This research synthesis documented that treatment subjects performed more PA behavior, had better fitness results, experienced greater quality of life, and reduced cardiac events following interventions than did control subjects. In 2-group comparisons, anthropometric measures and systolic and diastolic pressure were not better among treatment subjects than control subjects. Q values documented substantial heterogeneity among primary studies. The considerable variation of intervention effects should stimulate further research to determine which characteristics of designs, interventions, and samples distinguish effective interventions from those that are less effective or even detrimental.
We included single-group pre-post comparisons to complement the information provided by 2-group comparisons. Although the two types of ESs yielded similar patterns of mean ESs across dependent variables, single-group treatment ES estimates tended to be slightly larger than their 2-group counterparts; ESs for anthropometric measures are a notable exception. Although control groups experienced little improvement over the course of research participation (only fitness improved significantly), findings from single-group pre-post comparisons should be interpreted with caution. We will limit further discussion of findings to 2-group main effects and moderators.
This is the first meta-analysis to examine PA outcomes among cardiac populations. The findings are important because they document that PA behavior change is possible. The ES of .35 is equivalent to a 368.9 kcal/wk better post-intervention PA mean among treatment subjects. For instance, if control subjects spent an averaged of 1,615 kcal/wk in energy, treatment subjects spent 1,984 kcal/wk. It is unclear whether this difference in PA outcomes is clinically meaningful because we do not yet know the doses required to achieve specific health benefits. This amount of PA increase does not meet current recommendations for healthy adults. The dose necessary to achieve health benefits among those with cardiovascular diseases is not well established. Evidence regarding incremental health changes as subjects move from entirely sedentary to modest activity to moderate PA is not available. For example, we do not know if people who are entirely sedentary and adopt a small amount of PA experience similar health gains as people who perform modest activity and move to moderate activity. The modest ES suggests we need interventions that increase PA more and among more subjects. Most studies reported PA outcomes immediately after interventions. Since it is long-term PA that bestows health benefits, this field needs more studies with extended follow-up to determine how well subjects persist in PA after interventions end [22
Thompson et al. noted the urgent need to discover behavioral strategies and techniques that increase PA [22
]. Our exploratory moderator analyses offer intriguing suggestive information about possible moderators of PA results. Interventions that included supervised exercise were more successful in attaining long-term behavior change. Although the availability of supervised exercise may be limited due to access or cost issues, it appears to be more successful than other interventions components in changing PA [5
]. Supervised exercise may provide participants with clear information about the form, intensity, and duration of exercise. Participants’ consistent practice in both scheduling supervised PA and working through the supervised exercise sessions may teach them behavior patterns that foster continued PA. Exercise professionals who conduct supervised exercise may motivate in ways that are lacking in unsupervised PA at home. Studies using supervised exercise often included fitness testing, which was also associated with larger PA outcomes (albeit weakly). Fitness testing may give participants objective evidence about their physical health that they find motivating. It is also possible that fitness testing reassures some subjects that it is safe for them to perform PA.
The target behavior was important in the moderator analysis of PA. Interventions that focused solely on PA resulted in larger PA changes. This is consistent with findings from a meta-analysis of interventions to increase PA among older adults with diverse chronic illnesses [127
]. Changing a single behavior can be a difficult endeavor, and cardiac populations may feel overwhelmed when asked to change PA, diet, medication, and possibly smoking behavior simultaneously. Although it may be ideal to change multiple cardiac risk behaviors at once, it may work better to apply interventions in sequence with the goal of changing one behavior at a time. The most successful interventions appear to be delivered face-to-face and with ample contact time to either groups or individuals. Recent efforts to design alternative delivery modes (e.g. interventions delivered by e-mail) should be carefully evaluated for their long-term effects.
Our moderator analysis documents the intriguing finding that interventions that recommended more minutes per week of exercise were more effective in promoting PA than those recommending less exercise. Similarly, Conn et al. reported that older adults told to perform moderate intensity exercise were more likely to increase PA than those told to perform low intensity PA [127
]. It is possible that subjects more easily recognize rigorous recommendations -- more minutes per week or higher intensity exercise -- as a clear departure from their sedentary habits. The findings do not support the use of goal setting, self-monitoring, or recommending walking PA. The lack of support for goal setting and self-monitoring was somewhat surprising given the popularity of these strategies. Most intervention studies bundle behavior change interventions and rarely examine specific strategies, such as goal setting and self-monitoring. This meta-analysis is the first attempt to examine the effects of individual components. Unfortunately, we coded many PA behavior change intervention strategies but could not analyze them as moderators due to infrequent reporting. For some outcomes, the 2-group mean ES and variance component together suggest that certain studies in this body of research could plausibly yield true ESs as large as .50 (anthropometric measures), .60 (quality of life), or even .70 (PA). With better information on study-level features to model the ES heterogeneity, meta-analysts would be better able to identify types of studies that yield these impressive intervention effects. In other words, the heterogeneity of ESs suggests that better interventions may be present in the published literature, but without knowing more about moderator information it’s difficult to know why the studies with higher ESs are getting such great results.
We found that gender and age distribution in samples were not related to PA, which suggests that interventions are equally effective for women and men of diverse ages [33
]. The lack of studies targeting minority subjects prevented moderator analyses related to ethnicity. There is an urgent need for more intervention studies with these vulnerable populations. Functional status could be an important moderator of both PA behavior and health outcomes among studies designed to increase PA. We were unable to include New York Heart Association functional class as a variable because it was reported infrequently in primary studies. Future meta-analyses may be able to address important sample attributes, such as ethnicity and functional status, as potential moderators of ES as more studies report these attributes for the entire sample, focus on subjects with particular attributes, or report findings separately for sample subsets.
Regarding quality of life, the 2-group treatment versus comparison group ES was .24. Other research has noted modest improvements in quality of life among cardiac populations following PA or rehabilitation/education interventions [1
]. These improvements may result from improved fitness and physical function or from the association between PA and reduced mild depression.
Fitness ESs were significantly better among treatment subjects as compared to control subjects, though the magnitude was small. Cardiorespiratory fitness may vary considerably among subjects undertaking identical exercise programs because of individual and genetic influences. The ideal PA to achieve fitness improvements is not yet known. Due to scant data, we could not synthesize the exercise characteristics, such as form and dose, that are essential to achieve favorable results. This is especially unfortunate because exercise variations may determine outcomes. A recent review was also unable to synthesize exercise dose effects across studies due to inadequate reporting in the literature [4
]. Future work should examine the best exercise modes and doses for achieving optimal health outcomes. Although some primary studies reported co-morbid conditions, another potential influence on fitness outcomes, the reporting was not adequate to include them in the moderator analyses.
Subsequent cardiac events are important outcomes of any interventions with cardiac populations. Researchers have synthesized the effects of psycho-educational programs for cardiac populations and reported reduced cardiac events [32
]. Dusseldorp et al. examined the influence of proximal changes on distal outcomes such as mortality and documented that infarction recurrence was 36% less in studies that changed proximal variables as compared to only 2% for studies that did not change proximal outcomes [32
]. Although the magnitude of the statistically significant ES was modest in this meta-analysis and few studies reported these data, differences of even a few cardiac events are clinically very meaningful.
Previous meta-analyses have examined blood pressure outcomes and reported small decreases ranging from < 1 to 6 mmHg for systolic pressure and from 1 to 4 mmHg for diastolic pressure [5
]. In this synthesis, reductions in systolic and diastolic blood pressure were small and not significantly different from 0. Our search may have yielded more diverse studies than some previous meta-analyses that used limited search strategies and inclusion criteria [1
]. Research has established neither the body’s mechanisms for changing blood pressure in response to PA nor the optimal characteristics of training programs for this purpose [19
This synthesis used extensive and intensive search strategies to locate diverse studies. Even so, this does not ensure that their findings represent the effectiveness of interventions to increase PA among the general population of adults with cardiac diseases. Clark et al. suggested that the magnitude of effects may be somewhat smaller in research studies than what many people would achieve because both the treatment and control groups receive optimal medical care [1
]. The effects of interventions to increase PA and deal with secondary preventive behaviors may be more beneficial among patients who are treated where care is less optimal [1
]. It is possible that researchers purposefully recruited participants for these studies who were more sedentary than typical cardiac populations. But the opposite is also possible -- that researchers recruited healthier subjects with less risk due to human subjects concerns or patients’ willingness to participate in interventions [1
]. The differences between these subjects and the general population of adults with cardiac disease are unknown. The benefits of increasing PA are generally less than what pharmacological therapies can achieve for certain outcomes [22
]. Other important outcomes, such as fitness, may only change with PA. The changes documented in these studies may be over and above the benefits patients accrue from medical management.
This meta-analysis was limited by the studies retrieved. We analyzed only studies that included PA results. Given the small number of studies, readers should cautiously interpret findings about fitness, quality of life, blood pressure, anthropometric measures, and subsequent cardiac events. Many important study features, such as treatment fidelity or subject attributes like smoking, were unreported and thus could not be analyzed [1
]. We expected the mixed pattern of publication bias because meta-analyses of various populations often report such bias. Publication bias may result when investigators choose not to report studies unless they have statistically significant findings or when journals choose not to publish papers of this kind [35
]. Investigators may believe that pilot projects do not need to be disseminated when interventions are unsuccessful. Studies that lack statistically significant findings may be more likely to be presented in published papers without adequate data for calculating ES, thus excluding them from meta-analyses. Only when both effective and ineffective interventions become widely known can researchers build efficiently on the work that came before them.
Overall, this meta-analysis documents improved PA outcomes following interventions. PA is especially important among cardiac populations because it may not only reduce problems associated with type 2 diabetes and obesity but also influence lipids, cardiovascular functional capacity, and the atherosclerotic process [22
]. This field would benefit from further research to clarify which components of interventions are associated with better PA outcomes and to determine whether interventions are differentially effective for samples with particular characteristics.