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How can a clinical practitioner distinguish between good research and bad research?

How can a clinical practitioner distinguish between good research and bad research?

How can a clinical practitioner distinguish between good research and bad research?
HLT 490 Distinguishing Good Research and Bad Research

There are so many ways to find information. Technology has opened the doors such that one can read another’s dissertation from across the globe. There are experts who disagree with each other and yet have evidence to back up their arguments. How can a clinical practitioner distinguish between good research and bad research?

The major criteria used to evaluate scientific research are grouped under the headings “reliability”
and “validity.” Reliability is the degree to which a measure is free of measurement error. It is typically
assessed by looking at the consistency of a measure. For example, a reliable weight scale will produce a
consistent weight estimate for the same object over time. A reliable measure of playground aggression
will produce consistent aggression estimates for the same child across several observers. There are
several types of validity, and each refers to the confidence you can have in making certain conclusions.
We will discuss each in greater depth in the section on validity, but they are presented here to begin
familiarizing you with them.
Internal Validity
Internal validity is the confidence you can have in making cause-and-effect conclusions from
the results of your study. For example, let’s say you want to determine whether smoking cigarettes
causes lung cancer. The problem is that there are many possible causes of lung cancer – exposure to
environmental toxins, genetic predispositions, etc. A study has internal validity to the degree that it is able
to control these alternative causes and conclude that one factor alone (in this case smoking) produced an
effect. We will discuss how this is done in the sections on validity and experimental design.
External Validity
External validity is the confidence you can have in generalizing the findings of your study to
people, settings, and times not included in your study. Concerns about external validity are generally
concerns about the sample used in a study. If you learn that a sample was all-male or all-college-student
or all-White, you may have doubts about how well the results would generalize beyond those populations.
Construct Validity
Construct validity is the confidence you can have that the theoretical constructs you are
attempting to represent in your study (e.g., time pressure, anger) are accurately represented by your realworld methods. For example, let’s say you are conducting an experiment in which one group is supposed
to feel more time pressure than another. This could be done with poor construct validity, for example by
telling one group that they should feel rushed, or it could be done with better construct validity, for
example by giving students a test that is supposed to measure their potential for success and not giving
them enough time to finish each section before forcing them to move on.
Types of Research
Quantitative and Qualitative Research
Quantitative
In research that is quantitative, observations are transformed into codes according to some
consistent set of rules. For example, the “ambitiousness” of Presidential inauguration addresses could be
rated by several people using a 1-10 scale. A child’s reaction to his or her mother’s departure could be
categorized as “securely attached” or “anxiously attached” based on certain well-specified behaviors. The
essential feature of quantitative research is the existence of these codes, whether they are categorical
(e.g., attachment style) or numeric (e.g., ambitiousness), and the existence of a set of rules for using the
codes.
Advantages. There are three major advantages of quantitative methods: reliability, falsifiability,
and replication. The first advantage of transforming observations into codes is that it becomes possible to
evaluate the reliability of the measure you are using. If the same child is consistently categorized as
anxiously attached by different observers on different occasions, then we can have more confidence in
the measure of attachment style. Without a coding system, there is no objective method of comparing the
observations of multiple observers or of the same observer on multiple occasions. Thus, quantitative
by Bill Altermatt, last updated 1/3/2008
Evaluating Research, Types of Research page 2
methods permit us to detect and disregard unreliable measures. The second advantage is that it is much
easier to design a falsifiable study with quantitative methods. If our data have been coded as numbers,
we might expect the average for two groups to differ: the average ambitiousness of wartime Presidents
could be predicted to be higher than the average ambitiousness of peacetime Presidents. If our data
have been coded as categories, we might expect a greater abundance of one category in one group than
in another (e.g., a greater percentage of anxiously attached children in families with divorced parents than
in families without divorced parents). These hypotheses are easily tested in a manner that could either
support or disconfirm them, thus they are falsifiable. Finally, quantitative studies are easier to replicate
because later researchers can simply adopt the explicit coding systems described by the original
researchers.
Disadvantages. The major disadvantages to quantitative research are that 1) it presumes a
considerable degree of understanding of the phenomenon of interest and 2) it may neglect aspects of the
phenomenon that are unexpected. First, quantitative research presumes that the researcher understands
a phenomenon well enough to reliably measure it. For new or rare phenomena, this may be unrealistic.
For example, how do we code the visual hallucinations experienced by someone with a rare brain
trauma? The second disadvantage is that the coding system you select may neglect some important
aspect of the phenomenon. For example, you may be studying schoolyard bullying when you
unexpectedly witness one child humiliate a child in front of their peers and then console that child when
they are alone. It is very likely that your coding system has no code for this pattern, yet it could be very
important.

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HLT 490 Distinguishing Good Research and Bad Research
HLT 490 Distinguishing Good Research and Bad Research

Appropriate when: testing a hypothesis. Quantitative measures are appropriate for situations
where you have sufficient control to reliably measure the phenomenon you are interested in and sufficient
background knowledge to competently formulate a hypothesis.
Qualitative
Before contrasting quantitative research with qualitative research, it is worth noting that there is
widespread disagreement in how the words “qualitative” and “quantitative” are used with regard to
research. Quantitative is sometimes interpreted as “using numbers” while qualitative is “using categories”
(e.g., anxious, secure). As discussed above, I prefer to group these together under the single heading
“quantitative.” The reason for this is that there is a more profound difference in how research is
conducted that is not captured by the simple numbers vs. categories distinction. According to my
definition, qualitative research involves observations that are transformed into records based on the
observer’s intuitive sense of what is important. Some examples include: an anthropologist describing the
folkways of an unusual culture, a neurologist describing the symptoms of a rare disorder (an example of a
case study), or an ethologist describing the activities of a chimpanzee troop.
Advantages. The major advantage of qualitative research is that it can provide a very rich
description of a phenomenon, including not only detail of the phenomenon but also extensive detail about
the context in which the phenomenon was observed. Whereas quantitative research tends to take a more
narrow focus to answer a particular question, qualitative research tends to take a broader perspective to
describe a particular phenomenon. It is also possible that the description generated by qualitative
research may capture rare events that would be unlikely to be considered in a coding system.
Disadvantages. The major disadvantages of qualitative research are the mirror images of the
advantages of the quantitative approach: difficult to determine reliability, difficult to falsify, and difficult to
replicate. Two anthropologists may differ markedly in their interpretation of the same culture, but with no
coding system it is very difficult to estimate the degree of (un)reliability in their assessments. The lack of
coding system also makes replication very difficult. Falsifiability is jeopardized because observers’
intuitions may lead them to seek out, notice, interpret, and remember events that are consistent with their
expectations – the confirmation bias. Although quantitative research is also vulnerable to the
confirmation bias, its vulnerability is reduced by a more explicit separation of observations and
interpretations.
Appropriate when: the goal is description or when a phenomenon is new or rare. Qualitative
descriptions of events are very useful when the events are relatively new or rare, such as the three
examples cited earlier of the anthropologist, neurologist, and ethologist. Qualitative research is
inappropriate for testing hypotheses because it does not have sufficient means of controlling bias.
by Bill Altermatt, last updated 1/3/2008
Evaluating Research, Types of Research page 3
In naturalistic observation. Researchers using naturalistic observation frequently use qualitative
methods to interpret their data. To reduce the risk of spurious interpretations, these researchers rely on
multiple confirmations of a phenomenon and negative case analysis to explain anomalies. First,
researchers must have multiple confirmations of a phenomenon (e.g., Moore’s (1985) observation of
women initiating flirting by flipping their hair) before they identify it as a phenomenon. Second,
researchers who identify a consistent pattern but witness a “negative case” (an inconsistency in the
expected pattern) must attempt to explain that inconsistency in a process called negative case analysis.
Basic and Applied Research
A distinction is sometimes made between research that is “basic” and research that is “applied.”
Applied research is directed toward the solution of a particular problem. A lot of research on mental
illness is applied because it is directed toward the treatment or cure of mental illness. In contrast, basic
research is directed toward understanding the fundamental nature of a phenomenon. For example,
research on the role of neurotransmitters in attention could be considered basic research. Basic research
is sometimes criticized because the usefulness of its results may not be immediately apparent. With time,
however, basic research can often be applied to a particular problem. Schizophrenia involves both
problems with neurotransmitter levels and with attention, so basic research on these issues could help to
solve the problem of how to treat schizophrenia.

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