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Predictors of Noncompliance to Exercise Training in Heart Failure

Corvera-Tindel, Teresita PhD, RN; Doering, Lynn V. DNSc, RN; Gomez, Teresita MN; Dracup, Kathleen DNSc, RN

The Journal of Cardiovascular Nursing: July-August 2004 - Volume 19 - Issue 4 - p 269–277
Articles: Clinical Research
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Background/Objectives: Exercise training is an emerging therapy in heart failure (HF). However, factors influencing noncompliance to exercise have not been evaluated. We assessed clinical factors, functional status, and emotional predictors of noncompliance to a 12-week home walking exercise program.

Methods: Using a correlational design, we evaluated noncompliance of 39 HF patients (aged 63.2 ± 10.1 years, left ventricular ejection fraction 29.5% ± 8.0%, peak oxygen consumption 14.1 ± 3.7 mL/kg/min, HF duration 37.5 ± 32.9 months, 74% New York Heart Association class II) to home walking exercise. Noncompliance was defined as (1) completion of the 12-week program with 60% or less of prescribed weekly walking duration (noncompliant completers); or (2) failure to complete the 12-week program (dropouts). Univariate analyses (chi-square or t test) and multivariate backward logistic regression were performed to identify clinical factors (body mass index, comorbidities, and HF duration), functional status (peak Vo2), and emotional dysphoria (anxiety, hostility, depression) predictive of noncompliance to training.

Results: Mean compliance was 35% ± 30% (945/2700 minutes) for noncompliant patients (n = 13) and 99% ± 13% (2673/2700 minutes) for compliant patients (n = 26). In the multivariate analysis, higher comorbidity (odds ratio [OR]: 2.7, confidence interval [CI]: 1.11–6.71), longer HF duration (OR: 1.1, CI: 1.01–1.13), lower hostility (OR: 0.47, CI: 0.24–0.91), and lower body mass index (OR: 0.76, CI: 0.58–0.98) were predictive of noncompliance to exercise training in patients with HF.

Conclusions: Noncompliance should be monitored carefully in HF patients with multiple comorbidities, longer HF duration, lower body mass index, and lower hostility scores. In this subgroup of HF patients, tailored exercise prescriptions may enhance compliance to an exercise program.

Postdoctoral Nurse Research Fellow, Nursing Department, Greater Los Angeles, Veterans Affairs Health Care System (VAGLAHS), Los Angeles, Calif. (Corvera-Tindel)

Associate Professor, University of California, Los Angeles, School of Nursing, Los Angeles, Calif. (Doering)

Research Associate, VAGLAHS, Los Angeles, Calif. (Gomez)

Professor/Dean, University of California, San Francisco, School of Nursing, San Francisco, Calif. (Dracup)

The authors have no conflict of interest.

This study was supported by Veterans Administration Health Services Research and Development nursing research initiative 96.031.1.

Corresponding author Teresita Corvera-Tindel, PhD, RN, Nursing Department, VAGLAHS, Bldg 500, Room 6207, Mail code 118 R, 11301 Wilshire Blvd, Los Angeles, CA 90073 (e-mail: Teresita.Corvera@med.va.gov).

In the last 2 decades, exercise training has emerged as a beneficial therapeutic strategy to improve functional status and quality of life in patients with chronic heart failure (HF). 1–15 Compliance is crucial to deriving benefits from any exercise program, but up to a third of patients who participate in exercise training studies are noncompliant to the exercise protocol. 1,2

In patients with myocardial infarction (MI), the factors associated with compliance or noncompliance to cardiac rehabilitation programs have been well evaluated. Despite high acceptance of cardiac rehabilitation among MI patients, poor attendance is commonly reported. 16,17 The biggest drop in compliance to a cardiac rehabilitation program occurs after the first 8 weeks of program enrollment. 18 Factors positively associated with compliance to cardiac rehabilitation among MI patients include maximum oxygen consumption (Vo2max), peak heart rate, high-density lipoprotein cholesterol, and age. 18 Factors inversely correlated with compliance are body mass index (BMI), recent body fat (sum of 3 skinfold measurements), total cholesterol, triglycerides, and depression. 18 Among post-MI patients, demographic and/or clinical predictors of noncompliance to cardiac rehabilitation programs include lower education level, 19 unemployment, 19 accompanying illness or medical conditions, 20 transportation difficulties, 20 and low levels of physical activity. 21 Psychological variables predictive of noncompliance to a cardiac rehabilitation program include depression, anxiety, and hypochondriasis. 22–25 Furthermore, depression is not only a significant predictor of cardiac rehabilitation noncompliance, but also of poorer outcome (ie, maximum oxygen consumption) in patients with MI. 24 However, in HF patients, characteristics related to noncompliance to an exercise program are yet to be identified. Thus, the primary aim of this study was to identify significant predictors of noncompliance to a home walking exercise program implemented in patients with advanced HF. Because program completion and patient's clinical and emotional characteristics are important in evaluating response to exercise, and because functional status is a key outcome of exercise studies in heart failure, our secondary aims were to (1) evaluate the clinical and emotional characteristics among 3 groups of patients: compliant patients who completed the exercise program, noncompliant patients who completed the program, and dropouts; and (2) compare changes in functional status among these 3 groups.

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Methods

Study Design and Population

A nonexperimental prospective study was conducted by using data collected from subjects participating in a 12-week home walking exercise randomized clinical trial. Patients were recruited primarily from the VA Greater Los Angeles Health Care System (95%) and from a university affiliated medical center (5%) from 1998 to 2001. At the time of recruitment, the VA site had no established HF clinic; thus, patients were recruited from primary care and cardiology clinics. Both hospitals' institutional review boards approved the protocol. Patients included in the study were stable ambulatory HF patients, male (99%), aged between 33 and 81, left ventricular ejection fraction of 40% or less, New York Heart Association (NYHA) class II to IV, and without any orthopedic, pulmonary, and/or neurological limitations to exercise. A total of 99 patients met inclusion criteria. Of these, 10 withdrew consent, 4 died, 3 were lost to follow-up, and 3 had significant comorbidity requiring long-term hospitalization prior to study enrollment. Seventy-nine patients were randomized to a training group (n = 42) or a control group (n = 37). The present article focuses only on the patients randomized to the training group. Three patients, 2 who died after randomization and 1 who did not complete baseline questionnaires, were excluded from the current analysis. The final sample included 39 patients.

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Exercise Program

The walking exercise program was conducted at home. Patients were asked to walk once a day, 5 days a week for a period of 12 weeks. The exercise program was a progressive, low-intensity (40% to 65% of maximal heart rate) walking program wherein exercise duration and intensity was initiated at 10 minutes and 40% of maximal heart rate and progressively increased up to 60 minutes and 65% of maximal heart rate in the last 6 weeks of the program (Table 1). Patients wore a pedometer while walking and recorded the walking pedometer data in a diary. The pedometer recorded the time walked in minutes and the distance walked in miles and steps. A nurse visited patients weekly for the first 6 weeks and biweekly in the last 6 weeks. The purpose of the regular nurse home visits was 2-fold (1) to provide weekly walking prescription (which included duration, frequency, and intensity) and (2) to evaluate tolerance of the week's exercise prescription by walking with the patient and validating self-reported compliance to the protocol. Throughout the 12-week program, any untoward clinical events that influenced patient's compliance to the walking protocol were monitored and documented (ie, hospitalizations for HF, medication changes, flu/colds, etc).

Table 1

Table 1

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Data Collection

Exercise Compliance

The overall mean compliance rate for the 12-week program was calculated as the total actual time spent walking, as measured in minutes by the pedometer, for the 12 weeks, divided by the total prescribed walking time in minutes for 12 weeks (Table 1), multiplied by 100. On the basis of the above calculation, 100% compliance was equal to a total of 2700 minutes of walking time for the whole 12 weeks.

Compliance to the exercise program was defined as an overall mean compliance rate of more than 60% of prescribed weekly walking duration, as measured by the pedometer data. All patients who were classified as compliant completed the 12-week program. Noncompliance was defined as (1) completion of the 12-week program with 60% or less of prescribed weekly walking duration (noncompliant completers); or (2) failure to complete the 12-week program (dropouts).

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Clinical Evaluation

On initial examination, medical history (age, height and weight, left ventricular ejection fraction, smoking pack year history, type of cardiomyopathy, time of HF diagnosis, and comorbid conditions) was updated, and physical assessment was performed. From these data, the following were derived: BMI, HF duration, and Charlson comorbidity index score. Body mass index was defined as weight (in kilograms) divided by height (in square meters). 26Heart failure duration was calculated as the number of months from the time HF was initially diagnosed to the time of enrollment in the program. The Charlson comorbidity index score was calculated by assigning weights of 1, 2, 3, and 6 to predefined medical conditions (ie, 1 = MI, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, connective tissue disease, mild liver disease, diabetes; 2 = hemiphlegia, moderate or severe renal disease, diabetes with end-organ damage, any tumor, leukemia, lymphoma; 3 = moderate or severe liver disease; 6 = metastatic solid tumor, acquired immunodeficiency syndrome). 27 Weighted scores were summed to obtain a total comorbidity score.

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Functional Status

For this study, functional status was defined as the patient's achieved maximal exercise capacity and ability to perform activities of daily living (ADLs). Maximal exercise capacity was measured by peak oxygen consumption (Vo2) via cardiopulmonary exercise test (CPX), whereas ADL performance was measured by 2 tests: NYHA functional class and the 6-minute walk test (6-MWT). Measures of functional status (both peak Vo2 and ADLs performance tests) were obtained prior to initiation of the 12-week home walking exercise. Both peak Vo2 and 6-MWT were also measured at the end of the exercise program.

Peak Vo2 was determined as the highest 10-second average value of Vo2 observed over the last 30 seconds of CPX test. 9 The CPX with breath-by-breath gas exchange analysis (via a metabolic cart [Sensormedics Vmax 29]) was performed in an upright electronically braked cycle ergometer (Sensormedics 800S) with 3 minutes of rest, 3 minutes of unloaded pedaling, then, a work rate increase of 10 watts/minute in a ramp pattern up to symptom-limited maximum. Patients pedaled at a constant rate of 60 rpm. Gas analyzers were calibrated immediately before and after each patient's test.

New York Heart Association functional class was the clinician's determination of the patient's level of daily symptom-limited physical activity. 28 In the 6-MWT, patients were asked to walk in a corridor from end to end at their own pace, while attempting to cover as much ground as possible in the allotted period of 6 minutes. 29 In 10% of the sample, test-retest reliability yielded a correlation of 0.92 (P = .01).

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Emotional Dysphoria

The Multiple Affect Adjective Checklist (MAACL), which was obtained at baseline, measured negative emotions such as anxiety, hostility, and depression. 30 It is a self-administered questionnaire with 132 adjectives that measures current negative mood. 31 Subjects were asked to check all adjectives that reflect how they felt at the time. Of the 132 adjectives in the MAACL, 89 items measure anxiety (21), hostility (28), or depression (40). The remaining 43 items (adjectives) are not counted in scoring. Of the 89 items, 45 adjectives are negative and 44 are positive. The scoring is bipolar, so that checking a negative adjective contributes a point toward the score and not checking a positive adjective contributes a point. Higher scores indicate greater dysphoria. Multiple reports have demonstrated the sensitivity, reliability, and validity of the instrument. 32 In 5% of the sample, test-retest reliability yielded a correlation of 0.90 (P = .05), 1.0 (P < .001), and 0.95 (P = .02) for mood scores of depression, anxiety, and hostility, respectively.

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Statistical Analysis

All analyses were performed using SPSS 10.0. All data were expressed as mean ± SD or percentage. Initial descriptive statistics were used to explain overall compliance rates and weekly compliance rates.

Noncompliance was evaluated as a dichotomous variable. On the basis of previous research in patients with heart disease who were enrolled in cardiac rehabilitation programs, we hypothesized that BMI, comorbid conditions, functional status, emotional dysphoria, and HF duration influence noncompliance to exercise training. Initially, bivariate analyses using chi-square (for categorical variables) and t test (for continuous variables) were performed to identify differences between the two groups of compliant and noncompliant patients. Variables significant at the P < .20 level in univariate analyses and those variables considered to be clinically important were included in the multivariate backward logistic regression. To reduce the threat of multicollinearity, when multiple measures of a single variable were tested univariately, only the most highly significant measure was included in the multivariate model. The final model included BMI, comorbidity score, peak Vo2, HF duration, and emotional dysphoria. Baseline clinical factors and functional status (peak Vo2) variable were entered into the model first as a block, then, baseline emotional dysphoria (anxiety, depression, and hostility) as a second block. Significance was set at P ≤ .05.

For the secondary aims, a 1-way analysis of variance was performed to evaluate baseline clinical and emotional characteristics and change in functional status following the 12-week home walking exercise program among the 3 groups (compliant patients, noncompliant completers, and dropouts). A Bonferroni adjustment was performed for multiple comparisons. Significance was set at P ≤ .05.

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Results

The mean compliance of all patients randomized to 12 weeks of exercise training was 78% ± 36%. Of the 39 patients in the training group, 67% (n = 26) were compliant, 12% (n = 5) were noncompliant, despite completing the program (noncompliant completers), and 21% (n = 8) failed to complete the program (dropouts). Together, noncompliant completers and dropouts, constituting 33% of the sample, composed the noncompliant group. Mean compliance rates of the compliant and noncompliant groups were 99% ± 13% (2673/2700 minutes) and 35% ± 30% (945/2700 minutes), respectively (P < .001). The mean compliance rates of noncompliant completers compared to dropouts were 39% ± 13% (1053/2700) vs 33% ± 34% (918/2700), respectively (P < .001). Weekly compliance rates for each group are shown in Figure 1. In the compliant group, the rate of exercise compliance was more than 100% for the first 6 weeks and was maintained at more than 90% in the last 6 weeks. In contrast, the noncompliant group maintained the rate of exercise compliance more than 60% only through the fourth week of the program; then, their compliance rate progressively declined from 51% to 17%. Among noncompliant patients, completers started with a lower weekly compliance rate of 80% compared to dropouts, whose weekly compliance rate began at 118%. The rate of decline in mean compliance diverged between noncompliant completers and dropouts, with fifth week rates of 47% and 53%, and 12th week rates of 32% and 7%, respectively.

Figure 1

Figure 1

Initial univariate analyses (compliant vs noncompliant) are shown in Table 2. Predictors of noncompliance identified in the multivariate backward logistic regression are shown in Table 3. Significant predictors of noncompliance were higher Charlson comorbidity index score, longer HF duration, lower hostility scores, and lower BMI with odds ratio of 2.7, 1.1, 0.47, and 0.76, respectively.

Table 2

Table 2

Table 3

Table 3

The clinical and emotional characteristics of compliant patients, noncompliant completers, and dropouts are shown in Table 4. Noncompliant completers had a significantly longer HF duration (6.7 ± 4.4 years) compared to the compliant patients (2.5 ± 2.0 years, P = .003) and dropouts (3.0 ± 2.3 years, P = .03). Dropouts had a significantly higher Charlson comorbidity index score (3.9 ± 1.6) compared to the compliant patients (1.9 ± 1.4, P = .003) and noncompliant completers (1.8 ± 0.8, P = .03). Furthermore, compared to compliant and noncompliant completers, dropouts had a significantly higher incidence of diabetes (P = .002).

Table 4

Table 4

After the 12-week home walking exercise, there were no significant differences in functional status changes among the 3 groups. Specifically, the peak Vo2 changes were 1.0 ± 2.3 mL/kg/min vs 0.89 ± 2.1 mL/kg/min vs 2.8 ± 2.6 mL/kg/min (P = NS) for compliant, dropouts, and noncompliant completers, respectively. Similarly, there were no significant differences in 6-MWT changes among the 3 groups (139.0 ± 209.8 ft vs 14.1 ± 29.1 ft vs 160.7 ± 70.8 ft for compliant, dropouts, and noncompliant completers, respectively). However, when the benchmark of more than 99 ft was used as an indicator of clinically significant change in 6-MWT distances for HF patients, 33 both compliant patients and noncompliant completers demonstrated meaningful improvement in 6-MWT distances after the 12-week exercise program (139.0 ft and 160.7 ft, respectively). Clinical events, ie, hospitalizations for HF, medication changes, flu/colds, etc, did not differ between compliant and noncompliant groups.

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Discussion

This study provides a preliminary perspective of HF patients who are unlikely to comply with an exercise prescription. Our study is the first to examine factors that influence HF patients' compliance to a prescribed short-term home walking program and to evaluate the weekly compliance rate of the participants in an exercise program designed specifically for chronic HF patients outside the structure of a cardiac rehabilitation program.

The overall compliance rate of 78% observed in this study compares favorably to reports of compliance rates (range: 62%–110%) by investigators who implemented either a hospital-based or home-based exercise programs in patients with HF. 1,2,13,34 Compared to hospital-based exercise programs in HF, which included supervision by health professionals, the compliance rate in our study was lower than the 100% rate to bicycle ergometry or treadmill reported by Meyer et al, 34 and higher than the 62% rate to bicycle ergometry reported by Hambrecht et al. 2 The study's 78% compliance rate is lower compared to the 110% compliance rate reported by Oka et al, who implemented an unsupervised home walking exercise, 40 to 60 minutes per day and 3 times per week. 13 On the other hand, the compliance rate reported in this study was similar to that of 2 home-based bicycle ergometry programs, neither of which included supervision, and both of which reported compliance rates of 77% and 70%. 1,2 The exercise prescription implemented by these 2 home-based bicycle exercise ergometry programs was 20 minutes per day and 5 to 7 times per week. These equivocal comparisons suggest several factors that warrant further investigation regarding their influence on compliance to exercise among HF patients. These factors include mode of exercise, accessibility of the program, frequency and duration of exercise prescription, and exercise supervision by health professionals. Among the studies available to date, it is unclear whether mode of exercise (walking vs bicycle), accessibility (home vs hospital-based), or supervision confers a positive benefit in terms of patient compliance. Regarding frequency and duration of exercise prescription with walking protocols, it appears that a less intense prescription may improve compliance in HF patients.

In the current study, patients with increased comorbid conditions were less likely to comply with the exercise prescription. There was almost a 3-fold increased risk of noncompliance with a Charlson comorbidity score of 3 or more. Our finding is parallel to the findings of Lieberman et al who reported that increased medical comorbidities resulted in decreased enrollment and compliance to a cardiac rehabilitation program. 20 The predominant comorbid conditions included a history of rheumatoid arthritis, diabetes, and/or ischemic heart disease. These comorbid conditions may have limited mobility and/or aggravated pain, consequently, influencing patient's ability or motivation to comply with the exercise prescription. Interestingly, the proportion of diabetic patients was greatest in the dropout group compared to both compliant patients and noncompliant completers. It has been shown that diabetic patients have walking patterns that cause increased plantar pressures, which may exacerbate gait problems and limit walking abilities. 35 It is possible that walking exercise is less well suited for diabetic patients than is nonweight bearing forms of exercise. Further study is indicated to evaluate the role of diabetes in compliance to different forms of exercise in diabetic HF patients.

Patients with a longer HF duration were less likely to comply with an exercise prescription than were patients with a shorter HF duration. In fact, for a year's increase in HF duration, there was a 2-fold increase in risk of noncompliance. Noncompliant completers had longer HF durations compared to both dropouts (who had greater comorbidities as described above) and compliant patients (Table 4). This finding may be explained by the hypothesis that patients experiencing HF symptoms for a longer period of time may have become discouraged about their ability to influence the disease trajectory by exercising. As HF duration increases, patients experience repeated exacerbations and hospitalizations, and have recurring symptoms of dyspnea and/or fatigue. Such patients may have had time to contemplate their prognosis and may not believe an exercise program holds promise for them. In fact, noncompliant completers started the program with a first-week compliance rate of 80%, compared to compliant patients (155%) and dropouts (117%). Furthermore, their compliance rate declined steadily throughout the program. Our interpretation that HF duration contributes to noncompliance is supported by several factors. First, recent 5-year survival in men with HF remains soberingly low at 41%. 36 Second, in a related population of post-MI patients, researchers have demonstrated that patients with greater perception of disease severity are more likely to be noncompliant in attending a cardiac rehabilitation program than are patients who appraise their disease severity as low. 21,37 Third, Champion's Health Belief Model, which has been tested in the evaluation of compliance behaviors toward medication, diet, smoking cessation, and stress avoidance among HF veterans, suggests that when a health activity is appraised as being of little benefit, it is less likely to be performed. 38 Interventions based on positively altering patients' perception of benefit and designed to improve compliance to exercise and other recommendations warrant further investigation.

A competing interpretation of the findings about length of duration from diagnosis is that increasing disability is associated with disease progression, which is related to noncompliance. However, patients who were compliant and noncompliant were not significantly different by symptom level (as measured by NYHA classification) or 6-MWT distances, and were only marginally different by peak Vo2 at baseline. None of these variables were retained in the multivariate analyses, which suggests that the patients' perception of salience was more important than physical disability in predicting noncompliance.

There were no significant differences in improvement in ADLs performance (via 6-MWT) among the compliant patients, noncompliant completers, and dropouts. Interestingly, there was a trend toward higher baseline functional status (via both 6-MWT and peak Vo2) among compliant patients. Similarly, MI patients with lower baseline work capacity (ie, <6 metabolic equivalents) achieved greater improvement in outcome from participation in an exercise program than did patients with higher baseline functional status. 39 Together, these findings suggest that patients who are deconditioned experience greater gain from an exercise program than do conditioned patients with less disease severity. Therefore, HF patients with lower functional status may have the most to gain from an exercise program. This inference is supported by the fact that both noncompliant completers and compliant patients experienced clinically significant improvements in 6-MWT distances after the 12-week program. In addition, the benefit achieved by noncompliant completers, who stuck with the exercise program but walked less than recommended, infers that a less demanding exercise prescription may benefit some HF patients. In 12 weeks, the noncompliant completers achieved the equivalent of 30 minutes per day, 3 times a week. This level of frequency and duration may represent a reasonable and achievable prescription likely to yield improvement in physical functioning in HF patients with longer HF duration.

Among the emotional dysphorias, only hostility was predictive of noncompliance, ie, for every unit reduction in hostility score, there was almost a 47% chance of being noncompliant. This is likely attributed to increasing disability in the noncompliant group. Noncompliant patients included dropouts with increased comorbidities and noncompliant completers with prolonged HF duration. These patients may have adjusted their expectations downward, as a form of response shift. 40,41 As a result, they may experience less hostility even as they are less engaged in prescribed treatments such as exercise. Hostility is rarely evaluated in patients with heart disease. One study showed that hostility scores were not influenced by participation in a cardiac rehabilitation program 42; however, the effect of hostility on compliance to a cardiac regimen or exercise program has not been examined. Surprisingly, depression and anxiety were not significantly predictive of noncompliance to training, a finding that differs from studies conducted in cardiac rehabilitation programs with patients post MI. 22–25 The latter findings may be explained by the homogeneity and/or size of the sample, which limited our ability to detect within-group differences.

Finally, a 1-unit reduction in BMI corresponded to a 76% chance of being noncompliant. Our finding is contrary to reports of noncompliance in MI cardiac rehabilitation programs, in which obesity was directly correlated with noncompliance. 18 Although both compliant and noncompliant patients had mean BMIs of more than 25 kg/m2, the direct relationship of a lower BMI with noncompliance may be associated with recent reports regarding the inverse relationship of BMI and survival in HF. 43–46 Perhaps, patients with lower BMI are experiencing the progression of HF. Future research is required to explore the relationship of BMI, noncompliance to exercise training, neurohormonal activation, and progression of HF.

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Limitations

An obvious limitation of the study is the small sample size and homogeneous, all-male sample. Our findings need to be validated in larger samples and ones that include women and patients with diverse socioeconomic backgrounds to enhance generalizability. Future exercise-training clinical trials with long-term exercise programs are needed to evaluate the factors influencing compliance to training in patients with HF.

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Clinical Implications

Despite a small sample size, this study provides valuable information regarding factors that affect noncompliance to exercise prescriptions in patients with chronic HF. Several clinical implications can be drawn from these findings. First, in developing exercise programs for patients with chronic HF, clinicians should be aware of factors that may influence compliance, such as exercise modality, program accessibility, and availability of supervision. Since research findings regarding these factors are equivocal, clinicians should evaluate the specific characteristics and needs of their patients to enhance compliance. Second, patients should be assessed to identify comorbid conditions, such as diabetes, that affect mobility and choice of exercise modality. Third, clinicians should consider tailoring exercise prescriptions, so that there is a balance between the benefits of exercise and the motivation to participate, especially in patients with longer HF durations. A modest exercise frequency and duration may be sufficient to yield improvements in functional status. Finally, clinicians should be alert to noncompliance to exercise in patients with a longer HF duration, lower BMI, and lower levels of hostility. Strategies targeted toward these latter factors may supplement the success of an exercise program for patients with chronic HF. Therefore, future research should evaluate tailored exercise prescriptions, ie, those that target exercise modality, program accessibility, and supervision of exercise to specific patient characteristics, including disease duration, BMI, and emotional well-being.

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Keywords:

heart failure; home walking exercise; noncompliance

© 2004 Lippincott Williams & Wilkins, Inc.