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Depression and Illness Intrusiveness as Predictors of Quality of Life Among Implantable Atrioverter Defibrillator Recipients


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DEPRESSION AND ILLNESS INTRUSIVENESS AS PREDICTORS OF QUALITY OF LIFE AMONG IMPLANTABLE ATRIOVERTER DEFIBRILLATOR RECIPIENTS By REBECCA OWEN SOTILE A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2003

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Copyright 2003 by Rebecca O. Sotile

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iii ACKNOWLEDGMENTS I would like to thank my mentor, Dr. Samuel F. Sears, for his constant guidance, support, and understanding. I would also like to thank my first-year lab mates, Jason and Robyn, for all of their advice, support, and, most of all, for their laughter. My acknowledgments also go to Eva for her consta nt encouragement and willing assistance. I would also like to thank my committee, Dr s. Stephen Boggs, Dawn Bowers, and Robert Glueckauf, for their general support as well as their specif ic suggestions and contributions. My thanks also go to my boyfriend, Tom Horsman, for his love, courage, and the countless positive things he has brought to my life. Also I thank my sister, Julia, for being my best friend, my greatest source of comfort, and my most valuable point of perspective. My utmost thanks go to my parents, Wayne and Mary Sotile, for their incredible love and acceptance of who I am, and faith in the person I am becoming.

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iv TABLE OF CONTENTS Page ACKNOWLEDGMENTS ................................................................................................. iii LIST OF TABLES............................................................................................................. vi ABSTRACT...................................................................................................................... v ii CHAPTER 1 INTRODUCTION...1 Atrial Fibrillation.2 Medical/Pharmacologica l Treatments for AF..3 Device Therapies: The IAD.4 Psychological Effects of Shock...6 Depression....9 Quality of Life Illness Intrusiveness...11 Relationship Between Illness Intr usiveness and Quality of Life...13 Aims and Study Justification.14 Hypotheses.14 2 METHOD..16 Participants.16 Assessment.18 Generic Quality of Life..18 Center for Epidemiological Studies Depression Scale..18 Illness Intrusiveness Rating Scale..19 State-Trait Anxiety Inventory Pain and Intensity Ratings.20 Device Data Demographic Measures.21 3 RESULTS..22 Sample Descriptives...22 Correlations and Collinearity Evaluation...23 Regression Analyses: Illness Intrusiveness...23 Regression Analyses: Physical Quality of Life.25 Regression Analyses: Ment al Quality of Life

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v 4 DISCUSSION Implications for the Experience of Shock..29 Clinical Implications..30 Strength and Weaknesses of the Study..31 LIST OF REFERENCES...33 BIOGRAPHICAL SKETCH.38

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vi LIST OF TABLES Table page 2-1 Patient Demographics and Re levant Medical Variables..17 3-1 Means for Psychosocial Measures.....23 3-2 Correlations of Key Assessment Instruments....24 3-3 Regression Analysis: I llness Intrusiveness.......25 3-4 Regression Analysis: Phys ical Quality of Life.26 3-5 Regression Analysis: Me ntal Quality of Life

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vii Abstract of Thesis Presen ted to the Graduate School Of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science DEPRESSION AND ILLNESS INTRUSIVENESS AS PREDICTORS OF QUALITY OF LIFE AMONG IMPLANTABLE ATRIOVERTER DEFIBRILLATOR RECIPIENTS By Rebecca Owen Sotile May 2003 Chair: Samuel F. Sears Major Department: Clinical and Health Psychology The Implantable Atrial Defibrillator (I AD) corrects atrial and ventricular fibrillation via a high energy de fibrillation shock. Because th e application of shock is aversive and atrial fibrillati on (AF) is not an immediately life-threatening indication, the inter-relationship of shock, AF symptoms, illness intrusiveness and quality of life outcome will determine the potential value and future direction of IAD development. The purpose of this study was to examine a biopsychosocial model of illness for illness intrusiveness and quality of life in drug-refractory IAD patients. IAD adjustment was evaluated in 96 patients enrolled in the Jewel AF-AF Only Study > 3 months follow up (mean=19 months). Patients were mostly men (72%) and were 62+-12 years. A questionnaire and national cl inical database characterized patient demographics, AF disease burden, atrial defi brillation therapy, and psychol ogical distress. Within a biopsychosocial design, multiple hierarchical regressions indicated depression as a

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viii unique predictor of variance on illness intr usiveness scores, accounting for 11.4% of variance. Illness intrusiveness and depre ssion together predicted 11.1% of variance on physical quality of life. Beta weights revealed that illness intrusiv eness and age were the only predictors of variance of physical quality of life. Rega rding mental quality of life, results indicated that 32.3% of variance was accounted for by depression and illness intrusiveness together. Beta weights revealed that depression was the only unique contributor of variance to me ntal health. Maladjustment to the physical aspects of defibrillation may result from the presen ce of psychological dist ress. Psychological symptoms such as depression and illness in trusiveness are largely responsible for AF patients’ declines in quality of life. Acceptance of IAD th erapy may be facilitated by successful treatment of psychological distre ss among IAD patients and multi-disciplinary care that routinely addresses the psychologi cal impact of AF and device treatment.

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1 CHAPTER 1 INTRODUCTION Cardiac arrhythmias are a prominent cause of death, hospitalizations, and healthcare costs in the United States. Each y ear cardiac arrhythmias play a role in over 500,000 deaths and 724,000 hospitalizations, while also accounting for 11.9 billion dollars spent annually on h ealthcare costs (American Hear t Association, 2001). An arrhythmia is characterized by abnormal electrical impulse conduction in the heart (American Heart Association, 2001). A su stained rapid heartbeat (usually 160-280 beats/minute) is referred to as tachycardia. Tachycardia can begin in the atria or the ventricles and is often accompanied by sy mptoms such as chest pain, fainting, and dizziness. Prolonged tachycardia may result in fibrillation, which is an uncoordinated movement of electrical impulses through the heart. These impulses cause the heart chambers to twitch rapidly, resulting in ine fficient blood flow to the rest of the body, and have the potential to significantly affect mortality risk and quality of life (Allan & Scheidt, 1996). The implantable atrioverter defibrillator (IAD) is a device that corrects fibrillation in the atria. Correcting these irregular he artbeats requires a shock from the device, similar to the shock received during external cardioversion. Shock can be an aversive experience for patients, but the effects of untreated atrial fibr illation can be more detrimental. Therefore, the degree of intrusion from the illness may be an important index to understanding both patients’ willingness to get shocked and the effects of having

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2 been shocked. In this study, a biopsychosoc ial model including disease and treatment variables as well as predictors of illness intrusiveness and quality of life in atrial fibrillation patients who have been impla nted with the IAD were examined. Atrial Fibrillation Atrial fibrillation (AF) is the most common type of cardiac arrhythmia, occurring in over 2 million Americans. AF refers to ra pid contractions of th e atria, or upper heart chambers, and illicits an irregu lar response from the ventricles. This irregular rhythm causes a reduction in blood flow, and increase s the chances of formation of a blood clot that could travel to the brain, causing str oke and possibly death (L uderitz & Jung, 2000). Fifteen percent of all stroke s are caused by AF (American Heart Association, 2001). The prevalence of AF increases with age from less than 1% at 50 to 59 years to 9% at 80 to 89 years (Luderitz & Jung, 2000). The majority of hospitalizations from car diac arrhythmias are due to AF. Besides increasing the risk of blood cl ots and stroke, the hemodynami c effects of AF may cause decreased exercise tolerance and heart failur e. Disorders that may result in atrial fibrillation include: ischemic heart disease, rheumatic heart diseas e, hypertension, sick sinus syndrome, cardiomyopathy, and other stru ctural abnormalities. Atrial fibrillation can be paroxysmal or sustained; however, the majority of patients have paroxysmal atrial fibrillation, denoting a transi ent occurrence of AF (Lip, 2001). The initial impairment caused by atrial fibrillation is less obvious th an that caused by vent ricular fibrillation, or rapid contractions of the lower heart chambe rs, because atrial fibrillation only mildly affects cardiac output. In fact, a patient may be unaware that he/s he is in atri al fibrillation because various medications can keep the he art rate normal during atrial fibrillation

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3 (Allan & Scheidt, 1996). Approximately one-third of AF patients do not experience any symptoms, while the other two-thirds may experience heart palpitations, fatigue, dizziness, and presyncopal episodes (American Heart Association, 2001). Although the physical symptoms of AF may not be immediately apparent, significant psychological distress often accompan ies this condition. The Ablate and Pace Trial (Kay, Ellenbogen & Giudici 1998) included a sample of highly symptomatic, drugrefractory AF patients. Baseline assessment re vealed significantly lower quality of life among the AF patients as compared to patients with heart failure or a recent myocardial infarction. This illustrates that AF patient s may experience unique psychological issues that are not as prominent for other cardia c populations. Because multiple studies have illustrated that psychological intervention is effective in improving quality of life and physical symptoms among various cardiac pati ent populations (Bennett & Carol, 1994; Hill, Kelleher, & Shumaker, 1992; Linden, Stossel, & Maurice, 1996), this study suggests that AF patients may receive similar benefit from psychological intervention. Medical/Pharmacological Treatments for AF The treatment of cardiac arrhythmias varies based on the rhythm’s characteristics, etiology, and the patient’s experience of sy mptomotology. The most efficient way to describe treatment options is to consider them on a scale of physical and mental intrusiveness to the patient. The least se vere, a non-life-threatening, and asymptomatic paroxysmal arrhythmia, may be treated with simple behavioral interventions such as dietary modifications and sm oking cessation. A more severe symptomatic paroxysmal arrhythmia, (e.g., ventricular tac hycardia or atrial flutter), th at results from a manageable disease process may be treated with anti-arr hythmic medications such as beta-blockers

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4 (Canobbio, Fassio, & Gasparini, 1986). In addition to suppressing premature contractions that cause arrhythmias, beta-b lockers also reduce hear t rate, blood pressure, and strength of cardiac contra ction. Atrial fibr illation becomes more severe when the episodes are sustained or paroxysmal, symp tomatic, not drug-res ponsive, and/or lifethreatening. These may call for more invasive interventions such as catheter ablation of conduction pathways, surgical ablation, or re section of conducti on pathways (Canobbio et al., 1986). Although the treatment of AF varies widely, the majority of symptomatic patients are successfully treated with dual chamber pacemaker therapy and/or antiarrhythmic drugs. Most AF patients r eceive anticoagulants, such as aspirin or warfarin, which help prevent the formation of blood clots. However, AF patients whose symptoms are recurrent and re quire external cardioversion may benefit most from an implantable device called the implantable at rioverter defibrillato r (IAD; Lip, 2001). The IAD alleviates symptoms but does not cure the underlying disorder. Currently, there are no absolute indications for the implantation of an IAD; yet, the patients involved in clinical trials using the IAD have paroxysmal atrial fibrillation that is symptomatic and drug-refractory (Wellens, Lau, Luderiz, et al., 1998). Device Therapies: The IAD The technology of the IAD is similar to that of the implantable cardioverter defibrillator (ICD), which terminates life-thre atening ventricular arrythmias (Lip, 2001). The ICD re-establishes normal sinus rhythm in response to ventricular fibrillation, whereas the IAD is designed to re-establish norm al sinus rhythm in i ndividuals with atrial arrythmias. The ICD gained FDA approva l in 1985, and has been researched in

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5 numerous trials since 1996 (Davidson, VanRiper, Harper & Wenk, 1994). In contrast, the IAD is a much newer device, and IAD patient s have not been extens ively researched. The IAD is similar to the size of a pacemak er, and consists of an atrioverter can which is pectorally implanted, and three elect rical leads which connect to three different parts of the heart: the coronary sinus, the right atrium, and th e right ventricle (Lip, 2001). The IAD is capable of delivering two different types of shocks: a defibrillation shock for the atrium, and a pacing discharge to the ve ntricle to prevent a bradyacardiac response after defibrillation. The IAD can be progr ammed to shock automatically, or can be activated by the patient or physician with a hand-held activator (Lip, 2001). A recent trial illustrated that the Dual-Chamber ICD, which is essentially an ICD with atrial therapies, is well-tolerated in drug-refractory symptomatic AF populations (Gold, Sulke, Schwartzman, Mehra & Euler, 2001). The re searchers found that the dual-chamber ICD was successfully implanted in 99% of the samp le (N = 146), and illustrated 98% survival at 12-month follow-up. Additional results i ndicated that 99% of atrial arrhythmias among this sample were correctly predicted by the device, and 87% of atrial arrhythmias were successfully terminated. Perhaps even more critical, 7.6% of the sample required ventricular shocks for VT/VF which would ha ve been fatal (Gold et al., 2001). This study suggests that patients with atrial fibri llation receive substant ial physical benefit from implantable defibrillation devices such as the IAD. Although the IAD has been shown to provide relief from the physical symptoms of AF, to date no study has examined the ps ychological implicatio ns of device therapy for AF patients. An important difference be tween patients with atrial fibrillation and patients with ventricular fibrilla tion is that atrial fibrillation does not present a threat of

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6 immediate death, and a defibrillation charge from the IAD does not represent a lifesaving procedure as it does for ICD patients w ith life-threatening vent ricular arrhythmias. Therefore, the psychological stress associated with receiving a defibrillation shock may be different for IAD patients, a conc ept that was examined in this study. Psychological Effects of Shock Although both the IAD and the ICD have de monstrated to be effective life-saving devices (Gold et al., 2000), researchers continue to examine the issue of patient adaptation to this therapy. Recent studies re veal that there is a strong fear component associated with defibrillation, especia lly among patients receiving multiple shocks (Murgatroyd & Camm, 1997; Sear s, Todaro, Saia Lewis, So tile, & Conti, 1999; Sears & Conti, 2002). A recent major clinical trial, th e CABG Patch Trial, examined the value of prophylactic ICD implantation in patients undergoing coronary ar tery bypass graft surgery versus no ICD after CABG surgery (Namerow, Firth, Heywood Windle, Parides, et al., 1999). Data indicated that the mental and physical quality of life outcomes for the ICD patients were significantly worse compared to no-ICD patients. Further analyses revealed that there were no differences in quality of life for non-s hocked ICD patients vs. no-ICD patients. These results indicated th at the ICD group who had received shocks was responsible for the significantly worse me ntal and physical quality of life outcome scores between the groups. The Antiarrhythmics Versus Implantable De fibrillators (AVID) trial represents the first major comparison of self-percei ved quality of life among ICD patients and antiarrhythmic drug (AAD) therapy patients. AVID researchers concluded that ICD and AAD therapy have similar effects on self-p erceived quality of life among patients with

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7 ventricular arrhythmias. Although all patie nts had poor baseline quality of life, a significant finding was that adverse symptoms we re associated with major impairment in quality of life, regardless of the type of therapy and sporad ic shocks received from the ICD. Specifically, adverse symptoms am ong AAD patients were associated with reductions in physical functioning, and both ph ysical functioning and mental well-being in ICD patients (Schron, Exner, Yao et al ., 2002). The AVID st udy illustrated that frequent ICD shocks (>5) were associated with increased psychological distress and lower quality of life. Additionally, the study de monstrated that ICD patients receiving at least one shock in the first year of fo llow-up had significant declines in physical functioning and mental well-bei ng, along with increased patient concerns. This effect of shock was present independently of other ma rkers of disease severity (Schron et al., 2002). Such research highlights the fact that shock can be a frightening experience for ICD patients, and has implications for cl inical interventions with IAD patients. The Canadian Implantable Defibrillato r Study (CIDS) (Irvine, Dorian, Baker, O’Brien, Roberts, Gent, Newman, & Connolly, 2002) yielded similar results regarding the negative effects of shoc k. In a longitudinal quality of life comparison between shocked vs. non-shocked ICD patients, research ers concluded that non-shocked patients experienced improved quality of life at 2, 6, and 12 months follow-up. More specifically, patients receiving 5 or more shocks with in the first year of device implantation experienced significant declines in generic quality of life (Irvine et al., 2002). These results imply the existence of a “shock thre shold,” or maximum number of shocks that can be tolerated before patient s’ quality of life is significan tly compromised. Conversely, a number of studies have illustrated that shock is not a unique

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8 contributor to decreased psyc hological well-being. Several investigators have examined patients with ICDs and compared them to patients with permanent pacemakers on generic measures of quality of life. Very few cons istent differences were demonstrated between these two populations. For example, Duru a nd colleagues (2001) found no differences in generic quality of life score, anxiety or depression when comparing ICD patients with and without shock experience and pacemaker pa tients. ICD patients with a shock history were more likely to report limitations in leis ure activities and anxiet y about the ICD, but they also viewed the ICD as a “life extender. ” However, this study did not use a diseasespecific quality of life measur e, and therefore measurement may have been too gross to determine a difference between groups. He rbst, Goodman, Feldstein, and Reilly (1999) recently compared the quality of life and psyc hological distress of four patient groups: ICD only (n = 24) vs. ICD + anti-arrhythmic drug (n = 25) vs. anti-arrhythmic drug only (n = 35) vs. a general cardiac sample (n = 73) Quality of life was assessed via the SF-36 and three supplementary scales examining sleep, marital and family functioning, and sexual problems. Comparis ons were made between ICD groups and drug groups. Results indicated that there were no signifi cant differences on the 11 quality of life scales, even after controlling for age, gender, disease severi ty, and duration of treatment. Yet, significant differences were found in drug groups vs. no drug groups, such that the drug treated group consistently reported greater impairm ent in physical functioning, vitality, emotional, and sleep functioning, as well as psycholog ical distress. Overall, these results suggest that quality of life wa s maintained in ICD tr eated groups, while antiarrhythmic drug therapy was associated with diminished quality of life and increased psychological distress.

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9 Although study results vary, it is importan t to recognize that ICD-related fears are universal and may be the most pervasive ps ychosocial adjustment challenge ICD patients face. Psychological theory suggests that sympto ms of fear and anxiety can result from a classical conditioning paradigm in which certain stimuli or behaviors are coincidentally paired with an ICD shock and are thereby avoi ded in the future (Sears & Conti, 2002). Due to fear of present and/or future disc harges, some patients increasingly limit their range of activities and inadvertently diminish the benefits of the ICD in terms of quality of life (Sears & Conti, 2002). Collectively, these data imp licate that the experience of shock is often strongly associated with psyc hological distress and di minished quality of life (Sears et al., 1999). The experience of shock may be di fferent for IAD patients, who have the option of administering the shocks manually, and thus eliminate receiving an unexpected defibrillation charge that may lead to fear or anxiety. Atrial shocks are unpleasant and possibly frequent; subsequently IAD patients are likely to view shock as negatively as ICD patients do, and to expe rience similar symptoms of psychological distress. Depression Depression has been identified as a signifi cant characteristic related to health outcomes among various cardiac populations (Frasure-Smit h, Lesperance, & Talajic, 1995). Among ICD patients, prevalence rates of depressive symp tomatology range from 24% to 87% at various follow-up interval s (Hegel, Griegal, Black & Goulden, 1997; Konstam, Colburn & Butts, 1995; Sears et al., 1999). Early research highlights correlations between declines in physical ability/functioning and the development of depression in ICD patients (Pycha, Gulledge, Hutzler, Kadri, & Maloney, 1986). More

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10 recently, similar findings within the ICD patie nt population indicate that depression and mood disturbance post-implant may increase th e likelihood of an arrhythmia requiring a shock from the device (Dunbar, Kimble, Jenk ins, et al., 1999). Sears and colleagues (1999) postulate that depre ssion among device patients may result from the patient’s perceived lack of control over the defibr illation charges. These symptoms may eventually lead patients to have increased negative beli efs and hopelessness about their current and future health status. This negativ e view of the future is often reflected by a reduction in mental quality of life. A lthough many IAD patients maintain control over when a defibrillation charge is administere d, a single charge may not always correct an atrial arrhythmia. Thus, it is often necessary for IAD patients to experience multiple shocks, contributing to psychological distress (Irvine et al., 2002; Schron et al., 2002). Further, the after-effects of receiving a pain ful shock are likely similar for ICD and IAD patients. Due to the prevalence of depr ession among ICD patients and the relationship between shock, depression, and quality of life, this study predicts that depression among IAD patients will present similarly to ICD patients. Quality of Life To date the largest study examining quality of life among symptomatic AF patients found that both diseas e specific and generic qualit y of life were significantly lower for AF patients than for healthy contro ls (Dorian, Jung, Newman et al., 2000). AF patients scored significantly lower on all scales of the SF-36 except for the Bodily Pain scale. However, much of the current rese arch regarding quality of life among patients with defibrillators has focused on ICD patient s. Although ICD patients primarily report desirable quality of life, it is well establishe d that psychosocial dist ress contribu tes to a

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11 reduction in quality of life (Heller, Orm ont, Lidagoster et al., 1998; Luderitz, Jung, Deister & Manz, 1996; Pycha et al., 1986; Sears et al., 1999, 2000). Among the most common patient complaints regarding quality of life are social is olation, psychological distress, and physical complaints (Heller et al., 1998; Luderitz et al., 1996; Pycha et al., 1986; Sears et al., 1999). Poorer quality of life is more prevalent among patients who receive shocks from the ICD as compared to patients who have not received shocks from the ICD (Dunbar et al., 1999; Heller et al., 1998; Herbst et al., 1999; Kohn, Petrucci, Baessler, Soto & Movsovitz, 2000; Reid, Na gy & McKinley, 1999; Sears et al., 1999). Because shock has been established as a negative experience (Namerow et al., 1999; Sears et al., 1999; Sears & Con ti, 2002), it may be hypothesized that patients receiving shocks will also experience higher levels of illness intrusiveness as compared to patients who have received no shocks, which has been sh own in previous research (Schron et al., 2002; Irvine et al., 2002). Therefore, this study examined the relationship between factors affecting illness intrusiveness a nd subsequent quality of life within a biopsychosocial model that accounted for bot h psychological and medical data. Illness Intrusiveness The construct of illness intrusiveness is described as lifestyle disruptions, resulting from an illness and/or its treatment, that hinder participation in valued activities and interests (Devins et al., 1983). Because illness intrusiveness lim its participation in valued activities, it may in t urn decrease psychosocial well-being as it lowers an individual’s exposure to positively-valued inte ractions. Illness intrusiveness may cause further psychosocial decline by reducing an individual’s pe rsonal control over both

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12 positive and negative outcomes in important si tuations, especially among patients with chronic conditions (Devins et al., 1993). Studies indicate varying degrees of i llness intrusiveness across treatment modalities and illnesses (Dev ins et al., 1993). Among chr onic illness populations, a number of illness-related factors contribute to the construct of illness intrusiveness, including disease factors, such as pain and di sability, and treatment factors such as time required for treatment and mode of treatme nt (Devins, 1994). Illness intrusiveness among chronic illness populations has been shown to have a significant and unique relationship to several psychological variab les, including positive and negative mood, life satisfaction, and depression, and is furthe r influenced by psyc hological and social characteristics such as social support and c oping resources (Binik, Devins & Orme, 1989; Devins, 1994). Devins’ (1994) model hypothesizes that factors of an individual’s disease and treatment psychosocially impact quality of life through their relationship with illness intrusiveness. The model also accounts for direct effects of psychological and social factors on both illness intrus iveness and quality of life. Research on illness intrusiveness among AF patients found that symptomatic AF patients had significantly higher illness intrusiveness than same-aged non-AF patients (Dorian et al., 2002). Consistent with Devins ’ model, this study also found lower quality of life on several SF-36 scales among AF patients as compared to angioplasty, myocardial infarction and congestive heart fa ilure patients, even when controlling for physical impairment (Dorian et al., 2002). Despite AF patient s experiencing a variety of physical symptoms, these data suggest that psychological distress is an equally limiting aspect of the condition. The influence of psychological constructs such as illness

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13 intrusiveness on quality of lif e often overpowers the influence of AF’s unique physical limitations, and emphasizes the importance of psychological intervention in conjunction with standard medical care for AF patients. In this regard, illness intrusiveness emerges as an important target for multidisciplinary interventions. Relationship Between Illness Intrus iveness and Quality of Life The Devins (1994) model stems from re search involving the role of illness intrusiveness in quality of life among E nd-Stage Renal Disease patients, and has indicated that perceived illness intrusiveness was significantly correlated with three quality of life measures including satisfaction/happiness, pessimism/illness-related concerns, and depression/distr ess (See Figure 1; Devins, Mandin, Hons et al., 1990). Specifically, higher levels of perceived illness intrusiveness were significantly correlated with decreased life satisfaction and happiness, increased pessimism and illness-related concerns, and increased depressi on and distress. These results remained stable over time, even after controlling for re sponse style and background variab les (Devins et al., 1990). Similarly, an additional study with rheumatoid arthritis patients reve aled a statistically significant relationship between illness intrusiveness and phys ical disability, such that after controlling for physical disability, illness intrusiveness maintained a unique, significant relationship with depression (Devins, Edworthy, Guthrie et al., 1992). These data illustrate the role of illness intrusiveness as a mediator of the psychosocial impact of chronic illness, although no study to date has ex amined this potentially valuable construct in IAD patients. The current study will examine illness intrusiveness among IAD patients using analyses influen ced by Devins’ (1994) model.

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14 Quality of life Psychological & Social Factors Figure 1. Hypothesized relations among illness intrusiveness, its determinants, and quality of life in AF patients (Devins, 1994). Aims and Study Justification The purpose of this study was to test a biopsychosocial model of illness intrusiveness and quality of life in a sample of drug-refractory IAD patients. Using hierarchical multiple regression analyses controlling for demographic and biomedical data, this study explored predictors of illness intrusiveness and physical and mental quality of life. This model was adapted to identify areas of possible psychological intervention among IAD patients. Hypotheses The following hypotheses were investigated in this study: 1. It was hypothesized that CES-D ratings of depression would be significantly associated with Illness In trusiveness Rating Scale scor es among IAD patients, while controlling for demographics, number of shocks, and biomedical variables. 2. It was hypothesized that Illness Intrusiven ess Rating Scale scores would significantly predict variance in the Physical Functioning Scale of the SF-36 Quality of life Measure Treatment Factors Illness Intrusiveness Disease Factors

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15 among IAD patients, while controlling for demo graphics, number of shocks, biomedical variables, and psychol ogical variables. 3. It was hypothesized that CES-D ratings of depression would significantly predict variance in the Mental Scale of the SF-36 Quality of life Measure among IAD patients, while controlling for demographics, number of shocks, biomedical variables, and psychological variables.

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16 CHAPTER 2 METHOD Participants The participants (N = 96 ) were recruited from an ongoing multi-site FDA study spanning 23 IAD-implanting facilities. Part icipants were recruited by the research coordinator at each implanting facility. Each participant had undergone a full medical workup prior to recruitment. In order for a patient to qualify for incl usion in the study, he/she must have had lone AF, indicating AF was his/her only major h eart condition. All par ticipants were also drug-refractory, defined as having tried and failed at le ast one anti-arrhythmic drug within the year prior to the study. Participants must ha ve had at least one AF episode lasting 48 hours. At the time of the study, all subjects were taking an anti-coagulant such as warfarin. Particpant exclusion crite ria included documented risk of sudden death from ventricular fibrillation, which w ould indicate implantation of a traditional ICD. Table 1 provides a summary of the dem ographic and medical characte ristics of the study sample.

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17 Table 1. Patient Demographics a nd Relevant Medical Variables Mean (SD) or % Total (N = 96) Manual Shock (n = 42) Automatic Shock (n = 35) Demographics Age 62.2 (11.8) 59.8 (12.1) 64.3 (10.9) Gender (% Male) 72% 64% 80% Marital Status (% Married) 83.3% 83.3% 82.9% Ejection Fraction (N = 54) 52.1 (15.8) 56 (15.1) 45.3 (15.6) Pre-Implant Cardioversions 2.2 (2.1) 2.2 (2.1) 2.1 (2) Pre-Implant AF episodes 9.1 (13) 8.4 (12.3) 12.5 (20.7) AF Symptom Score 15.6 (8.49) 14.4 (8.2) 18.2 (9.2) Device Data Years Since Implant 1.6 (.87) 1.6 (.84) 1.6 (.81) Detected AF Episodes 176 (337) 167 (306) 191 (337) Total Atrial Shocks 12.8 (18.4) 13 (21.1) 12.5 (14.9) Manual Shock/month 0.93 (2.7) 1.4 (3.5) 0.46 (1.3) Automatic Shock/month 0.22 (.76) 0.0 (0.0) .57 (1.2) Atrial Shock Energy (J) 15.2 (7.8) 15 (7.9) 15.9 (7.9) Note : 18 patients did not receive any shocks or receive d both manual and automatic shocks, and therefore were not included in the statistical analyses

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18 Assessment Generic Quality of Life The Medical Outcomes Study Short-Form 36 Health Survey (SF-36; Ware, Snow, Kosinski & Gandek, 1993) was used to measure quali ty of life. This is a widely used and well-validated generic measure of health-related quality of lif e, and was shown to be the most effective measure for evaluating quali ty of life among pacemaker patients in a recent comparison study (Stofmeel, Post, Kelder et al., 2000). Because of its widespread application to cardiac patients and its role in validating othe r measures of cardiac illness, the SF-36 has become the standard measure of quality of life among cardiac populations (Stofmeel, et al., 2001; Hamilton & Haennel, 2000). Items included in the SF-36 were constructed by Ware and colleagues (1993), who used a sample of over 20,000 U.S. residents to assess perceptions of 40 mental and physical health concepts in the Medical Outcome Study (MOS). The SF-36 contains sc ales to measure the eight most salient concepts represented by this survey: Physi cal Functioning, Physical Role, Bodily Pain, General Health, Vitality, Soci al Functioning, Emotional Role and Mental Health. To avoid inflating experiment-wise error, the current study examined scores on only three scales of the SF-36: Physical Functioni ng, Mental Health, and Social Functioning. Center for Epidemiological Studies Depression Scale Depression was measured using the Ce nter for Epidemiological Studies – Depression Scale (CES-D), a 20-item self-report measure of depressive symptomatology (Radloff, 1977). Participants are asked how frequently over the past week they have experienced various depressive symptoms, a nd responses range from 0 (less than one day) to 3 (5-7 days). Total scores range fr om 0 to 60, and a standard cut-off score of 16

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19 indicates clinically signifi cant depressive symptoms (Radloff, 1977). The CES-D reflects the number and duration of depressive symptoms. The CES-D has a high internal reliability coefficient of .85, and has been repo rted as a more generally useful self-report measure of depression than the Beck Depre ssion Inventory, the MMPI Depression Scale, and the Zung Self Rating Scale of Depression (Turk & Okifuji, 1994). Illness Intrusivenss Rating Scale The Illness Intrusiveness Rating Scale (IIRS; Devins, Orme &Costello, 1988) is a 19-item self-report measure that asks responde nts to rate how much their illness and consequent treatment interferes with each of 13 life domains. Ratings occur along a 7point Likert scale, ranging from 1 (Not Very Much) to 7 (Very Much). The domains pertain to health, recreation, diet, work, financial situa tion, self-expression, family relations, relations with spouse, sex life, social relations, reli gious expression and community involvement. A total intrusiven ess score and a scor e for each of the 13 domains can be calculated. Tota l scores range from 13 (where the illness is not intrusive) to 91 (where the illness is extremely intr usive in all domains). Exploratory and confirmatory factor analyses across eight di fferent patient groups have revealed three underlying factors comprising the scale (Rel ationships and Personal Development, Intimacy, and Instrumental Life Domains). Re cent research indicates that the total IIRS score may be preferable for use in basic analyses (Devins et al., 2001). The IIRS has been shown to have adequate to high inte rnal consistency, reliability, and validity (Devins et al., 1993). Coefficient alpha ranges from 0.80 to 0.95 have been found across diagnoses (Devins et al., 2001).

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20 State-Trait Anxiety Inventory The STAI is a 40-item self-report ques tionnaire designed to measure both state and trait anxiety (Speilberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983). For the purposes of this study, only the 20-item trait sc ale of this questionnaire was administered. Trait anxiety is defined as a relatively e nduring personality characteristic, or more specifically, as anxiety proneness. The intern al reliability of both the state and trait anxiety scales has been shown to be unifo rmly high across samples of adults ranging from .89 to .96. Test-retest re liability coefficients for multiple samples of college students ranged from .73 to .86, with test-rete st validity specifically for the trait scale being reported at .73 for males and .77 for fe males. Concurrent validity between the STAI and IPAT Anxiety Scale and the Taylor Manifest Anxiety Scale ranged from .83 to .73 (Spielberger et al., 1983). Pain and Intensity Ratings Subjective ratings of pain and intensity were taken from the Patient Acceptance Scale (PAS), which provides statements about the pain and intensity of a defibrillation charge, and provides responses ranging from Strongly Disagree to Strongly Agree (Burns et al., 2002). Device Data Information was collected to address seve ral aspects of pati ents’ IAD history. The device data included number of years sin ce device implantation at the time of survey, number of treated episodes, and number of manual and auto matic shocks received per month.

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21 Demographic Measures This measure was developed to assess: marital status, age, religion, ethnicity, education level, employment status, number of doctor visits, exercise habits, smoking habits and alcohol consumption. This study used baseline data for quality of life measures only. All other data was collected at the follow-up in the closest proximity to the survey data (M = 4.7 months since last device interrogation, SD = 2.8 months).

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22 CHAPTER 3 RESULTS Sample Descriptives Illness intrusiveness scores for this sample ranged from 13 to 73 (M = 27; SD = 14). Additional descrip tive data was gained by using t-tests to compare this sample with the group of End Stage Renal Disease patients upon which Devins’ (1994) original work was based. The IAD sample’s mean illness intrusiveness rating was significantly lower than a published mean for pati ents receiving hemodialysis (p < .001), but not significantly different from a published mean for patients of successful renal transplantation (p = .504; Devins, 1994). In the present sample, 42% had illness intrusiveness scores above cut-off scores fo r an AF-only sample, but sample differences were insignificant. Results also indicate that IAD recipients may experience levels of illness intrusiveness similar to those experien ced by transplant recipients. Thus, the IAD may be considered analogous to a lifesavi ng “organ” which is cap able of prolonging and improving life. Additional descrip tive data was comput ed using t-tests. CES-D scores (M = 11.1; SD = 8.5; n = 81) were significantly different from healthy normals (M = 9.3; SD = 8.6; p < 0.05), although these differences are lik ely not clinically significant (Radloff, 1977). Regarding anxiety levels, the STAI scores of this sample (M = 33.9; SD = 10.8; n = 88) were not significantly different from sc ores of healthy normals (healthy males, M =

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23 34.9; SD = 9.9; healthy females, M = 34.8; SD = 9.2) (Speilberger, Gorsuch, Lushene, Vagg & Jacobs, 1983). Mean total symptom score (16.0) and mean AF symptom number (8.2) was also calculated. Means for all pa rticipants in this study are located in Table 2. Table 2. Means for Psychosocial Measures M SD n Min. Max. Depression (CES-D) 11.07 8.57 81 0 35 Trait Anxiety (STAI) 33.99 10.8 88 20 70 Illness Intrusiveness (IIRS) 27.00 14.4 93 13 73 Quality of life (SF-36) Physical 67.01 25.5 82 15 100 Mental 72.76 17.7 84 16 100 Total Symptom Score 15.95 8.50 82 1 41 Total Symptom Number 8.16 3.37 83 1 12 Correlations and Collinearity Evaluation Correlations were run among several of th e independent and dependent variables to determine the inter-correlations between variables. These results are presented in Table 3. Although there were significant correlations between some psychosocial variables, none exceeded r >.7, which is a cut-off to determine multicollinearity (Kleinbaum, Kupper, Muller & Nizam, 1998). Th erefore, all variable s were included in the planned analyses. Regression Analyses: Illness Intrusiveness A three-step multiple hierarchical regression analysis was conducted to examine the relationships between demographic, shoc k, and symptom variables, along with patient ratings of pain and discomfort, and the psychological construct of illness intrusiveness as

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24 the dependent variable. Speci fically, number of shocks and AF symptom score were included as disease-specific fact ors that may influence illness intrusiveness. Significance was set at alpha = .05. Table 3. Correlations of Ke y Assessment Instruments ________________________ CES-D IIRS Physical Mental Scale Scale CES-D ____ IIRS .447** ____ Physical -.298* -.263* ____ Scale Mental -.604** -.275* .300** ____ Scale ** Correlation is significant at the 0.01 level (2-tailed). Correlation is significant at the 0.05 level (2-tailed). On the first step of the analysis, sex a nd age were insignificant predictors of illness intrusiveness (F change (2, 52) = 1.847, p = .168), accounting for 6.6% of the variance. Number of manual and automatic at rial shocks, AF symptom score, and patient ratings of pain and discomfort were entere d on the second step of the analysis. These factors contributed 18.3% of variance, a lthough this variance was not significant (F change (5, 47) = 2.295, p = .060). On step three, CES-D scores were entered, significantly predicting 11.4% of varian ce in illness intrusiveness scores (F change (1, 46) = 8.202, p = .006). Specifically, higher depression was associated with higher illness intrusiveness. The overall model was significant (F (8, 54) = 3.279, p = .005), and accounted for 36.3% of variance in illness intrusiveness.

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25 Table 4. Regression Analysis : Illness Intrusiveness. Model R Square Change F Change df1 df2 Sig F Change 1 .066 1.847 2 52 .168 2 .183 2.295 5 47 .060 3 .114 8.202 1 46 .006 Regression Analyses: Physical Quality of Life A three-step multiple hierarchical regression analysis examined demographics, baseline physical quality of life scores, number of atrial shocks, and psychological variables (depression and illness intrusiveness) with post physical quality of life as the dependent variable. Pain and discomfort we re excluded since they failed to contribute significant variance to illness intrusiven ess in the presence of depression (F change (5, 47) = 2.295, p = .060). In step one of the analys is, baseline physical quality of life scores, age and sex were not significant predicto rs of post physical quality of life (F change (3, 64) = 1.634, p = .190). Step two of the analysis included number of total atrial shocks, which also failed to c ontribute signif icant variance (F change (1, 63) = .608, p = .439). Psychological variables (d epression and illness intrusiven ess) were entered on the third step of the analysis; they sign ificantly added 12.0% of the variance (F change (2, 61) = 4.575, p = .014). Specifically, higher age and hi gher illness intrus iveness predicted lower post physical quality of life. Therefor e, illness intrusiveness uniquely predicted post physical quality of life above and be yond a host of demographic, biomedical, and psychological variables. The ove rall model significantly acco unted for 20.0% of variance in post physical quality of life (F (6, 67) = 2.542, p = .029).

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26 Table 5. Regression Analysis: Physical Quality of Life. Model R Square Change F Change df1 df2 Sig F Change 1 .071 1.634 3 64 .190 2 .009 .608 1 63 .439 3 .120 4.575 2 61 .014 Regression Analyses: Me ntal Quality of Life The last three-step multiple hierarchi cal regression was conducted to examine demographic, baseline mental quality of life scores, total atrial s hocks and psychological variables (depression and illness intrusiveness), with post mental quality of life as the dependent variable. On step one, baseline me ntal quality of life, sex, and age did not contribute significant variance in post mental quality of life (F change (3, 64) = .814, p = .491). Step two included total atrial shocks, which also fa iled to explain significant variance in post mental quality of life (F change (1, 63) = .029, p = .865). Depression and illness intrusiveness were entered on the third step of the anal ysis, and significantly predicted post mental quality of life (F change (2, 61) = 15.412, p < .001), contributing 32.3% of the variance. Specifically, higher depression was associated with lower post mental quality of life. The overall model acc ounted for 36% of variance in post mental quality of life (F (6, 67) = 5.729, p < .001). As stated earlier, multicollinearity statistics were calculated to ensure that these results were not influenced by the correlation between depression and mental quality of life. The tolera nce value (.774) indicates an acceptable correlation level (Kle inbaum et al., 1998). Therefore, depression uniquely predicted mental quality of life within this biopsychosocial model, but no demographic or

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27 disease-specific variables were significant pr edictors of mental quality of life. The overall model accounted for 36.0% of variance in post mental quality of life. Table 6. Regression Analysis: Mental Quality of Life. Model R Square Change F Change df1 df2 Sig F Change 1 .037 .814 3 64 .491 2 .000 .029 1 63 .865 3 .323 15.412 2 61 .000

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28 CHAPTER 4 DISCUSSION The current study investigated the utility of Devins’ (1994) biopsychosocial model regarding the relationships between ps ychological variables and their influence on physical and mental quality of life within a sample of IAD patients. It was hypothesized that the psychological constructs of depression and illness intrusiveness would impact physical and mental quality of life above and beyond the influence of demographic, biomedical and disease-related variables. A series of three-step multiple hierarchical regression analyses indicated that the hypotheses regarding the impact of depression on illness intrusiveness and mental quality of lif e, and the impact of illness intrusiveness on physical quality of life were supported. Previous research in similar populations has established that depression and illness intrusiveness are related constructs (H egel et al., 1997; Konstam et al., 1995; Sears et al., 1999). This study extends the literature to include IAD patients, who have been shown to have unique psychological distress asso ciated with their condition (Kay et al., 1998). A decline in physical abil ities that hinders participatio n in valued activities is an integral part of Devins ( 1983) definition of illness intrusiveness. IAD patients whose illness causes a decline from previous functi oning may subsequently develop depression, and view their illness as more intrusive. The correlation between illness intrusiveness

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29 and physical quality of life is consistent with Devins’ (1983) theory that the construct of illness intrusiveness is a disruption of lifesty le that hinders participation in valued activities. Patients whose functioning is si gnificantly limited due to their illness will most likely report a reduction in the quality of their physical abiliti es. Additionally, the correlation and predictive relatio nship between the psychological construct of depression and mental quality of life is consistent with Devins’ (1983) biopsychosocial model. With regard to the relationships between disease, treatment, and psychological factors, this sample of IAD patients rated illness intrusiven ess and quality of life similarly to the EndStage Renal Disease patients comp rising Devins’ original sample. Implications for the Experience of Shock Collectively, these results suggest that shoc k is not the factor most responsible for reducing quality of life among IAD patients as it has been illustrated to be among ICD patients (Namerow et al., 1999; Schron et al., 2002; Irvine et al., 2002) This discrepancy may result from differences in perceived lack of control between these two populations. IAD patients have the option of delivering th e defibrillation charge manually, whereas all shocks received by ICD patients are automatica lly received with little warning. Since AF is not a life-threatening c ondition, IAD patients also have the option of avoiding the defibrillation charge and experiencing the AF episode. In this way, IAD patients are able to mentally separate the act of shock from other physical as pects of their illness. Even IAD patients who receive automatic shocks can receive advanced warning and therefore maintain a sense of control. Further, a defibrillation charge for IAD patients does not indicate a life-threaten ing arrhythmia as it does for IC D patients, suggesting that ICD patients may have a more emotional response to shock.

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30 Most of the literature in this area indicat es that, overall, shock is a physically aversive experience (Murgatroyd & Camm, 199 7; Sears et al., 1999; Sears & Conti, 2002; Namerow et al., 1999; Schron et al., 2002). Pauli and colleagues’ (1999) research clarified and disputed this idea by distinguish ing the psychological e ffects of shock from the physical effects. The pr esent study, in conjunction wi th the work of Pauli and colleagues (1999), indicates that IAD recipients will benefi t from being psychologically prepared for the emotional impact of defibril lation. Results suggest that IAD therapy is well accepted, but may be hindered by psyc hological factors such as depression. Depression and illness intrusiveness are re lated among IAD patients, lending support to early research among ICD patients that high lights correlations between declines in physical ability and the development of depre ssion (Hegel et al., 1997; Konstam et al., 1995). Most patients who are provided with appropriate cognitive-behavioral interventions should adapt well to receivi ng an IAD, and will likely not experience clinically significant levels of depression, illness intrusivenes s, or reduced quality of life (Kohn et al., 2000). Clinical Implications Clinically, this study highlights the need for healthcare providers to recognize, acknowledge, and refer psychological treatme nt for symptoms of distress among IAD patients in an attempt to reduce illness intr usiveness and optimize quality of life. The majority of these patients do not experience clinically significant depression or illness intrusiveness, but those who do will likely also experience reductions in physical and mental quality of life. Clinicians should be educated about the effects that psychological factors have on quality of life, and subsequently pay routine attention to both general and

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31 disease-specific quality of life among IAD pa tients. Since AF is a non-life-threatening condition, IAD patients can experience improved qua lity of life through various levels of psychosocial intervention, such as in-patient psychologica l consultation, support groups with other patients, and individual psychotherapy. This process will be facilitated by the integration of psychologists as essential pa rts of IAD patient treatment teams, and by future research exploring additional asp ects of defibrillation, including a comparison between the patient’s subjective experience of shock and the objective shock data recorded by the device Strengths and Weaknesses of the Study The current study has specific strengths and weaknesses to take into account when interpreting this data. The comprehens ive biopsychosocial design including both objective medical information and subjective psychological testing da ta provide a more complete view of the outcomes of interest th an previous work with the IAD designed to establish its efficacy (Gold, et al., 2001). Fu rther, the effects of shocks were well examined in the current data set and did not indicate the cumulative, detrimental effects that one might expect. A weakness of th e study includes the highly selected sample utilized. Patients in this study were volunteers who were drug-refractory and failed at least one anti-arrhythmic drug. Therefore, the results cannot be generalized to all patients with AF. The willingness to part icipate as a subject in this tr ial certainly selects for some personality variables that cannot be fully understood. The study also included baseline medical variables but did not in clude baseline psychosocial vari ables other than quality of life. In fact, because FDA investigators did not expect the signifi cance of psychological factors at the beginning of th e study, the remaining psychosocial factors are measured at

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32 only a single point in time. Th erefore, we are unable to determine the course of patient acceptance from the current data.

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33 LIST OF REFERENCES American Heart Association. (2001). About sudden death and cardiac arrest. In 2001 Heart and Stroke Statistical Update [On-line]. Available: www.americanheart.org/statistics/aboutsdca.html Last accessed 1/15/03. Allan, R. & Scheidt, S. (1996). Hear t & Mind: The Practice of Cardiac Psychology. Washington: American Psychological Association. Bennett, P. & Carroll, D. (1994) Cognitiv e-behavioral interventions in cardiac rehabilitation. Journal of Psychosomatic Research, 38 (3), 169-182. Binik, Y.M., Devins, G.M. & Orme, C.M. (1989). Psychological stress and coping in end-stage renal disease. In: Neufeld, R.W. J. (Ed.), Advances in the Investigation of Psychological Stress New York, NY: Wiley, 305-342. Burns, J.L., Sears, S.F., Sotile, R., Schwartzman, D.S., Hoyt, R.H., Alvarez, L. & Ujhelyi, M.R. (2002). Do patients accept impl antable atrial defibr illation therapy? Results from the Patient Atrial Shock Su rvey of Acceptance and Tolerance Study (PASSAT Study). (In Press). Canobbio, L., Fassio, T. & Gasparini, G. (1986). Cardiac arrhythmia: Possible complication from treatment with cisplatin. Tumori, 72 (2), 201-204. Davidson, T., VanRiper, S., Harper, P., & Wenk, A. (1994). Implantable cardioverter defibibrillators: A gui de for clinicians. Heart & Lung, 23 205-215. Devins, G.M (1994). Illness intrusiveness a nd the psychosocial impact of lifestyle disruptions in chronic lifethreatening disease. Advances in Renal Replacement Therapy, 1 251-263. Devins, G. M., Binik, Y. M., Hutchinson, T. A., Hollomby, D.J., Barre, P.E. & Guttmann, R.D. (1983). The emotional impact of end-stage renal disease: Importance of patients’ perceptions of in trusiveness and cont rol. International Journal of Psychiat ry in Medicine, 13 327-343.

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34 Devins, G.M., Dion, R., Pelletier, L.G., Shapiro, C.M., Abbey, S., Raiz, L.R., Binik Y.M., McGowan, P., Kutner, N.G., Beanlands, H. & Edworthy, S.M. (2001). Structure of lifestyle disruptions in chronic disease: A confirmatory factor analysis of the illness intrusiven ess ratings scale. Medical Care, 39 (10), 10971104. Devins, G.M., Edworthy, S.M., Guthrie, N.G. & Martin, L. (1992). Illness intrusivenes in rheumatoid arthritis: Differential imp act on depressive symptoms over the adult lifespan. Journal of Rheumatology, 19 709-715. Devins, G. M., Edworthy, S. M. & Se land, T. P. (1993). Differences in illness intrusiveness across rheumatoid arthritis, end-stage renal disease, and multiple sclerosis. Journal of Nervous & Mental Disease, 181 377-381. Devins, G.M., Mandin, H., Hons, R.B., Burgess, E.D., Klassen, J., Taub, K., Schorr, S., Letourneau, P.K. & Buckle, S. (1990). Il lness intrusiveness an d quality of life in end-stage renal disease: Comparison a nd stability across treatment modalities. Health Psychology, 9 (2), 117-142. Devins, G.M., Orme, C.M. & Costello, C. G. (1988). Measuring depressive symptoms in illness populations: Psychometric prope rties of the Center for Epidemiologic Studies Depression (CES-D) scale. Psychology & Health, 2 139-156. Dorian, P., Jung, W., Newman, D., Paquette, M., Wood, K., Ayers, G.M., Camm, J., Akhtar, M. & Luderitz, B. (2000). The impair ment of health-relat ed quality of life in patients with intermittent atrial fibril lation: Implications fo r the assessment of investigational therapy. Journal of th e American College of Cardiology, 36 (4), 1303-1309. Dunbar, S. B., Kimble, L. P., Jenkins, L. S., Hawthorne, M., Dudl ey, W., Slemmons, M., & Langberg, J. L. (1999). Association of m ood disturbance and arrhythmia events in patients after cardiovert er defibrillator implanta tion. Depression and Anxiety, 9 163-168. Duru, F., Barton, M., Luscher, T.F. & Ca ndinas, R. (2001). Endothelin and cardiac arrhythmias: Do endothelin antagoni sts have a therap eutic potential as antiarrhythmic drugs? Card iovascular Research, 49 (2), 272-280. Frasure-Smith, N., Lesperance, F., & Tala jic, M. (1995). The impact of negative emotions on prognosis following myocardial infarction: Is it more than depression? Health Psychology, 14 (5), 388-398. Gold, M.R., Brockman, R., Peters, R.W., Olsovsky, M.R. & Shorofsky, S.R. (2000). Aucte hemodynamic effects of right vent ricular pacing site and pacing mode in patients with congestive heart failure sec ondary to either ischemic or idiopathic dilated cardiomyopathy. The American Journal of Cardiology, 85 (9), 1106-1109.

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35 Gold, M.R, Sulke, N., Schwartzman, D.S., Mehra, R. & Euler, D.E. (2001). Clinical experiences with a dual-chamber implantabl e cardioverter defibrillator to treat atrial tachyarrhythmias. Journal of Cardiovascular Electrophysiology, 12 12471253. Hamilton, D.M. & Haennel, R.G. (2000). Validity and reliability of the 6-minute walk test in a cardiac rehabi litation population. Journal of Cardiopulmonary Rehabilitation, 20 (3), 156-164. Hegel, M.T., Griegal, L.E., Black, C. & G oulden, L. (1997). Anxi ety and depression in patients receiving implanted cardioverter defibrillators: A longitudinal investigation. Internat ional Journal of Psychiatry in Medicine, 27 57-69. Heller, S. S., Ormont, M. A., Lidagoster, L ., Sciacca, R. R., & Steinberg, J. S. (1998) Psychosocial outcome after ICD implan tation: A current perspective. Pacing and Clinical Electrophysiology, 21 1207-1215. Herbst, J. H., Goodman, M., Feldstein, S., & Reil ly, J. M. (1999). Health-related quality of life assessment of patients with life -threatening ventricula r arrhythmias. PACE, 22 (I), 915-926. Hill, D.R., Kelleher, K. & Shumaker, S.A. (1992). Psychosocial interventions in adult patients with coronary heart disease a nd cancer. General Hospital Psychiatry, 14S 28S-42S. Irvine, J., Dorian, P., Baker, B., O’Brien, B.J., Roberts, R., Gent, M., Newman, D. & Connolly, S.J. (2002). Quality of life in the Canadian Implantable Defibrillator Study (CIDS). American Heart Journal, 144 (2), 282-289. Kay, G. N., Ellenbogen, K. A. & Giudici, M. (1998). The Ablate and Pace Trial: A prospective study of cat heter ablation of the AV conduction system and permanent pacemaker implantation for treatm ent of atrial fibrillation. Journal of Interventions in Ca rdiac Electrophysiology, 2 121–135. Kleinbaum, D.G., Kupper, L.L., Muller, K. E. & Nizam, A. (1998). Applied Regression Analysis and Other Multivariable Methods CA: Brooks/Cole Publishing Company. Kohn, C. S., Petrucci, R. J., Baessler, C., Sot o, D. M., & Movsovitz, C. (2000). The effect of psychological intervention on patients’ long term adjustment to the ICD: A prospective study. PACE, 23 450-456. Konstam, V., Colburn, C. & Butts, L. ( 1995). Psychosocial adaptation of automatic implantable cardioverter defibrillato r recipients – Implications for the rehabilitation counselor. Journal of Applied Rehabilitation Counseling, 26 19-22.

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36 Linden, W., Stossel, C. & Maurice, J. (1996) Psychosocial interven tions for patients with coronary artery disease. Ar chives of Internal Medicine, 156 745-752. Lip, G.Y.H. (2001). Atrial Fibril lation in Clinical Practice London: Martin Dunitz. Luderitz, B. & Jung, W. (2000). Quality of li fe in patients with atrial fibrillation. Archives of Internal Medicine, 160 1749 – 1757. Luderitz, B., Jung, W., Deister, A., & Manz, M. (1996). Chapter 18: Quality of life in multiprogrammable implantable cardioverter-defibrillator recipients. In S. Saskena & B. Luderitz (Eds.), Inte rventional electrophysiology: A textbook (2nd ed.). Armonk, NY: Futura Publishing, 305-313. Murgatroyd, F.D. & Camm, A.J. (1997). Nonpharmacological Management of Atrial Fibrillation. NY: Futura Pub. Co. Namerow, P.B., Firth, B.R. & Heywood, G.M. (1999). Quality of life six months after CABG surgery in patients randomized to ICD versus no ICD therapy: Findings from the CABG Patch Trial. Pa cing and Clinical Electrophysiology, 22 1305 1313. Pauli, P., Wiedemann, G., Dengler, W., Benninghoff, G.B. & Kuhlkamp, V. (1999). Anxiety in patients with an automatic im plantable cardioverter defibrillator: What differentiates them from panic pa tients? Psychosomatic Medicine, 61 69-76. Pycha, C., Gulledge, A. D., Hutzler, J., Ka dri, N., & Maloney, J. (1986). Psychosocial responses to the implantable defi brillator: Preliminary observations. Psychosomatics, 12 841-845. Radloff, L.S. (1977). The CES-D Scale: A self -report depression scale for research in the general population. Applied Psychological Measures, 1 (3), 85-401. Reid, S. S., Nagy, S., & McKinley, S. (1999). Outcomes, problems, and quality of life with the implantable cardioverter defibr illator. Australian Jo urnal of Advanced Nursing, 16 (4), 14-19. Schron, E.B., Exner, D.V., Yao, Q., Jenkins, L.S., Steinberg, J.S., Cook, J.R., Kutalek, S.P., Friedman, P.L., Bubien, R.S., Page, R.L. & Powell, J. (2002). Quality of life in the antiarrhythmnics versus implantable defibrillators trial: Impact of therapy and influence of adverse symptoms a nd defibrillator shocks. Circulation, 105 (5), 589-594. Sears, S.F. & Conti, J.B. (2002). Current views on the quality of life and psychological functioning of implantable cardiovert er defibrillator patients. Heart, 87 488-493.

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37 Sears, S.F., Todaro, J.F., Saia Lewis, T., Sotile, W.M. & Conti, J.B. (1999). Examining the psychosocial impact of the implantable cardioverter defibrillator: A literature review. Clinical Cardiology, 22 481-489. Spielberger, C.D., Gorsuch, R.L., Lushene, R., Vagg, P.R. & Jacobs, G.A. (1983). Manual for the State-Trait Anxiety In ventory (Self-Evaluation Questionnaire: Form Y) Palo Alto: Consulting Psychologist Press, Inc. Stofmeel, M. A., Post, M. W. & Kelder, J. C. (2000). Quality of life of pacemaker patients. Pacing and Clinical Electrophysiology, 23 946-952. Turk, D. C. & Okifuji, A. (1994). Detec ting depression in chr onic pain patients: Adequacy of self-report. Beha vior Research and Therapy, 32 9-16. Ware, J.E., Snow, K., Kosinski, M. & Gandek, B. (1993). SF-36 Health Survey: Manual and Interpretation Guide Boston: Nimrod Press. Wellens, H.J., Lau, C.P., Luderitz, B., Akhtar, M., Waldo, A.L., Camm, A.J., Timmermans, C., Tse, H.F., Jung, W., Jordaens, L. & Ayers, G. (1998). Atrioverter: An implantable device for the treatment of atrial fibrillation. Circulation, 98 (16), 1651-1656.

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38 BIOGRAPHICAL SKETCH Rebecca Owen Sotile was born in Winston-Salem, NC on January 1st, 1979, to Wayne and Mary Sotile. She has one younger si ster, Julia, with whom she remains very close. She received a Bachelor of Arts in psychology from the University of North Carolina at Chapel Hill in 2001. She is curren tly living in Gainesville, FL, pursuing her Ph.D. in clinical and health psychology at the University of Florida Health Science Center. Her future plans include mastery of clinical and research skills with a focus on health psychology.


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Title: Depression and Illness Intrusiveness as Predictors of Quality of Life Among Implantable Atrioverter Defibrillator Recipients
Physical Description: Mixed Material
Copyright Date: 2008

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DEPRESSION AND ILLNESS INTRUSIVENESS AS PREDICTORS OF QUALITY
OF LIFE AMONG IMPLANTABLE ATRIOVERTER DEFIBRILLATOR
RECIPIENTS















By

REBECCA OWEN SOTILE


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA


2003




























Copyright 2003

by

Rebecca O. Sotile















ACKNOWLEDGMENTS

I would like to thank my mentor, Dr. Samuel F. Sears, for his constant guidance,

support, and understanding. I would also like to thank my first-year lab mates, Jason and

Robyn, for all of their advice, support, and, most of all, for their laughter. My

acknowledgments also go to Eva for her constant encouragement and willing assistance.

I would also like to thank my committee, Drs. Stephen Boggs, Dawn Bowers, and Robert

Glueckauf, for their general support as well as their specific suggestions and

contributions. My thanks also go to my boyfriend, Tom Horsman, for his love, courage,

and the countless positive things he has brought to my life. Also I thank my sister, Julia,

for being my best friend, my greatest source of comfort, and my most valuable point of

perspective. My utmost thanks go to my parents, Wayne and Mary Sotile, for their

incredible love and acceptance of who I am, and faith in the person I am becoming.
















TABLE OF CONTENTS

Page

A C K N O W L E D G M E N T S ......... .................................................................................... iii

L IST O F TA B L E S ......... ............................... ......... ... ....... ....... vi

ABSTRACT ........ .............. ............. .. ...... .......... .......... vii

CHAPTER

1 INTRODUCTION............... .................... ............. ............. 1
A trial Fibrillation......................... ................................ .........2
Medical/Pharmacological Treatments for AF................... ..............3
D evice Therapies: The IAD ................... ................ .................4
Psychological Effects of Shock ............... ...............................6
Depression........... ...................................................... 9
Quality of Life................................. ....................... ...... 10
Illness Intrusiveness ..................................... ........................ .. 11
Relationship Between Illness Intrusiveness and Quality of Life.................. 13
A im s and Study Justification.......................................................... 14
Hypotheses ................... .................. .................. ... ......... 14

2 M ETH OD ................... ...........................................16
Participants ....................... .............. 16
A ssessm ent.............. ............... ............ ................. ... ......... 18
G eneric Quality of Life................... ....... ........ ..... ............. 18
Center for Epidemiological Studies Depression Scale.......................18
Illness Intrusiveness Rating Scale ............... ............................19
State-Trait Anxiety Inventory.................................................20
Pain and Intensity Ratings.................. .............. .. ........ ....... 20
D evice D ata................... .................................... ......... 20
D em graphic M easures........... ................. ...... .............. 21

3 RESULTS...................................................22
Sample Descriptives ................. ................................. 22
Correlations and Collinearity Evaluation ................................... 23
Regression Analyses: Illness Intrusiveness.................. ...............23
Regression Analyses: Physical Quality of Life.............................25
Regression Analyses: Mental Quality of Life..................... ........26












4 D ISC U SSIO N ...................................................... .... ......... 28


Implications for the Experience of Shock ...................................29
C clinical Im plications ............................................. .............. ..30
Strength and Weaknesses of the Study ........... ...........................31


LIST OF REFERENCES................. ...................................... ..........33


BIOGRAPHICAL SKETCH ............................. ... .......................... 38










































v















LIST OF TABLES

Table page

2-1 Patient Demographics and Relevant Medical Variables ......... .............17

3-1 M eans for Psychosocial M easures............. ..................................... 23

3-2 Correlations of Key Assessment Instruments ........... ......... ..........24

3-3 Regression Analysis: Illness Intrusiveness............................................25

3-4 Regression Analysis: Physical Quality of Life....................................26

3-5 Regression Analysis: Mental Quality of Life........................ .........27















Abstract of Thesis Presented to the Graduate School
Of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

DEPRESSION AND ILLNESS INTRUSIVENESS AS PREDICTORS OF QUALITY
OF LIFE AMONG IMPLANTABLE ATRIOVERTER DEFIBRILLATOR
RECIPIENTS

By

Rebecca Owen Sotile

May 2003

Chair: Samuel F. Sears
Major Department: Clinical and Health Psychology


The Implantable Atrial Defibrillator (IAD) corrects atrial and ventricular

fibrillation via a high energy defibrillation shock. Because the application of shock is

aversive and atrial fibrillation (AF) is not an immediately life-threatening indication, the

inter-relationship of shock, AF symptoms, illness intrusiveness and quality of life

outcome will determine the potential value and future direction of IAD development.

The purpose of this study was to examine a biopsychosocial model of illness for illness

intrusiveness and quality of life in drug-refractory IAD patients. IAD adjustment was

evaluated in 96 patients enrolled in the Jewel AF-AF Only Study > 3 months follow up

(mean=19 months). Patients were mostly men (72%) and were 62+-12 years. A

questionnaire and national clinical database characterized patient demographics, AF

disease burden, atrial defibrillation therapy, and psychological distress. Within a

biopsychosocial design, multiple hierarchical regressions indicated depression as a









unique predictor of variance on illness intrusiveness scores, accounting for 11.4% of

variance. Illness intrusiveness and depression together predicted 11.1% of variance on

physical quality of life. Beta weights revealed that illness intrusiveness and age were the

only predictors of variance of physical quality of life. Regarding mental quality of life,

results indicated that 32.3% of variance was accounted for by depression and illness

intrusiveness together. Beta weights revealed that depression was the only unique

contributor of variance to mental health. Maladjustment to the physical aspects of

defibrillation may result from the presence of psychological distress. Psychological

symptoms such as depression and illness intrusiveness are largely responsible for AF

patients' declines in quality of life. Acceptance of IAD therapy may be facilitated by

successful treatment of psychological distress among IAD patients and multi-disciplinary

care that routinely addresses the psychological impact of AF and device treatment.














CHAPTER 1
INTRODUCTION

Cardiac arrhythmias are a prominent cause of death, hospitalizations, and

healthcare costs in the United States. Each year cardiac arrhythmias play a role in over

500,000 deaths and 724,000 hospitalizations, while also accounting for 11.9 billion

dollars spent annually on healthcare costs (American Heart Association, 2001). An

arrhythmia is characterized by abnormal electrical impulse conduction in the heart

(American Heart Association, 2001). A sustained rapid heartbeat (usually 160-280

beats/minute) is referred to as tachycardia. Tachycardia can begin in the atria or the

ventricles and is often accompanied by symptoms such as chest pain, fainting, and

dizziness. Prolonged tachycardia may result in fibrillation, which is an uncoordinated

movement of electrical impulses through the heart. These impulses cause the heart

chambers to twitch rapidly, resulting in inefficient blood flow to the rest of the body, and

have the potential to significantly affect mortality risk and quality of life (Allan &

Scheidt, 1996).

The implantable atrioverter defibrillator (IAD) is a device that corrects fibrillation

in the atria. Correcting these irregular heartbeats requires a shock from the device,

similar to the shock received during external cardioversion. Shock can be an aversive

experience for patients, but the effects of untreated atrial fibrillation can be more

detrimental. Therefore, the degree of intrusion from the illness may be an important

index to understanding both patients' willingness to get shocked and the effects of having






2


been shocked. In this study, a biopsychosocial model including disease and treatment

variables as well as predictors of illness intrusiveness and quality of life in atrial

fibrillation patients who have been implanted with the IAD were examined.

Atrial Fibrillation

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia, occurring

in over 2 million Americans. AF refers to rapid contractions of the atria, or upper heart

chambers, and illicits an irregular response from the ventricles. This irregular rhythm

causes a reduction in blood flow, and increases the chances of formation of a blood clot

that could travel to the brain, causing stroke and possibly death (Luderitz & Jung, 2000).

Fifteen percent of all strokes are caused by AF (American Heart Association, 2001). The

prevalence of AF increases with age from less than 1% at 50 to 59 years to 9% at 80 to 89

years (Luderitz & Jung, 2000).

The majority of hospitalizations from cardiac arrhythmias are due to AF. Besides

increasing the risk of blood clots and stroke, the hemodynamic effects of AF may cause

decreased exercise tolerance and heart failure. Disorders that may result in atrial

fibrillation include: ischemic heart disease, rheumatic heart disease, hypertension, sick

sinus syndrome, cardiomyopathy, and other structural abnormalities. Atrial fibrillation

can be paroxysmal or sustained; however, the majority of patients have paroxysmal atrial

fibrillation, denoting a transient occurrence of AF (Lip, 2001). The initial impairment

caused by atrial fibrillation is less obvious than that caused by ventricular fibrillation, or

rapid contractions of the lower heart chambers, because atrial fibrillation only mildly

affects cardiac output. In fact, a patient may be unaware that he/she is in atrial fibrillation

because various medications can keep the heart rate normal during atrial fibrillation









(Allan & Scheidt, 1996). Approximately one-third of AF patients do not experience any

symptoms, while the other two-thirds may experience heart palpitations, fatigue,

dizziness, and presyncopal episodes (American Heart Association, 2001).

Although the physical symptoms of AF may not be immediately apparent,

significant psychological distress often accompanies this condition. The Ablate and Pace

Trial (Kay, Ellenbogen & Giudici, 1998) included a sample of highly symptomatic, drug-

refractory AF patients. Baseline assessment revealed significantly lower quality of life

among the AF patients as compared to patients with heart failure or a recent myocardial

infarction. This illustrates that AF patients may experience unique psychological issues

that are not as prominent for other cardiac populations. Because multiple studies have

illustrated that psychological intervention is effective in improving quality of life and

physical symptoms among various cardiac patient populations (Bennett & Carol, 1994;

Hill, Kelleher, & Shumaker, 1992; Linden, Stossel, & Maurice, 1996), this study suggests

that AF patients may receive similar benefit from psychological intervention.

Medical/Pharmacological Treatments for AF

The treatment of cardiac arrhythmias varies based on the rhythm's characteristics,

etiology, and the patient's experience of symptomotology. The most efficient way to

describe treatment options is to consider them on a scale of physical and mental

intrusiveness to the patient. The least severe, a non-life-threatening, and asymptomatic

paroxysmal arrhythmia, may be treated with simple behavioral interventions such as

dietary modifications and smoking cessation. A more severe symptomatic paroxysmal

arrhythmia, (e.g., ventricular tachycardia or atrial flutter), that results from a manageable

disease process may be treated with anti-arrhythmic medications such as beta-blockers









(Canobbio, Fassio, & Gasparini, 1986). In addition to suppressing premature

contractions that cause arrhythmias, beta-blockers also reduce heart rate, blood pressure,

and strength of cardiac contraction. Atrial fibrillation becomes more severe when the

episodes are sustained or paroxysmal, symptomatic, not drug-responsive, and/or life-

threatening. These may call for more invasive interventions such as catheter ablation of

conduction pathways, surgical ablation, or resection of conduction pathways (Canobbio

et al., 1986).

Although the treatment of AF varies widely, the majority of symptomatic

patients are successfully treated with dual chamber pacemaker therapy and/or

antiarrhythmic drugs. Most AF patients receive anticoagulants, such as aspirin or

warfarin, which help prevent the formation of blood clots. However, AF patients whose

symptoms are recurrent and require external cardioversion may benefit most from an

implantable device called the implantable atrioverter defibrillator (IAD; Lip, 2001). The

IAD alleviates symptoms but does not cure the underlying disorder. Currently, there are

no absolute indications for the implantation of an IAD; yet, the patients involved in

clinical trials using the IAD have paroxysmal atrial fibrillation that is symptomatic and

drug-refractory (Wellens, Lau, Luderiz, et al., 1998).

Device Therapies: The IAD

The technology of the IAD is similar to that of the implantable cardioverter

defibrillator (ICD), which terminates life-threatening ventricular arrythmias (Lip, 2001).

The ICD re-establishes normal sinus rhythm in response to ventricular fibrillation,

whereas the IAD is designed to re-establish normal sinus rhythm in individuals with atrial

arrythmias. The ICD gained FDA approval in 1985, and has been researched in









numerous trials since 1996 (Davidson, VanRiper, Harper & Wenk, 1994). In contrast,

the IAD is a much newer device, and IAD patients have not been extensively researched.

The IAD is similar to the size of a pacemaker, and consists of an atrioverter can

which is pectorally implanted, and three electrical leads which connect to three different

parts of the heart: the coronary sinus, the right atrium, and the right ventricle (Lip, 2001).

The IAD is capable of delivering two different types of shocks: a defibrillation shock for

the atrium, and a pacing discharge to the ventricle to prevent a bradyacardiac response

after defibrillation. The IAD can be programmed to shock automatically, or can be

activated by the patient or physician with a hand-held activator (Lip, 2001). A recent

trial illustrated that the Dual-Chamber ICD, which is essentially an ICD with atrial

therapies, is well-tolerated in drug-refractory symptomatic AF populations (Gold, Sulke,

Schwartzman, Mehra & Euler, 2001). The researchers found that the dual-chamber ICD

was successfully implanted in 99% of the sample (N = 146), and illustrated 98% survival

at 12-month follow-up. Additional results indicated that 99% of atrial arrhythmias

among this sample were correctly predicted by the device, and 87% of atrial arrhythmias

were successfully terminated. Perhaps even more critical, 7.6% of the sample required

ventricular shocks for VT/VF which would have been fatal (Gold et al., 2001). This

study suggests that patients with atrial fibrillation receive substantial physical benefit

from implantable defibrillation devices such as the IAD.

Although the IAD has been shown to provide relief from the physical symptoms

of AF, to date no study has examined the psychological implications of device therapy

for AF patients. An important difference between patients with atrial fibrillation and

patients with ventricular fibrillation is that atrial fibrillation does not present a threat of









immediate death, and a defibrillation charge from the IAD does not represent a life-

saving procedure as it does for ICD patients with life-threatening ventricular arrhythmias.

Therefore, the psychological stress associated with receiving a defibrillation shock may

be different for IAD patients, a concept that was examined in this study.

Psychological Effects of Shock

Although both the IAD and the ICD have demonstrated to be effective life-saving

devices (Gold et al., 2000), researchers continue to examine the issue of patient

adaptation to this therapy. Recent studies reveal that there is a strong fear component

associated with defibrillation, especially among patients receiving multiple shocks

(Murgatroyd & Camm, 1997; Sears, Todaro, Saia Lewis, Sotile, & Conti, 1999; Sears &

Conti, 2002). A recent major clinical trial, the CABG Patch Trial, examined the value of

prophylactic ICD implantation in patients undergoing coronary artery bypass graft

surgery versus no ICD after CABG surgery (Namerow, Firth, Heywood, Windle, Parides,

et al., 1999). Data indicated that the mental and physical quality of life outcomes for the

ICD patients were significantly worse compared to no-ICD patients. Further analyses

revealed that there were no differences in quality of life for non-shocked ICD patients vs.

no-ICD patients. These results indicated that the ICD group who had received shocks

was responsible for the significantly worse mental and physical quality of life outcome

scores between the groups.

The Antiarrhythmics Versus Implantable Defibrillators (AVID) trial represents

the first major comparison of self-perceived quality of life among ICD patients and

antiarrhythmic drug (AAD) therapy patients. AVID researchers concluded that ICD and

AAD therapy have similar effects on self-perceived quality of life among patients with









ventricular arrhythmias. Although all patients had poor baseline quality of life, a

significant finding was that adverse symptoms were associated with major impairment in

quality of life, regardless of the type of therapy and sporadic shocks received from the

ICD. Specifically, adverse symptoms among AAD patients were associated with

reductions in physical functioning, and both physical functioning and mental well-being

in ICD patients (Schron, Exner, Yao et al., 2002). The AVID study illustrated that

frequent ICD shocks (>5) were associated with increased psychological distress and

lower quality of life. Additionally, the study demonstrated that ICD patients receiving at

least one shock in the first year of follow-up had significant declines in physical

functioning and mental well-being, along with increased patient concerns. This effect of

shock was present independently of other markers of disease severity (Schron et al.,

2002). Such research highlights the fact that shock can be a frightening experience for

ICD patients, and has implications for clinical interventions with IAD patients.

The Canadian Implantable Defibrillator Study (CIDS) (Irvine, Dorian, Baker,

O'Brien, Roberts, Gent, Newman, & Connolly, 2002) yielded similar results regarding

the negative effects of shock. In a longitudinal quality of life comparison between

shocked vs. non-shocked ICD patients, researchers concluded that non-shocked patients

experienced improved quality of life at 2, 6, and 12 months follow-up. More specifically,

patients receiving 5 or more shocks within the first year of device implantation

experienced significant declines in generic quality of life (Irvine et al., 2002). These

results imply the existence of a "shock threshold," or maximum number of shocks that

can be tolerated before patients' quality of life is significantly compromised.

Conversely, a number of studies have illustrated that shock is not a unique









contributor to decreased psychological well-being. Several investigators have examined

patients with ICDs and compared them to patients with permanent pacemakers on generic

measures of quality of life. Very few consistent differences were demonstrated between

these two populations. For example, Duru and colleagues (2001) found no differences in

generic quality of life score, anxiety or depression when comparing ICD patients with

and without shock experience and pacemaker patients. ICD patients with a shock history

were more likely to report limitations in leisure activities and anxiety about the ICD, but

they also viewed the ICD as a "life extender." However, this study did not use a disease-

specific quality of life measure, and therefore measurement may have been too gross to

determine a difference between groups. Herbst, Goodman, Feldstein, and Reilly (1999)

recently compared the quality of life and psychological distress of four patient groups:

ICD only (n = 24) vs. ICD + anti-arrhythmic drug (n = 25) vs. anti-arrhythmic drug only

(n = 35) vs. a general cardiac sample (n = 73). Quality of life was assessed via the SF-36

and three supplementary scales examining sleep, marital and family functioning, and

sexual problems. Comparisons were made between ICD groups and drug groups.

Results indicated that there were no significant differences on the 11 quality of life

scales, even after controlling for age, gender, disease severity, and duration of treatment.

Yet, significant differences were found in drug groups vs. no drug groups, such that the

drug treated group consistently reported greater impairment in physical functioning,

vitality, emotional, and sleep functioning, as well as psychological distress. Overall,

these results suggest that quality of life was maintained in ICD treated groups, while anti-

arrhythmic drug therapy was associated with diminished quality of life and increased

psychological distress.









Although study results vary, it is important to recognize that ICD-related fears are

universal and may be the most pervasive psychosocial adjustment challenge ICD patients

face. Psychological theory suggests that symptoms of fear and anxiety can result from a

classical conditioning paradigm in which certain stimuli or behaviors are coincidentally

paired with an ICD shock and are thereby avoided in the future (Sears & Conti, 2002).

Due to fear of present and/or future discharges, some patients increasingly limit their

range of activities and inadvertently diminish the benefits of the ICD in terms of quality

of life (Sears & Conti, 2002). Collectively, these data implicate that the experience of

shock is often strongly associated with psychological distress and diminished quality of

life (Sears et al., 1999). The experience of shock may be different for IAD patients, who

have the option of administering the shocks manually, and thus eliminate receiving an

unexpected defibrillation charge that may lead to fear or anxiety. Atrial shocks are

unpleasant and possibly frequent; subsequently IAD patients are likely to view shock as

negatively as ICD patients do, and to experience similar symptoms of psychological

distress.

Depression

Depression has been identified as a significant characteristic related to health

outcomes among various cardiac populations (Frasure-Smith, Lesperance, & Talajic,

1995). Among ICD patients, prevalence rates of depressive symptomatology range from

24% to 87% at various follow-up intervals (Hegel, Griegal, Black & Goulden, 1997;

Konstam, Colbum & Butts, 1995; Sears et al., 1999). Early research highlights

correlations between declines in physical ability/functioning and the development of

depression in ICD patients (Pycha, Gulledge, Hutzler, Kadri, & Maloney, 1986). More









recently, similar findings within the ICD patient population indicate that depression and

mood disturbance post-implant may increase the likelihood of an arrhythmia requiring a

shock from the device (Dunbar, Kimble, Jenkins, et al., 1999). Sears and colleagues

(1999) postulate that depression among device patients may result from the patient's

perceived lack of control over the defibrillation charges. These symptoms may

eventually lead patients to have increased negative beliefs and hopelessness about their

current and future health status. This negative view of the future is often reflected by a

reduction in mental quality of life. Although many IAD patients maintain control over

when a defibrillation charge is administered, a single charge may not always correct an

atrial arrhythmia. Thus, it is often necessary for IAD patients to experience multiple

shocks, contributing to psychological distress (Irvine et al., 2002; Schron et al., 2002).

Further, the after-effects of receiving a painful shock are likely similar for ICD and IAD

patients. Due to the prevalence of depression among ICD patients and the relationship

between shock, depression, and quality of life, this study predicts that depression among

IAD patients will present similarly to ICD patients.

Quality of Life

To date the largest study examining quality of life among symptomatic AF

patients found that both disease specific and generic quality of life were significantly

lower for AF patients than for healthy controls (Dorian, Jung, Newman et al., 2000). AF

patients scored significantly lower on all scales of the SF-36 except for the Bodily Pain

scale. However, much of the current research regarding quality of life among patients

with defibrillators has focused on ICD patients. Although ICD patients primarily report

desirable quality of life, it is well established that psychosocial distress contributes to a









reduction in quality of life (Heller, Ormont, Lidagoster et al., 1998; Luderitz, Jung,

Deister & Manz, 1996; Pycha et al., 1986; Sears et al., 1999, 2000). Among the most

common patient complaints regarding quality of life are social isolation, psychological

distress, and physical complaints (Heller et al., 1998; Luderitz et al., 1996; Pycha et al.,

1986; Sears et al., 1999). Poorer quality of life is more prevalent among patients who

receive shocks from the ICD as compared to patients who have not received shocks from

the ICD (Dunbar et al., 1999; Heller et al., 1998; Herbst et al., 1999; Kohn, Petrucci,

Baessler, Soto & Movsovitz, 2000; Reid, Nagy & McKinley, 1999; Sears et al., 1999).

Because shock has been established as a negative experience (Namerow et al., 1999;

Sears et al., 1999; Sears & Conti, 2002), it may be hypothesized that patients receiving

shocks will also experience higher levels of illness intrusiveness as compared to patients

who have received no shocks, which has been shown in previous research (Schron et al.,

2002; Irvine et al., 2002). Therefore, this study examined the relationship between

factors affecting illness intrusiveness and subsequent quality of life within a

biopsychosocial model that accounted for both psychological and medical data.

Illness Intrusiveness

The construct of illness intrusiveness is described as lifestyle disruptions,

resulting from an illness and/or its treatment, that hinder participation in valued activities

and interests (Devins et al., 1983). Because illness intrusiveness limits participation in

valued activities, it may in t urn decrease psychosocial well-being as it lowers an

individual's exposure to positively-valued interactions. Illness intrusiveness may cause

further psychosocial decline by reducing an individual's personal control over both









positive and negative outcomes in important situations, especially among patients with

chronic conditions (Devins et al., 1993).

Studies indicate varying degrees of illness intrusiveness across treatment

modalities and illnesses (Devins et al., 1993). Among chronic illness populations, a

number of illness-related factors contribute to the construct of illness intrusiveness,

including disease factors, such as pain and disability, and treatment factors such as time

required for treatment and mode of treatment (Devins, 1994). Illness intrusiveness

among chronic illness populations has been shown to have a significant and unique

relationship to several psychological variables, including positive and negative mood, life

satisfaction, and depression, and is further influenced by psychological and social

characteristics such as social support and coping resources (Binik, Devins & Orme, 1989;

Devins, 1994). Devins' (1994) model hypothesizes that factors of an individual's disease

and treatment psychosocially impact quality of life through their relationship with illness

intrusiveness. The model also accounts for direct effects of psychological and social

factors on both illness intrusiveness and quality of life.

Research on illness intrusiveness among AF patients found that symptomatic AF

patients had significantly higher illness intrusiveness than same-aged non-AF patients

(Dorian et al., 2002). Consistent with Devins' model, this study also found lower quality

of life on several SF-36 scales among AF patients as compared to angioplasty,

myocardial infarction and congestive heart failure patients, even when controlling for

physical impairment (Dorian et al., 2002). Despite AF patients experiencing a variety of

physical symptoms, these data suggest that psychological distress is an equally limiting

aspect of the condition. The influence of psychological constructs such as illness









intrusiveness on quality of life often overpowers the influence of AF's unique physical

limitations, and emphasizes the importance of psychological intervention in conjunction

with standard medical care for AF patients. In this regard, illness intrusiveness emerges

as an important target for multidisciplinary interventions.

Relationship Between Illness Intrusiveness and Quality of Life

The Devins (1994) model stems from research involving the role of illness

intrusiveness in quality of life among End-Stage Renal Disease patients, and has

indicated that perceived illness intrusiveness was significantly correlated with three

quality of life measures including satisfaction/happiness, pessimism/illness-related

concerns, and depression/distress (See Figure 1; Devins, Mandin, Hons et al., 1990).

Specifically, higher levels of perceived illness intrusiveness were significantly correlated

with decreased life satisfaction and happiness, increased pessimism and illness-related

concerns, and increased depression and distress. These results remained stable over time,

even after controlling for response style and background variables (Devins et al., 1990).

Similarly, an additional study with rheumatoid arthritis patients revealed a statistically

significant relationship between illness intrusiveness and physical disability, such that

after controlling for physical disability, illness intrusiveness maintained a unique,

significant relationship with depression (Devins, Edworthy, Guthrie et al., 1992). These

data illustrate the role of illness intrusiveness as a mediator of the psychosocial impact of

chronic illness, although no study to date has examined this potentially valuable construct

in IAD patients. The current study will examine illness intrusiveness among IAD

patients using analyses influenced by Devins' (1994) model.









Treatment Factors

Illness
Quality
Intrusiveness
of life
Disease Factors




Psychological & Social

Factors



Figure 1. Hypothesized relations among illness intrusiveness, its determinants, and
quality of life in AF patients (Devins, 1994).


Aims and Study Justification

The purpose of this study was to test a biopsychosocial model of illness

intrusiveness and quality of life in a sample of drug-refractory IAD patients. Using

hierarchical multiple regression analyses controlling for demographic and biomedical

data, this study explored predictors of illness intrusiveness and physical and mental

quality of life. This model was adapted to identify areas of possible psychological

intervention among IAD patients.

Hypotheses

The following hypotheses were investigated in this study:

1. It was hypothesized that CES-D ratings of depression would be significantly
associated with Illness Intrusiveness Rating Scale scores among IAD patients, while
controlling for demographics, number of shocks, and biomedical variables.

2. It was hypothesized that Illness Intrusiveness Rating Scale scores would significantly
predict variance in the Physical Functioning Scale of the SF-36 Quality of life Measure






15


among IAD patients, while controlling for demographics, number of shocks, biomedical
variables, and psychological variables.

3. It was hypothesized that CES-D ratings of depression would significantly predict
variance in the Mental Scale of the SF-36 Quality of life Measure among IAD patients,
while controlling for demographics, number of shocks, biomedical variables, and
psychological variables.















CHAPTER 2
METHOD

Participants

The participants (N = 96) were recruited from an ongoing multi-site FDA study

spanning 23 lAD-implanting facilities. Participants were recruited by the research

coordinator at each implanting facility. Each participant had undergone a full medical

workup prior to recruitment.

In order for a patient to qualify for inclusion in the study, he/she must have had

lone AF, indicating AF was his/her only major heart condition. All participants were also

drug-refractory, defined as having tried and failed at least one anti-arrhythmic drug

within the year prior to the study. Participants must have had at least one AF episode

lasting 48 hours. At the time of the study, all subjects were taking an anti-coagulant such

as warfarin.

Particpant exclusion criteria included documented risk of sudden death from

ventricular fibrillation, which would indicate implantation of a traditional ICD. Table 1

provides a summary of the demographic and medical characteristics of the study sample.









Table 1. Patient Demographics and Relevant Medical Variables

Mean (SD) or %

Total Manual Shock Automatic Shock

(N = 96) (n = 42) (n = 35)




Demographics

Age 62.2 (11.8) 59.8 (12.1) 64.3 (10.9)

Gender (% Male) 72% 64% 80%

Marital Status (% Married) 83.3% 83.3% 82.9%

Ejection Fraction (N= 54) 52.1 (15.8) 56 (15.1) 45.3 (15.6)

Pre-Implant Cardioversions 2.2 (2.1) 2.2 (2.1) 2.1 (2)

Pre-Implant AF episodes 9.1 (13) 8.4 (12.3) 12.5 (20.7)

AF Symptom Score 15.6(8.49) 14.4 (8.2) 18.2 (9.2)

Device Data

Years Since Implant 1.6 (.87) 1.6 (.84) 1.6 (.81)

Detected AF Episodes 176 (337) 167 (306) 191 (337)

Total Atrial Shocks 12.8 (18.4) 13 (21.1) 12.5 (14.9)

Manual Shock/month 0.93 (2.7) 1.4 (3.5) 0.46 (1.3)

Automatic Shock/month 0.22 (.76) 0.0 (0.0) .57 (1.2)

Atrial Shock Energy (J) 15.2 (7.8) 15 (7.9) 15.9 (7.9)

Note: 18 patients did not receive any shocks or received both manual and automatic shocks, and therefore
were not included in the statistical analyses










Assessment

Generic Quality of Life

The Medical Outcomes Study Short-Form 36 Health Survey (SF-36; Ware, Snow,

Kosinski & Gandek, 1993) was used to measure quality of life. This is a widely used and

well-validated generic measure of health-related quality of life, and was shown to be the

most effective measure for evaluating quality of life among pacemaker patients in a

recent comparison study (Stofmeel, Post, Kelder et al., 2000). Because of its widespread

application to cardiac patients and its role in validating other measures of cardiac illness,

the SF-36 has become the standard measure of quality of life among cardiac populations

(Stofmeel, et al., 2001; Hamilton & Haennel, 2000). Items included in the SF-36 were

constructed by Ware and colleagues (1993), who used a sample of over 20,000 U.S.

residents to assess perceptions of 40 mental and physical health concepts in the Medical

Outcome Study (MOS). The SF-36 contains scales to measure the eight most salient

concepts represented by this survey: Physical Functioning, Physical Role, Bodily Pain,

General Health, Vitality, Social Functioning, Emotional Role, and Mental Health. To

avoid inflating experiment-wise error, the current study examined scores on only three

scales of the SF-36: Physical Functioning, Mental Health, and Social Functioning.

Center for Epidemiological Studies Depression Scale

Depression was measured using the Center for Epidemiological Studies -

Depression Scale (CES-D), a 20-item self-report measure of depressive symptomatology

(Radloff, 1977). Participants are asked how frequently over the past week they have

experienced various depressive symptoms, and responses range from 0 (less than one

day) to 3 (5-7 days). Total scores range from 0 to 60, and a standard cut-off score of 16









indicates clinically significant depressive symptoms (Radloff, 1977). The CES-D reflects

the number and duration of depressive symptoms. The CES-D has a high internal

reliability coefficient of .85, and has been reported as a more generally useful self-report

measure of depression than the Beck Depression Inventory, the MMPI Depression Scale,

and the Zung Self Rating Scale of Depression (Turk & Okifuji, 1994).

Illness Intrusivenss Rating Scale

The Illness Intrusiveness Rating Scale (IIRS; Devins, Orme &Costello, 1988) is a

19-item self-report measure that asks respondents to rate how much their illness and

consequent treatment interferes with each of 13 life domains. Ratings occur along a 7-

point Likert scale, ranging from 1 (Not Very Much) to 7 (Very Much). The domains

pertain to health, recreation, diet, work, financial situation, self-expression, family

relations, relations with spouse, sex life, social relations, religious expression and

community involvement. A total intrusiveness score and a score for each of the 13

domains can be calculated. Total scores range from 13 (where the illness is not intrusive)

to 91 (where the illness is extremely intrusive in all domains). Exploratory and

confirmatory factor analyses across eight different patient groups have revealed three

underlying factors comprising the scale (Relationships and Personal Development,

Intimacy, and Instrumental Life Domains). Recent research indicates that the total IIRS

score may be preferable for use in basic analyses (Devins et al., 2001). The IIRS has

been shown to have adequate to high internal consistency, reliability, and validity

(Devins et al., 1993). Coefficient alpha ranges from 0.80 to 0.95 have been found across

diagnoses (Devins et al., 2001).









State-Trait Anxiety Inventory

The STAI is a 40-item self-report questionnaire designed to measure both state

and trait anxiety (Speilberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983). For the

purposes of this study, only the 20-item trait scale of this questionnaire was administered.

Trait anxiety is defined as a relatively enduring personality characteristic, or more

specifically, as anxiety proneness. The internal reliability of both the state and trait

anxiety scales has been shown to be uniformly high across samples of adults ranging

from .89 to .96. Test-retest reliability coefficients for multiple samples of college

students ranged from .73 to .86, with test-retest validity specifically for the trait scale

being reported at .73 for males and .77 for females. Concurrent validity between the

STAI and IPAT Anxiety Scale and the Taylor Manifest Anxiety Scale ranged from .83 to

.73 (Spielberger et al., 1983).

Pain and Intensity Ratings

Subjective ratings of pain and intensity were taken from the Patient Acceptance

Scale (PAS), which provides statements about the pain and intensity of a defibrillation

charge, and provides responses ranging from Strongly Disagree to Strongly Agree (Burns

et al., 2002).

Device Data

Information was collected to address several aspects of patients' IAD history.

The device data included number of years since device implantation at the time of survey,

number of treated episodes, and number of manual and automatic shocks received per

month.






21


Demographic Measures


This measure was developed to assess: marital status, age, religion, ethnicity,

education level, employment status, number of doctor visits, exercise habits, smoking

habits and alcohol consumption.


This study used baseline data for quality of life measures only. All other data was

collected at the follow-up in the closest proximity to the survey data (M = 4.7 months

since last device interrogation, SD = 2.8 months).















CHAPTER 3
RESULTS


Sample Descriptives

Illness intrusiveness scores for this sample ranged from 13 to 73 (M= 27; SD =

14). Additional descriptive data was gained by using t-tests to compare this sample with

the group of End Stage Renal Disease patients upon which Devins' (1994) original work

was based. The IAD sample's mean illness intrusiveness rating was significantly lower

than a published mean for patients receiving hemodialysis ( < .001), but not

significantly different from a published mean for patients of successful renal

transplantation (p = .504; Devins, 1994). In the present sample, 42% had illness

intrusiveness scores above cut-off scores for an AF-only sample, but sample differences

were insignificant. Results also indicate that IAD recipients may experience levels of

illness intrusiveness similar to those experienced by transplant recipients. Thus, the IAD

may be considered analogous to a lifesaving "organ" which is capable of prolonging and

improving life.

Additional descriptive data was computed using t-tests. CES-D scores (M =

11.1; SD = 8.5; n = 81) were significantly different from healthy normals (M = 9.3; SD =

8.6; p < 0.05), although these differences are likely not clinically significant (Radloff,

1977). Regarding anxiety levels, the STAI scores of this sample (M = 33.9; SD = 10.8; n

= 88) were not significantly different from scores of healthy normals (healthy males, M =









34.9; SD = 9.9; healthy females, M = 34.8; SD = 9.2) (Speilberger, Gorsuch,

Lushene, Vagg & Jacobs, 1983). Mean total symptom score (16.0) and mean AF

symptom number (8.2) was also calculated. Means for all participants in this study are

located in Table 2.

Table 2. Means for Psychosocial Measures
M SD n Min. Max.
Depression (CES-D) 11.07 8.57 81 0 35

Trait Anxiety (STAI) 33.99 10.8 88 20 70

Illness Intrusiveness (IIRS) 27.00 14.4 93 13 73

Quality of life (SF-36)
Physical 67.01 25.5 82 15 100
Mental 72.76 17.7 84 16 100

Total Symptom Score 15.95 8.50 82 1 41

Total Symptom Number 8.16 3.37 83 1 12


Correlations and Collinearity Evaluation

Correlations were run among several of the independent and dependent variables

to determine the inter-correlations between variables. These results are presented in

Table 3. Although there were significant correlations between some psychosocial

variables, none exceeded r >.7, which is a cut-off to determine multicollinearity

(Kleinbaum, Kupper, Muller & Nizam, 1998). Therefore, all variables were included in

the planned analyses.

Regression Analyses: Illness Intrusiveness

A three-step multiple hierarchical regression analysis was conducted to examine

the relationships between demographic, shock, and symptom variables, along with patient

ratings of pain and discomfort, and the psychological construct of illness intrusiveness as









the dependent variable. Specifically, number of shocks and AF symptom score were

included as disease-specific factors that may influence illness intrusiveness. Significance

was set at alpha = .05.

Table 3. Correlations of Key Assessment Instruments

CES-D IIRS Physical Mental
Scale Scale

CES-D


IIRS .447**


Physical -.298* -.263*
Scale

Mental -.604** -.275* .300**
Scale

** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).

On the first step of the analysis, sex and age were insignificant predictors of

illness intrusiveness (F change (2, 52) = 1.847, = .168), accounting for 6.6% of the

variance. Number of manual and automatic atrial shocks, AF symptom score, and patient

ratings of pain and discomfort were entered on the second step of the analysis. These

factors contributed 18.3% of variance, although this variance was not significant (F

change (5, 47) = 2.295, p = .060). On step three, CES-D scores were entered,

significantly predicting 11.4% of variance in illness intrusiveness scores (F change (1,

46) = 8.202, p = .006). Specifically, higher depression was associated with higher illness

intrusiveness. The overall model was significant (F (8, 54)= 3.279, p= .005), and

accounted for 36.3% of variance in illness intrusiveness.











Table 4. Regression Analysis: Illness Intrusiveness.


Model R Square F Change dfl df2 Sig
Change Change
1 .066 1.847 2 52 .168
2 .183 2.295 5 47 .060
3 .114 8.202 1 46 .006


Regression Analyses: Physical Quality of Life

A three-step multiple hierarchical regression analysis examined demographics,

baseline physical quality of life scores, number of atrial shocks, and psychological

variables (depression and illness intrusiveness) with post physical quality of life as the

dependent variable. Pain and discomfort were excluded since they failed to contribute

significant variance to illness intrusiveness in the presence of depression (F change (5,

47) = 2.295, p= .060). In step one of the analysis, baseline physical quality of life

scores, age and sex were not significant predictors of post physical quality of life (F

change (3, 64) = 1.634, = .190). Step two of the analysis included number of total atrial

shocks, which also failed to contribute significant variance (F change (1, 63) = .608, p =

.439). Psychological variables (depression and illness intrusiveness) were entered on the

third step of the analysis; they significantly added 12.0% of the variance (F change (2,

61)= 4.575, = .014). Specifically, higher age and higher illness intrusiveness predicted

lower post physical quality of life. Therefore, illness intrusiveness uniquely predicted

post physical quality of life above and beyond a host of demographic, biomedical, and

psychological variables. The overall model significantly accounted for 20.0% of variance

in post physical quality of life (F (6, 67) = 2.542, p = .029).











Table 5. Regression Analysis: Physical Quality of Life.


Model R Square F Change dfl df2 Sig
Change Change
1 .071 1.634 3 64 .190
2 .009 .608 1 63 .439
3 .120 4.575 2 61 .014


Regression Analyses: Mental Quality of Life

The last three-step multiple hierarchical regression was conducted to examine

demographic, baseline mental quality of life scores, total atrial shocks and psychological

variables (depression and illness intrusiveness), with post mental quality of life as the

dependent variable. On step one, baseline mental quality of life, sex, and age did not

contribute significant variance in post mental quality of life (F change (3, 64) = .814, p =

.491). Step two included total atrial shocks, which also failed to explain significant

variance in post mental quality of life (F change (1, 63) = .029, p = .865). Depression

and illness intrusiveness were entered on the third step of the analysis, and significantly

predicted post mental quality of life (F change (2, 61) = 15.412, p < .001), contributing

32.3% of the variance. Specifically, higher depression was associated with lower post

mental quality of life. The overall model accounted for 36% of variance in post mental

quality of life (F (6, 67) = 5.729, p < .001). As stated earlier, multicollinearity statistics

were calculated to ensure that these results were not influenced by the correlation

between depression and mental quality of life. The tolerance value (.774) indicates an

acceptable correlation level (Kleinbaum et al., 1998). Therefore, depression uniquely

predicted mental quality of life within this biopsychosocial model, but no demographic or









disease-specific variables were significant predictors of mental quality of life. The

overall model accounted for 36.0% of variance in post mental quality of life.

Table 6. Regression Analysis: Mental Quality of Life.

Model R Square F Change dfl df2 SigF
Change Change
1 .037 .814 3 64 .491
2 .000 .029 1 63 .865
3 .323 15.412 2 61 .000















CHAPTER 4
DISCUSSION

The current study investigated the utility of Devins' (1994) biopsychosocial

model regarding the relationships between psychological variables and their influence on

physical and mental quality of life within a sample of IAD patients. It was hypothesized

that the psychological constructs of depression and illness intrusiveness would impact

physical and mental quality of life above and beyond the influence of demographic,

biomedical and disease-related variables. A series of three-step multiple hierarchical

regression analyses indicated that the hypotheses regarding the impact of depression on

illness intrusiveness and mental quality of life, and the impact of illness intrusiveness on

physical quality of life were supported.

Previous research in similar populations has established that depression and

illness intrusiveness are related constructs (Hegel et al., 1997; Konstam et al., 1995; Sears

et al., 1999). This study extends the literature to include IAD patients, who have been

shown to have unique psychological distress associated with their condition (Kay et al.,

1998). A decline in physical abilities that hinders participation in valued activities is an

integral part of Devins (1983) definition of illness intrusiveness. IAD patients whose

illness causes a decline from previous functioning may subsequently develop depression,

and view their illness as more intrusive. The correlation between illness intrusiveness









and physical quality of life is consistent with Devins' (1983) theory that the construct of

illness intrusiveness is a disruption of lifestyle that hinders participation in valued

activities. Patients whose functioning is significantly limited due to their illness will

most likely report a reduction in the quality of their physical abilities. Additionally, the

correlation and predictive relationship between the psychological construct of depression

and mental quality of life is consistent with Devins' (1983) biopsychosocial model. With

regard to the relationships between disease, treatment, and psychological factors, this

sample of IAD patients rated illness intrusiveness and quality of life similarly to the End-

Stage Renal Disease patients comprising Devins' original sample.

Implications for the Experience of Shock

Collectively, these results suggest that shock is not the factor most responsible for

reducing quality of life among IAD patients as it has been illustrated to be among ICD

patients (Namerow et al., 1999; Schron et al., 2002; Irvine et al., 2002). This discrepancy

may result from differences in perceived lack of control between these two populations.

IAD patients have the option of delivering the defibrillation charge manually, whereas all

shocks received by ICD patients are automatically received with little warning. Since AF

is not a life-threatening condition, IAD patients also have the option of avoiding the

defibrillation charge and experiencing the AF episode. In this way, IAD patients are able

to mentally separate the act of shock from other physical aspects of their illness. Even

IAD patients who receive automatic shocks can receive advanced warning and therefore

maintain a sense of control. Further, a defibrillation charge for IAD patients does not

indicate a life-threatening arrhythmia as it does for ICD patients, suggesting that ICD

patients may have a more emotional response to shock.









Most of the literature in this area indicates that, overall, shock is a physically

aversive experience (Murgatroyd & Camm, 1997; Sears et al., 1999; Sears & Conti,

2002; Namerow et al., 1999; Schron et al., 2002). Pauli and colleagues' (1999) research

clarified and disputed this idea by distinguishing the psychological effects of shock from

the physical effects. The present study, in conjunction with the work of Pauli and

colleagues (1999), indicates that IAD recipients will benefit from being psychologically

prepared for the emotional impact of defibrillation. Results suggest that IAD therapy is

well accepted, but may be hindered by psychological factors such as depression.

Depression and illness intrusiveness are related among IAD patients, lending support to

early research among ICD patients that highlights correlations between declines in

physical ability and the development of depression (Hegel et al., 1997; Konstam et al.,

1995). Most patients who are provided with appropriate cognitive-behavioral

interventions should adapt well to receiving an IAD, and will likely not experience

clinically significant levels of depression, illness intrusiveness, or reduced quality of life

(Kohn et al., 2000).

Clinical Implications

Clinically, this study highlights the need for healthcare providers to recognize,

acknowledge, and refer psychological treatment for symptoms of distress among IAD

patients in an attempt to reduce illness intrusiveness and optimize quality of life. The

majority of these patients do not experience clinically significant depression or illness

intrusiveness, but those who do will likely also experience reductions in physical and

mental quality of life. Clinicians should be educated about the effects that psychological

factors have on quality of life, and subsequently pay routine attention to both general and









disease-specific quality of life among IAD patients. Since AF is a non-life-threatening

condition, IAD patients can experience improved quality of life through various levels of

psychosocial intervention, such as in-patient psychological consultation, support groups

with other patients, and individual psychotherapy. This process will be facilitated by the

integration of psychologists as essential parts of IAD patient treatment teams, and by

future research exploring additional aspects of defibrillation, including a comparison

between the patient's subjective experience of shock and the objective shock data

recorded by the device

Strengths and Weaknesses of the Study

The current study has specific strengths and weaknesses to take into account when

interpreting this data. The comprehensive biopsychosocial design including both

objective medical information and subjective psychological testing data provide a more

complete view of the outcomes of interest than previous work with the IAD designed to

establish its efficacy (Gold, et al., 2001). Further, the effects of shocks were well

examined in the current data set and did not indicate the cumulative, detrimental effects

that one might expect. A weakness of the study includes the highly selected sample

utilized. Patients in this study were volunteers who were drug-refractory and failed at

least one anti-arrhythmic drug. Therefore, the results cannot be generalized to all patients

with AF. The willingness to participate as a subject in this trial certainly selects for some

personality variables that cannot be fully understood. The study also included baseline

medical variables but did not include baseline psychosocial variables other than quality of

life. In fact, because FDA investigators did not expect the significance of psychological

factors at the beginning of the study, the remaining psychosocial factors are measured at






32


only a single point in time. Therefore, we are unable to determine the course of patient

acceptance from the current data.
















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BIOGRAPHICAL SKETCH

Rebecca Owen Sotile was born in Winston-Salem, NC on January 1st, 1979, to

Wayne and Mary Sotile. She has one younger sister, Julia, with whom she remains very

close. She received a Bachelor of Arts in psychology from the University of North

Carolina at Chapel Hill in 2001. She is currently living in Gainesville, FL, pursuing her

Ph.D. in clinical and health psychology at the University of Florida Health Science

Center. Her future plans include mastery of clinical and research skills with a focus on

health psychology.