Heart disease is the leading cause of death in adults worldwide.1 Physical activity (PA) is a key health behavior for preventing and improving the symptoms of heart disease.2 Indeed, engaging in regular PA has cardioprotective benefits and can reduce the incidence of cardiovascular events.3 Evidence indicates that a volume of PA of just 75 min/wk can lead to health benefits.4
Cardiac rehabilitation (CR) is a medically supervised program addressing health behavior changes and promoting self-management among individuals with heart disease.5 It includes a focus on PA counseling and training to help initiate regular PA.6 Participation in CR has shown to decrease total and cardiac mortality by 20% to 26%,7 and approximately 70% to 85% of participants report that they achieve the recommended PA guidelines while participating in CR.8,9 However, with only 38% to 56% of CR participants meeting PA guidelines 1 yr after CR program completion,10,11 long-term maintenance of PA among this population remains a challenge. Few CR programs have addressed long-term maintenance of PA or incorporated strategies to assist patients in maintaining PA over the long-term. Recognizing this gap, researchers have begun to develop interventions that can assist with PA and/or exercise maintenance among post-CR populations. This article reports on a systematic review of the literature for PA and exercise interventions among post-CR populations and examines the effect on maintenance. This review includes both concepts of PA and exercise to include a broader range of interventions. While exercise is PA that is planned and structured, PA is any movement that requires an increase in energy expenditure that is greater than resting requirement.
A systematic review was performed to identify interventions that aim to maintain PA or exercise levels in adults after CR in any country. This review adheres to the reporting guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement12 and addresses the items outlined in “A Measurement Tool to Assess Systematic Reviews” (AMSTAR) checklist.13,14 The systematic review methodology was prospectively registered in PROSPERO (registration number: CRD42016039426).
Eligible study designs included only randomized controlled trials (RCTs). The inclusion criteria included participants who were graduates of a CR program and interventions aimed at maintaining and/or increasing PA or exercise post-CR, compared with usual care. Excluded were study designs other than RCTs and interventions that did not include a PA component or exercise or were not post-CR. All intervention durations and duration of CR programs were considered. The primary outcome was change in PA or exercise. Both self-report and objective measures of PA and exercise were included.
A search of electronic databases included Ovid MEDLINE In-Process and Other Non-Indexed Citations (1946 to present); EMBASE Classic + (1947 to present); CINAHL (1981 to present); SPORTDiscus; and Dissertations and Theses (1980 to present) and were searched from inception to July 2016. The search strategy was developed with the assistance of a research librarian and was carried out by N.M. The strategy is illustrated using the MEDLINE search as an example (see Supplemental Digital Content 1, available at: http://links.lww.com/JCRP/A102) and was modified according to the indexing systems of the other databases. Gray literature, such as theses and dissertations, conference abstracts, and unpublished data and manuscripts (provided by original authors), that met the inclusion criteria was obtained. The bibliographies of key studies selected for the review and related systematic reviews were examined to identify further studies.
Papers were imported into EndNote (version X7.5.3, Thompson Reuters) and duplicates were removed using the “duplicate” function. Remaining duplicates were removed manually. Two reviewers (N.M. and S.S.) completed title and abstract screening, based on inclusion and exclusion criteria, to identify potentially relevant papers. The full texts of all studies that met the inclusion criteria were then obtained and reviewed independently by N.M. and S.S. Reasons for exclusion were recorded using a standardized data extraction form, which was created prior to data extraction. Any disagreements that arose between the reviewers were resolved through discussion or with a third reviewer (R.R.) until consensus was reached.
Data were extracted independently by N.M. and verified by S.S. from studies using Review Manager (RevMan) 5.3 (The Cochrane Collaboration, 2012, The Nordic Cochrane Centre, Copenhagen, Denmark). Disagreements were resolved through discussion between N.M. and S.S. and consulting article full texts until consensus was reached. Reviewers were not blinded to the authors or journals when extracting data. Extracted information consisted of participant characteristics (sample size, mean age, sex distribution, population), intervention description, outcomes (methods of measurement, units of measurement, follow-up length), and results (means and standard deviations at follow-up). The primary outcome measure was the mean change in PA or exercise following exposure to an intervention. Longest follow-up data available for each study were used, as outlined by the Cochrane handbook.15 Unpublished data were acquired through e-mail contact with authors of articles that described a PA or exercise outcome but did not report the data. When specific data were missing from an article, 2 attempts were made to contact the correspondence author by e-mail.
Enough studies provided PA or exercise data with comparable outcomes to conduct a meta-analysis. When possible, continuous outcomes were transformed into uniform measurement scales. One study provided outcomes by month and this was transformed to week by assuming an average of 4.3 wk in a calendar month. Metabolic equivalent (MET)-minutes per week (MET-min/wk) were transformed to calories per week (kcal/wk) by assuming the weight of the average person to be 150 lb.16 Since not all studies could be included in the meta-analyses (units not comparable), a descriptive synthesis of the evidence for all studies was performed.
Forest plots and the meta-analyses were created using RevMan 5.3 to compare the mean differences and 95% CIs in post-intervention PA between intervention and control groups. One study17 included 2 different intervention arms and in this case both interventions were included in the appropriate meta-analysis and the control group sample size was divided to include half in each meta-analysis as per the Cochrane handbook.15 A random-effects meta-analysis was used to provide an overall summary measure of effect (mean difference) and 95% CI for each PA outcome type. Standardized mean differences (SMD) were used because of the variability in the measurement methods for assessing PA across studies (eg, different objective and self-report measures). This allowed the results of the studies to be standardized on a uniform scale and represent the general effect size of the intervention.15A priori subgroup analyses were performed to test differences in the length of the intervention, length of CR, and objectively versus subjectively measured PA or exercise. Subgroup analyses were conducted within the outcome of exercise sessions/wk, which was the only exercise outcome with at least 10 studies included (as per the Cochrane handbook).15 Only 1 study within exercise sessions/wk outcome used an objective measure; therefore, an examination of objective versus subjective measures could not be conducted. A sensitivity analysis was completed to assess whether differences existed between unpublished and published data.
ASSESSMENT OF RISK OF BIAS AND QUALITY OF EVIDENCE
Risk of bias in included studies was evaluated using methods outlined in the Cochrane Handbook for Systematic Reviews of Interventions to assess the risk of selection, detection, attrition, and reporting biases.15 Risk of bias was assessed using RevMan 5.2 and was carried out by 2 independent assessors (N.M. and S.S.). If disagreements between assessors occurred, consensus was achieved through discussion.
The electronic database search identified 3313 articles (Figure 1). Of these articles, 1010 were identified in MEDLINE, 1476 in EMBASE, 609 in CINAHL, and 218 in SPORTDiscus. After deleting duplicates, 2660 relevant articles remained. A preliminary title and abstract review resulted in the retrieval of 294 articles for full-text screening. Contact with authors and searching of bibliographies identified an additional 5 articles. Of these 299 articles, 25 studies met the criteria for inclusion in the synthesis and 19 were included in the meta-analysis. Reasons for excluding studies included duplicates (n = 8), no measure of PA (n = 17), not an RCT (n = 63), not a post-CR population (n = 153), not a PA intervention (n = 22), unable to locate/access (n = 2), and unable to contact author (n = 4). Duplicate studies were retained on the basis of most recent data.
A summary of the included studies is available in the Table. These studies were published over a 20-yr period from 1995 to 2015. The included studies were conducted in 15 countries with 7 studies conducted in the United States,22,23,30,34,39–41 2 in Canada,35,38 2 in Belgium,24,25 2 in Italy,26,27 and 2 in Norway.19,37 The remainder were from Iran,18 Switzerland,20 Australia,21 France,28 Sweden,29 Scotland,31 Japan,32 Netherlands,33 Germany,17 and Poland.36 All studies used an RCT design. All studies were published in English.
The number of participants in each study ranged from 1322 to 3241.27 The mean sample size at baseline was 232, with a total number of 5804 participants at baseline and 5457 total participants at follow-up. Overall, 80.2% of the participants were male at baseline and the mean age of all participants at baseline was 60.4 yr. Most of the studies did not report any sex-specific results. One study reported that women tended to perform more PA sessions at follow-up than men36 and 3 studies reported no significant differences for the PA outcome between men and women.20,39,40
Individual study characteristics of included studies are summarized in Supplemental Digital Content Table 2, available at: http://links.lww.com/JCRP/A103. Intervention length ranged from 15 min36 to 3 yr.27 The modal intervention length was 12 wk. Three studies incorporated an online or mobile component,19,24,25 2 studies used telemonitoring,24,25 and 3 studies focused on the use of pedometers.21,32,34 Ten studies incorporated strategies such as addressing barriers, problem solving, and counseling. Twelve studies implemented strategies such as self-monitoring, including exercise logs and diaries, goal setting, and feedback. Seven interventions took place in a clinical setting,18,26,27,33,36,37,39 1 intervention took place in both a clinical setting and a home setting,18 and the remainder took place at home.
Length of CR preceding the intervention varied, ranging from 2 wk36 to 1 yr.29 The content and setting of CR also differed depending on the country in which it was provided. Four studies did not clarify the length or provide a description of CR.
There was considerable variety in the measurement of PA and exercise behavior. Nine of the studies used objective measures of PA or exercise24,25,28,31–34,39,40 and the remainder used subjective measures. The objective measures included triaxial and uniaxial accelerometers, pedometers, and a portable wristwatch heart rate monitor. The subjective measures included questionnaires, such as the Godin Leisure-Time and Minnesota Leisure-Time, and exercise diaries. Follow-up time ranged from 8 wk34 to 2 yr.26 A few studies reported on both a self-report and an objective measure and in these cases, the objective measures were used.
There was also considerable variety across outcomes. Nine studies used exercise sessions/wk.17,21–23,29,36–38,41 while 1 study used exercise sessions/mo.39 Five studies used steps/d.24,25,32–34 Two studies used MET-min/wk18,19 and 2 studies used kcal/wk.28,35 One study used minutes of moderate to vigorous physical activity/wk and 1 study used activity counts/wk.31 One study used a dichotomous outcome of PA or no PA20 and 1 study retrieved ordinal data related to level of exercise intensity.26 The remainder used scores on questionnaires.
RISK OF BIAS IN INCLUDED STUDIES
A summary of the risk of bias assessment can be seen in Supplemental Digital Content Figure 3, available at: http://links.lww.com/JCRP/A104. Overall, there were a high number of “unclear” verdicts, with many articles not reporting any information related to most biases. The majority of studies did report on randomization or blinding of participants or assessors. In PA studies, it is typically not possible to blind participants or treatment delivery personnel to allocation, creating a potential source of bias into the delivery.42 Similarly, performance bias can be difficult to assess in PA interventions as participants and treatment delivery personnel could not be blinded to treatment allocation. The largest risk of bias came from selection bias (mainly issues with allocation concealment) and attrition bias (issues with participants lost to follow-up). Most articles reported on all outcomes at all time points, including nonsignificant effects.
EFFECTS OF INTERVENTIONS
Thirteen studies reported significant differences between the intervention group and the control group for the PA outcome at the longest follow-up18–30,32–34,36,40 and 7 studies reported no significant difference between the intervention and control groups at the longest follow-up.17,31,35,37–39,41 Both interventions that encouraged family or spousal support18,33 were effective. Interventions mainly delivered by telephone were not consistently effective.31,35,41
A total of 19 studies tracked similar outcome variables and were able to be included in the meta-analysis. Overall, results of the meta-analysis found a significant difference in PA in the intervention groups compared with the control groups, via multiple exercise outcomes including exercise sessions per week (SMD = 0.20; 95% CI, 0.04-0.35) (Figure 2), kcal/wk (SMD = 0.59; 95% CI, 0.19-0.98) (Figure 3), and daily steps (SMD = 2.14; 95% CI, 0.90-3.38) (Figure 4).
Studies using number of exercise sessions per week as the outcome were mostly homogenous (I2 = 15%, P = .30). Studies measuring kcal/wk and steps per day revealed high levels of statistical heterogeneity between studies and therefore require caution when interpreting the results (I2 = 84%, P < .0002; I2 = 96%, P < .00001).
SUBGROUP AND SENSITIVITY ANALYSES
Results of the sensitivity analyses did not identify differences between the unpublished24,25,37 and published data. Therefore, the unpublished data were retained in the meta-analysis. Subgroup analyses examined length of preceding CR program before the intervention and length of intervention. No significant difference was observed for length of CR program; however, only interventions lasting ≥12 wk were effective (<12 wk SMD = 0.12; 95% CI, −0.16-0.40; I2 = 38%, P = .2 and ≥12 wk SMD = 0.25; 95% CI, 0.05-0.45; I2 = 10%, P = .35).
This systematic review examined the effectiveness of interventions to maintain PA among adults who have completed CR. Results from the descriptive synthesis combined with the meta-analysis suggest that PA and exercise interventions post-CR can help individuals with heart disease maintain PA in the long-term compared with controls. Although length of the preceding CR did not demonstrate a significant difference when it came to intervention effectiveness, the duration of the intervention was significant, with effective interventions lasting ≥12 wk.
The interventions in the included studies involved a range of strategies and delivery methods. Online/mobile interventions and pedometer-based interventions were consistently effective. Previous systematic reviews of internet- and/or mobile-based interventions and pedometer interventions for PA have reported consistent evidence that such programs are effective in increasing PA.43–45 Although rehospitalization data were not collected in the present review, a study examining a telemonitoring intervention reported fewer cardiovascular events among the intervention group, resulting in gross cost savings of US $1418 per patient.46 One study examining the effect of a pedometer intervention found the intervention to be associated with a 12% reduction in cardiac hospital admission rates.33 Pedometer and internet- or mobile-based interventions may be cost-effective alternatives to supervised exercise in the maintenance phase.
In a previous systematic review of PA interventions for individuals post-CR, Chase47 found that interventions consisting of behavioral strategies and combined behavioral and cognitive strategies were more successful in PA behavior change than cognitive strategies alone. Chase also noted the variety in CR programs across different countries in terms of CR length, content, and setting, which created difficulties with comparing the post-CR interventions. This review addressed this issue by documenting CR characteristics and length for each included study and conducting a subgroup analysis. This analysis found that length of preceding CR did not demonstrate significant differences for intervention effectiveness.
Participants were predominantly male and <65 yr of age; therefore, generalizability to female and older adults is limited. Cultural and socioeconomic demographics were also not consistently addressed in the included studies. Sex-specific findings were mostly not reported in the studies. However, 3 studies reported much higher attrition rates among women than among men,19,39,40 confirming the need to address sex and gender differences in PA research among individuals with heart disease. Physical activity maintenance is even more challenging among women with heart disease, who report PA levels that are significantly lower than in men both during and after CR.9,48–50 Given the importance of sex-based analysis and underrepresentation of women in these studies, this is an important area for further research.
The included studies used a range of both subjective and objective PA measures. Because of the range in PA outcomes tracked in the included studies, a subgroup analysis of subjective and objective measures was not possible. Both subjective and objective measures have limitations. Self-report measures may bring about an overestimation of PA and some questionnaires tend to ignore brief or low-intensity bursts of PA.51 In addition, participants tend to recall purposeful PA better than incidental PA.52
Objective measures can create a reactive response and pedometers and accelerometers respond poorly to activities such as cycling, skating, load carrying, and other nonstandard activities.51 There is also a lack of consistency in approaches to translating accelerometer signals into energy expenditure units.53 One systematic review comparing direct and self-report measures for assessing PA in adults found low to moderate correlations between the 2 methods, suggesting that measurement method can significantly impact on the observed levels of PA.54 There is a need for consistent assessment of PA in research to accurately assess and compare the effectiveness of PA interventions and impacts on health. Additional limitations of this review include the use of exclusively English language publications, which may have introduced a potential for English bias, and the use of Bushman's16 recommendation of transforming MET-min/wk to kcal/wk using an average body weight of 150 lb, which is likely an underestimation of body weight in a population with heart disease.
A qualitative synthesis exploring factors affecting PA maintenance among people who have completed CR found that barriers to PA maintenance included physical limitations and illnesses such as obesity, arthritis and back pain, lack of social support, lack of support with the transition from hospital-based PA to community or home-based PA, cost and perceived safety of the exercise program, and availability and accessibility of PA opportunities and options.55 Given the effectiveness of pedometer interventions, these interventions could promote walking as an accessible, safe, and inexpensive form of PA for individuals to ensure the continuity of their PA after CR. We know that any PA is better than no PA at all and this standard is more attainable for people living with other chronic conditions.4 As well, online/mobile interventions, which were consistently effective in this review, could be a cost-effective way of providing health professional support through the transition as well as connect users with others going through the same experience.
Physical activity and exercise interventions after CR may help individuals with heart disease maintain PA; however, measures and outcomes widely varied among the included studies and risk of bias across studies was high. Research on PA maintenance among adults living with heart disease should examine separately the effects for men and women and high-quality RCTs are needed.
The authors thank Michael Boutet at the University of Ottawa for assistance with development of the search strategy.
1. American Heart Association. Heart disease and stroke statistics—2015 update. http://circ.ahajournals.org/content/131/4/e29
. Published 2017. Accessed March 28, 2017.
2. Leon AS, Bronas UG. Pathophysiology of coronary heart disease and biological mechanisms for the cardioprotective effects of regular aerobic exercise
. Am J Life Med. 2009;3(5):379–385.
3. Bassuk SS, Manson JE. Epidemiological evidence for the role of physical activity
in reducing risk of type 2 diabetes and cardiovascular disease. J of App Physiol. 2005;99(3):1193–1204.
4. Warburton DER, Bredin SSD. Reflections on physical activity
and health: what should we recommend? Can J Cardiol. 2016;32:495–504.
5. Balady GJ, Williams MA, Ades PA, et al Core components of cardiac rehabilitation
/secondary prevention programs: 2007 update: a scientific statement from the American Heart Association Exercise
, Cardiac Rehabilitation
, and Prevention Committee, the Council on Clinical Cardiology; the Councils on Cardiovascular Nursing, Epidemiology and Prevention, and Nutrition, Physical Activity
, and Metabolism; and the American Association of Cardiovascular and Pulmonary Rehabilitation. J Cardiopulm Rehabil Prev. 2007;27:121–129.
6. Stone JA, Arthur HM, Suskin NG. Introduction to cardiac rehabilitation
. In: Stone JA, Arthur HM, Suskin NG, eds. Canadian Guidelines for Cardiac Rehabilitation
and Cardiovascular Disease Prevention. 3rd ed. Winnipeg, MB: Canadian Association of Cardiac Rehabilitation
7. Leon AS, Franklin BA, Costa F, et al Cardiac rehabilitation
and secondary prevention of coronary heart disease: an American Heart Association scientific statement from the Council on Clinical Cardiology (Subcommittee on Exercise
, Cardiac Rehabilitation
, and Prevention) and the Council on Nutrition, Physical Activity
, and Metabolism (Subcommittee on Physical Activity
), in collaboration with the American Association of Cardiovascular and Pulmonary Rehabilitation. Circulation. 2005;111(3):369–376.
8. Blanchard CM, Reid RD, Morrin LI, et al Demographic and clinical determinants of moderate to vigorous physical activity
during home-based cardiac rehabilitation
: the home-based determinants of exercise
(HOME) study. J Cardiopulm Rehabil Prev. 2010;30(4):240–245.
9. Reid RD, Morrin LI, Pipe AL, et al Determinants of physical activity
after hospitalization for coronary artery disease: the Tracking Exercise
After Cardiac Hospitalization (TEACH) Study. Eur J Cardiovasc Prev Rehabil. 2006;13(4):529–537.
10. Bock BC, Carmona-Barros RE, Esler JL, et al Program participation and physical activity
maintenance after cardiac rehabilitation
. Behavior Modif. 2003;27(1):37–53.
11. Izawa KP, Yamada S, Oka K, et al Long-term exercise
maintenance, physical activity
, and health-related quality of life after cardiac rehabilitation
. Am J Phys Med Rehab. 2004;83(12):884–892.
12. Moher D, Liberati A, Tetzlaff J, et al Preferred Reporting Items for Systematic Reviews and Meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097.
13. Shea BJ, Grimshaw JM, Wells GA, et al Development of AMSTAR: a measurement tool to assess the methodological quality of systematic reviews. BMC Med Res Methodol. 2007;7:10.
14. Shea BJ, Hamel C, Wells GA, et al AMSTAR is a reliable and valid measurement tool to assess the methodological quality of systematic reviews. J Clin Epidemiol. 2009;62:1013–1020.
15. Higgins JPT, Green S, eds. Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0. West Sussex, England: The Cochrane Collaboration; 2011. http://www.cochrane-handbook.org
. Accessed July 2016.
16. Bushman BA. How can I use METS to quantify the amount of aerobic exercise
. ACSM Health Fit J. 2012;16(2):5–7.
17. Sniehotta FF, Scholz U, Schwarzer R, Fuhrmann B, Kiwus U, Völler H. Long-term effects of two psychological interventions on physical exercise
and self-regulation following coronary rehabilitation. Inter J Behav Med. 2005;12(4):244–255.
18. Aliabad HO, Vafaeinasab M, Morowatisharifabad MA, Afshani SA, Firoozabadi MG, Forouzannia SK. Maintenance of physical activity
capacity after rehabilitation in coronary heart disease: a randomized controlled trial. Glob J Health Sci. 2014;6(6):198–208.
19. Antypas K, Wangberg SC. An internet- and mobile-based tailored intervention to enhance maintenance of physical activity
after cardiac rehabilitation
: short-term results of a randomized controlled trial. J Med Internet Res. 2014;16(3):e77.
20. Arrigo I, Brunner-LaRocca H, Lefkovits M, Pfisterer M, Hoffmann A. Comparative outcome one year after formal cardiac rehabilitation
: the effects of a randomized intervention to improve exercise
adherence. Eur J Cardiovasc Prev Rehabil. 2008;15:306–311.
21. Butler L, Furber S, Phongsavan P, Mark A, Bauman A. Effects of a pedometer-based intervention on physical activity
levels after cardiac rehabilitation
. J Cardiopulm Rehab Prev. 2009;29:105–114.
22. Duncan KA, Pozehl B. Staying on course: the effects of an adherence facilitation intervention on home exercise
participation. Prog Cardiovasc Nurs. 2002;17:59–65.
23. Duncan KA, Pozehl B. Effects of an exercise
adherence intervention on outcomes in patients with heart failure. Rehabil Nurs. 2003;28(4):117–122.
24. Frederix I, Van Driessche N, Hansen D, et al Increasing the medium-term clinical benefits of hospital-based cardiac rehabilitation
by physical activity
telemonitoring in coronary artery disease patients. Eur J Prev Cardiol. 2015;22(2):150–158.
25. Frederix I, Hansen D, Coninx K, et al Medium-term effectiveness of a comprehensive internet-based and patient-specific telerehabilitation program with text messaging support for cardiac patients: randomized controlled trial. J Med Internet Res. 2015;17(7):e185.
26. Giallauria F, Lucci R, D'Agostino M, et al Two-year multicomprehensive secondary prevention program: favorable effects on cardiovascular functional capacity and coronary risk profile after acute myocardial infarction. J Cardiovasc Med (Hagerstown). 2009;10(10):772–780.
27. Giannuzzi P, Temporelli PL, Marchioli R, et al Global secondary prevention strategies to limit event recurrence after myocardial infarction: results of the GOSPEL study, a multicenter, randomized controlled trial from the Italian Cardiac Rehabilitation
Network. Arch Intern Med. 2008;168(20):2194–2204.
28. Guiraud T, Granger R, Gremeaux V, et al Telephone support oriented by accelerometric measurements enhances adherence to physical activity
recommendations in noncompliant patients after a cardiac rehabilitation
program. Arch Phys Med Rehabil. 2012;93(12):2141–2147.
29. Hofman-Bang C, Lisspers J, Nordlander R, et al Two-year results of a controlled study of residential rehabilitation for patients treated with percutaneous transluminal coronary angioplasty. Eur Heart J. 1999;20:1465–1474.
30. Hopper DL. The Effects of Telephone Contact on the Exercise
Adherence of Cardiac Patients. [PhD thesis]. Denver, CO: University of Denver; 1995.
31. Hughes AR, Mutrie N, MacIntyre PD. Effect of an exercise
consultation on maintenance of physical activity
after completion of phase III exercise
-based cardiac rehabilitation
. Eur J Cardiovasc Prev Rehabil. 2007;14(1):114–121.
32. Izawa KP, Watanabe S, Omiya K, et al Effect of the self-monitoring approach on exercise
maintenance during cardiac rehabilitation
: a randomized, controlled trial. Am J Phys Med Rehabil. 2005;84:313–321.
33. Janssen V, De Gucht V, van Exel H, Maes S. A self-regulation lifestyle program for post-cardiac rehabilitation
patients has long-term effects on exercise
adherence. J Behav Med. 2014;37(2):308–321.
34. Kaminsky LA, Jones J, Riggin K, Strath SJ. A pedometer-based physical activity
intervention for patients entering a maintenance cardiac rehabilitation
program: a pilot study. Cardiovasc Diagn Ther. 2013;3(2):73–79.
35. Lear SA, Ignaszewski A, Linden W, et al The Extensive Lifestyle Management Intervention (ELMI) following cardiac rehabilitation
trial. Eur Heart J. 2003;24:1920–1927.
36. Luszczynska A. An implementation intentions intervention, the use of a planning strategy, and physical activity
after myocardial infarction. Soc Sci Med. 2006;62(4):900–908.
37. Madssen E, Arbo I, Granoien I, Walderhaug L, Moholdt T. Peak oxygen uptake after cardiac rehabilitation
: a randomized controlled trial of a 12-month maintenance program versus usual care. PLoS One. 2014;9(9):e107924.
38. Millen JA, Bray SR. Promoting self-efficacy and outcome expectations to enable adherence to resistance training after cardiac rehabilitation
. J Cardiovasc Nurs. 2009;24(4):316–327.
39. Moore SM, Charvat JM, Gordon NH, et al Effects of a CHANGE intervention to increase exercise
maintenance following cardiac events. Ann Behav Med. 2006;31(1):53–62.
40. Pinto BM, Goldstein MG, Papandonatos GD, et al Maintenance of exercise
after phase II cardiac rehabilitation
: a randomized controlled trial. Am J Prev Med. 2011;41(3):274–283.
41. Yates BC, Anderson T, Hertzog M, Ott C, Williams J. Effectiveness of follow-up booster sessions in improving physical status after cardiac rehabilitation
: health, behavioral, and clinical outcomes. Appl Nurs Res. 2005;18(1):59–62.
42. Foster C, Hillsdon M, Thorogood M. Interventions for promoting physical activity
. Cochrane Database Syst Rev. 2005;1:CD003180.
43. Bravata DM, Smith-Spangler C, Sundaram V, et al Using pedometers to increase physical activity
and improve health: a systematic review
. JAMA. 2007;298:2296–2304.
44. Foster C, Richards J, Thorogood M, Hillsdon M. Remote and web 2.0 interventions for promoting physical activity
. Cochrane Database Syst Rev. 2013;9:CD010395.
45. Lustria ML, Noar SM, Cortese J, Van Stee SK, Glueckauf RL, Lee J. A meta-analysis
of web-delivered tailored health behavior change interventions. J Health Commun. 2013;18(9):1039–1069.
46. Southard BH, Southard DR, Nuckolls J. Clinical trial of an Internet-based case management system for secondary prevention of heart disease. J Cardiopulm Rehabil Prev. 2003;23(5):341–348.
47. Chase JAD. Systematic review
of physical activity
intervention studies after cardiac rehabilitation
. J Cardiovasc Nurs. 2011;26(5):351–358.
48. Moore SM, Dolansky MA, Ruland CM, Pashkow FJ, Blackburn GG. Predictors of women's exercise
maintenance after cardiac rehabilitation
. J Cardiopulm Rehabil. 2003;23:40–49.
49. Treat-Jacobson D, Lindquist RA. Functional recovery and exercise
behavior in men and women 5 to 6 years following coronary artery bypass graft (CABG) surgery. Western J Nurs Res. 2004;26(5):479–498.
50. Leung YW, Ceccato N, Stewart DE, Grace SL. A prospective examination of patterns and correlates of exercise
maintenance in coronary artery disease patients. J Behav Med. 2007;30(5):411–421.
51. Shephard R, Tudor-Locke C, eds. The Objective Monitoring of Physical Activity
: Contributions of Accelerometry to Epidemiology, Exercise
Science and Rehabilitation. Berlin, DE: Springer; 2016.
52. Strath SJ, Bassett DRJ, Swartz AM. Comparison of the college alumnus questionnaire physical activity
index with objective monitoring. Ann Epidemiol. 2004;14:409–415.
53. Strath SJ, Kaminsky LA, Ainsworth BE, et al Guide to the assessment of physical activity
: clinical and research applications. A scientific statement from the American Heart Association. Circulation. 2013;128:2259–2279.
54. Prince SA, Adamo KB, Hamel ME, Hardt J, Connor Gorber S, Tremblay M. A comparison of direct versus self-report measures for assessing physical activity
in adults: a systematic review
. Int J Behav Nutr Phys Act. 2008;5:56.
55. Martinello N. Barriers and facilitators to physical activity
after cardiac rehabilitation
: a qualitative synthesis. Unpublished data, 2018.