NRS 493 Topic 4 Professional Capstone and Practicum Reflective Journal GCU

NRS 493 Topic 4 Professional Capstone and Practicum Reflective Journal GCU

NRS 493 Topic 4 Professional Capstone and Practicum Reflective Journal GCU

Students are required to submit weekly reflective narratives throughout the course that will culminate in a final, course-long reflective journal due in Topic 10. The narratives help students integrate leadership and inquiry into current practice.
This reflection journal also allows students to outline what they have discovered about their professional practice, personal strengths and weaknesses, and additional resources that could be introduced in a given situation to influence optimal outcomes. Each week students should also explain how they met a course competency or course objective(s).
In each week’s entry, students should reflect on the personal knowledge and skills gained throughout the course. Journal entries should address one or more of the areas stated below.  In the Topic 10 graded submission, each of the areas below should be addressed as part of the summary submission.

New practice approaches
Interprofessional collaboration
Health care delivery and clinical systems
Ethical considerations in health care
Practices of culturally sensitive care
Ensuring the integrity of human dignity in the care of all patients
Population health concerns
The role of technology in improving health care outcomes
Health policy
Leadership and economic models
Health disparities

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While APA style is not required for the body of this assignment, solid academic writing is expected, and in-text citations and references should be presented using APA documentation guidelines, which can be found in the APA Style Guide, located in the Student Success Center.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
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NRS 493 Topic 4 Professional Capstone and Practicum Reflective Journal GCU

In nursing research, the evaluation of evidence is a vital aspect when it comes to decision
making and the development of evidence. This is because the evaluation of evidence gives rise to
the evidence that will aid in the decision making. That said, there are two major ways of
evaluating evidence. The first way is the qualitative method. Qualitative evaluation of data
occurs when data has been deleted qualitatively through either direct or participant observation,
review of literature, focus groups, case studies and interviews (Marston et al., 2020). Qualitative
evaluation of data entails exploring and examining. the data collected, comparing and contrasting
the ideas and then eventually, interpreting the patterns arising from the data collected. This data
is however evaluated using non-numerical methods and thus, some of the strategies that are used
are usually thematic evaluation and content evaluation of the data where the data is evaluated
based on the themes present, or the content within the sources of data. This model of evaluation
has however been associated with certain shortcomings, key among them being that it is purely
subjective as it is not statistically grounded. Furthermore, the data generated may be skewed as
interpretation relies on the experience of the researcher. However, qualitative evaluation methods
have a range of strength as well, including the fact that research topics can be examined in great
detail and this arises due to the fact that the interviews are not restricted. to specific questions.
Furthermore, as new information emerges qualitative evaluation is flexible and it allows for
changes in methodology and direction.
The second mode of evaluation is quantitative methods and these are methods that are hinged on
the statistical assessment of data. Here, data is collected and coded in numerical forms and his
then paves way for data analysis. This analysis is also conducted quantitatively and this means
that the output is in numerical form as well (Smith & Hassan, 2020). Quantitative evaluation of
data is usually conducted in certain ways. First, there is the relation of measurement of data
scales with variables. For instance, data scales can be used to determine the correlation between
data, in addition to potential cause and effect relationships between the data available. On the
other hand, the quantitative data may also be used to understand the sample and this is through
descriptive statistics (Palinkas et al., 2019). The major shortcoming of this method is that it
places extensive focus on numbers because it is limited to the pursuit of concrete and statistical
relationships. As a result, researchers may ignore relationships and themes that are broader.
Furthermore, qualitative evaluation is inflexible. There is no room for research design and
models. As a result, the researcher has to be immensely careful when developing both the mode
and the hypothesis, as any mistakes made cannot be adjusted and this will ultimately lead to the
invalidation of the data. Finally, quantitative research can be misled and this is because of the
assumption that statistical evaluation methods are more credible than observational ones.
However, the main strength of this research is that it can be tested and checked, making it easier
for other researchers to replicate the data. Furthermore. The methods of analysis are similarly

Marston, C., Arjyal, A., Maskey, S., Regmi, S., & Baral, S. (2020). Using qualitative evaluation
components to help understand context: case study of a family planning intervention with female
community health volunteers (FCHVs) in Nepal. BMC health services research, 20(1), 685.
Palinkas, L. A., Mendon, S. J., & Hamilton, A. B. (2019). Innovations in Mixed Methods
Evaluations. Annual review of public health, 40, 423–442.
Smith, J. D., & Hasan, M. (2020). Quantitative approaches for the evaluation of implementation
research studies. Psychiatry research, 283, 112521.

Ayda Nahorai
replied toCoraline Powell
May 8, 2022, 4:23 PM
Replies to Coraline Powell
Hi Coraline
One of the factors distinguishing qualitative from quantitative studies is the nature of the
intended outcome. Qualitative researchers seek to learn from details of the testimonies of
those they are studying, also called their informants. Over the course of a study,
conclusions are drawn by compiling, comparing, and evaluating the informants’ feedback
and input. Qualitative research is often focused on answering the “why” behind a
phenomenon, correlation, or behavior.
In contrast, quantitative data are analyzed numerically to develop a statistical picture of a
trend or connection. Such statistical results may shed light on cause-and-effect
relationships. They may either confirm or disprove the study’s original hypothesis.
Whether positive or negative, the outcome can spark awareness and action. Quantitative
research is often focused on answering the questions of “what” or “how” in regards to a
phenomenon, correlation, or behavior.
Hoover, L., (2021)What Is Qualitative vs. Quantitative

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