Stratford University Sampling Strategy Research Paper

Develop
your own sampling strategy based upon your PICOT question. Read your
text book and identify how you will approach the sampling strategy by
understanding what the following means. a) parameters or attributes of the study population, b) representative of the defined population, c.appropriateness of the sampling plan to the research design, d) appropriateness and justification of the sample size, and e)evidence that the rights of human participants (subjects) have been protected.

After
reading and understanding what the above means, answer the questions
below regarding the sampling strategy you will use based on your PICOT
question. Support why you chose those answers with evidence-based
literature. Provide both in-text citation and a reference list.

The aim of the cosmic question you propose should
enable others to critique your sampling strategy.

Initial Post Due: Respond to 2 peers by: Saturday 11-13-21 by 23591

Response 1

My own sampling strategy is randomization
using excel. My PICOT questions deals with comparing the effectiveness
of hourly rounding versus routine falls prevention (environmental survey
and side rails). I wanted to know which of these interventions is more
effective. The target population I am envisioning are patients at risk
for falls. I am looking to recruit 70 subjects. 35 of which will be
randomly assigned to the intervention group (hourly rounding) while the
other 35 will receive the comparison group (routine falls prevention).

The inclusion criteria are geriatric
population (65 years of age), those diagnosed with osteoporosis, those
who are taking multiple antihypertensive medications which can cause
dizziness and orthostatic hypotension, those who have mobility problems
and those who are in complete bed rest. The exclusion criteria are
patients with cognitive issues such as (delirium and dementia) and other
psychiatric diagnosis.

The sampling strategy that I will use
is excel. I can use this by using the data analysis toolkpak feature in
Microsoft excel. I will use RAND function to generate random numbers
between 0 and 1. Then from there, I can sort the cells according to the
random numbers. I chose random sampling because it is free of bias and
when using excel, it is very convenient to do and easy to execute
without the need for consulting a statistician. There are factors that I
consider when determining the sample size. I am looking to use power
analysis.

Calculating power analysis can help me determine the
minimum sample size that I should use for a more valid ad reliable
finding (Dario & Picho, 2016). To do this, I need to know the
population means of the two groups as well as the population standard
deviation of the two groups. I will use SPSS sample power tool to carry
this out. For example, in my first group, I will set the population mean
of 5 and standard deviation of 2.5 and for the comparison group, the
population mean will be set to 3 and 2.5 as the standard deviation.

To
get a power of 91% I need to have a minimum sample size of 35 per
group, with a total of 70 for the entire population. Some of the
potential threats to internal and external validity. Some of the
possible threats to internal validity is attrition as some of the
participants may choose to drop out of the study. Also, social
interaction between participants during the course of the study may
negatively affect internal validity (Patino & Ferreira, 2018).
Threats to external validity include Hawthorne effect when the
participants who receive the hourly rounding and the routine falls
prevention may choose to change their behavior because they know they
are being studied.

References

Dario,
T., & Picho, K. (2016). Threats to Internal and External Validity in
Health Professions Education Research. Journal of the Association of
American Medical Colleges, 91(12), 21. doi: 10.1097/ACM.0000000000001446

Patino, C., Ferreira, J. (2018). Internal and
external validity: can you apply research study results to your
patients? Journal Brasileiro de Pneumologia, 44(3), 183. doi:
10.1590/S1806-37562018000000164

Response 2

PICOT/Research
Question: In adult patients 85-year-old and older diagnosed with
coronary artery disease, is aspirin a more effective agent than heparin
in reducing the risk of stroke?

Target Population and Sample

The
target population for the evidence-based project is older adults
(85-years and above) with coronary disease using aspirin or heparin as a
means to manage the condition. Older adults have been targeted since
they have a higher prevalence of contracting a coronary disease, which
can lead to other conditions. Aspirin therapy is considered a lifesaving
option, but it is not for everyone. Thus, patients need to have the
facts before considering the medication. Taking aspirin helps in
lowering the risk of heart attack and stroke, but its intake is not for
everyone. Factors determining aspirin intake depend on patient age,
history of heart disease, overall

health, and risks of
experiencing a future stroke or heart attack. On the other hand,
intravenous heparin is considered as effective as aspirin when it comes
to the prevention of new cardiac events after experiencing unstable
coronary artery disease. This evidence-based project will investigate
whether aspirin is effective as intravenous heparin for older patients
with CAD in preventing the occurrence of stroke. A sample of 135 older
patients taking aspirin and heparin will be investigated.

Sampling Approach

In
the evidence-based project, the researcher will use a randomized
controlled trial or RCT. This sampling method entails a way of doing
impact assessment in which the population that receives the program or
policy intervention is randomly selected from the entire eligible
population (White, 2017). Moreover, a control group has to be selected
randomly from the same eligible population. In the case of RCT, the
policy of the program is considered as an “intervention” where the
treatment (the elements of policy or program being assessed) is examined
for its capacity to attain its objectives, as in the measure of a
predetermined set of indicators. The advantage of using RCT is that the
approach offers a powerful response to questions, where evaluators and
program implementers are helped to understand what has attained results
from the intervention. One of the differentiating features of the RCT is
the aspect that random assignment of the population eligible for the
treatment is to either one or more treatment groups (those receiving the
intervention variation or treatment) or the control group (those
receiving no intervention or usual intervention, in case treatment, is
an innovation of prevailing intervention).

The sampling approach
of RCT is appropriate in various ways. The approach has to be planned
from the start of program implementation and program participation which
has to be controlled with experiment (White, 2017). Besides, the RCT
approach necessitates the use of a large sample size. The sample size
has to be large enough to have the capacity to detect the program
effects. Moreover, RCTs must be undertaken considering the formative
evaluation or research. In addition, RCT has to be appropriate and
relevant to the program nature being evaluated.

The disadvantage
of RCT is associated with the feasibility or the cost that fails to
last long enough to determine the aspirin effects. Besides, RCT can be
applied to non-pharmacological interventions and recruitment.

The
ethics of the sampling approach relates to the idea that external
validity or representativeness tends to be too controlled to be
generalized.

Other advantages of the sampling approach are that
RTC enhances the capacity to answer specific and broad questions. The
method is associated with internal validity. The approach of randomness
and blinding lower the level of bias and confounding. Finally, the use
of control is crucial for the attainment of trusted results (Schmidt
& Brown, 2017).

Inclusion Criteria

Entail attributes
of subjects are considered crucial for selection or participation. In
this evidenced-based project, inclusion criteria are:

CAD patient in the induction phase

Age above 85 years

MI

Exclusion Criteria

Entail
attributes of subjects that are crucial for the selection of
respondents to take part in a project. In the present evidenced-based
project, some of the exclusion criteria are;

Patients in need of third-line medications

Aged below 85 years

Patients on ventilator support

Retro-positive patients

Factors determining the sample size

In the evidence-based project, the sample size will be determined by the following factors;

The confidence levels

The margin of error

The percentage or proportion of the sample that will have to select a given answer to the survey questions

Potential threats to internal and external validity as sources of sampling bias

Some
of the threats to internal validity as a source of sampling bias are
instrumentation, selection bias, testing, social attrition, and
interaction, history, regression to the mean, and maturation.

On
the other hand, some of the threats to external validity as a source of
sampling bias are experiment effect, history, selection bias, testing
effect, situation effect, and aptitude-treatment (Schmidt & Brown,
2017). Also, it is difficult to deal with the issue of generalizability
as it demonstrates that the researcher has assumptions that other
populations are similar to the one being tested. Moreover, participants
in the research might not cooperate with every procedure.

What is your cosmic question (question asked to peers to respond to based on chapter discussed i.e., sampling strategy?

Apart from the random sampling approach, what other sampling strategy can be used for the study?

References

Schmidt,
N. A., & Brown, J. M. (2017). Evidence-Based Practice for Nurses:
Appraisal and Application of Research: Appraisal and Application of
Research. Jones & Bartlett Learning.

White, A. H. (2017).
Using samples to provide evidence. Evidence-Based Practice for Nurses:
Appraisal and Application of Research: Appraisal and Application of
Research, 285.