused on smoking, diet, physical activity and alcohol consumption and data were collected in one, three and five years (Hempler et al., 2012). After five years, the result of the study found that when patients have positive changes in both physical activity and dietary habits over extended periods of time they were more likely to initiate lipid-lowering medications and blood pressure-lowering medications (Hempler et al., 2012). The study concluded that patients who were able to change their health behaviors also were more likely to take their medication, “rather than substituting them with behavioral changes” (Hempler et al.,
2012, p. 2).
The finding that patients who practice healthy self-care behaviors were more likely to show better medication adherence are consistent throughout the current body of literature. Other studies were conducted using different chronic disease populations, such as patients with MI, HIV, Hepatitis C, and their findings support the relationship between positive health behaviors and improved medication adherence (Batool & Kausar, 2015;
Lee et al., 2018; Pellowski & Kalichman, 2016). Given that these relationships are consistent across populations with chronic diseases, it is important to also conduct research studies specifically on patients with CAD that focus on patients’ physical activity, diet, smoking cessation, and their relation to medication adherence as a way to ascertain whether CAD management shares these relationships or if there are others important to treating and managing CAD. The management and treatment of CAD in particular requires the modification of health behaviors such as physical activity, healthy
9 diet, and smoking, as well as excellent medication adherence (Capewell et al., 2010;
Ministry of Health, 2017; WHO, 2017d).
Self Determination Theory
Self-Determination Theory (SDT) is a middle-range theory that guides this study.
Self-Determination Theory was originally developed by Deci and Ryan in the early
1970s, and it was introduced as a theory in the mid-1980s (Deci & Ryan, 2008). Self-
Determination Theory has been “elaborated on and refined by scholars from many countries” (Deci, 2011, p. 1). Also, this theory has been used in several fields, such as health care sciences and education (Deci & Ryan, 2008). “This theory is a human motivation theory, which means that it emphasizes the extent to which behaviors are relatively autonomous versus relatively controlled” (Patrick & Williams, 2012, p. 2).
According to SDT, when human basic psychological needs (autonomy, competence, and relatedness) are satisfied, they will be more likely to follow healthy lifestyles and change unhealthy behaviors (Williams et al., 2009). According to Patrick and Williams (2012), these psychological needs are important in the process of formulating human motivation toward healthy behaviors.
The concepts of SDT are autonomy, competence, and relatedness. The theory defines autonomy as an individual’s volition to regulate their behaviors based on their own values, choices, and interests (Anja, Maarten, Hans, Bart, & Willy, 2010; Patrick &
Williams, 2012). Patients feel autonomy when they regulate their health behavior voluntarily and without external pressure (Williams et al., 2009). Whereas, patients feel controlled when they experience external pressure to change and regulate their health behavior (Williams et al., 2009). According to SDT, controlled regulation is largely
10 unrelated to long-term adherence, whereas autonomy is highly related to long-term adherence (Ryan, Patrick, Deci, & Williams, 2008; Williams, Rodin, Ryan, Grolnick, &
Deci, 1998).
The theory defines competence as patients’ need to feel competent and confident in their ability to improve their skills and knowledge to make a health change and to reach their goals (Anja et al., 2010; Patrick & Williams, 2012). Being competent means having an appropriate or substantial amount of skills and knowledge to perform a task
(Anja et al., 2010; Williams et al., 2009). Competence is related to individual autonomy because autonomy “requires a person’s experience and competence to change” (Ryan et al., 2008, p. 3). Patients feel competent when they consider themselves capable to achieve their health goals such as adhering to their medication (Williams et al., 2009).
The theory defines relatedness as the status of connection between patients and others and to individuals feeling understood and cared for and the feeling of belonging to a group of people who are invested in one’s wellbeing, (Anja et al., 2010; Ryan et al.,
2008; Patrick & Williams, 2012). Relatedness is essential for motivating and supporting individuals’ autonomy, because it improves the internalization of extrinsic causes (Deci
& Ryan, 2012; Deci & Ryan, 2008). For example, patients can voluntarily engage in behavioral change, such as adhering to their medication for the sake of others who mean a lot to them, such as a spouse, friends, or other patients (Deci & Ryan, 2008; Patrick &
Williams, 2012). Relatedness support could include “providing unconditional regard, being empathetic with patient concerns, and providing a consistently warm interpersonal environment” (Patrick & Williams, 2012, p. 12). Because of this, healthcare providers might support patients’ need for relatedness by expressing understanding of patients
11 concerns. This requires, however, that healthcare providers become actively engaged with their patients (Patrick & Williams, 2012). Relatedness is important because it provides individuals’ support to individuals, and individuals’ support has been shown to improve health behaviors in various domains of health, such as patients with cancer or other chronic illnesses (Patrick & Williams, 2012).
Application of Self Determination Theory to Study
Self Determination Theory is highly important to health care practice, because of the central concept of autonomy that has been “deeply explored using empirical methods”
(Deci & Ryan, 2012, p. 5). This theory is unique when compared to other theories such as self-efficacy theory or the theory of planned behavior because it contains empirical indicators that can measure autonomy in the health domain (Ng et al., 2012). Several researchers have used this theory to examine and explore the relationships between the contextual and individual-level factors related to SDT, including whether participants perceive their healthcare providers as supportive, if participants psychological needs are satisfied, and how participants think about the causes of their physical health status
(Patrick & Williams, 2012; Ryan & Deci, 2000; Ryan & Deci, 2017).
According to Ryan and Deci (2000), when patients perceive themselves as being autonomous, are competent, and have a positive sense of relatedness, they are more likely to have positive health behaviors, such as physical activity, dietary habits, and smoking cessation. Hence, this theory will be used to explore the relationships among CAD patients’ perceived psychological needs (autonomy, competence, and relatedness) for health behaviors and medication adherence in Saudi patients with CAD (Table 1).
Improved patient psychological needs are expected to lead to better disease control,
12 which could eventually lead to better health outcomes, reduce patients’ utilization of health care services, and, ultimately, reduce health care costs (Meng et al., 2013; Ryan &
Deci, 2017; Yukawa et al., 2010).
The relationships between the autonomy, competence, and relatedness are important. Results of other studies that used SDT revealed that patients who are autonomous are also highly competent in achieving positive health outcomes (Coa &
Patrick, 2016; McSpadden et al., 2016; Williams et al., 2009). Furthermore, patients who receive support from their surroundings and perceived to have excellent relationships with them are also more likely to change and improve their health behaviors (Williams et al., 2009). When psychological needs are satisfied, patients will have better health outcomes (Ryan & Deci, 2017). Seeing this, and because no information exists about
CAD Saudi patients’ psychological needs, this study will explore the variables of autonomy, competence, and relatedness, in health behaviors as well as their relation to patient’s medication adherence.
Conceptual, Operational, and Empirical definition
Table 1 Study Variables
Variable name Conceptual definition Operational / Empirical definitions Perceived Individual’s volition in regulating Degree of patients’ perceived Autonomy in one’s own health behaviors. autonomy in performing Health Behaviors (Anja et al., 2010;Patrick & physical activity, improving Williams 2012) diet, and quitting smoking (Williams, Ryan, & Deci, n.d). Treatment Self-Regulation Questionnaire (TSRQ) (Williams et al., n.d).
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Perceived Feeling confident in their ability Degree of patients perceived Competence in to improve their skills and confidence in performing Health Behaviors knowledge to make a health physical activity, improving change and to reach their goals diet, and quitting smoking (Anja et al., 2010; Patrick & (Williams et al., n.d). Williams, 2012). Perceived Competence Scales (PCS) (Williams et al., n.d).
Perceived “Feeling understood and cared Degree of patients perceived Relatedness in for by others” (Ng et al., 2012, p. connection and support by Physical Activity 326). Also, relatedness refers to their surroundings toward the “practitioner-patient their physical activity. relationship” and feeling of Relatedness to Others in support (Ryan et al., 2008, p 3). Physical Activity Scale (ROPAS) (Wilson, & Bengoechea, 2010)
Self-Reported The extent to which patients Degrees to which the patient’s Medication follow the instructions they are follow instructions in taking Adherence given for prescribed medication his/her medication. (Lourenço et al., 2014). Four item Morisky, Green, & Levine MGL (4 items) medication adherence scale (Morisky, Green, & Levine, 1986).
By exploring and identifying the relationship between CAD patients’ perceived autonomy, competence, and relatedness and medication adherence in Saudi population, researchers will have better understanding of the status of patients’ psychological needs.
This study will be the first step to provide information about the status of the relationship among the psychological needs and patients’ medication adherence (Figure 1). The results of this study will serve as basis for building educational programs based on SDT for patients with CAD in Saudi Arabia. According to Deci and Ryan (2012), it is important to conduct studies that focus on patients’ perceived health-behavior change, because they might provide “support for an SDT approach to patient care and establish
14 the groundwork for more refined studies, such as ones addressing specific social- contextual factors that promote and maintain health-behavior changes and improve health” (p. 1).
Figure 1. Study model. Adapted from “Facilitating health behaviour change and its maintenance: Interventions based on Self-Determination Theory,” by R. M Ryan, H. Patrick, E. L., Williams, 2008, The European Health Psychologist ,10, 2-5 p. 4.
Significance to Nursing
Nurses are a major part of healthcare systems, and they play an integral role in prompting the quality of healthcare. Nursing research has an important role in influencing the current and future professional of nursing practice (Tingen, Burnett, Murchison, &
15
Zhu, 2009). Understanding patients’ needs is important for nurses in order to help enhance and improve healthcare services provided to patients. This study is significant for its contribution to nursing practice, theory, and patients’ health. This study will investigate the status of patients perceived psychological needs (autonomy, competence, and relatedness) for health behavior based on SDT and its relation to medication adherence in a population that has never been examined before through this theoretical lens. Applying theories into nursing research is important to provide reliable theoretical frameworks that help to produce valid research results (Tingen et al., 2009).
Nursing science aims to generate knowledge and to explain how that knowledge can be used in practice, education, and research. This study contributes to this field by providing new knowledge to the nursing domain, as well as to other healthcare domains, that will help guide the future of nursing practice toward improving patients’ health.
Information about patients perceived psychological needs might be used to build future nursing interventions. These interventions will seek to improve patients perceived psychological needs, as well as increasing medication adherence in a population that showed low medication adherence.
Summary
Cardiovascular disease is a major cause of death in the world. The percentage of deaths due to CVD in Saudi Arabia increased from 35% in 2002 to 46% in 2014; however, the percentage decreased to 37% in 2016 (WHO, 2018a). But still these numbers are considered high when compared to other countries in the region. One of the most common types of CVD is coronary artery disease (CAD). In Saudi Arabia, the prevalence of CAD ranged from 5.5% in 2002, 30.9% in 2005, and 24.25% in 2017.
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Multiple studies suggest that CAD is a serious, life-threatening disease in Saudi Arabia
(Al-Nozha et al., 2004; Finegold, Asaria, & Francis, 2013; Saquib et al., 2017).
Many behavioral health factors have contributed to an increase the number of incidences of CAD in Saudi Arabia. The WHO as well as the Saudi Ministry of Health listed poor diet, obesity, tobacco use, and physical inactivity as the most negative health behavior factors leading to CAD in Saudi Arabia. In addition to these factors, poor medication adherence was evident in several studies in Saudi Arabia. This raises questions about the role of patients’ psychological needs to modify unhealthy behaviors and follow healthy ones.
Previous research explored risk factors of CAD in Saudi Arabia, but addressing the perceived psychological needs, as a way to reduce and minimize negative health behaviors in the CAD population has not been explored. Furthermore, there is no evidence of exploring the relationships among patient’s perceived psychological needs in the context of SDT in Saudi Arabia. Resultantly, this study will be beneficial to nursing practice as well as other healthcare sectors since it will provide information about the status of Saudi Arabia CAD patients’ autonomy, competence, and relatedness in health behaviors as well as their relationships to medication adherence.
This study served two main purposes. First, the study sets out to explore the levels of the perceived psychological needs (autonomy, competence, and relatedness) for health behaviors and medication adherence of patients with CAD in Saudi Arabia. Second, it sought to establish and assess the relationships among perceived psychological needs
(autonomy, competence, and relatedness) for health behaviors and medication adherence.
The results of this study will offer the basis for future development of an intervention for
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CAD patients that might be tested in forthcoming experimental studies. These interventions that will focus on meeting and improving patient’s psychological needs will likely improve patients’ well-being.
The study examined the following questions:
Among patients with CAD in Saudi Arabia:
1. What is the level of perceived autonomy for patients’ physical activity, diet,
and smoking?
2. What is the level of perceived competence for patients’ physical activity, diet,
and smoking?
3. What is the level of perceived relatedness for patients’ physical activity?
4. What is the level of self-reported medication adherence?
5. What are the relationships among CAD patients’ perceived psychological
needs (autonomy, competence, relatedness) for health behaviors and
medication adherence?
H1 5A: An increase of perceived autonomy for health behaviors will increase
medication adherence.
H1 5B: An increase of perceived competence for health behaviors will
increase medication adherence.
H1 5C: An increase of perceived relatedness for physical activity will increase
medication adherence.
6. Do perceived autonomy, competence, and relatedness for health behaviors
explain medication adherence?
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CHAPTER II
LITERATURE REVIEW
This literature review is divided into three sections. The first section provides background information about CVD and CAD, detailing health behaviors that contribute to CAD and medication adherence. The paper then explores the relationship between health behaviors and medication adherence. Finally, the third section reviews the implementation of Self Determination Theory (SDT) in previous studies and how basic psychological needs (autonomy, competence, and relatedness) relate to health behaviors.
Cardiovascular Disease
Worldwide Cardiovascular Disease
Cardiovascular disease (CVD) is the major cause of morbidity and mortality worldwide (Tolmie et al., 2009). Cardiovascular disease includes conditions that affect the heart function, such as coronary artery disease (CAD), hypertension (HTN), arrhythmia, heart valve problems, and heart failure (AHA, 2018; WHO, 2017d). In 2015 approximately 17.9 million people died from CVD, which represents 31% of all deaths worldwide (WHO, 2017a). Of these deaths, CAD caused 7.4 million deaths, and strokes resulted in 6.7 million deaths (WHO, 2017a).
The distribution of CVD deaths varies across the globe. “Nearly 75% of CVD deaths occurred in low- and middle-income countries” (WHO, 2017a, p. 1). The percentage of deaths caused by CVD in the European Region amounts to 50% of all deaths (WHO, 2017b). However, in the Eastern and Mediterranean Region, “deaths due to CVD range from 49% in Oman to 13% in Somalia” (WHO, 2017b, p. 1). According to
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the WHO, sedentary lifestyle in the Mediterranean Region is one of the risk factors that
contributed to CVD (WHO, 2017b). Other factors include; HTN, which ranges from 28%
in the United Arab of Emirates to 41% in Morocco and Libya, diabetes which ranges
from 4% of people in Iran to 19% in Sudan, and Hypercholesterolemia which ranges
from 14% (Lebanon) to 52% (Iran) (WHO, 2017b).
Cardiovascular Disease in the United States
In the United States, CVD is the main cause of death and adult morbidity for “people of most ethnicities including African Americans, Hispanics, and whites” ("Heart Disease
Facts," 2017, p. 2). According to the American Heart Association (AHA), CVD is the leading cause of death in the United States. One of every 3 deaths in the U.S. is caused by
CVD, with nearly 801,000 deaths annually (Benjamin et al., 2017). Around 75 million of
American adults have HTN and the prevalence increased with age and among African
Americans (“High Blood Pressure, 2016”). Approximately “790,000 people have heart attacks each year, and, of those, about 114,000 will die” (Benjamin et al., 2017, p. 2). In the
U.S, 65.3 years is the average age of men when they had their first heart attack and 71.8 years for women (Benjamin et al., 2017). Finally, around 5.7 million (9%) of Americans have congestive heart failure, which is the least cause of death among CVDs (Benjamin et al., 2018).
Coronary artery disease in the United States. The AHA reported one in seven
deaths in the U.S. results from CAD, which kills more than 360,000 patients every year
(Benjamin et al., 2017). “From 2004 and 2014, the annual death rate attributed to CAD
declined to 35.5%” (Benjamin et al., 2017, p. 2). In 2018, 43% of deaths attributed to
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CVD were due to CAD (Benjamin et al., 2018). Still, CAD is the leading cause of death among Americans (Benjamin et al., 2018; “Coronary Artery Disease,” 2016).
Both heart attacks and CAD rank among the ten most expensive hospital treatments (Benjamin et al., 2017). The estimated cost of the treatment of heart disease in the U.S. from 2012 to 2013 was $199.6 billion (Benjamin et al., 2017). The treatment of heart attacks accounts for $11.5 billion, and CAD treatment accounts for $10.4 billion.
Yet, the AHA suggested that between 2013 and 2030, treatment costs of CAD would increase by about 100% (Benjamin et al., 2017).
Cardiovascular Disease in Saudi Arabia
Cardiovascular disease is the leading cause of death in Saudi Arabia (WHO,
2014). In 2014, the WHO reported that 46% of deaths in Saudi Arabia resulted from
CVD and 37% in 2016 (WHO, 2014; WHO, 2018a). One study that took place between
January 2000 and December 2005 assessed “the prevalence and the pattern of medical disorders by affected body system among patients admitted into Saudi Arabian hospitals”
(Alamoudi, Attar, Ghabrah, & Al-Qassimi, 2009, p. 3). That study found that CVD is the major cause of adult hospitalization (19.9%), followed by respiratory disease (14.5%), diabetes mellitus (10.5%), and bronchial asthma (5.8%) (Alamoudi et al., 2009).
The most recent information about CVD in Saudi Arabia was found in a meta- analysis study conducted by Saquib et al. (2017). According to the analysis, “the most common types of CVD in Saudi Arabia are CAD (18%), HTN (16%), stroke (14%), peripheral artery disease (11%), and congenital heart disease (10%)” (Saquib et al., 2017, p. 111). The review of the literature indicated CAD as one of the most common causes of adult hospitalizations in the Middle East (Moattari et al., 2014).
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Coronary artery disease in Saudi Arabia. Deaths due to CAD are alarming, particularly in quickly developing countries like Saudi Arabia (Kovel et al., 2016). Since
1998, "CAD has become the leading cause of death in Saudi Arabia, and it has reached epidemic proportions” (Kovel et al., 2016, p. 1). Osman et al. (2011) reported that the
Saudi annual mortality report from 2005 indicated that acute MI emerged as one of the major causes of death (30.9%) among CVD patients. According to Aljefree and Ahmed
(2015), only one national survey took place in Saudi Arabia by Al Nozha et al. in 2004; the results showed that the prevalence of CAD among Saudis was 5.5% (approximately
858,000 patients), increasing more in men and in urban areas. That survey by Al-Nozha et al. (2004) included participants of both sexes ages of 30 to 70 living in both rural and urban communities. The results indicated a higher prevalence of CAD in men (6.6%) as compared to women (4.4%) and among urban Saudis (6.2%) as compared to rural Saudis
(4.0%). Additionally, the prevalence of CAD increased with age from 3.9% in 30- to 39- year-olds to 9.3% in the 60- to 70-year-olds (Al-Nozha et al., 2004). The data from the
WHO in 2008 ranked Saudi Arabia as number 13 in CAD-related deaths (20.600)
(Finegold, Asaria, & Francis, 2013).
In 2009, the first nationwide registry of patients with acute coronary syndrome
(ACS), which include includes unstable angina, non-ST-elevation MI, ST-elevation MI, and sudden cardiac death in Saudi Arabia was published (Al-Habib et al., 2009). The
Saudi Project for Assessment of Coronary Events (SPACE) registry provided information about the characteristics and prevalence of risk factors among ACS patients in Saudi
Arabia (Al-Habib et al., 2009). The SPACE registry reported that ACS occurred more frequently in males (77%) than females (23%), and that ischemic heart disease was
22 present in 32% of the population (Al-Habib et al., 2009). The SPACE registry “reported diabetes as the most common risk factor for CAD (56%), followed by HTN (48%), being a current smoker (39%), and hyperlipidemia (31%)" (Al-Habib et al., 2009, p. 255). In
2017, deaths due to CAD are still high. According to the latest WHO data published in
2017, CAD deaths in Saudi Arabia reached 23,624 (24.25%) of total deaths, and Saquib et al. (2017), reported that the most common type of CVD in Saudi Arabia is CAD
(18%). All these statistics highlights the need to conduct studies that focus on patients with CAD to minimize disease complication and improve well-being. One of the aspects that need to be studies are the health behaviors that contribute to CAD.
Health Behaviors Contributing to Cardiovascular Disease. The WHO defines behavioral risk factors as any “attribute, characteristic or exposure of an individual that might increases the likelihood of developing a disease or injury” (WHO, 2017c, p. 1).
The WHO reported that most instances of CVD could be prevented by addressing and focusing on behavioral risk factors that contribute to the disease (WHO, 2017d). These behavioral risk factors include smoking, unhealthy diet and obesity, physical inactivity, and the use of alcohol (Ministry of Health, 2017; WHO, 2017a).
For the purpose of this study, the major health behavior risk factors (physical inactivity, diet, and smoking) (Kalaf et al., 2016; Ministry of Health, 2017; WHO, 2017a) of CAD will be discussed in the literature review. In addition, the review of the literature will focus on patients’ medication adherence in Saudi Arabia in order to understand the relationship between health behaviors as guided by patients’ psychological needs from the perspective of SDT and medication adherence.
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A recent study by Ahmed et al. (2017) aimed to report the prevalence of CVD risk factors among patients visiting cardiac clinics in Saudi Arabia. The study found that
(49.8%) of the study participants had more than three risk factors for CVD (Ahmed et al.,
2017). The study ranked dyslipidemia as the most dominant risk factor of CVD (68.6%).
The study also found that expatriates had higher rates of the risk factors HTN (47.5%) and dyslipidemia (75.5%) when compared with Saudi nationals. Other factors included obesity (52.6%), and smoking (24.3%) (Ahmed et al., 2017). The study concluded that modifiable CVD risk factors are a serious issue in Saudi patients and that the government needs to encourage research that screens, explores, and examines CVD risk factors in
Saudi Arabia (Ahmed et al., 2017). Moreover, the government needs to emphasize the role of primary healthcare services in reducing the risk factors of CVD in general and
CAD in particular, which would eventually improve well-being (Ahmed et al., 2017).
Aljefree and Ahmed (2015) conducted a systematic review that categorized CVD risk factors in the Gulf Cooperation Council (GCC) region into two groups. They are;
“(1) metabolic risk factors including obesity, HTN, diabetes, and dyslipidemia and; (2) behavioral risk factors including diet, smoking, and physical inactivity” (Aljefree &
Ahmed, 2015, p. 18). The author of this systematic review, however, indicated that limited information exists about behavioral risk factors in Saudi Arabia, as well as perceived health behaviors of patients diagnosed with CVD. Most studies, in Aljefree and
Ahmed’s (2015) systematic review, suggested a high number of uncontrolled behavioral risk factors, one example being that a high number of Saudis live a sedentary life. In addition, the use of tobacco products and unhealthy food is slightly higher among patients with CVD as opposed to non-CVD patients (Aljefree & Ahmed, 2015).
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Health behaviors contributing to coronary artery disease. The behavioral risk factors of CAD and CVD are similar. Ram and Trivedi (2012) conducted a study using
135 newly diagnosed patients with CAD to examine various behavioral risk factors in the occurrence of CAD. The authors reported that smoking, and alcohol use were significantly higher among patients with CAD (Ram & Trivedi, 2012). Also, patients who were obese and physical inactive were more likely to have CAD (Ram & Trivedi,
2012). Further, nutritional components such as salt and oil intake per day were significantly higher among patients with CAD (Ram & Trivedi, 2012). Thus, modifiable health behavioral risk factors were the reasons of CAD, which increased the need of proper control strategies to reduce CAD complications (Ram & Trivedi, 2012).
Coronary artery disease increases mortality and morbidity in Saudi Arabia (Taha et al., 2011). Saudi patients with CAD are at high risk of recurrent CAD events due to poor lifestyle, poor diet, and absence of proper health education (Al-Nozha et al., 2004;
Finegold et al., 2013; Mahrous, 2013; Saquib et al., 2017). Patient re-hospitalization and visits to the emergency room frequently occur “after hospital discharge” (Jack et al.,
2009, p. 178). Hospital readmission in Saudi Arabia is quite common, and it is costly to the government “in both human resources and finances” (Mahrous, 2013, p. 106).
Therefore, research focusing on behavioral risk factors is needed to help healthcare providers improve patients’ health. The review of the literature suggests that improving behavioral risk factors has always linked with better health outcomes. For example, physical activity is important to improve cardiovascular function and to prevent or reduce
CAD complications.
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Health Behaviors and Coronary Artery Disease
Coronary Artery Disease and Physical Inactivity
Physical inactivity is one of the major risk factors that contribute to the development of CAD (Winzer, Woitek, & Linke, 2018). “Physical inactivity is the fourth-leading risk factor (6%) for global mortality” (Al-Zalabani et al., 2015, p. 209).
The AHA defines physical inactivity as failing to follow the recommended levels of regular physical activity (“American Heart Association, n.d.”). The US Department of
Health and Human Services recommends that adults should perform "at least 150 minutes to 300 minutes a week of moderate intensity or 75 minutes to 150 minutes a week of vigorous intensity aerobic physical activity” (Piercy et al., 2018, p. 2020). Physical inactivity was associated with many diseases, including CAD (Al-Nozha et al., 2007).
There have been studies suggesting that people who are physically active have a substantially lower risk of CAD than those who are inactive ("Institute of Medicine
(U.S.) Committee on Health and Behavior," 2001).
Al-Nozha et al. (2007) conducted a study to assess physical activity levels among
Saudi adults using data from the CAD study in Saudi Arabia. This data was a National
Epidemiological Health Survey, that was collected between 1995 and 2000 (Al-Nozha et al., 2007). The prevalence of physical inactivity was high (96.1%). The results showed that women were more inactive (98.1%) than men (93.9%). Also, as age increases, physical inactivity also increases and as the level of education increases, the level of physical inactivity decreases (Al-Nozha et al., 2007). A more recent study conducted by
Al-Zalabani et al. (2015) correlated with the AL-Nozha et al.’s findings (2007). Al-
Zalabani et al. (2015) used a national survey of 4,758 participants in Saudi Arabia, and
26 the results of this national survey found high physical inactivity among people in different regions in Saudi Arabia, specifically 66.6% among men and 72.9% among women (Al-Zalabani et al., 2015).
It is clear that the level of physical inactivity in Saudi Arabia is high. Even though a little improvement has taken place since 2000, several further actions can be taken.
Furthermore, most of these studies suggest that females are less active than males in
Saudi Arabia. In the Gulf area, “women are often over-protected due to religious or cultural barriers and cannot publicly participate in physical activities,” such as sports
(Kanter & Caballero, 2012, p. 495). Nevertheless, with the new development of the health care system in Saudi Arabia and the new 2030 vision presented by Prince
Mohammed bin Salman, cultural changes will improve women’s health in Saudi Arabia
(Alharbi, 2018).
Coronary Artery Disease and Diet/Obesity
The prevalence of obesity is high in Saudi Arabia compared to other countries in the region (Saad & Latif, 2017). Approximately 35% of the Saudi society are obese, which breaks down to 44% of women and 26.4% of men (Pasha, 2017). The WHO also reported that around 18% of Saudi children are obese (Hamdan, 2013; Pasha, 2017). This high percentage of obese people has contributed to the development of health issues, such as diabetes and heart diseases (Hamdan, 2013). These rates are higher than for people in the U.S. (Allison et al., 2004; Alshaikh et al., 2016). Hamdan (2013) reported that in
Saudi Arabia, the percentage of obese people over the age of 40 is 72.4%. In Saudi
Arabia “Social aspects, sedentary lifestyle, and high-calorie foods contribute to higher incidents of obesity among people in Saudi Arabia” (Saad & Latif, 2017, p. 1).
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According to Midhet, Al Mohaimeed, and Sharaf (2010), many patients who visited primary health care centers in Saudi Arabia showed a poor dietary habits. Only patients with chronic diseases were more likely to have health education from health centers (Midhet et al., 2010). The health education sessions aimed to help patients to improve their diet and, increase their physical activity (Midhet et al., 2010). Still, more lifestyle modification programs need to be implemented in health centers to improve patients’ awareness of the consequences of poor dietary habits and obesity as well as chronic disease risk factors (Midhet et al., 2010).
Saad and Latif (2017) conducted a study to “characterize the major cardiovascular risk factors using Framingham Risk Score (FRS) among Saudis patients in Medina” (p.
1). The FRS is a ten-year risk assessment method used to predict future incidents of CAD
(Saad and Latif, 2017). Around 14% of subjects enrolled in the study had normal body weights, and 43% were either overweight or obese (Saad and Latif, 2017). “The study found that BMI strongly correlates with the expected ten years FRS for CVD and CAD”
(Saad and Latif, 2017, p. 1). The study concluded that a significant increase in CVD, which included CAD risk, occurred among Saudis patients who were obese, overweight, and physically inactive (Saad & Latif, 2017).
Similarly, women have a high risk of CVD and CAD in Saudi Arabia. Alshaikh et al. 2016 found that both obesity and physical inactivity were high among women in Saudi
Arabia. In a systematic review conducted by Alshaikh et al. (2016), 26% of Saudi women, aged 20 to 39, were overweight and 29% were obese. Also, a study conducted in
Saudi Arabia using data from the Saudi national health survey concluded that 28.7% of the Saudis were obese (Memish et al., 2014). The study found that women were more
28 obese (33.5%) than men (24.1%) (Memish et al., 2014). To conclude, obesity in Saudi
Arabia is contributing to many diseases such as CAD, therefore, studies that focusing on improve dietary habits and reduce obesity are needed.
Coronary Artery Disease and Smoking
The consumption of tobacco is one of the major risk factors for morbidity and mortality worldwide (Moradi-Lakeh et al., 2015). According to the WHO (2017a), the use of tobacco is among the major causes of CAD worldwide (WHO, 2017a). In the U.S., one of every three death from CVD’s is due to smoking (“Smoking and Heart Disease and Stroke,” 2018). The use of tobacco products can stimulate the development of atherosclerosis, which could cause major CVD such as CAD (Jiang et al., 2015). The use of tobacco products has a major effect on the cardiovascular system. Extensive use of these products can cause inflammation of the myocardium, which can “lead to systolic and diastolic dysfunction, arrhythmia”
(Graham, 2013, p. 174), heart failure, and even death.
A health survey conducted by Al-Nozha et al. (2009) that collected data about smoking status among Saudi between 1995 and 2000 showed “a significant association between cigarette smoking and CAD, particularly among men” (Al-Nozha et al., 2009, p.
170). The most recent study that examined the prevalence of smoking in Saudi Arabia was published by Moradi-Lakeh et al. (2015). This study was based on a national survey, which found that men (12.2 %) were more likely to smoke compared to women (1.1 %)
(Moradi-Lakeh et al., 2015). The study also provided information about the mean age of starting smoking, which was 19.1 years (Moradi-Lakeh et al., 2015).
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In another recent study by Saad and Latif (2017), the researchers sought to
“characterize the major cardiovascular risk factors using FRS among Saudi patients in
Medina” (p. 1). The study results showed that 31% of men and 23.8% of women smoked cigarettes, and smoking correlates with heart problems including CAD (Saad & Latif,
2017). The percent of men and women who smoke in Saudi Arabia seems to be low compared to other countries in the Middle East (Moradi-Lakeh et al., 2015). Nonetheless, many potential areas for improvement exist, especially for CAD patients. Most of those studies suggested the need to develop educational programs to improve awareness about the risk of smoking and encourage quitting (Moradi-Lakeh et al., 2015).
Medication Adherence
Medication adherence is one of the most important factors in improving and maintaining patients’ health (Lourenço et al., 2014; Patel et al., 2015). In order for medication to be effective for patients’ treatment, patients must adhere to their prescribed medications (Shaik et al., 2016). Medication adherence is defined as the degree to which patients follow the instructions given by the healthcare providers about their prescribed medication (Lourenço et al., 2014). According to Al-Ganmi et al. (2016) non-adherence to medication is defined as “taking less than 80% of prescribed doses and can also include taking too many doses and it is associated with an increased risk of poor health, adverse clinical events and death” (p. 3002). Non-adherence has been linked to poor patient health and increased rates of hospitalization, as well as an increased healthcare costs and increased mortality (Lourenço et al., 2014; Patel et al., 2015). Non-adherence to prescription medications has also been identified as a leading cause of diseases complications and death (Aggarwal & Mosca, 2010).
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Medication adherence is low among Saudi population (Altuwairqi, 2016; Patel et al., 2015; Shaik et al., 2016). In the past decade, the number of studies on medication adherence has increased in Saudi Arabia. Of those studies some were conducted to identify the level of medication adherence among people with chronic conditions such as heart disease (Altuwairqi, 2016; Khayyat et al., 2017; Al Shaik et al., 2016; Patel et al.,
2015). For example, Khayyat et al. (2017) conducted a study to assess the level of medication adherence among patients with HTN in primary healthcare clinics. The author concluded that more than half (54%) of patients with HTN in Makkah/Saudi Arabia were non-adherent to their medications (Morisky medication adherence scale (MMAS) score <
6). These results were similar to a study by Shaik et al. (2016), where more than half of patients (55%) with HTN had low adherence to their medications. Moreover, Altuwairqi
(2016) similarly conducted a study to examine medication adherence among patients with heart diseases in Riyadh, Saudi Arabia using the MMAS. The study found that only
24.5% of patients with heart diseases had high medication adherence (Altuwairqi, 2016).
Other 41.7% participants had medium adherence and 33.7% had low adherence
(Altuwairqi, 2016). Medication adherence is considered to be low among Saudi patients especially patients with heart diseases (Altuwairqi, 2016). Therefore, a new study focusing on medication adherence and health behaviors in this population is needed.
Health Behaviors and Medication Adherence
In patients with CAD, the management of risk factors through health behaviors modification (e.g., smoking cessation, diet or physical activity) is essential in improving the survival as well as contributing in preventing cardiovascular complications (Lee et al.,
2018). Multiple studies have established that there is a significant relationship between
31 health behaviors and medication adherence among a variety of chronic diseases (Batool
& Kausar, 2015; Han et al., 2017; Hempler et al., 2012; Lee et al., 2018; Mosleh &
Darawad, 2015; Pellowski & Kalichman, 2016).
Physical Activity and Medication Adherence
Regular physical activity is one of the most important factors that contribute to improve patients’ health (WHO, 2017a). There have been studies conducted to explore the relationship between physical activity and medication adherence. For example, Saleh,
Mumu, Ara, Hafez, and Ali, (2014) conducted a study “to explore the relationship between poor adherence to self-care practices, medication and health related quality of life among type 2 diabetic patients” (p. 3). The study found significant association between physical inactivity and self- care, which includes medication adherence. That is, the higher the level of physical inactivity, the less medication adherence and poor quality of life (Saleh et al., 2014).
In contrast, Seyde, Firooze, Ahmad, and Mohammad (2017) conducted a study to explore “the effects of self‐efficacy, other physical symptoms on physical activity and medication adherence in patients with chronic illness” (p. 1). The study found a positive relationship between self-efficacy and physical activity; however, there was no association between physical activity and medication adherence. In sum, conflicting results have been reported related to the relationship between physical activity and medication adherence. More studies need to be conducted to better understand the relationship between physical activity and medication adherence (Seyde et al., 2017).
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Diet and Medication Adherence
According to Batool and Kausar (2015) disease complications from unhealthy behaviors account for 50% of the mortality from the 10-leading cause of death. Diet or eating behavior is an important factor in patients’ health. In addition, patients who followed healthy diets tend to have better medication adherence (Batool & Kausar, 2015).
A study conducted in Pakistan to measure health-related behaviors and medication adherence among patients with hepatitis C supported the relationship between diet and medication adherence (Batool & Kausar, 2015). The study found significant relationship between medication adherence, diet, and eating behavior, which positively affected patients’ health. Similarly, Pellowski and Kalichman (2016) conducted a study to assess the relationship between medication adherence and health behaviors, including diet and physical activity, among patients with HIV. The study found a significant association between healthier diet, higher physical activity behaviors, and higher medication adherence (Pellowski & Kalichman, 2016).
Following good dietary patterns results in weight control, especially for patients who are at risk of diabetes and CVD (Grandy, Fox, & Hardy, 2013). Losing weight, especially for obese patients is considered beneficial for the treatment plan. In one intervention study conducted by Grandy et al. (2013) that aimed to examine the relationship between weight loss and medication adherence, patients who were able to lose weight were more likely to have better medication adherence. The relationship between weight loss and medication adherence was significantly associated with each other, which resulted to better disease control.
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Smoking and Medication Adherence
Globally, smoking results in the mortality and morbidity of millions of people each year, and it is found to be among the factors that affects adherence to healthy lifestyles including medication adherence among patients with chronic diseases
(“Smoking and Heart Disease and Stroke,” 2018). A study conducted by O’Connor et al.
(2013) to identify factors associated with low medication adherence among patients with
HIV found that smoking was one of the predictors of medication non-adherence. The study concluded that smokers tend to have low medication adherence, which contributes to increasing disease complications. According to O’Connor et al. (2013) the relationship between smoking and medication adherence could be explained in part by “the fact that smokers are likely to be less health conscious in general” (p. 48). In contrast, Nguyen et al. (2016) explored the relations between smoking, and HIV medication adherence in
Vietnam. The study found no association between smoking and medication adherence.
However, the study concluded that patients with greater nicotine dependence were more likely to not adhere to their prescribed medication (Nguyen et al., 2016).
Smoking is, however, a predictor for medication non-adherence among patients with CVD and chronic obstructive pulmonary disease (COPD). Aggarwal and Mosca
(2010) explored the prevalence and predictors of non-adherence to blood pressure and cholesterol-lowering medications among patients with CVD. The study found significant association between medication non-adherence and smoking. Also, in patients diagnosed with COPD, researchers found similar results. Ágh, Inotai, and Mészáros (2011) examined medication adherence and identified factors related to adherence in COPD
34 patients. Poor medication adherence among patients with COPD was observed, and smoking was among the factors related to low adherence.
Physical Activity, Diet, Smoking and Medication Adherence
The three most important health behaviors that contribute to CAD complications are physical activity, diet, and smoking (WHO, 2017a). Controlling and improving theses three health behaviors is associated with better disease management. Moreover, medication adherence is also important, especially for patients with CAD. Researchers throughout the years have examined the relationship between these health behaviors and medication adherence. Most studies suggested that when patients have better health behaviors, they are more likely to have better medication adherence. The most recent study that examined the relationship between health behaviors and medication adherence is a study conducted by Lee et al. (2018). The study found a significant association between health behaviors (physical activity, diet, smoking) and medication adherence among patients with CAD. Unhealthy behavior was associated with poor medication adherence. The study concluded that many patients with CAD are experiencing difficulties in lifestyle modification and medication adherence, which raises the need to conduct studies to determine why patients might have these difficulties (Lee et al., 2018).
Additional studies also support the results found in Lee et al. (2018). In Jordan, patients with CAD who have poor health behaviors were more likely to have poor medication adherence (Mosleh & Darawad, 2015). Similarly, Hempler et al. (2012) suggested that when patients with CAD improved these three health behaviors they were more likely to improve their adherence to lipid-lowering medications and blood pressure- lowering medications. Moreover, Han et al. (2017) added similar results that when
35 patients have better physical activity, they were more likely to quit smoking and have better medication adherence. Patients with positive health behaviors were more likely to improve their medication adherence, which in turn improved their health outcomes (Han et al., 2017).
The finding that patients who follow healthy behaviors were more likely to show better medication adherence is consistent throughout the current body of literature. The management and treatment of CAD in particular requires the modification of health behaviors such as physical activity, healthy diet, and smoking, as well as excellent medication adherence (Capewell et al., 2010; Ministry of Health, 2017; WHO, 2017d).
While there is commonality between these relationships across populations with chronic diseases, it is also important to conduct research studies specifically on patients with
CAD that focus on patients’ physical activity, diet, smoking cessation, and their relation to medication adherence, in order to determine whether these relationships are consistent or if there are other health behaviors that are important in treating and managing CAD.
Self Determination Theory
“The use of theory offers structure and organization to nursing knowledge by providing it with a systematic meaning of the collecting data to describe, explain, and predict nursing practice” (McEwen & Wills, 2014, p. 25). Further, the use of theory will promote a rational and systematic practice by validating intuition or research hypotheses
(McEwen & Wills, 2014). Self-determination theory was developed by Edward L. Deci and Richard M. Ryan and it has been applied to several fields, such as health care sciences and education (Deci & Ryan, 2008). According to the theory, there are three psychological needs (autonomy, competence, and relatedness) that need to be satisfied
36 for individuals to adopt healthy behaviors (Ryan & Deci, 2017). According to Ryan and
Deci (2000), satisfaction of autonomy, competence, and relatedness will relate positively to many health behaviors such as physical activity, dietary habits, and smoking cessation.
When humans experience less satisfaction of their basic psychological needs they are more likely to have negative health behaviors (Ryan & Deci, 2017).
Self Determination Theory defines autonomy as an individual’s volition to regulate their health behaviors based on their own values, choices, and interests (Anja et al., 2010; Patrick & Williams 2012). Self Determination Theory further defines competence as patients’ need to feel competent and confident in their ability to improve their skills and knowledge to make a health change and to reach their goals (Anja et al.,
2010; Patrick & Williams, 2012). Support for competence is afforded when healthcare providers supply effective and relevant feedback to patients, and providers enhance patients’ health self-management by providing tools to change (Anja et al., 2010; Patrick
& Williams, 2012). Based on other studies that made use of SDT, patients who are autonomous are also highly competent in achieving positive outcomes (Williams, Grow,
Freedman, Ryan, & Deci, 1996; Williams et al., 2009).
The theory defines relatedness as the status of connection between patients and other individuals, as well as feeling understood and cared for by their healthcare providers or others (practitioner-patient relationship) (Anja et al., 2010; Patrick &
Williams, 2012; Ryan et al., 2008). Also, relatedness means a feeling of belonging to a group with social connections (Deci & Ryan, 2008). According to Ryan and Deci (2008), relatedness proves essential for motivating and supporting individuals’ autonomy because it improves the internalization of extrinsic causes (Ryan et al., 2008). For instance,
37 patients can voluntarily engage in behavioral change for the sake of a close personal relationship, such as a spouse, child, friends, or even their health care providers (Patrick
& Williams, 2012). Relatedness is important because it provides social support to individuals. Social support has shown a beneficial in various domains of health behaviors, involving patients with cancer or other chronic diseases. Relatedness support could include providing “unconditional regard, being empathetic with patient concerns, and providing a consistently warm interpersonal environment” (Patrick & Williams 2012, p. 4). Because of this, healthcare providers might support patients’ need for relatedness by expressing understanding of patients concerns. This requires that healthcare providers becoming actively engaged with their patients (Patrick & Williams 2012). The theory suggests that all these basic psychological needs must be satisfied to produce healthy outcomes (Ryan & Deci, 2017).
Basic Psychological Needs and Behaviors Contributing to Coronary Artery Disease
Self-determination theory proposes that when people have their basic psychological needs met, they will tend to develop, maintain, or improve well-being
(Ryan & Deci, 2017). According to SDT, when the basic psychological needs are neglected, people will show lowered energy, loss of volition, and reduced well-being
(Ryan & Deci, 2017). Thus, the basic psychological needs are important to energize people to action and develop or maintain well-being (Ryan & Deci, 2017). These basic psychological needs are part of human structure and thus apply to people of all cultures
(Ryan & Deci, 2017). In the health domain, satisfaction of these psychological needs results in motivating patients to follow healthy habits and behaviors (Ryan & Deci,
2017). Williams et al. (2005) found that when the basic psychological needs are satisfied,
38 patients had autonomy, which improved their diet, increased exercise, and reduced smoking. Thus, the literature review in the following section will focus on behaviors contributing to CAD and their relation to the satisfaction of the psychological needs. The major health behaviors factors contributing to CAD are physical inactivity, diet, and smoking.
There have been studies that adopted SDT to examine healthy diets for weight loss and long-term health. For example, Shaikh, Vinokur, Yaroch, Williams, and Resnicow
(2011) concluded that patients who experienced satisfaction of the need for autonomy showed increased consumption of healthy fruits and vegetables as compared to patients who were not autonomous in the study. Also, Pelletier, Dion, Slovinec-D’angelo, and
Reid (2004) found that patients who experienced more satisfaction in their autonomy
(high autonomous) were more likely to follow a healthy dietary program. Moreover, Ng,
Ntoumanis, Thøgerse-Ntoumani, Stott, and Hindle (2013) found that when individuals experience satisfaction of the basic psychological needs, they are more likely to be motivated to control their weight and eat healthy food, which was positively associated with well-being.
The psychological needs are important for maintaining health behavior and promoting tobacco cessation (Ryan & Deci, 217). For example, Williams, Gagne, Ryan, and Deci (2002) found that individuals perceived autonomy and perceived competence predicted patients’ cessation over 30 months. Similar results were found when Williams et al. (2006) showed that patients experience more autonomy and competence satisfaction for tobacco cessation when compared to a control group.
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According to Ryan and Deci (2017) satisfaction of the basic psychological needs are important in improving patients’ regular exercise and physical activity. Williams et al.
(1996), who conducted a six-month study exercise motivation program, found that autonomous behavior served as a predictor for exercise and weight loss 18 months after the six-month intervention program ended. D’Angelo, Reid, and Pelletier (2007) conducted a cross-sectional study, wherein they examined exercise programs for cardiac rehabilitation patients. The study examined “patients’ global orientation toward self- determination, perceived autonomy, perceived competence for exercising, intention to exercise, and specific plans for exercising” (Ryan & Deci, 2017, p. 469). The study found similar results that autonomy mediated by perceived competence, predicted intention to exercise, which predicted patients’ specific exercise plans. Finally, the study concluded that people with a self-determined personality are more likely to adhere to long-term exercise plans, which will in turn affect their long-term health statuses (D’Angelo et al.,
2007). Similarly, Fortier, Sweet, OʼSullivan, and Williams (2007) in a randomized control trial that tested a physical activity intervention revealed that participants who reported more satisfaction of their perceived autonomy and perceived competency engaged in significantly more physical activity at 13 weeks than people who did not.
Gaps
Several gaps have been identified in this literature review. First, there was a lack of current information about medication adherence of patients diagnosed with CAD in
Saudi Arabia. Most of the studies suggested that there is low medication adherence among patients with CVD in general and not CAD in specific. Thus, it is important to conduct a new study to look at medication adherence among patients with CAD in Saudi
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Arabia. Second, there is a lack of information regarding patients’ perceived health behaviors and their relation to medication adherence among patients with CAD in Saudi
Arabia. Information about this relationship will add beneficial knowledge for future nursing research in Saudi Arabia. Third, there is no evidence of using SDT in a Saudi population to measure patients’ health behaviors and perceived psychological needs.
Cultural and religious factors differ in Saudi Arabia as compared to Western countries, and there is always the capacity to explore new results using theories that have been applied in Western nations. However, limited studies have been conducted in Saudi
Arabia to examine psychological needs (autonomy, competence, and relatedness) in health behaviors, as well as to assess the relationship between these needs and medication adherence. The result of such a study will provide the basis for future development of an intervention that might be tested in future experimental studies. Research interventions will likely focus on improving patients’ psychological needs, which should eventually improve patients’ health behaviors and medication adherence, as well as well-being.
Conclusion
Cardiovascular diseases are the leading cause of death not only in Saudi Arabia, but also globally. Coronary artery disease is the most common type of CVD that causes morbidity and mortality in Saudi Arabia. Many health behaviors contribute to CAD complications, such as physical inactivity, diet, and smoking. Satisfaction of the psychological needs of autonomy, competence, and relatedness have been linked to improving patients’ health behaviors. Furthermore, improving patients’ health behaviors has been linked to improved patients’ medication adherence. However, there are no studies in Saudi Arabia that examine the relationship between health behaviors and self-
41 reported medication adherence from the perspective of SDT psychological needs. Thus, such study is needed. By examining patients’ health behaviors and perceived autonomy, competence, and relatedness, as well as their relation to medication adherence, researchers will gain valuable information that will assist in developing future medical plans to help improve treatment of CAD patients. What is more, the review of the literature reveals the need to conduct research studies that examine, evaluate, and contribute to improving patients’ holistic health statuses in addition to reducing and minimizing CAD risk factors in Saudi Arabia.
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CHAPTER III
METHODOLOGY
This study served two main purposes. First, the study sets out to explore the levels of the perceived psychological needs (autonomy, competence, and relatedness) for health behaviors and medication adherence of patients with CAD in Saudi Arabia. Second, it sought to establish and assess the relationships among perceived psychological needs
(autonomy, competence, and relatedness) for health behaviors and medication adherence.
The study examined the following questions:
Among patients with CAD in Saudi Arabia:
1. What is the level of perceived autonomy for patients’ physical activity, diet,
and smoking?
2. What is the level of perceived competence for patients’ physical activity, diet,
and smoking?
3. What is the level of perceived relatedness for patients’ physical activity?
4. What is the level of self-reported medication adherence?
5. What are the relationships among CAD patients’ perceived psychological
needs (autonomy, competence, relatedness) for health behaviors and
medication adherence?
H1 5A: An increase of perceived autonomy for health behaviors will increase
medication adherence.
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H1 5B: An increase of perceived competence for health behaviors will
increase medication adherence.
H1 5C: An increase of perceived relatedness for physical activity will increase
medication adherence.
6. Do perceived autonomy, competence, and relatedness for health behaviors
explain medication adherence?
Research Design
A cross-sectional descriptive exploratory correlational design was used to explore the levels of perceived psychological needs (autonomy, competence, and relatedness) for health behaviors and self-reported medication adherence of patients with CAD in Saudi
Arabia. Further, this design was used to examine whether relationships exist among research variables (Grove, Burns, & Gray 2013).
Research Setting
The study was conducted at the Madinah Cardiac Center (MCC) in Saudi Arabia.
The MCC is a heart disease specialty center located in Madinah in west Saudi Arabia.
The Ministry of Health (MOH) established the center in August 2011. The capacity of the
MCC is 130 inpatient beds with more than 24 outpatient cardiovascular clinics. All medical care services are provided to patients at no cost. These services include clinical checkups in addition to management of congenital heart disease, CAD, heart failure, and other medical and surgical conditions of the heart.
Sampling
This study used a convenience sampling of Saudi patients diagnosed with CAD who were eligible and willing to participate in the study. Convenience sampling is a
44 nonprobability sampling method that selects potential participants based on their availability for the study (Henry, 1990). This study took place at MCC in Saudi Arabia, and participants were recruited from the cardiovascular clinic. Recruitment started after obtaining Institutional Review Board Approval (IRB) from the University of Akron
(Appendix A) and the MCC (Appendix B) to ensure protection of the participants and follow research subject protection.
Determination of sample size. Sample size determination for this study was based on a power analysis (Cohen, 1988). The power analysis consisted of four parameters: (a) significance level (α); (b) estimated variance; (c) power (1- β); and (d) effect size (d). The purpose of the sample size planning is to determine an adequate number of subjects to keep alpha and beta errors at an acceptable low level to ensure that the study is not costly or difficult (Hulley et al., 2013). Table 2 provides the total number of participants needed for each effect size (Large, medium, and small) for multiple regression analysis.
Table 2
Multiple Regression Power Analysis
Effect size conventions Alpha Power Number of predictors Sample Size
.02 0.05 .80 4 602 .12 0.05 .80 4 105 .15 0.05 .80 4 85 .35 0.05 .80 4 40 ______
A meta-analysis conducted by Ng et al. (2012) examined studies that utilized self- determination theory in healthcare domain found that “the effect sizes in experimental
45 studies (ρ = .33, 95% CI = [.27, .39]) were larger than those in cross-sectional studies (ρ
= .12, 95% CI = [.07, .17]) and prospective studies (ρ = .13, 95% CI = [.05, .21])” (Ng et al., 2012, p. 332). The meta-analysis suggested using a medium effect size to detect statistical significance. A power analysis for multiple regression was conducted in the
G*Power software program. Parameters used to estimate the sample size include: effect size (f2) =. 12; alpha =. 05; power =. 80; and number of predictors = 4. The total sample size based on this approach was 105 participants. The effect size of 0.12 was considered conservative for effect size in multiple regression. To allow for 15% attrition, the sample size was increased to 121 participants (Grove et al., 2013). Further, a power analysis for
Pearson r correlation coefficient was also conducted using effect size (f2) = 0.3; alpha =.
05; power =. 80. The total sample size based on Pearson r correlation coefficient was 76 participants. This number is less than the number of multiple regression, therefore the number of participants was based on multiple regression. As a result, the estimated total of 121 participants for the sample size was used for the study based on the proper effect size for multiple regressions.
Inclusion and exclusion criteria. The inclusion criteria included Middle Eastern adult patients 18 years and older who have been diagnosed with CAD, MI, or stable angina. Participants must be able to read and speak Arabic. The exclusion criteria included any patients with congenital heart disease because this would affect the validity of the research results. Patients with end stage heart failure, end-stage lung disease, severe end-stage renal failure, or cancer were excluded. As indicated, this study used convenience sampling of Middle Eastern patients diagnosed with CAD who met the criteria. Participants were carefully examined to ensure they met the inclusion criteria.
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Selections of study participants. After obtaining appropriate IRB from the
University of Akron and MCC, the data collection phase started. According to the
Department of Information Technology (IT) at MCC, the total reserved appointment in
MCC outpatients’ clinics from March 10 to April 30 was 3581 patients with CVDs.
After considering the inclusion and exclusion criteria, except for reading and writing in
Arabic, the total number of CAD patients was 1019. All these patients were diagnosed with CAD (Figure 2).
Figure 1. Selections of study participants.
Each day, the research assistant from the MCC had access to the electronic medical record for patents with CAD and identify potential study participants. The research assistant then had a list of potential participants who were visiting the
47 cardiovascular clinic for follow up. The research assistant first approached all potential participants by following the recruiting standard script (Appendix C). Potential study participants received a letter from the cardiac clinic explaining the purpose as well as how to participate in the study (Appendix D). The letter included a general description of research objectives and information regarding the protection of human subjects in the study. Furthermore, information regarding the number of items in the survey, time needed to finish the survey, risks and benefits of the study, and participant confidentiality were included in the letter. Next, potential participants were asked to indicate interest to the research assistant, nurses in the cardiac clinic or calling the researcher at the number provided (0594771137), or by e-mail at [email protected]. For those participants who indicated their interest to participate in the study they were sent to the primary researcher room after they completed their visit with their doctors.
The initial interview took place at the outpatients’ cardiac. During the initial interview with potential participants, the researcher first screened participants for study inclusion criteria. Screening involved asking potential participants questions related to the inclusion criteria (Appendix C). After screening, the researcher explained the purpose and nature of the study to the potential participants and asked whether or not they agree to complete the survey. For those participants who agreed to complete the survey, they were asked to sign the informed consent (Appendix E).
Data Collection Procedure
After informed consent, participants were provided with iPads that contain research survey (Appendix F). The survey included the demographic and the actual study questions. In addition, participants were informed about the estimated time to complete
48 the survey, which was around 10-15 minutes. To ensure confidentiality, participants at the cardiac clinic were asked to sit alone in the research room to complete the survey.
Participants were informed that if they have any questions or concerns about the survey, they could call the researcher at the MCC research office. Participants then were asked to complete study survey and press the bottom button (i.e., submit) on his or her iPad upon finishing. They then were asked to leave the iPads in the research room. The researchers examined each iPad to ensure that participants submitted their answers. At the end of each day, the researcher downloaded the data from the iCloud and save data on an external USB drive to use them as backup. Further, a paper copy of the survey was given for those participants who prefer so. The majority of participants completed the survey using the iPads (n 93) vs. paper survey (n 28).
Electronic Tablet-Based Data Collection
The survey was created on Qualtrics and participants were provided with an iPad that has a link to the study survey. Data were collected using Qualtrics software uploaded on two iPads. Qualtrics is free online survey software (“Qualtrics,” 2015) provided by the
University of Akron.
The use of tablet-based electronic survey methods for data collection is growing
(Leisher, 2014). According to Parker, Manan, and Urbanski, (2012), the tablet-based data collection approach is an effective method by which to collect data from research participants. Leisher (2014) pointed out several advantages to the tablet-based electronic survey method. They: (1) are considered less expensive compared to a paper-based survey; and (2) require less time to complete the survey compared to a paper-based survey (Leisher, 2014). In addition, King et al. (2013) and Handfield (2017) indicated
49 that the tablet-based electronic surveys would save time in data entry because the data will be already entered by participants. By doing so, there was less chance of data entry errors. With Qualtrics, data were easily exported to SPSS program and were ready for analysis (“Qualtrics,” 2015). This method of survey might not be appropriate for people unfamiliar with electronic tools (Handfield, 2017). Some people with low literacy levels have difficulties using electronic devices, and sometimes they need more assistance in completing the surveys. Therefore, both research and research assistant were available for any assistant if needed.
Data Collection Instruments
A total of five questionnaires were used (Table 3). First, demographic information was collected using a questionnaire developed by the researcher. These demographic data included information about participants’ gender, age, marital status, employment status, level of education and time since diagnosis with CAD (Appendix G). Second, the
Treatment Self-Regulation Questionnaire (TSRQ) (Appendix H) was used to examine patients’ perceived autonomy for heath behaviors (physical activity, diet, smoking),
Third, the Perceived Competence Scale (PCS) was used to assess patients’ perceived competence for health behaviors (physical activity, diet, smoking) (Appendix I), and fourth, Relatedness to Others in Physical Activity Scale (ROPAS) (Appendix J), was used to examine patients’ perceived relatedness in physical activity. Lastly, the four- items Morisky, Green, and Levine (MGL) adherence scale was used to assess participants’ medication adherence (Appendix K).
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Table 3
Data Collection Instruments
Questionnaire Information
Demographic Demographic data included: gender, age, marital status, Data employment status, level of education and time since diagnosis with CAD.
Treatment Self- A total of 18-items developed to assess perceived autonomy in Regulation health behaviors (physical activity, 6 items, diet 6 items, and Questionnaire smoking 6 items). Each of the 6 items aim to examine (TSRQ) autonomous motivation for each health behavior. Each item is measured with a 7-point Likert-scale ranging from: (1= Not at all to 7= very True). Cronbach alpha reliability was > 0.73 (Levesque et al., 2007)
Perceived 12-item questionnaire that assesses the degree to which Competence individuals feel confident about their ability to change healthy Scale (PCS) behaviors (physical activity, 4 items, diet 4 items, and smoking 4 items). Each item is measured with a 7-point Likert-scale ranging from; (1= Not at all to 7= very True). Cronbach alpha reliability was 0.94 (Williams & Deci, 1996). Cronbach’s alpha reliability was 0.90 (Williams et al., 1998).
Relatedness to The ROPAS is a 6 item, self-report instrument designed to Others in Physical measure perceived relatedness under SDT. Each of the 6 item is Activity Scale measured with 6-point Likert-scale ranging from; (1= False to 6= (ROPAS). True). Cronbach alpha reliability ranged from 0.89 to 0.93. Cronbach alpha reliability ranged from 0.70 to 0.97
Four item MGL This MGL adherence scale has four items. Each item has two Medication possible responses (Yes= 0, No= 1). The total score of this scale Adherence Scale ranges from 0 to 4. Predictive and concurrent validity was established by examining a group of patients with HTN and the relationship between the four -item MGL adherence score and patient’s blood pressure. The Cronbach alpha reliability was 0.61.
Treatment Self-Regulation Questionnaire (TSRQ). The original TSRQ has a total of 45 items. In this study, only items measuring the autonomous regulatory style
51 subscales were used. The TSRQ has a total of 18-items developed to assess perceived autonomy in health behaviors (physical activity, 6 items, diet 6 items, and smoking 6 items) and understand why individuals would follow some healthy behaviors and try to change unhealthy behaviors (Williams et al., n.d.). The TSRQ aims to understand whether a person’s motivation and volition for a particular behavior (physical activity, diet, smoking) is autonomous or not (Williams et al., n.d.). “The TSRQ was first used for behaving in a healthy way by Williams, Grow, Freedman, Ryan, and Deci (1996), and has also appeared in research by Williams, Freedman, and Deci (1998), Williams, Rodin,
Ryan, Grolnick, and Deci (1998), Williams, Cox, Kouides, and Deci (1999), and several other studies” (Williams et al., n.d., p. 2). Other studies used the TSRQ including
Levesque et al. (2007) who conducted a study to validate the TSRQ and Chan, Lonsdale,
Ho, Yung, and Chan, (2009) who conducted a study to examine patients autonomous and controlled motivation after anterior cruciate ligament surgery.
For each health behavior the TSRQ has six items aim to examine autonomous motivation. An example of item that examines autonomous motivation is item number one, which is, “the reason I would not smoke is because I feel that I want to take responsibility for my own health” (Williams et al., n.d, p. 5). Each TSRQ item is measured with a 7-point Likert-scale ranging from; (1= Not at all to 7= very True)
(Williams et al., n.d).
The validity and reliability of the TSRQ was established by Levesque et al.
(2007). According to Levesque et al. (2007) construct validity of the 15-items was obtained by “exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) using data that was collected from four different settings across three health behaviors
52
(physical activities, diet and smoking)” (Levesque et al., 2007, p. 693). “The results of the CFA for all data sets were acceptable and the factor loadings for all models were significant (z > 1.96)” (Levesque et al., 2007, p. 697). The construct validity of the TSRQ was examined through the correlations between the subscales of the instrument and health outcomes (Levesque et al., 2007). Levesque et al. (2007) reported a Cronbach alpha of 0.73 to 0.93 for two of the subscales (autonomous motivation and controlled amotivation). In addition, two of the three subscales to measure amotivation were found to have a Cronbach alpha of 0.73-0.79 (Levesque et al., 2007).
Perceived Competence Scale (PCS). The Perceived Competence Scale (PCS) aims to understand how people feel about following healthy behaviors. The PCS is a short, 12-item questionnaire that assesses the “degree to which individuals feel confident about being able to make (or maintain) a change toward healthy behaviors, participate in a health-care program, or carry out a treatment regimen” (Williams et al., n.d., p. 1). The
PCS has three sections of the questionnaire that aim to understand how people feel about their confidence and ability to engage and follow healthy behavior, which is known as people perceived competence (Williams et al., n.d.). The PCS focuses on three health behaviors, which are physical activities, eating healthy diet, and smoking (Williams et al., n.d.). Each of the three health behaviors has four items Williams et al., n.d.). People who tend to have better competence in managing their health behaviors were more likely to have a better health status (Williams et al., n.d.). For example, the study conducted by
Williams et al. (2006), which showed when patients have better competence satisfaction, they were more likely to quit smoking and have better health. Each PCS item is measured
53 with a 7-point Likert-scale ranging from; (1= Not at all to 7= very True) (Williams et al., n.d.).
Williams and Deci (1996) established construct validity for PCS using factor analysis. The PCS for smoking cessation was correlated to autonomy support from health providers (Williams, Freedman, & Deci, 1998). The Cronbach alpha reliability was 0.94
(Williams & Deci, 1996). Furthermore, concurrent validity of the PCS was established in the study by Williams et al. (1998) with high correlation with glucose (HbA1c). The
Cronbach alpha reliability was 0.90 (Williams et al., 1998).
Relatedness to Others in Physical Activity Scale (ROPAS). The ROPAS is a 6 item, self-report instrument designed to measure perceived relatedness under SDT
(Wilson & Bengoechea, 2010). Each of the 6 item is measured with 6-point Likert-scale ranging from; (1= False to 6= True). Wilson and Bengoechea (2010) published the results of two of their studies in one article to establish validity and reliability of the ROPAS. In the first study, CFA supported the construct validity of a 6-item ROPAS measurement model. The Cronbach alpha reliability ranged from 0.89 to 0.93 (Wilson & Bengoechea,
2010). In the second study, the results of multiple regression provided further support to relationship between ROPAS perceived autonomy, competence and high well-being
(Wilson & Bengoechea, 2010). The Cronbach alpha reliability ranged from 0.70 to 0.97
(Wilson & Bengoechea, 2010).
Four item MGL Medication adherence scale. The four-items Morisky, Green, and Levine (MGL) adherence scale is a self-report questionnaire aims to assess medication adherence (Morisky, Green, & Levine, 1986). This scale provides information about patients’ level of compliance in taking their medication as prescribed by their
54 health providers (Morisky et al., 1986). According to Morisky et al. (1986) “ the theory underling this measure was that drug error of omission could occur in any or all of several ways; forgetting, carelessness, stop the drug when feel better or starting the drug when feeling worse” (p. 69).
This MGL (4-itme) adherence scale has four items. Each item has two possible responses (Yes= 0, No= 1) (Morisky et al., 1986). The total score of this scale ranges from 0 to 4 (Morisky et al., 1986). Higher number indicate better medication adherence
(Morisky et al., 1986). Specifically, a score of 0 will indicate low/poor medication adherence, a score of 1 or 2 would indicate medium medication adherence and a score of
3 or 4 will indicate high medication adherence (Morisky et al., 1986).
According to Morisky et al. (1986), the MGL (4-itme) adherence scale is a valid and reliable instrument to measure medication adherence. Predictive and concurrent validity was established by examining a group of patients with HTN and the relationship between the MGL (4-itme) adherence score and patient’s blood pressure (Morisky et al.,
1986). Morisky et al. (1986) reported a significant association between the MGL (4-itme) adherence score and blood pressure control at 6-month follow-up. That is patients with high medication adherence had normal blood pressure. “The point biserial correlation was equal to 0.43 (p <0.01)” (Morisky et al., 1986, p. 71). At 42 months this association was even stronger. Specifically, patients with high medication adherence were more likely to have normal blood pressure compared to patients who had poor medication adherence (r= 0.58; p > 0.01) (Morisky et al., 1986). Finally, the Cronbach alpha reliability was 0.61 (Morisky et al., 1986).
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Instrument translation process. After reviewing the literature and the SDT website, no Arabic versions of the TSRQ, PCS, ROPAS or, MGL (4 items) medication adherence scale were found to exist. Thus, the instruments were translated into Arabic.
The researcher used the back-translation technique because it allows comparison of the original source language with the back-translation (Duffy, 2006). According to Beaton,
Bombardier, Guillemin, and Ferraz (2000), two forward translations need to be conducted by two translators who have knowledge of both languages. In this study, two independent translators completed the translation and back-translation process. Both were bilingual experts and fluent in both Arabic and English. The first translator translated the instruments from English to Arabic. Then the second translator re-translate the Arabic version back to English. Then a native English expert compared the back-translated instruments (English) with the original tool in English to determine errors or discrepancy of meanings. The final Arabic version of the TSRQ, PCS, ROPAS, and MGL (4 items) were used to collect data.
Protection of Human Subjects
Both IRB approval from the University of Akron and MCC were obtained before starting the data collection phase. All study participants received a letter about the study in the MCC clinic. Before participating in the study, the research assistant explained to the participants that participation in the study was voluntary and if they experience discomfort at any time, they may stop and withdraw from the study. The researcher and research assistant explained the rights of being research participants to the patients. These rights included that participants will not face any physical or psychological dangers. All participants received a written consent form. The researcher and research assistant
56 explained that signing the consent forms mean that patients agreed to participate in the study. They also were informed that all the results of this study will be reported anonymously and that no one will be identified.
Maintaining Confidentiality and Anonymity
Participants were not required to identify themselves on the survey, and all data were stored in the researcher’s office at MCC in a locked file cabinet. To maintain confidentiality, all the online surveys taken on the iPads and papers were anonymous and no names were required. All obtained data were saved in the online iCloud and on the
USB, and only the researcher has access to them. The researcher’s computer, iPads, USB drive, and the online iCloud had a secure password.
Rights and Privacy
In this study, the researcher addressed three principles relating to the moral standards of research involving human subjects. These standards were created by the
National Commission for the Protection of Human Subjects of Biomedical and
Behavioral Research in 1978 (The Belmont Report, 1978). The three principles are
“respect for persons, beneficence, and justice” (The Belmont Report, 1978, p. 4).
Summary
A study using a cross-sectional descriptive exploratory correlational design with a convenience sample of 121 Middle Eastern patients diagnosed with CAD was conducted.
The study aimed to explore the levels of the perceived psychological needs (autonomy, competence, and relatedness) for health behaviors and self-report medication adherence of patients with CAD in Saudi Arabia. In addition, this study aimed to assess the relationships among perceived psychological needs (autonomy, competence, and
57 relatedness) for health behaviors and medication adherence. The study was conducted at
MCC in Saudi Arabia, and the data was collected using a survey comprised of five parts, namely demographic, TSRQ, PCS, ROPAS, and MGL (4 items). These questionnaires were entered in to Qualtrics online software and answered via iPads by participants. Data was exported and screened for any missing data or outliers.
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CHAPTER IV
STUDY RESULTS
This study served two purposes: First, the study set out to explore the levels of perceived psychological needs (autonomy, competence, and relatedness) for health behaviors and medication adherence of patients with CAD in Saudi Arabia. Second, it sought to establish and assess the relationships among perceived psychological needs
(autonomy, competence, and relatedness) for health behaviors and medication adherence.
The study examined the following questions:
Among patients with CAD in Saudi Arabia:
1. What is the level of perceived autonomy for patients’ physical activity, diet,
and smoking?
2. What is the level of perceived competence for patients’ physical activity, diet,
and smoking?
3. What is the level of perceived relatedness for patients’ physical activity?
4. What is the level of self-reported medication adherence?
5. What are the relationships among CAD patients’ perceived psychological
needs (autonomy, competence, and relatedness) for health behaviors and
medication adherence?
H1 5A: An increase of perceived autonomy for health behaviors will increase
medication adherence.
H1 5B: An increase of perceived competence for health behaviors will
increase medication adherence.
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H1 5C: An increase of perceived relatedness for physical activity will increase
medication adherence.
6. Do perceived autonomy, competence, and relatedness for health behaviors
explain medication adherence?
Data Management
Data Entry
A total of the 121 subjects consented to participant in the study and subsequently completed the study survey. The majority of them (n = 93) used the iPads’ “Qualtrics” application as compared to those who completed a paper survey (n = 28). Data on the paper survey were manually entered into Qualtrics and then all data were exported from
Qualtrics software into the Statistical Package for the Social Sciences IBM SPSS
Statistics Base 24.
Data Screening
After exporting data into an SPSS data set, descriptive statistics were used to detect any missing data by examining frequency distribution tables, as recommended by
Tabachnick and Fidell (2007). Also, descriptive statistics were used to describe the demographic characteristics of the sample. No missing data on the study variables were identified, and by examining the boxplots, no outliers were found.
Characteristics of Study Sample
Demographic Data
Table 4 displays study participants’ demographic data. The study consisted of
121 participants; two thirds were males. The majority of study participants were married and had a high school degree or less as their highest level of education. A quarter of the
60 subjects were employed. The rest of the subjects were unemployed or retired. They had a mean of 44 months since the time they were diagnosed with CAD.
Table 4
Demographic Characteristics
Measure n M (SD) Age (Years) 121 57.85 (10.9) Time since Diagnosis with 121 43.93 (55.8) CAD (Months) Measure n % Gender Male 81 66.9 Female 40 33.1 Marital Status Single 6 5.0 Married 103 85.1 Divorced 2 1.7 Widowed 10 8.3 Level of education No schooling completed 6 5.0 High School or less 73 60.3 Undergraduate 40 33.1 Graduate 2 1.7 Employment Status Employed 31 25.6 Unemployed 33 37.3 Retired 57 47.1
61 iPads vs. Paper Demographic Characteristics
Table 5 displays the differences between survey type (iPads vs. paper) used by study participants in terms of their demographic information. As stated earlier, the majority of study participants used the iPad survey. However, there were 28 participants who preferred to use the paper surveys. Of these 28, the majority were married females who were unemployed with education level at high school or less.
For continuous variables, Independent Samples t-test was performed to examine the differences in age and time since diagnosis with CAD between the two groups. The test revealed that only the participants’ age was statistically significant. Participants who chose to use paper surveys were slightly older. For categorical variables, Chi-square tests were performed to examine any differences between the two groups. The tests revealed statistically significant differences between the two groups, specifically gender and employment status. There were more males in the iPad survey group and more females in the paper survey group. There were also more participants who indicated “no school completed” in the paper survey group. For employment status, there were more retired participants in the iPad group and more unemployed in the paper survey group.
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Table 5
Demographic Characteristics of Survey Types
Measure iPad (n=93) Paper (n=28) p M (SD) M (SD) Age (year) 56.68 (10.5) 61.75 (11.5) .03 Time since CAD 40.51 (37.8) 55.29 (93.6) .42 diagnosis (month) Measure iPad (n=93) Paper (n=28) n (%) n (%) Gender .01 Male 72 (77) 9 (32) Female 21 (22) 19 (68) Marital status .56 Single 6 (6.5) -- Married 80 (86) 23 (82.1) Divorced 2 (2.2) -- Widowed 5 (5.4) 5 (17.9) Level of education .12 No schooling 1 (1.1) 5 (17.9) completed High school or less 56 (60.2) 17 (60.7) Undergraduate 34 (36.6) 6 (21.4) Graduate 2 (2.2) -- Employment status <.01 Employed 30 (32.3) 1 (3.6) Unemployed 15 (16.1) 18 (64.3) Retired 48 (51.6) 9 (32.1) Note. The marital status and education level categories have several cells with expected count less than 5. These two categories were collapsed into 2 X 2 tables (Married status
63 versus single/divorced/widowed; no schooling to high school education versus undergraduate/graduate education) and then analyzed with Fisher's exact tests.
Reliability of Study Instruments
A total of three instruments were used to measure the study’s independent variables. First, the Treatment Self-Regulation Questionnaire (TSRQ) was used to examine patients’ perceived autonomy in physical activity (PA-PA), perceived autonomy in diet (PA-Diet), and perceived autonomy in smoking (PA-Smoking). Second, the
Perceived Competence Scale (PCS) was used to assess patients’ perceived competence in physical activity (PC-PA), perceived competence in diet (PC-Diet), and perceived competence in smoking (PC-Smoking). Third, the Relatedness to Others in Physical
Activity Scale (ROPAS) was used to examine perceived relatedness in physical activity
(PR-PA). The dependent variable, medication adherence, was measured using the four- item scale MGL (4 items). All of the instruments were translated into Arabic prior to the beginning of the study. As a result, the following reliability analysis report is for the
Arabic version of each instrument (Table 6).
All instruments measuring the independent variables showed high reliability
(Cronbach’s α > 0.85) but the instrument measuring the dependent variable, medication adherence, showed low reliability (α = 0.58). Further examination revealed that removing item number four (“Sometimes if you feel worse when you take the medicine, do you stop taking it?”) from the MGL (4 items) scale increased the Cronbach’s alpha reliability to 0.61, which is similar to the Cronbach’s alpha reliability reported for the original
English version of this instrument (Morisky et al., 1986). Due to the reliabilty change, to answer research question 6, multiple regression was conducted twice with the MGL (4
64 items), and with the MGL (3 items). This strategy examined whether or not the multiple regression yielded different results.
Table 6
Reliability Test Table Instrument Name Number of Items Cronbach's Alpha TSRQ (PA-PA) 6 0.87 TSRQ (PA-Diet) 6 0.86 TSRQ (PA-Smoking) 6 0.89 PCS (PC-PA) 4 0.93 PCS (PC-Diet) 4 0.90 PCS (PC-Smoking) 4 0.97 ROPAS (PR-PA) 6 0.94 MGL (4 items) 4 0.58 MGL (3 items) 3 0.61
Reliability of iPads vs. Paper Surveys
Reliability testing was also conducted to examine the differences between the reliability of the iPads and the paper surveys and was comparable between the groups
(Table 7). All instruments measuring the study’s independent variables exceeded a
Cronbach’s alpha of 0.82. The instrument measuring the study’s dependent variable had a lower Cronbach’s alpha in the paper survey group with MGL (4 items). As for the MGL
(3 items), Cronbach’s alphas for the groups were comparable (Table 7).
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Table 7
Reliability Test of iPads and Paper Surveys
Cronbach’s Alpha Instrument Name Number of Items iPads Paper TSRQ (PA-PA) 6 0.86 0.89 TSRQ (PA-Diet) 6 0.88 0.82 TSRQ (PA-Smoking) 6 0.90 0.84 PCS (PC-PA) 4 0.93 0.89 PCS (PC-Diet) 4 0.91 0.87 PCS (PC-Smoking) 4 0.98 0.97 ROPAS (PR-PA) 6 0.93 0.94 MGL (4 items) 4 0.61 0.46 MGL (3 items) 3 0.61 0.62
Analysis of the Research Questions
Research question 1. What is the level of perceived autonomy for patients’ physical activity, diet, and smoking?
To answer this question, descriptive statistics were conducted using the data collected from the 121 participants. The possible range of the level of perceived autonomy was 6-42. A higher number indicates higher perceived autonomy. The mean of
PA-PA was 33.8 (SD = 7.44), and the median was 36 with the subject scores ranging from 14 to 42. The mean of PA-Diet was 34.6 (SD = 7.22), and the median was 36 with the subject scores ranging from 12 to 42. The mean of PA-Smoking was 38.3 (SD =
6.38), and the median was 42 with the subject scores ranging from 6 to 42.
Each participant’s responses on the subscales of the TRSQ scale can be averaged.
By doing this, individual’s score can be compared to the original scaling of 1 = not at all
66 true to 7 = very true in the TRSQ. The mean of the PA-PA subscale was 5.6 with the median of 6 and standard deviation of 1.2. The mean of the PA-Diet subscale was 5.8 with the median of 6 and standard deviation of 1.2. The mean of the PA-Smoking subscale was 6.4 with the median of 7 and standard deviation of 1.1.
Research question 2. What is the level of perceived competence for patients’ physical activity, diet, and smoking?
To answer this question, descriptive statistics were also conducted using the data collected from the 121 participants. The possible range score of perceived competence was 4-28. A higher number indicates higher perceived competence. The mean of the PC-
PA was 15.5 (SD = 7.33), and the median was 16 with the subject scores ranging from 4 to 28. The mean level of PC-Diet was 17.2 (SD = 7.10), and the median was 17 with the subject scores ranging from 4 to 28. The mean level of PC-Smoking was 23.2 (SD =
8.36), and the median was 28 with the subject scores ranging from 4 to 28.
Each participant’s responses on the four items of the PCS can also be averaged.
By doing this, individual’s score can be compared to the original scaling of 1 = not at all true to 7 = very true in the PCS. The mean of the PC-PA subscale was 3.9 with the median of 4 and standard deviation of 1.8. The mean of the PC-Diet subscale was 4.3 with the median of 4.3 and standard deviation of 1.8. The mean of the PC-Smoking subscale was 5.8 with the median of 7 and standard deviation of 2.1.
Research question 3. What is the level of perceived relatedness for patients’ physical activity?
To answer this question, descriptive statistics were also conducted using the data collected from the 121 participants. The possible range of scores for perceived
67 relatedness for patients’ physical activity was 6-36. A higher number indicates higher perceived relatedness for patients’ physical activity. The mean of PR-PA was 24.3 (SD
=9.66), and the median was 28 with the subject scores ranging from 6 to 36.
Each participant’s responses on the six items of the ROPAS can also be averaged.
By doing this, individual’s score can be compared to the original scaling of 1 = false to 6
= true. The mean of the perceived relatedness to others in physical activity was 4.1 with the median of 4.7 and standard deviation of 1.6.
Research question 4. What is the level of self-reported medication adherence?
For this question, the analysis was conducted in two different ways. First, descriptive statistics were conducted using the data collected from the 121 participants.
The analysis was conducted based on the original analysis published by (Morisky et al.,
1986). The MGL (4 items) measured the level of medication adherence. Each of the four items had two possible responses (Yes = 0, No = 1) (Morisky et al., 1986). If a participant answered “No” to all four items, the value of medication adherence would be 4 out of 4.
The possible range for the medication adherence score was 0-4. As stated in Chapter 3, a higher number indicates better medication adherence (Morisky et al., 1986). Specifically, a total score of 3 or 4 indicates high medication adherence, while a score of 1 or 2 indicates medium medication adherence, and a score of 0 indicates low/poor medication adherence (Morisky et al., 1986). The mean of the self-reported, MGL (4 items), medication adherence in this study was 2.2 (SD= 1.27), and the median was 2 with the subject scores ranging from 0 to 4.
Second, the frequency of how many times patients answered “No” was calculated to indicate the level of medication adherence (Table 8). Around half of the study
68 participants had high medication adherence at 47.1%, followed by 40.5% who had medium medication adherence, and slightly more than 10% had low medication adherence.
Table 8
Level of Medication Adherence
Number of items answered by (NO) Frequency % Low 0 15 12.4 Medium 1 23 19.0 2 26 21.5 High 3 37 30.6 4 20 16.5
Research question 5. What are the relationships among CAD patients’ perceived psychological needs (autonomy, competence, and relatedness) for health behaviors and medication adherence?
Research hypotheses. This question has three hypotheses, first an increase of perceived autonomy for health behaviors will increase medication adherence. Second, an increase of perceived competence for health behaviors will increase medication adherence. Third, an increase of perceived relatedness for physical activity will increase medication adherence. To answer this question and examine these hypotheses using
Pearson’s r test, several assumptions needed to be examined first.
Statistical assumptions. The Pearson r correlation test was performed on continuous variables and no outliers were identified. Other important Pearson r correlation assumptions included; (a) normality, (b) linearity, and (d) homoscedasticity
(Mertler & Vannatta, 2013).
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Normality. According to Mayers (2013), one method to check normality beside visual examination of graphs is calculating the z score of the skew and kurtosis for each variable. For studies using a small sample size (i.e., < 50), a z-score between ± 1.96 for both skewness and kurtosis would be considered acceptable to assume a normal distribution (Mayers, 2013; Kim, 2013). If the sample size was between 51 and 100 participants, a z-score between ± 2.58 for both skewness and kurtosis would be considered acceptable to assume a normal distribution, and a z-score between ± 3.29 for both skewness and kurtosis would be considered acceptable for a sample size of more than 100 (Mayers, 2013). For this current study with 121 subjects, a skewness and kurtosis z score of ± 3.29 was used to assess the assumption of normality in each variable. Table 9.1 presents z scores of skewness and kurtosis for research variables.
Table 9.1
Z-score of Skewness and Kurtosis (Non-Transformed Variables)
Skewness Kurtosis Variable Name Stat SE z-score Stat SE z-score PA-PA -.855 .220 -3.88 -.126 .437 -0.28 PA-Diet -.880 .220 -4 .181 .437 0.41 PA-Smoking -2.63 .220 -11.99 8.26 .437 18.90 PC-PA .016 .220 0.07 -.911 .437 -2.08 PC-Diet -.230 .220 -1.04 -.718 .437 -1.64 PC-Smoking -1.46 .220 -6.64 .498 .437 1.13 PR-PA -.613 .220 -2.78 -.952 .437 -2.17 MGL (4 items) -.258 .220 -1.17 -1.012 .437 -2.31
According to the z-scores in Table 9.1, four of the study’s independent variables
(PA-PA, PA-diet, PA-Smoking, and PC-Smoking) had z scores of skewness greater than
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± 3.29 indicating non-normal distribution. PA-Smoking was severely negatively skewed, followed by PC-Smoking, PA-Diet, and PA-PA. For severely negatively skewed data to become normally distributed, Mertler and Vannatta, (2013) recommend to perform a reflection on the negatively skewed data and then apply a square root transformation.
“Reflection involves finding the largest score in the distribution and adding 1 to it to form a constant that is larger than any score in the distribution” (Mertler & Vannatta, 2013, p.
33). Thus, the values of these four variables were reflected before applying a square root transformation to each value. Table 9.2 presents the z scores of skewness and kurtosis of the four transformed independent variables.
Table 9.2
Z-score of Skewness and Kurtosis (Transformed Variables) Skewness Kurtosis Variable Name Stat SE z-score Stat SE z-score PA-PA .226 .220 1.02 -.976 .437 -2.23 PA-Diet .237 .220 1.07 -1.09 .437 -2.49 PA-Smoking .734 .220 3.33 -.806 .437 -1.84 PC-Smoking 1.24 .220 5.63 -.192 .437 -0.43
The reflected square root transformation achieved a normal distribution for PA-
PA and PA-Diet. However, the transformation failed to obtain a normal distribution for
PA-Smoking and PC-Smoking due to the extreme left skew because most subjects chose the far-right items, “very true,” in their responses to questions about their perceived competence in not smoking.
Linearity. Linearity “presupposes that there is a straight-line relationship between two variables” (Mertler & Vannatta, 2013, p. 34). The assumption of linearity was checked by inspecting the bivariate scatterplots between the dependent variable and each
71 independent variable. Each scatterplot appeared to show a linear relationship, which satisfied this assumption.
Homoscedasticity. The assumption of homoscedasticity is that the “variability in scores for one continuous variable is roughly the same at all values of another continuous variable” (Tabachnick & Fidell, 2007, p. 85). The assumption of homoscedasticity was checked by examining the scatterplots between residuals and predicted. They all have similar width, thereby indicating homoscedasticity.
The Correlation between Study Variables
Due to some issues in the distribution of normality as mentioned above, parametric (Pearson’s product moment correlation coefficient) and non-parametric
(Spearman’s rank correlation coefficient) tests were conducted to examine the relationships between study variables when appropriate. Pearson and Spearman correlations have similar thresholds for interpretation; values of -1 or +1 represent perfect correlation, and values of 0 represent no correlation between the variables (Mayers,
2013). The strength of both Pearson and Spearman correlations can be interpreted using
Cohen’s (1988) recommendations. According to Cohen (1988), there are three sizes of a correlation coefficient. They are: weak (less than ± .30), moderate (between ± .30 and ±
.50), and strong (more than ± .50).
Pearson’s r correlation. The Pearson’s r was conducted using the original variables (PC-PA, PC-Diet, and PR-PA) that were normally distributed and the dependent variables (MGL 4-items). The Pearson’s r results appear in Table 10.1. All variables were positively correlated. However, only two (PC-PA, PC and Diet) of the study’s independent variables were correlated with the dependent variable, but the
72 correlations were weak. This indicates that patients with high PC-PA and PC-Diet are more likely to have better medication adherence.
The test revealed a moderately positive correlation between PC-Diet and PC-PA.
Also, the PR-PA was moderately positive correlated with PC-PA and PC-Diet. They are
PC-PA and PC-Diet: Both are positively weak correlated with medication adherence
MGL (4 items).
Table 10.1
Pearson r Correlations
Measure 1 2 3 4 1.dMGL (4 items) ---- 2. PC-PA .154* ---- 3. PC-Diet .179* .435** ---- 4. PR-PA .036 .436** .420** ---- M 2.2 15.5 17.2 24.3 SD 1.27 7.33 7.10 9.66 Note. **p < 0.01. *p < 0.05
Spearman’s rho correlation. The relationships between the four non-normally distributed, non-transformed variables (PA-PA, PA-Diet, PA-Smoking, PC-Smoking) and the dependent variable medication adherence, (MGL-4 item) were examined using the Spearman’s rho test (Table 10.2). All variables were positively correlated. Only two
(PA-PA and PA-Diet) of the four independent variables were significantly positively correlated with the dependent variable, although the correlation was weak.
In regard to the relationships among the independent variables, the strongest correlation was between PA-PA and PA-Diet, followed by PA-Smoking and PC-
73
Smoking, and PA-PA and PA-Smoking. This indicates that patients with high PA-PA and
PA-Diet are correlated with better medication adherence on the survey tools.
Table 10.2
Spearman's rho Correlation
Measure 1 2 3 4 5 1. MGL (4 items) ---- 2. PA-PA .219** ---- 3. PA-Diet .178* .695** ---- 4. PA-Smoking .132 .386** .281** ---- 5. PC-Smoking .106 .076 .093 .480** ---- M 2.2 33.8 34.6 38.3 SD 1.27 7.44 7.22 6.38 Note. **p < 0.01. *p < 0.05
Research question 6. Do perceived autonomy, competence, and relatedness for health behaviors explain medication adherence?
To answer this question using multiple linear regression, several assumptions needed to be examined first.
Statistical assumptions. The assumptions of multiple linear regression were examined prior to performing the test. The first assumption to be examined is normality of errors. Before checking for normality of errors after modeling, a second look at the distribution of the independent variables provides a good idea about the data. As indicated before, four of the independent variables were not normally distributed, therefore, the reflected square root transformation was applied. However, the transformation failed to obtain a normal distribution for two independent variables, PA-
Smoking and PC-Smoking. The assumption of normality after modeling was checked
74 both graphically (using histograms and Q-Q plots) and using hypothesis tests
(Kolmorogov-Smirnov and Shapiro-Wilk). This was done for each of the 4 models. The models using the MGL (3-item) scale as the dependent variable showed strong departures from normality (Kolmogorov-Smirnov and Shapiro-Wilk tests of the residuals were both significant, and histograms of the residuals showed two peaks). The models using the
MGL (4-item) scale as the dependent variable showed borderline acceptable normality
(non-significant Kolmogorov-Smirnov test) as well as acceptable histograms.
The assumption of linearity was checked by examining the residuals plots, as well as by inspecting the bivariate scatterplots. Each scatterplot appeared to show a linear relationship, which satisfied this assumption. Other important assumptions for multiple linear regressions included multicollinearity and independent errors.
Multicollinearity. Multicollinearity was examined by looking at the value of variance inflation factors (VIF) for each predictor as recommended by Mertler and
Vannatta, (2013). According to Mertler and Vannatta (2013), “VIF value that are greater than 10 are generally cause of concern” (p. 167). In this study, the highest VIF value was
2.54 (PA-Diet). Hence, no multicollinearity occurred in the study variables.
Independent errors. The assumption of independent errors was examined by conducting Durbin–Watson test. The Durbin–Watson test value needed to be close to 2, which means that no correlation exists between residuals (Mayers, 2013). The Durbin–
Watson test value was 1.932, which is close to 2. As such, the assumption of independent errors was met.
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Multiple Linear Regression Analysis
After examining the assumptions, four multiple linear regression analyses were conducted due to non-normal distribution of four independent variables and slightly improvement in reliability of the MGL (3 items) comparing to the MGL (4 items). The intent was to understand whether any of the models explain the variance of the dependent variable (medication adherence). The four regression analyses were (1) non- transformed independent variables and the MGL (4 items) as dependent variable, (2) non-transformed independent variables and the MGL (3 items) as dependent variable, (3) four transformed and three non-transformed independent variables and the MGL (4 items) as dependent variable, and (4) four transformed and three non-transformed independent variables and the MGL (3 items) as dependent variable. Each of the analyses is presented in the sections below.
Multiple regression result of the original variables and the MGL (4 items). A multiple linear regression was conducted to explain medication adherence based on PA-
PA, PA-Diet, PA-Smoking, PC-PA, PC-Diet, PC-Smoking, and PR-PA (Table 11). The regression results showed that the independent variables only explained 7.5% of the variance of the 4-items medication adherence scale, F(7,113) = 1.302, p = .256, R2 = .075,
R2 adj = .017. Also, the test revealed that none of the independent variables were significant predictors for the dependent variable.
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Table 11 Predictors of Medication Adherence Medication adherence MGL (4 items) Variable B SE B b 95% CI for B Constant .539 .823 [-1.09, 2.16] PA-PA .018 .021 .106 [-0.02, 0.06] PA-Diet .008 .024 .044 [-0.04, 0.05] PA-Smoking .007 .023 .034 [-0.03, 0.05] PC-PA .014 .020 .079 [-0.02, 0.05] PC-Diet .016 .022 .091 [-0.02, 0.06] PC-Smoking .019 .017 .123 [-0.01, 0.05] PR-PA -.017 .014 -.128 [-0.04, 0.01] R2 .075 F 1.302 Note. N =121. CI= confidence interval.
Multiple regression result of the original variables and the MGL (3 items). A multiple linear regression was also conducted to explain medication adherence using the
MGL (3 items) based on PA-PA, PA-Diet, PA-Smoking, PC-PA, PC-Diet, PC-Smoking, and PR-PA (Table 12). The regression results showed that the independent variables only explained 6.2% of the variance of the 3-item medication adherence scale, F(7,113) =
1.062, p = .392. R2 = .062, R2 adj = .004. Similar to the previous analysis that used the
MGL (4 items), none of the independent variables were significant predictors for the dependent variable.
Table 12 Predictors of Medication Adherence Medication adherence MGL (3 items)
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Variable B SE B b 95% CI for B Constant .597 .694 [-0.77, 1.97] PA-PA .003 .018 .022 [-0.03, 0.03] PA-Diet .006 .020 .038 [-0.03, 0.04] PA-Smoking .004 .019 .025 [-0.03, 0.04] PC-PA .005 .017 .033 [-0.02, 0.03] PC-Diet .027 .018 .177 [-0.01, 0.06] PC-Smoking .012 .015 .095 [-0.01, 0.04] PR-PA -.011 .012 -.103 [-0.03, 0.01] R2 .062 F 1.062 Note. N =121. CI= confidence interval.
Multiple regression result for the transformed variables and the MGL (4 items). A multiple linear regression was conducted to explain medication adherence based on PA-PA (t), PA- Diet (t), PA-Smoking (t), PC-PA, PC-Diet, PC-Smoking (t), and
PR-PA (Table 13). The regression results showed that the independent variables only explained 7.4% of the variance of the 4-items medication adherence scale, F(7,113) =
1.291, p = .261, R2 = 074, R2 adj = .017. Also, the test revealed that none of the independent variables were significant predictors for the dependent variable.
Table 13 Predictors of Medication Adherence Medication adherence MGL (4 items) Variable B SE B b 95% CI for B Constant .597 .136 [1.09, 4.30] PA-PA (t) -.135 .144 -.133 [-0.40, 0.13] PA-Diet (t) -.017 .323 -.017 [-0.30, 0.26] PA-Smoking(t) -.084 .020 -.031 [-0.72, 0.55] PC-PA .012 .022 .072 [-0.02, 0.05]
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PC-Diet .018 .097 .102 [-0.02, 0.06] PC-Smoking (t) -.092 .014 -.107 [-0.28, 0.10] PR-PA -.016 .136 -.120 [-0.04, 0.01] R2 .074 F 1.291 Note. N =121. CI= confidence interval. (t) = transformed variable
Multiple regression result for the transformed variables and the MGL (3 items). A multiple linear regression was conducted to explain medication adherence using the MGL (3 items) based on PA-PA (t), PA- Diet (t), PA-Smoking (t), PC-PA, PC-
Diet, PC-Smoking (t), and PR-PA (Table 14). The regression results showed that the independent variables only explained 6.0% of the variance of the 3-items medication adherence scale, F(7,113) = 1.027, p = .417, R2 = .060, R2 adj = .002. Also, the test revealed that none of the independent variables were significant predictors for the dependent variable.
Table 14
Predictors of Medication Adherence
Medication adherence MGL (3 items) Variable B SE B b 95% CI for B Constant 1.62 .685 [0.26, 2.98] PA-PA (t) -.058 .115 -.068 [-0.28, 0.17] PA-Diet (t) -.008 .122 -.010 [-0.24, 0.23] PA-Smoking(t) .028 .272 -.012 [-0.51, 0.56] PC-PA .003 .017 .018 [-0.03, 0.30] PC-Diet .029 .019 .191 [-0.00, 0.06] PC-Smoking (t) -.068 .082 -.095 [-0.23, 0.09] PR-PA -.011 .012 -.095 [-0.03, 0.01] R2 .060
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F 1.027 Note. N =121. CI= confidence interval. (t) = transformed variable
Summary
This chapter presented the answers to research questions after collecting data from Madinah Cardiac Center (MCC) in Saudi Arabia. Descriptive statistics indicated that about 67% of the participants were men, more than 80% were married, and the average age was 57.85 years. In addition, close to half of participants were retired with a high school degree or less as their highest level of education. The participants average time since diagnosis with CAD was 3.5 years. The majority of study participants (n= 93) used the iPad survey compared to the paper type of survey (n = 28). Moreover, there were some demographic differences in age, gender, level of education, and employment status between participants who used the iPad survey vs. the paper survey.
All translated study instruments were reliable with Cronbach’s alpha of 0.86 or higher except for the MGL (4 items), where Cronbach’s alpha was 0.58. With this, one item was removed from the MGL (4 items) to increase the Cronbach’s alpha to 0.61, which was consistent with the original MGL (4 items) reliability reported by (Morisky et al., 1986). Four variables were transformed due to normality issues (PA-PA, PA-Diet,
PA-smoking, and PC-Smoking).
The results of the study suggest that patients with CAD have high autonomy for their health behaviors. The level of perceived competence for health behaviors was medium for both PC-PA and PC-Diet as well as high for PC-Smoking. Participants also had medium level of PR-PA. Finally, close to half of the study participants had high medication adherence.
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The result of Spearman’s rho showed a weak positive correlation between MGL
(4 items) and both PA-PA and PA-diet. While Pearson’s r test showed weak positive correlation between MGL (4 items) and both PC-PA and PC-Diet. The multiple regressions yielded no significant results, therefore indicating that none of the independent variables explain the dependent variable. The models using the MGL (3- item) scale as the dependent variable showed strong departures from normality. However, the models using the MGL (4-item) scale as the dependent variable showed borderline acceptable normality. More details and discussion about the result of this study will be presented in the next chapter.
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CHAPTER V
DISCUSSION
This study was conducted to explore two areas of interest. First, the study was designed to explore the levels of perceived psychological needs (autonomy, competence, and relatedness) for health behaviors and medication adherence of patients with CAD in
Saudi Arabia. Second, it sought to assess the relationships among perceived psychological needs (autonomy, competence, and relatedness) for health behaviors and medication adherence.
This chapter presents a detailed discussion of the major findings, followed by a discussion of the strengths and limitations of the study. This chapter concludes with the implications of the study findings for health practice and recommendations for future research.
Review and Discussion of Findings
Demographics
Overall the sample in this study was closely representative of the target population (CAD patients in Saudi Arabia). In this study, 67% of the study subjects were males. During the period of data collection, March 10 to April 30, the majority of potential participants who met the study inclusion criteria were men (n = 750, 71.7%) compared to women (n = 296, 28.3%) according to the Department of Information
Technology (IT) at Madinah Cardiac Center (MCC). According to the Statistical
Yearbook published by the Saudi Ministry of Health (MOH), the total number of patients diagnosed with CAD who visited the emergency department in 2015 was around 153,500
82 and gender break down was men (n = 88,514, 57.6%) and women (n = 65,040, 42.4%)
("Statistical Yearbook 1436H," 2015). Moreover, in a study conducted by Al Ahmari et al. (2017) with patients from King Abdul Aziz Hospital in Saudi Arabia, the prevalence of CAD for men was twice as high as women.
Although the overall the sample is similar to the target population, there are some differences within the study sample in their preference for completing the survey (iPads versus paper). The majority of participants who chose to use paper surveys were women who were older and unemployed. This finding suggests that electronic tablet-based data collection methods, such as using iPads to collect the data, may not be appropriate for some participants who were not familiar with electronic tools (iPads) (Handfield, 2017).
Participants’ age could be a contributing factor for subjects who preferred the paper survey method due to the fact that some elderly patients were not familiar with iPads or their use. Elderly is defined as “a chronological age of 65 years old or older” (Orimo et al., 2006, p. 149). Around 64% of participants who used the paper survey in this current were > 60 years old. The reason may not be related to their age; however, it may be related to their lack of familiarity with the use of iPads.
It is not fully clear why more women (64%) in this current study preferred to complete the paper survey, as no question about their reason for choosing the paper survey was asked in the data collection phase. Handfield (2017) mentioned that some participants who preferred to complete the paper survey may have had a “lack of familiarity with electronic tools” (p. 1). Finally, 64% of subjects who preferred the paper survey method were unemployed. Still, the reason that the majority of participants who preferred the paper survey were unemployed is unknown. Therefore, having a paper
83 survey method for patients who did not prefer or were not familiar with the use of electronic tools (iPads) was necessary because it allowed more individuals to participate in this study.
Levels of Perceived Psychological Needs for Health Behaviors
The first aim of this study was to measure the levels of the perceived psychological needs (PPN) (autonomy, competence, and relatedness) for health behaviors. Information about the levels of PPN in health behaviors will help healthcare providers understand the status of PPN among patients with CAD in Saudi Arabia since patient’s autonomy, competence, and relatedness for health behaviors are essential needs in patients’ health (Ryan & Deci, 2017). High levels of perceived autonomy, competence, and relatedness for health behaviors are expected to lead to better health behaviors, which could eventually lead to better health outcomes (Ryan & Deci, 2017).
Studies have been conducted to measure the levels of PPN for different health behaviors and health conditions. Some studies measured the levels of perceived autonomy, competence and relatedness in health behaviors such as physical activity, diet, and smoking, (Kennedy, Goggin, & Nollen, 2004; Koponen, Simonsen, & Suominen,
2017; Williams, Gagne, Ryan, & Deci, 2002; Williams et al., 2009). In addition to examining the level of PPN for different health behaviors, some of these studies also examined the relationships between perceived autonomy, competence, and relatedness for health behaviors (Kennedy, Goggin, & Nollen, 2004; Wilson & Bengoechea, 2010;
Williams et al., 1998). The following sections will discuss the levels of perceived psychological needs for each health behaviors.
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Levels of perceived autonomy in health behaviors. This study measured the levels of perceived autonomy for three health behaviors (physical activity, diet, and smoking). In this study, autonomy in health behaviors was defined as an individual’s volition to regulate their behaviors based on their own values, choices, and interests
(Anja et al., 2010; Patrick & Williams 2012). This variable was measured with Treatment
Self-Regulation Questionnaire (TSRQ) (Williams et al., n.d.) and specifically for physical activity, diet, and smoking.
The results of this study showed that the levels of perceived autonomy in physical activity (PA-PA), diet (PA-Diet), and smoking (PA-Smoking), were relatively high with the means ranging from 5.6 to 6.4 out of possible 7. PA-Smoking had the highest average score of 6.4. These findings are important because they indicate a high level of perceived autonomy for health behaviors among Saudi patients with CAD similar to other studies in the literature (Russell & Bray 2010; Spindler et al., 2019; Williams, Gagné, Mushlin, &
Deci, 2005). For example, the study by Williams et al. (2005) was conducted to examine the “effect of diagnostic testing for CAD on motivation for change and on lifestyle change for patients with chest pain” (p. 304). This study used one item from the TSRQ to measure patients’ motivation for lifestyle change. The study found that patients with
CAD had a high level of motivation for change on the TSRQ item with a mean of 6 out of possible 7. Moreover, Russell and Bray (2010) conducted a study to examine
“relationships between cardiac rehabilitation and participants’ perceived autonomy support, motivation for exercise, and exercise behavior” (p. 74). In their study, motivation for exercise was measured using the Exercise Self-Regulation Questionnaire
(ESRQ), which has similar items to the TSRQ. The study found that patients in cardiac
85 rehabilitation had “high levels of self-determined motivation for exercise with a mean of
5.8 out of a possible 7” (p. 77). Furthermore, Spindler et al. (2019) conducted an interventional study to examine the effect of telerehabilitation, which is a part of a telehealth program for patients’ lifestyle changes and self-care efforts. The population of their study was patients with CVD, CAD, heart failure, and artery sclerosis. High autonomous motivation on six TRSQ items with a mean of 6 out of a possible 7 was reported (Spindler et al., 2019).
Studies conducted in different populations also revealed similar findings. For example, Koponen, Simonsen, and Suominen (2017) conducted a study to examine the relationship between the six central quality dimensions of primary health and diabetic patients’ autonomous motivation for effective diabetes self-management. Autonomous motivation was measured by eight items from the TSRQ that included two health behaviors (diet and exercise). The study revealed a high level of autonomous motivation for diet and exercise on the TSRQ items with a mean of 5.6 out of a possible 7. Similarly,
Williams et al. (2002) use five items of the TSRQ in their intervention study to measure autonomous motivation on patients who smoked. They found a high autonomous motivation for smoking with a mean of 6.3 out of a possible 7, indicating that the patients had a high motivation in quitting smoking. Although the results of the studies mentioned above cannot be directly compared to those in the current study, they all show a high level of perceived autonomy as well as high level of autonomous motivation in health behaviors regardless the study population.
The results of this study showed that perceived autonomy for smoking is higher than PA-PA and PA-diet. Information about patients’ smoking status would have helped
86 to explain the reason for having high level of PA-Smoking, but this information was not collected in this study. Nevertheless, there might be another explanation for higher perceived autonomy related to smoking. Ghouri, Atcha, and Sheikh (2006) reported in
Saudi Arabia between 1996 and 2001, smoking prevalence was 13% of the population.
The low prevalence of smoking is related to the fundamental teachings of Islam which are opposed to any acts that may harm human organs (Ghouri et al., 2006). This religious belief may have influenced how the study participants responded to the questions in the
PA-Smoking survey. Therefore, it is believed that the results of PA-Smoking might be influenced by social desirability bias and hence failed to reflect true response to smoking questions on the survey. This explanation is congruent with the social desirability bias reported from previous studies aimed to examine smoking behavior in Saudi Arabia. For example, Alotaibi, Alsuliman and Durgampudi (2019) conducted a systematic review and meta-analysis on “smoking prevalence in Saudi college students from 2010-2018” (p. 1).
The results of their study revealed a high prevalence of smoking among Saudi college students, specifically male students (Alotaibi et al., 2019). The authors discussed that social desirability bias may have influenced participants when they reported their smoking behavior, especially women due to their “fear of societal rejection” (Alotaibi et al., 2019, p. 7). Ghouri et al. (2006) also mentioned that “social pressure” plays a strong role in the differences in smoking prevalence between males and females in in 30 countries with highest proportion of Muslims (p. 291).
Ryan and Deci (2017) posited that having a high level of autonomy toward any health behaviors improves an individual’s ability to follow healthy behaviors. Ryan and
Deci (2017) further pointed out that patients’ perceived autonomy in health behaviors can
87 be influenced by their perceived autonomy support (the amount of support patients received from their health care providers). When patients perceive their health care providers supporting their perceived autonomy, they are more likely to have high perceived autonomy toward their health behaviors (Williams, Gagné, Mushlin, & Deci,
2005). Williams et al. (2006) conducted an interventional study to examine the effects of the Self Determination Theory (SDT) intervention on smoking cessation. The intervention aimed to support participants’ autonomy to quit smoking. Patient’s motivation to quit smoking was assessed using the TSRQ-smoking. Participants in the intervention group had a high level of motivation on the TSRQ-smoking with a mean of
4.7 compared to the control group mean of 4.2. Williams et al. concluded that “perceived autonomy support led to increases in autonomous and competence motivations, which in turn led to greater cessation” (p. 91).
Level of perceived competence in health behaviors. This current study measured perceived competence in three health behaviors (physical activity, diet, and smoking). In this study, perceived competence in health behaviors was defined as individuals’ feeling confident in their ability to improve their skills and knowledge to make a health change and to reach their goals (Anja et al., 2010; Patrick & Williams,
2012). This variable was measured with Perceived Competence Scale (PCS) (Williams et al., n.d.) and specifically on physical activity, diet and smoking. The result of the study showed that perceived competence in smoking (PC-Smoking) was higher (� = 5.8) than both perceived competence in physical activity (PC-PA) (� = 3.9) and perceived competence in diet (PC-Diet) (�= 4.3). The subject scores ranged from 1 to 7. According to Ryan and Deci (2017), high levels of perceived competence in health behaviors will
88 result in better health outcomes. These results are important because they indicate that
Saudi patients with CAD have high levels of PC-Smoking, PC-PA, and PC-Diet.
The result of the study revealed a high level of perceived competence in smoking among Saudi patients with CAD. This result is encouraging, even though data on patients' smoking status was not collected. These results still showed that patients perceived themselves competent to either quit or continue to not smoke. However, this finding cannot be directly compared to other studies using the same instrument but with different study designs. For example, Williams et al. (2002) conducted a study to examine the effects of an intervention created by the National Cancer Institute (NCI) and used by physicians as a model to help patients who smoked to quit smoking. The study aimed to examine “whether the style used by physicians in administering the 4-As intervention would affect smokers’ motivation to quit” (Williams et al., 2002, p. 40). The study did not indicate a specific patients’ population, but they recruited individuals who currently smoke. The study measured PC-Smoking twice (before and after the intervention) using four items PCS. The study showed a low-level perceived competence in smoking with a mean of 3.6 out of a possible 7 before intervention and a slight improvement in perceived competence in smoking with a mean of 4.2 after intervention. Similarly, Williams et al.
(2006) also conducted an interventional study to examine the effect of a SDT intervention on smoking cessation. The intervention was designed to help participants quite smoking using a SDT counseling intervention that focused on autonomy support. Perceived competence in smoking was measured twice (before and after the intervention) using four items PCS. The study pretest results showed a medium-level of perceived competence in smoking with a mean of 4.4 out of a possible 7. The post-intervention result indicated a
89 slight improvement in perceived competence in smoking with a mean of 4.7 out of possible 7.
Both of these studies (Williams, et al. 2002; Williams, et al. 2006) were conducted in the USA and reported lower levels of perceived competence in smoking compared to the current study where it was conducted in Saudi Arabia, which showed high level of perceived competence in smoking (mean of 5.8 out of possible 7.0). The reason could be similar to the reason of having a high level of PA-smoking. Religious and social factors might influence patients to report high perceived competence in quitting smoking or continuing not to smoke. Al-Mohrej et al. (2016) conducted a study to “analyze the socio-demographic of Saudi ex-smokers” (p. 146) and to understand the reasons people quit smoking between the period of April and May 2013. The authors reported that both religious and social factors were major factors that influenced participants to quit smoking in Saudi Arabia (Al-Mohrej et al., 2016). Therefore, it is possible that some religious and social factors may have influenced participants in this current study to report high levels of PC-Smoking. A study conducted by Young et al.
(2009) provides additional support for this hypothesis. Young et al. (2009) aimed to examine the “role of religion and religious authorities in influencing smoking behavior among Muslims in Malaysia and Buddhists in Thailand” (p. 1). The majority of participants in both religions “believed that their religion discourages smoking” (p. 1).
Also, half of them reported that their religious leaders supported them to quit smoking.
Yong et al. (2009) concluded that religious factors have influenced participants in both religions to quit smoking. The result of Yong et al. (2009) provided a support that religion may influence people to quit smoking or continuing not to smoke, and this result
90 may explain why Saudi patients with CAD, in this current study, reported high level of
PC-Smoking. Also, the level of perceived autonomy support, which was not investigated in this current study, may have influenced patients’ level of PC-Smoking. The study by
Williams et al. (2006) revealed that a high level of perceived autonomy support would increase patients' competence motivations to quit smoking.
The result of this study also revealed that perceived competence in diet was higher than perceived competence in physical activity among Saudi patients with CAD.
These results are not congruent with the results of a study by Mokhtari et al. (2017) that was conducted to examine the level of perceived competence in both diet and physical activity among two groups of adolescents (normal weight and obese). The level of perceived competence in physical activity (with a mean of 24 out of a possible 28) was higher than perceived competence in diet (with a mean of 22 out of a possible 28).
However, a comparison between the results of the current study and the study by
Mokhtari et al. (2017) cannot be made because of differences within the populations
(patients with CAD in Saudi Arabia vs. obese adolescents in the USA).
The results of the current study are similar, however, to the results of a study by
Milne, Wallman, Guilfoyle, Gordon, and Corneya (2008) which aimed to examine constructs of SDT, which included the level of perceived competence in physical activity among breast cancer survivors. The level of perceived competence in physical activity among breast cancer survivors who met the Australian physical activity guidelines (with a mean of 6.2 out of a possible 7.0) was higher than the level of perceived competence in physical activity of participants who did not meet guidelines (with a mean of 4.6 out of a possible 7.0).
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One reason that perceived competence in physical activity was lower than both perceived competence in diet and perceived competence in smoking may be due to the high level of physical inactivity among Saudis. According to a systematic review conducted by Al-Hazzaa et al. (2018), the majority of the Saudi population did not meet the physical activity guidelines recommendation. Data about the status of patients’ physical activity would have helped to explain the reason for having low levels of PC-
PA, but this information was not collected in this study.
Patients’ actions toward their health behavior may be related to their perceived competence (Ryan & Deci, 2017). Research has found that patients who perceived themselves as competent are more likely to follow healthy behaviors, specifically, physical activity, healthy diet, and not smoking or quitting smoking (Halvari, Ulstad,
Bagøien, & Skjesol, 2009; Milne et al., 2008; Mokhtari et al., 2017; Williams, Niemiec,
Patrick et al., 2009). A high level of perceived competence in smoking and a moderate level of perceived competence in both physical activity and diet found in patients with
CAD in this current study may indicate that these patients are more likely in participating in physical activity (Halvari et al., 2009), eating a healthy diet (Mokhtari et al., 2017), and quitting smoking (Williams, Niemiec, Patrick et al., 2009).
Level of perceived relatedness in physical activity. Perceived relatedness in physical activity (PR-PA) is essential for patients while they engage in physical activity
(Wilson & Bengoechea, 2010). In this study, perceived PR-PA was defined as individuals
“feeling understood and cared for by others” (Ng et al., 2012, p. 326). This variable was measured with Relatedness to Others in Physical Activity Scale (ROPAS). Wilson and
Bengoechea (2010) published the results of two of their studies in one article in order to
92 establish validity and reliability of the ROPAS. The first study revealed a high level of
PR-PA among study participants (with a mean of 4.9 out of a possible 6.0). In contrast, the results in this current study on Saudi patients with CAD revealed slightly lower level of PR-PA than those in Wilson and Bengoechea (2010). In the current study, the mean of
PR-PA was 4.1 with the subject scores ranging from 1 to 6. This finding indicates that not all patients in the study felt connected to others about engaging in physical activity. The different findings between Wilson and Bengoechea’s (2010) study and the current study are due to the different study populations. Participants of the current study were CAD patients from Saudi Arabia, whereas participants in Wilson and Bengoechea’s (2010) study were Canadian university students. Both studies differ in participants' age, as well as in culture.
Although ROPAS is a valid tool to measure the concept, relatedness in physical activity, few studies used this tool to measure the same concept. For example, the
Psychological Need Satisfaction in Exercise (PNSE) was developed by Wilson, Rogers,
Rodgers, and Wild (2006). Ball, Bice, and Maljak (2017) used this tool in their study to
“explore the relationships between SDT, adults’ barriers to exercise, and those who have met and have not met the Center for Disease Control and Prevention (CDCP) recommendations for weekly physical activity” (p. 19). Another tool called the Basic
Psychological Needs in Exercise Scale (BPNES) was also used to measure PR-PA in other studies. Kirkland et al. (2011) used BPNES “to examine the relationship between motivation, basic psychological needs satisfaction, and exercise in a sample of older adults” (p. 181). To know more about how Saudi patients with CAD perceived about
93 their relatedness to others in physical activity, future studies are encouraged to use more than one instrument to measure this concept.
The result of the current study revealed an overall moderate level of PR-PA among Saudi patients with CAD. It was unclear why the Saudi patients with CAD felt moderate degree of relatedness when in engaging in physical activity since no specific information regarding physical activity in a group setting was collected in this study.
However, a plausible reason for this finding could be that some patients did not participate in any physical activity, which might influence their responses to the questions that asked them about how they feel while performing physical activity. A recent systematic review by Al-Hazzaa (2018) revealed majority of the Saudis from children to adults were not physically active to “meet the recommended guidelines for moderate to vigorous PA [physical activity]” (p. 50) and females in Saudi Arabia have high prevalence of inactivity.
The relationships among the PPN for health behaviors
The second aim of this study was to measure the relationships between study variables. In the sections below the relationships among the independent variables will be discussed first. The relationships between independent variables and the dependent variable will follow.
Relationships among independent variables. This study revealed several positive relationships among independent variables: (1) PA-PA and PA-Diet (rho = .695, p = < 0.01), (2) PA-Smoking and PC-Smoking (rho = .48, p = < 0.01), (3) PR-PA and
PC-PA (r = .436, p = < 0.01), (4) PC-Diet and PC-PA (r = .435, p = < 0.01), (5) PR-PA and PC-Diet (r = .42, p = < 0.01), (6) PA-Smoking and PA-PA (rho = .386, p = < 0.01),
94 and (7) PA-Diet and PA-Smoking (rho = .281, p = < 0.01). These relationships will be discussed below.
The positive significant correlation between PA-PA and PA-Diet indicates that patients with high perceived autonomy in performing physical activity had better perceived autonomy in controlling their diet. A study by Jutta et al. (2009) revealed similar findings. Jutta et al. aimed to examine the relationship between self-determined motivation of physical activity and diet during a weight control program using an adapted version of the TSRQ. The study revealed a positive relationship between motivation for physical activity and diet (Jutta et al., 2009).
The positive significant correlation between PA-Smoking and PC-Smoking indicates that patients with high perceived autonomy for not smoking were more likely perceived being competent to quit smoking or to continue not to smoke. This finding is in line with a previous study that reported a positive relationship between PA-Smoking and
PC-Smoking (Williams et al., 2006). Williams et al. (2006) conducted an interventional study to examine the effects of an intervention guided by SDT on participants’ smoking behaviors. In William et al.’s study, the measurements (TSRQ and PCS) used were the same as the current study. The study revealed positive relationship between participants’ autonomous and competence motivations for smoking. Patients with high level of autonomous motivations were more likely to be competence to quit smoking or to continue not to smoke.
The results of current study also showed a positive significant correlation between
PR-PA and PC-PA. This indicates that patients who perceived themselves as having high relatedness with others in physical activity were more likely to have high levels of
95 perceived competence in performing physical activity. This finding is in line with findings of Wilson and Bengoechea’s (2010) study, which revealed positive relation between PR-PA and PC-PA. The difference between the current study and the study by
Wilson and Bengoechea (2010) is the measurement used. Wilson and Bengoechea (2010) measured perceived competence using the Intrinsic Motivation Inventory which “assess participants' subjective experiences related to target activity in laboratory experiments”
(“Intrinsic Motivation Inventory,” 2017, p. 1) and the current study used the perceived competence scale (PCS) (Williams et al., n.d).
The positive correlation between PC-Diet and PC-PA indicates that patients who perceived themselves as competent in improving their diet were more likely perceived as being competent in performing physical activity. This result was consistent with the results of a systematic review by Teixeira, Carraca, Markland, Silva, and Ryan (2012) where the authors reported that of the studies review, “perceived competence was positively associated with physical activity in 56% of the independent samples” (p. 21).
The results of the current study showed a positive significant correlation between
PR-PA and PC-Diet, which indicates that patients who perceived themselves as having high connection with others in physical activity were more likely to have high perceived competence in improving their diet. This finding supports the relationship, which was proposed this relationship by Ryan and Deci (2017), between perceived relatedness and perceived competence in one health behaviors, physical activity (Ryan & Deci, 2017). In a study by Vlachopoulos, Ntoumanis, and Smith (2010) to compare the SDT concepts
(autonomy, competence, and relatedness) in exercise behavior among two samples of people who perform physical activity, a positive correlation between the three SDT
96 concepts measured in physical activity behaviors, although Vlachopoulos et al. measured
PR-PA with a different instrument. Also, the current study found a positive relationship between PR-PA and PC-Diet, whereas the study by Vlachopoulos et al. (2010) measured the relationship only in physical activity behavior. Therefore, direct comparison cannot be made.
The positive significant correlation between PA-Smoking and PA-PA indicates that patients who perceived themselves having high autonomy in quitting smoking or to continuing to not smoke were more likely perceived as having high autonomy to perform physical activity. According to Kaczynski, Manske, Mannell, and Grewal (2008), the majority of studies conducted to measure the relationship between smoking and physical activity indicated that smokers are more likely to be physically inactive. Heydari et al.
(2015) also support that smoking behavior has a negative influence on physical activity, and most smokers tend to have a low level of physical activity.
The positive significant correlation between PA-Diet and PA-Smoking indicates that patients who perceived themselves as having high autonomy in improving their diet were more likely perceived as having high autonomy to quitting smoking or to continue not to smoke. It is important to know the relationship between smoking and poor diet because they are two risk factors for many diseases. The findings of the current study support the results of Heydari, Heidari, Yousefifard, and Hosseini (2014), who reported that smokers tend to consume poor quality food compared to nonsmokers.
Overall, the results of the relationships between the independent variables were consistent with the SDT. Using the framework of SDT, individuals with high perceived autonomy are more likely to also have high perceived competence (Ryan & Deci, 2017).
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Williams et al. (2009) reported that high perceived autonomy would result in high perceived competence for health behaviors. Perceived competence is related to individual autonomy because autonomy “requires a person’s experience and competence to change”
(Ryan et al., 2008, p. 3).
The relationship between the independent variables (PPN in health behaviors) and dependent variable (medication adherence)
The study had three hypotheses related to the relationships between PPN in health behavior and medication adherence. They are 1) An increase of perceived autonomy for health behaviors will increase medication adherence; 2) an increase of perceived competence for health behaviors will increase medication adherence; 3) an increase of perceived relatedness for physical activity will increase medication adherence.
The results of this current study showed significant positive relationships between medication adherence and several independent variables (PA-PA, rho = .219, p < 0.01;
PA-Diet, rho = .178, p < 0.05; PC-PA, rho = .154, p < 0.05; PC-Diet, rho = .179, p <
0.05). These findings support the assumptions that patients with high perceived autonomy and perceived competence in physical activities and diet were more likely to have better medication adherence. For example, Lee et al. (2018) reported a positive relationship between the actual health behaviors (physical activity, diet, and smoking) and medication adherence among patients with CAD. Moreover, Han et al. (2017) suggested that patients who were physically active, not obese, and non-smokers have better medication adherence. The differences between this current study and studies by Lee et al. and Han et al. are how they collected information on behaviors. The current study is through subject’s self-report and both Lee et al. and Han et al. collected actual behaviors. For
98 example, Han et al. (2017) asked participants (Korean patients with hypertension, diabetes, and hyperlipidemia) to indicate the number of days and the number of minutes they perform physical activity each week. The study also asked patients about their smoking and drinking status. Obesity was measured by calculating Body Mass Index
(BMI). Lee et al. (2018) measured lifestyle modifications regarding several health behaviors such as diet, exercise, and smoking behaviors among patients with CAD.
Lifestyle modifications for health behaviors was measured using a survey that asked patients questions about their actual health behaviors diet, exercise, and smoking behaviors. Medication adherence was measured using the six-item Modified Morisky
Scale (MMS).
Other studies with different patient populations that examined patients perceived psychological needs (PPN) also produced similar results. Williams et al. (2009) found that perceived autonomy and competence in diabetes self-management were positively related to medication adherence. Whereas, Kennedy et al. (2004) reported a positive relationship between perceived autonomy and competence for medication use and medication adherence among HIV patients. The results of this current study add more support to the notion that high levels of perceived autonomy and competence are positively related to medication adherence.
The study revealed that the relationship between PR-PA and medication adherence was very small and not significant (p = 0.34). Direct comparison of this finding to the literature is difficult because other studies used different tools to measure the concept, relatedness. These studies found positive relationships between PR-PA and some other health behaviors such as physical activity. For example, Weman-Josefsson,
99
Lindwall, and Ivarsson (2015) conducted a study to “explore relationships between the latent constructs of psychological need satisfaction exercise behavior” (p. 1). The study measured PR-PA using the 12-items BPNES and revealed a positive relationship between
PR-PA and exercise intensity. High exercise intensity was positively correlated with PR-
PA (Weman-Josefsson et al., 2015). This result suggest that high level of PR-PA would increase exercise intensity.
Also, both PA-Smoking (p = 0.07) and PC-Smoking (p = 0.12) were not related to medication adherence. In this study, a non-significant relationship could be explained by the low reliability (α = 0.58) of the MGL (4 items), which was used to measure medication adherence. Low measurement reliability may lead to a non-significant relationship between study variables (Charter, 1997; Goodwin & Leech 2006). Another explanation could be that there is no actual relationship exists between PA-Smoking, PC-
Smoking and medication adherence among Saudi Arabian patients with CAD. It is difficult to compare this result because there is limited information in the literatures about the relationship between PA-Smoking, PC-Smoking and medication adherence among this population.
The study was designed to examine which of the independent variables explain the dependent variable. According to the SDT, satisfaction of the PPN can predict health behaviors, such as medication adherence (Ryan & Deci, 2017). In one study, perceived autonomy predicted longtime medication adherence among adult patients (Williams et al., 1998). This illustrates the importance of patients’ autonomy in improving their health.
High levels of PPN in some other health conditions also resulted in improving medication adherence. For example, both perceived autonomy measured by TSRQ, and perceived
100 competence measured by one item from PCS predicted medication adherence among
HIV patients (Kennedy et al., 2004).
Therefore, for the current study, multiple regression analysis was proposed to determine which of the independent variables predict the dependent variable. Multiple regression analysis was conducted, but none of the regression models was significant, and the variance explained was very small (7.5%). This result was not surprising since the bivariate correlations between the independent and dependent variables were small. One of the reasons that none of the models were significant was the reliability and variability of the MGL (4 items). According to Marczyk et al. (2005) researchers need to use reliable instruments, with a correlation coefficient of .80 or higher, to reduce the chance of “obtaining a score that can be due to random factors and measurement error” (p. 103).
That is, low reliability may attenuate the correlations in this study. Another factor may be that the amount of variability in MGL (4 items) was restricted. The MGL (4 items) has a total score that ranges from 0 to 4. Restriction of score range might be one of the reasons this study yielded non-significant results (Goodwin & Leech, 2006).
The Level of Medication Adherence
The study also aimed to measure the level of self-reported medication adherence in patients with CAD. The result of this study indicated that nearly half of the study participants (47.1%) reported high medication adherence, while 40.5% reported medium medication adherence, and only 12.4% reported low medication adherence.
Rates of medication adherence in Saudi population vary depending on the health condition. Altuwairqi (2016) using Morisky Medication Adherence Scale (MMAS-8) found that 41.7% of patients with heart diseases in King Fahad Hospital in Riyadh
101 reported medium medication adherence, which is similar to the 40.5% found in the current study. However, 33.7% of patients in the study by Altuwairqi (2016) reported low medication adherence. In contrast, only about 12.4% patients in this current study reported low medication adherence. Finally, only 24.5% of Altuwairqi (2016) study reported high medication adherence, whereas in this current study 47.1% reported high medication adherence.
Patients with hypertension (HTN) in Saudi Arabia have varied medication adherence rates. Khayyat et al. (2017) determined that only 22.5% of patients with HTN in Makkah/Saudi Arabia had high medication adherence, which is less than what this current study found (47.1%). Khayyat et al. (2017) also reported that 23.5% of patients reported medium medication adherence, which is also different than the result of the current study (40.5%), while the majority of their study’s participants reported low medication adherence (54%), which is not in line with the findings of this current study
(12.4%). Shaik et al. (2016) also found that 55% of their participants reported low medication adherence. In contrast, in the study by Alotayfi et al. (2018), only 6.2% of their participants reported high medication adherence, while 26.4% reported low medication adherence and the majority of their participants (67.4%) reported medium adherence.
The results of these previous studies are not congruent with the results of the current study. The majority of these studies reported a higher percentage of study participants reporting low level of medication adherence, whereas around half of patients in this current study reported high medication adherence. One explanation for this finding might relate to the differences in study population. The majority of these studies were not
102 focused on the CAD population in particular, but rather on CVD and HTN medication adherence behavior. Different diseases and their symptoms may affect medication adherence (Ferdinand et al., 2017). This also may include the severity of symptoms, which may affect patients’ medication adherence (Ferdinand et al., 2017). A meta- analysis conducted by DiMatteo, Haskard, and Williams (2007) to examine the relationship between patients’ adherence and disease severity awareness, concluded that
“patients’ awareness of disease severity can predict their adherence” (p. 521). Patients with CAD often may have more symptoms when compare to patents with HTN.
Therefore, patients with CAD may tend to report more medication adherence. In this current study, high medication adherence may be related to the high CAD symptoms, or high patients’ awareness of the severity of the disease therefore, high medication adherence was reported by nearly half of the study participants.
In addition to the differences in the studies’ population, there are other differences when comparing the results of previous studies and the current study. First, it is important to mention that the majority of these studies had a higher sample size >200 as compared to this current study’s n=121. Second, all of these previous studies used the (MMAS-8) to measured medication adherence, whereas this current study used the MGL (4 items). The
MMAS-8 is an upgraded version of the MGL (4 items) with higher reliability (α = 0.83)
(Morisky et al., 2008). There were limited numbers of studies that aimed to measure medication adherence among Saudis with CAD; therefore, this current study was designed to measure medication adherence among Saudis with CAD.
103
Strengths of the Study
This study is one of the first research projects that aimed to measure the level of patients PPN (autonomy, competence, and relatedness) for health behaviors from the perspective the SDT among Saudi patients with CAD. Utilizing a theoretical framework to guide research studies is important to help guide the structure of the research, as well as to produce reliable results (Grant & Osanloo, 2014). The PPN concepts of patients’ autonomy, competence, and relatedness have not been extensively studied in Saudi
Arabia. According the World Health Organization (WHO), poor diet, physical inactivity, and smoking are major risk factors for heart diseases. Therefore, this study was designed to explore the level of PPN in the three health behaviors that are risk factors for CAD
(physical activity, diet, and smoking). As this study is currently unique in its scope, it may serve as a basis for future research to explore the psychological needs from the perspective of the SDT in Saudi Arabia. Future researchers may examine health behaviors related to other medical illnesses, such as Saudi patients with heart failure, diabetes mellitus, and other chronic conditions.
An additional strength is the information regarding the reliability of the translated instruments that was used to measure patients’ psychological needs. In this study, all instruments were translated into the Arabic language, and high reliability was reported, with a Cronbach’s alpha of = 0.86 or higher on the study instruments. This is the first study that provides information about the reliability of the Arabic versions of the TSRQ,
PCS, and ROPAS. This reliability information will help future Arab researchers who want to measure the PPN to have evidence about the reliability of the Arabic version of each of these instruments.
104
There are few studies that have focused only on CAD among Saudi patients. In
Saudi Arabia, most studies have been done on patients with CVD such as HTN, heart failure, and congenital heart diseases. The current study was focused only on patients with CAD, which provided valuable information about this population in Saudi Arabia.
Since this study looked at the importance of the PPN on patients’ health behaviors, it will guide health care providers to help patients build CAD-management skills that support their autonomy, competence, and relatedness, as well as their medication adherence.
Moreover, policymakers in the health care system may use the results of this study as evidence about the relationship among PPN in health behaviors. This evidence may benefit other populations with chronic illnesses and encourage health care policies that focus on supporting patients’ PPN.
Study Limitations
This study has several limitations. First, the use of non-probability sampling procedure (convenience sampling) can limit the generalizability of study results to the larger population. This sample of 121 Saudi patients diagnosed with CAD from one
Saudi hospital in one region could not represent all Saudi CAD patients in all Saudi areas.
Therefore, future researchers may recruit a larger sample size from all Saudi areas.
Second, the reliability and variability of one instrument was low. The reliability of the instrument MGL (4 items), which was used to measure medication adherence, was low (α = 0.58). According to Polit (2010), a Cronbach’s alpha of more than 0.70 will be considered acceptable; however, a Cronbach’s alpha “of 0.80 or greater are highly desirable” (p. 335). The reason for having a weak correlation is unknown, however, the reliability may influence the result of this study, as demonstrated by the weak correlation
105 between the study’s independent and dependent variables. According to Goodwin and
Leech (2006), instrument reliability "places an upper bound on how high the correlation can be between the measured variables" (p. 263). As mentioned before, the amount of variability of the MGL (4 items) was also low, and this might be one of the reasons this study yielded weak correlation. Low variability in the study variables might reduce the size of correlation between study variables (Goodwin & Leech, 2006).
Third, there was a lack of normality in some of study variables (PA-PA, PA-Diet,
PA-Smoking, and PC-Smoking). Several reasons for having non-normally distributed data in research are possible such as: the presence of outliers, presence of extreme high scores (Mayers, 2013), or reasons related to measurement’s errors (random errors). In this study there were no outliers; however, there were extreme scores in some of the study variables. In this study, several factors contributed to the problem of normality, especially for the two variables: PA-Smoking and PC-Smoking. As mentioned in Chapter Four, the transformation failed to obtain normal distribution for PA-Smoking and PC-Smoking due to the extreme left skew that caused respondents to choose higher agreement for all items
“very true.” Ansari and Farooqi (2017) reported that they modified and changed some items in their survey that was used to measure the prevalence of smoking among a group of females at the University of Dammam to reduce cultural biases. Also, other studies about smoking behavior in Saudi Arabia have suggested some limitations to their research due to some cultural bias (Desouky, Elnemr, Alnawawy, & Taha 2016; Ibrahim,
AlShammari, Alshammari, 2017; Moradi-Lakeh et al., 2015).
106
Implication for Future Research
This current study is the first study to provide information about the levels of PPN as well as the level of self-reported medication adherence among Saudi patients with
CAD. Also, this study provides valuable information for the health care system in Saudi
Arabia about the relationships between PPN and medication adherence. The findings of this study suggest positive relationships between two concepts (autonomy and competence) of the PPN, specifically PA-PA, PA-Diet, PC-PA, PC-Diet, and medication adherence. These findings may influence clinical practice by directing more attention toward patients’ PPN and providing patients with the proper education to support their
PPN for health behaviors. This also may influence healthcare management and policymakers in Saudi Arabia to develop or modify health care policies to encourage healthcare providers to focus on supporting the PPN.
The findings of this study provide a new path for future research to examine the concepts of SDT in Saudi Arabia or any other Arabic-speaking countries. The study provided new information about the reliability of the Arabic version of the instruments used to measure the PPN. Now that the TSRQ, PCS, and ROPAS are translated into
Arabic, and Cronbach’s alpha of more than 0.80 was reported, many researchers will be able to use these instruments to conduct studies to measure the PPN in Arab regions.
However, more studies are needed to further validate the Arabic version of these instruments among different Arab countries and disease populations.
This study also highlights the important of using instruments with more variability in their scores. The variability in MGL (4 items) was low. The lower the variability in study variables, the greater the chance is to have low size of correlation
107 coefficient (Goodwin & Leech, 2006). Therefore, an instrument with high variability would have improved the correlation size. There are other instruments with more variability such as the MMAS-8. The MMAS-8 has been translated into 33 languages (De las Cuevas, & Peñate, 2015), which made it popular among studies that aimed to measure medication adherence. Therefore, it is recommended to use the MMAS-8 to measure medication adherence in future studies. However, permission and license approvals will need to be obtained by future researchers before using (MMAS-8) to measure medication adherence.
The levels of PPN (autonomy, competence, and relatedness) for health behaviors among Saudi patients with CAD varied depending on the health behaviors. Both PA-
Smoking and PC-Smoking were the highest, followed by PA-PA, PA-Diet, PC-PA, and
PC-Diet. The level of PR-PA was medium. The SDT emphasizes the importance of autonomy support to improve patients’ perceived autonomy, perceived competence, and perceived relatedness (Ryan & Deci, 2017). However, this current study did not measure perceived autonomy support, which multiple other studies have measured (Koponen,
Simonsen, & Suominen, 2017; Miežienė, Šinkariova, & Adomavičiūtė, 2015; Williams et al., 2009; Williams et al., 2005). Future studies may focus on measuring the relationship between patients’ perceived autonomy support, perceived autonomy, competence, and relatedness for Saudi patients with CAD. This could support the evidence that patients who perceive their health care providers as supporting patient autonomy are more likely to have high perceived autonomy, competence, and relatedness.
Finally, future studies may ask participants about the status of their health behaviors. For example; asking participants about their smoking status, which could help
108 researcher to better analysis and discuss their findings. Researcher will have the opportunity to compare the level of PPN with the smoking status of their participants
(smokers vs nonsmokers). This information will improve the compressions between study findings.
Conclusion
In Saudi Arabia, the majority of patients diagnosed with CAD are men. This current study has a sample that reflects the similar gender break down. The levels of PPN among Saudi patients with CAD were high for PA-Smoking, PC-Smoking, followed by
PA-PA, PA-Diet, PC-PA, and PC-Diet. The level of PR-PA was medium, which suggests that that not all patients in the study felt connected to others about engaging in physical activity. The study revealed that not all the PPNs for health behavior were positively correlated with medication adherence. High levels of PA-PA, PA-Diet, PC-PA, and PC-
Diet were positively correlated with medication adherence. However, the levels of PA-
Smoking, PC-Smoking, and PR-PA were not positively correlated with medication adherence. These results are consistent with some of the results of previous studies.
Also, this study revealed that close to half of the participants reported high medication adherence. In contrast, previous research conducted in Saudi Arabia has indicated low medication adherence among patients with heart diseases. This difference is important, because this current study is one of the few studies that measured medication adherence with a focus only on patients with CAD.
This study addresses a gap in the literature regarding the relationships between
PPN and medication adherence. The translated instruments in this study can be used in research focusing on the level of PPN and medication adherence for Arabic speakers;
109 however, more studies need to be conducted to test the validity and reliability of these instruments in different Arab regions, as well as with different patient populations. This current study serves an important function, as it is the first attempt to understand perceived psychological needs in patients with CAD in Saudi Arabia.
110
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APPENDICIES
142
APPENDIX A
IRB APPROVAL FROM THE UNIVERSITY OF AKRON
143
APPENDIX B
IRB APPROVAL FROM MADINAH CARDIAC CENTER (MCC)
144
APPENDIX C
SCRIPT FOR RECRUITMENT
After identifying a potential participant, the research assistant greets him/her in the Cardiac Clinic at Madinah Cardiac Center (MCC) during the clinic visit. The research assistant will introduce himself with the script below:
Introducing yourself to the potential participants: Hello, my name is Fahad Mousa Almarwani, I am a research assistant from MCC and we are conducting a study to look at patients perceived psychological needs for health behaviors and medication adherence. The primary researcher is Mr. Abdulaziz Almarwani, a Ph.D. candidate from the University of Akron. Also, he is a Nursing instructor in Tibah University. In order to participate in this study, you will need to complete a research survey. It will take you 10-15 minutes to complete it. Please read the letter and let me know if you are interested in this study and willing to answer some questions.
If potential participants agree to participate in the study the research assistant will ask the following questions: • How old are you? • What is your nationality? • Are you a patient who has been diagnosed with CAD? • Do you read and write in Arabic? • Have you been diagnosed with congenital heart disease? • Have you been diagnosed with heart failure? • Have you been diagnosed with renal failure? • Have you been diagnosed cancer?
If potential participants meet the inclusion and exclusion criteria:
Again, thank you for your willingness to answer the research questions. In order to participate in this study, you need first to sign the informed consent. The informed consent has all the information about the risks and benefits of participating in this study. Also, informed consent will contain information about the level of your involvement in this study. By signing this consent, you agree to participate in this study and all information obtained from you will be used in this research. I would like to tell you that participating in this study is anonymous, and no identification will be used in the research. You also can withdraw from the study any time you wish to do so. Also, you can
145 send an email to the researcher after 6 months if you are interested in knowing the results of the study. Let me know if you have any questions after the informed consent.
After potential participants sign the informed consent: For the purpose of your confidentiality I would like to ask you to come to the research room (nursing room at the clinic). In the research room I will give you the research survey. In the research room: This iPad has the research survey; it might take you 10-15 minutes to complete the survey. Once you finish the survey please place the iPad on the table. I will come and get it. If you have any questions you may ask Mr. Abdulaziz Almarwani. If potential participants complete the survey: Thank you very much for completing the survey.
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APPENDIX D
OPEN LETTER TO STUDY PARTICIPANTS
ﻮﻨﻋ نا فﺎﺷﻛﺗﺳا ﺗﺣﻻا ﯾ تﺎﺟﺎ ا ﻟ ﻧ ﺔﯾﺳﻔ ﺔﯾﺳﺎﺳﻷا ﻟ ﯾﻛوﻠﺳﻠ تﺎ ا ﺔﯾﺣﺻﻟ ﻗﻼﻋو ﺎﮭﺗ ﺑ ﻟﻻﺎ ازﺗ م ا ﻟ اود ﻲﺋ ﺑ نﯾ ﻟا ﻰﺿرﻣ Title ﺔﺳارﺪﻟا نﯾﺑﺎﺻﻣﻟا بﻠﺻﺗﺑ نﺎﯾرﺷﻟا ﯾﺟﺎﺗﻟا ﺔ ﻲﻓ ا ﺔﻛﻠﻣﻣﻟ ا ﺔﯾﺑرﻌﻟ ا ﺔﯾدوﻌﺳﻟ The Relationship of Perceived Basic Psychological Needs for Health Behaviors and Medication Adherence in Saudi Arabian Patients with Coronary Artery Disease. ﺐﯿﺒﻄﻟا ﺑﻋ د ا ﻟ زﯾزﻌ ا ﻟ ارﻣ ﻲﻧو Principal Abdulaziz Almarwani ﺚﺣﺎﺒﻟا Investigator نﻮﻔﯿﻠﺗ ٠٥٦١٥٥٦٦٣٥ (Telephone (0561556635 [email protected]. [email protected]
ﺎﺳر ﺔﻟ ﺔﯿﺤﯿﺿﻮﺗ ﻟ ﻦﯿﻛﺮﺘﺸﻤﻠ ﻰﻓ ا ﺔﺳارﺪﻟ ﻰ ﯿﺮﺸﻠﻟ ﯿﯿﻮ ﺔ ﺳ
فدﮭﺗ هذھ ا دﻟ ﺔﺳار ﻟ صﺣﻔ ﺗﺣﻻا ﯾ تﺎﺟﺎ This study serves two main purposes. First, to explore the levels ﺔﯾﺳﻔﻧﻟا تﺎﯾﻛوﻠﺳﻠﻟ ﺔﯾﺣﺻﻟا ﺎﮭﺗﻗﻼﻋو of the perceived psychological needs (autonomy, competence, and مازﺗﻟﻻﺎﺑ ﻲﺋاودﻟا نﯾﺑ ﻟا ﻰﺿرﻣ نﯾﺑﺎﺻﻣﻟا relatedness) for health behaviors and medication adherence of patients with coronary artery disease in Saudi Arabia. Second, to بﻠﺻﺗﺑ نﺎﯾرﺷﻟا .ﺔﯾﺟﺎﺗﻟا هذھ ﺔﺳاردﻟا ﺔﯾﻧﺑﻣ ﺔﯾﻧﺑﻣ ﺔﺳاردﻟا هذھ .ﺔﯾﺟﺎﺗﻟا assess the relationships among perceived psychological needs ﻰﻠﻋ ﺔﯾرظﻧ ( ا ﻟ ﯾدﺣﺗ د ا ﻟ ذ ا )ﻲﺗ ا ﻟ ﻲﺗ فدﮭﺗ autonomy, competence, and relatedness) for health behaviors and) صﺣﻔﻟ اﻻ ﺗﺣ ﯾ تﺎﺟﺎ ا ﻟ ﻧ ﯾﺳﻔ ﺔ ضﯾرﻣﻠﻟ ﮫﻠﺛﻣﻣ .medication adherence ﺔﯾرﺣ( ﺗﺧﻻا ﯾ رﺎ و ﻔﻛ ﮫﺗءﺎ او روﻌﺷﻟ ﺑ ﺑﺗرﻻﺎ طﺎ You will be eligible to participate in this study if you meet the نﯾطﯾﺣﻣﻟﺎﺑ )ﮫﺑ هذھرﯾﺛﺂﺗو لﻣاوﻌﻟا ﻰﻠﻋ following criteria: you are a Middle Eastern adult 18 years and ﯾﻛوﻠﺳ ﺎ ﮫﺗ ا ﺔﯾﺣﺻﻟ ﺔﺳرﺎﻣﻣﻛ ا ﯾرﻟ ﺔﺿﺎ او ﺗ ﺑ عﺎ ,older and have been diagnosed with coronary artery disease ﺔﯾﻣﺣ ذﻏ ا ﺋ ﺔﯾ عﻼﻗﻻاو نﻋ ا ﻟ نﯾﺧدﺗ ﻗﻼﻋو ﺎﮭﺗ myocardial infarction, or stable angina and can read and speak Arabic. ىدﻣﺑ ﻟﻻا ازﺗ م ا ﻟ اود ﻲﺋ . There are no potential risks of participating in this study, as it ﺗﺳﺗ فدﮭ ذھ ه ا ﻟ ﺔﺳارد ا ﻟ ﻰﺿرﻣ ا ﻟ ﺑﺎﺻﻣ نﯾ only requires you to answer research survey that contains 71 بﻠﺻﺗﺑ ﻟا رﺷ ا ﯾ ﯾ ن ا ﻟ ﺗ ﺎ ﺟ ﯾ ﺔ ﻓ ﻲ ا ﻟ قرﺷ ا طﺳوﻻ items, which require 10 -15minutes to be completed. This study نﻣ رﻣﻋ ١٨ ﺎﻋ م قوﻓﺎﻣﻓ او نﯾردﺎﻘﻟ ﻰﻠﻋ مﮭﻓ will have future benefits to patients diagnosed with CAD, as it ةءارﻗو ﺋﺳﻻا ﺔﻠ ﺑ ﺎ ﻟ ﺔﻐﻠ ا .ﺔﯾﺑرﻌﻟ may provide valuable information about patient’s psychological ﻻ دﺟوﺗ يا رطﺎﺧﻣ ﻠﻣﺗﺣﻣ ﺔ ﻧﻋ د ا ﺔﻛرﺎﺷﻣﻟ needs in health behaviors and their relation to medication ﻲﻓ ذھ ا ا ﻟ رد ﺔﺳا ثﯾﺣ adherence. The information will be used to build research interventions in the future that might improve the well-being of نا ا ﻟ ﺔﻛرﺎﺷﻣ فوﺳ ﺗ ﻘ ﻰﻠﻋرﺻﺗ ﺑﻌﺗ ﺔﺋ ﺔﺋ ﺑﻌﺗ ﻰﻠﻋرﺻﺗ ﻘ ﺗ فوﺳ ﺔﻛرﺎﺷﻣ ﻟ ا نا patients diagnosed with CAD. تارﺎﻣﺗﺳا عزوﺗ ﻰﻠﻋ ا ﻟ ﻰﺿرﻣ ا ﻟ ﺑﺎﺻﻣ نﯾ You will be not be eligible to participate in this study if you بﻠﺻﺗﺑ نﯾﯾارﺷﻟا ﺔﯾﺟﺎﺗﻟا قرﻐﺗﺳﺗو ﻌﺗ ﺎﮭﺗﺋﺑ ﺎﻣ :have one of the following conditions برﺎﻘﯾ ١٠ ﻰﻟا ١٥ ﻗد .ﺔﻘﯾ وﺳ ﻓ ﺎ ﺗ ﺟ بﻠ ھ ذ ه .Congenital heart disease 1- ﺔﺳاردﻟا رﯾﺛﻛﻟا نﻣ تﺎﻣوﻠﻌﻣﻟا نﻋ .End stage heart failure 2-
147
ﺗﺣﻻا ﯾ تﺎﺟﺎ ا ﻟ ﻧ ﯾﺳﻔ ﺔ و تﺎﯾﻛوﻠﺳﻟا ﺔﯾﺣﺻﻟا .Have had bypass surgery 3- ﺔﺳرﺎﻣﻣﻛ ا ﯾرﻟ ﺔﺿﺎ او ﺗ ﺑ عﺎ ﺔﯾﻣﺣ ذﻏ ا ﺋ ﺔﯾ .Have been diagnosed with end-stage renal failure 4- عﻼﻗﻻاو نﻋ ا ﻟ نﯾﺧدﺗ ﺎﮭﺗﻗﻼﻋو ىدﻣﺑ ﻟﻻا ازﺗ م .Have been diagnosed with end-stage lung disease 5- ﻲﺋاودﻟا نﯾﺑ ﻰﺿرﻣﻟا نﯾﺑﺎﺻﻣﻟا بﻠﺻﺗﺑ .Have been diagnosed with Cancer 6- .نﯾﯾارﺷﻟا هذھ تﺎﻣوﻠﻌﻣﻟا فوﺳ ﺳﺗ مھﺎ ﻲﻓ ﻲﻓ مھﺎ رﯾوطﺗ ﺔﺣﺻ ا ﻟ ﻰﺿرﻣ ﻲﻓ ا ﻟ ﺗﺳﻣ ﻘ لﺑ ا ﻟ بﯾرﻘ Participating in this study is anonymous and voluntary and you may withdraw from the study any time you wish to do so. All data نآ . ﺎﺷ will be saved in a secure online database and only the researcher will have access to them. ذھ ه ا ﻟ ﺔﺳارد ﻻ ﺗ ﻧ بﺳﺎ ا ﻟ ﻰﺿرﻣ ا ﻟ ﺑﺎﺻﻣ نﯾ ضارﻣﻻﺎﺑ :ﺔﯾﻟﺎﺗﻟا ١- ـ ضارﻣا بﻠﻘﻟا .ﺔﯾﺛاروﻟا ٢ ـ ضارﻣا لﺷﻔﻟا ﻲﺑﻠﻘﻟا مدﻘﺗﻣﻟا ٣ ـ نﻣ قﺑﺳ مﮭﻟ ﺔﯾﻠﻣﻋءارﺟا بﻠﻗ .حوﺗﻔﻣ
٤- ضرﻣا ا ﻟ لﺷﻔ ا يوﻠﻛﻟ .Thank you ٥ ـ ضارﻣا ا ﻟ لﺷﻔ ا ﻟ ﻲﺳﻔﻧﺗ ٦ ـ رﻣا ضا ا ﻟ ﺳ ر نﺎط
ﺔﻛرﺎﺷﻣﻟا ﻲﻓ هذھ ﺔﺳاردﻟا رﺑﺗﻌﺗ ﮫﻟوﮭﺟﻣ ﮫﻟوﮭﺟﻣ رﺑﺗﻌﺗ ﺔﺳاردﻟا هذھ ﻲﻓ ﺔﻛرﺎﺷﻣﻟا ﺔﯾﻋوطو نﻟو ﯾ بﻠطﺗ نﻣ ا نﯾﻛرﺎﺷﻣﻟ ا فﺷﻛﻟ فﺷﻛﻟ ا نﯾﻛرﺎﺷﻣﻟ ا نﻣ بﻠطﺗ ﯾ نﻟو ﺔﯾﻋوطو نﻋ مﮭﯾﻣﺎﺳا ﻲﻓ .تارﺎﻣﺗﺳﻻا ﻊﯾطﺗﺳﯾ ﻊﯾطﺗﺳﯾ .تارﺎﻣﺗﺳﻻا ﻲﻓ مﮭﯾﻣﺎﺳا نﻋ كرﺎﺷﻣﻟا نا فﻗوﺗﯾ بﺣﺳﻧﯾو نﻣ ﺔﻛرﺎﺷﻣﻟا ﺔﻛرﺎﺷﻣﻟا نﻣ بﺣﺳﻧﯾو فﻗوﺗﯾ نا كرﺎﺷﻣﻟا ﻲﻓ ا ﻟ ثﺣﺑ ﻲﻓ يا تﻗو .دﯾرﯾ ﻊﯾﻣﺟ ا ﻟ ﺑ ﯾ ﺎ ﻧ تﺎ تﺎ ﻧ ﺎ ﯾ ﺑ ﻟ ا ﻊﯾﻣﺟ .دﯾرﯾ تﻗو يا ﻲﻓ ثﺣﺑ ﻟ ا ﻲﻓ ﺳوف ﺗﺣﻔظ ﺑﻌﯾداً ﻋن اي ﺷﺧص ﻻ ﯾدﯾر ھذا .ثﺣﺑﻟا
ﺷﻛراً ﻟﻛم
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APPENDIX E
INFORMED CONSENT
ﺔﻘﻓاﻮﻣ ﺔﯿﻄﺧ ﺔﺳارﺪﻟ( ﻠﻛا )ﺔﯿﻜﯿﻨﯿ INFORMED CONSENT (CLINICAL STUDY) ﻮﻨﻋ نا ا ﻟ ﺔﺳارﺪ فﺎﺸﻜﺘﺳا ﺘﺣﻻا ﯿ تﺎﺟﺎ TITLE The Relationship of Perceived ﺔﯿﺴﻔﻨﻟا ﺔﯿﺳﺎﺳﻷا Basic Psychological Needs for تﺎﯿﻛﻮﻠﺴﻠﻟ ﺔﯿﺤﺼﻟا Health Behaviors and Medication ﻗﻼﻋو ﺘ ﮭ ﺎ ﺑ ﺎ ﻻ ﻟ ﺘ ﺰ ا م Adherence in Saudi Arabian ﻲﺋاوﺪﻟا ﻦﯿﺑ ﻟا ﻰﺿﺮﻤ Patients with Coronary Artery ﻦﯿﺑﺎﺼﻤﻟا ﺐﻠﺼﺘﺑ .Disease نﺎﯾﺮﺸﻟا ﯿﺟﺎﺘﻟا ﺔ ﻲﻓ ﻲﻓ ﺔﻜﻠﻤﻤﻟا ﻌﻟا ﺑﺮ ﺔﯿ ا دﻮﻌﺴﻟ ﺔﯾدﻌﻟا ﯿﺑ ﺐﯿﺒﻄﻟا ﺚﺣﺎﺒﻟا PRINCIPAL INVESTIGATOR / DOCTOR ﺒﻋ ﺪ ا ﻟ ﺰﯾﺰﻌ ا ﻟ اوﺮﻤ ﻲﻧ Abdulaziz Almarwani
ﺪﻌﺑ ﻨﻣ ﺎ ﺔﺸﻗ هﺬھ ا ﺔﺳارﺪﻟ :ﻊﻣ :Having discussed this research project with ﺐﯿﺒﻄﻟا ﺒﻋ ﺪ ا ﻟ ﺰﯾﺰﻌ ا ﻟ اوﺮﻤ ﻲﻧ Dr.: Abdulaziz Almarwani ﺔﻌﺟاﺮﻣو ا ﺎﺳﺮﻟ ﺔﻟ ا ﻟ ﺔﯿﺤﯿﺿﻮﺘ ﻦﻋ ا ﺔﺳارﺪﻟ ا ﻓﺮﻤﻟ ﺔﻘ ﻲﻨﻧﺈﻓ اوأ ﻖﻓ And reviewed the OPEN LETTER, which is ﻋﻮط ﺎ ﻋ ﻠ ﻰ ا ﻟ ﺸﻤ ﺎ ر ﻛ ﺔ ﻲﻓ ﺬھ ه ا ﻟ .ﺔﺳارﺪ attached, I agree, voluntarily to the participation in this study.
ﻢﺳا ا ﻟ ﺾﯾﺮﻤ :Patient's name ﺔﻗﻼﻌﻟا ﺾﯾﺮﻤﻟﺎﺑ :Relationship
:ﺔﻣﺪﻘﻣ ا ﺖﻧ ﻮﻋﺪﻣ ﻟ ﻛرﺎﺸﻤﻠ ﺔ ﻲﻓ ﺔﺳارد ﺔﯿﻤﻠﻋ ﯿﻘﺑ ةدﺎ ﺘﺳﻻا ذﺎ ذﺎ ﺘﺳﻻا ةدﺎ ﯿﻘﺑ ﺔﯿﻤﻠﻋ ﺔﺳارد ﻲﻓ ﺪﺒﻋ ا ﺰﯾﺰﻌﻟ ا اوﺮﻤﻟ ﻲﻧ ﺎط( ﺐﻟ ارﻮﺘﻛد ه ﻲﻓ ﻠﻛ ﺔﯿ ا ﻟ ﺾﯾﺮﻤﺘ ﻲﻓ ﺎﺟ ﺔﻌﻣ Introduction: You are invited to نوﺮﻛا )ﺔﯿﻜﯾﺮﻣﻻا participate in a research project being conducted by Abdulaziz :فدﮭﻟا فدﮭﺗ هذھ ﺔﺳاردﻟا صﺣﻔﻟ ﺗﺣﻻا ﯾ تﺎﺟﺎ ا ﻟ ﻧ ﯾﺳﻔ ﺔ ﯾرﺣ( ﺔ Almarwani, a student in the School ﺗﺧﻻا ﯾ رﺎ ﻔﻛو ﺗءﺎ ﮫ ﺗﺧﻻا ﯾ رﺎ او روﻌﺷﻟ ﺑ ﺗرﻻﺎ ﺑ طﺎ ﺑ ﺎ ﻟ نﯾطﯾﺣﻣ ﺑ )ﮫ of Nursing at The University of Akron. تﺎﯾﻛوﻠﺳﻠﻟ ﺔﯾﺣﺻﻟا ﺎﮭﺗﻗﻼﻋو مازﺗﻟﻻﺎﺑ ا ﻲﺋاودﻟ نﯾﺑ ﻟا ﻰﺿرﻣ ﻰﺿرﻣ Purpose: This study is conducted to explore نﯾﺑﺎﺻﻣﻟا بﻠﺻﺗﺑ نﺎﯾرﺷﻟا .ﺔﯾﺟﺎﺗﻟا ددﻌﻟا بوﻠطﻣﻟا لﺎﻣﻛﻟ هذھ the levels of perceived psychological needs ﺔﺳاردﻟا وھ ١٢١ ﺷﻣ ﺎ .كر (autonomy, competence, and relatedness) for health behaviors and medication ارﺟﻻا ء :تا ﺔﻛرﺎﺷﻣﻠﻟ ﻲﻓ هذھ ﺔﺳاردﻟا بﺟوﺗﺳﯾ كﯾﻠﻋ لﺎﻣﻛا adherence of patients with coronary artery ﺗﺳا ﺑ ﺎ ﺔﻧ ا ﻟ ثﺣﺑ ﻲھو ﺑﻋ ةرﺎ نﻋ ٧٢ ﺳؤاﻻً ﻗﺻﯾراً ﻗد ﺗﺣﺗﺎج ﻣن ١٠ disease in Saudi Arabia. Further, to assess ﻰﻟا ١٥ ﺔﻘﯾﻗد ﺎﻣﻛﻟ .ﮫﻟ ﯾﺑﺗﺳﻻا نﺎ فوﺳ كﻟﺄﺳﯾ :نﻋ ا ،سﻧﺟﻟ ا ،رﻣﻌﻟ the relationships among perceived ئوﺳﻣ ا ﻟ ﻠﻌﺗ ،مﯾ ا ﺎﺣﻟ ﺔﻟ ،ﺔﯾﻋﺎﻣﺗﺟﻻا او ةدﻣﻟ ا ﺔﯾﻧﻣزﻟ نﻣ ا تﻗوﻟ ا يذﻟ ,psychological needs (autonomy مﺗ ﮫﯾﻓ كﺻﯾﺧﺷﺗ ﺑ ضرﻣ بﻠﺻﺗ ا ارﺷﻟ ﯾ ﯾ ن. دﻌﺑ أذ كﻟ ﻧھ كﺎ ﺔﻠﺋﺳا competence, and relatedness) for health behaviors and medication adherence. The
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نﻋ ا ﯾﻛوﻠﺳﻟ تﺎ ا ﺔﯾﺣﺻﻟ ،لﺛﻣ ﺔﺳرﺎﻣﻣ ا ﯾرﻟ ،ﺔﺿﺎ ا ﻟ طﻣﻧ ا اذﻐﻟ ،ﻲﺋ estimated number of participants in this ،نﯾﺧدﺗﻟا مازﺗﻟﻻاو لوﺎﻧﺗﺑ .ءاودﻟا .study is 121 participants Procedures: In order to participate in this ذھ ه ا ﻟ ﺔﺳارد ﻻ ﺗ ﻧ بﺳﺎ ا ﻟ ﻰﺿرﻣ ا ﻟ ﺑﺎﺻﻣ نﯾ ﺑ ضارﻣﻷﺎ ا ﻟ ﺗ ﺎ ﻟ ﯾ ﺔ : study, you will need to complete a research ضارﻣا ا ﻟ ﻘ بﻠ ا ،ﺔﯾﺛاروﻟ ضارﻣا ا ﻟ لﺷﻔ ا ﻟ ﻘ ﻠ ﻲﺑ ا ،مدﻘﺗﻣﻟ نﻣ قﺑﺳ survey. The survey has 72 items and it will مﮭﻟ ءارﺟا ﻣﻋ ﻠ ﯾ ﺔ ﻗ بﻠ ﻣ ﻔ ﺗ ،حو أ رﻣ ض ا ﻟ ﻔ ﺷ ل ا ﻟ ﻛ ﻠ و ي ، ضارﻣا take you between 10 to15 minutes to complete. The research survey will ask you لﺷﻔﻟا ﻲﺳﻔﻧﺗﻟا ، ضارﻣا ا نﺎطرﺳﻟ about some demographic data such as age, رطﺎﺧﻣﻟا :تﺎﻘﯾﺎﺿﻣﻟاو ﺔﻛرﺎﺷﻣﻟا ﻲﻓ هذھ ﺔﺳاردﻟا رﺑﺗﻌﺗ ﺔﻟوﮭﺟﻣ ,gender, level of education, marital status ﺔﯾﻋوطو نﻟو ﯾ بﻠطﺗ نﻣ ا نﯾﻛرﺎﺷﻣﻟ ا فﺷﻛﻟ نﻋ مﮭﯾﻣﺎﺳا ﻲﻓ employment status, and time since you were .تارﺎﻣﺗﺳﻻا ﻊﯾطﺗﺳﯾ ا ﻟ كرﺎﺷﻣ نا ﯾ فﻗوﺗ ﯾو بﺣﺳﻧ نﻣ ا ﻟ ﺔﻛرﺎﺷﻣ .diagnosed with Coronary Artery Disease ﻲﻓ ا ﻟ ثﺣﺑ ﻲﻓ يا و ﻗ ت ﯾ ر ﯾ د . ﻣﺟ ﯾ ﻊ اﻟﺑﯾﺎﻧﺎت ﺳوف ﺗﺣﻔظ ﺑﻌﯾداً ﻋن Then, the survey will ask you questions يا صﺧﺷ ﻻ ﯾ د رﯾ ذھ ا ا ﻟ .ثﺣﺑ ﻧھ كﺎ لﺎﻣﺗﺣا طﯾﺳﺑ دوﺟوﻟ about your health behaviors, physical ﺔﻘﯾﺎﺿﻣﻟا ،ﺔﯾﻧﺎﻣﺳﺟﻟا ،ﺔﯾﺳﻔﻧ ﺔﯾﻋﺎﻣﺗﺟا ،ﺔﯾﻧوﻧﺎﻗ ﺔﯾدﺎﺻﺗﻗاو دﻧﻋ activity, smoking, diet, and medication adherence. ﺔﻛرﺎﺷﻣﻟا ﻲﻓ هذھ .ﺔﺳاردﻟا Exclusion: If you have one of the following conditions this study is not suitable for you: :دﺋاوﻔﻟا ﻻ دﺟوﺗ يا رطﺎﺧﻣ ﺔﻠﻣﺗﺣﻣ دﻧﻋ ا ﺔﻛرﺎﺷﻣﻟ ﻲﻓ اذھ ا ﻟ ﺔﺳارد Congenital heart disease, end stage heart ثﯾﺣ failure, have had bypass surgery, have been نا ا ﻟ ﺔﻛرﺎﺷﻣ فوﺳ رﺻﺗﻘﺗ ﻠﻋ ﻰ ﺑﻌﺗ ﺔﺋ تارﺎﻣﺗﺳا عزوﺗ ﻰﻠﻋ diagnosed with cancer, have been diagnosed ﻰﺿرﻣﻟا نﯾﺑﺎﺻﻣﻟا بﻠﺻﺗﺑ نﺎﯾرﺷﻟا .ﺔﯾﺟﺎﺗﻟا وﺳ ﻓ ﺎ ﺗ ﺟ بﻠ ھ ذ ه with end-stage lung disease, or have been ﺔﺳاردﻟا رﯾﺛﻛﻟا نﻣ تﺎﻣوﻠﻌﻣﻟا نﻋ تﺎﺟﺎﯾﺗﺣﻻا ﺔﯾﺳﻔﻧﻟا و تﺎﯾﻛوﻠﺳﻟا diagnosed with end-stage renal failure Risks and Discomforts: Participating in ﺔﯾﺣﺻﻟا ﺔﺳرﺎﻣﻣﻛ ﺔﺿﺎﯾرﻟا عﺎﺑﺗاو ﺔﯾﻣﺣ ﺔﯾﺋاذﻏ عﻼﻗﻻاو نﻋ this study is anonymous and voluntary and نﯾﺧدﺗﻟا ﺎﮭﺗﻗﻼﻋو ىدﻣﺑ ﻟﻻا ازﺗ م ا ﻟ اود ﻲﺋ نﯾﺑ ﻰﺿرﻣﻟا ﻣﻟا ﺎﺻ ﺑ ﯾ ن you may withdraw from the study any time ﻠﺻﺗﺑ ب ا ﻟ رﺷ ا ﯾ ﯾ ن . you wish to do so. All data will be saved in a secure online database and only the ﺔﯾرﺳﻟا :ﺔﯾﺻوﺻﺧﻟاو نﻟ نوﻛﯾ كﺎﻧھ يا تﺎﻣوﻠﻌﻣ ﺔﯾﻔﯾرﻌﺗ researcher will have access to them. There تﺎﻧﺎﯾﺑﻠﻟ ﻲﺗﻟا ﺔﻣدﻘﺗ .ثﺣﺑﻠﻟ هذھ ﺔﻘﻓاوﻣﻟا فوﺳ ظﻔﺣﺗ ﻲﻓ فﻠﻣ ,will be minimal physical, psychological social, legal or economic risks related to ﻧﻣ لﺻﻔ نﻋ ﺎﻣوﻠﻌﻣ كﺗ ا ﻟ ﺔﯾﺛﺣﺑ نﻟو ﯾ نﻛﻣﺗ يا صﺧﺷ طﺑرﺑ كدودر كدودر طﺑرﺑ صﺧﺷ يا نﻛﻣﺗ ﯾ نﻟو ﺔﯾﺛﺣﺑ ﻟ ا كﺗ ﺎﻣوﻠﻌﻣ نﻋ لﺻﻔ ﻧﻣ participating in this study as the study. هذﺎﮭﺑ ا اوﻣﻟ .ﺔﻘﻓ فوﺳ ﯾ مﺗ ﻔﺗﺣﻻا ظﺎ ﺑ ﺎ تﺎﻣوﻠﻌﻣﻟ ا ﻟ ﻔﯾرﻌﺗ ﺔﯾ ﻲﻓ ﻊﻗوﻣ Benefits: You will receive no direct benefit نﻣآ نﻟو ﯾ ﻊﯾطﺗﺳ دﺣأ لوﺧدﻟا ﺎﮭﯾﻠﻋ رﯾﻏ ثﺣﺎﺑﻟا .طﻘﻓ نﻟ نوﻛﯾ from your participation in this study, but ﻧھ كﺎ يا تﺎﻣوﻠﻌﻣ نﻋ ﺔﯾوھ ا نﯾﻛرﺎﺷﻣﻟ ﻲﻓ ﻧ ﺗ ﺎ ﺞﺋ اذھ ا ﻟ ثﺣﺑ وا your participation may help us better ﻲﻓ لﺎﺣ رﺷﻧ ذھ ا ا ﻟ ثﺣﺑ ﻲﻓ ﺔﻠﺟﻣ .ﺔﯾﻣﻠﻋ understand the relationship of perceived basic psychological needs for health ﺔﯾﺻوﺻﺧ ا :تﻼﺟﺳﻟ ﻊﯾﻣﺟ ا ﻟ ﺑ ﯾ ﺎ ﻧ تﺎ هذھ ا ﺔﺳاردﻟ فوﺳ ظﻔﺣﺗ ﻲﻓ behaviors and medication adherence in Saudi Arabian patients with coronary artery ﻛﻣ بﺗ ا ﻟ ﺑ ثﺣﺎ ﻲﻓ زﻛرﻣ ا ﻟ ﻘ .بﻠ ﻟ ﻔﺣﻠ ظﺎ ﻰﻠﻋ ﺔﯾﺻوﺻﺧﺔﺻﺻ ﻠ ﺎﻔﻠﻟ ب زر ﻓثﺎﺑﻟا ﺗﻛ disease. This study will have future benefits ،نﯾﻛرﺎﺷﻣﻟا ﻊﯾﻣﺟ ﺗﺳﻻا ﺑ ﯾ ﺎ ﻧ ﺎ ت ﻧورﺗﻛﻟﻻا ﺔﯾ فوﺳ ظﻔﺣﺗ نودﺑ ءﺎﻣﺳا to patients diagnosed with CAD, as it may نﯾﻛرﺎﺷﻣﻟا نﻟو بﻠطﯾ نﻣ كرﺎﺷﻣﻟا ﺔﺑﺎﺗﻛ مﺳﻻا ﻲﻓ .ﺔﻧﺎﺑﺗﺳﻻا ’provide valuable information about patients ﻊﯾﻣﺟ ا ﻟ ﺑ ﯾ ﺎ ﻧ تﺎ فوﺳ ظﻔﺣﺗ ﻲﻓ ( يﻻا )دوﻼﻛ شﻼﻓو درﺎﻛ ﻊﻣ psychological needs in health behaviors and ةرﺎﺷﻻا نآ ا ﻟ ﺑ ثﺣﺎ ا ﺋرﻟ ﻲﺳﯾ وھ نﻣ ﻊﯾطﺗﺳﯾ عﻼطﻻا ﻠﻋ ﺎﮭﯾ ﻓ .طﻘ .their relation to medication adherence ﻊﯾﻣﺟ ةزﮭﺟأ ا ﺑﻣﻛﻟ رﺗوﯾ ةزﮭﺟأو يﻻا ﺑ دﺎ فوﺳ بﻠطﺗ رﻗﻣﺎً ﺳرﯾﺎً Confidential and anonymous: No لوﺧدﻟ ا ﺎﮭﯾﻟ طﻘﻓو ا ثﺣﺎﺑﻟ ا ﻲﺳﯾﺋرﻟ وھ نﻣ نوﻌﯾطﺗﺳﯾ عﻼطﻻا identifying information will be included in the data you provide. Your signed consent ﻠﻋ ﺎﮭﯾ . فوﺳ ﯾ ﺗ م ا فﻼﺗ ﻊﯾﻣﺟ ا ﻟ ﺑ ﯾ ﺎ ﻧ تﺎ دﻌﺑ ثﻼﺛ تاوﻧﺳ نﻣ ا ﺎﻣﺗ م م ﺎﻣﺗ ا نﻣ تاوﻧﺳ ثﻼﺛ دﻌﺑ تﺎ ﻧ ﺎ ﯾ ﺑ ﻟ ا ﻊﯾﻣﺟ فﻼﺗ ا م ﺗ ﯾ فوﺳ . ﺎﮭﯾ ﻠﻋ
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.ﺔﺳاردﻟا اذا نﺎﻛ كﯾدﻟ يا لاؤﺳ نﻋ هذھ ،ﺔﺳاردﻟا ﻰﺟرﯾ ﺔﻠﺳارﻣ ,form will be kept separate from your data فرﺷﻣ ا ﺎﺳرﻟ ﺔﻟ ا ﻟ ﺛﺣﺑ ﺔﯾ ا ﻟ روﺗﻛد ﻟ ﯾ دﻧ ا ﺎﺷ سﻛﻧ نﻣ لﻼﺧ لﺎﺻﺗﻻا and nobody will be able to link your ﻰﻠﻋ وا ٣٣٠٩٧٢٦٦٩٩[email protected] وا لﺎﺳرا responses to you. Any identifying information collected will be kept in a ﯾرﺑ د إ ﻟ ﻲﻧورﺗﻛ ا ﻰﻟ هذھ ا ﻟ ﺔﺳارد وا ﻻا لﺎﺻﺗ ﻰﻠﻋ ا ﻟ ﺑ ثﺣﺎ ثﺣﺎ ﺑ ﻟ ا ﻰﻠﻋ لﺎﺻﺗ ﻻا وا ﺔﺳارد ﻟ ا هذھ ﻰﻟ ا ﻲﻧورﺗﻛ ﻟ إ د ﯾرﺑ secure location and only the researchers will ﺑﻋ د ا ﻟ زﯾزﻌ ا ﻟ اورﻣ ﻲﻧ ﻰﻠﻋ ٠٥٦١٥٥٦٦٣٥ وا have access to the data. Participants will not be individually identified in any publication [email protected] or presentation of the research results. Confidentiality of records: All data will be stored in the researcher’s office at Madhinah Cardiac Center (MCC) in a locked file cabinet. To maintain confidentiality, all the online surveys taken on the iPads and papers will be anonymous and no name will be اذإ نﺎﻛ كﯾدﻟ يا ﺳ لاؤ لوﺣ كوﻘﺣ ﺎﺷﻣﻛ كر ﻓ ﻲ ھ ذ ه ا ﻟ د ر ا ﺳ ﺔ required. All obtained data will be saved in كﻧﻛﻣﯾ لﺎﺻﺗﻻا ﻰﻠﻋ مﺳﻗ ا ﻟ ثﺣﺑ ﻲﻓ ﺔﻌﻣﺎﺟ نورﻛا ﻰﻠﻋ ا مﻗرﻟ the online iCloud and on the USB, and only :ﻲﻟﺎﺗﻟا ٧٦٦٦ ٩٧٢ ٣٣٠ وا لﺎﺳرا دﯾرﺑ ا ﻰﻟ the researcher will have access to them. The researcher’s computer, iPads, USB drive, [email protected] and the online iCloud will have a secure password. Three years after completing the ﺎﻧآ مﻠﻋا ﻲﻧﻧا فوﺳ كرﺎﺷا ﻲﻓ هذھ ﺔﺳاردﻟا ﻲﺗﻟاو دﻗ نوﻛﺗ وا ﻻ study, all data will be destroyed. If you have نوﻛﺗ ﻔﻣ ةدﯾ ﻲﻟ ﺑ لﻛﺷ ﻣ ﺑ ﺎ رﺷ نﻛﻟو دﻗ رﻓوﺗ هذھ ا ﺔﺳاردﻟ تﺎﻣوﻠﻌﻣ any questions about this study, you may ةدﯾدﺟ ﻟ ﻰﺿرﻣﻠ ا ﻟ نﯾذ ﺎﻌﯾ نوﻧ نﻣ ﻧ سﻔ ا ضرﻣﻟ ﻲﻓ ا ﺗﺳﻣﻟ ﻘ .لﺑ ل ﺳﻟا ﻓضﻣ س ن و ﻌ نذﻟا ﺿﻣ دد contact the academic advisor (Dr. Linda Shanks) at (330-972-6699) or at{[email protected]} or you may contact the principal investigator Mr. Abdulaziz Almarwani at (0571556635) or ([email protected]).
If you have any questions about your rights as research subject, you may contact The University of Akron IRB [email protected] or 330-972-7666.
I understand that I will be participating in a study, which may, or may not benefit me directly, but I will provide new knowledge, which could benefit other patients with similar conditions to mine in the future.
ﻊﯿﻗﻮﺘﻟا Signature
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APPENDIX F
ARABIC STUDY SURVEY
آوﻻ ﺷﻛراً ﻟﻘﺑوﻟك اﻟﻣﺷﺎرﻛﺔ ﻓﻲ ھذه اﻟدراﺳﺔ. ﺛﺎﻧﯾﺎَ اﻟرﺟﺎء وﺿﻊ داﺋرة ﻋﻠﻰ اﻻﺟﺎﺑﺔ اﻟﻣﻧﺎﺳﺑﺔ ﻟﻸﺳﺋﻠﺔ :ﺔﯾﻟﺎﺗﻟا 1. سﻧﺟﻟا o رﻛذ o ﻲﺛﻧا 2. مﻛ ؟كرﻣﻋ
3. ﻲھﺎﻣ ﻟﺎﺣ كﺗ ﺔﯾﻋﺎﻣﺗﺟﻻا ؟ o بزﻋأ o جوزﺗﻣ o لﻣرأ o ﻧﻣ لﺻﻔ 4. ﺎﻣ ﻰﻠﻋا ﺔﺟرد وآ ىوﺗﺳﻣ ﻲﺳارد تﻣﻗ ﺑ ﺈ ؟هزﺎﺟﻧ o مﻟ لﻣﻛأ ﻲﻣﯾﻠﻌﺗ )ﻲﻣا( o ﻧﺎﺛﻟا ﺔﯾو ا ﺔﻣﺎﻌﻟ وا ا لﻗ o سوﯾروﻟﺎﻛﺑﻟا o تﺎﺳارد ﻠﻋ ﯾ ﺎ 5. ﺎﻣ ﻲھ ﻟﺎﺣ كﺗ ا ﺔﯾﻔﯾظوﻟ ا ﻟﺎﺣﻟ ؟ﺔﯾ o ﺎط بﻟ o فظوﻣ o رﯾﻏ فظوﻣ o ﺗﻣ ﻘ دﻋﺎ لﺑﻗ مﻛ رﮭﺷ مﺗ كﺻﯾﺧﺷﺗ ضرﻣﺑ بﻠﺻﺗ ﯾﯾارﺷﻟا ن ؟ﺔﯾﺑﻠﻘﻟا
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ﺮﮭﺷﻷﺎﺑ
لاؤﺳﻟا ﻲﻟﺎﺗﻟا وھ نﻋ بﺎﺑﺳﻻا ﻲﺗﻟا كﻠﻌﺟﺗ سرﺎﻣﺗ ﺔﺿﺎﯾرﻟا وا رﻣﺗﺳﺗ ﺔﺳرﺎﻣﻣﺑ .ﺔﺿﺎﯾرﻟا ﯾﺛﻛﻟا ر نﻣ نﻣ سﺎﻧﻟا مﮭﯾدﻟ ﺳأ بﺎﺑ .ﺔﻔﻠﺗﺧﻣ ﻊﯾﻣﺟ ﺎﺟﻹا ﺑ تﺎ ﻲھ لاؤﺳﻟ دﺣاو لﻛو بﺑﺳ نﻣ ﺑﺳﻻا بﺎ ا ﻟ ﺗ ﺎ ﻟ ﺔﯾ ﻟ ﺔﯾد ﺔﯾد ﻟ ﺔﯾ ﻟ ﺎ ﺗ ﻟ ا بﺎ ﺑﺳﻻا نﻣ بﺑﺳ لﻛو دﺣاو لاؤﺳﻟ ﻲھ تﺎ ﺑ ﺎﺟﻹا ﻊﯾﻣﺟ ﻘﻣ ﯾ سﺎ نﻣ ٧ ﻗرا .مﺎ كﻟذﻟ دﯾرﻧ نا فرﻌﻧ ىدﻣ ﺔﺣﺻ لﻛ نﻣ ا ﺑﺳﻻ بﺎ .ﺔﯾﻟﺎﺗﻟا ( ﻊﺿ د ا ﺋ ر ة ﻋ ﻠ ﻰ ا ﻟ ر ﻗ م بﺳﺎﻧﻣﻟا ) :لاؤﺳﻟا بﺑﺳﻟا ﻲﻓ ﻲﻧﻧأ فوﺳ سرﺎﻣأ ﺔﺿﺎﯾرﻟا مﺎظﺗﻧﺎﺑ :وھ
١ ٢ ٣ ٤ ٥ ٦ ٧ ﺟﺪاً ﺮﯿﻏ ﺢﯿﺤﺻ ﻰﻟا ﺪﺣ ﺎﻣ ﺤﺻ ﯿ ﺢ ﺤﺻ ﯿ ﺢ ١ . ﻲﻨﻧﻷ ﺪﯾرأ ﻞﻤﺤﺗ ﺔﯿﻟوﺆﺴﻤﻟا هﺎﺠﺗ ١ ٢ ٣ ٤ ٥ ٦ ٧ ﺤﺻ ﺘ ﻲ . ٢. ﻷﻧﻨﻲ ﺷﺨﺼﯿﺎً أﻋﺘﻘﺪ أن اﻟﺮﯾﺎﺿ ﺔ أ ﻞﻀﻓ ١ ٢ ٣ ٤ ٥ ٦ ٧ ءﻲﺷ ﺤﺼﻟ ﺘ ﻲ .
٣ ﻧﻷ. ﻲﻨ ﻓ تﺮﻜ ﺑ ﻌ ﻨ ﺎ ﯾ ﺔ ﻲﻓ ،ﻚﻟذ ﺪﻘﺘﻋأو نأ ١ ٢ ٣ ٤ ٥ ٦ ٧ ﺔﺿﺎﯾﺮﻟا ﻢﮭﻣ اﺪﺟ ﺔﺒﺴﻨﻟﺎﺑ ﺪﯾﺪﻌﻠﻟ ﻦﻣ ﺐﻧاﻮﺟ ﯿﺣ ﺎ .ﻲﺗ ٤. ﻷن اﻟﺮﯾﺎﺿﺔ ﺧﯿﺎر ﻣﮭﻢ أرﯾﺪ ﻓﻌﻠﮫ ﺣﻘًﺎ. ١ ٢ ٣ ٤ ٥ ٦ ٧
٥ نﻷ. ا ﯾﺮﻟ ﺔﺿﺎ ﺗ ﺘ ﻖﻔ ﻊﻣ أ ﺪھ فا ﯿﺣ ﺎ .ﻲﺗ ١ ٢ ٣ ٤ ٥ ٦ ٧
٦ . نﻷ ﺔﺿﺎﯾﺮﻟا ﮫﻤﮭﻣ ﻲﻓ ﻲﻠﻌﺟ ﺎﺤﺑ ﻟ ﺔ ١ ٢ ٣ ٤ ٥ ٦ ٧ ﺔﯿﺤﺻ ﺎﻋ ﺔﯿﻟ رﺪﻗ .نﺎﻜﻣﻹا
لاؤﺳﻟا ﻲﻟﺎﺗﻟا وھ نﻋ بﺎﺑﺳﻻا ﻲﺗﻟا كﻠﻌﺟﺗ أدﺑﺗ لﻛﺄﺑ لﻛا ﻲﺣﺻ او عﺎﺑﺗ مﺎظﻧ اذﻏ ﻲﺋ ﻲﺣﺻ وا وا ﻲﺣﺻ ﻲﺋ اذﻏ مﺎظﻧ عﺎﺑﺗ او ﻲﺣﺻ لﻛا رارﻣﺗﺳﻻا أذﺑ .كﻟ ا رﯾﺛﻛﻟ نﻣ ا ﻟ ﻧ سﺎ مﮭﯾدﻟ ﺑﺳأ بﺎ ﺧﻣ ﺗ ﻠ ﻔ ﺔ . ﻣﺟ ﯾ ﻊ ﺎﺟﻹا ﺑ تﺎ ﻲھ لاؤﺳﻟ دﺣاو لﻛو بﺑﺳ بﺑﺳ لﻛو دﺣاو لاؤﺳﻟ ﻲھ تﺎ ﺑ ﺎﺟﻹا نﻣ ﺑﺳﻻا بﺎ ا ﻟ ﺗ ﺎ ﻟ ﺔﯾ ﺔﯾدﻟ ﯾﻘﻣ سﺎ نﻣ ٧ ا ﻗر ﺎ م . كﻟذﻟ دﯾرﻧ نا فرﻌﻧ ىدﻣ ﺔﺣﺻ لﻛ نﻣ بﺎﺑﺳﻻا بﺎﺑﺳﻻا نﻣ لﻛ ﺔﺣﺻ ىدﻣ فرﻌﻧ نا دﯾرﻧ كﻟذﻟ .ﺔﯾﻟﺎﺗﻟا ( ﻊﺿ ةرﺋاد ﻰﻠﻋ ا مﻗرﻟ ا )بﺳﺎﻧﻣﻟ :لاؤﺳﻟا
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بﺑﺳﻟا ﻲﻓ ﻲﻧﻧأ فوﺳ ﻊﺑﺗا مﺎظﻧ ﻲﺋاذﻏ ﻲﺣﺻ :وھ
١ ٢ ٣ ٤ ٥ ٦ ﺮﯿﻏ ﻰﻟا ﺪﺣ ﺎﻣ ٧ ﺟﺪاً ﺤﺻ ﯿ ﺢ ﺤﺻ ﯿ ﺢ ﺤﺻ ﯿ ﺢ ١ . ﻲﻨﻧﻷ ﺪﯾرأ ﻞﻤﺤﺗ ﺔﯿﻟوﺆﺴﻤﻟا هﺎﺠﺗ .ﻲﺘﺤﺻ ١ ٢ ٣ ٤ ٥ ٦ ٧
٢. ﻷﻧﻨﻲ ﺷﺨﺼﯿﺎً أﻋﺘﻘﺪ أن اﻟﻨﻈﺎم اﻟﻐﺬاﺋﻲ ١ ٢ ٣ ٤ ٥ ٦ ٧ ﻞﻀﻓأ ءﻲﺷ .ﻲﺘﺤﺼﻟ
٣ ﻧﻷ. ﻲﻨ ﻓ تﺮﻜ ﺑ ﻌ ﻨ ﺎ ﯾ ﺔ ﻲﻓ ،ﻚﻟذ ﺪﻘﺘﻋأو نأ ١ ٢ ٣ ٤ ٥ ٦ ٧ عﺎﺒﺗا مﺎﻈﻨﻟا ﻲﺋاﺬﻐﻟا ﻢﮭﻣ اﺪﺟ ﺔﺒﺴﻨﻟﺎﺑ ﺪﯾﺪﻌﻠﻟ ﻦﻣ ﻮﺟ ا ﺐﻧ ﺣ ﯿ ﺎ .ﻲﺗ ٤ . نﻷ مﺎﻈﻨﻟا ﻲﺋاﺬﻐﻟا ﯿﺧ رﺎ ﻢﮭﻣ ﯾرأ ﺪ ﻌﻓ ﻠ ﮫ ١ ٢ ٣ ٤ ٥ ٦ ٧ ﺣﻘًﺎ.
٥. نﻷ ا ﺗ ﺒ ﺎ ع ﻧ ﻈ ﺎ م ﻏ ﺬ ا ﺋ ﻲ ﯾ ﻖﻔﺘ ﻊﻣ فاﺪھأ ١ ٢ ٣ ٤ ٥ ٦ ٧ ﯿﺣ ﺎ .ﻲﺗ
٦ . نﻷ عﺎﺒﺗا مﺎﻈﻧ ﻲﺋاﺬﻐﻟا ﻲﺤﺻ ﮫﻤﮭﻣ ﻲﻓ ١ ٢ ٣ ٤ ٥ ٦ ٧ ﻲﻠﻌﺟ ﺎﺤﺑ ﺔﻟ ﺔﯿﺤﺻ ﺎﻋ ﻟ ﺔﯿ رﺪﻗ .نﺎﻜﻣﻹا
لاؤﺳﻟا ﻲﻟﺎﺗﻟا وھ نﻋ بﺎﺑﺳﻻا ﻲﺗﻟا كﻠﻌﺟﺗ فﻗوﺗﺗ نﻋ نﯾﺧدﺗﻟا وأ نوﻛﺗ رﯾﻏ .نﺧدﻣ ا ﻟ ﺛﻛ ﯾ ر نﻣ نﻣ سﺎﻧﻟا مﮭﯾدﻟ بﺎﺑﺳأ .ﺔﻔﻠﺗﺧﻣ كﻟذﻟ دﯾرﻧ نا فرﻌﻧ ىدﻣ ﺔﺣﺻ لﻛ نﻣ بﺎﺑﺳﻻا .ﺔﯾﻟﺎﺗﻟا ﯾﻣﺟ ﻊ ﺎﺟﻵا ﺑ تﺎ تﺎ ﺑ ﺎﺟﻵا ﻲھ لاؤﺳﻟ دﺣاو لﻛو بﺑﺳ نﻣ ﺑﺳﻻا بﺎ ا ﻟ ﺗ ﺎ ﻟ ﺔﯾ ﺔﯾدﻟ ﻘﻣ ﯾ سﺎ نﻣ ٧ ﻗرا .مﺎ ﻊﺿ( د ا ةرﺋ ﻰﻠﻋ ا مﻗرﻟ مﻗرﻟ ا ﻰﻠﻋ ةرﺋ ا د ﻊﺿ( .مﺎ ﻗرا )بﺳﺎﻧﻣﻟا :لاؤﺳﻟا بﺑﺳﻟا ﻲﻓ ﻲﻧﻧأ ﻻ نﺧدأ :وھ ١ ٢ ٣ ٤ ٥ ٦ ٧ ﺮﯿﻏ ﻰﻟا ﺪﺣ ﺟﺪاً ﺤﺻ ﯿ ﺢ ﺎﻣ ﺤﺻ ﯿ ﺢ ﺤﺻ ﯿ ﺢ ١ . ﻲﻨﻧﻷ ﺪﯾرأ ﻞﻤﺤﺗ ا ﻟ ﻟوﺆﺴﻤ ﺔﯿ هﺎﺠﺗ .ﻲﺘﺤﺻ ١ ٢ ٣ ٤ ٥ ٦ ٧
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٢. ﻷﻧﻨﻲ ﺷﺨﺼﯿﺎً أﻋﺘﻘﺪ أن ﻋﺪم اﻟﺘﺪﺧﯿﻦ ھﻮ أﻓﻀﻞ ١ ٢ ٣ ٤ ٥ ٦ ٧ ءﻲﺷ ﺤﺼﻟ ﺘ ﻲ .
٣ ﻧﻷ. ﻲﻨ ﻓ تﺮﻜ ﺑ ﻌ ﻨ ﺎ ﯾ ﺔ ﻲﻓ ،ﻚﻟذ ﺪﻘﺘﻋأو نأ مﺪﻋ ١ ٢ ٣ ٤ ٥ ٦ ٧ ﻦﯿﺧﺪﺘﻟا ﻢﮭﻣ اﺪﺟ ﺔﺒﺴﻨﻟﺎﺑ ﺪﯾﺪﻌﻠﻟ ﻦﻣ ﺐﻧاﻮﺟ .ﻲﺗﺎﯿﺣ ٤ . نﻷ ﺪﻋ م ا ﻟ ﺘ ﻦﯿﺧﺪ ﻮھ ﯿﺧ رﺎ ﻢﮭﻣ ﯾرأ ﺪ ﻓ ﻌﻠﮫ ﺣﻘًﺎ. ١ ٢ ٣ ٤ ٥ ٦ ٧
٤ نﻷ. مﺪﻋ ا ﻟ ﻦﯿﺧﺪﺘ ﯾ ﺘ ﻖﻔ ﻊﻣ ﺪھأ فا ﯿﺣ ﺎ .ﻲﺗ ١ ٢ ٣ ٤ ٥ ٦ ٧
٦ . نﻷ ﺪﻋ م ا ﻟ ﺘ ﻦﯿﺧﺪ ﮫﻤﮭﻣ ﻲﻓ ﻲﻠﻌﺟ ﺎﺤﺑ ﻟ ﺔ ﯿﺤﺻ ﺔ ١ ٢ ٣ ٤ ٥ ٦ ٧ ﺎﻋ ﻟ ﯿ ﺔ ﻗ رﺪ ﻜﻣﻹا .نﺎ
ﺎﻣ ىدﻣ ﺔﺣﺻ لﻛ نﻣ اذھ ا لﻣﺟﻟ ﺑ ﺎ ﻟ ﺔﺑﺳﻧ ،كﻟ ﻰﻠﻋ ا ﻓ ضارﺗ أ كﻧ تﻧﻛ ﺗ يوﻧ نا ﺗ فﻗوﺗ نﻋ ﺗ نﯾﺧد نﯾﺧد ﺗ نﻋ فﻗوﺗ ﺗ نا يوﻧ ﺗ تﻧﻛ كﻧ أ ضارﺗ ﻓ ا ﻰﻠﻋ ﻧﮭﺎﺋﯾﺎً أو كﻧأ ﻻ نﺧدﺗ ﻻا ن دﺧﺗﺳا م ا ﻟ ﻣ ﻘ سﺎﯾ :ﻲﻟﺎﺗﻟا
١ ٢ ٣ ٤ ٥ ٦ ٧ ﺮﯿﻏ ﻰﻟا ﺪﺣ ﺎﻣ ﺟﺪاً ﺻﺤﯿﺢ ﺤﺻ ﯿ ﺢ ﺤﺻ ﯿ ﺢ ١ . ﺮﻌﺷأ ﺑ ﺎ ﻟ ﺜ ﺔﻘ ﻲﻓ ﻗ ﻲﺗرﺪ ﻰﻠﻋ مﺪﻋ ١ ٢ ٣ ٤ ٥ ٦ ٧ ﻦﯿﺧﺪﺘﻟا
٢ . ﺮﻌﺷأ نﻵا ﻲﻨﻧأ ردﺎﻗ ﻰﻠﻋ مﺪﻋ ١ ٢ ٣ ٤ ٥ ٦ ٧ .ﻦﯿﺧﺪﺘﻟا
٣ . ﺎﻧأ ردﺎﻗ ﻰﻠﻋ مﺪﻋ ﻦﯿﺧﺪﺘﻟا ﺪﻌﺑ .نﻵا ١ ٢ ٣ ٤ ٥ ٦ ٧
٤ . ﺎﻧأ ردﺎﻗ ﻰﻠﻋ ﺔﮭﺟاﻮﻣ يﺪﺤﺗ مﺪﻋ ١ ٢ ٣ ٤ ٥ ٦ ٧ .ﻦﯿﺧﺪﺘﻟا
ﺎﻣ ىدﻣ ﺔﺣﺻ لﻛ نﻣ اذھ ا لﻣﺟﻟ ﺑ ﺎ ﻟ ﺔﺑﺳﻧ ،كﻟ ﻰﻠﻋ ا ﻓ ضارﺗ أ كﻧ تﻧﻛ ﺗ يوﻧ نﯾﺳﺣﺗ كﻣﺎظﻧ ا ﻟ ذﻐ ا ﻲﺋ ﻲﺋ ا ذﻐ ﻟ ا كﻣﺎظﻧ نﯾﺳﺣﺗ يوﻧ ﺗ تﻧﻛ كﻧ أ ضارﺗ ﻓ ا ﻰﻠﻋ لﻛﺷﺑ د ا ﺋ م أ و ا ﻔﺣﻟ ظﺎ ﻰﻠﻋ ﺎظﻧ م ذﻏ ا ﻲﺋ .ﻲﺣﺻ مدﺧﺗﺳا ا ﻟ ﻘﻣ ﯾ سﺎ ا ﻟ ﺗ ﺎ :ﻲﻟ
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١ ٢ ٣ ٤ ٥ ٦ ٧ ﺟﺪاً ﺮﯿﻏ ﻰﻟا ﺪﺣ ﺎﻣ ﺤﺻ ﯿ ﺢ ﺤﺻ ﯿ ﺢ ﺤﺻ ﯿ ﺢ ١ . ﺮﻌﺷأ ﺔﻘﺜﻟﺎﺑ ﻲﻓ ﻲﺗرﺪﻗ ﻰﻠﻋ ظﺎﻔﺤﻟا ﻰﻠﻋ ﺎﻈﻧ م ١ ٢ ٣ ٤ ٥ ٦ ٧ ﺬﻏ ا ﻲﺋ .ﻲﺤﺻ
٢ . ﺮﻌﺷأ نﻵا ﻲﻨﻧأ ردﺎﻗ ﻰﻠﻋ ظﺎﻔﺤﻟا ﻰﻠﻋ مﺎﻈﻧ ١ ٢ ٣ ٤ ٥ ٦ ٧ ﺬﻏ ا ﻲﺋ .ﻲﺤﺻ
٣ . ﺎﻧأ ردﺎﻗ ﻰﻠﻋ ظﺎﻔﺤﻟا ﻰﻠﻋ مﺎﻈﻧ ﻲﺋاﺬﻏ ﻲﺤﺻ ١ ٢ ٣ ٤ ٥ ٦ ٧ ﻞﻜﺸﺑ د ا ﺋ ﻢ .
٤ . ﺎﻧأ ردﺎﻗ ﻰﻠﻋ ﺔﮭﺟاﻮﻣ يﺪﺤﺘﻟا ﻞﺜﻤﺘﻤﻟا ﻲﻓ ١ ٢ ٣ ٤ ٥ ٦ ٧ ا ﻔﺤﻟ ظﺎ ﻰﻠﻋ ﺎﻈﻧ م ﺬﻏ ا ﻲﺋ .ﻲﺤﺻ
ﺎﻣ ىدﻣ ﺔﺣﺻ لﻛ نﻣ اذھ ا لﻣﺟﻟ ﺑ ﺎ ﻟ ﺔﺑﺳﻧ ،كﻟ ﻋﻠﻰ اﻓﺗراض أﻧك ﺗﻧوي إﻣﺎ أن ﺗﺑدأ اﻵن ﻧظﺎ ًﻣﺎ داﺋ ًﻣﺎ ﻟﻣﻣﺎرﺳﺔ اﻟرﯾﺎﺿﺔ ﺑﺎﻧﺗظﺎم أو ﻟﻠﺣﻔﺎظ داﺋ ًﻣﺎ ﻋﻠﻰ ﻧظﺎم اﻟﺗﻣرﯾن اﻟﻣﻧﺗظم اﻟﺧﺎص ﺑك. اﺳﺗﺧدم اﻟﻣﻘﯾﺎس :ﻲﻟﺎﺗﻟا
١ ٢ ٣ ٤ ٥ ٦ ٧ ﺟﺪاً ﺮﯿﻏ ﻰﻟا ﺪﺣ ﺎﻣ ﺤﺻ ﯿ ﺢ ﺤﺻ ﯿ ﺢ ﺤﺻ ﯿ ﺢ ١ . رﻌﺷأ ﺔﻘﺛﻟﺎﺑ ﻲﻓ ﻲﺗردﻗ ﻰﻠﻋ ﺔﺳرﺎﻣﻣ ا ﺔﺿﺎﯾرﻟ ١ ٢ ٣ ٤ ٥ ٦ ٧ .مﺎظﺗﻧﺎﺑ
٢ . رﻌﺷأ نﻵا ﻲﻧﻧأ ردﺎﻗ ﻰﻠﻋ ﺔﺳرﺎﻣﻣ ا ﺔﺿﺎﯾرﻟ ١ ٢ ٣ ٤ ٥ ٦ ٧ .مﺎظﺗﻧﺎﺑ
٣ . ﺎﻧأ ردﺎﻗ ﻰﻠﻋ ﺔﺳرﺎﻣﻣ ا ﺔﺿﺎﯾرﻟ مﺎظﺗﻧﺎﺑ ﻰﻠﻋ ١ ٢ ٣ ٤ ٥ ٦ ٧ ىدﻣﻟا .لﯾوطﻟا
٤ . ﺎﻧأ ردﺎﻗ ﻰﻠﻋ وﻣ ﺔﮭﺟا ا ﻟ يدﺣﺗ ا ﻟ ﺛﻣﺗﻣ ل ﻲﻓ ١ ٢ ٣ ٤ ٥ ٦ ٧ ﺔﺳرﺎﻣﻣ ا ﯾرﻟ ﺔﺿﺎ ﺑ ﺎ ﻧ .مﺎظﺗ
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تﺎﺣﯾرﺻﺗﻟا ﺔﯾﻟﺎﺗﻟا لﺛﻣﺗ رﻋﺎﺷﻣ ﺔﻔﻠﺗﺧﻣ ىدﻟ سﺎﻧﻟا ﺎﻣدﻧﻋ نوﻛرﺎﺷﯾ ﻲﻓ يأ طﺎﺷﻧ .ﻲﻧدﺑ ﻰﺟرﯾ ﻰﺟرﯾ .ﻲﻧدﺑ طﺎﺷﻧ يأ ﻲﻓ نوﻛرﺎﺷﯾ ﺎﻣدﻧﻋ سﺎﻧﻟا ىدﻟ ﺔﻔﻠﺗﺧﻣ رﻋﺎﺷﻣ لﺛﻣﺗ ﺔﯾﻟﺎﺗﻟا تﺎﺣﯾرﺻﺗﻟا ﺎﺟﻹا ﺑ ﺔ ﻰﻠﻋ ﺋﺳﻻا ﻠ ﺔ ا ﻟ ﺗ ﺎ ﻲﻟ نﻣ لﻼﺧ ا ﻟ ﺗ رﯾﻛﻔ ﻲﻓ ا ﯾرطﻟ ﺔﻘ ا ﻟ ﻲﺗ رﻌﺷﺗ ﺎﮭﺑ ﻧﻋ د ا ﻟ ﺔﻛرﺎﺷﻣ ﻲﻓ يأ طﺎﺷﻧ طﺎﺷﻧ يأ ﻲﻓ ﺔﻛرﺎﺷﻣ ﻟ ا د ﻧﻋ ﺎﮭﺑ رﻌﺷﺗ ﻲﺗ ﻟ ا ﺔﻘ ﯾرطﻟ ا ﻲﻓ رﯾﻛﻔ ﺗ ﻟ ا لﻼﺧ نﻣ ﻲﻟ ﺎ ﺗ ﻟ ا ﺔ ﻠ ﺋﺳﻻا ﻰﻠﻋ ﺔ ﺑ ﺎﺟﻹا ﻲﻧدﺑ مادﺧﺗﺳﺎﺑ ا سﺎﯾﻘﻣﻟ ا .مدﻘﻣﻟ
١ ٢ ٣ ٤ ٥ ٦ ﻄﺧ ﺂ ﻲﻓ ا ﻟ ﻐ ﺎ ﺐﻟ ﺌطﺎﺧ ﺔ ا ﺮﺜﻛ ﺤﺻ ﯿ ﺤ ﮫ ﻲﻓ ﺤﺻ ﯿ ﺢ ﺮﯿﻏ ﻦﻣ ا ﻧ ﮭ ﺎ ﺮﺜﻛا ﻦﻣ ﺐﻟﺎﻐﻟا ﺐﻟﺎﻐﻟا ﺤﺻ ﯿ ﺤ ﺔ ﺤﺻ ﯿ ﺤ ﺔ ﺎﮭﻧا ﺤﺻ ﯿ ﺢ ﺌطﺎﺧ ﺔ ١ . ﺮﻌﺷأ ﻲﻨﻧﺄﻛ ترﻮط ﺔﻗﻼﻋ ﺔﻘﯿﺛو ﻊﻣ ١ ٢ ٣ ٤ ٥ ٦ ﻦﯾﺮﺧﻵا ٢ . ﺮﻌﺷأ ﻲﻨﻧﺄﻛو ﻲﻓ ﺔﻟﺎﺣ ﺐﺳﺎﻨﺗ ةﺪﯿﺟ ﻊﻣ ١ ٢ ٣ ٤ ٥ ٦ ﻦﯾﺮﺧﻵا
٣ . ﺮﻌﺷأ ﻲﻨﻧﺄﻛو لﻮﻤﺸﻣ ﻦﻣ ﻗ ﺒ ﻞ ﻦﯾﺮﺧﻵا ١ ٢ ٣ ٤ ٥ ٦
٤ ﺮﻌﺷأ. ﻲﻨﻧﺄﻛو ءﺰﺟ ﻦﻣ ﺔﻋﻮﻤﺠﻣ ﻲﻧﻮﻛرﺎﺸﯾ ١ ٢ ٣ ٤ ٥ ٦ اﺪھأ ﻲﻓ
٥ . ﺮﻌﺷأ ﻢﻋﺪﻟﺎﺑ ﻦﻣ ﻞﺒﻗ ﻦﯾﺮﺧﻵا ﻲﻓ اﺬھ ١ ٢ ٣ ٤ ٥ ٦ طﺎﺸﻨﻟا
٦ . ﺮﻌﺷأ نأ ﻦﯾﺮﺧﻵا ﻲﻨﻧوﺪﯾﺮﯾ نأ كرﺎﺷأ ١ ٢ ٣ ٤ ٥ ٦ ﻢﮭﻌﻣ .
ﻰﺟﺮﯾ ﺎﺟﻹا ﺔﺑ ﻦﻋ ﻞﻛ لاﺆﺳ ﻦﻣ ﺌﺳﻷا ﻠ ﺔ ا ﻟ ﺘ ﺎ ﻟ ﺔﯿ ﺑ ﻨ ءﺎ ﻰﻠﻋ ﻚﺘﺑﺮﺠﺗ ﺼﺨﺸﻟا ﺔﯿ ﺎﻤﯿﻓ ﯾ ﻖﻠﻌﺘ لوﺎﻨﺘﺑ ﻚﺘﯾودا .
؟ ﻞھ ﻖﺒﺳ نآ ﺖﯿﺴﻧ نأ ﺗ ﺬﺧﺄ ا ﻟ وﺪ ا ء ا صﺎﺨﻟ ﻚﺑ ﻢﻌﻧ ﻻ
؟ ﻞھ ﺘﻌﺗ ﺮﺒ ﻧ ﻚﺴﻔ ﻞﻤﮭﻣ ﻲﻓ ﺑ ﺾﻌ ﯿﺣﻷا نﺎ ﻲﻓ لوﺎﻨﺗ ءاوﺪﻟا ﻢﻌﻧ ﻻ
؟ ﻨﻋ ﻣﺪ ﺎ ﺮﻌﺸﺗ ،ﻦﺴﺤﺘﻟﺎﺑ ﻞھ ﺗ ﺘ ﻮ ﻗ ﻒ ﻲﻓ ﺾﻌﺑ ﯿﺣﻷا نﺎ ﻦﻋ ﺗ ﻨ لوﺎ ا ﻟ ءاوﺪ ﻢﻌﻧ ﻻ
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؟ ﻲﻓ ﺑ ﺾﻌ ﯿﺣﻷا ،نﺎ إ اذ ﻨﻛ ﺖ ﺗ ﺮﻌﺸ ﺳﺎﻜﺘﻧﺎﺑ ﺔ ﺎﺣ ﻟ ﻚﺘ ا ﯿﺤﺼﻟ ﺔ ﻨﻋ ﺪ ﺗ ﻨ لوﺎ ،ءاوﺪﻟا ﻞھ ﺗ ﺘ ﻮ ﻗ ﻒ ﻦﻋ ﻨﺗ لوﺎ ا ءاوﺪﻟ ﻢﻌﻧ ﻻ
ﺷﻛراً ﺟزﯾ ًﻼ ﻟﻛم
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APPENDIX G
DEMOGRAPHIC DATA
Please complete the following questions: Male Female
A. What is your gender?
B. What is your age?
Years old.
C. What is your marital status?
Single. Married. Divorced. Widowed.
D. What is the highest degree or level of school you have completed?
No schooling completed. Undergraduate. High School or less. Graduate.
E. What is your employment Status?
Employee. Student. Unemployed. Retired.
F. How long have you been diagnosed with Coronary Artery Disease?
Month/s
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APPENDIX H
TREATMENT SELF-REGULATION QUESTIONNAIRE (TSRQ) (TSRQ) EXERCISE
The following question relates to the reasons why you would either start to exercise regularly or continue to do so. Different people have different reasons for doing that, and we want to know how true each of the following reasons is for you. All 6 response are to the one question.
Please indicate the extent to which each reason is true for you, using the following 7-point scale: The reason I would exercise regularly is: 1. Because I feel that I want to take responsibility for my own health. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 2. Because I personally believe it is the best thing for my health. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 3. Because I have carefully thought about it and believe it is very important for many aspects of my life. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 4. Because it is an important choice I really want to make. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 5. Because it is consistent with my life goals. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 6. Because it is very important for being as healthy as possible. 1__:__2__:__3__:__4__:__5__:__6__:__7__: TSRQ (Diet) The following question relates to the reasons why you would either start eating a healthier diet or continue to do so. Different people have different reasons for doing that, and we want to know how true each of the following reasons is for you. All 6 response are to the same question.
Please indicate the extent to which each reason is true for you, using the following 7-point scale: The reason I would eat a healthy diet is: 1. Because I feel that I want to take responsibility for my own health. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 2. Because I personally believe it is the best thing for my health. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 3. Because I have carefully thought about it and believe it is very important for many aspects of my life.
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1__:__2__:__3__:__4__:__5__:__6__:__7__: 4. Because it is an important choice I really want to make. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 5. Because it is consistent with my life goals. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 6. Because it is very important for being as healthy as possible. 1__:__2__:__3__:__4__:__5__:__6__:__7__:
TSRQ (Smoking) The following question relates to the reasons why you would either stop smoking or continue not smoking. Different people have different reasons for doing that, and we want to know how true each of the following reasons is for you. All 6 response are to the same question.
Please indicate the extent to which each reason is true for you, using the following 7-point scale:
The reason I would not smoke is: 1. Because I feel that I want to take responsibility for my own health. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 2. Because I personally believe it is the best thing for my health. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 3. Because I have carefully thought about it and believe it is very important for many aspects of my life. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 4. Because it is an important choice I really want to make. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 5. Because it is consistent with my life goals. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 6. Because it is very important for being as healthy as possible. 1__:__2__:__3__:__4__:__5__:__6__:__7__:
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APPENDIX I
PERCEIVED COMPETENCE SCALE (PCS) Smoking
Please indicate the extent to which each statement is true for you, assuming that you were intending either to permanently quit smoking now or to remain permanently abstinent from smoking. Use the following scale: 1. I feel confident in my ability to not smoke. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 2. I now feel capable of not smoking. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 3. I am able to not smoke anymore. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 4. I am able to meet the challenge of not smoking. 1__:__2__:__3__:__4__:__5__:__6__:__7__:
(PCS) Maintaining a Healthy Diet Please indicate the extent to which each statement is true for you, assuming that you were intending either to permanently improve your diet now or to maintain a healthy diet. Use the following scale: 1. I feel confident in my ability to maintain a healthy diet. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 2. I now feel capable of maintaining a healthy diet. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 3. I am able to maintain a healthy diet permanently. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 4. I am able to meet the challenge of maintaining a healthy diet. 1__:__2__:__3__:__4__:__5__:__6__:__7__:
(PCS) Exercising Regularly Please indicate the extent to which each statement is true for you, assuming that you were intending either to begin now a permanent regimen of exercising regularly or to permanently maintain your regular exercise regimen. Use the following scale: 1. I feel confident in my ability to exercise regularly. 1__:__2__:__3__:__4__:__5__:__6__:__7__:
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2. I now feel capable of exercising regularly. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 3. I am able to exercise regularly over the long term. 1__:__2__:__3__:__4__:__5__:__6__:__7__: 4. I am able to meet the challenge of exercising regularly. 1__:__2__:__3__:__4__:__5__:__6__:__7__:
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APPENDIX J
RELATEDNESS TO OTHERS IN PHYSICAL ACTIVITY SCALE
The following statements represent different feelings people have when they engage in physical activity. Please answer the following question by considering how YOU TYPICALLY feel when participating in physical activity using the scale provided.
1. I feel like I have developed a close bond with others. 1__:__2__:__3__:__4__:__5__:__6__: 2. I feel like I fit in well with others. 1__:__2__:__3__:__4__:__5__:__6__: 3. I feel like I am included by others. 1__:__2__:__3__:__4__:__5__:__6__: 4. I feel like I am part of a group who share my goals. 1__:__2__:__3__:__4__:__5__:__6__ 5. I feel like I am supported by others in this activity. 1__:__2__:__3__:__4__:__5__:__6__: 6. I feel like others want me to be involved with them. 1__:__2__:__3__:__4__:__5__:__6__:
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APPENDIX K
FOUR ITEM MGL MEDICATION ADHERENCE SCALE
Please answer each of the following questions based on your personal experience in regard to your medications.
Question Yes No Do you ever forget to take your medicine? Are you careless at times about taking your medicine? When you feel better, do you sometimes stop taking your medicine? Sometimes if you feel worse when you take the medicine, do you stop taking it?
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