PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of jahaLink to Publisher's site
 
J Am Heart Assoc. 2013 October; 2(5): e000418.
Published online 2013 October 25. doi:  10.1161/JAHA.113.000418
PMCID: PMC3835256

Cardiac Rehabilitation Patient and Organizational Factors: What Keeps Patients in Programs?

Abstract

Background

Despite documented benefits of cardiac rehabilitation, adherence to programs is suboptimal with an average dropout rate of between 24% and 50%. The goal of this study was to identify organizational and patient factors associated with cardiac rehabilitation adherence.

Methods and Results

Facilities of the Wisconsin Cardiac Rehabilitation Outcomes Registry Project (N=38) were surveyed and records of 4412 enrolled patients were analyzed. Generalized estimating equations were used to account for clustering of patients within facilities. The results show that organizational factors associated with significantly increased adherence were relaxation training and diet classes (group and individual formats) and group‐based psychological counseling, medication counseling, and lifestyle modification, the medical director's presence in the cardiac rehabilitation activity area for ≥15 min/week, assessment of patient satisfaction, adequate space, and adequate equipment. Patient factors associated with significantly increased adherence were aged ≥65 years, the American Association of Cardiovascular and Pulmonary Rehabilitation (AACVPR) high‐risk category, having received coronary artery bypass grafting, and diabetes disease. Non‐white race was negatively associated with adherence. There was no significant gender difference in adherence. None of the baseline patient clinical profiles were associated with adherence including body mass index, total cholesterol, low‐density lipoprotein, high‐density lipoprotein, triglycerides, and blood pressure.

Conclusions

Factors associated with adherence to cardiac rehabilitation included both organizational and patient factors. Modifiable organizational factors may help directors of cardiac rehabilitation programs improve patient adherence to this beneficial program.

Keywords: adherence, cardiac rehabilitation, coronary heart disease, exercise, secondary prevention

Introduction

Cardiac rehabilitation (CR) is a class I indication for patients with coronary heart disease (CHD).1 Several major meta‐analyses have shown that participation in CR promotes a healthy lifestyle, reduces risk factors, improves health‐related quality of life, and decreases mortality and morbidity.27 Importantly, recent studies have demonstrated a dose‐response relationship with higher attendance associated with lower mortality and morbidity.89 However, between 24% and 50% of patients who enroll in CR programs withdraw from the program.1011 This problem of dropout is persistent, having been documented in the literature for at least 4 decades,1213 and continues to pose a challenge to health policy makers in the management of CHD.11,14

Several studies have been directed toward factors that improve patient adherence and completion of CR programs; the majority of these studies have examined patient factors.1417 While health system‐level factors that impact CR enrollment have been examined recently,1821 few studies have investigated the role of organizational and system‐level factors on CR adherence2223; also they are qualitative studies that do not quantify the strength of key findings. Moreover, to the best of our knowledge, there have been no studies that have examined the role of organizational and patient factors in patient adherence concurrently. Therefore, the aim of this study was to concurrently investigate the role of organizational and patient factors in CR adherence in a multisite study of 38 CR facilities in Wisconsin.

Methods

Data Sources

Data were provided by 38 of the 69 CR facilities in the Wisconsin Cardiac Rehabilitation Outcomes Registry (WiCORE) Project in 2010. Program managers or coordinators of the 69 CR facilities were contacted via email requesting consent for participation in the study. A web‐based survey that inquired into key organizational data was sent via email to 38 program managers and coordinators who chose to participate in the study. Patient data obtained from the WiCORE files included 4412 patients who enrolled in CR programs in these 38 CR facilities during the time period from January 1 to December 31, 2010, and were collected by the CR staff at each facility using the WiCORE web‐based interface. The present study was approved by the Institutional Review Board of Brandeis University.

Measures

Patient factors

The WiCORE patient data set included: gender, race, age, educational level, social support, health insurance status, tobacco use (“current” smoker defined as actively using tobacco products at the time of the assessment or having quit within the past 12 months; “former” smoker defined as having used tobacco products in the past, but quit more than 12 months prior to the assessment; or “never smoked”), American Association of Cardiovascular Pulmonary Rehabilitation (AACVPR) risk category for cardiac events during exercise (low, moderate, high, as defined in the AACVPR Guidelines (p 63),24 history of depression defined as whether the patient has a documented history of clinical depression (yes/no), days to start CR program (days from hospital admission, due to a cardiac event or referral date for angina diagnosis, to the first CR exercise session), admitting diagnosis and coronary procedures (yes/no): acute myocardial infarction (AMI), angina, heart failure, coronary artery bypass surgery (CABG), percutaneous coronary intervention (PCI), and valve replacement, comorbid conditions including diabetes, arthritis, gastrointestinal disease, pulmonary disease, back pain, peripheral vascular disease, renal disease, stroke, and musculoskeletal disease, as well as previous history of heart diseases (yes/no). Baseline levels of clinical measures were also collected including body mass index (BMI), total cholesterol, low‐density lipoprotein (LDL), high‐density lipoprotein (HDL), triglycerides, systolic blood pressure, diastolic blood pressure, hemoglobin A1‐c (A1C) for diabetic patients, left ventricular ejection fraction (%), physical activity (min/week), and medication use (yes/no): beta‐blockers, angiotensin‐converting enzyme inhibitors or angiotensin receptor blockers (ACEI/ARB), lipid medications, and aspirin.

Organizational factors

Facility variables included: (a) facility characteristics: geographical location (urban, rural defined by U.S. Census Bureau at http://www.census.gov/geo/www/ua/2010urbanruralclass.html), CR program location (in‐hospital, outside hospital), medical school affiliation (yes/no), and whether other rehabilitation services were offered (maintenance or Phase III CR, pulmonary rehabilitation) (yes/no); (b) reminders after missing 2 classes (yes/no); (c) medical director involvement at the activity area for ≥15 min/week (yes/no), as observed by the CR staff (program managers or coordinators); (d) CR program resources: offering gender‐specific classes (yes/no), scheduling classes before work and/or after work (yes/no), adequate equipment as judged by the CR staff (program managers or coordinators) (yes/no), adequate space as judged by the CR staff (program managers or coordinators) (yes/no), CR promotion to patients and healthcare providers (quarterly versus yearly/never), rewarding patients (yes/no), assessment of patient satisfaction (yes/no), provision of transportation (yes/no), and provision of parking (yes/no); and (e) types of CR services attended by patients (yes/no) including sessions on relaxation training (either individual or group format), diet (individual and group formats), psychological counseling (individual and group formats), lifestyle modification (individual and group formats), smoking cessation (individual and group formats), and medication counseling (individual and group formats).

Outcome

The outcome variable is adherence, which, in this study, is defined as attending at least the median number of exercise sessions (≥21) attended by the entire cohort.

Statistical Analyses

Summary statistics were used to describe the baseline characteristics and the proportion of adherents. Bivariate analyses were performed on patient‐ and organization‐level factors to assess differences between adherent patients (adherents) and nonadherents. The differences were assessed using P values obtained by generalized estimating equations (GEE) with the LOGIT link function. A logistic regression model was fitted to identify significant patient and organizational predictors for CR adherence, the dependent (dichotomous) variable. This final parsimonious model was chosen with a stepwise forward variable selection technique in which all patient and organizational factors listed under Methods: “Patient factors” and “Organizational factors” were entered in the model one by one. If a variable had a value of P<0.05, it was kept in the model for the next run in which a new variable was entered for examination. If a variable had a value of P≥0.05, it was removed from the model. Admitting diagnosis, age, sex, and race were always kept in the model as they have frequently been reported to be associated with adherence and the process continued until all patient and organizational variables were examined. The GEE procedure was used to account for clustering of patients within CR facilities. The LOGIT link function and the exchangeable working correlation matrix were used in the GEE analysis. A value of P<0.05 was considered statistically significant. All statistical analyses were performed using SPSS 19.0 (IBM Corporation).25

Results

Adherence and Patient Factors

Our cohort consisted of 4412 patients who attended a median of 21 CR sessions with a range of 1 to 67 sessions. The mean age (±standard deviation) of patients was 65±12 years; within the cohort, 30.4% were women and 95.3% were whites. The mean number of days from hospital admission due to a cardiac event, or referral date for angina diagnosis, to the first CR exercise session was 20±13 days. Among patient characteristics, adherence was significantly (P<0.05) associated with race, age, and AACVPR risk categories (Table 1). Adherence was also significantly associated with CABG procedure and diabetes diagnosis (both P<0.001) (Table 2). Conversely, adherence was not significantly associated with gender, educational status, social support, health insurance status, smoking status, history of depression, or comorbid conditions (Tables (Tables11 and and2).2). LDL cholesterol was the only variable among baseline clinical or physical variables that was significantly different between adherents and nonadherents 2.5±1.0 mmol/L (95.3±37.5 mg/dL) and 2.6±1.0 mmol/L (99.1±37.6 mg/dL), respectively (P=0.04). However, this small difference (0.1 mm/L or 3.8 mg/dL) is not clinically significant.

Table 1.
Patient Characteristics Associated With CR Adherence (Attending ≥21 CR Sessions)
Table 2.
Patient Diagnosis and Comorbidities Associated With CR Adherence (Attending ≥21 CR Sessions)

Adherence and Organizational Characteristics

Of the 38 CR facilities, one facility was affiliated with a medical school and one facility offered transportation for patients. All except 3 facilities offered a maintenance CR program (phase III). Table 3 presents organizational characteristics associated with adherence. Four organizational characteristics were positively associated with adherence: medical director involvement ≥15 min/week at the activity area (P=0.04), adequate equipment (P=0.03), adequate space (P=0.02), and assessment of patient satisfaction (P<0.02).

Table 3.
CR Facility Characteristics and Adherence Rates (Attending ≥21 CR Sessions)

Table 4 presents the CR services attended by patients. Six services were positively associated with adherence (P<0.05): group‐ and individual‐based diet sessions, group‐based psychological counseling, relaxation training, group‐based lifestyle modification, and group‐based medication counseling.

Table 4.
CR Services Associated With Adherence (Attending ≥21 CR Sessions)

Adherence and Regression Analysis

Patient characteristics

Results of the logistic regression model examining both the patient and organizational factors role in CR adherence are presented in Tables Tables55 and and6.6. Patient predictors of CR adherence are presented in Table 5. Older patients (aged ≥65 years) were more likely to adhere with CR than younger patients (aged <65 years). Non‐white patients were less likely to adhere than white patients. Patients with CABG, patients in the AACVPR high‐risk category, and diabetic patients were more likely to adhere than patients who did not have a CABG procedure, patients in the AACVPR low‐risk category, and patients without diabetes, respectively. None of the baseline clinical (lipid profile, blood pressure, hemoglobin A1‐c for diabetic patients, body mass index) or physical activity variables were a predictor of adherence.

Table 5.
Adjusted ORs of CR Adherence (Attending ≥21 CR Sessions) by Patient Characteristic
Table 6.
Adjusted ORs of CR Adherence (Attending ≥21 CR Sessions) by Characteristics of CR Facilities

Organizational characteristics

Table 6 describes organizational predictors of adherence. Patient attendance at each of the following CR services was positively and significantly associated with adherence: group‐ and individual‐based diet classes, group‐based psychological counseling, medication counseling, and lifestyle modification, as well as relaxation training (either individual or group format) classes. Other organizational factors positively and significantly associated with adherence included: presence of the medical director in the exercise area for ≥15 min/week as observed by program managers and coordinators, assessment of patient satisfaction, adequate space, and adequate equipment as judged by program managers and coordinators.

Discussion

This is the first study, to the best of our knowledge, to examine the role of organizational factors in explaining adherence to CR programs. The study includes a large number of patients (N=4412) who participated in CR at 38 program sites in Wisconsin from January 1 to December 31, 2010, and provides a comprehensive examination of organizational program factors as well as patient factors. A median number of 21 CR sessions was attended by this cohort, a number comparable to the median number of 25 sessions in 2 recent Medicare studies.89 In fact, the actual number of sessions patients attended upon completion of the CR program in our study varied by program and by patient though a standard program consists of 36 exercise sessions for Medicare beneficiaries.26 Because more than half of the cohort in this study is Medicare beneficiaries (aged ≥65 years), we expected to have a median number of sessions comparable to that of the Medicare beneficiaries (25 sessions).89

Notably, the average time from hospital admission due to a cardiac event or referral date for angina diagnosis to the first CR exercise session was 20±13 days. This was faster than the average in 2 recent studies, which average times from hospital discharge to CR enrollment of approximately 35 days.2728 Nevertheless, it will be worthwhile to investigate the reasons for such a lag in time documented in all these studies.

Patient Factors

Older patients (aged ≥65 years) were more likely to adhere than younger patients (aged <65 years) and non‐white patients were less likely to adhere than white patients confirming similar findings in published studies.15,2930 The positive association between adherence and CABG observed in this study also supports previously reported findings.9,31 We found that AACVPR high‐risk patients attended more CR sessions than AACVPR low‐risk patients—also confirming previously reported findings.32 We also observed higher adherence in patients with diabetes than without diabetes. Although the literature on adherence and diabetes is inconsistent: other studies have reported that patients with diabetes were more likely to adhere than patients without diabetes,32 less likely to adhere,33 and to have similar adherence rates.15 Differences in the association between diabetes and adherence may partially be explained by the variation in the cut‐off point, in terms of number of CR sessions, used for adherence definition across published studies. However, an additional possible explanation for our finding could be that patients with diabetes were prescribed more CR sessions than patients without diabetes because diabetic patients were at higher AACVPR risk compared to their counterparts; in this study, 75.6% of patients with diabetes were either at high‐ (38.0%) or moderate‐risk (37.6%) according to the AACVPR‐risk categories.

Organizational Factors

Diversity in the services offered and meeting explicit patient needs have been underlined as means to improve adherence to CR.3435 In this study, patients were more likely to adhere in CR programs where patients attended diet classes and relaxation training (either individual or group format) and group‐based psychological counseling, medication counseling, and lifestyle modification. Interestingly, adherence was associated with group rather than individual classes for psychological counseling, medication counseling, and lifestyle modification.

Group sessions in which participants felt they were members of a group, or a club, and were welcomed, felt they belonged, and shared their experiences with patients with similar conditions have all been shown to be strong motivating factors to adhere to CR whereas patients who did not experience group solidarity were more likely to drop out.22,36 Our observation that group‐based sessions seem to keep patients in CR programs longer than individual‐based sessions is consistent with these observations.

Diet classes were predictors of adherence in the present study. This result may indicate that patients who attended diet classes perceived additional benefits of the CR program—a factor frequently documented as a predictor of adherence.22,3637 In diet classes, patients learn strategies to translate knowledge into behavioral change such as healthy eating habits for eating at or outside home and using recipes of inexpensive and healthy foods. In addition, participation of patients' spouses at group diet classes may provide a family support for patients to attend more CR sessions as reported by some program managers/coordinators who participated in our study. Patients whose spouses participated actively in group counseling were found to have the highest compliance with weekly exercise compared to other groups in which spouses did not participate.38

Previous studies have demonstrated psychological distress as a predictor of patient drop‐out from CR programs17,39 while relaxation training has been associated with reduced distress and depression.4041 Consistent with these observations, patients in our study who received relaxation training and psychological counseling were more likely to adhere to CR than patients not participating in these services.

Lifestyle modification has been perceived as a challenge to CHD patients in a qualitative study; this is probably due to both the implementation of too many changes at once and to the lack of professional support in the community.42 Our finding of positive association between lifestyle modification and adherence to CR reveals the potential of this aspect of CR services in addressing this challenge for CHD patients. In particular, lifestyle modification classes addressed content aspects critical to CHD patients, including assessment, education, and monitoring of weight loss, tobacco cessation, stress management, and dietary and physical activity behaviors, as well as support from a health professional who helps empower patients to make practical lifestyle changes and to overcome obstacles.18,4344 Pertinent to CR staff support, we found that involvement in the exercise area by the medical director for ≥15 min/week was positively associated with adherence. It may well be an indirect effect of the medical director whose presence in the activity area positively influences the CR staff, and consequently they have greater influence on patients' adherence and performance. Another explanation could be that the visibility of the medical director to patients during exercise keeps patients in a program, particularly if the director is the referring physician as previous studies have shown that the referring physician's support is an influential factor in CR participation and adherence.18,43 Frequent encouragement by professionals and discussing progress has been reported to be among the most important CR features for continuing in CR programs.45

Our finding of a positive association between assessment of patient satisfaction and CR adherence supports recent recommendations by the Michigan Society for Cardiovascular and Pulmonary Rehabilitation46 on the use of patient satisfaction surveys as a tool to improve adherence to CR. Assessment of patient satisfaction has increasingly gained the attention of policy makers because it provides an opportunity for CR managers to identify and address problems and, therefore, potentially improve health services.47 Adequate resources, including space and equipment, as judged by our survey respondents, including program mangers and coordinators, were positively associated with adherence in this study. Conversely, inadequate physical space and lack of equipment have been identified as barriers to CR enrollment in qualitative studies.4849 Our results support and extend adequate space and equipment as predictors of CR adherence.

Limitations

Due to data limitations, we were unable to examine a number of factors that have been associated with adherence in other published studies; these factors included copayment,50 income,37 self‐motivation,37,51 and work demands.32 Another factor for which data were unavailable was the number of CR sessions covered by the patient's health insurance plan, which could have limited the number of CR sessions an individual patient was permitted to attend. An additional limitation is related to the nature of observational studies. Some of the services attended by patients could be considered as outcomes in our GEE modeling rather than predictors (Table 6). For example, the more exercise sessions patients attend, the more likely they are to get the educational classes because these classes are usually held in conjunction with the exercise session. Self‐selection bias must be considered as only 38 of the 69 CR facilities in the WiCORE Project (55%) chose to participate in our study in 2010, hence limiting the generalizability of our findings. In addition, the relatively small number of CR programs included in the analysis (n=38) may explain the failure to detect statistically significant relationships between adherence indicators and some of the organizational factors. For example, nonsignificant trends were observed in the associations between adherence and the following factors: CR programs located inside hospitals, gender‐specific classes, CR classes held after work hours, available parking, and CR promotion. Therefore, we suggest replicating the present adherence study with a larger number of CR facilities.

Conclusions

Both organizational and patient factors have key roles in CR adherence. The interpretation of the results of this study has important implications for CR program directors; organizational factors do influence patient adherence with CR programs. Some modifiable organizational factors have been identified, including medical director involvement, adequate space and equipment, assessment of patient satisfaction, and the characteristics of educational classes, each of which may help decision makers improve patient adherence to CR programs.

Disclosures

None.

Acknowledgments

The authors would like to thank the Wisconsin Society for Cardiovascular and Pulmonary Health and Rehabilitation members particularly the WiCORE administrators and staff who provided the data, specifically, Mark Vitcenda, MS (WiCORE Project Manager) for providing the data files and reviewing the manuscript, Sandra Zemke, BSN (Supervisor of CR programs, Aurora St. Luke's Medical Center) for her contribution in the development of the organizational questionnaire, and the many CR staff participating in WiCORE for their efforts in entering patient data and providing invaluable feedback.

References

1. Smith S, Benjamin E, Bonow R, Braun L, Creager M, Franklin B, Gibbons R, Grundy S, Hiratzka L, Jones D, Lloyd‐Jones D, Minissian M, Mosca L, Peterson E, Sacco R, Spertus J, Stein J, Taubert K. AHA/ACCF secondary prevention and risk reduction therapy for patients with coronary and other atherosclerotic vascular disease: 2011 update: a guideline from the American Heart Association and American College of Cardiology Foundation. Circulation. 2011; 124:2458-2473. [PubMed]
2. Oldridge N. Exercise‐based cardiac rehabilitation in patients with coronary heart disease: meta‐analysis outcomes revisited. Future Cardiol. 2012; 8:729-751. [PubMed]
3. Lawler P, Filion K, Eisenberg M. Efficacy of exercise‐based cardiac rehabilitation post‐myocardial infarction: a systematic review and meta‐analysis of randomized controlled trials. Am Heart J. 2011; 162:571-584. [PubMed]
4. Heran BS, Chen JM, Ebrahim S, Moxham T, Oldridge N, Rees K, Thompson DR, Taylor RS. Exercise‐based cardiac rehabilitation for coronary heart disease. Cochrane Database Syst Rev. 2011; 7:CD001800. [PubMed]
5. Clark AM, Hartling L, Vandermeer B, McAlister FA. Meta‐analysis: secondary prevention programs for patients with coronary artery disease. Ann Intern Med. 2005; 143:659-672. [PubMed]
6. Oldridge NB, Guyatt GH, Fischer ME, Rimm AA. Cardiac rehabilitation after myocardial infarction. Combined experience of randomized clinical trials. JAMA. 1988; 260:945-950. [PubMed]
7. Taylor RS, Brown A, Ebrahim S, Jolliffe J, Noorani H, Rees K, Skidmore B, Stone JA, Thompson DR, Oldridge N. Exercise‐based rehabilitation for patients with coronary heart disease: systematic review and meta‐analysis of randomized controlled trials. Am J Med. 2004; 116:682-692. [PubMed]
8. Suaya JA, Stason WB, Ades PA, Normand SL, Shepard DS. Cardiac rehabilitation and survival in older coronary patients. J Am Coll Cardiol. 2009; 54:25-33. [PubMed]
9. Hammill B, Curtis L, Schulman K, Whellan DJ. Relationship between cardiac rehabilitation and long‐term risks of death and myocardial infarction among elderly Medicare beneficiaries. Circulation. 2010; 121:63-70. [PMC free article] [PubMed]
10. Carlson JJ, Johnson JA, Franklin BA, VanderLaan RL. Program participation, exercise adherence, cardiovascular outcomes, and program cost of traditional versus modified cardiac rehabilitation. Am J Cardiol. 2000; 86:17-23. [PubMed]
11. Scane K, Alter D, Oh P, Brooks D. Adherence to a cardiac rehabilitation home program model of care: a comparison to a well‐established traditional on‐site supervised program. Appl Physiol Nutr Metab. 2012; 37:206-213. [PubMed]
12. Hellerstein HK. Exercise therapy in coronary disease. Bull NY Acad Med. 1968; 44:1028-1047. [PubMed]
13. Oldridge NB, Wicks JR, Hanley C, Sutton JR, Jones NL. Noncompliance in an exercise rehabilitation program for men who have suffered a myocardial infarction. Can Med Assoc J. 1978; 118:361-364. [PMC free article] [PubMed]
14. Murray J, Craigs CL, Hill KM, Honey S, House A. A systematic review of patient reported factors associated with uptake and completion of cardiovascular lifestyle behaviour change. BMC Cardiovasc Disord. 2012; 12:120. [PMC free article] [PubMed]
15. Soleimani A, Abbasi A, Nejatian M, Salarifar M, Darabian S, Karimi AA, Davoodi S, Kassaian SE, Abbasi SH, Sheikhfathollahi M. Factors predicting discontinuation of a hospital‐based cardiac rehabilitation programme. Kardiol Pol. 2009; 67:140-146. [PubMed]
16. Marzolini S, Brooks D, Oh P. Sex differences in completion of a 12‐month cardiac rehabilitation programme: an analysis of 5922 women and men. Eur J Cardiovasc Prev Rehabil. 2008; 15:698-703. [PubMed]
17. Yohannes AM, Yalfani A, Doherty P, Bundy C. Predictors of drop‐out from an outpatient cardiac rehabilitation programme. Clin Rehabil. 2007; 21:222-229. [PubMed]
18. Grace SL, Gravely‐Witte S, Brual J, Monette G, Suskin N, Higginson L, Alter DA, Stewart DE. Contribution of patient and physician factors to cardiac rehabilitation enrollment: a prospective multilevel study. Eur J Cardiovasc Prev Rehabil. 2008; 5:548-556. [PMC free article] [PubMed]
19. Grace SL, Chessex C, Arthur H, Chan S, Cyr C, Dafoe W, Juneau M, Oh P, Suskin N. Systematizing inpatient referral to cardiac rehabilitation 2010: Canadian Association of Cardiac Rehabilitation and Canadian Cardiovascular Society joint position paper endorsed by the Cardiac Care Network of Ontario. Can J Cardiol. 2011; 27:192-199. [PubMed]
20. Gravely‐Witte S, Leung YW, Nariani R, Tamim H, Oh P, Chan VM, Grace SL. Effects of cardiac rehabilitation referral strategies on referral and enrollment rates. Nat Rev Cardiol. 2010; 7:87-96. [PubMed]
21. Brown TM, Hernandez AF, Bittner V, Cannon CP, Ellrodt G, Liang L, Peterson ED, Piña IL, Safford MM, Fonarow GC. American Heart Association Get With The Guidelines Investigators Predictors of cardiac rehabilitation referral in coronary artery disease patients: findings from the American Heart Association's Get With The Guidelines Program. J Am Coll Cardiol. 2009; 54:515-521. [PMC free article] [PubMed]
22. Pentecost C, Taket A. Understanding exercise uptake and adherence for people with chronic conditions: a new model demonstrating the importance of exercise identity, benefits of attending and support. Health Educ Res. 2011; 26:908-922. [PubMed]
23. Jones M, Jolly K, Raftery J, Lip GY, Greenfield S. ‘DNA’ may not mean ‘did not participate’: a qualitative study of reasons for non‐adherence at home‐ and centre‐based cardiac rehabilitation. Fam Pract. 2007; 24:343-357. [PubMed]
24. American Association of Cardiovascular and Pulmonary Rehabilitation Guidelines for Cardiac Rehabilitation and Secondary Prevention Programs. 2004. 4th edChampaign, IL: Human Kinetics.
25. IBM Corporation IBM SPSS Statistics for Windows, Version 19.0. 2010. Armonk, NY: IBM Corporation.
26. Centers for Medicare and Medicaid Services: Decision Memo for Cardiac Rehabilitation Programs (CAG‐00089R) Available at: http://www.cms.gov/medicare-coverage-database/details/nca-decision-memo.aspx?NCAId=164&NcaName=Cardiac+Rehabilitation+Programs&NCDId=36&ncdver=3&IsPopup=y&bc=AAAAAAAACAAAAA%3D%3D&. Accessed July 20, 2013.
27. Zullo MD, Jackson LW, Whalen CC, Dolansky MA. Evaluation of the recommended core components of cardiac rehabilitation practice: an opportunity for quality improvement. J Cardiopulm Rehabil Prev. 2012; 32:32-40. [PubMed]
28. Russell KL, Holloway TM, Brum M, Caruso V, Chessex C, Grace SL. Cardiac rehabilitation wait times: effect on enrollment. J Cardiopulm Rehabil Prev. 2011; 31:373-377. [PubMed]
29. Sarrafzadegan N, Rabiei K, Shirani S, Kabir A, Mohammadifard N, Roohafza H. Drop‐out predictors in cardiac rehabilitation programmes and the impact of sex differences among coronary heart disease patients in an Iranian sample: a cohort study. Clin Rehabil. 2007; 21:362-372. [PubMed]
30. Caulin‐Glaser T, Maciejewski PK, Snow R, LaLonde M, Mazure C. Depressive symptoms and sex affect completion rates and clinical outcomes in cardiac rehabilitation. Prev Cardiol. 2007; 10:15-21. [PubMed]
31. Turner S, Bethell HJ, Evans J, Goddard JR, Mullee MA. Patient characteristics and outcomes of cardiac rehabilitation. J Cardpulm Rehabil. 2002; 22:253-260. [PubMed]
32. Sanderson BK, Phillips MM, Gerald L, DiLillo V, Bittner V. Factors associated with the failure of patients to complete cardiac rehabilitation for medical and nonmedical reasons. J Cardiopulm Rehabil. 2003; 23:281-289. [PubMed]
33. Wittmer M, Volpatti M, Piazzalonga S, Hoffmann A. Expectation, satisfaction, and predictors of dropout in cardiac rehabilitation. Eur J Prev Cardiol. 2011; 19:1082-1088. [PubMed]
34. Clark A, Barbour R, White M, MacIntyre P. Promoting participation in cardiac rehabilitation: patient choices and experiences. J Adv Nurs. 2004; 47:5-14. [PubMed]
35. Gutin B, Prince L, Stein R. Survey of cardiac rehabilitation centers in New York City. J Community Health. 1990; 15:227-238. [PubMed]
36. Shahsavari H, Shahriari M, Alimohammadi N. Motivational factors of adherence to cardiac rehabilitation. Iran J Nurs Midwifery Res. 2012; 17:318-324. [PMC free article] [PubMed]
37. Daly J, Sindone AP, Thompson DR, Hancock K, Chang E, Davidson P. Barriers to participation in and adherence to cardiac rehabilitation programs: a critical literature review. Prog Cardiovasc Nurs. 2002; 17:8-17. [PubMed]
38. Dracup K, Meleis AI, Clark S, Clyburn A, Shields L, Staley M. Group counseling in cardiac rehabilitation: effect on patient compliance. Patient Educ Couns. 1984; 6:169-177. [PubMed]
39. Glazer KM, Emery CF, Frid DJ, Banyasz RE. Psychological predictors of adherence and outcomes among patients in cardiac rehabilitation. J Cardiopulm Rehabil Prev. 2002; 22:40-46. [PubMed]
40. Van DJ, White A. Relaxation therapy for rehabilitation and prevention in ischaemic heart disease: a systematic review and meta‐analysis. Eur J Cardiovasc Prev Rehabil. 2005; 12:193-202. [PubMed]
41. Vázquez FL, Torres A, Blanco V, Díaz O, Otero P, Hermida E. Comparison of relaxation training with a cognitive‐behavioural intervention for indicated prevention of depression in university students: a randomized controlled trial. J Psychiatr Res. 2012; 46:1456-1463. [PubMed]
42. Condon C, McCarthy G. Lifestyle changes following acute myocardial infarction: patients perspectives. Eur J Cardiovasc Nurs. 2006; 5:37-44. [PubMed]
43. Ades P, Waldmann M, Polk D, Coflesky J. Referral patterns and exercise response in the rehabilitation of female coronary patients aged greater than or equal to 62 years. Am J Cardiol. 1992; 69:1422-1425. [PubMed]
44. Wormald H, Ingle L. GP exercise referral schemes: improving the patient's experience. Health Education Journal. 2004; 63:362-373.
45. Moore SM, Kramer FM. Women's and men's preferences for cardiac rehabilitation program features. J Cardpulm Rehabil. 1996; 16:163-168. [PubMed]
46. Michigan Society for Cardiovascular and Pulmonary Rehabilitation Michigan Cardiac Rehabilitation Outcomes Report 2008–2009. Michigan Department of Community; 2011. Available at: http://www.michigan.gov/documents/mdch/Outcomes_Document_353656_7.pdfAccessed February 25, 2013.
47. Boyer L, Francois P, Doutre E, Weil G, Labarere J. Perception and use of the results of patient satisfaction surveys by care providers in a French teaching hospital. Int J Qual Health Care. 2006; 18:359-364. [PubMed]
48. Gurewich D, Prottas J, Bhalotra S, Suaya JA, Shepard DS. System‐level factors and use of cardiac rehabilitation. J Cardiopulm Rehabil Prev. 2008; 28:380-385. [PubMed]
49. Rahim A. Overview of Cardiac Rehabilitation Programs in Malaysia Updates & Innovations. Kuala Lumpur, Malaysia: National Heart Institute; 2012. Available at: http://www.ijncollege.edu.my/PDF/AizaiCRP2012Edited.pdfAccessed March 11, 2013.
50. Cooper AF, Jackson G, Weinman J, Horne R. Factors associated with cardiac rehabilitation attendance: a systematic review of the literature. Clin Rehabil. 2002; 16:541-552. [PubMed]
51. Jack K, McLean SM, Moffett JK, Gardiner E. Barriers to treatment adherence in physiotherapy outpatient clinics: a systematic review. Man Ther. 2010; 15:220-228. [PMC free article] [PubMed]

Articles from Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease are provided here courtesy of Wiley-Blackwell