Epidemiological Research Article Analysis: Cardiovascular Health

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In “Long-Term Retention of Older Adults in the Cardiovascular Health Study: Implications for Studies of the Oldest Old,” researchers Strotmeyer et al. (2010) highlight the need for research that addresses the health outcomes for older adults. As the researchers identify, lack of follow-up care is a primary concern for older populations who commonly experience inhibiting health problems that prevent them from receiving medical care. This report will evaluate the methodological elements of this longitudinal study to determine the merits of the researchers’ findings for various cardiovascular disorders and the implications of this study to evidence-based practice. Further, the criteria on evidence-based nursing research and practices defined by Polit and Beck (2014) will be utilized to evaluate the strengths and weaknesses of the hypothesis, research question, and research design, and statistical data that is utilized in this research.

Analysis of Hypothesis and Research Question

In “Long-Term Retention of Older Adults in the Cardiovascular Health Study: Implications for Studies of the Oldest Old,” researchers Strotmeyer et al. (2010) express the objective of determining the relationship between the types of visits that geriatric patients receive from healthcare practitioners and their propensity to return for follow-up care. The researchers make use of data from the Cardiovascular Health Study (CHS) cohort, which assesses the propensity of patients from different age and demographic groups to attend additional in-person visits after initially receiving care. In order to analyze this relationship, the researchers devote the second paragraph of the study to the following research question: whether older age is associated with returning to a clinic visit according to the data in the CHS study (Strotmeyer, 2010, p. 697). Through this statement, researchers prominently establish the research question that will be evaluated early on in the study.

However, in addition to evaluating the clarity of the research question, it is also necessary to evaluate the strength of the research question. Polit and Beck (2014) provide criteria for evaluating the efficacy of the research question presented by Strotmeyer et al. According to the authors, a sound research question enables the researchers to develop an explanatory framework for evaluating the underlying cause of a phenomenon (Polit & Beck, 2014, p. 11). The phenomenon that is stated in the research question in this study is the prevalence of follow-up medical care obtained by patients.

Further, in order to develop a clear explanatory framework of the factors that contribute to or inhibit the stated phenomenon, the research question must also establish whether the research utilizes quantitative or qualitative methods of investigation. As the research question presented by Strotmeyer et al. establishes, the research will adopt a qualitative approach in order to establish the relationship between the numerical variables of age and the frequency of in-person clinical visits made by patients (2010, p. 696). Through the purpose of describing the phenomenon of in-person clinical visits, a sound quantitative-based research question enables the researchers to evaluate the dimensions of characteristics of the phenomenon or determine (Polit & Beck, 2014, p. 12). The research question meets the criteria of an effective question because it clearly establishes a framework through which the study will describe the phenomenon under evaluation.

In addition to presenting a clear research question, Strotmeyer et al. clearly state the hypothesis for this research. The hypothesis of this research expands upon the framework presented by the research question by attempting to focus on the specific factors that contribute to the phenomenon addressed by the research question. In addition to determining the frequency of in-person clinical visits among different demographic groups, the hypothesis also aims to assess the characteristics that contribute to either a higher or lower frequency of visits. Within the third paragraph of the article, the researchers establish their hypothesis that the type of visits that patients receive would be related to important demographic, lifestyle, health, and function variables (2010, p. 697). Thus, the hypothesis predicts that the health status of patients is a key causative factor that impacts the prevalence of follow-up visits among elder patients.

Evaluating the wording of the hypothesis reveals its strengths and weaknesses. The first characteristic of the hypothesis to consider is whether it is directional or non-directional. As Polit and Beck note, a directional hypothesis specifies both the relationship and the direction of the relationship between the variables (2014, p. 109). Yet, by contrast, a nondirectional hypothesis does not clarify the direction of the relationship between the variables (2014, p. 109). The second characteristic to consider is whether the hypothesis is simple or complex. A simple hypothesis contains a single variable and a dependent variable while a complex hypothesis contains multiple independent or dependent variables (2014, p. 109). The appropriateness of the complexity of the hypothesis is dependent upon the variables that are to be assessed by the research question.

Utilizing the criteria presented by Polit and Beck, it can be determined that the hypothesis presented by Strotmeyer possesses minor weaknesses yet is strong overall. First, the hypothesis can be classified as a nondirectional hypothesis because while it assesses that there is a relationship between the demographics, lifestyle, health, and function of patients and their propensity to receive in-person clinical care, the researchers fail to predict whether these factors increase or decrease the likelihood of such visits. It is inferred from the previous discussion of the literature that factors such as poor health and cognitive abilities might decrease the likelihood of a patient to arrive for in-person checkups (Strotmeyer et al., 2010, p. 696-697). Yet, the researchers fail to explicitly state how these factors relate to retention for follow-up clinical visits in the hypothesis. This omission weakens the strength of the hypothesis by failing to provide a clear position that the research intends to confirm. However, the authors do specifically offer a directional statement regarding the variable of age, stating that they anticipate that the oldest patients in the study would have the lowest retention rates for in-person clinical visits (2010, p. 697). In order to strengthen the hypothesis, the researchers must be consistent in applying a directional hypothesis.

The second classification under which the hypothesis is evaluated is the use of a simple or complex hypothesis. For this research, Strotmeyer et al. selected a complex hypothesis to test in their research. While the primary dependent variable that the authors highlight for this research is age, the research also assesses demographic factors, lifestyle characteristics, health status, nutrition and physical activity of the research subjects (Strotmeyer et al., 2010, p. 697). The selection of a complex hypothesis was appropriate to this study because it defines the variables that were tested through statistical analysis. Through analyzing the data of the CHS, the authors were able to isolate the specified variables and determine how these variables affected the phenomenon addressed by the research question and hypothesis. In consideration of the scope of this research, it is necessary to include multiple dependent variables. As the research question suggests, there are several causative factors that can impact the habits of patients. In order to obtain a meaningful answer to the research question, it is necessary to analyze additional variables that might impact the behaviors of study participants. Thus, while the hypothesis could be improved upon by adopting a directional format, its main strength is that it thoroughly assesses the variables that impact the frequency of clinical visits made by the research subjects.

Analysis of Study Design

The next area of analysis is the study design selected by Strotmeyer et al. Thus, the first attribute of the study to consider in making this assessment is whether this quantitative study utilizes experimental research or nonexperimental research in order to test its hypothesis. According to authors Polit and Beck (2014), experimental research refers to a study in which researchers use methods of intervention in order to evaluate a specific intervention or therapy (p. 59). An example of experimental research is a clinical study that tests the effect of medication on research participants. Researchers intervene in such a study to administer the medication to certain groups while depriving a control group of the medication. In contrast, nonexperimental research refers to a study where researchers collect data on a phenomenon that already exists without actively intervening (2014, p. 59). This research is an example of nonexperimental research because it utilizes data that was previously collected in the Cardiovascular Health Study (CHS). Because the researchers utilize methods of statistical analysis to evaluate data that was previously collected, there is no intervention in this study. Thus, the efficacy of the intervention does not need to be assessed in order to evaluate the study design.

Because the research utilizes previously collected data, it is necessary to consider the methods of analysis that were adopted by the CHS. In order to test their hypothesis on the relationship between dependent variables and the retention rates of patients, Stotmeyer et al. analyzed data from the findings of the CHS, which is a longitudinal cohort study (Stotmeyer et al., 2010, p. 696). According to the definition of Polit and Beck, longitudinal studies feature a design that collects data several times over an extended period of time in order to evaluate changes that take place over time (Polit & Beck, 2014, p. 163). In medical research, longitudinal have several strengths over short-period studies. The primary benefit is that through evaluating repeated correlations over a longer period of time, longitudinal studies can best establish causality (2014, p. 163). In contrast to a cross-sectional design, longitudinal designs strengthen causal inferences that can be made by the researchers while also enabling researchers to focus on general and nonclinical populations (2014, p. 163). Thus, in general, longitudinal studies are ideal for nursing research because they enable practitioners to establish solid evidence upon which practice can be based.

In order to determine the strengths of the research design in this article, it is necessary to consider the objectives of both Strotmeyer et al. and the CHS upon which their analysis is based. The primary feature of the research design selected by Strotmeyer et al. is that it utilizes a nonexperimental design. In order to assess their hypothesis that select dependent variables impact follow-up care among patients, the researchers decided to evaluate existing data rather than conduct their own research with interventions. For the purpose of this study, the approach that the researchers adopted was appropriate. Because previously existing research was already available to describe the phenomenon that the researchers wish to focus upon, it was appropriate for the researchers to utilize readily available data. In the case of this study, conducting a separate experiment would not only be redundant because of the availability of applicable data, but it would also be costly and time-consuming. Thus, adopting a nonexperimental approach adopted by Strotmeyer et al. was appropriate for the research design.

However, the results that Strotmeyer et al. obtain also rely upon the soundness of the CHS. According to the descriptions provided by Strotmeyer et al., the CHS is a multicenter cohort study that evaluated the risk factors of cardiovascular disease (Strotmeyer et al., 2010, p. 697). The selection of a cohort design is a notable feature of the design selected for the CHS. As Polit and Beck note, a cohort design is a design utilized in nonexperimental studies which follow a defined group of people, referred to as a cohort, over a period of time in order to evaluate the outcomes for the cohorts (Polit & Beck, 2014, p. 376). Conforming to the longitudinal design, the data obtained for the CHS is collected over multiple points in time within the total length of the study. In order to evaluate the health status of the participants, the CHS participants underwent a baseline assessment in 1988 (Strotmeyer et al., 2010, p. 697). Additionally, researchers contacted CHS participants every 6 months and conducted an annual assessment in 1999 followed by a follow-up assessment in 2005 through 2006 (2014, p. 696). Thus, the CHS covered a span of eighteen years in total. Through conducting periodic assessments over a significant span of time, the CHS provides an effective foundation for Strotmeyer et al. to evaluate long-term trends in follow-up care among elderly patients. Further, because Strotmeyer et al. hold the primary objective of establishing long-term trends among their subjects, their selection of a nonexperimental design that utilizes a previously conducted longitudinal cohort study is the most appropriate design for testing their hypothesis.

Review of Statistical Data

Before assessing the statistical methods of the research, it is necessary to assess the data collected by the researchers. One factor is assessing the strengths of the statistical sample is the size of the total sample. The CHS, from which the data for this study is obtained, includes 5,888 participants that are representative of the general geriatric population in the United States (Strotmeyer et al., 2010, p. 696). The CHS accesses several sources of data in order to obtain the cohorts for the study. As Strotmeyer et al. specify, the CHS obtains its sampling from “Medicare eligibility lists, noninstitutionalized, ambulatory men and women aged 65 and older” (p. 697). Further, the researchers specify that the mean enrollment age was 73 while the age range was 65 through 100, and 58.6 percent of the study participants were female while 15.7 percent of the study participants were African American (2010, p. 697). Additionally, the data was collected from four U.S. field centers in North Carolina, California, Maryland, and Pennsylvania (2010, p. 697). As the description of the collected data reveals, the researchers obtained a sample that was representative of the regional and racial diversity of the United States while focusing upon an elderly population above the age of 65 for the study. Further, by evaluating a large sample, the researchers reduce their risk of committing a Type II error that arrives at a false negative conclusion.

Yet, a primary criticism of this data is that the only racial minority group includes is African Americans. Currently, there are other racial minority groups that are rapidly rising in population, such as Asian Americans and Latinos. However, because this study draws from data that was initially collected during the 1980s, access to these other groups might have been limited and African Americans show a high rate of cardiovascular disease. Still, it must be noted that follow-up research should include samples that are representative of the diverse racial groups in the United States. Another weakness of the study is to highlight is that the researchers fail to conduct a power analysis in order to determine the sample size that they would need to avoid making a Type II error or drawing incorrect conclusions from their sample. However, because they are utilizing previous data from the CHS study, a power analysis would not yield useful results for this study. Because the researchers are limited to the confines of the CHS data, they are unable to obtain the ideal sample size that is necessary to limit error in their findings. Future research can benefit from utilizing a power analysis before specifying the sample size for evaluation.

The second focus of analysis considers the method of statistical analysis that is utilized in the research. In assessing the factors that contribute to the retention of elderly patients in seeking follow-up clinical care, the researchers utilize multivariate statistical analysis. The variables that the researchers focused upon in their analysis included age, sex, race, clinic, site, weight, current smoking, high school graduate, low cognition, and self-reported health (2010, p. 697). By clearly defining the variables under evaluation, the researchers clearly identify the specific characteristics of the population that is being evaluated. Further, these characteristics are appropriate because they pertain to the variables that the researchers specify in the research question and hypothesis of the study.

Clinical Applications of Research

To support the clinical implications of the research, Strotmeyer et al. (2010) conduct a literature review that highlights the significance of their research question to clinical practice. As Strotmeyer et al. established in the introduction of their article, elderly patients above the age of 80 years of age are among the fastest-growing segment of the population, yet this age group is also underrepresented in research (2010, p. 696). Establishing their focus on retention rates of elderly patients who receive follow-up care, the authors defined retention as “retaining surviving participants enrolled at baseline for subsequent assessments in a longitudinal cohort study” (2010, p. 696). Additionally, through a review of prior longitudinal cohort studies, the researchers determined that the typical retention rate within five years of an initial appointment was between 70 to 80 percent (2010, p. 696). Through an evaluation of the literature, the researchers establish the importance of studying retention rates among older populations as well as the typical retention rates that can be expected among general patient populations.

Additionally, the literature review discusses the variables that impact retention for follow-up visits as well as the consequences of failing to maintain regular check-ups. As the researchers note, geriatric patients benefit from periodic in-person clinical visits because the physiological indicators of health accelerate more rapidly in older age groups (2010, p. 696). Failing to maintain visits serves as a double-edged sword because it can contribute to a declining health status that in turn makes it difficult for older patients to seek medical services that are impacted by rapid deteriorations in health (2010, p. 696). As an evaluation of the references list for the article reveals, the research utilized by the authors is highly credible in supporting their study. The sources have all been recently published within the past ten years and are obtained from credible medical journals and academic sources. The literature review is critical for establishing the research question and hypothesis because it explores the variables that contribute to the phenomenon that the researchers wish to assess.

Discussion and Conclusion

In the research “Long-Term Retention of Older Adults in the Cardiovascular Health Study: Implications for Studies of the Oldest Old,” researchers Strotmeyer et al. assess the impact that variables such as demographic information, health status, lifestyle characteristics, and physical functioning have upon the retention rate for patients in receiving follow-up care at health clinics. By examining these variables, the researchers attempt to test the hypothesis that older participants possess demographic and health barriers that reduce their retention rates for in-person clinical visits. Through multivariate statistical analysis, the researchers were able to confirm their hypothesis and determine that an increase in age is strongly correlated with reduced retention for in-person visits. Further, this trend held true for older adults across the tested variable groups.

Through sound methodology and a supportive literature review, the researchers present findings that hold significant implications from the standpoint of research-based practice. As the literature review conducted by the researchers revealed, the health outcomes of elderly patients are significantly related to their ability to receive in-person care. Yet, factors that correlate with aging, such as a deterioration in health and cognitive abilities can undermine the ability of patients to receive critical medical services in old age. Based on this research, nurse practitioners must consider modifications in their practice that will meet the needs of elderly patients, and especially patients above the age of eighty years of age. As the data determines, incorporating home-based visits into practice will increase the propensity of patients to receive follow-up care. Overall, Strotmeyer et al. provide sound evidence for the importance of adapting healthcare practices in order to increase the accessibility of healthcare services for elderly patients.


Polit, D., & Beck, C. T. (2014). Essentials of nursing research: Appraising evidence for nursing practice (4th ed.). Philadelphia, PA: Lippincott Williams & Wilkins.

Strotmeyer, E. S., Arnold, A. M., Boudreau, R. M., Ives, D. G., Cushman, M., Robbins, J. A., Harris, T. B., & Newman, A. B. (2010). Long-term retention of older adults in the cardiovascular health study: Implications for studies of the oldest old. Journal American Geriatrics Society, 58(4), 696-701.