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Journal of Cardiopulmonary Rehabilitation & Prevention:
doi: 10.1097/HCR.0b013e3181a333a3
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Does Protection Motivation Theory Explain Exercise Intentions and Behavior During Home‐Based Cardiac Rehabilitation?

Blanchard, Chris M. PhD; Reid, Robert D. PhD; Morrin, Louise I. BSc(PT); McDonnell, Lisa MSc; McGannon, Kerry PhD; Rhodes, Ryan E. PhD; Spence, John C. PhD; Edwards, Nancy PhD, RN

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Department of Medicine, Dalhousie University, Halifax, Nova Scotia (Dr Blanchard), University of Ottawa Heart Institute, Ottawa, Ontario (Dr Reid and Ms McDonnell), and Calgary Health Region, Calgary, Alberta (Ms Morrin), Canada; Department of Health and Sport Studies, University of Iowa, Iowa City (Dr McGannon); Department of Physical Education, University of Victoria, Victoria, British Columbia (Dr Rhodes), University of Alberta, Edmonton, Alberta (Dr Spence), and Department of Nursing, University of Ottawa, Ottawa, Ontario (Dr Edwards), Canada.

Corresponding Author: Chris M. Blanchard, PhD, Dalhousie University, Halifax, Nova Scotia, Canada B3H 1V7 (

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OBJECTIVE: Home-based cardiac rehabilitation (CR) programs have been shown to be effective in increasing exercise capacity, which is a significant predictor of longevity for patients with heart disease. However, adherence to these programs has been problematic. Therefore, it is important to identify key theoretical correlates of exercise for these patients that can be used to inform the development of behavioral interventions to help tackle the adherence problem. The purpose of this study was to determine whether protection motivation theory (PMT) explained significant variation in exercise intentions and behavior in patients receiving home-based CR.

METHODS: Patients (N = 76) completed a questionnaire that included PMT constructs at the beginning and midpoint (ie, 3 months) of the program and an exercise scale at 3 and 6 months (ie, at the end of the CR program).

RESULTS: Path analyses showed that response efficacy was the sole predictor of 3-month (β = .53) and 6-month (β = .32) intentions. However, the indirect effect of baseline response efficacy on 3-month exercise behavior through intention was nonsignificant (β = −.01), whereas it was significant (β = .11) for 3-month response efficacy on 6-month exercise behavior. Self-efficacy significantly predicted 3-month (β = .36) and 6-month (β = .32) exercise behaviors, whereas 3-month intention significantly predicted 6-month exercise behavior (β = .23).

CONCLUSIONS: Coping appraisal variables (ie, response efficacy and self-efficacy) are potentially useful in explaining exercise behavior during home-based CR.

Research suggests that home-based cardiac rehabilitation (CR) programs suffer from poor exercise adherence.1,2 Indeed, results from our own program show that up to 60% of patients do not adhere to their exercise prescriptions (ie, exercise for at least 30 minutes, 5 d/wk for a total of 150 minutes), suggesting the need for behavioral intervention. Before developing such an intervention, however, it is important to identify key theoretical correlates of exercise that can be subsequently used to develop a context-specific exercise intervention for these patients.3,4

One theory that has the potential to explain exercise behavior is protection motivation theory (PMT).5 The theory suggests that intention is the most proximal predictor of behavior. Intention, in turn, is influenced by threat and coping appraisal. In the home-based CR context, the threat appraisal depends on patient estimates of the severity of heart disease (ie, perceived severity) and the chance of having another heart-related event (ie, perceived vulnerability). Coping appraisal is influenced by the patients' expectancies that engaging in exercise will be effective in reducing the chance of having another heart-related event (ie, response efficacy) and the belief that they have the necessary skills to engage in exercise (ie, self-efficacy). Preliminary research provides support for the use of PMT in patients at risk for heart disease6 and those with established heart disease not attending any form of CR.7 However, PMT is yet to be examined among home-based CR patients.

The purpose of this study was to determine whether PMT explained significant variation in exercise intentions and behavior from baseline to 3 months (ie, midprogram) and 3 to 6 months (ie, postprogram) among patients receiving home-based CR. It was hypothesized that perceived vulnerability, response efficacy, and self-efficacy would significantly predict intention for both time intervals, which, in turn, would significantly predict exercise behavior for both time intervals.6,7

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The University of Ottawa Heart Institute provided a 6-month comprehensive home-based CR program that included a risk factor assessment (baseline, 3 months, and 6 months), cardiopulmonary stress test (baseline and 6 months), physician assessment, personalized action plan for risk reduction, an individualized exercise prescription, and ongoing scheduled contacts both face to face (n = 2) and by telephone (n = 20).

Patients were eligible to participate if they had established coronary heart disease (CHD) and were post–acute event patients, could ambulate independently, were 18 years or older, could read and write English, and provide informed consent. Patients were excluded if they had a positive graded exercise test (ie, horizontal or downsloping ST-segment depression > 1 mm), uncontrolled atrial or ventricular dysrhythmias, or were unable to participate in exercise because of physical limitations.

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Once ethical approval was obtained from the University of Ottawa Heart Institute, the home-based CR staff was asked to inform patients about the current study at their initial orientation meeting. Interested patients were asked to speak to the research coordinator from whom they received an information letter, informed consent, and a more detailed explanation about the study. If interested, patients signed the informed consent and received a questionnaire that included PMT, demographic, and medical questions. They were asked to complete the questionnaire at home and bring it back to their initial session (on site) with their home-based CR mentor. To obtain the 3- and 6-month follow-up data, the same questionnaire, plus an exercise measure, was mailed to patients 2 weeks prior to their scheduled follow-up assessments at the hospital with their mentor, at which time, the research coordinator obtained the questionnaire and provided the patients with funds to cover parking costs (ie, $13.00).

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Perceived severity was measured via “How serious do you think your heart problem will be over the next 3 months?” rated on a scale from 1 (not at all serious) to 7 (very serious). Perceived vulnerability was measured via “Do you think your heart problem will give you further trouble in the next 3 months?” rated on a scale from 1 (definitely not) to 7 (definitely yes). Self-efficacy was measured via “I am confident that I can exercise over the next 3 months” rated on a scale from 1 (strongly disagree) to 5 (strongly agree). Response efficacy was measured via “Participating in exercise will improve my heart health over the next 3 months” rated on a scale from 1 (strongly disagree) to 5 (strongly agree). All 4 items were adopted from previous CHD studies.7,8 Intention was measured via “During my home-based CR for the next 3 months, I definitely (a) intend and (b) plan to exercise on a weekly basis” rated on a scale from 1 (strongly disagree) to 5 (strongly agree) and the 2 items were averaged (baseline intention, α = .94; 3-month intention, α = .95).8,9 Finally, exercise was measured via the validated Godin Leisure-Time Exercise Questionnaire (Leisure Score Index),10,11 which has been frequently used in the CHD population.9,12 The index assessed the frequency of mild, moderate, and strenuous exercise performed for at least 10 minutes in duration during free time in a typical week during the past 3 months. A total Leisure Score Index score was calculated by adding the frequency of exercise within the mild, moderate, and strenuous categories.

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Recruitment rates and sample characteristics were calculated. Next, means, standard deviations, and zero-order correlations among the PMT constructs were calculated and paired-sample t tests were conducted to determine the potential change in the PMT constructs over time (Bonferroni correction set to P < .01). This was followed by path analyses using maximum likelihood procedures in LISREL 8.8 to test the tenets of PMT. For latent concept specification, the loading for each concept indicator was fixed to 1.0 and the indicator error was fixed to 0%. The first path analysis (Figure 1a) tested the baseline to 3-month time interval, whereas the second analysis tested the 3-to 6-month time interval (Figure 1b).

Figure 1
Figure 1
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Of the potential 103 patients who were eligible, 14 did not approach the research coordinator, 3 were not interested, 3 did not want to complete the questionnaire, 3 were too busy, and 4 were non-English speaking, leaving 76 patients who agreed to participate and completed the baseline, 3-month, and 6-month assessments. Their mean age was 62.64 (SD = 10.98) years, with an average body mass index of 29.24 (SD = 4.85), and they had approximately 13.8 years (SD = 3.12) of education. Most patients were married (80%), white (93%), retired (57%), male (76%), and had an annual household income of less than $60,000 (60%).

Descriptive statistics are given in Table 1. The means were at the lower end of the 7-point scale (ie, < 3.0) for perceived severity and vulnerability at baseline and 3 months, whereas the means were at the upper end of the 5-point scale for self-efficacy, response efficacy, and intention. The paired-sample t tests showed that intentions, self-efficacy, and response efficacy were stable from baseline to 3 months. However, perceived severity (t74 = 2.05, P = .04), perceived vulnerability (t74 = 2.66, P = .01), and exercise (t74 = 2.16, P = .03) significantly decreased during this period. Finally, on the basis of criteria for the magnitude of correlations,13 the majority of the PMT correlations were in the small (ie, ≥0.1) to moderate (ie, ≥.30) range.

Table 1
Table 1
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Path analyses showed that 29% and 25% of the variance in intention was accounted for in 3- and 6-month intentions, respectively. Closer inspection revealed that response efficacy was the sole predictor of 3-month (β = .53) and 6-month (β = .32) intentions. However, the indirect effect of baseline response efficacy on 3-month exercise behavior through intention was nonsignificant (β = −.01), whereas it was significant (β = .11) for 3-month response efficacy on 6-month exercise behavior. Of note, baseline intention did not significantly predict 3-month exercise behavior; however, 3-month intention significantly predicted 6-month exercise behavior (β = .23). However, the examination of the modification indices suggested that the path from self-efficacy to 3- and 6-month exercise behaviors be freed. Therefore, the models were rerun and showed that self-efficacy significantly predicted 3-month (β = .36) and 6-month (β = .32) exercise behaviors. A total of 13% of the variance in 3-month exercise behavior and 19% of the variance in 6-month exercise behavior was accounted for. See Figures 1a and 1b for the final PMT models.

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This study showed that neither perceived vulnerability nor perceived severity of heart disease significantly predicted intention to exercise during home-based CR, which is consistent with previous research in people living with heart disease.7,8 Therefore, threat appraisal variables such as these may not have a motivational influence on exercise levels in home-based CR patients. However, response efficacy did significantly predict intention at the baseline and 3-month measurement periods, which supported our hypothesis. Of further note is that the indirect effect of baseline response efficacy on 3-month exercise behavior through baseline intention was nonsignificant, whereas the indirect effect of 3-month response efficacy on 6-month exercise behavior through 3-month intention was significant. This temporal relationship suggests that in the early phases of a home-based CR program, efforts to increase patient confidence that exercise will reduce further risk of heart-related events may have little effect on the patient's actual exercise behavior. On the other hand, as patients progress through the program and begin to experience the benefits associated with exercise, their response efficacy (eg, 3 months into the program) judgments may become more accurate, resulting in a positive effect on subsequent exercise behavior (ie, the next 3 months).

Interestingly, self-efficacy did not predict intention for either time interval and only 3-month intention significantly predicted 6-month exercise behavior. The lack of a self-efficacy-intention relationship is inconsistent with both previous PMT studies,6,7 which may be sample or context specific. However, self-efficacy did have a direct significant relationship with exercise for both time intervals, which was stronger than the intention-exercise relationship. Therefore, in terms of the first 3 months of home-based CR, it appears that patient confidence in ability to exercise is the dominant predictor of exercise regardless of intentions to exercise. As such, it is crucial that staff ensure that the patients have skills needed to engage in exercise early on (eg, ensure that the patients know what constitutes “exercise,” how to measure intensity). However, as the patients progress through the program, continuing to ensure that they have the skills to exercise in addition to providing them with strategies to change/increase their intentions to exercise will also be important. One way to strengthen these intentions is to focus on changing the patient response efficacy. Another method is to help patients translate intentions into specific plans (ie, where, when, and how to perform exercise) and devise strategies to cope (ie, coping plans) with barriers that may prevent them from translating their plans into action.14

Despite these promising findings, it is important to note that the patients were self-selected. Future studies need to randomly select patients with CHD to reduce potential bias in the sample. Second, the small number of female patients did not allow for gender comparisons to be made, an important consideration in future PMT studies. Third, the use of self-reported exercise may have lead to an over-or underestimation of actual behavior. Future studies should attempt to correct this by using pedometers or accelerometers to obtain objective exercise data. Fourth, this study was done in the home-based CR context only and future studies should examine whether PMT behaves similarly across other contexts (eg, center-based CR). Finally, this study was designed to explain exercise intentions and behavior during home-based CR. Whether PMT can explain exercise intentions and behavior in patients after completing home-based CR program will be important to delineate.

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In spite of these limitations, our study showed that PMT was a promising theoretical framework to explain exercise intentions and behavior during home-based CR. Interestingly, threat appraisal variables (ie, perceived severity and vulnerability) appear to have little effect on motivating patients to engage in exercise during home-based CR, whereas coping appraisal variables may have a stronger effect (ie, response efficacy and self-efficacy).

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This project was supported by a standard research grant from the Social Sciences and Humanities Research Council of Canada; C.M.B. is supported by a Canada Research Chair in Cardiovascular Disease and Physical Activity; R.E.R. is supported by a Michael Smith Scholar Award and a CIHR New Investigator Award; and N.E. holds a Nursing Chair funded by the Canadian Health Services Research Foundation, the Canadian Institutes of Health Research, and the Government of Ontario.

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1. Cardiac Care Network of Ontario. The Ontario Cardiac Rehabilitation Pilot Project: report and recommendation. http// Accessed September 29, 2004.

2. Jolly K, Lip GYH, Sandercock J, et al. Home-based versus hospital-based cardiac rehabilitation after myocardial infarction or revascularisation: design and rationale of the Birmingham Rehabilitation Uptake Maximisation Study (BRUM): a randomized controlled trial. BMC Cardiovasc Disord. 2003;3: 1471–2261.

3. Baranowski T, Anderson C, Carmack C. Mediating variable framework in physical activity interventions: how are we doing? How might we do better? Am J Prev Med. 1998;15: 266–297.

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5. Rogers R. Cognitive and physiological processes in fear appeals and attitude change: a revised theory of protection motivation. In: Cacioppo J, Petty R, eds. Social Psychology, A Sourcebook. New York: Guilford Press; 1983:153–176.

6. Plotnikoff R, Higginbotham N. Protection motivation theory and exercise behavior change for the prevention of coronary heart disease in a high risk, Australian representative community sample of adults. Psychol Health Med. 2002;7:87–98.

7. Plotnikoff R, Higginbotham N. Protection motivation theory and the prediction of exercise and low-fat diet behaviors among Australian cardiac patients. Psychol Health. 1998;13:411–429.

8. Blanchard C, Reid R, Morrin L, et al. Using social cognitive variables to explain the change in physical activity over a 12-month period in cardiac patients not receiving cardiac rehabilitation. J Cardpulm Rehabil. 2006;26:377–383.

9. Blanchard C, Courneya K, Rodgers W, et al. Is the theory of planned behavior a useful framework for understanding exercise behavior during phase II cardiac rehabilitation? J Cardpulm Rehabil. 2003;23:29–39.

10. Godin G, Shepard RJ. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci. 1985;10:141–146.

11. Jacobs DR, Ainsworth BE, Hartman TJ, Leon AS. A simultaneous evaluation of ten commonly used physical activity questionnaires. Med Sci Sports Exerc. 1993;25:81–89.

12. Blanchard CM, Rodgers WM, Courneya KS, Daub B, Black B. Self-efficacy and mood in cardiac rehabilitation: should gender be considered? Behav Med. 2002;27:149–160.

13. Cohen A. A power primer. Psychol Bull. 1992;112:155–159.

14. Sniehotta F, Scholz U, Schwarzer R. Action plans and coping plans for physical exercise: a longitudinal intervention study in cardiac rehabilitation. Br J Health Psychol. 2006; 11:23–37.

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exercise; home-based cardiac rehabilitation; protection motivation theory

© 2009 Lippincott Williams & Wilkins, Inc.


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