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7/29/2019 Nursing Research 2 Lecture
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Measurement
What is measurement?
Measurement involves rules for assigning number to qualities of object to
designate the quantity of the attribute. Attributes do not inherently have numeric values;
human invent rules to measure attributes. Many quantitative researchers concur with a
statement by early American psychology L. L. Thurstone: ―Whatever exists, exists in
some amount and can be measured. ― attributes are not constant; they vary from day to
day, from situation to situation, or from one person to another. This variability is capable
of a numeric expression that signifies how much of an attribute is present.
Measurement requires number to be assigned to object according to rules. Rulesfor measurement temperature, weight, and other physical attributes are familiar to us.
Rules for measurement many variables for nursing studies, however, have to be
created. Whether data are collected by observation, self-report, or some other method,
researchers must specify the criteria according to which number are to be assigned.
Levels of measurement
Normal measurement- the lowest level, involves using number simply to
categorize attributes. Examples of variables that are normally measured include gender
and blood type. The number used in normal measurement do not have quantitative
meaning. If we coded males as 1 and females as 2, the number would not have
quantitative implication __ the number 2 does not mean ―more than‖ 1 nominal
measurement provides information only about categorical equivalence and
nonequivalence and so the number cannot be treated mathematically. It is nonsensical,
for example, to compute the average gender of the sample by adding the numeric
values of the codes and dividing by the number of participants.
Ordinal measurement- ranks object on their relative standing on an attribute. If
a researcher orders people from heaviest to lightest, this is ordinal measurement. As
another example, consider this ordinal coding scheme for measuring ability to perform
activity of daily living : 1= completely dependent ; 2= need another person‘s assistance;
3= needs mechanical assistance and 4= completely independent in twice as good as
needing mechanical assistance. As with nominal measures, the mathematic operations
permissible with ordinal-level data restricted.
Interval measurement-occurs when researchers can specify the ranking of
object on an attribute and the distance between those object. Most educational and
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psychological test yield interval-level measures. For examples, the Stanford-Binet
intelligence scale—a standardized intelligence (IQ) test used in mant countries—is an
interval measure, a scire of 140 on the Stanford-Binet is higher than a score of
120,which, in turn, is higher than 100. Moreover, the difference between 140 and 120 is
presumed to be equivalent to the difference between 120 and 100. Interval scales
expand analytic possibilities: interval level data can be averaged meaningfully for
example. Many sophisticated statistical procedure require interval measurements.
Ratio measurement is the highest level-. Ratio scales, unlike interval scales,
have a rational, meaningful zero and therefore provide information about the absolute
magnitude of the attribute. The Fahrenheit scale for measuring temperature(interval
measurement) has an arbitrary zero point. Zero on the thermometer does not signify the
absence of heat; it would not be appropriate to sat that 60 F is twice as hot as 30 F.
many physical measures, however, are ratio measures with a real zero. A person
weight, for example, is a ratio measure. Ir is acceptable to say that someone who
weight 200pounds is twice as heavy as someone who weight 100 pounds. Statistical
procedure suitable for interval data are also appropriate for ratio-level-data.
Researchers usually strive to use the highest levels of measurement possible—
especially fpr their dependent variables—because higher levels yield more information
and are amenable to more powerful analyses than lower levels.
Advantages of measurement
a major strength of measurement is that it removes guesswork and ambigulity in
gathering data communicating information. Consider how handicapped health careprofessionals would be in the absence of measurement of body temperature, blood
pressure , and so on. Without such measures, subjective evaluations of clinical
outcomes would have to be used. Because measurement is based on explicit rules
resulting information tends to be objective, that is, it can be independently verified. Two
people measuring the weight of a person using the same scale would likely get identical
results. Not all measures are completely objective, but most incorporate mechanisms
for minimizing subjectivity.
Measurement also makes it possible to obtain reasonably precise information
instead of describing Nathan as ―tall,‖ we can depict him as being 6 feet 3 inches tall if necessary, we could achieve even greater precision, such precision allows researchers
to make fine distinctions among people with different degrees of an attribute.
Finally, measurement is a language of communication. Numbers are less vague
than words and can thus communicate information more clearly. If researcher reported
that the average oral temperature of a sample of patients was ―somewhat high‖ different
readers might develop different conceptions about the sample‘s physiological state. If
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the researcher reported an average temperature of 99.6 F however, there is no
ambiguity.
Reliability
Ratability is the consistency with which an instrument measures the attribute. If a scale weighed a person at 120 pounds one minute and 150 pounds the next, we
would consider it unreliable. The less variation an instrument produces in repeated
measurement, the higher its reliability.
Reliability also concerns a measure‘s accuracy. An instrument is reliable to the
extent that its measures reflect true scores—that is, to the extent that measurement
errors are absent from obtained scores. A reliable instrument maximized the true score
component and minimizes the error component of an obtained score.
Three aspect of reliability are of interest ot quantitative researchers: stability,
internal consistency and equivalence.
Stability
The stability of an instrument is the extent to which similar results are obtained
on two separate accasions. The reliability estimate focuses on the instrument‘s
susceptibility to extraneous influences over time, such as participant fatigue
assessments of stability are made through test-retest reliability procedures.
Researchers administer the same measure to a saple twice and then campare the
score.
Fictitious data for test-retest reliability of self-esteem scale
Subject number Time1 Time 2
1 55 57
2 49 46
3 78 74
4 37 35
5 44 46
6 50 56
7 58 55
8 62 669 48 50
10 67 63
r=.95
Suppose, for example, we were interested in the stability of a self-report scale that
measured self-esteem. Because self-esteem is a fairly stable attribute that does not
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change much from one day to another, we would expect a reliability measure of it to
yield consistent scores on two different days. As a checj on the instrument‘s stability, we
administer the scale 2 weeks apart to a sample of 10 people. Fictitious data for this
example are presented in table 14.1.
The score on the two tests are not identical but, on the whole, differences are not large.Researchers compute a reliability coefficient, a numeric index that quantifies an
instrument reliability, to objectively determine how small the differences are. Reliability
coefficients (designated as r) range from .00 to 1.00.* the higher the value, the more
reliable (stable) is the measuring instrument. In the example shown in table 14.1 the
reliability coefficient is .95, which is quite high.
Internal consistency
Scales and test that involve summing item scores are most always evaluated for their
internal consistency. Ideally \, scale are composed of items that all measure the oneunitary attribute and nothing else. On a scale to measure nurses‘ empathy, it would be
inappropriate to include an item that measures diagnostic competence. An instrument
may be said to be internally consistent to the extent that its items measure the same
trait.
Internal consistency reliability is the most widely used reliability approach among nurse
researchers. This approach is the best means of assessing an especially importance
source of measurement error in psychosocial instruments, sampling of items . internal
consistency is usually evaluated by calculating coefficient alpha (or cronbach’s
alpha).the normal range of values for coefficient , the more accurate (internallyconsistent) the measure.
Equivalence
Equivalence in the content of reliability assessment, primarily concerns the degree to
which two or more independent observers or coders agree about the scoring on an
instrument. With a high level of agreement, the assumptions is that measurement errors
have been minimized.
The degree of error can be assessed through interrater( or interobserver) reliability
procedures, which involve having two or more trained observers or coders. Makesimultaneous, independent observations. An index of equivalence or agreement is then
calculated with these data to evaluate the strength of the relationship between the
ratings. When two independent observers score some phenomenon congruently, the
score are likely to accurate and reliable.
Validity
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Validity is the degree to which an instrument measures what it is supposed to measure.
When researcher develops an instrument to measures hopelessness, how can they be
sure that resulting scores validity reflect this construct and not something else, such as
depressions?
Reliability and validity are not totally independent qualities of an instrument. Ameasuring device that is unreliable cannot possibly be valid. An instrument cannot
validly measure an attribute if it is erratic and inaccurate. An instrument can, however,
be reliable without being valid. Suppose we wanted to assess patients‘ anxiety be
measuring the circumference, but such measures would not be valid indicators of
anxiety. Thus, the high reliability of an instrument provides no evidence of its validity;
low reliability of a measure is evidence of low validity.
Content validity
Content validity concerns the degree to which an instrument has appropriate sampleof items for the construct being measured and adequately covers the construct domain.
Content validity is crucial for test of knowledge, where the content validity question is
:‖how representative are the questions on this test of the universe of questions on this
topic?‖
Content validity is also relevant in measures of complex psychosocial traits.
Researchers designing a new instrument should begin whit a thorough
conceptualization of the construct so the instrument can capture the full content domain.
Such a conceptualization might came from rich first hand knowledge, an exhaustive
literature review, or findings from a qualitative inquiry.
An instrument‘s content validity is necessarily based on judgment. No totally objective
methods exist for ensuring the adequate content coverage of an instrument, but it is
increasingly common to use a panel of substantive experts to evaluate the content
validity of new instrument. Researchers typically calculate a content validity index
(CVI) that indicates the extent of expert agreement. We have suggested a CVI value of
.90 as the standard for establishing excellence in a scale‘s content validity.(polit &beck,
2006)
Criterion-related validity
In criterion-related validity assessments, researchers seek to establish a relationship
between scores on an instrument and some external criterion. The instrument, whatever
abstract attribute it is measuring is said to be valid if its score correspond strongly with
score on the criterion.
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After a criterion is establish, validity can be estimated easily. A validity coefficient is
computed by using a mathematic formula that correlates scores on the instrument with
cores on the criterion variable. The coefficients (r) range between .00 and 1.00, with
higher values indicating greater criterion-related validity. Coefficients of .70 or higher are
desirable.
Sometimes a distinction is made between two types of criterion-related validity.
Predictive validity refers to an instrument‘s ability to differentiate between people‘s
performances or behaviors on a future criterion. When a school of nursing correlates
students‘ incoming high school grades with their subsequent grades-points averages,
the predictive validity of high school grades for nursing school performance is being
evaluated. Concurrent validity refers to an instrument‘s ability to distinguish among
people who differ in their present status on some criterion. For example, a psychological
test to differentiate between patients in a mental institution who could and could not be
relased could be correlated predictive and concurrent validity, and then is the difference
in the timing of obtaining measurement on a criterion.
Construct validity
Construct validity construct validity is a key criterion for assessing the quality of a study,
and construct validity has most aften been linked to measurement issues. The key
construct validity questions with regards to measurement are: ‗what is this instrument
really measuring?‘ and ―does it validly measure the abstract concept of interest?‖
Construct validity is essentially a hypothesis-testing endeavor, typically linked to a
theoretical perspective about the construct.
Construct validation can be approached is several ways, but it always involves logical
analysis and testing relationship predicted on the basic of firmly grounded
conceptualization.
One approach to construct validation is the known-groups technique. In this procedure,
groups that are expected to differ on the target attribute are administered the
instrument, and group scores are compared.
Another method involves examining relationship based on theoretical predition.
Researchers might reasons as follows: according to theory, construct X is related toconstruct Y; scales are related to each pther, as predicted by the theory ; therefore, it is
inferent that A and B are valid measures of X and Y. this logical analysis is fallible, but it
does offer supporting evidence.
Another approach to construct validation employs a statistical procedure known as
factor analysis, which is method for identifinf clusters of related items on a scale.
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Sensitivity and specificity
Reliability and validity are two most important criteria for evaluationg quantitative
instrument, but researchers sometimes need to consider other qualities. In particular, for
sscreening and diagnostic instruement—be they self-report, observational or
biophysiologic—sensitivity and specificity need to be evaluated.
Sensitivity is the ability of measure to identify a case correctky,that is, to screen is or
diagnosis a condition correctly. A measure‘s sensitivity is its rate of yielding ‗thru
positive.‖ Specificity is the measure‘s ability to identify noncases correctly thaht is to
screen out those without the condition.
The uses of data analysis
Once the researcher variables have been measured the resulting queantitative data can
be analyzed in a variety of ways, and the analyses can serve many different purposes.
The purposes can be categorized and illustrated along three difference dimensions, as
discuseed in the next sections.
Analyses for description versus inference
One of the most basic distinctions in statistical analysis is the difference between
descriptive statistics and inferential statistics.
Descriptive statistic al researchers want, at a minimum, to describe their data in a
convenient and informative manner.
Descriptive statistics which are used by researchers to describe and summarize data,
help to make data readily comprehensible.
Descriptive statistics can be communicated in three ways: in a narrative fashion, in a
graph, or in a table.
Inferential statistics Researchers typically derive their data by obtaining measurements
from a sample, that is, from a relatively small group of people with characteristics thatare relevant to the researcher question. However, researchers are almost always
interested in answering research questions about a population—the entire group of
people with the relevant characteristics —rather than about the particular individuals
compressing the sample.
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Inferential statistics use the laws of probability to help researchers draw conclusions
about population characteristics, based on information from samples. Most researcher
use statistics based on sample to address questions about a population, and thus
inferential statistics are widely used in research.
Inferential statistics are sometimes used to draw conclusions about a single populationvalue.
More frequently, inferential statistics are used to draw conclusions about the
relationship between variables in the population. A relationship is a bond or
association between variables. For example, the researcher might want determine
whether the average birth weight of aids babies is lower than the birth weight of other
babies. The relationship in question concerns birth weight(the dependent variable) in
relation to the infants‘ AIDS status(the independent variable).
Univariate, bivariate, and multivariate statistics
Univariate statistics involve two variable at a time. Example include the percentage of
men and women in the sample, or the average heart rate of the sample members.
Bivariate statictics involve two variables examined simultaneously. If the researcher
compared the average heart rate of men versus women, bivariate statistical procedure
would be used.
Multivariate statistics when tree or more variables ate included in the same analysis.
For example a researcher might use gender, weight, and amount of exercise to better
understand variations in heart rate.
Analyses for different purposes
A third dimensions for characterizing quantitative analysis concerns the role that the
analysis palys in the research process. Statistical analysis is typeically used for many
more purposes than simply to answer the researcher‘s substantive questions.here are a
few examples of different purposes for using statistical analysis:
1. Data cleaning. Typically, one of the firth things that a researcher does with a data
set(we are assuming that the researcher is using a computer for data analysis )
is to determine if the data are ―clean‖. Before the more substantive analyses canbegin, the researcher must have confidence that the number and codes entered
in the computer file are accurate.
2. Sample description. Researcher almost always want to learn the main
characteristics of their sample.
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3. Assessment of bias. Researcher often perform statistical analyses to determine if
there might be systematic biases that need to be taken into consideration in
interpreting the results of the substantive.
4. Evaluation of measuring tools in mant studies, the researcher undertakes
analyses designed to examine whether the measuring instrument used to collect
the data are reliable and valid.
5. Evaluation of the need for transformations. Data that are gathered by the
researcher often need to be transformed or altered before the substantive
analyses can proceed, and the use of descriptive statistics comes to the
researcher‘s assistance. The term missing values refers to the absence of
information for a specific variable for some of the subject, as a result of errors,
refusals, misunderstanding, and so on.
6. Addressing research questions. Finally, statistical analyses are used to directly
address the substantive research questions.
The data analysis plan
The prudent researcher endeavors to develop a realistic data analysis plan that guided
progress toward the goal of answering the researcher questions and interpreting the
results.
Introduction
The final phases of the research process entail decisions about communicating and
utilizing a study‘s findings. This chapter focuses on communicating research findings;
the research utilization process is described in chapter 17. Communicating a study‘sfindings—even findings from small-scale practice-based studies—is important for
several reasons. First and foremost, communicating research is the first step to
research utilization and evidence-based practice. Evidence-based practice is dependent
on researchers ―getting the word out‖ and making their study findings public so that they
can be evaluated as part of the body of evidence for practice decisions. In other words,
research-based evidence needs to be accessible in order to influence nursing practice.
Communicating research findings is important for another reason, in a vert real sense,
research is a public or community enterprise and all researchers have an obligation to
their sponsors, study participants and colleagues to share their findings. When aresearcher fails to communicate a study‘s findings, the time and talent of many people
are disregarded, trust can be undermined, and knowledge that could benefit patients,
nurses, the nursing profession, and society in lost. Most study‘s consent forms advice
potential participants that, while they may not benefit directly from study participation.
The knowledge gained will help others. This statement is frequently extended as a study
benefit to balance even minor risk such as discomfort, in convenience, and invasion of
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privacy. In a vert real sense, this statement constitutes an implicit contract that study
findings will be communicated. With this in mind, failure to communicate a study‘s
findings gas bees labeled a form of scientific misconduct (Winslow, 1996).
Finally, communicating a study‘s findings helps to make a project worthwhile. It provides
an opportunity to interact with other researchers and clinicians who are interested in thestudy problem and receive feedback on the study‘s methods and interpretation of
finding. Other researcher interested in the same problem will be able to reference your
work, learn from experience, and further extend the knowledge base about a problem
without reinventing the wheel.
Despite the importance of communicating study findings, in too many instances sudty
findings remain hidden and private. In fact, in 1995 hicks estimated that dewer than 3%
of nurse researchers actually communicate their study‘s findings in any sort of formal
way. Whole more recent data about nurses‘ publication activities are not available, it is
interesting to speculate whether this number has changed. Reasons documented byhicks for not communicating a study‘s findings still seem valid: lack of time. Lacks of
confidence in the quality of their study, lack of confidence in the ability publish or
present findings and lack of knowledge about opportunity and opinions for
communication study finding. This chapter addresses these barriers. The chapter
particulatly focuses on communicating findings from small-scale practice-based studies,
since these are the type of studies in which most baccalaureate-prepared nurses are
involed. Since nurses can—do—conduct these types of studies, they need to know how
to communicate their findings.
This chapter begins by considering some of the decisions that need to be made beforepackaging a study‘s findings. Next, steps in publishing a report of study findings,
presenting study findings and creating a research poster are described. The chapter
closes by sharing strategies for success that apply to any research communication
strategy.
Decision and options
Decisions about the focus of a report, intended audience, and most appropriate outlet
are interrelated and need to mesh with one another in order to effectively communicate
research findings and achieve the desired impact. Decision about the report‘s focushave implications for the appropriate audience and both of these decisions have
implications for the most effective communication outlet.
Decision #1 what to tell the first step in the research communication process is to
determine the report‘s focus. The decision affects both who w\to tell and how best to
reach them. When deciding on the focus of a research report, it is important to think of
research findings in the broadest since of the wood and consider sharing information
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about a study‘s processes and method, problem encountered and solution, as well as to
influence public knowledge, attitude, opinions, and policy. Additionally, information
about successful (and unsuccessful) research process contributes to the development
of scientific rigor in research and influence future nursing research endeavors. In other
words, a single research project contains many types of findings and offers many
opportunities to influence nursing and health care. In fact, most research projects can
generate at least three different types of reports: a summary of the problem background
and literature review, a report of study methods and lessons learned, and a report of the
study‘s results and their interpretation. decideing in the focus of a communication
project can be facilitated by identifying your goal or agenda for communication a study‘s
findings: do you want to create awareness of a situation, influence a change in practice,
stimulate debate and discussion, argue for a policy change, or share study findings for
the purpose of achieving personal recantation or reward of some sort?
In many studies, more data are collected than can be communicated in a single
report. A researcher will decide to develop a separate report for each research question.
If a study includes both quantitative and qualitative findings, these also will sometimes
be reported separately. To some extent this strategy makes sense , as different findings
may be of interest to different audeiences. It is important, however,to void simply
repackaging the same findings and communicating them in outlets. This practice, which
is referred to as self-plagiarsm, limits the number of different studies that can be made
available in scare journal and presentation space. In is considered unethical to
simultaneously submit essentially the same report to multiple journals. Some journals
will not accepts reports that have been presented at a widely attended national
conference. It is acceptable, however, to develop a multi-prong approach to sharingmultiple findings from a singke research study. For example a study‘s methodology
could be the focus of a report for nurse researchers and published in a journals such as
nursing research.in addiction, aposter or newsletter artcle could be developed for
clinicians or healrhcare consumers,and relevant findinfs could be reported in the form of
a letter or white paper tp policy makers
Decision#2 who to tell the decision about the intended audience for a research report
is influenced by the focus or content of the report: different stories are suited for
different groups. Choosing the riht(or best) audience for specific study findings involves
considering(1) who wants to know and (2) who need to know about a particular study‘sfindings. Consider the potential benefits of targeting research communication effort
toward the following audiences:
Clinicians can use information about research a outcomes to develop evidence-
based practice patterns.
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Nurse‘s researchers can use information about research method and study
results to conduct further research and add to the body of knowledge about a
problem area.
Nurses educators and administrations are potentially powerful agent for
research-driven changes in practice because of their responsibly for educating
nurses and managing nursing care delivery system.
Provides in other disciplines such as medicine and social work can use nursing
research finding to develop evidence-based practice patterns in ther own field
which facilitates interdisciplinary continuity of care for parents.
Consumers mat be motivated by nursing research findings to change behaviors
nursing research finding also can help consumers develop further understanding
about their illness and its management.
Consumers and legislators can use findings from nursing research to influence
health-related public policy.
Decisions#3 how to tell
Research findings can be communicated in written publications, as oral presentations,
or as poster presentations. The focus of a report and its intended audience has
implications for which strategy will be most effective. Written report, such as journal
articles, has the advantage of being accessible to the broadest audience. For nurses
working in academic settings, publishing findings in a journal, particularly a peer-
reviewed or refereed journal is considered the most prestigious and influential
communications strategy. Disadvantage of written reports, particularly reports submitted
to professional journals, include the lag time between study completion and publication
of findings(which often stretches to two years) and the fact that preparing a manuscript
for publication can be a very time-consuming process. Additionally, publishing in
professional journals in a competitive endeavor and there is simply not enough journal
manuscript development, there really are no costs associated with publishing findings
as written report.
Authorship issues
Since many nursing research project involve a team approach, nurse researchers oftenfind themselves facing issues related to authorship: specifically, who count as an author
and in what order multiple authors should be recognized .although authorship issues
can also arise with conference and poster presentations, they tend to be most apparent
and problematic when study‘s findings are being communicated(published) in written
form.
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Project planning
Once decisions have been made about the focus of the study report the intended
audience, appropriate communication outlet, and authorship issues, project planning
can commence. Project planning begins by assembling all of the materials that will be
needed to develop the manuscript, presentation, or poster.resources and artiles thatwere used to develob the resacrh problem and its background, data collection
instrument,consent forms,irb approval letters, interview transcripts, and computer
printouts of study results should be garhered and organized in the order in which they
will be used to develop the research report. For example,the first folder of materials
might be vopies of key articles that were used to develop the study;s problem statement
and literarure review, sice these are the firt section of an articles(or presentation or
poster). The second folder might be copies of data collection instruments and consent
form for the resus section, and so on. Int also is essential to secure the author
guidelines provided by the selected journals or presentation guidelines provided by
conference organizers so that the report can ve developed in the appropriate format.
Introduction
The overall purpose of nursing research is to generate knowledge that can be used to
guide nursing practice. This means that nurses must read critique, synthesize, and
replicate research finding, as well as apply and test the effectiveness of those findings
in practice. indeed, unless research findings are used to guide nursing practice research
is little more than a costly and time-consuming intellectual exercise. Understanding the
research process in the first step toward having an evidence-based practice and has
been the focus of this test book so far. This step is necessary so that you can identifyquality research studies and credible research findings. concesistent with the
expectation that baccalaureate –prepared nurses can ―apply research findings from
nursing and other disciplines in their clinical practice ―this chapter describes the
research unitization process. When research findings—rather than tradition, authority
,trial and error, or only logical thinking—are used to guide nursing decisions, the results
are higher quality care, improved patients outcomes, and decreased healthcare costs.
Patients and their families, healthcare agencies their practice. An evidence-based
practice also enhances the nursing profession‘s visibility and credibility bt demonstrating
its scientific based.
Like other activities in the research process, applying research findings to practice
settings requires critical thinking and careful decision making. The importance of critical
thinking in making a decision about a study‘s quality and implications of a proposed
innovation, the application of research findings can be inappropriate and ineffective—as
well as costly and even dangerous(settler, 2001). This chapter is intended to help you
develop the critical thinking skill that is foundational to research utilization.
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The chapter begins by comparing research utilization and evidence-based practice.
Next, the continuum of activities that comprise research utilization is described. The
next section of the chapter briefly summarizes three recognized and widely cited models
for research utilization. These models are then synthesized and widely cited models for
research utilization is presented. The chapter closes by describing barriers to research
utilization and suggesting strategies for developing a culture of research utilization.
Research utilization and evidence-based practice
Resech utilization refers to using research knowledge to change an existing clinical
practice or professional situation. Occasionally the knowledge may be from a single
isolated study; more typically, however, it is derived from a set a related studies (melnyk
& fineout-overholt, 2005). The knowledge is reviewed, disseminated, and applied to
specific practice problem or issue. In many instances, the impetus for a research
utilization project is suggestions made by a researcher in a research article‘s
discussions section (e.g., implications for practice).typical products of research
utilization project are new policies, procedure, or programs, or changes in routine
practice (melnyk & fineout-overholt, 2005).
Evidence-based practice differs from reseach utilization in that evidence from source
other than reserch studies is considered in the decision making process. In addition to
research findings, evidence based practice recognizes clinical experience expert
opinion,parients vales and preferences and clinical resources as valid and important
sources of evidence for evidence,skills beyod those needed to critique a single research
studt are required.
The research utilization continuum
Research can influence nursing practice directly my providing the impetus for making a
change in practice, or indirectly influencing personal understanding and approach to
patient interaction or serving as a catalyst for evaluation of a current practice. These
influences on clinical practice reflect instrumental, conceptual and symbolic utilization of
research findings.
Instrumental utilization
Instrumental utilization of research finding refers to the concrete application of research
findings, such as adopting an intervention that is described in the research literature
(settler, 1985). In other words, instrument utilization is an action-oriented application of
study finding to a cynical situation; it is a discrete and clearly identifiable attempt to base
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specific actions on research findings. Instrumental utilization includes the direct
application of a research-based intervention.
Conceptual utilization
Conceptual utilization refers to a research to a research-based change in one‘sunderstanding of a practice situation (settler, 1985). Conceptual utilization is the
cognitive application of research findings to one‘s personal clinical practice. Conceptual
utilization can be thought of as research-based enlightenment or change in
understanding or a new perspective that may lead to a change in one‘s personal
response pattern to a situation. Example of conceptual utilization includes the following:
Increased awareness of clinical problem, such as the incidence of a specific
condition or a treatment side effect, which could alter personal observation and
assessment practices.
Increased understanding of a subjectively experienced event or phenomenon,such as prenatal loss, a chronic illness, or being a victim of violence, which could
alter interactions with patients.
Increased awareness of environmental changes as well as new trends and
healthcare issues, such as the prevalence of MRSA (methicillin-resistant
staphylococcus aureus) infections, which could affect safely precautions taken in
personal practice.
Symbolc utilization
Symbolic utilization refers to using research findings to legitimize or call attention
to a current practice (settler,1985). More specifically, symbolic utilization means
using research findings as the basis for. Continuing current practices or as a catalyst
for evaluating current policies and practice. Symbolic utilization also can entail using
findings from a qualitative study to augment, validate, or illustrate quantitative
research in providing newborn care after taking part in a prenatal support program
might be used as a supplemental piece of evidence for a decision about continuing
the program.
Knowledge creep (settler, 1985) refers to the evolution or percolation of ideas for a
practice change.
Decision accretion refers to momentum for a change that evolves over time as
results of gaining additional information.
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Major steps in a quantitative study
In quantitative studies, researchers move from the beginning point of a study(the posing
og a question) to the end point( the obtaining of an answer) in a reasonable linear
sequence of steps that is broadly similar across studies.
Phase1 the conceptual phase
The early steps in a quantitative research project typically involve activities with a strong
conceptual or intellectual element. During this phase, researchers call on such skills as
creativity, deductive reasoning, and a grounding in existing research evidence on the
topic of interest.
Step 1:Formulating and delimiting the problem
Quantitative researchers begin by identifying an interesting, significant research
problem and formulating good research questions. In developing research questions,nurse researchers must pay close attention to substantive issues (in this research
question important, given the evidence base?)Theoretic issues (is there a conceptual
context for enhancing understanding of this problem?) clinical issues(could study
findings be useful in clinical practice?)methodologic issues(how can this question best
to answered to yield high-quality evidence? And ethical issues (can this question be
rigorously addressed in an ethical manner?).
Step 2: Reviewing the related literature
Quantitative research in typically conducted within the context of previous knowledge.
Quantitative researchers typically strive to understand what is already known about a
topic by undertaking a thorough literature review before any data are collected.
Step3: Undertaking clinical fieldwork
Researchers embarking on a clinical study often benefit from spending time in
appropriate clinical settings, discussing the topic with clinical fieldwork can provide
perspective on recent clinical trends, current diagnostic procedures‘, and relevant health
care deliver models; in can also help researchers better understanding clients‘
perspective and the settings in which care is provided.
Step 4: Difining the framework and developing conceptual definitions
When quantitative research is performed within the context of a conceptual framework,
the findings may have broader significance and utility even when the research question
is not embedded in a theory, researchers must have a conceptual rationale and a clear
vision of the concepts under study.
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Step 5: Formulationg hypotheses
Hypothesis state researchers expectations about relationship among study variavle.
Hypotheses are predictions of expected outcomes; they state the relationship
researchers expect to observe in the study data. The research question identifies the
concepts under investigation and asks how the concepts might are designed to testhypotheses through statistical analysis.
Phase 2: the design and planning phase
In the second major phase of a quantitative study, researchers make decisions about
the study site and about the methods and procedures to be used to address the
research question. Researchers typically have considerable flexibility in designing a
studt and make many methodological decisions. These decisions have crucial
complications for the integrity and generalizability of the study findings.
Step 6: Selecting a research design
The research design is the overall plan for obtaining answers to the questions being
studied and for handling various challenges to the worth of the study‘s evidence. In
designing the study, researchers decide which specific design will be adopted and what
they will do to minimize bias and enhance the interpretability of results, in quantitative
studies, research design tend to be highly structured and controlled. Research designs
also indicare other aspects of the research—for example, how often data will be
collected, what type of comparisons will be made, and where the study will take place .
the research design is the architectural backbone of the study.
Step 7: developing protocols for the intervention
In experimental research, researchers create the independent variable, which means
that participants are exposed to different treatment or conditions. An intervention
protocol for the study‘s would need to be developed, specifying exactly what the
intervention will entail(e.g who would administer it, how frequently and over how long a
period the treatment would last, and so on) and what the alternative condition would be.
The goal of well-articulated protocols is to have all subjects in each group treated in the
same way. In no experimental research, of course, this step is not necessary.
Step8: identifying the population
Quantitative researchers need to know what characteristics the study participants
should possess, and clarify the group to whom study results can be generalized – that is
they must identify the population to be studied. A population is all the individual or
objects with common defining characteristics. For example, the population of interest
might be all adult male patients undergoing chemotherapy in Dallas.
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Step 9: designing the sample plan
Researchers typically collect data from a sample, which is a subset of the population.
Using sample is clearly more practical and less costly than collecting data from an entire
population, but the risk is that the sample might not adequately reflect the population‘s
traits. In a quantitative study , a sample‘s adequacy is assessed by the criterion of representativeness ( I,e., how typical or representative the sample is of the population).
The sampling plan specifies in advance how the sample will be selected and how
many subjects there will be.
Step 10: specifying methods to measure variables
Quantitative researchers must develop or borrow methods to measure the research
variables as accurately as possible. Based on the conceptual definitions, researchers
select or design methods to operationalize the variable and collect their data. A variety
of quantitative data collection approaches exit; the primary methods are self reports(e.g., interview) observations(eg., observing children‘s behavior), and
biophysiologic measurements. The task of measuring research variables and
developing a data collection plan is a complex and challenging process.
Step 11: developing methods to safeguard human/animal rights
Most nursing research involves human subjects, although some involve animal. In either
case, procedure need to be developed to ensure that the study adheres to ethical
principles. Each aspect of the study plan needs to be scrutinized to determine whether
the rights of subjects have been adequately protected.
Step 12: Reviewing and finalizing the research plan
Before actually collecting data, researchers often perform a number of ―tests‖ to ensure
that procedures will work smoothly. For example, they may evaluate the tradability of
written materials to determine if participants with low reading skills can comprehend
them, or they may pretest their measuring instruments to assess their adequacy.
Researchers usually have their research plan critiqued ny reviewers to obtain
substantive, clinical, or methodologic feedback before implementing the plan.
Researchers seeking financial support submit a proposal to a funding source, and
reviers usually suggest improvements.
Phase 3 : The empirical phase
The empirical portion of quantitative studies involves collecting research data and
preparing the data analysis. The empirical phase is often the most time consuming part
of the study. Data collection may require months of work.
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Step 13: Collecting the data
The actual collection of data in a quantitative study often proceeds according to a
reestablished plan. The researcher‘s plan typically articulates procedure for training
data collection staff, describing the study to participants, the actual collection of
data(e.g, where and when the data will be gathered), and recording information.
Step 14: Preparing the data for analysis
Data collected in a quantitative study are rarely amenable to direct analysis. Preliminary
steps are needed. One such step is coding, which is the process of translating verbal
data into numeric form(e.g., coding gender information as ―1‖ for females and ―2‖ for
males). Another preliminary step involves transferring the data from written documents
onto computer files for analysis.
Phase 4: The analytic phase
Quantitative data gathered in the empirical phase are not reported as a mass of
numbers. They are subjected to analysis and interpretation, which occurs in the fourth
major phase of a project.
Step 15: Analyzing the Data
To answer research questions and test hypotheses, researchers need to analyzed their
data in an orderly, coherent fashion. Quantitative information in analyze though
statistical analyses, which include some simple procedure (e.g., computing an
average) as well as complex and sophisticated methods.
Step 16: The Dissemination phase
In the analytic phase, researchers come full circle: the questions posed at the outset are
answered. The researcher‘s job is not completed, however; until study results are
disseminated.
Step 17: Communicating the findings
A study cannot contribute evidence to nursing practice if the results are not
communicated. Another —and often final—task of a research project, therefore, is the
preparation of a research report that can be shared with others. We discuss research
reports in the next chapter.
Step 18: Putting the evidence into practice
Ideally, the concluding step of high-quality studies is to plan its use in practice settings.
Although nurse researchers may not themselves be in opposition to implement a plan
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for utilizing research findings, they can contribute to the process by developing
recommendations regarding how the evidence could be incorporated into nursing
practice, by ensuring that adequate information has been provided for a meta-analysis,
and by vigorously pursuing opportunities to disseminate the findings to practicing
nurses.