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Factors associated with patient outcomes following same-day discharge percutaneous coronary intervention Lauck, Sandra Béatrice 2007

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FACTORS ASSOCIATED WITH PATIENT OUTCOMES FOLLOWING SAME-DAY DISCHARGE PERCUTANEOUS CORONARY INTERVENTION  By  SANDRA BEATRICE LAUCK B.A., The University of British Columbia, 1995  A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN NURSING in THE FACULTY OF GRADUATE STUDIES  THE UNIVERSITY OF BRITISH COLUMBIA August 2007 © Sandra Beatrice Lauck, 2007  ABSTRACT  Coronary artery disease continues to cause the majority of deaths and disability in Canada; the resultant demand for percutaneous coronary intervention (PCI) exercises constant pressure on health care systems to meet the growing needs of patients. The practice of same-day discharge PCI has emerged as a medically safe option to optimize resource utilization and to improve access to care. The purpose of this study was to describe elective same-day discharge PCI patients' health behaviour in the two to five days following their procedure. The concepts of cardiac self-efficacy and self-care agency provided a theoretical framework. A telephone questionnaire drawing from existing validated tools was developed to explore the relationships between patient and procedural characteristics, and individuals' capacity to care for themselves following PCI in a study sample of 98 participants. The findings revealed a high degree of adherence to the discharge guidelines, including following medication regimen, making a follow-up appointment, and managing the dressing. Yet, within 24 hours of discharge, over 30% of patients experienced symptoms of myocardial ischemia, with 80% opting to take no action, and a further 10% of the total sample presented to an emergency department. Participants' awareness of how to appropriately manage their chronic disease was low: although over 70% of patients understood the results of their PCI procedure, 38% believed that they no longer had coronary artery disease, 50% did not know how to prevent their heart disease from worsening, and 77% did not intend to participate in cardiac rehabilitation.  Ill  To identify factors associated with lower levels of CSE and SCA, multiple linear regression analysis was carried out. Lack of social support emerged as a significant and consistent predictor of poorer outcomes. In addition, other aspects of psychoemotional distress were also significant factors in patients' cardiac self-efficacy and self-care agency in the recovery period. Same-day discharge PCI presents a feasible and safe option for delivery of care for most patients, but requires improved bridging between acute intervention and chronic disease management, and the identification of tailored interventions or support for individuals at higher risk during the recovery period.  iv TABLE OF CONTENTS Abstract  ii  Table of Contents  iv  List of Tables  ,  vii  List of Figures  x  Acknowledgements  xi  Dedication  xiii  CHAPTER 1 Introduction Percutaneous Coronary Intervention Length of Hospital Stay Changes in the Patient Population  1 1 2 3  Purpose of the Study  4  Significance of the Study  4  Scope of the Study  •••• 5  CHAPTER 2: LITERATURE REVIEW Background Coronary Artery Disease and Associated Risk Factors Treatment Options for Symptomatic Coronary Artery Disease PCI: Patients and Procedures  6 6 8 9  Preparation for Discharge Length of Stay Learning Needs Patient Satisfaction  10 10 12 15  Post -PCI Outcomes Predictors of Outcomes Patient Characteristics Disease Severity and Co-Morbidities Procedural Characteristics  17 17 20 23 26  V  Recovering and Making Changes Recovery Immediately Following PCI Making Changes: Linking CAD and Cardiac Risk Facto Modification  28 28 32  Summary  35  CHAPTER 3: METHODS Theoretical Background  37  Summary of Research Project  42  Research Design  42  Research Questions  43  Research Methods Research Protocol Sample Measurement  43 43 44 45  Socio-Demographic Variables Cardiac Disease Co-Morbidities Cardiovascular Risk Factors Procedural Characteristics Self-Care Agency Patient Satisfaction Cardiac Self-Efficacy Self-Care Behaviour  •  46 47 47 49 49 50 50 51 51  Data Quality  53  Data Analysis Plan Data Screening Description of Sample Statistical Analysis  53 53 54 54  Ethical Considerations  58  CHAPTER 4: ANAYLSIS AND RESULTS Efficiency of Sampling  60  Characteristics of Participants Demographic Characteristics Cardiac Disease and Co-Morbidities  61 61 64  vi Hospitalization and Procedural Characteristics  67  Self -Care Recovery Behaviors Patient Destination Following Discharge Adherence to Instruction Management of Complications and Symptoms  69 69 70 73  Chronic Disease Management  75  Screening for Psychosocial Distress  77  Factor Analysis and Measurement Results Factor Analysis of Cardiac Self-Efficacy (CSE) Items Factor Analysis of Self-Care Agency (SCA) Items Cardiac Self-Efficacy and Self-Care Agency Factor Scores  77 77 78 81  Relationship between Patient Characteristics and CSE and SCA Bivariate Analysis: CSE Bivariate Analysis: SCA - Disease Management Bivariate Analysis: SCA - Lifestyle Management Multivariate Analysis  82 82 87 93 99  Summary  109  CHAPTER 5: DISCUSSION Self Care Recovery Behaviour  Ill  Cardiac Self-Efficacy and Self Care Agency Demographics, Co-Morbidities and Procedural Characteristics Social Support and Psychoemotional Health Predictive Model  115 115 120 123  Methods and Limitations of the Study  123  Implications  126  REFERENCES  129  APPENDICES Appendix A: Chart Extraction Appendix B: Telephone Interview Appendix C: CAD-Specific Index Appendix D: STOP-D Screening Tool Appendix E: UBC-PHC BREB Approval Form  152 156 172 173 174  vii LIST OF TABLES Table 1 Initial Variables Collapsed into New Multivariate or Bivariate Variables  56  Table 2 Post-Discharge Telephone Interview Contact Day  61  Table 3 Demographic Characteristics  63  Table 4 Cardiac Disease and Co-Morbidity Characteristics  65  Table 5 CAD-Specific Index of Co-Morbidity Scores  67  Table 6 Hospitalization and Procedural Characteristics  68  Table 7 Patient Destination  70  Table 8 Adherence to Instructions  72  Table 9 Management of Complications and Symptoms  74  Table 10 Chronic Disease Management  76  Table 11 STOP-Distress Screening Tool  77  Table 12 Exploratory Factor Analysis of Cardiac Self-Efficacy (CSE) Items  78  Table 13 Factor Loadings for 3-Factor Analysis of Self-Care (SCA) Agency  79  Table 14 Factor Loadings for 2-Factor Analysis of Self-Care Agency  80  Table 15 Cardiac Self-Efficacy and Self-Care Agency Factor Scores  81  Table 16 Relationships between Demographics and Cardiac Self-Efficacy  83  Table 17 Relationships between Co-Morbidity and Cardiac Self-Efficacy  84  Table 18 Relationships between Procedural Characteristics and Cardiac Self-Efficacy  86  Table 19 Relationships between STOP-D Scores and Cardiac Self-Efficacy  87  Table 20 Relationships between Demographics and Disease Management  88  Table 21 Relationships between Co-Morbidity and Disease Management  89  Table 22 Relationships between Procedural Characteristics and Disease Management  91  Table 23 Relationships between STOP-D Scores and Disease Management  92  Table 24 Relationships between Demographics and Lifestyle Management  93  Table 25 Relationships between Co-Morbidity and Lifestyle Management  94  Table 26 Relationships between Procedural Characteristics and Lifestyle Management  96  Table 27 Relationships between STOP-D Scores and Lifestyle Management  97  Table 28 Linear Regression Model of Cardiac Self-Efficacy on Predictor Variables  99  Table 29 Model Summary of Predictors of Cardiac Self-Efficacy  101  Table 30 Linear Regression Model of Self-Care Agency - Disease Management on Predictor Variables  102  Table 31 Model Summary of Predictors of Self-Care Agency - Disease Management  104  Table 32 Linear Regression Model of Self-Care Agency - Lifestyle Management on Predictor Variables  105  Table 33 Model Summary of Predictors of Self-Care Agency - Lifestyle Management  108  X  LIST OF FIGURES  Figure 1 Theoretical Elements of Self-Care  39  Figure 2 Theoretical Background Model  41  Figure 3 Recruitment, Enrolment and Response Rates of Participants  60  ACKNOWLEDGEMENTS It is with great gratitude for the learning and the partnership that I acknowledge the contributions of individuals and organizations that have supported and collaborated with this study. First, I wish to acknowledge and thank the patients who consented to participate in this study. Their enthusiasm, encouragement, and desire to contribute sustained me throughout this project. The Heart Centre at St. Paul's Hospital and the staff of the Cardiac Short Stay Unit played an immeasurable role in the success of this study. Not only did the research questions arise from discussions at staff meetings, but nurses and the unit coordinator remained committed to inviting and facilitating participation, and provided me with friendship and encouragement. I wish to thank Dr. Joy Johnson, Thesis Chair, for her sustained interest in this project, for guiding my learning, and sharing her passion for good research. Dr. Johnson's willingness to share her time and expertise, her commitment to teaching me how to conduct research, while promoting the autonomy of independent thinking created a truly exceptional learning environment. I am also very appreciative of the collaboration and support of the other members of my thesis committee, Dr. Pam Ratner and Martha Mackay, whose committed efforts and support greatly enhanced the quality of my work and my research capacity. My thanks go to Shahadut Hossain for providing statistical consultation on this project. I am thankful for the support given to me by the Heart and Stroke Foundation of Canada Nursing Research Fellowship Award, and the Cardiovascular Nurse Scientist Facilitating Unique Training Using Research and Education (FUTURE) program. As a recipient of the University Of British Columbia School Of Nursing Helen Shore Nursing  Endowment Fund, I am deeply appreciative of the personal interest that Ms. Shore took in this research project and the support provided to complete this study. This project was also supported by Registered Nurses Foundation of BC Sisters of Charity of the Immaculate Conception Award and by the St. Paul's Hospital Foundation Kihlman Nursing Award.  DEDICATION  To Rob, my partner for life  1  CHAPTER 1 Introduction Percutaneous Coronary Intervention Coronary artery disease (CAD) is Canadians' leading cause of mortality and admission to hospital. Over one third of all deaths of Canadian men and women are attributable to CAD, representing a greater disease burden and economic impact than any other disease (Heart & Stroke Foundation of Canada, 2003). In addition to cardiac risk factor modification, which is mostly behavioural and pharmacological in nature, treatment modalities for CAD include pharmaco-therapeutics, coronary artery bypass graft (CABG) surgery, and non-surgical percutaneous coronary intervention (PCI), which encompass balloon angioplasty and coronary stent implantation. The advancement of PCI technology and operator technique, and constant pressure on the health-care system to optimize the utilization of resources, have promoted PCI as a viable alternative to costly open heart surgery (Leeper, 2004; Scroggins, Houston, Clark, & Cushman, 2001). In the 30-year interval since the first coronary artery balloon inflation, PCI has emerged as a safe, economic and less invasive alternative to open heart surgery, and has changed the face and the delivery of cardiac care (Banning et al., 2003). It offers patients a reasonable option to relieve cardiac symptoms, while minimizing procedural risks and facilitating a swift return to normal activities (Higgins, Dunn, & Theobald, 2000). The number of PCIs has surpassed open heart surgeries in the treatment of coronary blockages, and is now performed 1.6 times more often than CABG surgery in Canada (Heart & Stroke Foundation, 2003). The number of PCIs performed in Canada has grown by 36% between1994/95 and 2000/01 (Heart & Stroke Foundation, 2003). Likewise, in the United  States, PCI has seen an annual rate increase of 32.6% in the past 10 years compared to an average increase in CABG surgery of 2.9% per year (Sistino, 2003). Today, PCI is the most common major medical intervention performed in Canadian hospitals (Arjomand, Zoltan, McCormick, & Goldberg, 2003). In spite of increasing clinical and anatomic complexity of presenting conditions, major improvements have been reached in the safety of PCI procedures (Resnic, 2007). Length of Hospital Stay When the practice of angioplasty first developed, patients admitted on a non-urgent, elective basis were routinely hospitalized for about three days, usually under the monitoring surveillance provided in coronary or intensive care units (Arjomand et al., 2003). Today, most elective patients undergoing PCI experience accelerated arterial sheath removal within 3 to 4 hours following intra-procedural anti-coagulation (Leeper, 2004), and are discharged within 24 hours of admission (Grines et al., 1998; Wong, Wu, Chan, & Yu, 2006). St. Paul's Hospital (SPH), in Vancouver British Columbia, a major cardiac referral centre, is one of the few Canadian centres to practice "same-day discharge" for elective patients undergoing PCI via the femoral artery approach, for both planned and "ad-hoc" cases, where the decision to proceed to PCI is made immediately following diagnostic coronary angiography. This practice is based on the findings of research conducted by investigators at that centre, which demonstrated the safety and cost benefits of same day discharge, and supported same-day discharge as a feasible option in "carefully selected patients" (Khatri et al., 2002, p. 427). In the study sample, most participants were male (82%), with an average age of 63 years, a low incidence of heart failure (5%) and other co-morbidities [cerebrovascular accident (7%), diabetes mellitus (21%), mean creatinine (103 mg/L)], and who had undergone single vessel  PCI (79%). In a study of PCIs performed using the radial approach for vascular access, Ziakas et al. (2003) also concluded that same-day discharge was a safe practice. More recently, a Dutch study of 800 elective outpatients and planned PCI cases assigned patients to routine overnight hospitalization or same-day discharge in a blinded, randomized study (Heyde et al., 2007). The study exclusion criteria included ad-hoc PCI, elective use of intravenous anti-platelet agents (Glycoprotein Ilbllla inhibitors), and having a residence more than 60 minutes away from the PCI centre. These criteria excluded 20% of the patients from the study. The researchers concluded that there were no significant differences in the incidence of major adverse cardiac events, vascular complications and indication for extended observation between the study groups. Additionally, patients discharged the day of their procedure reported significantly higher rates of overall satisfaction and lower costs associated with the procedure were incurred. These findings merited editorial attention from the journal editor; Resnic (2007) outlined the merits of this innovative study and called for a duplication of findings in the American healthcare setting. Changes in the Patient Population The number of PCI procedures conducted continues to climb as the population ages, as CAD affects an increasing number of people, and as procedural technology advances (Deaton & Namasivayam, 2004; Leeper, 20034). With the use of multiple stenting, drugeluting stents, and other interventional devices, the population eligible for PCI is expanding to include patients with multivessel disease, left main coronary artery disease, chronic total occlusions, and occluded bypass grafts, who previously might have been treated medically or have been referred to cardiac surgery (Dzavik, 2003; Heyde et al., 2007). In addition to these procedural changes, the rise in prevalence of co-morbidities, including heart failure, diabetes,  4 renal failure, and cerebrovascular disease (Wu, Goss, Maynard, Stewart, & Zhao, 2004), and the increasing awareness of the incidence of depression and anxiety among cardiac patients (Artinian, 2003) may be unaccounted for in the provision of PCI care. Purpose of the Study This research aimed to study whether patient and procedural characteristics, in the setting of elective same-day discharge PCI, are associated with patient outcomes related to cardiac self-efficacy and self-care agency, following returning home in the 2 to 5 days postdischarge period. The study addressed a gap in current knowledge created by recent changes in PCI practice and the increasing complexity of patients eligible for PCI management of CAD, as well as the relationship and differences between what medical advances can offer and the experiences and perceptions of patients. Significance of the Study By determining whether interventional cardiology patient and procedural factors are associated with outcomes such as compliance with discharge instructions, confidence in the capacity to care for oneself, and knowledge of symptom maintenance and management, the provision of quality care may be guided. Little is known about the relationship between patient characteristics, severity of disease, and procedural complexity on patient outcomes, particularly when patients are discharged from hospital on the day of their procedure. The potential exists for a gap between what the system can deliver and the self-care capacity of patients and their families. The provision of interventional cardiology care is evolving rapidly, offering patients non-surgical options for the management of complex CAD, valvular heart disease, and congenital heart defects. Although the scope of this study was limited to PCI, the landscape  of cardiac care includes the prospect of an increasing number of cardiac surgeries being performed percutaneously. This study was designed to provide a better understanding of the relationship between patients' experiences following same-day discharge PCI, and patients' characteristics, severity of disease, and complexity of the procedures that they undergo. Scope of the Study This study focused on stable patients with a history suggestive of coronary artery disease, referred for elective planned or ad-hoc percutaneous coronary intervention with femoral artery vascular access, admitted and discharged on the same day as the procedure.  6 CHAPTER 2: LITERATURE REVIEW This review of the published literature relates to patient outcomes following percutaneous coronary intervention and is limited to scholarly works published between the years 1995 and 2007. The literature review has two main objectives: (1) to focus on factors that affect patients' experiences and recovery following PCI and (2) to assess the existing knowledge related to patients' outcomes after angioplasty, including self-care following discharge. The literature search was conducted using the Cumulative Index of Nursing and Allied Health Literature (CINAHL), the standard medical literature analysis and retrieval system online (MEDLINE) and PUBMED databases, as well as Google Scholar. The following key words were used, in combination, to perform a search of the literature: percutaneous coronary intervention, coronary angioplasty, coronary angiogram, patient outcomes, discharge, learning needs, self-efficacy, self-care, patient satisfaction, and cardiovascular risk factors. Background The study of patient outcomes following PCI requires a rudimentary grasp of the disease process and its associated risk factors, treatment options, patient characteristics, and procedural details to understand the clinical context. This background sets the stage for the identification and study of factors that may influence the post-PCI recovery phase. Coronary Artery Disease and Associated Risk Factors CAD involves the progressive accumulation of fatty substances in the inner lining of the vessels responsible for the supply of oxygenated blood to the heart muscle, the valvular structures, and the cardiac conduction system (Woods, Sivarajan Froehlicher, & Motzer,  7 2005) . As the inner lumen narrows, coronary blood flow is reduced, metabolic oxygen demands are unmet, and individuals may experience symptoms of myocardial ischemia, which include and other anginal pain, shortness of breath, and fatigue (Granger & Miller, 2001). Despite major progress achieved in the prevention, detection and treatment of coronary artery disease, cardiovascular diseases remain the leading cause of death worldwide (Braunwald, 1997; Heart & Stroke Foundation of Canada, 2003). In 2005, symptomatic cardiovascular disease was the primary admitting diagnosis to Canadian acute care facilities, totalling 411,000 hospitalizations, as well as the specific cause of death of 34% of Canadian women and 32% of Canadian men (Canadian Institute of Health Research, 2006). Although nearly one half of patients with cardiovascular disease do not have any established risk factors (Braunwald, 1997), known causes associated with this process are multi-factorial and can be categorized as either non-modifiable or modifiable. Nonmodifiable risk factors include age (>45 years for men, >55 years or being post-menopausal for women), family history of cardiovascular disease in a first degree relative, and personal history of cardiovascular disease. Modifiable cardiovascular risk factors include smoking, dyslipidemia, diabetes, hypertension, obesity, and sedentary lifestyles (Furberg et al., 1996). More recent research has highlighted the prognostic importance of depression in patients with CAD, and researchers have argued for its inclusion as a separate risk factor (Frasure-Smith & Lesperance, 2003). This recommendation is echoed in works focused on acute coronary syndrome (Dunn, Corser, Stommel, & Holmes-Rovner, 2006), PCI (Astin, Jones, & Thompson, 2006), cardiac medication adherence (Bane, Hughes, & McElnay, 2006) , and heart failure (Artinian, 2003).  8 Treatment Options for Symptomatic Coronary Artery Disease Coronary artery bypass graft surgery and percutaneous coronary intervention are two options available for myocardial revascularization in the setting of stable angina (Grech, 2003). PCI is a non-surgical procedure that involves the cannulation of a major access artery, such as the femoral or radial artery, using a vascular access device or sheath. During the angioplasty, a small balloon is inflated within the narrowed atherosclerotic section of the coronary artery, pushing back the plaque and creating a widened lumen to optimize blood flow. To avoid elastic recoil of the artery after vessel expansion, a small permanent wire mesh - a coronary stent - is implanted to maintain the vessel's patency (Arjomand et al. 2003). The arterial access sheath is removed following the procedure, and the patient is discharged when hemostasis, the clotting and closure of the puncture site, is achieved. The first human angioplasty was performed in 1977, followed by the introduction of stent implantation in 1986 (Arjomand et al., 2003). PCI patient volumes surpassed bypass surgeries in 1990 (Scroggins et al, 2001). Today, 35,000 PCIs are performed yearly in Canada (CIHR, 2006). In the United States and the United Kingdom, there has been a fivefold increase in the number of PCIs every decade since the introduction of the practice (Wong et al., 2006). The cost-effectiveness and comparative outcomes of coronary artery bypass graft surgery versus PCI for revascularization continues to be studied in the stable elective patient population as well as in higher risk patients (Lipinski, Fearon, Froelicher, & Vetrovec, 2004; Radford, 2006; Weintraub et al., 2007). The results of the Angina With Extremely Serious Mortality Evaluation (AWESOME) study which randomized high risk patients to PCI or CABG, showed no difference in mortality between the two groups but found higher rates of  unstable angina and repeat revascularization procedures in the PCI arm (Stroupe et al, 2006). The recently published results of the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluations (COURAGE) trial, where patients with stable CAD were randomized to optimal medical therapy with or without PCI, demonstrated that elective PCI failed to reduce the rate of death, myocardial infarction and hospitalization for acute coronary syndromes in 2,287 patients between 1999 and 2004 (Boden et al., 2007). These findings may potentially affect how patients with stable CAD are managed in the future. PCI: Patients and Procedures Several factors related to both the patient population and the medical procedures have contributed to recent changes in the delivery of PCI. Individuals referred for PCI are increasingly presenting with additional co-morbidities that affect their procedural risk and recovery. Diabetes, renal dysfunction, heart failure, and obstructive lung disease, in addition to coronary artery disease, are often present in these patients and contribute to the incidence of complications and difficulties during the recovery phase (Qureshi et al., 2003). PCI procedures have increased in complexity and risk as advances in operator technique and interventional cardiology technology have enabled cardiologists to manage percutaneously coronary artery disease that had previously required surgical intervention. This shift in practice has served to maintain or reduce costs and resource utilization (Arjomand et al., 2003; Legrand et al., 2004). Technological progress such as smaller balloons, drug-eluting stents, distal protection devices, rotational atherectomy, and intravascular ultrasound, as well as pharmaceutical advances in the concomitant administration of anti-platelet agents, have resulted in practices that routinely include multi-  10 vessel and higher risk proximal disease, surgical graft lesions, and chronic total occlusions (Dzavik, 2003; Grech, 2003; Resnic, 2007). Preparation for Discharge Length of Stay Outpatient coronary angioplasty with early ambulation and discharge is accepted as a feasible and safe practice to meet the growing demands for access to PCI care and the challenges of resource utilization (Slagboom, Kiemeneij, Laarman, & van der Wieken, 2005). There is no consensus in the literature about the optimal duration of hospitalization before and following PCI. Although many studies of patients' outcomes following PCI failed to report the duration of hospitalization (Gulanick, Bliley, Perino, & Keough, 1998; Higgins et al., 2000; Jaber et al., 2005; Nones Cronin, Holbrook Freeman, Ryan, & Drake, 2000; Qureshi et al., 2003), other researchers have reported an average length of stay (LOS) of overnight to two days with recovery in a cardiac monitoring clinical area (Gentz, 2000; Leeper, 2004; Wong et al., 2006; Wu, Goss, Maynard, Stewart, & Zhao, 2004). Some centres' standards of care include transfer to a cardiac telemetry unit, with a reported average LOS of 3.7 days (Sullivan, Howland-Grandman, Schell, & Goldsmith, 1997). Some research findings support same-day discharge following PCI for patients with stable coronary artery disease, simple or uncomplicated medical presentation, and predictable outcomes (Banning et al., 2003; Dalby et al., 2003; Grines et al., 1998; Khatri et al., 2002; Slagboom et al., 2005; Heyde et al, 2007). The American College of Cardiology/American Heart Association Task Force on Practice Guidelines for PCI (Smith et al., 2005) did not offer specific recommendations related to length of stay.  11  Although the study of the relationship between length of stay and PCI patient outcomes is limited, there is extensive literature to support reducing hospitalization as a means of curtailing the cost of treatment (Riegel et al., 1996). Cardiac care has been a major target of this trend in patient care and public policy because of extensive waiting lists and high costs, as well as medical advances facilitating changes in patient care. The need to fully utilize hospital beds, to meet the demands of increasing numbers of patients on waiting lists and to balance the rising costs of research and development for cardiac devices, has created a powerful force driving cardiac care (Higgins et al., 2000). In addition to reflecting the health-care resources consumed (Philbin, Rogers, Sheesley, & Lunch, 1997), length of stay is a surrogate measure of contact time between patients and health-care professionals, especially nurses (Edwardson, 1999). Traditionally, hospitalization has provided the opportunity for nurses to administer care and emotional support, initiate education, identify vehicles and obstacles to health promotion, and prepare patients and their families for discharge (Banning et al., 2003). For individuals undergoing invasive cardiac procedures, the hours in hospital may be a unique opportunity for nurses and patients to address potential complications of the procedure, identify cardiac risk factor modification objectives and strategies, set up a continuum of care in the community to address the chronic nature of heart disease, and identify patients' stressors and support (Gulanick et al., 1997). In summary, PCI technology and operator technique have progressed in the past decade such that procedures have become less invasive and capacity to provide the service has increased (Grech, 2003). Concurrently, the burden of heart disease and demand for PCI has increased (Heart & Stroke Foundation of Canada, 2003). Shortened LOS is driven by  12 medical advances and increased capacity and demand to provide PCI services (Banning et al., 2003; Grines et al, 1998; Khatri et al., 2002; Resnic, 2007), rather than by evidence describing patients' needs and outcomes. Evidence related to the outcomes of patients with various lengths of stay is lacking in the published literature. Learning Needs In a comprehensive review of 19 studies of patients undergoing PCI, Gentz (2000) identified 7 studies that provided information about patients' perceived learning needs. They reported two priority content areas requested by patients: (1) information related to the procedure and coronary artery disease and (2) "survival" management. Informational needs focused on "understanding the outcome of the procedure, anatomy and physiology, risk factor management and lifestyle changes, and medications" (p. 163). Skaggs and Yates (1999), whose work was not included in Gentz's (2000) study, echo this finding, stating that two priority learning needs for patients include: (1) knowing the results of the angioplasty, and (2) learning how to change the course of their heart disease. In a study comparing learning priorities of patients and their nurses, Brezynskie, Pehdon, Lindsay and Ada (1998) found that patients gave higher priority to knowing the outcome of their PCI, understanding what lifestyle changes may prevent worsening of heart disease, and what to do with problems related to medications, than nurses did. PCI nurses placed higher concern on understanding the causes that led to the need for PCI, when to take anti-anginal medications, and what to report to healthcare providers following PCI. The second learning priority, survival management, focused on learning how to manage cardiac symptoms, should individuals experience further cardiac problems upon returning home (Czar & Engler, 1997; Gentz, 2000; Skaggs & Yates, 1999;). This included  13 whether to expect symptoms of angina following PCI, how to respond, and implications for long term survival. Tooth, McKenna, Maas and McEniery (1997) reported preliminary findings about the effects of pre-coronary angioplasty and counselling on patients and their spouses in a group of 80 patients and their spouses, randomized to usual care or a pre-procedure intervention. They found that patients who received pre-PCI support reported improved knowledge and reduced anxiety 4 months following the procedure. In addition, their spouses experienced better quality of life at 11 months compared with the control group. Given the limited time available during PCI hospitalization, pre-procedure education may offer a feasible option to improve patients' outcomes. Looking to the cardiac surgery and myocardial infarction literature, education has been shown to significantly decrease cardiac mortality, improve psychoemotional status, improve knowledge, and reduce risk behaviour (Cupples, 1991). In a European publication, Kattainen, Merilanen, and Jokela (2004) stated that most studies of learning needs of cardiac patients focus almost exclusively on the period of hospitalization, concentrating on discharge information. Based on the findings of studies of early recovery of cardiac surgery patients that demonstrated that learning needs extend beyond the time of discharge, the authors identified a significant gap in research pertaining to the informational needs of PCI patients in the period immediately following their return home and long-term follow-up. Although not necessarily applicable to the PCI patient population, long-term learning needs of cardiac patients have been identified as focussing on treatments and complications, on-going symptom management, activities, enhancing quality of life, and medications (Jaarsma, Kastermans, Dassen, & Philipsen, 1995). Studies of cardiac surgery patients reveal  14 that information needs related to anxiety, depression, anger, and mood changes emerge in the first month of recovery, in addition to learning to cope with fatigue, sleep disturbances, changes in appetite, discomfort in incisional areas, and shortness of breath (Moore, 1996). Further research is needed to study the learning requirements of PCI patients, both in the period immediately following the return home, and the longer term recovery phase. Apart from identifying learning needs, limited attention has been paid to identifying the needs of specific patient population groups. Although there is a lack of evidence in the PCI literature, other studies of cardiac care have identified variations in learning needs among women, elderly people, patients with lower levels of formal education, and younger men, as well as spouses and support persons (Kattainen et al., 2004). As the patient population expands to include more of these patient groups, there is a pressing need to better understand PCI learning needs by addressing possible similarities and disparities among an increasingly varied population. In addition, researchers have not routinely included the family or spouses of PCI patients although they assume a significant role in the support and care of individuals preparing for and recovering from PCI (Tooth et al., 1997). Kattainen et al. (2004) designed and validated the Nursing Information and Support (NIS) scale for cardiac surgery and PCI patients, a four-dimensional instrument including physical, psychosocial, emotional support, and disease specific categories. The NIS scale is aimed at assessing the importance and adequacy of information for both groups of patients. Although grounded in theory and clinical practice, this tool is awkward in its translation from the original Finnish version, and lacks specificity to PCI. Earlier, Bubela et al. (1990) developed the Patient Learning Needs Scale (PLNS) to measure patients' perceptions of their learning needs at the time of hospital discharge. It consists of a self-administered  15 questionnaire, given before discharge from the acute care setting, focusing on behavioural, cognitive, and decisional categories of needs. It outlines a structure of seven learning factors that were found to be of high importance to patients: medications, activities of living, community and follow-up, feelings related to their condition, treatment and complications, enhancing quality of life, and skin care. Each category details specific learning needs. The scale was tested for reliability and validity in oncologic and surgical clinical areas only, and was found to be an effective tool (Bubela et al., 1990; Galloway, Bubela, McKibbon, Rebeyka, & Saxe-Braithwaite, 1995; Galloway & Gray don, 1996). Again, the lack of specificity for PCI patients would require some adaptation and validation of the items to make it a useful tool to measure patients' learning needs in this clinical context. Patient Satisfaction Patient satisfaction has been studied and measured in the context of hospital management, clinical research, and health care services research in spite of the absence of concept development, standardized definitions and measurement (Mark & Wan, 2005; Staniszewska & Ahmed, 1999). Donabedian (1988) argued that two key aspects of nursing care - technical performance and interpersonal care - were important elements in patient satisfaction. The American Nurses' Association define patient satisfaction as "a measure of a patient's or a family's opinion of care received from nursing staff (Yellen, Davis, & Ricard, 2002, p. 24). The lack of standardized and psychometrically tested instruments, difficulties inherent in comparisons across clinical settings, and absence of agreement on the meaning of results are examples of obstacles to accurately assess patient satisfaction (Yellen et al., 2002).  16 Specific measurement of patient satisfaction following discharge from PCI is lacking in the literature. Mark and Wan (2005) conducted a study to examine five sources of measurement equivalence in patient satisfaction among 1,897 participants. They found that in decreasing order, quality of nursing care, staff teamwork, staff care and concern, discharge instructions, adequacy of technology and equipment, and pain management were significant predictors of patient satisfaction. Their Patient Satisfaction Questionnaire outlines 10 questions related to the identified variables, asking participants to rate their responses on a Likert-type scale of 1 to 6, with higher scores reflecting higher satisfaction (Mark & Wan, 2005). A study of patient satisfaction measurement in the American "disease management industry" found that there are "positive associations between patient satisfaction and clinical outcomes" (Sen et al., 2005, p. 288), and that the assessment of patient satisfaction combines the assessment of hospital structures, care processes, and patient outcomes. Sen et al. (2005) recommended the use of another version of the Patient Satisfaction Questionnaire developed by Ware et al. (1983), which explores key predictors, such as access to care, availability of services, technical quality of care, interpersonal care, communication, and financing of care. The Patient Satisfaction Scale (PSS) was specifically developed to measure patient satisfaction with nursing care. It was conceptualized to have three dimensions: technicalprofessional factors, trusting relationships, and education (Risser, 1977). The instrument was validated in the hospital setting in 1982 by Hinshaw and Atwood (1982) and re-named the Patient Satisfaction Instrument (PSI). Both versions are used extensively by nursing researchers (Yellen et al., 2002).  17 Gulanick et al. (1997) published the findings of a qualitative study examining the experience of 26 men and 19 women following angioplasty. Emerging positive themes included contentment with comfort measures, satisfaction with supportive in-hospital care, and trust in medical competence. Negative and often contradictory themes centred on anger over unmet needs for comfort or support, feeling dehumanized, and frustration over lack of control in decision making. More recently, another qualitative study examined 14 patients' experiences during and after PCI and coronary angiography (Lunden, Bengston, & Lundgren, 2006). Emotions, bodily sensations, nursing interventions of importance, and personal strategies were identified as the main categories related to the experience of undergoing the procedure. The authors concluded that the advances made in PCI technology and practice do not seem to have affected the experience of patients since the publication of Gulanick et al.'s study: patients continue to experience severe back pain and discomfort during vascular sheath removal, articulate the importance of nursing-patient contact time, and are stressed by the uncertainty of their procedure and outcome. Post-PCI Outcomes Predictors of Outcomes Models to predict in-hospital PCI mortality have been well-established through large sample studies and registries. Risk scores have been developed to predict in-hospital and 30day mortality (Qureschi et al., 2003; Wu et al., 2006; Wu et al., 2004), as well as quality of life benefit following PCI (Spertus, Salisbury, Conoway, & Thompson, 2004). In their study of hospitalized PCI patients, Wu et al. (2004) found that, consistent with previous medical research, co-morbidities, including older age, renal insufficiency, peripheral vascular disease,  18 left ventricular dysfunction, and chronic obstructive pulmonary disease, predict 30-day mortality. Qureshi et al. (2003) developed a simplified scoring system to predict mortality for hospitalized PCI patients based on pre-procedural clinical features. The instrument allocates a weighted score to the four major predictors of co-morbidities: (1) recent myocardial infarction, (2) renal dysfunction (increased serum creatinine level), (3) multivessel disease, and (4) age greater than 65 years. The instrument recently developed and validated by Wu et al. (2006) to predict in-hospital mortality for PCI allocates higher predictive scoring to: (1) older age, (2) female gender, (3) low left ventricular ejection fraction, (4) pre-procedural MI, (5) peripheral arterial disease, (6) congestive heart failure, (7) renal failure, and (8) left main coronary artery disease. Siotia and Gunn (2006) summarized the most important prognostic factors pertinent to the elective population as advanced age over 75 years, with low ejection fraction, the presence of congestive cardiac failure, and renal failure having a lesser impact. No studies were identified that focused exclusively on predicting outcomes of patients undergoing non-urgent elective PCI. In a prospective study of 1,518 non-acute patients, Spertus et al. (2004) identified characteristics associated with improved quality of life (QOL) following PCI. They found that pre-procedural angina frequency is the primary prognostic indicator of 1-year QOL. The authors argue that the inclusion of thesefindingscould alter the evaluation of the appropriateness of elective PCI, since only 23% of American PCI patients are asymptomatic (Spertus et al., 2004). The nursing literature offers a unique perspective on understanding patient outcomes following PCI. In a comprehensive critical summary of nursing-sensitive outcomes, Leeper  (2004) examined the indicators related to costs of care and length of stay, morbidity, symptom management, patient and family knowledge, patient responses, behaviour, and functional status following PCI. She credited advances in nursing practice with the dramatic changes to PCI delivery of care in the past decade through quality improvement projects and research. Morbidity has been positively affected by the development of sheath removal protocols, the use by nurses of mechanical compression devices, and the nursing and medical management of minor and major vascular complications. Information related to groin discomfort, energy level, ability to resume normal activities, psychological functioning, and lifestyle pattern has contributed to improving standards of practice. Leeper recommended that further research is required to study nursing outcomes of specific patient groups, including elective patients. Fitzgerald, Zlotnick and Kolodner (1996) studied the impact of pre-PCI functional status, age, gender, educational status, prior myocardial infarction, number of PCI target lesions, and incidence of pre-procedural angina on 135 patients, examining outcomes one year following discharge, using a self-reporting questionnaire. The instrument used was the Functional Status Questionnaire (FSQ), validated by Jette et al. (1986). The FSQ assesses activities of daily living, social interaction, work performance, quality of interaction, and mental health of general populations. Although many patients reported benefits and improvements in many aspects of their lives, Fitzgerald et al. also found that patients continued to experience difficulties in mental health (25%), work performance (17%), quality of interaction (10%), and activities of daily living (14%). The researchers identified the patients' baseline scores on their functional status as the variable most predictive of their outcomes. They referred to an unpublished 1993 doctoral thesis by McKenna who studied  20 205 patients and identified pre-PCI life satisfaction and psychological well-being as the main predictors of post-PCI life satisfaction and psychological well-being. In an Australian study of 130 patients following PCI, Tooth, McKenna, Maas, and McEniery (1997) studied the responses to a self-administered questionnaire about functional status, cardiac symptoms and psychological status. The authors found longer duration of CAD, presence of on-going chest pain, persistent shortness of breath, and not working were associated with poorer psychological outcomes and reduced functional status. This study suggests that both pre- and post-PCI factors may predict patients' outcomes. Patient Characteristics In contrast with the decline of mortality due to CAD among men in the past decade, the number of women affected by heart disease continues to rise. In North America and Europe, heart disease remains the leading cause of death and disability for both genders (American Heart Association, 2006; Heart & Stroke Foundation of Canada, 2003). Due to the absence or under-representation of women's experience of heart disease in clinical studies, relatively little is known about the effect of gender on patients' outcomes (Plach & Stevens, 2001). Although there are no existing nursing studies comparing gender outcomes specifically following PCI, other studies of gender differences of cardiac patients suggest that women with heart disease are more vulnerable than men in the recovery phase. Artinian and Duggan (1995) and King, Porter, and Rowe (1994) found that following cardiac surgery, women reported more difficulty ambulating, had poorer subjective perceptions of their physical health, as well as more anxiety and depression. Others have reported more difficulty with household activities as well as a higher prevalence of feelings of guilt, anxiety, and depression (Plach & Stevens, 2001). Gallagher, McKinley, and Dracup (2003) studied 196  women following discharge from an acute cardiac event and found that age of less than 55 years, unemployment or retirement, poor adjustment and readmission were predictors of poorer outcomes. The study of women's health behaviour and treatment suggests that gender affects outcomes. Hawthorne (1994) and LaCharity (1997) suggest that gender bias interferes with early recognition and management of CAD in women. There is also evidence that women are more likely to minimize the significance of their symptoms, and delay seeking medical attention (Dempsey, Dracup, & Moser, 1995). In a large prospective study of over 12,000 American patients who underwent PCI, Wu et al. (2004) found that women tended to be older and to have more co-morbidities. Even when these variables are controlled in statistical analyses, women require a longer length of stay and have a higher post-procedure mortality rate. These findings are echoed by Watanabe, Maynard, and Ritchie (2001) who found that women had a higher incidence of same-admission mortality and complications, confirming female gender as an independent predictor of mortality following PCI. In a study of 177 patients under the age of 40 years with premature CAD, Lansky et al. (2004) found that premenopausal women had a higher incidence of diabetes and hypercholesterolemia than did men of the same age, and are at higher risk of developing vascular and ischemic complications after PCI, independent of their risk factors and smaller body stature. Female gender is also associated with higher risk of adverse clinical events in patients undergoing PCI for more unstable CAD in the setting of non-ST elevation acute coronary syndromes (Glaser et al., 2006). Lacking from this debate is a better understanding of the impact of gender on the recovery from PCI, particularly in the context of nursing-sensitive outcomes.  Revascularization by either PCI or CABG surgery is an effective intervention to relieve symptoms of ischemia and improve quality of life in individuals over the age of 70 years (Ramanathan et al., 2005; Rossi et al., 2006). Risk factors and co-morbidities are often compounded as people age, raising the rate of complications associated with cardiac interventions (Ramanathan et al.). Advanced age and female gender, both independent predictors of early and late mortality and adverse cardiac events in the setting of PCI, are associated with further poor outcomes one year and longer following revascularization (Rathmore et al., 2006). Overall, the rate of repeat revascularization (excluding early events) following PCI in the elderly was reported at 14%, which compared to a rate of 17% in the general population (Clark, Bakhai, Lacey, Pelletier, & Cohen, 2004). Improvements in functional status and quality of life in a study of nearly 1,800 patients in several American centres were comparable for patients under and over the age of 70 years, leading researchers to conclude that elderly patients benefited substantially from percutaneous revascularization (Seto et al., 2000). This literature search failed to identify any evidence to guide the care of the many Canadian patients who travel from remote areas of the provinces and territories to access PCI care in the large urban centres, and are discharged following their procedure to return home where access to specialized medical care may be limited. Although the importance of social support is documented in the general cardiac literature (Deaton & Namasivayan, 2004), there is no existing study of the relationship between patients' marital status and social support system and their outcomes following PCI. Fitzgerald et al. (1996) stressed the importance of considering patients' social, functional,  23 and psychological status before PCI to predict outcomes and to tailor post-procedure interventions. In an observational study of 1,346 patients undergoing PCI, socio-economic status (SES) was not associated with differences in major adverse cardiac events, such as death, MI, or revascularization. Individuals with lower SES experienced a higher rate of rehospitalization for non-procedure related events and reported lower health-related quality of life at baseline and 12 months compared with people with higher SES (Denvir, Lee, Rysdale, Walker, Eteiba et al., 2006). There is a salient need for nursing researchers to examine the potential relationships, with impact on and implications of social support/isolation, geographic location, and access to care, and socio-economic status on PCI patients' outcomes. Disease Severity and Co-Morbidities To understand the effect of patients' medical condition on their outcome following PCI, it is important to consider the indications for PCI, the degree of heart disease of interventional cardiology patients, and the significance of comfounding co-morbidities. Symptoms of coronary ischemia experienced by patients most frequently include angina or chest pain, referred pain to other areas of the body, and shortness of breath (Woods et al., 2005). A widely accepted stratification of severity of ischemic symptoms is the Canadian Cardiovascular Society functional classification for angina (CCS), which grades patients into four classes of severity, ranging from I (angina during strenuous exertion) to IV (inability to carry out any physical activity without discomfort) (Grech, 2003). CCS classification has been used in large randomized trials of CABG patients to measure quality of life following surgery and has been found to be sensitive to improvements in physical  functioning (Higgins, Hayes, & McKenna, 2001). Medical studies frequently use the CCS classification to quantify patients' severity of CAD in the study of PCI outcome predictors (Cox & Naylor, 1992; Jaber et al., 2005). Higher CCS classes signify unstable disease and are predictive of poorer outcome in hospitalized PCI patients (Wu et al., 2004). CAD can be further quantified by the number and location of diseased coronary arteries found on angiographic examination and target lesions revascularized during PCI. Left main and multivessel disease increases the risk of complications and is an independent predictor of outcome following PCI (Qureshi et al., 2003). PCI of calcified chronic total occlusions (Dzavik, 2003) and single-remaining vessel (Tavano et al., 2007) may offer significant relief of anginal symptoms but also presents higher risks of complications. The benefits of PCI in multivessel coronary artery disease compared with medical therapy continue to be questioned (Hueb et al., 2007). The presence of heart failure and multi-system co-morbidities further compounds the potential negative outcomes of patients following PCI (Herrman, 2004; Wu et al., 2004). Studies of outcome predictors include heart failure, renal dysfunction, diabetes, peripheral vascular disease, chronic obstructive pulmonary disease, hypertension, dyslipidemia, and a history of cerebrovascular accidents (Qureshi et al., 2003; Spertus et al., 2004; Wu et al., 2004; Wu et al., 2006). The severity of heart failure can be estimated by measuring left ventricular ejection fraction (EF) and classifying patients' symptoms according to the New York Heart Association (NYHA) functional classification. Serum creatinine and glomerular filtration rate (GFR) are basic measurements of renal function (Woods et al., 2005). The prevalence of diabetes mellitus (DM) is associated with a higher incidence of multivessel disease and higher plaque burden, and is a predictor of poor outcomes in both  25 PCI and CABG revascularization (West, Ruygrok, Disco, Webster, Lindeboom et al., 2004). Over 50% of diabetics die of coronary artery disease and account for 20% of PCI procedures (Morgan, Kapur & Beatt, 2003). In addition, individuals with DM experience a significantly higher incidence of restenosis and repeat revascularization, in spite of advances in stent technology and concomitant therapies such as the use of platelet inhibitors (Morgan, Kapur & Beatt, 2003; Thanyasiri, Celermajer & Adams, 2005). Following PCI, chronic kidney disease is associated with a higher incidence of inhospital complications, including mortality, neurological events, and gastrointestinal bleeding, especially in individuals with the dual diagnosis of renal disease and DM (Nikolsky et al., 2004). PCI requires the injection of iodinated contrast media, which can result in procedure-related contrast-induced nephropathy (CIN). Congestive heart failure, chronic kidney disease, diabetes, age over 75 years, anemia, and total volume of intra-procedure contrast are predictors of CIN (Mehran et al., 2004). The development of post-PCI CIN is an independent predictor of one-year mortality (Nikolsky et al, 2004). Peripheral arterial disease (Singh et al., 2004) and chronic obstructive pulmonary disease (Slevaraj, Gurm, Gupta, Ellis, & Bhatt, 2005) are associated with poorer procedural outcomes, and are independent predictors of in-hospital death and long term mortality. Extreme body mass index (underweight and class III obesity -BMI > 40) is emerging as a significant co-morbidity in the setting of PCI (Minutello et al., 2004). The American National Institute of Mental Health has identified the co-occurrence of depression and CAD as a key research priority, citing the growing body of evidence that has identified depression as an additional co-morbidity in the setting of heart disease (Dunn et al., 2006). Symptoms of depression are predictive of increased morbidity and mortality after  26 hospitalization for coronary heart disease (Frasure-Smith, Lesperance & Talajic, 1993; Travella, Forrester, Schultz, & Robinson, 1994), and are associated with a 3- to 4-fold increase in negative outcomes following myocardial infarction (Frasure-Smith et al, 2000). In a study of 46 first-time PCI patients and 40 patients undergoing a repeat PCI procedure, Lenzen, Gameland, and Immink (2002) found that there was no significant difference in the level of anxiety between the groups, concluding that anxiety about the return of symptoms and future prospects remains significant regardless of individuals' previous experience with PCI. Depression, anxiety and stress are now recognized psychosocial risk factors that are associated with a similar risk of CAD, including restenosis and progression of atherosclerosis, as conventional risk factors (Sullivan, LaCroix, Spertus, Hecht, & Russo, 2003) . Anxiety experienced by patients awaiting coronary angiography has been previously studied (de Jong-Watt & Arthur, 2004), but to date, there is no study of stress and anxiety in the immediate post-discharge period. Procedural Characteristics Platelets inhibitors, including glycoprotein Ilbllla (GPIIbllla) inhibitors as well as other anticoagulants, are being increasingly used before, during, and in the immediate recovery phase following PCI (Leeper, 2004; Wu et al, 2004). They have resulted in a marked decrease in the need for repeat revascularization (Denvir, Lee, Rysdale, Prescott, et al., 2006). The impact of these agents on the incidence of vascular access bleeding has been studied by researchers (Cura, Kapadia, & L'Allier, 2000; Vlasic, 2004). Limited by small sample sizes and wide variability in PCI interventions, these studies revealed that patients who receive anti-platelet therapy are at higher risk for vascular site complications (Leeper, 2004) . In contrast, other researchers have found that the infusion of GPIIbllla actually  27 decreased the incidence of complications related to vascular access removal (Juran, Lang Rouse, O'Brien, DeLuca, & Sigmon, 1999). PCI requires arterial vascular access, usually through the femoral or radial arteries. The transfemoral arterial sheath must be removed following the procedure, and hemostasis can be achieved either by compression of the puncture or by insertion of a vascular closure device. The traditional method of manual compression of the puncture site, using either manual pressure or a compression device, has a complication rate of up to 5% (Hamner, Dubois, & Rice, 2005). The alternative method of using a closure device can involve an implantable collagen plug or a percutaneous suture device. The incidence of vascular access complications has been reported, with great discrepancy, to range between 0.1% and 61%, depending on the definition of complications, who assesses the nature and severity of complications (self-report versus health care professional findings), and the presence of other variables including type of procedure, anticoagulation, closure devices, age, gender, obesity and co-morbidities (Dumont, Keeling, Bourguignon, Sarembock, & Turner, 2006; Konstance et al., 2004; O'Neill, 2006). Vascular complications, include bleeding and hemorrhage, arteriovenous fistula, pseudoaneurysm, limb ischemia and loss of distal pulse, vascular surgery repair, need for blood transfusion, and infection (Hamner et al., 2005; Homes & Hollabaugh, 1997; Leeper, 2004). The use of arterial access closure devices, either suture-based or collagen plugs, significantly shortens the length of bedrest to 2 hours, increases patient comfort, but has not been shown to reduce the risk of access site complications (Wong et al., 2006). Gender has been identified as a predictor of access site complications, with women requiring longer compression time (Leeper, 2004). Although the most common complication following PCI is  28 the development of hematoma, the incidence of major complications associated with vascular access management is consistently reported to be around 2 to 6% (Andersen, Bregendahl, Kaestal, Skriver, & Ravkilde, 2005; Wong et al., 2006). The study of length of bedrest following hemostasis has confirmed the safety of ambulation within three to four hours (Tagney & Lackie, 2005; Vlasic, 2004), with a higher incidence of bleeding associated with sheath times greater than eight hours (Juran et al., 1999). In a multi-centre descriptive correlational study of 4,010 patients, Juran et al. (1999) conducted the Standards of Angioplasty Nursing Techniques to Diminish Bleeding Around the Groin (SANDBAG) study. The investigators found only minimal differences in bleeding outcomes regardless of the nursing intervention implemented. These included bedrest time, type of wound dressing, frequency of assessment of the vascular access site, and administration of analgesics. Predictors of negative outcomes were prolonged manual sheath removal by nurses, increased time between sheath removal and ambulation, and complaints of nausea, vomiting and back pain following the procedure (Juran et al., 1999). Recovering and Making Changes  Recovery Immediately Following PCI There are no existing studies about patients' readiness for discharge following sameday PCI. Similarly, there is a lack of understanding of patient outcomes in the days following discharge from PCI. We lack information about compliance with discharge instructions, including the filling of prescriptions, especially for anti-platelet agents aimed at preventing in-stent restenosis, laboratory follow-up for patients with impaired renal function, and appointment scheduling for medical follow-up. This gap in research limits our understanding  29 of the potential obstacles to recovery, including when patients return home, their activities during wound healing, and their resumption of activities of daily living. In a limited study of 130 patients, Tooth et al. (1999) found that PCI results in overall improvement of functional and psychological status as well as a reduced rate of symptoms when measured at both 3 and 10 months following discharge. The study did not explore patients' experiences in the early discharge period. In their study of 105 patients, Nones Cronin et al. (2000) questioned participants who had undergone PCI 1, 3, and 6 months earlier. The study focused on the occurrence of chest pain and the actions taken, the patients' concerns and learning needs, and their lifestyle changes. The investigators found a high prevalence of recurring chest pain (42%, n=44), repeated reports of stress, anxiety and depression, a perceived lack of prescription for risk factor modification, and failure to assimilate recommendations that had been made. The researchers suggested that, unlike the more invasive CABG surgery, the relatively simple nature of PCI as a coronary reperfusion intervention may be erroneously perceived by patients as a cure for CAD. By minimizing the physical intrusion of the procedure, the required length of stay, contact time with health care professionals, and relatively rapid recovery, the authors expressed concern that nurses are failing to communicate the chronic nature of CAD and the need for behaviour modification. Few researchers have examined the recovery patterns of PCI patients beyond the traditional medical outcome measures of mortality, morbidity, re-hospitalization and other adverse events (Smith et al., 2001). The most common post-procedures symptoms reported include acute in-stent restenosis, bleeding complications, impaired renal function, and cardiac rhythm disturbances (Smith et al., 2001). Up to 50% of patients reported experiencing chest pain and other symptoms of cardiac ischemia following PCI (Kimble &  30 King, 1998; Nones Cronin et al., 2000; Skaggs & Yates, 1999; Wong et al., 2006). PCI patients also report experiencing puncture site pain, shortness of breath, and back and muscle pain (Kimble & King, 1998). Female patients reported significantly higher levels of fatigue, anxiety, dizziness, and difficulties breathing (Brezinka, Dusseldorp, & Maes, 1998). Pre-procedural angina frequency has been reported as the most important prognostic indicator of quality of life improvement following PCI (Spertus et al., 2004). In a study of 130 participants, predictors of PCI patients' improved functional status were identified as the severity of pre-procedure chest pain and shortness of breath on exertion, duration of CAD, and employment status (Tooth et al., 1997). Female cardiac patients, including PCI, CABG and AMI patients, generally reported lower levels of functioning and exercise tolerance in comparison with men (Brezinka et al., 1998; King et al., 1994). Patients with lower levels of self-confidence experienced increased difficulties in resuming activities of daily living (Gulanick, Kim, & Holm, 1991). In a longitudinal pilot study of the early recovery trajectory of 40 patients at 2, 4, and 6 week following PCI, Barnason, Zimmerman, Brey, Catlin and Nieven (2006) identified fatigue as the most frequent and persistent symptom that significantly affected health status and functioning. They also found that physical and psychosocial functioning improved over time. Psychoemotional adjustment and dysfunction are common themes in the literature exploring recovery following PCI (Leeper, 2004). In a Canadian descriptive correlational study of 22 males following PCI and 25 males after CABG, White and Frasure-Smith (1995) employed the Mishel Uncertainty in Illness Scale (MUIS), the General Health Questionnaire (GHQ) and the Perceived Social Support Scale (PSSS) to compare the impact of social support on uncertainty and psychologic stress symptoms during the first 3 months after  31 coronary angioplasty and CABG. The investigators found: (1) patients who underwent PCI experienced significantly more uncertainty than did cardiac surgery patients, (2) all patients experienced less stress at one month than at three months following PCI, and (3) PCI patients with low perceived social support experienced significantly more stress than similar patients with high support. In a study published three years later, Kimble and King (1998) studied the perceived side effects and benefits of PCI two weeks following discharge in a sample of 62 participants. They concluded that further research was needed to examine the impact of uncertainty on recovery outcomes in spite of finding that over 79% of the patients reported positive benefits from the procedure in the early phase. Odell, Grip, and Hallberg (2006) conducted a grounded theory study of 9 patients who had experienced in-stent restenosis and the exacerbation of ischemic symptoms, and identified "living with uncertainty" as the core category. Uncertainty was experienced in relation to the seriousness of their illness, the threat of angina, not knowing the natural progression of cardiac disease, which was related to lack of knowledge and a perception of responsibility for the occurrence of restenosis. Additional themes included "fighting for access to care", "moderating health threats", "trying to understand", and "controlling relatives' anxiety" (Odell et al., 2006). Gallagher et al. (2003) tested the effects of a telephone-counselling intervention on the psychosocial adjustment of women following a cardiac event. They used a prospective randomized control trial of 196 women hospitalized following a myocardial infarction (15%), CABG (51%), PCI (12%), or stable angina (23%). The telephone counselling intervention, aimed at providing individualized information and support, and promoting self-managed recovery and psychosocial adjustment, had no significant effect. The authors identified age less than 55 years, unemployment and retirement, and poor psychoemotional adjustment  32 scores at baseline as predictors of poorer outcomes. In their comparative study of PCI and CABG patients, Kattainen et al. (2004) found that women undergoing PCI had greater learning needs with respect to their psychosocial functioning than did men post-PCI, and men and women following CABG. They called for further research to investigate patterns of recovery following discharge from PCI. Making Changes: Linking Coronary Artery Disease and Cardiac Risk Factor Modification Research supporting the pivotal role of cardiac risk behaviour modification following PCI is well documented in the literature. Dendale et al. (2004) conducted a retrospective nonrandomized comparative study of 140 Belgian patients who participated in a 3-month program consisting of exercise, psychological and dietary counselling, and smoking cessation support, and then compared with 83 patients who did not receive the program. The incidence of major adverse cardiac events, including death and myocardial infarction, was significantly lower in the rehabilitation group (24%) than in the control group (42%). Yu et al. (2004) had similar findings in a prospective randomized control study of 269 post-PCI or post-AMI Chinese patients who either participated in an eight-week cardiac rehabilitation and prevention program consisting of exercise and classes on risk factor modification, or received usual care. Quality of life measurements revealed that the intervention group scored significantly higher than the control group, with higher quality of life scores sustained at 2 years following the cardiac event. The authors also asserted that the direct health expenses incurred during the study period were significantly lower in the intervention group. Further evidence, consistent with these findings, was published by a Swedish group (Lisspers et al., 2005) who studied the effects of a behaviourally oriented cardiac  33 rehabilitation and secondary prevention program, focused on smoking cessation, diet modification, exercise, and stress reduction for 46 post-PCI patients. When compared with a standard-care control group (n=42), the investigators found that the intervention group was found to have a significantly lower incidence of major adverse cardiac events and cardiovascular mortality at 6.5 years follow-up. The experimental group had significantly higher rates of lifestyle changes at repeated measure over the course of 4 years of follow-up. This outcome was associated with the intense, comprehensive and long term nature of the intervention program, including a 4-week in-patient phase followed by a 11-week structured maintenance phase. Similar findings in the evaluation of an individualized, comprehensive, home-based program, combining exercise, risk factor modification and psychological counselling of a randomized study of 99 post-PCI patients, found that the intervention group experienced significant improvements in serum cholesterol profile, exercise participation, body mass index, and return to work (Higgins et al., 2001). In an innovative approach, Charlson et al. (2002) integrated economic theory with health behaviour intervention to improve patient outcomes following PCI. Their model proposed that framing risk-factor modification within the theoretical underpinning of potential net-present value and reduction of biological age will increase patients' motivation to choose and address specific behaviours and increase the effectiveness of the interventions. Unlike patients recovering from CABG surgery or an acute myocardial infarction, Higgins et al. (2001) suggested that PCI patients may not routinely participate in cardiac rehabilitation programs because of the nature of PCI and its discharge regimen. Wenger (1991) offered three potential explanations to this situation: (1) short duration of PCI hospitalization, (2) improved functional status experienced by patients immediately  following the procedure, and (3) clinicians' belief that improved psychological well-being occurs spontaneously as physical status improves. Fernandez, Griffiths, Juergens, Davidson, and Salamanson (2006) echoed concerns that PCI patients might underestimate their disease severity because of their short hospitalization, rapid procedural technique, clinical improvement without open-heart surgery, and facilitated return to work and to activities of daily living. Following PCI, nearly 50% of patients believed that they had been cured and no longer had heart disease (Campbell & Torrance, 2005; Steptoe et al., 1999). Patients also differ in the causal attributions that they make about their risk factors for CAD. Astin and Jones (2004) studied gender differences in the responses of 140 pre-PCI participants to questions about what they believed caused their coronary heart disease. Women most commonly attributed their disease to stress followed by family history, cholesterol and smoking, whereas men cited poor diet most frequently, followed by smoking, stress and family history. The patients' attributions were significantly discordant with their attending physician's medical history and diagnosis. Failure to address the modifiable risk factors of CAD is associated with disease progression, increased morbidity and mortality, and diminished quality of life (Yusuf et al., 2004). Smoking cessation alone has been reported to decrease the relative risk of a second AMI by 50% within thefirstyear of stopping following AMI, and to eliminate the absolute risk in 15 years compared with lifelong non-smokers (Edwards, 2004). In spite of the wellpublicized benefits of smoking cessation, 20% of patients continue to smoke following a cardiac event (Scholte op Reimer et al., 2006). Similar compelling benefits are attributed to the treatment and reduction of hypertension, hypercholesterolemia, diabetes, physical  35 inactivity, and obesity (Fernandez et al., 2006), and the impact of cardiac rehabilitation programs on improving long-term quality of life (Yu et al., 2004). This body of evidence contrasts with the perception of some nursing and non-nursing researchers of the small contribution of nurses to risk factor management in comparison with the role of physicians (Scholte op Reimer et al., 2002). Many centres have failed to develop a systematic referral system for PCI patients to participate in cardiac rehabilitation and risk factor modification programs (Leeper, 2004). Patients' ability to recognize their personal risk factors for heart disease is a crucial element of behavioural change and requires a tailored approach to counselling (Deaton & Namasivayam, 2004). Questions such as, "Do you plan on attending a cardiac rehabilitation program?" with a planned referral system and information about available resources, can improve patients' outcomes (Deaton & Namasivayam., 2004) and address the poor connection between evidence-based guidelines and clinical practice (Scholte op Reimer et al., 2002). Although behaviour modification is a pivotal element of the management of many chronic disorders, it is a complex and multidimensional phenomenon, with to date, little evidence of successful interventions (Cheng et al., 2007; Steptoe et al., 1999). The process of discharge and recovery from PCI, following both standard and more accelerated discharge, is poorly studied in the research literature. Additionally, there is a gap in understanding whether and how shortened hospitalization affects patients' understanding of their cardiac risk factors and their capacity to modify their health behaviour. Summary  The practice of percutaneous coronary intervention followed by rapid discharge from hospital is well established and promises to evolve rapidly to routine same-day discharge as  36 demand for percutaneous management of CAD continues to grow. Given the increasing complexity of patients and procedures, there is a gap in the available evidence to guide the care of patients and to optimize their outcomes in this changing clinical environment. No studies have examined the immediate transition from hospital to home on the same day to better understand the challenges and opportunities of elective PCI. In the context of PCI patient outcomes, this review of the literature has highlighted aspects of the pre-discharge phase, including patient learning needs and satisfaction with care, predictors of outcomes such as patient and procedural characteristics, and the process of recovery and coronary risk reduction. Short term hospitalization transfers the responsibility for care from health-care professionals to patients. The concept of self-care, the regulatory behaviour that people deliberately initiate and perform to maintain their life, health, continuing personal development, and well-being (Orem, 2001), emerges as an obvious underpinning of any study of patient outcomes following discharge from PCI. Additionally, this literature review underscores the role of individuals' belief in their capability to plan and carry-out self-care instructions and decision-making, and to deal with complications and uncertainty. The link between behaviour, including self-care behaviour, and the capacity to deal with situations as they arise, is the basis of the construct of self-efficacy, described originally by Bandura (1977). In this paradigm, the notion of self-efficacy explains individuals' ability and confidence to select and initiate behaviour that may lead to desired outcomes, and various associated emotional reactions, including uncertainty, stress and depression (Maibach & Murphy, 1995). The constructs of self-care and self-efficacy provided the theoretical framework that guided the development of the methods applied in this study.  37 CHAPTER 3: METHODS Theoretical Background This study incorporated elements of the constructs of self-care (SC) and SC deficit originally elaborated by Orem (1979, 2001) and further developed by Connelly (1987, 1993), and self-efficacy (SE) as theorized by Bandura (1977, 1980, 1995), as the theoretical underpinnings of this exploration of patients' outcomes following same-day discharge PCI. Self-care is an active, deliberate, and cognitive process of self-determined decision making that is widely practiced in primary care as individuals initiate behaviour to care for themselves to promote their health and well-being (Chriss, Sheposh, Carlson, & Riegel, 2004; Jaarsma, Huijer Abu-Saad, Dracup, & Halfens, 2000). The ability of individuals to act as SC agents to take the required action to maintain and manage their health depends on specialized capabilities collectively labelled "self-care agency" (Artinian, Magnan, Sloan, & Lange, 2002; Lukkarinen & Hentinen, 1997). SC agency is defined as a complex and acquired ability to "meet one's constant requirement for care that regulates life processes, maintains or promotes the integrity of human structure, functioning or development, and promotes well-being" (Lukkarinen & Hentinen, 1997, p. 295). Maintenance and management are the two major elements of the process of self-care (Riegel, Carlson, & Glaser, 2000). SC maintenance involves routine monitoring of symptoms and adherence to treatment. SC management refers to the decision-making process involved in the recognition, evaluation, and treatment of arising symptoms, as well as the evaluation of treatment and intervention (Chriss et al., 2004). According to Orem's self-care deficit theory, individuals' failure to care for themselves hinges on limitations of knowing, judgement, and decision making (Orem, Taylor, & Renpenning, 1995). In a study of SC behaviour of patients  38 with heart failure, Jaarsma et al. (2000) reframed these broadly described sets of deficits as follows: 1. Knowledge: limitations of knowing about one's own functioning. 2. Decision: limitations in making judgements and decisions about what one should do to care for oneself. This includes the inability to produce alternative actions, avoiding decision making, or having over-riding interests or concerns. 3. Skill or opportunity: limitation in engaging in result-achieving courses of action, derived from a lack of support, resources or energy. According to Orem's theory, factors that influence SC agency include age, gender and health status, health care services, family structure, lifestyle factors, the individual's developmental stage, and socio-cultural orientation (Orem et al., 1995). Connelly (1987) conceptualized a Model of Self-Care in Chronic Illness (MSCCI), suggesting that predisposing factors (self-concept, health motivations, patients' perceptions) and enabling factors (patients' characteristics, psychological status, regimen features, cues to action, social support, and system characteristics) influence SC behaviour. In a study focusing on heart failure, Rockwell and Riegel (2001) derived a model of seven predictors of SC based on Connelly's work. The predictors tested were: (1) symptom severity, (2) co-morbidity, (3) social support, (4) education, (5) age, (6) socio-economic status, and (7) gender. Using multiple regression analysis in their study of 209 patients, they found that their model explained only 10.3% of the variance in heart failure self care, with education and symptom severity being the sole statistically significant predictors. The Self-as-Carer Inventory (SCI) was developed by Hanson and Bickel (1985) and validated by Geden and Taylor (1991) to measure SC agency. The instrument, consisting of  39 40 statements quantified by a 6-point Likert-type scale, has been employed in various studies focussing on the management of chronic illness (Lukkarinen & Hentinen, 1997). For the purpose of this study, the following SC theoretical framework emerges as relevant to the development of the research instrument: Figure 1: Theoretical Elements of Self-Care  Because the theory of SC focuses primarily on SC agency, defined as the decisionmaking phase, and SC behaviours, conceptualized as the productive phase of health maintenance and management actions, it omits processes that facilitate the transition between these two stages (Carroll, 1995). Rising from social learning theory, the theory of selfefficacy (SE) developed by Bandura (1977, 1980, 1995) aims at explaining the link between self-perception and behaviour. In contrast to SC, SE is not concerned with individuals' skills, but rather their perception and belief that they can carry out the behaviour required to reach  40 the desired goal and to achieve an expected outcome (Clark & Dodge, 1999). Bandura defined the concept of self-efficacy as "the exercise of human agency through people's beliefs in their capabilities to produce desired effects by their actions" (Bandura, 1997, p. iv). SE involves a behaviour-specific process that evolves in the context of a continuous interaction between personal, behavioural, physiological, and social-environmental influences. Out of this process arises the individual's confidence in his or her capability to organize and execute the required course of action to address a specific problem at a specific time (Bandura, 1977; Clark & Dodge, 1999; Sullivan, LaCroix, Russo, & Katon, 1998). Selfefficacy represents individuals' perceived capacity to integrate cognitive, social, and behavioural skills to meet the needs of managing their illness (Bandura, 1986). Each situational demand determines efficacy beliefs, because individuals are motivated to perform behaviours that they believe will produce the desired outcomes (Maibach & Murphy, 1995). According to Maibach and Murphy (1995), who examined the SE construct as it relates to health promotion research and practice in elderly patients recovering from CABG surgery, there are four processes that influence SE beliefs: (1) choice behaviour, (2) effort expenditure and persistence, (3) thought patterns, and (4) emotional effects. The specific and combined effects of these factors shape individuals' level of SE. Carroll (1995) argued that several important antecedents, such as direct performance of an activity, vicarious experience, verbal persuasion by a credible authority, and the individual's own physiological state influence SE expectations. The Cardiac Self-Efficacy Questionnaire is a 13-item instrument developed by Sullivan et al. (1998) to study SE and self-reported functional status in patients with CAD. Participants are asked to rate their confidence with knowing and acting on each statement on  41 a 5-point Likert scale. The format of the questionnaire consistently uses, "How confident are you that you know or can?" to explore respondents' belief about their capability to manage their cardiac care (Sullivan et al., 1998, p. 475). SE theory, including how people judge their specific capabilities and confidence, and their SE expectations, offers a potential mediator between SC agency and SC behaviour to provide a more complete theoretical framework. Building on the previous figure, Figure 3.2 is a graphic representation of the study's theoretic framework:  Figure 2: Theoretical Model Patient and Procedural Characteristics Socio-demographic variables  Cardiac disease severity  Presence of o-morbidities Cardiovascular risk factors  Self-care agency  PCI procedural characteristics  Cardiac self-efficacy  Self-Care Behaviour  42 Summary of Research Project  This study was designed to describe elective same-day discharge PCI patients' individual and procedural characteristics, and recovery upon return home. The intent was to better understand the process of transition from short-term hospitalization and accelerated discharge, to caring for themselves following PCI, by identifying the factors associated with key outcomes. This study provides preliminary findings to establish predictors of patient outcomes in the immediate days following same-day PCI. Research Design  Individuals with stable CAD who were either referred for PCI after undergoing coronary angiography as an earlier diagnostic test, or who had a PCI performed immediately following positive angiographic findings ("ad hoc PCI"), were elgible for this study. Because the process of discharge varies for patients admitted on an elective or urgent basis, the study was limited to the outcomes of patients undergoing elective PCI. This minimized the confounding effects of medical emergencies, such as acute coronary syndrome. The setting for this study was the Heart Centre at St. Paul's Hospital, in Vancouver, British Columbia (BC), a provincial quaternary referral program for cardiac patients. The PCI program at St. Paul's Hospital is one of four provincial centres that offer access to PCI services for B.C. and Yukon patients. Patients were recruited in the Cardiac Short Stay Unit (CSSU), where patients are routinely admitted, recovered, and discharged from their elective PCI. A retrospective descriptive correlational design was used to answer the research questions. Before their discharge from the hospital, data were collected from the enrolled patients' charts, including demographic information, cardiac disease descriptors and co-  43 morbidities, risk factors for heart disease, and procedural characteristics. The study participants were contacted by telephone by the investigator 2 to 5 days following discharge and were administered a questionnaire pertaining to their discharge process, recovery, adherence to instructions, knowledge of long term management of CAD, and levels of confidence in caring for themselves. Research Questions  1.  What are the self-care recovery behaviours of elective same-day discharge PCI patients in the initial 2 to 5 days following return home?  2.  What are the relationships between elective same-day discharge PCI patient and procedural characteristics and patients' cardiac self-care agency in the initial 2 to 5 days following return home?  3.  What are the relationships between elective same-day discharge PCI patient and procedural characteristics and patients' cardiac self-efficacy in the initial 2 to 5 days following return home? Research Methods  Research Protocol At St. Paul's Hospital, elective percutaneous coronary interventions are performed Monday to Friday. Prior to admission, patients are contacted and booked for their procedure by a centralized office where a daily schedule is generated, specifying the patients' baseline demographics and the type of procedure booked. All patients listed for a booked PCI or coronary angiography with PCI, if their diagnostic test was found to be positive ("+/- PCI") were identified and screened for eligibility. Patients recovering from PCI were initially approached by the Cardiac Short Stay Unit (CSSU) registered nurse to assess their interest in  44 participation in this study. If the patient wished to join the study, or expressed interest in obtaining further information about the project, the investigator spoke with the patient, explained the study, obtained consent if the patient was willing, made arrangements for telephone follow-up, and proceeded with the hospital chart data collection. Sample The study population included all elective PCI patients admitted to St. Paul's Hospital between January 2 , 2007 an May 31 , 2007. The population included both men and women. nd  st  Every eligible individual was approached for participation in the study. To control for the potential variation in vascular access complications, only patients undergoing PCI via the femoral artery were included. In total, 5 elective radial PCI procedures were performed during the study period and were excluded. The study included patients who achieved hemostasis by means of compression device and closure device; both methods are routinely employed in clinical practice. The exclusion of hospitalized patients under investigation for symptoms suggestive of myocardial ischemia or diagnosed with acute coronary syndrome ensured that the study was focused solely on stable patients admitted and discharged on the day of their procedure. Other exclusion criteria included lack of capacity to give consent, lack of English comprehension, and lack of access to telephone services. In the past, approximately 500 elective PCIs were performed annually at St. Paul's Hospital (M. Wilson, personal communication, September 12, 2006). Nevertheless, it was anticipated that recent changes to practice, including rising clinical time allocated to investigational interventional procedures and nursing staff shortages, would create challenges for recruitment. In addition, cardiac catheterization laboratory renovations to upgrade  45 imaging and monitoring equipment, which required intermittent closure of clinical space, coincided with participant recruitment. The original intention was to recruit 120 to 150 participants; however, because of difficulties encountered at the study site,fivemonths of enrolment were required to obtain a sample of 100 patients. Although a population-based approach was taken and every potential participant was approached, it is customary to complete and interpret inferential statistics even in the case of a population-based approach. Consequently, we examined a priori analyses of the required sample size, assuming medium sized effects, alpha=.05 (2-tailed) and statistical power of 80%. Conventional power analysis using power tables, such as those of Cohen (1988) require the preliminary calculation of non-centrality parameters, and constituted a challenge for this research project (Dunlap, Xin, & Myers, 2004). Alternative and simpler approaches to sample size calculations have been proposed. Tabachnick and Fidell (1996) suggested a rule of thumb that the sample size should equal or exceed 50 + 8/?, where p equals the number of predictor variables included in the analysis. Knapp (1998) echoed Tabachnick et al.'s approach by proposing that the minimum n required equals 10 times the number of study variables. In this study's setting, it was anticipated that 9 to 12 predictor variables would emerge as bivariately significant, and be included in the predictive model. Thus, a minimum sample size of 120 to 150 was initially sought. Measurement The literature did not reveal any tools to study the potential correlates of patient outcomes following PCI. Beyond the collection of data related to patient and procedural characteristics, the study required the development of an instrument to measure both patients'  46 self-care agency and cardiac self-efficacy following PCI, and to describe self-care behaviours following discharge. Established instruments were used when available and appropriate. To efficiently collect data, a comprehensive chart extraction tool and patient questionnaire, using standard demographic and clinical data as recorded on hospital admission records and the British Columbia Cardiac Services Registry, were developed for this study (see Appendix A). In addition, a telephone interview script, combining questions arising from validated instruments and items developed to address the needs and purpose of the present study was prepared to consistently collect and record data from the participants (see Appendix B). In the following section, the study variables are itemized as they pertain to the theoretical framework and research questions. All data extracted from the patients' charts are referred to as #C (chart), whereas items from the telephone interview tool are numbered without an additional label. Socio-Demographic Variables  The socio-demographic variables were collected with well-established survey questions, reflecting standardized practice in Canada. The items included gender (#C1), birth date and age (#C2), and marital status (#C3). Additionally, cultural background (#79, 80, 85), employment, and education status (#81-84), annual household income (#86-89), and total number of household members (#90) were recorded. Health authority, community of residence and postal code, and location of referring physician were noted to calculate the distance in kilometres from residence to referral centre and to community medical services (#C4-5).  47 Cardiac Disease  Markers of cardiac disease included CCS Class (#C18), NYHA Functional Class and left ventricular ejection fraction (#C19), presence of single or multi-vessel CAD as defined as narrowings greater than 70% (#C 14), and prior cardiac event, including previous PCI, CABG or acute myocardial infarction (#C20). Co-Morbidities  Standard co-morbidities were noted as documented in the BC Cardiac Services Registry. These included renal dysfunction, peripheral vascular disease, cerebrovascular disease, hypertension, and diabetes (#C20). The burden of co-morbidities is conventionally measured using the Charlson Comorbidity Index (Charlson, Pompei, Ales, & MacKenzie, 1987; Charlson, Szatrowski, Peterson, & Gold, 1994) to predict outcome. This index assigns a weighted score to co-morbidities, and accounts for the added confounding effect of age. The validation of the instrument showed that higher co-morbidity index scores were associated with stepwise increases in the mortality rate attributable to co-morbid disease (Charlson et al., 1987). The weighted co-morbidity/age index has been used in studies to indicate individuals' severity of condition and to predict the mortality risk associated with co-morbid conditions, with test reliability reported as 0.91 (Skaggs et al., 1999). Because of the prognostic importance of comorbid diseases in the setting of stable CAD, a study by Sachdev, Sun, Tsiatis, Nelson, Mark et al. (2004) suggested using a modified version of the Charlson Score, the CAD-Specific Index, which excluded congestive heart failure and myocardial infarction, as these are direct and concurrent manifestations of CAD, rather than a separate comorbid conditions. Sachdev et al. found that diabetes, renal insufficiency, chronic obstructive pulmonary disease, and peripheral vascular diseases had  48 the greatest prognostic significance among CAD patients, whereas peptic ulcer disease, connective tissue disease, and lymphoma were less significant. The CAD-Specific index also excluded hemiplegia, leukemia, lymphoma, severe liver disease, and acquired immunodeficiency syndrome as these were rarely identified among patients with CAD. The CAD-Specific index enhanced the predictive value of the Charlson Index in patients with stable CAD. In the present study, the CAD-Specific Index was used to quantify the comorbidity of participants. A summary of the Sachdev et al. Due to lack of clinical data, any history of malignancy was recorded as "Any tumour" (weight = 2) and did not differentiate with "Metastatic solid tumour" (weight = 5). "Moderate or severe renal disease" was attributed to participants with a serum creatinine greater than 265 mmol/L (based on Sachdev et al's criterion). All cases of diabetes were recorded as "Diabetes mellitus" (weight = 2) as data were missing to differentiate with "Diabetes with end-organ damage" (weight = 3). The summary of the items utilized in CAD-Specific Index can be found in Appendix C. In addition, the participants underwent a short screening for mood disorders, using the STOP-Distress tool (#74-78). These items were administered during the post-discharge participant telephone interview. Measurements of depression utilized in studies include the Cardiac Depression Scale (Astin, Jones, & Thompson, 2005), and the Beck Depression Inventory (Frasure-Smith, et al., 2000). STOP-D, a 5-item, self-report screening tool for depression, anxiety, stress, anger, and poor social support, was recently developed in the cardiac out-patient setting of St. Paul's Hospital, Vancouver, BC (Young & Fofonoff, personal communication, July 10, 2006). This yet-unpublished instrument was validated using the Beck Depression Inventory-1 l(BDI), the Beck Anxiety Inventory (BAI), the StateTrait Anger Expression Inventory-2 (STAXI-2), and the MOS Social Support Survey (SSS).  49 STOP-D offers the advantage of requiring only one to two minutes for patients to complete to provide valid severity scores in the five key areas of psychological distress. The instrument has not been validated for use over the telephone. The STOP-D items are stand-alone screening tools for the various psychological distress conditions, depression, anxiety, stress, anger, and lack of social support. Because each item has been validated against the standard psychological screening diagnostic instrument, a cut-off score has been determined for each item to determine the potential need for further assessment. To maximize sensitivity and specificity, the authors have set the cutoff score for depression and anxiety at 3, whereas the cut-off scores for stress and anger item are set at 5, and that of the social support item at 4 (Young, Ignaszewski, Fofonoff, & Kaan, n.d.). The screening tool utilized in the outpatient clinics (pre- and post-heart transplant, cardiac rehabilitation, and adult congenital heart) where the instrument was originally validated, is provided in Appendix D. Cardiovascular Risk Factors  BC Cardiac Services Registry documentation was used to collect relevant information about the presence of additional risk factors, including smoking, dyslipidemia, and obesity (#C18). Procedural Characteristics  Information differentiating single vs. multi-vessel procedures (#C15), the number of stents deployed (#C16), the target vessels (#C17), the use of intravenous glycoprotein inhibitors (#C6-7), the process of hemostasis, including associated complications (#C8-12), and the total duration of hospitalization (#C13) was obtained from the cardiac catheterization laboratory reports and nursing records.  Self-Care Agency  The respondents were asked several questions pertaining to the adequacy of the information they received before their hospital discharge to assess their knowledge, decisionmaking, and competency and skill to care for themselves (#39-44 and #53-57). Given the absence of self-care agency assessment tool for PCI patients, the questions were constructed based on the various patients' learning needs identified in the literature. Items were based on the PTCA Learning Needs Inventory (PTCALNI), a validated Canadian list of learning priorities developed by Brezynskie et al. (1998) at the University of Ottawa Heart Institute (#39-44 and 53), and complemented by items from the Patient Learning Needs Scale by Bubela et al. (1990) (#54-57). The scale was adapted to a three point response format - "no", "somewhat", "yes" - to standardize responses. In the interview process, responses such as "no", "not really", and "not at all" were recorded as no; "not really", "kind of, and "more or less" were recorded as somewhat; and "Yes", "I think so", and "definitely" were recorded as Yes. Patient Satisfaction  Patients' experience and level of satisfaction with the care received while in hospital have been identified as elements that contribute to self-care agency because they relate to knowledge transfer, decision making and opportunity to practice skill and competency (Jaarsma et al., 2000). Several questions were asked to assess the patients' satisfaction with their hospitalization and discharge process (#59-67). Using the instrument validated by Mark and Wan (2005) in their study of the measurement equivalence of patient satisfaction tools, the  51 participants were asked to rate their responses to the 9 selected questions, on a modified 4point scale including "poor", "fair", "good" and "excellent". Cardiac Self-Efficacy  In the absence of an appropriate validated tool to measure patients' readiness for discharge following PCI, questions were constructed to assess participants' self-efficacy and perceived readiness to leave the hospital. Consistent with the study's theoretical framework, questions about the participants' capacity and confidence to engage in their required course of action were selected from the self-efficacy literature. Items (#70-72) were drawn from the Cardiac Self-Efficacy Questionnaire (Sullivan et al., 1998), a tool with established internal consistency and validity. Additionally, respondents were asked questions modelled on the Jenkins Self-Efficacy Expectation scale for maintaining health (Perkins & Jenkins, 1998) and Clark and Dodge's (1999) study of self-efficacy as a predictor of disease management (#68, 69). Items #73 and 74 were added to the questionnaire because they refer to pertinent aspects of self-efficacy omitted from the existing instruments. The response scale was standardized to a 4-point response, with "not confident at all" indicating the lowest level of confidence, and "very confident" being the highest score. The use of ordinal-level responses aimed at providing consistency and ease of use. Together, these questions formed a consistent and comprehensive assessment of PCI patients' self-efficacy at discharge. Self-Care Behaviour  Supported by the study's theoretical framework, questions were developed to describe the participants' exercise of self-care behaviour, in both the maintenance and management of their health following discharge (#2-38, #45-51). In the absence of a  52 validated measurement of self-care behaviour, the study was limited to describing behaviour and sources of information. Guidelines contained in the patient teaching booklet given to patients at the time of discharge (Going Home After Percutaneous Coronary Intervention, Vancouver Coastal Health and Providence Health Care, 2006) were itemized and utilized to formulate questions (#2-36) related to symptom monitoring and adherence to treatment. Questions were developed to assess the patients' behaviour self-care management including symptom recognition, evaluation and treatment, as well as short term and longer term treatment evaluation (#44-51). In the absence of a validated tool to measure self-care in the post-PCI population, questions were modelled on instruments employed in other cardiac studies. Question #44 was drawn from Artinian et al. (2002) and served as the introduction to questions related to selfcare management. In addition, three sets of questions, the Self-as-Carer Inventory (SCI) utilized by Lukkarinen and Hentinnen. (1997) in their study of self-care agency and heart disease, the Self-Management of Heart Failure Instrument (Rockwell & Riegel, 2001), and the Heart Failure Self-Care Behaviour Scale (Jaarsma, 2000), constituted the template for the formulation of questions 45 to 48. Questions about participants' intention to attend a cardiac rehabilitation program were added (#49-51), based on the findings of Dendale et al. (2005) and Deaton and Namasivayan (2004) which suggest that patients who are aware of available resources and who express intention to attend are more likely to participate in the longer-term management of their chronic illness. In addition, Dendale et al. (2005) demonstrated that attendance at a cardiac rehabilitation program reduces the likelihood of major adverse cardiac events following PCI.  53 Data Quality  Every effort was made to minimize any potential source of systematic or random error in this study. Random error was minimized by the collection of most data by one investigator, ensuring the consistent treatment of arising personal or situational factors, although 6 telephone interviews were performed by two research assistants who received extensive training. Other factors that may have contributed to random error included the varying time interval between discharge and interview, the level of discomfort experienced by the respondents in answering questions on the telephone, and issues related to privacy. Care was taken during data collection to ensure that these sources of potential random error were kept to a minimum. Given the exploratory and descriptive nature of this study, there was great reliance on the data collection tool. Validity of the instrument was based on the utilization of previously validated questions, and on face validity and content validity of the items developed exclusively for this study and not previously validated. Pre-testing and modification of the instrument with 8 participants achieved the goal of ensuring that the questions were readily understood and answered without hesitancy or need for clarification. Data Analysis  Data Screening In addition to the strategies outlined to ensure data quality, additional measures were taken to ensure data accuracy. The data set was searched for errors in data entry, and the values in the frequency distributions were inspected, with special attention paid to the highest and lowest values to assess the validity of potential outliers (Polit, 1996). As recommended  54 by Bums and Grove (2005), the accuracy of the data points was randomly checked with the original data collection record. To avoid problems associated with missing data (Hazard Munro, 2001), efforts were made to accurately complete the data sets when possible, including contacting study participants and retrieving medical records. Only two data sets were incomplete due to the investigator's inability to contact the participants in spite of repeated efforts. As suggested by Hazard Munro (2001), listwise deletion was used because this technique is the easiest and most direct method of dealing with missing data. To fulfill the requirements of inferential statistics in the use of regression analysis, the data were tested to ensure that they met the assumptions of independence of observation, normal distribution, and homogeneity of variance (Huck, 2004). Description of Sample To understand the main characteristics of the study sample, descriptive statistics, including frequency distributions and measures of central tendency and dispersion, were used to summarize the participants' main attributes (Burns & Groves, 2005; Polit, 1996). Statistical Analysis Descriptive statistics and multiple linear regression analysis were used to answer the research questions.  To address question 1, What are the self-care recovery behaviours of elective same-  day discharge PCI patients in the initial 2 to 5 days following return home?, the identified  components of self-care behaviour were described. The following statistical plan was devised and implemented to answer questions 2 and 3, What are the relationships between elective same-day discharge PCI patient and  55 procedural characteristics and patients cardiac self-efficacy and self-care agency. Factor  analysis was used as a data reduction technique to determine how the 7 items related to selfefficacy and the 13 self-care agency measures clustered together to form uni-dimensional constructs consistent with the study's theoretical framework. The ensuing factor extraction aimed at identifying intercorrelated variables to identify as much variance as possible from the common factors. It was decided that a maximum of two factor loading was necessary to optimize the study's power. The ordinality of the items violated the required assumptions of standard exploratory factor analysis (Pallant, 2005). Therefore, exploratory factor analysis was performed using the Mplus® statistical software program (Muthen & Muthen, Version 4.21, 2006), which has the capacity to fix latent variable models that contain ordinal outcome variables, assuming a theoretical basis for model specification, a reasonable sample size of 100, complete data, and continuously distributed latent variables (http://www.utexas.edu/itsrc/tutorials/stat/mplus and http://www.statmodel.com/features.shtml). Separate exploratory factor analyses were performed for the two underlying theoretical constructs, self-efficacy and self-care agency. The exploratory analysis of the relationship between patient and procedural characteristics, and the outcome variables of interest was performed using correlation analysis for continuous variables (age, time of bedrest and hospitalization, ejection fraction, creatinine, and body mass index scores), t-tests for dichotomous variables (gender, education, GPIIbllla infusion, method of hemostasis, severity of CAD, single vs. multivessel PCI, previous AMI, PCI and CABG, other co-morbidities), and exploratory one-way analysis of variance (ANOVA) for variables with 3 or more responses (marital status, health authority residence, main activity, number of household members, income, smoking history and  56 STOP-D classification). Many variables were not normally distributed. To retain statistical power and to facilitate the analysis, the following variables were collapsed as outlined in Table 1. Table 1 Initial Variables Collapsed into New Multivariate or Bivariate Variables Explanatory Variable  Initial Multi-Variate Coding  New Multi-Variate or Bivariate Coding  Marital status  Single Married Common law Divorced Widowed  Health authority of residence  Vancouver Coastal Health (VCH) 1. Local (VCH - Lower Mainland, FH) Fraser Health (FH) Interior Health (IH) 2. Remote (VCH- outside of Northern Health (NH) Lower Mainland, IH, NH, Yukon Yukon)  Main activity  1. Working (Caring for family, Caring for family working for profit/pay, Working for profit/pay caring for family and Caring for family and working working) Recovering from illness/disability 2. Not working (recovering Looking for work from illness/disability, Retired looking for work, retired)  Income  < 25,000 25,000 - 50,000 50,000-75,000 75,000- 100,000 > 100,000  1 Number of household members 2 3 4 5 and more  1. No partner (single, divorced, widowed) 2. Partnered (married, common law)  1. < 25,000 2. 25,000-50,000 3. > 50,000  1. Living alone (1: respondent only) 2. Not living alone (2 and more)  57 Explanatory Variable Number of stents  Initial Multi-Variate Coding  1 2 i  New Multi-Variate or Bivariate Coding  1. 1 stent only 2. 2 or more stents  j  4 and more CCS Class  0 1 2 3 Atypical  1. CCS Class 0, 1,2, atypical 2. CCS Class 3  Creatinine  Continuous variable (normal: below 120mmol/L)  Within normal range (<120 mmol/L) 2. Above normal range (>120 mmol/L)  BMI  Continuous variable (normal: below 25)  1. Below 25 2. 25 and above  1.  1. less than 202 minutes (above (M=202 minutes, SD=56 minutes) mean) 2. More than 202 minutes (below mean) Continuous variable 1. Less than 10 hours (above (M=10 hours, SD=90 minutes) mean) 2. More than 10 hours (below mean)  Duration of bedrest Continuous variable  Duration of hospitalization  i j.  STOP-Distress:  Score between 0 and 9 Cut-off score for sensitivity and specificity: 3  1. Score between 0 and 3 2. Score between 4 and 9  STOP-Distress:  Score between 0 and 9 Cut-off score for sensitivity and specificity: 3  1. Score between 0 and 3 2. Score between 4 and 9  STOP-Distress:  Score between 0 and 9 Cut-off score for sensitivity and specificity: 5  1. Score between 0 and 5 2. Score between 6 and 9  STOP-Distress:  Score between 0 and 9 Cut-off score for sensitivity and specificity: 5  1. Score between 0 and 5 2. Score between 6 and 9  Depression item  Anxiety item  Stress item  Anger item  58 Explanatory Variable  Initial Multi-Variate Coding  New Multi-Variate or Bivariate Coding  STOP-Distress: Social support item  Score between 0 and 9 Cut-off score for sensitivity and specificity: 4  1. Score between 0 and 4 2. Score between 5 and 9  To identify candidate variables for multivariate analysis, and because of the exploratory nature of this preliminary analysis, the initial level of significance was set at .20. In cases where the Levene's Test for Equality of Variance was less than .05, equal variances between groups was not assumed and analysis was done accordingly (Hazard Munro, 2005; Huck, 2004). To construct and test the predictive model, variables were trimmed in decreasing order of significance from .20 to less than .05. Only variables with a significance level of less than .05 were retained in the final model. Ethical Considerations The Ethics Review Boards of Providence Health Care and the University of British Columbia (ERB-PHC/UBC) reviewed this study and granted authorization (UBC-PHC BREB H06-00211) to conduct the research. Protection of the participants was of high priority in this study. Following the PCI, the participants were informed of the purpose of the study, that their participation was strictly voluntary, and that they were free to withdraw their consent at any time, without threat, penalty, or interference with their clinical care. If willing to participate, informed consent was obtained. A copy of the consent form can be found in Appendix E. Consent was confirmed when the participants were called to complete the questionnaire. The study participants were provided with a signed, witnessed copy of their consent to participate. Anonymity of the study participants was maintained at all times, with  59 all data organized with subject codes, and all identifiable information secured in a locked file. In the event that the participants asked questions about their disease, treatment or outcome, answers were provided to the best of the investigator's ability after data collection was complete. If outstanding information was required, recommendations to contact other healthcare professionals were made as appropriate.  60 CHAPTER 4: ANALYSIS AND RESULTS Efficiency of Sampling The total number of elective patients undergoing PCI either as a planned procedure or on an ad-hoc basis between January 2 and June 1, 2007, and details pertaining to recruitment and enrolment to the study are shown in Table 1. Study enrolment required the presence of the investigator to perform consistent chart extraction and schedule telephone appointment. Due to the absence of the investigator, 8 potential participants were not enrolled. In spite of numerous attempts to reach participants following their discharge home, 5 enrolled participants failed to complete the telephone interview, accounting for an attrition rate of 5%. The final sample size was 98. Figure 3 Recruitment, Enrolment and Response Rates of Participants 126 Patients Undergoing PCI  Ineligible: 10 (8%) Not fluent in English: 9 No telephone: 1  Enrolled: 103 (82%)  Incomplete (no interview): 5 (4%)  Eligible: 116(92%)  Missed: 8 (6%)  Complete: 98 (78%)  Refused: 5 (4%)  61 The telephone follow-up was scheduled to occur two to five days following discharge. The calls were placed during all days of the week, including weekends. On average, contact was made 3.4 days (S.D. = 1.2) following hospital discharge. Table 2 reports when calls were completed for all study participants. Table 2 Post-Discharge Telephone Interview Contact Day Number of days following discharge  Frequency (%) (n=98)  2 days  34 (34.7)  3 days  18(18.4)  4 days  20 (20.4)  5 days  26 (26.5)  Characteristics of Participants In an effort to identify factors associated with self-efficacy and self-care outcomes, data were collected to describe the patients' demographics, severity of disease, and procedural characteristics, using both objective chart extraction and self-reported responses. Demographic Characteristics The complete summary of the participants' demographic characteristics is presented in Table 3. The average age of the participants was 62.8 years (SD = 9.9, range 41 - 90), with women representing less than a quarter of the sample (22%). Although 62.2% of the participants reported that they were married, 44.9% were reported to be "single" in the  62 hospital admission documentation. Only 18.4% stated that they lived alone, and 58.2% of the participants reported living with one other person. Nearly one half of the participants (44%) had addresses that were within the catchment of the Vancouver Coastal Health Authority, which includes Vancouver and some of its surrounding suburbs, but also more remote communities on the Sunshine Coast and northern coastal area. A closer examination of the data revealed that 80% resided close to Vancouver whereas 20 % lived in more remote areas of the health authority. One third of the participants (29.6%) lived in the Yukon and the Northern Health Authority, which spans two thirds of the northern area of British Columbia. Graduation from secondary school was achieved by 70.4% of all participants, with 88.6% of that group reporting additional post-secondary education. Participants reported near equal rates of employment and retirement (41.8% and 42.9% respectively), with 11.2% stating that their employment status was suspended because of their on-going recovery and disability. Self-reported annual household income, excluding other assets, was less than $25,000/year for one quarter of the respondents (25.8%), with similar percentages in the $25,000 to $50,000, and $50,000 to $75,000 categories (23.7% and 25.5%, respectively). Only 3.1% reported being in the $75,000 to $100,000 stratum while 21.4% claimed total incomes greater than $100,000/year. Most (65.3%) participants were born in Canada, while few (3.1%) came from Asia, 22.4% were born in Europe, and 9.2% were born in other countries, including the United States, Australia, and New Zealand.  63 Table 3 Demographic Characteristics Characteristic Age (Years, Mean ± SD)  Frequency (%) (n = 98) 62.8 ± 9.9  Gender Male Female  76 (77.6) 22 (22.4)  Marital Status Single Married Common law Divorced/separated Widowed  11(11.2) 61 (62.2) 6 (6.1) 11(11.2) 9 (9.2)  Household members 1 (respondent only) 2 3 4 5 or more  18(18.4) 57 (58.2) 12(12.2) 9 (9.2) 2 (2.0)  Residence BC Health Authority: Vancouver Coastal  44 (44.9)  Greater Vancouver area Remote Vancouver Coastal  Fraser Interior Vancouver Island Northern Out of province: Yukon  Total household income (gross) < $24,999 $25,000 to $49,999 $50,000 to $74,999 $75,000 to $99,999 > $100,000 Refused to respond  15 (15.3) 9 (9.2) 1(1-0) 25 (25.5) 4(4.1) 25 (25.8) 23 (23.7) 25 (25.5) 3 (3.1) 21 (21.4) 1(1)  35 (79.6) 9 (20.4)  64 Characteristic Educational Attainment < High school graduate High school graduate  No post secondary education Post-secondary education:  Frequency (%) (n - 98) 29 (29.6) 69 (70.4)  7(11.4) 62(88.6) 28(45.1) 11 (17.7) 23(37.2)  Incomplete post-secondary education Post-secondary certificate or diploma University degree  Occupation Caring for family Working for profit/pay Caring for family and working for pay/profit Recovering from disability/illness Unemployed/looking for work Retired  1 (1.0) 39 (39.8) 2 (2.0) 11 (11.2) 3(3.1) 42 (42.9)  Birthplace Canada Asia Europe Other  64 (65.3) 3(3.1) 22 (22.4) 9 (9.2) Cardiac Disease and Co-Morbidity  The summary of the cardiac disease and co-morbidity findings is presented in Table 4. Nearly all of the patients experienced symptoms of angina and other clinical manifestations related to CAD, with one half being classified as CCS Class 2 (56.1%) and 25.5% as CCS Class 3. Inconsistent with the "elective" nature of same-day discharge PCI, 1 patient presented with CCS Class 4, suggestive of acute coronary syndrome. Just fewer than one fifth (17.3%) of the patients had a concurrent diagnosis of heart failure, with most of this group identified as NYHA Class II (76.5%). The mean ejection fraction of the participants was 57.8% (SD 9.0) with a range of 20% to 82%. Almost half (43.3%) of patients had a previous acute myocardial infarction. Nearly one third of the patients (31.6%) had previously undergone PCI, while 11.2% presented following coronary artery bypass surgery.  65 The majority of patients had pre-existing hypertension (69.4%) and dyslipidemia (79.6%). One quarter of the participants (26.5%) were diabetic, with 30.8% requiring insulin and the remainder (69.2%) taking oral anti-hyperglycemics or relying on diet control. Although 25.5% of the participants reported being life-long non-smokers, 17.3% identified as current smokers. Of the 57.1% who were former smokers, data were not available to differentiate between recent and longer term smoking cessation. Only one patient had severe renal failure requiring dialysis with a chronic creatinine level of 950 mmol/L. Excluding this outlier, the mean creatinine of the participants was 94 mmol/L (SD 24.9, range 49-228). Some participants were also diagnosed with peripheral vascular disease (6.1%), cerebrovascular disease (8.2%), respiratory disease (9.2%), liver and gastrointestinal disease (11.2%), and a history of malignancy (5.1%). Table 4 Cardiac Disease and Co-Morbidity Characteristics Characteristic  Frequency (':%) (n = 98)  CCS* class  0  2 3 4 Atypical  3(3.1) 8 (8.2) 55 (56.1) 25 (25.5) 1 (1.0) 6(6.1)  Heart failure If history of heart failure, NYHAf class I II III IV  17(17.3)  Ejection fraction (Mean ± SD)  57.8% ± 9.0  Prior PCI  31 (31.6)  3 (17.6) 13 (76.5) 1 (5.9) 0  66 Characteristic Prior acute myocardial infarction  Frequency (%) (n = 98) 43 (43.9)  Prior CABG surgery  11 (11-2)  Hypertension  68 (69.4)  Hyperlipidemia  78 (79.6)  Dialysis  1 (1.0)  Creatinine (mmol/L, Mean ± SD)  94 ± 24.9  Diabetes mellitus (DM)  26 (26.5)  If history of DM No insulin Insulin  Smoking Never Former Current  18 (69.2) 8 (30.8)  25 (25.5) 56(57.1) 17(17.3)  Peripheral vascular disease  6 (6.1)  Cerebrovascular disease  8 (8.2)  Previous respiratory disease  9 (9.2)  Previous liver/gastrointestinal disease  11 (11.2)  Previous malignancy  5(5.1)  Height (cm; Mean ± SD)  173 ± 8.8  Weight (kg; Mean ± SD)  83.6 ± 16.2  Body mass index (kg/m Mean ± SD)  28 ± 4.6  2;  * Canadian Cardiovascular Society, |New York Heart Association A summary of the participants' CAD-Specific Index of co-morbidity scores and risk stratification are presented in Table 5. The mean score was 1.97 (range: 0-9, SD=1.7).  67 Table 5 CAD-Specific Index of Co-Morbidity Scores Score  Frequency (%) (n = 98)  Risk Stratification  0  18(18.4)  Low  1  31 (31.6)  Low  2  11 (11.2)  Intermediate  3  25 (25.5)  Intermediate  4  7(7.1)  High  5  3 (3.2)  High  6  1 (1.0)  High  7  1 (1.0)  High  9  1 (1.0)  High  Hospitalization and Procedural Characteristics Table 6 summarizes the hospitalization and procedural characteristics of the participants. Angiography revealed that 59.2% of the participants had multivessel coronary artery disease, but most participants underwent a single-vessel (75.5%) and single stent deployment (55.1%) reperfusion procedure. The most frequently targeted vessels were the right coronary artery (40.8%), the left anterior descending (34.7%) and the left circumflex (26.5%). Of the 11 participants who had had a previous bypass surgery, 6 (6.1%) presented for PCI of a saphenous vein graft.  Glycoprotein Ilbllla inhibitor therapy was initiated and maintained post-procedure on 28 participants (28.6%), for a mean duration of 266 minutes (SD=100). The method to achieve hemostasis following vascular access sheath removal was split nearly evenly between compression device (51.0%) and vascular closure device (47.0%), with manual pressure being used for 2 participants. For the compression device group, the mean time of clamp application was 44.7 minutes (SD=14), followed by a mean bedrest time of 246 minutes (SD=20). Of the 46 participants who received a closure device, the rate of rebleeding requiring subsequent compression device application in the immediate postprocedure period was 19%. The incidence of minor hematoma was 9.2%, with a vagal reaction reported in 2.0% of participants during sheath removal. The mean bedrest time in the closure device group was 156.7 minutes (SD=42). The overall time of hospitalization, as measured by thefirstand last contact with a nurse was 591.5 minutes (SD=90.3), or 9.9 hours (SD= 1.5). Table 6 Hospitalization and Procedural Characteristics Variable  Frequency (' (n=98)  Coronary artery disease on angiography Single vessel Multi-vessel (2 or greater)  40 (40.8) 58 (59.2)  PCI target vessels Single vessel Multi-vessel (2 or greater)  74 (75.5) 24 (24.5)  Number of coronary stents deployed 0 2 3 4 and greater  1(1.0) 54 (55.1) 24 (24.5) 15 (15.3) 3(3.1)  69 Variable PCI target vessel distribution* Left main artery Left anterior descending artery Left circumflex artery Right coronary artery Diagonal artery Obtuse marginal artery Saphenous vein graft  Frequency (%) (n=98) 2 (2) 34 (34.7) 26 (26.5) 40 (40.8) 5 (5.1) 9 (9.2) . 6(6.1)  Glycoprotein Ilb/IIIa inhibitor peri-procedure Glycoprotein Ilb/IIIa inhibitor infusion time (minutes; mean ± SD)  Vascular hemostasis method Compression device Clamp time to achieve hemostasis (minutes; mean ± SD)  Closure device  Re-bleed requiring application of compression device  Manual pressure  28 (28.6) 266 ±100.4  50(51.0) 44.7 ± 14.0  46 (47.0) 9 (19.0)  2 (2.0)  Vascular access hemostasis complications Vagal reaction Minor hematoma (<10 cm diameter) Major hematoma (> 10 cm diameter)  2 (2) 9 (9.2) 0  Duration of bedrest following hemostasis Compression device (minutes, mean ± SD) Closure device (minutes, mean ± SD)  246.4 ± 19.5 156.7 ± 42.0  Duration of hospitalization (minutes, mean ± SD)  591.5 ± 90.3  "Includes multivessel PCI, total exceeds 100%. Self-Care Recovery Behaviour Patients' Destination Following Discharge The patients' destination immediately following discharge is presented in Table 7. Following discharge from hospital, 51.0% of the participants reported staying in close proximity to the PCI centre (requiring an overnight stay at a hotel or a relative's or friend's  70 house), while 48% returned directly home. One 90 year old patient was re-admitted to hospital for management of post-PCI delirium immediately following her discharge, and subsequently discharged 3 days later. The majority of the participants (91.8%) were accompanied at the time of discharge, most frequently by a spouse (62.2%), a friend (13.3%), a son or daughter (12.2%), or another family member (11.1%). Eight participants (8.2%) left the hospital unaccompanied. Table 7 Patient Destination Variable Patient disposition Returned directly home Stayed in hotel/with family or friend Re-admitted to hospital Patients accompanied at discharge No Yes If yes, who accompanied participants? Spouse Son/daughter Friend Other family member Caregiver  Frequency (%) 47 (48.0) 50 (51.0) 1(1-0) 8 (8.2) 90(91.8) 56 (62.2) 11(12.2) 12 (13.3) 10 (11.1) 1 (1-1)  Adherence to Instructions As outlined in Table 8, most of the participants (97%) reported taking appropriate oral anti-platelet therapy, with most of this group (79%) having filled their prescription, either close to the hospital (45.5%) or at their usual pharmacy (54.5%). Over three quarters (77.5%) of participants correctly identified the action of clopidogrel as an anti-platelet agent.  A small number of the participants (4.1%) believed clopidogrel had more extensive protective benefits, whereas 18.4% did not know the purpose of the medication. As directed in the discharge guidelines, 83.7% of the participants had removed their groin dressing by the time of the interview, with most (53.7%) adhering to the recommendation to do so the day after the procedure. When contacted 2 to 5 days post-PCI, 18 (16.3%), participants had not yet removed their dressing. The same percentage of participants did not recall being given instructions about dressing care, although data is missing to confirm whether these were the same participants. When surveyed about their exercise regimen since discharge, 2 (2.0%) participants reported "not walking at all", and 30 (30.6%) reported restricting their activity to "around the house". When compared with the recommended walking distance targets outlined in the patient discharge guidelines, 52.0% of the participants had not reached the recommended target, 27.6% exercised at the target level, and 20.4% exceeded the recommendations. Of the 95% of participants who identified themselves as current drivers, 54.1% had resumed driving by the time of the interview, with most (89.0%) reporting driving 24 to 48 hours following PCI, and 7 participants (7.1%) having driven immediately following discharge. Nearly one half of the participants (48%) reported being currently in the workforce, with most (53.2%) planning to return to work within the week after PCI, and an additional 12.8% scheduling their return to work 1 week after discharge.  72 Table 8 Adherence to Instructions Variable Anti-platelet medication Presently taking clopidogrel (anti-platelet agent) Yes On-going therapy No Filled prescription Yes On-going therapy Short term supply provided by hospital No Where was prescription filled? Close to hospital or en-route home Usual pharmacy When was prescription filled? Before procedure Day of procedure Day following procedure 2 days following procedure 3 days or more following procedure What is the main effect of clopidogrel? Thins the blood, anti-platelet, "super-aspirin" Keeps artery open Prevents heart attacks Don't know Dressing removal Recalled being told when to remove dressing Dressing had been removed by the time of telephone interview Ifyes, when was it removed? < 24 hours after discharge 1 day after 2 days after 3 days or more after  Frequency (%) (n =98) 82 (83.7) 13 (13.3) 3(3.1) 77 (78.6) 13 (13.3) 2 (2.0) 6(6.1) 35 (45.5) 42 (54.5) 1 (1.0) 34 (44.2) 25 (32.5) 16(16.3) 1 (1.0) 76 (77.5) 3(3.1) 1 (1.0) 18 (18.4) 82 (83.7) 82 (83.7) 6 (7.3) 44 (53.7) 25(30.5) 7(8.5)  73 Variable  Frequency (%) (n=98)  First shower Recalled being told when to have 1 shower Had shower prior to telephone interview st  75 (76.5) 78 (79.6)  Ifyes, timing of 1 shower < 24 hours after discharge 1 day after 2 days after 3 days or more after st  Walking Walking distance since discharge No walking Around house only 1 block 2 blocks 3 blocks 4 blocks and more Walking distance compared with recommended target Below target recommendation At target recommendation Above target recommendation Driving Does not usually drive Has started driving since discharge  4  Presently working: If yes, plan to return to work  51 (52.0) 27 (27.6) 20 (20.4) 5 (5.1) 53 (54.1) 7 (7.4) 18(33.4) 30 (55.6) 2 (3.6)  Al (48.0)  < 1 week after discharge Iweek 2-4 weeks Do not know  Appointments Follow-up medical appointment made Aware of need for post-procedure bloodwork  59  2 (2.0) 30 (30.6) 7(7.1) 15(15.3) 4(4.1) 40 (40.9)  Ifyes, timing of resumption of driving < 24 hours after discharge 1 day after 2 days after 3 days or more after  Work  ^ < °) 22 (28.2) 7(9.0) 6  25 (53.2) 6(12.8) 7(14.9)) 9(19.1)  48 (49.0) 8 (8.2)  74 Management of Complications and Symptoms A majority of the participants (60.2%) reported having a bruise at the groin vascular access site. Of this group, most reported the size of the bruise as large (50.8%), and feeling soft (81.4%) (see Table 9). Although 33 (55.9%) participants reported that the bruise was getting better, 9 (15.3%) believed that it was getting worse. Most (76.7%) stated that were not worried about the bruise. At the time of interview, 36 (36.7%) participants stated that they currently experienced pain at the groin site. When scaled between 0 (no pain) and 10 (worse pain), the mean groin pain score was 2.47 (SD=1.7). Nearly one third of the participants (30.6%) reported experiencing chest pain or other usual ischemic symptoms with most of them (80%) taking no action, 13.3% taking nitroglycerin, and 2 participants (6.7%) going to an emergency department. Within 24 hours of discharge, 10 participants (10.2%) presented at an emergency department for management of vascular access or ischemic complications. Table 9 Management of Complications and Symptoms Variable Groin bruise present  Frequency (  59 (60.2)  If bruise present:  Bruise size:  Small Medium Large  Bruise feeling: Soft Hard  Bruise change:  Getting better Staying the same Getting worse  18(30.6) 11 (18.6) 30(50.8) 48(81.4) 11 (18.6) 33 (55.9) 17(28.8) 9 (15.3)  75 Variable Worried about the bruise?  Frequency (%) 14 (23.3) 46(76.7)  Yes No  Groin pain present  36 (36.7)  If groin pain: Groin pain rate between 0 and 10 (mean ± SD)  Chest pain since discharge  If chest pain: "Did nothing", "waited", "stopped what I was doing" Took nitroglycerin Went to emergency department  2.47 ±1.7  30 (30.6) 24(80.0) 4 (13.3) 2(6.7)  Chronic Disease Management When surveyed about whether thy understood the causes of their coronary artery disease, 43% of the participants answered "not at all" or "not very well", whereas 57% responded "quite well" or "very well" (see Table 10). Similarly, half (50%) of the participants claimed to know what lifestyle changes were required to prevent their heart disease from getting worse, and the other half (50%) either "did not know at all", or "knew somewhat". Most (77%) did not plan on attending a cardiac rehabilitation program. While in hospital, only 14 (14.3%) patients reported receiving specific information related to cardiac risk factors and behaviour modification, and 11 (11.2%) recalled being informed about cardiac rehabilitation programs in their area of residence. Finally, when asked whether they believed that they still had coronary artery disease following their PCI, 37.8% stated that they did not.  Table 10  76 Chronic Disease Management Variable  Frequency (%) (n = 98)  How well do you understand the causes of your heart disease? Not at all Not very well Quite well Very well  19(19.4) 23 (23.5) 36 (36.7) 20 (20.4)  Do you know what lifestyle changes are needed to prevent your heart disease from getting worse? No Somewhat Yes  24 (24.5) 25 (25.5) 49 (50.0)  While in hospital, did anyone speak with you about the causes of your heart disease? No Yes  84 (85.7) 14 (14.3)  If yes, who spoke with you? Physician Nurse  7(50.0) 7(50.0)  Do you plan to attend a cardiac rehabilitation program? No Yes  75 (76.5) 23(23.5)  While in hospital, did anyone tell you about cardiac rehabilitation programs in the area where you live? No Yes  87 (88.8) 11(11.2)  Ifyes, who spoke with you? Physician Nurse  Now that you have had an angioplasty, do you think you still have coronary artery disease? No Yes  Screening for Psychosocial Distress  8 (72.7) 3 (27.3)  37 (37.8) 61 (62.2)  77 The highest mean scores on the STOP-Distress brief screen were attributed to anxiety (3.33, SD=2.9), stress (4.24, SD=3.1), and depression (3.81, SD=3.3). The scores measuring anger (1.8, SD=2.4) and social support (1.69, SD=2.6) were lower. When the data was further examined to assess whether participants were below or above the screening cut-off, 49.0% of the participants were above the cut-off for depression, 53.1% scored high in anxiety, 35.7% in stress, 9.2% in anger, and 14.3% in lack of social support. Table 11 STOP-Distress Screening Tool Variable Depression  Mean Score (SD) (n = 98) 3.81 (3.1)  Below cut-off  Above cut-off  50(51.0)  48 (49.0)  Anxiety  3.33 (2.9)  46 (46.9)  52 (53.1)  Stress  4.24 (3.1)  63 (64.3)  35 (35.7)  Anger  1.80 (2.4)  89 (90.8)  9 (9.2)  Social support  1.69 (2.6)  84 (85.7)  14(14.3)  Factor Analysis and Measurement Results Factor Analysis of Cardiac Self-Efficacy (CSE) Items In the exploratory analysis of the 7 self-efficacy items, a large Eigenvalue was attributed to the first factor related to confidence about returning home (4.6), and provided strong supportfora single factor analytic structure (see Table 12). One factor accounted for 57% of the variability in the 7 items. The item loadings all exceeded the accepted standard minimum of 0.4 in magnitude and demonstrated that all the items loaded onto the single factor. Although items 4 (physical activity) and 5 (calling physician) seemed to be less  important than the other 5 items, as indicated by lower loadings, overall, the items clustered to form a single factor. The items were therefore treated as a single scale. Table 12 Exploratory Factor Analysis of Cardiac Self-Efficacy Items Items  #  Factor Loadings  Eigenvalues  How confident did you feel: 1.  About returning home?  0.828  4.562  2.  About caring for yourself?  0.954  0.754  3.  About taking your medications?  0.719  0.660  4.  About knowing how much physical activity is good for you after your angioplasty?  0.579  0.435  5.  About knowing when you should call or visit your doctor about your heart disease?  0.582  0,303  6.  About following instructions?  0.824  0.211  7.  About coping at home?  0.912  0.076  Factor Analysis of Self-Care Agency Items The initial calculation of the eigenvalues, the sum of the squared weights for each factor, of the 13 items related to cardiac self-care agency, demonstrated strong support for a two or three factor structure. A three-factor model provided the best goodness-of-fit analysis, with a chi-square value of 21.4, df 21, p = 0.43. The factor loadings for a 3-factor model are presented in Table 13.  79 It was determined that the study would be best served by identifying a one- or twofactor model to avoid exaggerated inferences and data dilution. Two items "knowledge of action required if chest pain returns" and "knowledge of changes required to prevent heart disease from getting worse" were eliminated since they did not load strongly on any factor for any of the models. A 2-factor model using the 11 remaining items was found to be adequate, with p=0.44. The first factor included the items related to knowing the results, how to care for one self, what to expect, when to call a doctor, what to do with problems with medications, and knowing one's medications. A second factor included knowledge of when to take and to stop medications, of exercise regimens, and when to resume usual tasks. The item "now that you've had your angioplasty, do you understand what symptoms to expect?" loaded equally on both factors. The item was attributed to Factor 1 for concept consistency. The factor loadings of the 11 items are presented in Table 14.  Table 13 Factor Loadings for 3-Factor Analysis of Self-Care Agency Item Knowledge of u  Factors Loadings Factor 1  Factor 2  Factor 3  1.  Results of angioplasty  0.609  0.138  0.312  2.  Action if chest pain returns  0.416  0.354  0.085  3.  Caring for self  0.347  0.732  0.007  4.  What to expect  0.330  0.789  -0.049  5.  When to call doctor  0.887  0.118  -0.055  6.  What lifestyle changes are needed  0.408  0.310  0.195  80 Item Knowledge of  Factors Loadings  #  Factor 1  Factor 2  Factor 3  7.  What to do if problems with medications  0.212  0.275  0.532  8.  How medications work  0.429  0.342  0.645  9.  When to take medications  0.044  0.149  0.928  10.  When to stop medications  0.042  0.014  0.935  11.  How much exercise  0.092  0.610  0.447  12.  When to start doing usual tasks  0.003  0.807  0.383  13.  What symptoms to expect  0.194  0.572  0.334  Table 14 Factor Loadings for 2-Factor Analysis of Self-Care Agency Item # Knowledge of:  Factors Loadings Factor 1 0.458  Factor 2 0.346  1.  Results of angioplasty  3.  Caring for self  0.519  0.127  4.  What to expect  0.756  0.066  5.  When to call doctor  0.811  0.012  7.  What to do if problems with medications  0.632  0.073  8.  How medications work  0.523  0.257  9.  When to take medications  0.315  0.550  10.  When to stop medications  0.501  0.699  11.  How much exercise  0.039  0.938  81 12.  When to start doing usual tasks  -0.086  0.933  13.  What symptoms to expect  0.465  0.461  Cardiac Self-Efficacy and Self-Care Agency Factor Scores Scores were calculated by adding the respondents' scores associated with each item and dividing by the number of items in the factor, thus computing a new variable, and obtaining a score for cardiac self-efficacy, as well as the two components of self-care agency. These two different dimensions were labelled "disease management" (factor 1) and "lifestyle management" (factor 2), with item 13 (symptoms to expect) attributed to factor 1 for conceptual consistency. Descriptive statistics of the cardiac self-efficacy and self-care agency variables are presented in Table 15. Table 15 Cardiac Self-Efficacy and Self-Care Agency Factor Scores Min. LOO  Max. 4XX)  Mean 335  SD ^65  Self-Care Agency Factor 1: Disease management** (7 items)  1.00  3.00  2.43  .46  -.522  -.622  Self-Care Agency Factor 2: Lifestyle management** (4 items)  1.00  3.00  2.51  .49  -.974  .652  Cardiac Self-Efficacy* (7 items)  Skewness Kurtosis 7819 -.414  * Original scale: 1-4; not confident at all; somewhat confident; moderately confident; very confident. ** Original scale: 1-3; no; somewhat; yes.  Relationship between Patient Characteristics and Cardiac Self-Efficacy and Self-Care Agency Bivariate Analysis: CSE The findings associated with cardiac self-efficacy (CSE) scores are summarized in Table 16, 17, 18 and 19. The analyses of the participants' demographics and outcome variables demonstrated that there were no relationships between age, the residence of the participants, and whether they described themselves as being in the work force or not, and their cardiac self-efficacy. There was a significant difference in the CSE scores of the "single" participants and those who had a partner. This was further reflected in a difference in scores between participants living alone and those who reported living in a household of 2 or more, whether with a spouse, a family member or a friend. A review of the associations between co-morbidities and cardiac self-efficacy revealed no relationships between the participants' CSE score and their CCS classification, the co-existence of heart failure, increased creatinine, a concurrent diagnosis of diabetes, peripheral vascular, respiratory or gastrointestinal disease, body mass index score or their smoking history. Yet, there was a significant relationship found between low ejection fraction (< 60%) and lower CSE scores. There were significant relationships noted between the participants' cardiac selfefficacy scores and all items of the STOP-D screening items, except in the anger domain. The participants whose responses were higher than the cut-off scores of for depression, anxiety, stress, and lack of social support scored consistently lower on the assessment of their cardiac self-efficacy.  83 Table 16 Relationships between Demographics and Cardiac Self-Efficacy  Variable  N  Mean  SD  Age: 65 and younger Over 65  61 37  3.4 3.3  0.6 0.5  Sex: Male Female  76 22  3.3 3.4  0.6 0.7  Relationship status: No partner Partnered  31 67  3.06 3.49  0.7 0.6  Size of household: 1 (respondent only) 2 or more  18 80  3.13 3.40  0.7 0.6  Residence: Local Remote  54 44  3.4 3.3  0.6 0.7  Education: High school not completed High school completed  29 69  3.24 3.40  0.7 0.6  Occupation: Working Not working  46 52  3.3 3.4  0.6 0.7  Income: < 24,999 25,000-49,999 > 50,000  25 23 49  3.4 3.4 3.3  0.8 0.6 0.6  t  df  sig.  0.86  96  High .387 -.15  -0.15  96  .878  -0.39  0.29  -3.21  96  .002  -0.70  -0.17  -1.63  96  .105  -0.61  -0.16  0.41  96  .683  -0.21  0.32  -1.09  96  .280  -0.44  0.13  -0.45  96  .655  -0.32  F 0.54  2 94 96  .582  95% CI of the difference  3.1 3.2 3.1  Low .39  0.20  3.8 3.7 3.5  84 Table 17 Relationships between Cardiac Disease Severity and Co-Morbidity and Cardiac Self-Efficacy  Variable  N  Mean  SD  CCS Classification of Angina: 0,1, II, atypical III  73 25  3.4 3.3  0.6 0.8  Heart failure: No Yes  81 17  3.3 3.4  0.7 0.6  Ejection fraction: < 60% > 61%  40 52  3.2 3.4  0.7 0.6  Previous PCI: No. Yes  67 31  3.30 3.46  .64 .66  History of AMI: No Yes  55 43  3.42 3.30  .64 .67  Previous CABG: No Yes  87 11  3.38 3.14  .64 .75  Hypertension: No Yes  30 68  3.50 3.28  .50 .70  Dyslipidemia: No Yes  20 78  3.56 3.29  .53 .67 0.7  t  df  sig.  0.18  96  .860  -0.27  0.33  -0.19  96  .853  -0.38  0.31  -1.90  96  .05  -0.53  0.01  -1.04  96  .301  -.42  .13  1.11  96  .270  -.12  .41  1.13  96  .261  -.18  .65  1.57  96  .121  -.06  .50  1.67  96  .101  -.05  .59  95% CI of the difference High Low  85  Variable  N  Mean SD  Creatinine: < 120 mmol/L > 121 mmol/L  88 10  3.3 3.5  Diabetes: No Yes  72 26  3.4 3.3  0.7 0.7  Smoking history: Never Former Current  25 56 17  3.5 3.3 3.4  0.5 0.7 0.6  0.6  Peripheral vascular disease: No Yes  92 6  3.4 3.1  0.6 0.9  Cerebrovascular disease: No Yes  90 8  3.4 3.0  0.6 0.8  Liver/GI disease: No Yes  87 11  3.3 3.4  0.7 0.6  Previous malignancy: No Yes  93 5  3.38 2.97  .64 .67  CAD-Specific Index: Low risk Intermediate risk High risk  49 36 13  3.4 3.4 2.9  0.6 0.6 0.8  Body mass index: <25 >26  20 77  3.3 3.4  0.7 0.6  df  sig.  95% CI of the difference High  Low  -0.76  96  .448  -0.60  0.30  0.34  96  .729  -0.25  0.35  F 1.20  2 96 98  .305  3.3 3.1 3.1  3.7 3.5 3.7  0.81  96  .420  -0.32  0.78  1.61  96  .111  -0.1  0.85  -0.42  96  .678  -0.50  0.33  1.35  96  .181  -0.19  0.99  F 2.72  2 95 97  .071  3.22 3.22 2.50  3.59 3.62 3.44  -0.74  96  .462  -0.45  0.20  86 Table 18 Relationships between Procedural Characteristics and Cardiac Self-Efficacy  Variable  N  Mean  SD  Severity of CAD on angiography: Single vessel Multivessel  40 58  3.4 3.3  0.6 0.7  PCI procedure: Single vessel Multivessel  74 24  3.3 3.4  0.7 0.5  PCI stents: Single stent procedure Multi-stent procedure  55 42  3.3 3.4  0.7 0.6  Glycoprotein Ilbllla inhibitor infusion: No Yes  70 28  3.4 3.3  0.6 0.7  Method of hemostasis Compression device Closure device  50 48  3.25 3.48  .68 .59  Duration of bedrest: Less than 202 minutes 203 minutes or longer Duration of hospitalization Less than 10 hours 10 hours and more  39 59  3.4 3.3  47 3.46 51 3.25  0.6 0.7 .56 .71  t  df  sig.  95% CI of the difference High Low -0.18 0.35  0.61  96  .541  -0.82  96  .412  -0.43  0.18  -0.57  96  .568  -0.34  0.19  0.53  96  .596  -0.21  0.34  -1.76  96  .081  -.49  .03  0.96  96  .341  -0.14  0.40  1.63  96  .106  -.05  .47  87 Table 19 Relationships between Patients' STOP-Distress and Cardiac Self-Efficacy Scores  Variable  N  Mean  SD  STOP-D Depression Score 0-3 Score 4-9  50 48  3.49 3.20  .57 .70  STOP-D - Anxiety Score 0-3 Score 4-9  46 52  3.59 3.14  .57 .65  STOP-D - Stress Score 0-5 Score 6-9  63 35  3.50 3.08  .59 .67  STOP-D-Anger Score 0-5 Score 6-9  89 9  3.38 3.02  .64 .70  STOP-D - Social support Score 0-4 Score 5-9  84 14  3.46 2.71  .59 .67  t  df  sig.  2.22  96  .029  .03  .54  3.58  96  .001  .20  .70  3.21  96  .002  .59  .67  1.67  96  .104  .64  .70  4.31  96  .000  .40  1.09  95% CI of the difference High Low  Bivariate Analysis: Self-Care Agency - Disease Management There was a trend towards significance (p=.09) found in the relationship between marital status and disease management. The use of a compression device to achieve vascular access hemostasis, and the ensuing shorter duration of hospitalization were significantly associated with higher self-care agency related to disease management. Participants with higher scores in four of thefiveSTOP-Distress measurements (depression, anxiety, stress,  88 and lack of social support) also scored significantly lower in the same dimension than participants with STOP-D scores below the cut-off. The relationships between patients' characteristics and disease management are summarized in Tables 20 to 23. Table 20 Relationships between Demographics and Disease Management Variable  Age: 65 and younger Over 65 Sex: Male Female  N  61 37 76 22  Mean  2.4 2.5 2.4 2.5  SD  0.5 0.4 0.4 0.5  Relationship status: No partner partnered  31 67  2.3 3.5  .54 .40  Size of household: 1 (respondent only) 2 or more  18 80  2.5 2.4  0.5 0.4  Residence: Local Remote  54 44  2.4 2.4  0.5 0.5  Education: High school not completed High school completed  29 69  2.4 2.4  0.5 0.4  Occupation: Working Not working  46 52  2.3 2.5  .45 .46  Income: < 24,999 25,000 - 49,999 > 50,000  25 23 49  2.4 2.5 2.4  .0.5 0.4 0.5  t  df  sig.  95% CI of the difference High  Low  -0.67  96  .507  -0.25  0.13  -.95  96  .34  -.32  .11  -1.71  48  .05  -.40  .03  0.62  96  .536  -0.16  0.31  -0.06  96  .995  -0.19  0.18  -0.32  96  .752  -0.23  -1.07  96  .285  -0.28  0.08  F 0.27  96  .764  2.2 2.3 2.3  2.6 2.7 2.5  0.17  89 Table 21 Relationships between Co-Morbidity and Disease Management  Variable  N  Mean  SD  t  df  sig.  95% CI of the difference  CCS Classification of Angina:  0,1, II, atypical III Heart failure:  No Yes  Ejection fraction:  <60% >61%  Previous PCI:  No Yes  History of AMI:  No Yes  Previous CABG:  No Yes  Hypertension:  No Yes  Dyslipidemia:  No Yes  73 25  2.4 2.4  0.5 0.5  81 17  2.4 2.4  0.5 0.4  81 17  2.4 2.4  0.5 0.4  67 31  2.4 2.5  0.4 0.5  55 43  2.5 2.4  0.5 0.5  87 11  2.4 2.3  0.5 0.4  30 68  2.3 2.5 ,  0.4 0.5  20 78  2.4 2.4  0.4 0.5  88 10  2.4 2.6  0.5 0.4  Creatinine:  < 120 mmol/L > 121 mmol/L  0^4  96  !971  High ^21  Low 022"  0.12  96  .911  -0.23  0.26  0.12  96  .911  -0.23  0.26  -0.77  96  .442  -0.27  0.12  0.56  96  .574  -0.13  0.24  0.92  96  .358  -0.16  0.43  -1.85  96  .068  -0.38  0.01  -0.46  96  .674  -0.28  0.18  -1.34  96  .183  -0.50  0.10  90  Variable  N  Mean  SD  df  sig.  9 5 % CI of the  difference Diabetes:  No Yes  72 26  2.4 2.4  0.4 0.5  25 56 17  2.5 2.4 2.5  0.5 0.5 0.4  Smoking history:  Never Former Current  Peripheral vascular disease:  No Yes  92 6  2.4 2.5  90 8  2.4 2.4  0.5 0.4  87 11  2.4 2.5  0.4 0.4  93 5  2.45 2.11  .46 .28  49 36 13  2.5 2.4 2.4  0.4 0.5 0.5  20 77  2.4 2.5  0.4 0.5  Liver/GI disease:  No Yes  Previous malignancy:  No Yes  CAD-Specific Index:  Low risk Intermediate risk High risk  Body mass index:  <25 >26  Low  -0.22  0.19  2.3 2.2 2.3  2.6 2.5 2.6  -0.18  96  .861  F 0.10  2 95 97  .102  -0.51  96  .612  -0.49  0.29  1.61  96  .111  -0.30  0.38  -0.77  96  .439  -0.40  0.18  1.61  96  .111  -.08  .75  F .290  2 95 97  .749  2.36 2.23 2.06  2.58 2.58 2.71  -0.61  96  .545  -0.30  0.16  0.5 0.5  Cerebrovascular disease:  No Yes  High  91 Table 22 Relationships between Procedural Characteristics and Disease Management  Variable  N  Mean  SD  Severity of CAD on angiography: Single vessel Multivessel  40 58  2.5 2.4  0.5 0.4  PCI procedure: Single vessel Multivessel  74 24  2.5 2.4  0.5 0.4  PCI stents: Single stent procedure Multi-stent procedure  55 42  2.4 2.4  0.5 0.4  Glycoprotein 11 b 111 a inhibitor infusion: No Yes  70 28  2.4 2.4  0.5 0.5  Method of hemostasis Compression device Closure device  50 46  2.35 2.52  .49 .40  Duration of bedrest: Less than 202 minutes 203 minutes or longer  39 59  2.53 2.37  .42 .47  Duration of hospitalization Less than 10 hours 10 hours and more  t  df  046  96  95% CI of the difference High Low .646 -0.14 0.23  0.77  96  .443  -0.13  0.30  0.42  96  .676  -0.14  0.23  -0.17  47 51  2.54 2.33  .40 .48  96  sig.  .866  -0.22  0.19  -1.92  94  .050  -.36  .005  1.70  96  .091  -.03  -.34  2.33  96  .022  .03  .39  92 Table 23 Relationships between STOP-Distress and Disease Management  Variable  STOP-D - Depression Score 0-3 Score 4-9 STOP-D - Anxiety Score 0-3 Score 4-9  N  Mean  SD  50 48  2.53 2.33  0.4 0.5  46 52  2.55 2.33  0.4 0.5  STOP-D - Stress Score 0-5 Score 6-9  63 35  2.56 2.21  0.4 0.5  STOP-D - Anger Score 0-5 Score 6-9  89 9  2.4 2.3  0.5 0.4  STOP-D - Social support Score 0-4 Score 5-9  84 14  2.50 1.99  0.4 0.5  t  df  sig.  95% CI of the difference High Low  2.21  96  .029  0.02  0.38  2.40  96  .018  0.38  0.40  3.54  54  .001  0.15  0.54  0.89  96  .373  -0.17  0.46  4.24  96  .000  0.27  0.76  Bivariate Analysis: Self-Care Agency - Lifestyle Management When measuring self-care agency in the lifestyle management domain, women had significantly higher scores. The only procedural characteristic associated with lower levels of lifestyle management was the provision of multivessel PCI, compared with single vessel procedures. The depression, stress, and lack of social support dimensions of the STOPDistress screening tool were significantly associated with changes in the lifestyle management scores. Tables 24 to 27 summarize the findings.  93 Table 24 Relationships between Demographics and Lifestyle Management  Variable  N  Mean  SD  Age: 65 and younger Over 65  61 37  2.5 2.5  0.5 0.5  Sex: Male Female  76 22  2.5 2.7  0.5 0.3  Relationship status: No partner Partnered  31 67  2.5 2.5  0.4 0.5  Size of household: 1 (respondent only) 2 or more  18 80  2.4 2.5  0.5 0.5  Residence: Local Remote  54 44  2.5 2.5  0.5 0.5  Education: High school not completed High school completed  46 52  2.5 2.5  0.5 0.5  Occupation: Working Not working  46 52  2.5 2.6  0.5 0.5  Income: < 24,999 25,000 - 49,999 > 50,000  25 23 49  2.6 2.4 2.5  0.5 0.5 0.5  df  sig.  95% CI of the difference High Low  -0.05  96  .959  -0.21  0.20  -2.30  96  .024  -0.49  -0.04  -0.82  96  .422  -0.30  0.13  -0.63  96  .530  -0.33  0.17  -0.64  96  .522  -0.26  0.13  -1.02  96  .300  -.30  .10  -1.02  96  .308  -0.30  0.09  F 0.76  2 94 96  .473  2.41 2.20 2.35  2.80 2.69 2.63  94 Table 25 Relationships between Cardiac Disease Severity and Co-Morbidity and Lifestyle Management  Variable  CCS Classification of Angina: 0,1, II, atypical III Heart failure: No Yes  N  73 25 81 17  Mean  2.54 2.42 2.5 2.5  SD  0.5 0.6  81 17  2.42.4  0.5 0.4  Previous PCI: No Yes  67 31  2.47 2.60  .50 .46  History of AMI: No Yes  55 43  2.5 2.5  0.5 0.5  Previous CABG: No Yes  87 11  2.5 2.4  0.5 0.6  Hypertension: No Yes  30 68  2.4 2.5  0.6 0.5  20 78  2.64 2.48  df  sig.  95% CI of the difference High  Low  1.07  96  .287  -.10  .35  0.50  96  .616  -0.19  0.32  0.50  96  .616  -0.19  0.32  -1.20  96  .234  -.37  .08  0.91  96  .384  -0.11  0.29  0.89  96  .375  -0.17  0.45  -0.92  96  .359  -0.31  0.11  1.31  96  .193  -.08  .40  .46 .57  Ejection fraction: < 60% >61%  Dyslipidemia: No Yes  t  .31 .52  95  Variable  N  Mean  SD  Creatinine: < 120 mmol/L > 121 mmol/L  88 10  2.5 2.6  0.5 0.3  Diabetes: No Yes  72 26  2.48 2.60  .52 .37  Smoking history: Never Former Current  25 56 17  2.6 2.5 2.5  0.4 0.5 0.5  Peripheral vascular disease: No Yes  92 6  2.53 2.21  0.5 0.8  Cerebrovascular disease: No Yes  90 8  2.5 2.5  0.5 0.3  Liver/GI disease: No Yes  87 11  2.48 2.77  0.5 0.3  Previous malignancy: No Yes  93 5  2.53 2.20  0.5 0.5  CAD-Specific Index: Low risk Intermediate risk High risk  49 36 13  2.55 2.44 2.58  0.4 0.6 0.4  Body mass index: <25 >26  20 77  t  0.5 0.5  sig.  9 5 % CI of the difference High  Low  -0.74  96  .435  -0.45  0.20  -1.05  96  .297  -.34  .10  F 0.56  2 95 97  .571 2.43 2.33 2.23  2.76 2.61 2.74  1.57  96  .118  -.08  .73  -0.13  96  .900  -0.38'  0.34  -1.91  96  .058  -.60  .01  1.47  96  .146  -.12  .77  .647  2 95 97  .526 2.42 2.25 2.31  2.67 2.63 2.84  95  .175  -.41  .08  -1.37 2.37 2.54  df  96 Table 26 Relationships between Procedural Characteristics and Lifestyle Management  Variable  N  Mean  SD  Severity of CAD on angiography: Single vessel Multivessel  40 58  2.5 2.5  0.5 0.5  PCI procedure: Single vessel Multivessel  74 24  2.57 2.33  .46 .53  PCI stents: Single stent procedure Multi-stent procedure Glycoprotein Ilbllla inhibitor infusion: No Yes Method of hemostasis Compression device Closure device Duration of bedrest: Less than 202 minutes 203 minutes or longer Duration of hospitalization Less than 10 hours 10 hours and more  55 42  70 28 50 46 39 59  47 51  2.56 2.43  2.5 2.5 2.44 2.60 2.60 2.45  2.59 2.44  .47 .50  t  df  sig.  0A6  96  95% CI of the difference High Low M8 -0.15 0.25  2.08  96  .040  .01  .46  1.36  95  .178  -.06  .33  -0.33  96  .745  -0.25  0.18  -1.64  94  .103  -.35  .03  1.42  96  .158  -.06  .34  1.47  96  .146  -.05  .33  0.5 0.5 .50 .44 .38 .54  .40 .55  97 Table 27 Relationships between STOP-Distress and Lifestyle Management  Variable  STOP-D - Depression Score 0-3 Score 4-9  N  Mean  SD  50 48  2.63 2.40  0.4 .5  STOP-D - Anxiety Score 0-3 Score 4-9  46 52  2.61 2.42  STOP-D - Stress Score 0-5 Score 6-9  63 35  2.60 2.34  0.4 0.6  STOP-D - Anger Score 0-5 Score 6-9  89 9  2.5 2.4  0.5 0.6  STOP-D - Social support Score 0-4 Score 5-9  84 14  2.60 1.93  0.4 0.6  0.4 0.5  t  df  sig.  2.44  96  .017  0.04  0.43  1.90  96  .060  -0.01  0.38  2.34  52  .023  0.04  0.48  0.42  96  .674  -0.27  -0.42  3.99  15  .001  0.32  1.04  95% CI of the difference High Low  Multivariate Analysis A multivariate regression analysis was performed to determine the explanatory contribution of the identified factors associated with the study's outcome variables. Only the variables that were significant at p <20 in the bivariate analysis were included in the initial statistical models. For theoretical reasons and given the potential confounding effects highlighted in the literature review, gender was included in all models. Initially, all the explanatory variables were included in the model and the model's significance levels,  98 trimming process were retained. Summaries of the multiple regression modeling findings are presented in Tables 28 to 33. The significant variables associated with cardiac self-efficacy were (1) ejection fraction, (2) STOP-D anxiety score, (3) STOP-D lack of social support score, and (4) marital status. This model accounted for 34% of the variation in results. When predicting self-care agency related to disease management, the significant variables were (1) the duration of hospitalization, (2) the STOP-D score for stress and (3) for lack of social support. With the inclusion of sex, this model accounted for 24% of the variation of data. Lastly, self-care agency related to lifestyle management was significantly associated with (1) whether patients had a single vs. multivessel procedure, and (2) the STOP-D score for lack of social support. This model predicted 29.5% of variation in responses.  Table 28 Linear Regression Model of Cardiac Self-Efficacy on Predictor Variables with p<.20 in Bivariate Analysis Model  Stress  Dep.  2  Anger  3  Hosp.  4  Hem.  5  CAD Index  Dysli.  7  Anx."  EF  y  6  1 P B P  2 P B P  3 P B P  4 P B P  5 P B P  .925* -.02 -.01  Mar. Stat.  Soc. Sup.  10  Gender 11  12  .795 .04 .03  .449 -.17 -.07  .381 -.13 -.10  .395 .13 .10  .288 -.04 -.11  .386 -.13 -.08  .138 -.25 -.19  .010 .32 .25  .038 .28 .20  .002 -.63 -.34  .414 -.12 -.08  .807 .04 .03  .443 -.17 -.07  .375 -.13 -.10  .379 .13 .10  .250 -.04 -.11  .386 -.13 -.08  .078 -.26 -.20  .009 .32 .24  .036 .28 .20  .001 -.63 -.34  .410 -.18 -.08  .446 -.16 -.07  .378 -.13 -.10 .439 -.11 -.09  .357 .13 .10  .247 -.-4 -.11  .357 -.13 -.08  .057 -.24 -.18  .009 .32 .24  .033 .28 .20  .001 -.62 -.34  .388 -.12 -.08  .345 .14 .11  .253 -.04 -.11  .379 -.13 -.08  .028 -.27 -.20  .010 .31 .24  .037 .27 .20  .000 -.65 -.35  .405 -.18 -.08  .080 .20 .16  .295 -.04 -.10  .365 -.13 -.08  .024 -.27 -.21  .011 .31 .24  .034 .27 .20  .000 -.65 -.35  .415 -.11 -.07  R Square .39  .39  .39  .39  .38  o o  Model Stress  1  Dep.  2  Anger  5  Hosp.  4  Hem.  5  CAD Dysli. Index  7  Anx.  8  EF  9  6  Mar. Stat.  10  Soc. Sup.  Gender 11  12  R Square  6  P B P  7 P B P  .078 .20 .16  .209 -.04 -.11  .02 -.28 -.21  .073 .21 .16  .018 -.29 -.22  .011 .30 .23 .010 .31 .24  .037 .27 .20 .015 .31 .22  .000 -.67 -.36 .000 -.67 -.36  .393 -.12 -.08 .359 -.13 -.08  §**  .011 -.31 -.24  P B P  *Values in bold indicate the variable with least significance in the given model. This variable is eliminated in the subsequent model. **The final model includes variables with p<.05. STOP-D Stress item Stop-D Depression item STOP-D Anger item Duration of hospitalization  .016 .29 .22  .011 .32 .23  .000 -.66 -.36  .446 -.11 -.07  Method of hemostasis CAD-Specific Index of Co-morbidity Dyslipidemia STOP-D Anxiety item Ejection fraction Marital status STOP-D Lack of Social Support item Gender is included in all models for theoretical purposes  5 6  7 8  1  9  2  10  3  11  4  12  .38  .36  .34  Table 29 Model Summary of Predictors of Cardiac Self-Efficacy Model Summary R Square .34  (Constant) Gender STOP-D Anxiety item STOP-D Lack of Social Support item Ejection fraction Marital status  ANOVA  Sum of df Mean Square F Sig. Adjusted Std. Error of Estimate R Square Squares .544 Regression 13.01 5 2.60 8.81 .000 .30 Residual 25.41 86 .30 Total 38.42 91 Coefficients b  Std. Error  3.71 -.11 -.31 -.66 .29 .32  .408 .139 .118 .173 .117 .124  Beta (P)  t  Sig.  -.07 -.24 -.36 .22 .23  9.09 -0.77 -2.60 -3.80 2.46 2.60  .000 .446 .011 .000 .016 .011  CN O  Table 30 Linear Regression Model of Self-Care Agency - Disease Management on Predictor Variables with p<.20 in Bivariate Analysis Model  CAD Index  Anxiety  2  Dep/  Hemos.  4  Bedrest  5  Hosp.  6  Stress  7  1  1 P B P  2 P B P  3 P B P  4 P B P  .824* -.01 -.23  Mar. Stat.  8  .807 .03 .03 .795 .03 .03  .722 -.04 -.04  .678 -.06 -.07  .348 -.14 -.15  .186 -.14 -.16  .165 -.19 -.20  .089 .17 .17  Soc. Supp.  Gender" 1  9  .012 -.36 -.27  .830 .02 .02  .738 -.04 -.04  .690 -.06 -.07  .352 -.14 -.15  .190 -.14 -.15  .130 -.20 -.21  .069 .18 .18  .011 -.36 -.27  .832 .02 .02  .790 -.03 -.03  .689 -.06 -.07  .348 -.14 -.15  .191 -.14 -.15  .112 -.18 -.20  .070 .17 .18  .010 -.36 -.28  .830 .02 .02  .697 -.06 -.06  .365 -.13 -.14  .184 -.14 -.16  .045 -.20 -.21  .070 .17 .17  .008 -.37 .28  .790 .03 .03  R Square .26  .26  .26  .26  CO  o  Model  CAD Index  Anxiety  2  Dep.  3  Hemos.  4  Bedrest  5  Hosp?  Stress  7  1  5  P B P  Soc^ Supp.  Gender  8  .283 -.10 -.11  9  .040 -.20 -.21  .061 .17 .17  .006 -.37 -.28  .809 .02 .02  .055 -.16 -.18  .032 -.21 -.22  .081 .16 .16  .007 -.36 -.28  .737 .03 .03  P  .048 -.17 -.18  P B P  *Values in bold indicate the variable with least significance in the given model. This variable is eliminated in the subsequent model. **The final model includes variables with p<.05. 'CAD-Specific Index of Co-morbidity STOP-D Anxiety item Stop-D Depression item  10  .226 -.11 -.12  6 P B  2  Mar. Stat.  .043 -.20 -.21  .004 -.39 -.30  .835 .02 .02  R Square .27  .26  .24  Method of hemostasis Duration of bedrest Duration of hospitalization STOP-D Stress item Marital status STOP-D Lack of Social Support item Gender is included in all models for theoretical purposes  4  5 6  7  8 9  10  Table 31 M o d e l S u m m a r y of Predictors of S e l f - C a r e Agency - Disease Management  Model Summary R Square  .24  Adjusted R Square  .21  ANOVA Std. E r r o r of Estimate  .407  Regression Residual Total  S u m of Squares  4.83 15.37 20.20  df  M e a n Square  4 93 97  1.21 .17  F  Sig.  7.31 .000  Coefficients  (Constant) Gender STOP-D Stress item STOP-D Lack of Social Support item Duration of hospitalization  b  Std. E r r o r  3.37 .02 -.20 -.39 -.17  .243 .100 .096 .131 .083  Beta (p)  t  Sig.  .02 -.21 -.30 -.18  13.86 0.21 -2.06 -2.96 -2.01  .000 .835 .043 .004 .048  IT)  o  Table 32 Linear Regression Model of Self-Care Agency - Lifestyle Management on Predictor Variables with p<.20 in Bivariate Analysis Model  BMI  1  Anx.  2  Hem.  J  Stress  4  CAD Hosp. Index  6  5  1 P B P  2 P B P  .985* .000 -.01  PCI Proc.  Bed rest  7  8  Dyslip Dep.  10  Stent  11  9  Soc. Gender 13 Sunp.  .889 .02 .02  .846 .03 .03  .714 .05 .05  .673 -.01 -.04  .612 -.06 -.06  .421 -.11 -.10  .417 -.12 -.13  .379 -.10 -.09  .322 -.12 -.13  .318 -.12 -.12  .000 -.56 -.41  .256 .13 .11  .883 .00 -.01  .850 .03 .03  .618 .06 .06  .662 -.01 -.04  .614 -.06 -.06  .424 -.11 -.10  .408 -.13 -.13  .382 -.10 -.09  .315 -.11 -.12  .312 -.18 -.12  .000 -.57 -.41  .252 .13 .11  .849 .03 .03  .615 .06 .06  .660 -.01 -.04  .612 -.06 -.06  .421 -.11 -.10  .405 -.13 -.13  .376 -.10 -.09  .310 -.11 -.12  .309 -.12 -.12  .000 -.57 -.41  .244 .13 .11  R .31  .31  .31 P B P  4 P B P  .34 .695 .05 .05  .553 -.02 -.06  .323 -.10 -.10  .166 -.18 -.16  .303 -.11 -.11  .340 -.11 -.09  .355 -.10 -.11  .488 -.08 -.08  .000 -.60 -.44  .230 .13 .11  MD O  Model BMI  1  Anx.  2  Hem.  3  Stress CAD Hosp. Index 4  6  5  PCI Proc.  7  Bed rest  Dyslip Dep." Stent 1  11  8  Soc. Gender 13 SuDp.  5  P B P  6 P B P  7 P B P  8 P B P  9 P B P  .613 -.01 -.05  .332 -.10 -.10  .164 -.18 -.16  .332 -.10 -.10  .323 -.11 -.09  .397 -.08 -.08  .492 -.08 -.08  .000 -.59 -.43  .216 .13 .11  R  2  .34  .34 .351 -.09 -.10  .167 -.18 -.16  .327 -.10 -.10  .265 -.12 -.10  .392 -.08 -.08  .288 -.10 -.11  .021 -.24 -.21  .359 -.09 -.09  .241 -.13 -.10  .378 -.08 -.08  .239 -.12 -.12  .020 -.24 -.21  .454 -.07 -.07  .275 -.12 -.10  .488 -.08 -.08  .000 -.59 -.42  .224 .13 .11  .000 -.58 -.42  .186 .14 .12  .000 -.62 -.44  .139 .15 .313  .34  .33  .33 .080 -.15 -.15  .015 -.25 -.22  .247 -.12 -.10  .000 -.61 -.44  .119 .16 .14  o  Model BMI  1  Anx.  2  Hem.  J  Stress CAD Hosp. Index 4  6  5  10 P B  .081 -.15 -.15  P  PCI Proc.  7  Bed rest  Dyslip Dep.  10  Stent  11  8  .021 -.23 -.21  Soc. Gender 13 Sunp. .000 -.63 -.45  .131 .15 .13  1 j **  .32  .30 .043 -.20 -.18  P B P  *Values in bold indicate the variable with least significance in the given model. This variable is eliminated in the next model.  R  **The final model includes variables with p<.05. 'Body mass index STOP-D Anxiety item Method of hemostasis STOP-D Stress item 2 3  4  CAD-Specific Index of Co-morbidity Duration of hospitalization PCI Procedure Duration of bedrest Dylipidemia 5  6 7  8  9  .000 -.64 -.46  .102 .17 .15  Stop-D Depression item "Number of stents STOP-D social support Gender is included in all models for theoretical purposes lu  12  13  Table 33 Model Summary of Predictors of Self-Care Agency - Lifestyle Management  Model Summary  ANOVA  R Square  Adjusted R Square  Std. Error of Estimate  .30  .27  .416  Regression Residual Total  Sum of Squares  df  Mean Square  6.82 16.30 23.12  3 94 97  2.27 .17  F  Sig.  13.11 .000  Coefficients  (Constant) Gender STOP-D Lack of Social Support item PCI Procedure (single vs. multi-vessel procedure)  b  Std. Error  Beta (p)  t  Sig.  3.28 .17 -.64 -.20  .241 .102 .122 .098  .15 -.46 -.18  13.62 1.65 -5.25 -2.05  .000 .102 .000 .043  109 Summary  In this study, data was collected on 98 participants, 78% of whom were men with an average age of 63 years, who were discharged the evening of their percutaneous coronary intervention. Following the initial chart extraction, telephone interviews took part 3.4 days following discharge. An equal proportion of participants lived in the Greater Vancouver area and in more remote communities, most having completed high school, with as many individuals having access to a household total income of more and less than $50,000.00. Most participants had a history of hypertension, dyslipidemia and symptomatic coronary artery disease, with a quarter being additionally burdened with diabetes. One third of participants had previous experience with PCI, and 11% had previous surgical revascularization. The average body mass index was 28, above the high normal of 25. On angiography, 60% of participants had multi-vessel disease but most had a single target vessel PCI, with equal numbers achieving hemostasis with a compression or closure device. Adherence to follow-up instructions was high, with 87% of patients taking appropriate anti-platelet therapy, and most removing their dressing as instructed. Yet, a majority of participants did not meet recovery exercise targets, but returned to work within a week of the procedure. A third of participants reported experiencing chest pain or other ischemic symptoms within 2 to 5 days following discharge with most people taking no action, and 60% had a hematoma at the vascular access site. Nearly half of participants claimed to not understand at all or very well the underlying causes of their heart disease, with most not knowing what changes may be required to modify their risk for heart disease. In addition, 40% of participants claimed to no longer have heart disease following their PCI procedure.  110 In a multiple regression analysis of the relationship between variables and cardiac self-efficacy, and self-care agency related to disease and lifestyle management, lack of social support emerged as a consistently significant variable in all three models. Together with limited other significant variables, the models explained between 24 and 34% of the variation in responses.  Ill  CHAPTER 5: DISCUSSION This final chapter summarizes the key findings of this study. I describe the health behaviours of the participants in the days following discharge from percutaneous coronary intervention (PCI), and the factors associated with cardiac self-efficacy and self-care agency and contrast and compare key findings with the literature. An overview of the limitations of this study and a discussion of implications that these findings may have for the delivery of care of elective PCI patients conclude this chapter. Self-Care Recovery Behaviour To survey the participants' adherence to post-PCI discharge instructions (Going Home After Percutaneous Coronary Intervention, Vancouver Coastal Health, 2006), questions were posed of the participants to determine their self-care behaviour in relation to their immediate recovery. The questions related to discharge disposition, self-care, management of complications, patients' longer term intentions, and understanding of chronic disease management. This study found that the participants had a high degree of adherence to specific instructions. Nearly all of the patients (92%) were accompanied at the time of discharge, stayed overnight close to the hospital if their residence was outside of the Greater Vancouver area (94%), removed their dressing and showered within 2 days of their procedure (92%), and were taking appropriate anti-platelet medication (97%). There was more variation in adherence to their exercise instruction with 52% of the participants reporting activity levels below the recommended target, including one third of the sample limiting their walking to their homes only, and 20% exceeding the recommendations. Although most of the employed participants planned on returning to work within a week of their procedure (53%), nearly  112 20% did not know when they would resume their normal working activity. This finding was further reflected in the responses to the cardiac self-efficacy (CSE) and self-care agency (SCA) items focusing on exercise, where nearly 60% were uncertain about their understanding of how much exercise to do following PCI, and 35% were not at all or only somewhat confident about knowing how much physical activity is appropriate in the recovery phase. The rate of post-PCI complications identified in this study was at the higher end of the wide range reported in the literature (Dumont et al., 2006; Konstance et al., 2004; O'Neill, 2006) with 60% of participants stating that they had a hematoma at the access site, describing it as medium to large in size (70%), but most believing it was getting better or staying the same (85%) and not feeling worried about it (77%). The incidence of postprocedure chest pain confirmed previous research findings (Kimble & Kingle, 1998; Nones Cronin et al., 2000; Skaggs et al., 1999; Wong et al., 2006), with 31% of this study's participants self-reporting experiencing ischemic symptoms, and the great majority (80%) taking no action in response to these symptoms. Angina frequency has been identified as the most important prognostic indicator of quality of life following PCI (Spertus et al., 2004), and is associated with a higher incidence of depression, stress, and anxiety (Nones Cronin et al., 2000). Odell et al. (2006) framed the threat of angina and not knowing the natural progression of heart disease within the greater context of "living with uncertainty". Because 31% of this study's participants did not know what symptoms to expect, and a further 34% only somewhat knew, one can speculate that the occurrence of chest pain in the days following PCI may be a source of uncertainty, psychoemotional distress, and ultimately poorer long term quality of life.  113 In this study, 10% of the patients presented at a hospital emergency department within 24 hours of discharge for management of vascular access or ischemic complications. Data were not collected regarding the exact nature of the visits and the treatment received, and no questions were asked about whether other participants had contemplated seeking emergency medical attention. A closer examination of the data revealed that all 10 participants who sought follow-up at an emergency department did not live alone, with 7 of them being married or in common-law relationships, 2 widowed and 1 single. Additionally, all except one participant (single) scored low (0 or 1 out of 9) on the lack of social support item of the STOP-D screening tool. Information pertaining to re-admission following sameday discharge PCI has not been reported elsewhere. Thus, this finding adds to our understanding of self-care behaviour following PCI, and may help guide clinical programs. Patients' capacity to recognize their personal risk factors for heart disease is a pivotal element of behavioural change and long term risk factor modification (Deaton & Namasivayam, 2004). In this study, 43% of the participants stated that they did not understand the causes of their heart disease at all or very well, and 50% did not know what lifestyle changes were needed to prevent their heart disease from worsening. Consistent with previous research (Campbell et al., 2005; Steptoe et al., 1999), 38% of the participants believed that they no longer had heart disease following successful PCI. Previous researchers (Higgins et al, 2001; Nones Cronin et al., 2000) have speculated that the erroneous perception that heart disease is cured through PCI may be related to the short duration of hospitalization, the improved functional status, and the low levels of in-hospital referrals for cardiac rehabilitation. Only 14% of the participants in this study recalled being spoken to about their causes for heart disease, with only one quarter indicating that they planned to  114 attend cardiac rehabilitation. Existing evidence supports personalized and intensive risk factor counseling and modification following PCI (Dendale et al, 2004; Lisspers et al., 2005; Yu et al., 2004), and the findings suggest that program changes may be required. In their surveys of patients' learning needs, Brezynskie et al. (1998) and Gentz (2000) identified that "learning how to change the course of my heart disease" is a priority learning need for PCI patients. Despite this primary concern, the teaching focus post-PCI continues to be primarily on the period of hospitalization and the discharge process (Kattainen et al., 2004), with a perceived lack of prescription for risk factor modification (Nones Cronin et al., 2000). The findings of this study support the existing evidence and researchers who have called for a better connection between clinical guidelines and existing practice, and an improved assimilation of long term behaviour modification in the PCI trajectory (Scholte op Reimer et al.,2002; Tooth et al., 1997). In addition to the need for risk factor modification, researchers have also identified information related to the procedure as a second priority learning need for PCI patients (Brezynskie et al., 1998; Gentz, 2000; Skaggs et al., 1999). In this study, when asked whether they understood the results of their PCI, 71% answered positively, whereas only 8% said "no" and 21% responded "somewhat". Patients are discharged with a computer-generated diagram of their native disease and post-PCI results. The review of this information during hospitalization with a health care professional, and upon returning home may help patients meet this learning need. In summary, the results of this study point to the high degree of adherence to discharge guidelines, and short-term complication rates consistent with existing evidence. In this study, the decreased length of stay associated with same-day discharge resulted in  115 findings consistent with previous research. The study findings suggest that patients undergoing same-day discharge PCI follow guidelines and are mostly able to care for themselves, understand the results of their procedure, but do not learn how to how to modify their heart disease risk profile while in hospital. Nevertheless, it is disturbing to note the incidence of re-admission to an emergency department, exclusively in patients with a partner. Further research is needed to focus specifically on the behaviour of patients who live alone and suffer a lack of social support, as they may not be inclined to seek help. Cardiac Self-Efficacy and Self-Care Agency Related to Illness and Lifestyle Management Demographic, Co-Morbidity and Procedural Characteristics This study originated from the initiation of same-day discharge at St. Paul's Hospital, in 2002, based on the medical triage of "carefully selected patients" (Khatri et al., 2002) and the subsequent practice of standardizing same-day discharge to all medically stable elective patients, to determine factors associated with cardiac self-efficacy (CSE) and self-care agency (SCA) outcomes. A comparison of the study sample reported by Khatri et al. (2002), who studied the safety of same day discharge at St. Paul's Hospital, and this study's sample showed similarities in the participants' ages (65 vs. 63 years in the present study), gender (83% vs. 78% men), and the proportion living with a spouse or relative (88% vs. 82%). This study's sample tended to have more co-morbidities than Khatri et al.'s sample. In the present study, there was a higher prevalence of heart failure (17% vs. 6%), diabetes (27% vs. 18%), and hypertension (69% vs. 54%). Additionally, there was a higher percentage of patients who currently or formerly smoked (74% vs. 63%), with a history of AMI (44% vs. 33%), previous PCI (32% vs. 21%), multivessel procedure (24% vs. 18%). The rise in co-morbidities in the  116 elective PCI population mirrors recently reported increases in the prevalence of diabetes, hypertension, and metabolic syndrome (Freeman et al., 2006), and confirms the increasing complexity and burden of chronic disease of elective PCI patients. There was also evidence that the procedures tended to be more complicated in this study compared with Khatri et al.'s with higher use of glycoprotein Ilbllla inhibitor (29% vs. 18%), and closure devices (47% vs. 20%). The duration of observation, on average, was lower in the initial study (8 hours ± 2 hours) than in the present study (10 hours ±1.5 hours). It is interesting to note that the proportion of women undergoing elective PCI has not significantly increased over the course of 5 years, in spite of increased evidence supporting the devastating effects of CAD on women (Heart & Stroke Foundation of Canada, 2003). This study also found a higher rate of repeat-PCI procedures and use of closure devices in the present study. This is not surprising as the safety and efficacy of repeat percutaneous revascularization and the use of closure devices have been established (Qureshi et al., 2003). The main purpose of this study was to extend the analysis beyond the description of the elective PCI sample and their self-care behaviour to focus on their level of cardiac selfefficacy and self-care agency. Additionally, the study aimed at identifying patient and procedural factors associated with these outcomes. The purpose of the following discussion is to describe how the findings relate to factors associated with cardiac self-efficacy and selfcare agency compare with the evidence uncovered in the literature review. In the literature review, prediction models of major adverse cardiac events in the context of PCI consistently included recent myocardial infarction, heart failure and low ejection fraction, renal dysfunction, multivessel disease, age greater than 65 years, and female gender (Qureshi et al., 2003; Siotia & Gunn, 2006; Wu et al., 2006). Other  117 researchers have measured functional status following PCI. They have identified duration of CAD, severity of chest pain and pre-PCI functional status, as well as age, gender, educational status, prior myocardial infarction and number of PCI target lesions as predictors of activities of daily living, social interaction, work performance, quality of interaction, and mental health (Fitzgerald et al., 1996; Tooth et al., 1997). In the present study, CSE and SCA were not associated with age, residence, and income. It had been hypothesized that increased age, the need to travel great distances to access medical care, and possibly, lesser socio-economic resources might be associated with poorer outcomes. Gender was not significantly associated with CSE and self-care agency related to disease management; however women had significantly higher scores in SCA related to lifestyle management, indicating a higher level of knowledge related understanding medication and exercise prescription and recommendations. Although women may have higher levels of knowledge about their lifestyle management, the literature strongly supports the evidence that they remain at higher risk during the recovery phase. This suggests that patient education may be a necessary but not a sufficient determinant of outcomes. Female gender is consistently attributed to more negative outcomes following PCI, such as on-going delay in seeking medical attention (Dempsey et al., 1995), longer recovery, anxiety and depression (Plach & Stevens, 2001), and post-procedure mortality (Wu et al., 2004). There was no significant relationship found between the participants' CES and the dual dimensions of SCA, and their level of education, income, present occupation, and residence. This finding related to the lack of significance of formal education is consistent with previous research: except for one study by Fitzgerald et al. (1996) which identified educational status as a predictor of functional status after PCI, there is no evidence that  118 supports education as a predictor of outcome. The self-reporting of total household income did not include the value of assets, which would amount to a significant percentage in this older sample. Nevertheless, there was no relationship found between income and the measured outcomes, including for the 25.8% of participants who reported their total annual income as less that $25,000 per year. In the introduction to the study, it was hypothesized that the distance between participants' community and the PCI centre, as well as their local access to specialized healthcare, might be a factor in patients' outcomes. This was not confirmed by the study. The need to travel to a PCI centre from remote areas of the BC and the Yukon was not associated with differences in CSE and SCA. The only significant finding related to the relationship between co-morbidity and the variables of interest was the higher CSE score of participants with normal left ventricular ejection fraction, compared with participants with impaired left ventricular function. This finding was not confirmed when the bivariate analysis measured the relationship between a concomitant diagnosis of heart failure and CSE. Ejection fraction remained significant in the multiple regression trimming procedure. It is an unexpected finding that the well-established practice of self-care education associated with the management of heart failure did not translate into higher levels of self-care agency in the setting of recovery from PCI. The lack of association between severity of CAD as evidenced by the angiographic diagnosis of multivessel disease, and CSE and SCA outcomes may be a reflection of patients' lack of cognisance of the coronary artery involvement of their disease, since this is not always correlated with symptom severity (Tavano et al., 2007). In contrast, patients undergoing a single vessel procedure had significantly lower lifestyle management SCA than those who had a multivessel PCI. This variable maintained its significance in the predictor modeling  119 analysis. Patients are usually aware of the coronary involvement of their procedure. In multivessel procedures, patients may have more uncertainty about following medication and exercise regimen, due to the perceived acuity of their condition and procedure. There were no significant associations identified between CSE and SCA, and a history of previous PCI, myocardial infarction or coronary artery bypass surgery. It is interesting to note that previous cardiac events were not associated with changes in outcomes. This is consistent with research by Lenzen et al. (2002) who studied patients undergoing PCI for the first time and as a repeat procedure. They found no difference in the level of anxiety between the groups, and concluded that previous experience with PCI did not mitigate the associated fear and uncertainty related to the return of symptoms and long term outcomes. Unlike other published predictor models, additional co-morbidities, measured separately or combined in the CAD-Specific Index did not play a significant role in patients' CSE and SCA. Although stable CAD patients with an additional diagnosis of diabetes, renal insufficiency, chronic obstructive pulmonary disease, and peripheral vascular disease are known to have significantly worse morbidity and mortality (Sachdev et al., 2004), the 36.7% intermediate risk and 13.3% high risk participants in the study sample did not have significantly different levels of CSE and SCA. Likewise, low risk participants did not differ from the other groups. A possible explanation for this finding might be the lack of cognisance of the burden and implications of co-morbidities: the most common comorbidities identified in the study sample, hypertension (69.4%), hyperlipidemia (79.6%), and diabetes (26.5%) are often not associated with severe symptomology. There were no procedural characteristics associated with differences in CSE scores. The use of a closure device was significantly with higher SCA related to illness management  120 (p=.05), which was further reflected in a significant difference in the same domain compared with the duration of hospitalization. Duration of hospitalization remained significant in the multiple regression modelling of predictors of disease management. The selection of the method of hemostasis is primarily based on the timing of the procedure (hemostasis by compression device if PCI completed prior to 11:00 am, and use of closure device after 11:00), but is determined on the basis of medical or nursing clinical input, depending on the anticipated management of patients. This unanticipated finding merits further study to confirm its predictive value to better understand the phenomenon at play. Participants undergoing a single vessel procedure had significantly higher SCA related to lifestyle management compared with those who had multivessel PCI targets. Although this finding was not confirmed in the analysis of the relationship between lifestyle management and severity of CAD on angiography or the number of stents implanted, patients would likely associate undergoing a single vessel procedure as less critical than multivessel procedure. This, in turn, could account for patients having higher levels of knowledge about the lifestyle management of their illness. There were no significant relationships identified between the use of glycoprotein Ilbllla inhibitors associated with more complex procedures (Leeper, 2004; Wu et al., 2006), as this variable, much like the severity of CAD on angiography and number of stents implanted, are more likely to not be perceived by patients as markers of more severe disease. Social Support and Psychoemotional Health The literature review failed to identify any research related to the impact of marital status and social support in the context of PCI, and only identified the role of this factor in the general cardiac literature (Deaton & Namasivayam, 2004). Spurred by this gap, this study  121 recorded marital status and asked respondents to identify the number of individuals living in their household. For statistical and conceptual reasons, this information was further treated in a binary manner, dividing the responses between "single" and "in relationship" for marital status, and "living alone" (household of 1) and "not living alone" (household of 2 or more) for household size. The exploratory bivariate analysis revealed a significant relationship between marital status and CSE and the SCA dimension of disease management. Although this finding was not reflected in the analysis of the association with the size of household, higher scores indicating more severe distress on the STOP-D item related to lacking social support were significantly associated with lower scores on measures of CSE, and SCA related to illness and disease management. Together, these results present consistent evidence that not having a partner and perceiving a lack of social support places individuals at higher risk in the PCI recovery period. In the multiple regression analyses, lack of social support emerged as a significant predictor in participants' cardiac self-efficacy and in both dimensions of self-care agency. In the case of CSE and disease management, this finding was also reflected in the significance of marital status. This consistent finding related to the poorer outcomes associated with lacking social support, living in isolation, and not having a partner, is an important contribution of this study to existing evidence. Absent from this analysis is an understanding of how the relationships between social support, and CSE and SCA are potentially associated with other explanatory variables, such as age, gender, income or concurrent chronic diseases. In addition, this study'sfindingwould be complemented by further study of the role, responsibilities and associated burden of caregivers, because they appear to play an important role in the recovery from PCI.  122 Evidence uncovered in the literature review called for research related to the cooccurrence of depression and CAD to address the causes and mechanisms of increased morbidity and mortality of individuals with this dual diagnosis (Dunn et al., 2006; FrasureSmith et al., 2000). In an attempt to integrate this new evidence into the present study and to initiate a discussion relevant to the clinical care of PCI patients, the participants were screened over the telephone using the STOP-Distress instrument for the rapid screening of depression, anxiety, stress, anger and low social support. Almost one half (49%) of the participants scored high for depression, whereas 53% scored high for anxiety, and 36% for stress. The bivariate analysis uncovered a consistently high degree of significance between lower scores on the measures of CSE and the two dimensions of SCA, and higher (more severe) scores on the items of the STOP-D instrument. Depression was significantly associated with CSE, disease management and illness management. A similar conclusion applies to anxiety, and stress. In spite of the limitations of the instrument, these consistent findings raise the concern that the evidence uncovered by previous research that symptoms of depression are predictive of negative outcomes following hospitalization for coronary heart disease and PCI. Researchers have suggested and studied the use of a pathway or decisionmaking instrument to assist clinicians in identifying and referring patients at higher risk for poorer outcomes related to lack of adequate social support in the recovery period (Dunn et al., 2006; Frasure-Smith, 1993). The role of psychoemotional distress in the recovery of PCI patients was confirmed in the multiple regression analysis, where stress emerged as a significant predictor of disease management, and anxiety was significantly associated with cardiac self-efficacy.  123 Presently, there is no program to support systematic depression screening, referral, or a plan of care in the clinical setting. We also lack evidence related to how to best design and implement interventions to address this potentially pressing issue. It is essential to identify the relationship between psychoemotional distress and other factors, such as social support as discussed above, but also gender, age, and the burden of multiple chronic diseases, given the existing evidence of the potential impact of these variables. Given the body of evidence that supports the recognition of depression as an additional risk factor for heart disease, it is likely that these findings may be replicated and validated in further research. Predictive Model The multiple regression analyses used to trim the predictive models succeeded in identifying significant variables associated with cardiac self-efficacy and self-care agency. The CSE model, with the inclusion social support, anxiety, marital status, and ejection fraction, while maintaining sex as a forced variable, accounted for over one third (34.5%) of variation in responses. This finding has significant clinical implications to support the care of elective PCI patients. Although the models developed for the two dimensions of self-care agency had lesser predictive power, they clearly identified significant predictors of outcomes. The consistent importance of social support is clearly an important predictor of outcome for this patient population. Methods and Limitations of the Study The results of this study must be considered within the context of the research method used and its limitations. There are four main limitations associated with this study: sample size, instrumentation, analysis, and study protocol. Each are discussed in turn.  124 The original intention to recruit between 120 and 150 participants was hampered by the clinical challenges encountered at the study site. The predictive models alone initially had between 13 and 17 explanatory variables, which was reduced through a trimming procedure to the two to four most significant variables. Using the method proposed by Tabachnick and Fidell (1996), a sample size of 186 would have been required to conduct a study with 17 explanatory variables. Consequently, the study may have been underpowered. The second limitation is related to instrumentation. Within the study's theoretical framework, it was conceptualized that cardiac self-efficacy and self-care agency were affected by patient and procedural variables, which in turn, produced self-care behaviours aimed at the maintenance (short term) and management (long term) recovery following PCI. The inability to identify a reliable and quantifiable instrument to measure self-care behaviour, such as medication administration, medical follow-up or dressing removal, limited the study of self-care behaviour to descriptive statistics. Conversely, the theoretical underpinnings of cardiac self-efficacy and self-care agency, aimed at the identification of factors associated with these outcomes, were supported by the use of validated instruments. It was also necessary to augment the measures by incorporating non-validated items based on findings in the literature, and to capture the data required to answer the research questions. The construction of a cohesive adapted instrument required the creation of consistent scales for administration of the questionnaire over the telephone. The study'sfindingswould have been strengthened by the use of a valid and reliable measure of CSE and SCA in the PCI population. As discussed earlier, the STOP-D instrument also ha limitations, but accomplished the objective of including a feasible screening measure of psychoemotional distress.  125 Although validated in out-patient cardiac clinics and used clinically at the study site, this instrument is as yet unpublished, not validated for use over the telephone, or with the PCI patient population (Young et al.; n.d.). The alternative method of using gold standard instruments such as the Beck Depression Inventory or the Beck Anxiety Inventory would have proven unfeasible, given the primary objectives and limitations of this study. Although further research will be required to validate the STOP-D instrument in its telephone use and in the PCI population, its selection as a screening tool for this study achieved the goal of providing a snapshot of the participants' psychoemotional state. The analytic plan combined descriptive, bivariate and multivariate analyses to answer the research questions. The need to collapse and dichotomize 16 variables to facilitate the analysis, although done with conceptual consistency, may have resulted in lost variation or erroneous categorization. Although every effort was made to consistently quantify the participants' responses when interpreting and recording answers as "yes", "no", and "somewhat", or as "not at all", "somewhat", "moderately", or "very" confident, the study is limited by the potential bias of the investigator in the interpretation of participants' answers, as well as the statistical challenges of translating these responses into a scale. The factor analysis demonstrated that the self-care agency items could have loaded onto two or three factors. Because of the small sample size, the decision to limit the model to two factors was a potential source of conceptual and statistical error. Limitation in the study protocol also must be recognized. The participants were interviewed between two and five days following discharge to ensure that patients would have returned home at the time of the administration of the questionnaire, and to allow the investigator the flexibility required to complete the data collection. The variation in the time  126 lapsed since discharge may have resulted in recall bias. Some participants had already resumed their activities of daily living including their work schedule, while others might have just returned to their remote residence by the time of the telephone interview. The study did not control for this potential bias, which may have contributed to inaccuracies in the collection of data. The reliance on self reporting, including post-discharge behaviour, perceptions of complications, education, income, employment status and household size, as well as the use of telephone interviewing carry inherent threats to the validity of the study's results (Polit et al., 2004). Implications Short-term recovery behaviour from same-day discharge PCI has not been previously described in the literature. In addition, this study offers some preliminary findings of the factors associated with patients' self-efficacy and self-care agency during the phase of transition between hospitalization and resumption of activities of daily living. Although the practice of same-day discharge was initiated at the study site over five years ago, most PCI centres continue to monitor patients for more extensive periods. As recently as May 2007, the issue of same-day discharge elective PCI merited an editorial published in Circulation, the peer reviewed publication of the American Heart Association (Resnic, 2007). Although cautiously supportive, the author anticipated reluctance from both patients and physicians to implement this practice, due to uncertainty about safety, anxiety related to PCI and long term prognosis, and medico-legal issues. This study is timely and significant in its limited findings, and is well positioned to provide some recommendations as centres consider implementing same-day discharge elective PCI.  127  Although most patients followed discharge guidelines, and exhibited confidence and knowledge in their capacity to care for themselves, a smaller group is at higher risk in the recovery period. Existing predictive scores do not address the immediate recovery period, nor do they include the assessment of social support and psychoemotional status. This study found new and meaningful evidence about the relationship between lack of social support, and other measures of psychoemotional distress, and poorer outcomes. Same-day discharge PCI without an appropriate follow-up or referral intervention for patients screened for low levels of social support is not adequate care. Patients, their families, and healthcare providers and administrators would benefit from a validated scoring system to screen patients at higher risk for lower levels of self-efficacy and self-care agency. In particular, this would assist nurses to argue for home care referral, social worker input, or extended hospitalization for the likely small but significant number of patients who meet medical discharge criteria, but may be at higher risk due to social isolation. It is unlikely that an overnight hospital stay would be sufficient to remedy the negative effects of lack of social support on the recovery post-PCI. There is a pressing need to study the implementation of an intervention to support PCI patients who lack social support. In this study, a majority of participants failed to meet their need to learn to change the course of my heart disease. As hypothesized, the reduced contact time between patients, families, and health care providers, and the focus on completing the tasks associated with admission, the procedure, and discharge, may not be conducive to risk factor counseling. The lack of systematic referral to cardiac rehabilitation is contrary to evidence based practice. For example, with one fifth of the sample self-identifying as current smokers, an opportunity was missed to support patients in smoking cessation, a behaviour modification with extensive and  128 well-proven cardiovascular benefits. Similarly, more than one third of the participants in this study were discharged believing that they no longer had coronary artery disease. In addition to the prognostic implications of this finding, there are also ethical considerations to providing an intervention without addressing the chronic and potentially terminal nature of CAD. To be successful, nurses must be allowed the time, resources and education to fulfil their role related to risk factor modification. Given the time limitations associated with early discharge, research is needed to identify and study a valid intervention that would use other forums, such as telephone follow-up and the internet, to help patients meet their learning needs. A third implication arises from the preliminary findings related to the prevalence and significant impact of psychoemotional distress on the capacity to care for oneself in the discharge period. The study found that the scores for depression and anxiety were high for one half the participants, with one third also scoring high for stress. Compounded with a significant association with lower self-efficacy and self-care scores, these findings raise awareness of the need for further investigation, and to begin the process of testing an intervention to meet the need for referral and treatment of a known predictor of morbidity and mortality in the setting of CAD. This study of self-care behaviour and factors associated with cardiac self-efficacy and self-care management related to disease and illness management succeeded in contributing novel findings to existing evidence. Same-day discharge PCI is a viable option to promote access to care, yet patients who are socially isolated must be identified and supported in the recovery period to promote improved patient outcomes.  129 REFERENCES  American Heart Association. (2007). Heart disease and stroke statistics - Update at a  glance. 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American Heart Journal, 145, 278-284.  APPENDIX A  STUDY TITLE: Factors Associated With Patient Outcomes Following Same-Day Discharge Percutaneous Coronary Intervention  Investigators: Sandra B. Lauck, B.A., RN, CCN(C) Master's of Science in Nursing Candidate (Thesis Project) School of Nursing University of British Columbia  Joy L. Johnson, PhD, RN, FCAHS Professor School of Nursing University of British Columbia  Pamela Ratner, PhD, RN Professor School of Nursing University of British Columbia  1  APPENDIX A Data Collection: Part 1  Chart Extraction 2007  y  |  Study ID #: Telephone #: Planned call-back date:  From Patient's Chart: C.1.  Gender  C.2.  Date of birth Age  C.3.  Marital status  • • • • • •  C.4.  Residence (Distance to SPH)  Municipality: Postal code: Health authority: • Vancouver Coastal • Fraser • Interior • Vancouver Island • Northern • Yukon  C.5.  Residence (Distance to medical services)  Referring physician: Municipality: Postal code:  C.6.  Glycoprotein llbllla inhibitor (use of agent) Glycoprotein llbllla inhibitor (infusion time) Vascular hemostasis (method)  • •  Yes No  •  N/A  C.7. C.8.  • Male • Female Day month years Single Married Common-law Divorced Separated Widowed  hrs and • •  year  min =  min  Compression device Closure device • Hemostasis achieved • Compression device required  154  APPENDIX A Vascular hemostasis for compression device (clamp time) Vascular access complication  •  C.11.  Vagal reaction  • •  C.12.  Duration of bedrest (Post hemostasis) Duration of hospitalization  C.9.  C.10.  C.13.  N/A (Closure device hrs and min =  • •  None Hematoma - minor (<10 cm diameter) • Hematoma - major (>10 cm diameter) Minor Major hrs and Admission time: Discharge time: Total duration:  min =  hrs and  From HeartView: C.14.  Coronary artery disease  • •  Single vessel (>70%) Multi-vessel (>70%)  C.15.  PCI Targets  • •  Single vessel procedure Multi-vessel procedure  C.16.  Stent deployment  • o  C.17.  PCI target(s)  C.18.  C C S Class  min  • • • •  1 2 3 4 and greater  • • • • • • • n  LAD RCA Cx LM Diagonal OM Bypass graft Other:  From B.C. Cardiac Registry:  =  min  min  min  •••  APPENDIX A  155  • • • C.19.  Heart failure  III IV Atypical  •  Yes  •  No  EF  %  N Y H A Class • • • • C.20.  Co-morbidities  I II III IV •  No •  Yes  Prior AMI  •  No •  Yes  Hypertension  • •  No • No •  Yes Yes  •  No •  Yes  •  No •  Yes  •  No •  Yes  Dialysis Creatinine GFR  Hyperlipidemia DM •  Type I  •  T y p e II - n o i n s u l i n  •  T y p e II - i n s u l i n  PVD Cerebrovascular disease Smoking  •  Never •  Prior PCI Prior C A B G  Current • • •  Former No • Yes No • Yes  Co-morb: Resp.  •  No •  Yes  C o - m o r b : Liver/GI  •  No •  Yes  Co-morb: Malignancy  •  No •  Yes  n  Height  Weight  156  APPENDIX B Data Collection: Part 2 Telephone Interview 2007 1.  y  m  d  S t u d y ID #:  Hello. This is  calling from the U B C S c h o o l of Nursing.  When you were at St. Paul's Hospital for your angioplasty, you agreed that we could call you today to ask s o m e questions about your return home and recovery after your angioplasty. Is this a good time to s p e a k ? (if no, set-up alternate time) A s we mentioned when you were in hospital, I want to ask you s o m e questions to help us learn more about how you have done following your angioplasty. I will be writing down your answers as we speak and I want you to know that all the information you give me will remain strictly confidential.  These first questions are about what you have done since leaving the hospital.  2.  After your angioplasty, did y o u go straight h o m e or did y o u stay c l o s e r to the hospital? DO NOT READ ANSWERS - SELECT APPROPRIATE  CHOICE  • •  W e n t directly h o m e S t a y e d in town/hotel/family/friends  3. W h e n y o u left the hospital, did a n y o n e take y o u h o m e ?  •  Yes  •  N o (Go to question 5)  4. W h o took y o u h o m e ? DO NOT READ ANSWERS - SELECT  APPROPRIATE CHOICE • •  5.  Spouse Son/daughter  • •  Friend Caregiver  •  S o n / d a u g h t e r in-law  H a v e y o u m a d e a follow-up appointment with your family doctor?  t  1  APPENDIX B  •  Yes  •  No  •  No (Go to question 10)  6. Do you work? •  Yes  7. Were you given any information about returning to work after your angioplasty? •  Yes  •  No  8. Who told you about returning to work? DO NOT READ ANSWERS SELECT APPROPRIATE CHOICE • • •  -  Nurse Doctor Read about it in booklet  9. When do you plan on returning to work? DO NOT READ ANSWERS SELECT APPROPRIATE CHOICE  -  • < 1 week • 1 week • 2 weeks • 3 weeks • 4 weeks • > 1 month • Not sure  10. Have you started driving again? •  Yes  •  No (Go to question 12)  11 .When did you start driving again? D O NOT READ ANSWERS APPROPRIATE CHOICE • Day of procedure • Day following procedure • 2 Days after procedure  -  SELECT  158  APPENDIX B  I have a few questions about a drug called Plavix or clopidogrel. Do you know which medication that is? (prompt if necessary: Those are the small pink pills that you started taking before your angioplasty 12. Have you started taking Plavix®? •  Yes  •  No  •  Long term therapy (Go to question 18)  13. Have you filled your prescription for Plavix®? •  Yes  •  No (Go to question 16)  14. When did you fill your prescription for Plavix®? D O NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • • •  Day of discharge Day following procedure > 2 days following procedure  15. Where is the pharmacy where you filled your prescription for Plavix®? (Prompt if necessary: For example, is it your home pharmacy or one closer to the hospital?) D O NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • • •  Close proximity to hospital En route home Neighbourhood/usual pharmacy  16. Were you given any information about what Plavix® does? •  Yes  •  No (Go to question 18)  17. Who told you about Plavix®? D O NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • • • •  Nurse Doctor Pharmacist Read drug information in box  159  APPENDIX B  18. In your own words, can you describe what Plavix® does? DO NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • • • • • •  Thins the blood Stops blood from sticking to stent Stops blood clots Changes the platelets Don't know Other:  19. Were you told that you needed to have any blood tests done after your angioplasty? • •  Yes No  20. Have you removed your bandage? • •  Yes No  21 .Were you told when to remove your groin bandage? •  Yes  •  No (Go to question 23)  22. Who told you about removing your bandage? D O NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • • •  Nurse Doctor Read about it in booklet  23. When did you remove the groin bandage? D O NOT READ SELECT APPROPRIATE CHOICE • • • •  Day of discharge Day following procedure 2 Days following procedure 3 Days following procedure or later  ANSWERS-  160  APPENDIX B  24. Have you had a shower since leaving the hospital? • Yes • No (Go to question 26)  25. When did you have your first shower? D O NOT READ ANSWERS SELEC T APPROPRIA TE CHOICE • • • •  Day of discharge Day following procedure 2 Days following procedure 3 Days following procedure or later  26. Were you told when to have your first shower? •  Yes  •  No (Go to question 28)  27. Who told you about having your first shower? DO NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • • •  Nurse Doctor Read about it in booklet  28. Do you have a bruise in the groin area? PLEASE NOTE ANY  ADMISSION TO ER •  Yes  •  No (Go to question 33)  I'm going to ask you a few questions about your bruise. 29. Would you say the size of your bruise is smaller than a loonie, medium size like a doughnut or larger than that? • • •  Small Medium Large  30. Would you say your bruise feels soft like normal skin or hard like a ball?  161  APPENDIX B • •  Soft Hard  31 .Would you say that your bruise is getting better, staying the same or getting worse? • • •  Getting better Getting worse Staying the same  32. Does your bruise worry you? •  Yes  •  No  33. Since your discharge from hospital, have you started walking again? •  Yes  •  No (Go to question 35)  34. What is the farthest you have walked? Would you say it's less than a city block, 2 blocks, 3 blocks or more than 3 blocks? • • • • •  Around house < 1 block 2 blocks 3 blocks > 3 blocks  35. Have you had any chest pain or other heart symptoms since you left the hospital? •  Yes  •  No (Go to question 37)  36. When you got chest pain or other heart symptoms, what did you do? DO NOT READ ANSWERS - SELECT ALL APPROPRIATE CHOICES • • • •  Stopped what I was doing/laid down Took nitroglycerin It went away on its own Called my doctor  162  APPENDIX B • • •  Went to hospital Waited for chest pain to go away Did nothing  37. Do you have any pain in the area where the doctors did the angioplasty? (Prompt if necessary: usually the groin area) • •  Yes No (Go to question 39)  38.1 would like you to rate the pain in your groin/wrist between 0 and 10, with 0 being no pain and 10 being the worst pain you can imagine. What number would give your pain right now? 0 1 No pain  2  3  4  5  6  7  8  9  10 Pain as bad as you can imagine  This second set of questions is about things you know about caring for yourself after your angioplasty. 39. When you left the hospital, did you understand the results of your angioplasty? DO NOT READ ANSWERS - SELECT APPROPRIATE CHOICES • • •  No Somewhat Yes  40. Do you know what to do if your heart symptoms come back? DO NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • • •  No Somewhat Yes  41 .After your angioplasty, did you know how to take care of yourself? DO NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • • •  No Somewhat Yes  .  APPENDIX B  42. After your angioplasty, did you know what to expect when you got home? DO NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • • •  No Somewhat Yes  43. Did you know when to see a doctor? DO NOT READ ANSWERS SELECT APPROPRIATE CHOICE • • •  No Somewhat Yes  44. Do you know what lifestyle changes are needed to prevent your heart disease from getting worse? DO NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • • •  No Somewhat Yes  45. When you were in the hospital for your angioplasty, did anyone speak with you about the causes and risk factors of your heart disease? DO NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • •  No (Go to question 48) Yes  46. Who spoke to you about the causes and risk factors for heart disease? DO NOT READ ANSWERS - SELECT APPROPRIATE CHOICES • • •  A doctor A nurse Both  47. How was the information about the causes and risk factors for heart disease given? DO NOT READ ANSWERS - SELECT APPROPRIATE  1  164  APPENDIX B CHOICES •  In a conversation  •  In a booklet  •  Both  48. I'm interested in knowing how well you feel you understand the causes of your heart disease. How well would you say you understand the causes of your heart disease? Not at all, not very well, quite well or very well? • • • •  Not at all Not very well Quite well Very well  49 Do you plan on attending a cardiac program like a Healthy Heart Program? DO NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • Yes • No  50. Did any one tell you about cardiac rehab programs in the area where you live? D O NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • •  Yes No (Go to question 52)  51. Who told you about these programs? DO NOT READ SELECT APPROPRIATE CHOICES • • • •  ANSWERS-  Friend Family RN MD  52. Do you know what to do to do if you have problems with your heart medications? D O NOT READ ANSWERS - SELECT APPROPRIATE CHOICE •  No  APPENDIX B • •  Somewhat Yes  53. Do you understand how your medicines work? D O NOT READ ANSWERS - SELECT APPROPRIA TE CHOICE • • •  No Somewhat Yes  54. Do you understand when to take your medicines? D O NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • • •  No Somewhat Yes  55. Do you understand when to stop your medicines? D O NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • • •  No Somewhat Yes  56. Do you understand how much exercise to get? D O NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • • •  No Somewhat Yes  57. Do you understand when you can start doing the things that you usually do at home? D O NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • • •  No Somewhat Yes  58. Now that you've had your angioplasty, do you understand what symptoms  165  166  APPENDIX B to expect? •  No  •  Somewhat  •  Yes  The next questions have to do with your satisfaction with the care you received while you were in hospital. 59. How would you rate the overall ability of the doctors, nurses, and other staff to work together in a an organized matter while you were in hospital? Would you say it was poor, fair, good or excellent? •  Poor  •Fair  •Good  •Excellent  60. How would you rate how quickly the nursing staff answered your calls? Would you say it was poor, fair, good or excellent? •  Poor  •Fair  •Good  •Excellent  61. How would you rate the overall courtesy and friendliness of the nursing staff? Would you say it was poor, fair, good or excellent? •  Poor  •Fair  •Good  •Excellent  62. How would you rate the overall quality of the nursing care you received? Would you say it was poor, fair, good or excellent? •  Poor  •  Fair  •Good  •Excellent  63. How would you rate your overall satisfaction with pain relief and comfort measures? Would you say it was poor, fair, good or excellent? •  Poor  •Fair  •Good  •Excellent  64. Did the nurses treat you like a person, rather than a disease? Would you say never, rarely, sometimes or always? •  Never  •  Rarely  •  Sometimes  •  Always  167  APPENDIX B 65. Did the nurses answer your questions to your satisfaction? Would you say never, rarely, sometimes or always? •  Never  •  Rarely  •  Sometimes  • Always  66. Did the nurses call you by name? Would you say never, rarely, sometimes or always? •  Never  •  Rarely  •  Sometimes  • Always  67. How comfortable were you sharing your concerns with the nurses? Would you say you were: • • • •  Totally uncomfortable Somewhat uncomfortable Somewhat comfortable or Totally comfortable?  This 3 set of questions are about how you confident you felt when you left the hospital after your angioplasty. r d  68. How confident did you feel about returning home? Would you say not confident at all, somewhat confident, moderately confident or very confident? • • • •  Not confident at all Somewhat confident Moderately confident Very confident  69. How confident did you feel about caring for yourself? Would you say not confident at all, somewhat confident, moderately confident or very confident? • • • •  Not confident at all Somewhat confident Moderately confident Very confident  70. How confident did you feel about taking your medications? Would you say not confident at all, somewhat confident, moderately confident or very  APPENDIX B confident? • • • •  Not confident at all Somewhat confident Moderately confident Very confident  71. How confident were you about knowing how much physical activity is good for you after your angioplasty? Would you say not confident at all, somewhat confident, moderately confident or very confident? • • • •  Not confident at all Somewhat confident Moderately confident Very confident  72. How confident were you that you knew when you should call or visit your doctor about your heart disease? Would you say not confident at all, somewhat confident, moderately confident or very confident? • • • •  Not confident at all Somewhat confident Moderately confident Very confident  73. How confident did you feel about following instructions? • • • •  Not confident at all Somewhat confident Moderately confident Very confident  74. How confident did you feel about coping at home? Would you say not confident at all, somewhat confident, moderately confident or very confident? • • • •  Not confident at all Somewhat confident Moderately confident Very confident  168  169  APPENDIX B  75. Now that you have had an angioplasty, do you think you still have coronary artery disease? D O NOT READ ANSWERS - SELECT APPROPRIATE CHOICE • •  Yes No  These next few questions are about your mood and generally how you feel about things. It's not unusual for people to feel down or blue after a cardiac procedure. Again, I want you to know that all your answers are confidential. This time, I would like you to use a scale of 0 to 9 to rate your response, with 0 meaning "not at all" and 9 meaning "severely".  74. Over the last 2 weeks, how much have you been bothered by feeling sad, down, or uninterested in life? If 0 is not at all and 9 is severely, what number would you choose? 0 1 2 3 4 5 6 7 8 9  75. How much have you been bothered by feeling anxious or nervous? If 0 is not at all and 9 is severely, what number would you choose? 0 1 2 3 4 5 6 7 8 9  76. How much have you been bothered by feeling stressed? 0 1 2 3 4 5 6 7  8  9  77. How much have you been bothered by feeling angry? 0 1 2 3 4 5 6 7  8  9  78. How much have you been bothered by not having the social support you feel you need? 0 1 2 3 4 5 6 7 8 9 That is the end of the study's questions. W e find it very helpful to describe who has taken part in our research, so I'm going to ask you a last set of questions about you.  1  APPENDIX B 79. In what country were you born? •  Canada (Go to question 81)  80. In what year did you first immigrate to Canada?  81. Have you graduated from high school? DO NOT READ ANSWERS SELECT APPROPRIATE CHOICE •  Yes  •  No (Go to question 84)  82. Have you ever attended any other kind of school such as university, community college, business school, trade or vocational school, or other post-secondary institution? DO NOT READ ANSWERS - SELECT APPROPRIATE CHOICE •  Yes  •  No (Go to question 84)  83. What is the highest level of education you have attained? D O NOT READ ANSWERS - SELECT APPROPRIATE CHOICES • Some trade, technical, vocational school or business college • Some community college, C E G E P or nursing school • Some university • Diploma or certificate from community college, C E G E P or nursing school • Bachelor's or undergraduate degree or teacher's college • Master's degree • Doctorate • Other (specify)  84. What do you consider to be your current main activity? (for example, working for pay, caring for family) DO NOT READ ANSWERS - SELECT APPROPRIATE CHOICES • • •  Caring for family Working for profit or pay Caring for family and working for pay or profit  171  APPENDIX B • • • •  Recovering from illness/disability Looking for work Retired Other (specify)  85. This next question is about ethnic background. Most people in Canada describe themselves as Canadians first but also identify themselves based on their background or nationality of their ancestors. What would you say is your main ethnic background?  86. Again, because it is so helpful to describe our participants, I'm going to ask you to estimate your household's total annual income before taxes. Would you say it is: above i  or  below (STOP HERE)  $25,000 per year?  87. Would you say it is: above i  or  below (STOP HERE)  $50,000 per year?  88. Would you say it is: above 4  or  below (STOP HERE)  $75,000 per year?  or  below  $100,000 per year?  89. Would you say it is: above  90. How many people live in your house? DO NOT READ ANSWERS SELECT APPROPRIATE •  1 D2  D3  D4  -  CHOICE D5  D6  D7  D8  D9  niOormore  These are all the questions I have. I want to thank you for the time you've taken to speak with me and help this research project.  1  APPENDIX C  The CAD-Specific Index  Sachdev et al. (2004)  CAD  Condition  Current smoker  1  Hypertension  1  Cerebrovascular disease  1  Diabetes  2  Chronic pulmonary disease  2  Peripheral vascular disease  2  Any tumour  2  Diabetes with end-organ disease  3  Moderate or severe renal disease  7  Metastatic solid tumour  5  CAD-Specific Score 0 to 1: Lowest risk group  Survival probability of 89.2%  CAD-Specific Score 2 to 3: Intermediate risk group  Survival probability of 81.6%  CAD-Specific Score > 4:  Survival probability of 67.9%  Highest risk group  173  APPENDIX D  DATE:  NAME:  Please answer the following questions so we can offer you additional services should you need them. Please answer each question by circling how you have been feeling. Be assured that your answers are CONFIDENTIAL. Over the last two weeks, how much were you bothered by: 1. Feeling sad, down, or uninterested in life?  0  not at all  1  3  5  3  5  6  7  moderately  a little  severely 2. Feeling anxious or nervous?  0  1  2  not at all  a little  3. Feeling stressed?  0  1  5  3  not at all  a little  6  5  3  not at all  7  8  8  7  6  9  severely  7  8  moderately  a little  9  severely  moderately  4. Feeling angry?  0  6 moderately  9  severely  5. Not having the social support you feel you need?  0  1  2  not at all  3  4  a little  5  6  7  8  moderately  9 severely  Please provide your phone number For Office Use Only •  _,  Nurse discussed responses with patient  •^Referral sent to •  Psychology  n Left messaqe on • Offered TreatmenToiT treatment  NOTES:  • Handouts given to patient  • Psychiatry  •  u  t t  . ,  Letter sent to family  • Patient declined referral  • No response from patient • Patient is in treatment with Psychologist • Patient declined  174  APPENDIX E  UBC-PHC BREB APPROVAL H06-00211 Consent Form  Going Home After Percutaneous Coronary Intervention: Patients' Experiences  Principal Investigator:  Joy Johnson, PhD, RN, FCAHS Professor UBC S c h o o l of Nursing Tel. XXX-XXX-XXXX  Co-Investigators:  P a m e l a Ratner, PhD, RN, Professor UBC S c h o o l of Nursing Tel. XXX-XXX-XXXX S a n d r a Lauck, BA, RN, C C N ( C ) Master's of S c i e n c e in Nursing C a n d i d a t e Thesis Project UBC S c h o o l of Nursing Tel. XXX-XXX-XXXX Pager. XXX-XXX-XXXX  Purpose of Study: .  .  .  You h a v e u n d e r g o n e a p e r c u t a n e o u s c o r o n a r y intervention (PCI) to o p e n a b l o c k a g e in your c o r o n a r y arteries c a u s e d b y the a c c u m u l a t i o n of p l a q u e . In a d d i t i o n , a stent m a y h a v e b e e n i m p l a n t e d to help k e e p your artery o p e n . You will b e d i s c h a r g e d h o m e this e v e n i n g after ensuring that y o u h a v e r e c o v e r e d sufficiently from your p r o c e d u r e a n d after r e c e i v i n g d i s c h a r g e instructions. O n c e you l e a v e the hospital, y o u will return h o m e to c o m p l e t e your recovery. You h a v e b e e n a s k e d to p a r t i c i p a t e in this study to help us better understand h o w patients r e c o v e r from PCI o n c e they l e a v e the hospital the e v e n i n g of their p r o c e d u r e . Results of this study will help ensure that the services a n d t e a c h i n g w e provide m e e t PCI patients' needs.  

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