Article Analysis 2

Used in Current
Research
Kathleen Zellner, MSN, RN, BC; Connie J. Boerst, MSN, RN, BC; and
Wil Tabb, PhD

ABSTRACT
Undergraduate nursing research courses should empha-

size the statistics most commonly used in the nursing litera-
ture to strengthen students’ and beginning researchers’ un-
derstanding of them. To determine the most commonly used
statistics, we reviewed all quantitative research articles
published in 13 nursing journals in 2000. The findings sup-
ported Beitz’s categorization of kinds of statistics. Ten pri-
mary statistics used in 80% of nursing research published
in 2000 were identified. We recommend that the appropriate
use of those top 10 statistics be emphasized in undergradu-
ate nursing education and that the nursing profession con-
tinue to advocate for the use of methods (e.g., power analy-
sis, odds ratio) that may contribute to the advancement of
nursing research.

A
dilemma faced by teachers of nursing research in un-
dergraduate baccalaureate programs is identifying
the key concepts that would be most meaningful to

students as they enter professional practice. have
been an integral part of nursing practice and research since
the beginning of modern nursing. Florence Nightingale’s
innovative use of descriptive statistics and her use of the
now-famous radial graphs, sometimes called coxcombs, rep-
resents an early and effective use of statistical analysis of
data in nursing research. This marked the spread of the use

of statistical analysis in nursing, which migrated from the
larger field of 19th-century biomedical research (Nightin-
gale, 1859).

curricula include a component of statistical
methods as part of nursing research courses to enable stu-
dents to understand current research and contribute to its
ongoing discussion. Learning statistics can be a difficult
task for any student, and nursing students often struggle
with learning the concept and the transfer of their knowl-
edge to nursing literature (Schuster & Ritchey, 1998). Such
difficulty can often deter students from furthering their
nursing degree (Stranahan, 1995).

In developing statistics courses for undergraduate nurs-
ing students, it is important to consider how to teach sta-
tistics, what statistics to teach, and what statistics are
common in the literature to provide students with a basic
comprehension of data that will enable them to interpret
statistical results. Therefore, it is important to identify the
statistical tests and procedures needed to comprehend mod-
ern nursing research.

journals frequently publish articles in which a
basic understanding of statistics is assumed for an educated
reading of the research. To guide nursing instructors, we
aimed in this research to identify the statistical tests used
most frequently in nursing research articles. We anticipate
that this information could then help faculty in emphasizing
the statistics nurse readers would most likely encounter.

TheoReTiCAl FRAMeWoRK

The teaching of statistics can be linked to the Conversa-
tion Theory of Gordon Pask (1975). His theory focused on the
premise that “learning occurs through conversations about
a subject matter which serve to make knowledge explicit”
(Theory Into Practice Database, n.d., Overview Section, ¶1).
Pask’s (1975) theory serves as a foundational component to
student learning of statistics through the application of cog-
nitive learning. His methods of teaching relationships and
the use of problem-solving strategies facilitate an under-

Received: October 1, 2004
Accepted: June 30, 2005
Ms. Zellner is Associate Professor and Ms. Boerst is Associate

Professor and Undergraduate Program Director, Bellin College of
, and Dr. Tabb is ad hoc professor, University of Wisconsin
Green Bay, Green Bay, Wisconsin.

Address correspondence to Connie J. Boerst, MSN, RN, BC, As-
sociate Professor and Undergraduate Program Director, Bellin Col-
lege of , 725 South Webster Avenue, PO Box 23400, Green
Bay, WI 54305-3400; e-mail: [email protected].

February 2007, Vol. 46, No. 2 55

STATISTICS USeD IN NURSING ReSeARCH

standing of statistics. Pask’s work provided the early steps
for later use of learning theories related to teaching statis-
tics. An appropriate assumption made on the basis of Pask’s
theory is to teach statistics so students have the advantage
of performing statistics while learning the concepts.

liTeRATURe RevieW

Johnson (1984) and Knapp and Miller (1987) wrote two of
the early articles addressing the incorporation of statistical
concepts and biometrical methods into undergraduate nurs-
ing curricula. Johnson (1984) argued that many nursing
students have high levels of anxiety regarding their math-
ematical ability and recommended that statistical concepts
be taught simultaneously with a nursing research course.
Knapp and Miller (1987) recommended that in addition to
requiring college algebra, statistics, and an introduction to
biomedical computing, nursing programs must ensure that
these courses are relevant to nursing. Similarly, Stranahan
(1995) concluded that being enrolled in both classes simulta-
neously is more beneficial to learning. In addition, Schuster
and Ritchey (1998) agreed and found that an interdisciplin-
ary statistics course incorporating the mathematics of both
statistics and nursing research enabled students to inter-
pret “the meaning of the statistics within the context of the
nursing research literature” (p. 34).

Johnson (1984), Knapp and Miller (1987), Beitz and Wolf
(1997), and Robinson (2001) asserted that to make statis-
tics meaningful, the examples used in teaching statistical
techniques need to be relevant to learners. Beitz and Wolf
(1997) recommended that to make statistical concepts seem
less abstract, educators should build in concrete activities
that make the concepts more meaningful. According to Be-
itz (1998), students’ greatest confusion in using statistics is
in transferring statistical knowledge and selecting the most
appropriate statistical test for a given situation. To that end,
Beitz developed an organized table that lists the statistical
tests central to nursing research and provides students with
an overview of the definition and application of a variety of
statistical measures. Robinson (2001) acknowledged Beitz’s
work and developed the Guidelines for Statistical Analysis
(p. 137), as well as the Golden Rules for Statistical Analysis
Adequacy (p. 138).

Authors agree that knowledge of statistics is a vital and
essential skill, necessary for the progression of the nurs-
ing profession, and needed for students to be able to read,
interpret, and integrate nursing research (Robinson, 2001;
Schuster & Ritchey, 1998; Taylor & Muncer, 2000).

The literature offers little information regarding which, if
any, statistical techniques are used most frequently and which
should therefore receive greater emphasis in statistics cours-
es. Although Beitz (1998) developed a chart listing the major
statistical tests, she provided no explanation of the criteria for
a test to be considered major. If frequently used tests could
be identified, taught, and emphasized in undergraduate pro-
grams, educators could spend more time providing application
opportunities and less time on seldom used or higher level sta-
tistics that are beyond the needs of beginning learners.

Graduate nursing research courses could build on this
knowledge, as Knapp and Miller (1987) suggested. Gradu-
ate courses could explore the lesser known but equally as
important and higher level statistical techniques. The pur-
pose of this article was to identify the most frequently used
statistics in nursing research today so that educators would
be able to share the results with beginning nursing research-
ers, enabling them to apply and critique this information.

A content analysis of current nursing research provides
many useful results. It informs readers of current topics of
professional interest and summarizes the principle meth-
ods used in research. It identifies the topics that might be
highlighted in classroom discussions to empower students
to become more literate readers of nursing journals. This
study joins a number of analyses of statistical methods in
professional research (Beitz, 1998; Polit & Sherman, 1990;
Robinson, 2001; Taylor & Muncer, 2000), which identify the
key statistical tools used in research. As such, it serves as a
guide to educators about appropriate classroom topics and a
resource to learners of essential research skills.

MeThoD

We reviewed a selection of 462 articles from 13 nursing
journals published in 2000. In choosing the journals for in-
clusion in the study, we believed it desirous to incorporate
those with wide readership, as well as those publishing ex-
tensive scholarship. The nursing journals used in this study
were identified through a three-step process. First, we used
the “Brandon/Hill Selected List of Print Books
and Journals” (B/H) by Hill and Stickell (2002). The B/H
is a “guide for nurses and librarians who find themselves
responsible for choosing a collection of current nursing lit-
erature” (Hill & Stickell, 2002, p. 100); it also includes a
comprehensive list of journals identified as key components
of any library.

Using the B/H list, we then cross-referenced those jour-
nals with the Key and Electronic Journals: Charac-
teristics and Database Coverage, 2001 ed. (KeNJ), a compre-
hensive guide of more than 200 national and international
nursing journals compiled by Margaret Allen (2001). Jour-
nals are included on the KeNJ list on the basis of criteria
of peer review; research percentages (i.e., percentages of
research articles for the journal for a particular year); inclu-
sion in the B/H, the Canadian Association list, and/
or the Research Journals Index; or being indexed in
the British Index, CINAHL, PubMed/Medline, and
other databases.

The final step was to identify those journals for which the
annual percentage of published research articles was 40%
or more. Thirteen journals, representing 11 specialty areas,
were chosen using this process. See Table 1 for a complete
list of the journals selected, including the percentage of re-
search published annually and the number of articles re-
viewed for this study. each issue of the selected journals was
reviewed, and all quantitative research articles (N = 462)
were scrutinized for the kinds of statistical methods used.
By mutual agreement, we designed a data-reporting grid,

56 Journal of Education

zeLLNeR, BOeRST, & TABB

focusing on the specific sta-
tistical methods used. Be-
cause all authors were re-
sponsible for data collection,
interrater reliability was
established via concurrent
review of two previously
published research articles,
with group discussion and
review to determine consis-
tency of data identification.

ReSUlTS

After all 462 articles
were reviewed, it became
apparent that regardless
of journal orientation or
focus, authors used and
consistently reported us-
ing similar statistical
methods. These similari-
ties served as the basis for
creating a set of categories
of statistical methods that
would summarize our re-
view. The typology used by
this study, although devel-
oped independently, came
to mirror the descriptions
of statistical techniques
noted in other studies (Beitz, 1998); the results are re-
ported in Table 2.

Descriptive
Descriptive statistics were the tools used most frequent-

ly in the nursing research articles. Measures of central ten-
dency and dispersion accounted for approximately 63% of
the statistics used. Authors assumed readers were famil-
iar with the basic concepts of mean, median, variance, and
standard deviation, as well as the use of percentiles and
percentages in research. Many articles also displayed these
statistics in plots or graphs. Although these tools were often
carried into more formal discussions, they in themselves of-
ten provided useful and relevant information gained from
the nursing research. These techniques are an assumed
base of knowledge for nurses and are another indication
of the ongoing need for nursing students to master math-
ematical skills early and comprehensively, as advocated by
Knapp and Miller (1987).

inferential
Most authors subjected their instrument to a measure-

ment of reliability; the most commonly applied measure-
ment was Cronbach’s alpha. However, the next step of anal-
ysis, the examination of the scores of the instrument, varied
widely. Many authors simply tabulated the scores or plotted
their frequency.

Interestingly, although most researchers used well-
known statistical methods, such as t tests, analysis of vari-
ance (ANOVA), and regression analysis in its many forms,
individual research needs often guided authors to other,
lesser known tests. Although it is possible to compile a list
of common statistical tests (e.g., the top 10 list presented in
Table 3), a comprehensive handbook of statistical methods
is always an important reference tool to consult when read-
ing nursing research (Polit, 1996).

Additional Findings
Articles addressing the nature of biomedical research

(Cummings & Rivara, 2003; International Committee of
Medical Journal editors, 1997) have suggested that it would
be more appropriate to use odds ratios as a way of express-
ing research outcomes. Where the outcomes of logistic re-
gression have required it, this method of statistical report-
ing was described. In reviewing the articles for this study,
we found that this approach is just beginning to be used in
nursing research and, in fact, would have been number 11 if
the top 10 list were expanded.

Our readings also confirmed that nursing research has
not included reference to the appropriateness of sample size,
which often limited the generalization of study conclusions
(Kachoyeanos, 1998; Polit & Sherman, 1990). Although sam-
ple sizes were usually clearly defined and the methods used
for sample selection discussed, a closer analysis of sample

TablE 1

Journals Selected for Inclusion in the Study, Percentage of
Research Published annually, and Number of articles Reviewed

Journal Title Specialty area
% of Research

Published annually
No. of articles

Reviewed

American Journal of Critical Care Critical care 73 28

Applied Research Research 71 22

Cancer Cancer 69 34

Heart & Lung: The Journal of Acute
and Critical Care

Critical care 58 25

Journal of Advanced Research 65 160

Journal of Community Health Community health 60 12

Journal of Administration Administration 35a 28

Journal of Care Quality Administration 41 15

Journal of Education Education 46 22

Journal of Scholarship Research 48 27

Journal of Obstetric, Gynecologic,
and Neonatal

Maternal-child 40 24

Research Research 83 42

Western Journal of Research Research 73 23

a Although below the cut-off point of 40% research published annually, this journal was selected for its accessibility
and wide readership.

February 2007, Vol. 46, No. 2 57

STATISTICS USeD IN NURSING ReSeARCH

size was often lacking. Readers were then required to consult
standard works on research design and sampling methods to
judge the adequacy of the sample for the research questions
explored. Nurse researchers are still not using power analy-
sis, which is used to estimate the size of a sample needed to
obtain a significant result, in their discussions. Kachoyeanos
(1998) noted that “In recent review of nursing research, the
overall lack of adequate statistical power became quite clear”
(p. 105). In addition, Polit and Sherman (1990) stated that
“nursing research needs to pay greater attention to issues of
power in designing their studies” (p. 368).

CoNClUSioN

The widespread use of statistical methods in a variety
of nursing journals underscores the importance of including
statistical skills in nursing education. A review of more than
400 nursing research articles revealed that regardless of
journal orientation and focus, the same 10 statistics were re-
peatedly used in approximately 80% of the research. These
10 statistics were included in the chart developed by Beitz
(1998) and termed “major statistics and statistical tests” (p.
49). We contend that initial statistics and nursing research
courses should emphasize these 10 statistics to strengthen
students’ and beginning researchers’ understanding.

Pask’s Conversation Theory (1975), while applicable to
any teachable subject, provides an extensive overview and

TablE 2

Used in the Journal articles
Reviewed and Frequency of Their Occurrence

Statistic n (%)

Descriptive statistics: Measures of central tendency

Mean 261 (12.4)

Median 41 (2)

Mode 12 (0.6)

Frequency distribution 189 (9)

Graphs and plots

Bar graphs 61 (2.9)

Dot plot 16 (0.8)

Line graph 25 (1.2)

Skew 3 (0.1)

Descriptive statistics: Measures of dispersion

Variance 4 (0.2)

Standard deviation 209 (10)

Range 129 (6.1)

Percentages, percentiles, and quartiles 361 (17.2)

Inferential statistics: Parametric

Z score 4 (0.2)

t test, independent and dependent 124 (5.9)

Analysis of variance (ANOVA), all kinds 100 (4.8)

Multiple comparison/post-hoc tests
(e.g., Scheffe, Tukey)

34 (1.6)

Analysis of covariance (ANCOVA) 12 (0.6)

Correlation 109 (5.2)

Cronbach’s alpha 82 (3.9)

Regression, all kinds 77 (3.7)

Odds ratio 27 (1.3)

Discriminant analysis 2 (0.1)

Factor analysis 23 (1.1)

Inferential statistics: Nonparametric

Chi square 114 (5.4)

Mann-Whitney test 18 (0.9)

Kruskal-Wallis test 9 (0.4)

Wilcoxon’s test 13 (0.6)

Fisher’s exact test 12 (0.6)

McNemar test 5 (0.2)

Power analysis 24 (1.1)

Total 2100 (100.1)

Note. Percentages do not equal exactly 100% due to rounding.

TablE 3

Top 10 a Used in the Journal articles
Reviewed and Frequency of Their Occurrence

Statistic n (%)

Descriptive statistics: Measures of central tendency

Mean 261 (12.4)

Frequency distribution 189 (9)

Descriptive statistics: Measures of dispersion

Standard deviation 209 (10)

Range 129 (6.1)

Percentages, percentiles, and quartiles 361 (17.2)

Inferential statistics: Parametric

t test, independent and dependent 124 (5.9)

Analysis of variance (ANOVA), all kinds 100 (4.8)

Correlation 109 (5.2)

Cronbach’s alpha 82 (3.9)

Inferential statistics: Nonparametric

Chi square 114 (5.4)

Total 1678 (79.9)

a The top 10 statistics represent approximately 80% of all statistical
measures used in the 462 articles reviewed.

58 Journal of Education

discussion of the use of learning statistics. The main empha-
sis of the theory is to teach back what a person had learned;
in other words, manipulation of the subject matter facili-
tates learning. Although not all students learn in the same
manner, using Pask’s theory would allow students to learn
the subject as well as the relationships among the concepts,
which aids in the understanding and application of statis-
tics and how this applies to nursing.

At the same time, as nursing research becomes more
sophisticated, it is clear that greater understanding of the
techniques and issues of quantitative study needs to be em-
phasized. The nursing profession should continue to move
forward in the use of more advanced statistical analyses,
including logistic regression and power analysis.

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February 2007, Vol. 46, No. 2