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Running head: QUANTITATIVE ARTICLE ANALYSIS
Quantitative Article Analysis
Kelly Price
Ferris State University
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QUANTITATIVE ANALYSIS
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According to Beyea and Nicoll (1997), quantitative research methods are based on
objectivity and variables can be measured specifically. “The framework for quantitative research
is derived from nonexperimental, experimental, and quasiexperimental designs” (Beyea &
Nicoll, 1997, p. 324). The article Factors influencing heart failure patients’ sleep quality is a
quantitative research article that has a nonexperimental research design (Wang, Lee, Tsay, &
Tung, 2010). This design includes exploratory, descriptive, and correlational studies. Nurses
who use nonexperimental designs usually use surveys or questionnaires to obtain data (Beyea &
Nicoll, 1997).
The purpose of the study presented in the article was to “explore the factors related to the
sleep quality of patients with heart failure” (Wang et al., 2010, p. 1731). The importance of this
purpose is evident in the article because the authors discuss that previous research mainly
focused on investigating sleep quality in those patients with sleeping disorders. The problem
statement in the article addresses that sleep problems are common in patients with heart failure
(HF) and that this has a negative impact on their life. The study found that patients with HF
often struggle lying supine to sleep, falling asleep, staying asleep, and waking up early. The aim
of this study was to describe the factors influencing sleep quality in patients with HF. This
included using demographics, disease characteristics, life style, and emotional status as well as
perceived health (Wang et al., 2010).
Wang and colleagues found that previous literature reviews and studies had been done
prior to their current study. Throughout the article, the authors reviewed five studies that
investigated the sleep quality of patients with HF. The study framework of the article Factors
influencing heart failure patients’ sleep quality included the description of factors influencing
sleep quality in patients with HF and the research design included a predictive correlational and
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nonexperimental design. Data was collected for two months from September to December in
2007 using a questionnaire for demographics, disease characteristics, and life style. The data
was collected using an experienced nurse to monitor, read the questions, and explain the
questionnaire to the participants. In addition, the participants were asked to answer the questions
in person and were not allowed to take the questionnaire home. Each question was explained
appropriately and was given by the nurse in a standardized fashion.
The sample in the article was a convenience sampling of 101 patients with HF from
cardiology clinics from Taipei, Taiwan. According to Wang and colleagues, a sample size of 81
participants would be required for the purpose of the study. The sample size was sufficient for
this study given the number of variables and design. Unfortunately, a convenience sample was
used for this study. According to Nieswiadomy (2008), in this type of sampling there is no
accurate way to determine the representativeness of the population. In addition, convenience
sampling is often used in nursing research because of the savings in time and money. The
sample from this article was a limitation due to 92% of the HF participants were in the NYHA
functional class of I or II; thus the results may be not be representative of other clinical HF
populations (Wang et al., 2010).
The instruments used to collect the data in the study included the Perceived Health Scale,
the Physical Activity Scale for the Elderly (PASE), revised Short-Form Geriatric Depression
Scale (SF-GDS), and the Pittsburgh Sleep Quality Index (PSQI) (Wang et al., 2010). All
instruments were translated into Chinese and the consistencies of the instruments were tested
using Cronbach’s alpha analysis. Wang et al. (2010) reported with each instrument their internal
consistency scale or Cronbach alpha analysis in the study. The following were noted to be
strengths of the Wang et al. (2010) study: descriptive statistics to describe the participant’s
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characteristics. These statistics include percentages, means, and standard deviations. The
characteristics described included the patient’s demographics, disease characteristics, perceived
health, depression, and physical activity. The values were reported in tables in throughout the
study. The inferential statistics used in this study included independent t-tests and one-way
analysis of variance (ANOVA) to analyze the relationships among demographics, lifestyle, and
sleep quality (Wang et al., 2010). Also, Pearson correlation coefficients were used to analyze the
relationships among perceived health, depressed mood, physical activity levels, and sleep
quality. This was presented in a table in the study and P-values were given to show the level of
significance. In addition, “multiple regressions were done in the study to examine the important
predictive factors of sleep quality” (Wang et al., 2010, p. 1733).
The results of this study was presented objectively and the figures illuminated the results
presented in the tables. Wang et al. (2010) found that in this study a majority of the participants
were male with a mean age of 74. In addition, the majority had NYHA class II heart failure,
hypertension, coronary heart disease, and increased cholesterol. As a whole the participants had
poor quality of sleep, short duration of night sleep, frequent waking in the night due to urination,
lack of sleep efficacy, and daytime sleepiness (Wang et al., 2010). Wang and his colleagues also
found that “sleep quality was positively associated with NYHA functional class, number of
hospitalizations, number of comorbidities, number of medications taken, and depression score”
(p. 1734). This means that those patients who had more hospitalizations, worse HF functional
class, a greater number of comorbidities, used more medications, and have depression suffer
from poorer sleep quality.
In conclusion, factors associated with poor sleep quality included gender, number of
hospitalizations due to heart failure, NYHA HF functional class, comorbidities, depressed mood,
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perceived health, and exercise habits (Wang et al., 2010). The limitations identified in the study
include using a convenience sample and a self-report questionnaire. In addition, “92% of the
participants were in NYHA functional class I or II, thus the results may not be generalizable to
clinical heart failure populations…” (Wang et al., 2010, p. 1735). Most of the participants were
male and in the age range of 75-84 years. These results may not be representative of those with
heart failure who are younger or female. In addition with the self-questionnaire, the authors
raised interest with validity and reliability. Perhaps objective sleep measurements should have
been used.
This study I believe supports current evidence based practice. Nurses can use the
information studied to implement in their current practice. Education is a major component
when teaching patients with heart failure. According to the authors, nurses should teach patients
self-care skills and encourage adherence to their treatment plans. Patients with HF should be
taught about their medications and to increase their exercise to increase their sleep quality.
Patients with HF should also be assessed for any psychological conditions and those who suffer
from depression should be referred to the proper medical professionals. In addition, nurses can
provide a listening ear, and engage in support for patients with HF. Also, nurses can refer
patients to social sources such as support groups that can be useful in preventing sleep problems
(Wang et al., 2010). Implications for practice would also include teaching patients sleep hygiene
and to increase leisure time activities.
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References
Beyea, S.C., & Nicoll, L.H. (2010). Qualitative and quantitative approaches to nursing research.
Association of periOperative Registered Nurses 66(2), 323-325.
Nieswadomy, R. (2008). Foundations of nursing research (5th ed). Upper Saddle River, NJ:
Pearson Prentice Hall.
Wang, T.J., Lee, S.C., Tsay, S.L., & Tung, H.H. (2010). Factors influencing heart failure
patients’ sleep quality. Journal of Advanced Nursing 66(8), 1730-1740.
doi: 10.1111/j.1365-2648.2010.05342.x
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Appendix A
N350 Fall 2010 Research in Nursing: Research Article(s) Critique Form(s)
Name: Factors influencing heart failure patients’ sleep quality
Quantitative Article:
Resources:
Text: Nieswiadomy, R.M. (2007). Foundations of Nursing Research (5th Ed.) Upper Saddle River, New
Jersey: Prentice Hall. ISBN 10:0-13-612980-3
Quantitative Research Article Analysis
Ethical Aspects: Wang, Lee, Tsay, & Tung (2010) state “the study was approved by the appropriate
ethics committees” (p. 1733).
Problem Statement: “The aim of the study was to describe the factors influencing the sleep quality of
patients with heart failure (HF)” (Wang et al., 2010, p. 1730).
Literature Review: The article provides previous research in regards to sleep quality and heart failure.
The research was clear and supports the necessity of the current article (Wang et al., 2010).
Study Framework: The study framework included describing the factors influencing the sleep quality of
patients with HF, including demographics, life style, and emotional status (Wang et al., 2010).
Hypotheses and Research Questions: Those suffering from HF have poorer quality of sleep. Exploring
the factors of sleep quality in HF patients can be used to help develop interventions to improve overall
sleep quality (Wang et al., 2010).
Quantitative Research Designs: Research design included a predictive correlational and
nonexperiemental design (Wang et al., 2010).
Qualitative Research Designs: Grounded theory-analysis
Sampling Procedure: The sampling procedure was convenience sampling of 101 patients with HF from
cardiology clinics from Taipei, Taiwan (Wang et al., 2010).
Data Collection Procedures: Data was collected for 2 months September-December 2007 using a
questionnaire for demographics, disease characteristics, and life style (Wang et al., 2010).
QUANTITATIVE ANALYSIS
Data Collection Methods: Data was collected using the Perceived Health Scale, Physical Activity Scale
for the Elderly (PASE), revised Short-form Geriatric Depression Scale (SF-GDS), and Pittsburgh Sleep
Quality Index (PSQI). The questions were read to each participant by an experienced nurse and
appropriate explanations were given. Each participant was asked to answer each question without
assistance and not allowed to take the questionnaire home (Wang et al., 2010).
Descriptive Statistics: Percentages, means, and standard deviations were used to explain the patient
characteristics (Wang et al., 2010).
Inferential Statistics: Independent t-tests and one-way analysis of variance (ANOVA) was used to
measures the relationships among life style, demographics, and sleep quality (Wang et al., 2010).
Presentation of Study Findings: The findings of this study indicated that sleep quality was associated
with gender, the number of previous hospitalizations due to HF, New York Heart Association (NYHA)
class, number of comorbidities, depressed mood, perceived health, and exercise habits. In addition this
study yielded that age, taking beta-blockers, hypertension, coronary artery disease (CAD), depression,
and anxiety are additional factors for decreased sleep quality in HF patients (Wang et al., 2010).
You earned 29/30 point
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