This week, you will be submitting a data analysis plan for your research proposal. Share your research questions and research project as well as your anticipated type of quantitative analysis with the class. What quantitative test/s are you going to conduct on your data (t-test, correlation, chi-square, regression, ANOVA, ANCOVA, etc.) and explain why you feel this is the best test.
Research Questions
1. What are the perceived effects of mindfulness-based interventions (MBIs) on stress levels
among nurses working in Intensive Care Units (ICUs)?
2. How do ICU nurses perceive the feasibility and acceptability of integrating MBIs into
their daily routine?3
3. What are the potential barriers and facilitators to successfully implementing MBIs for
stress reduction in ICU nursing staff?
ResearchProposalProject_Design.pdf
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Research Proposal Project: Design
Cristina Lopez
NURS540
03/31/2024
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The research proposal focuses on employing mindfulness-based interventions to reduce
stress among ICU nurses. Stress causes burnout and job dissatisfaction among ICU nurses. MBIs
may lower stress, improve sleep, minimize burnout, and increase self-compassion among
healthcare professionals, especially ICU nurses, according to research. This section discusses
sampling, reliability, and validity to ensure study credibility and validity. Sampling information
will contain demographics, sample size, and selection criteria. The consistency and dependability
of the data gathering procedure and measurement instrument will be examined. Additionally, the
research’s validity will be tested, including the sample and measuring equipment. These factors
will be extensively examined to provide the groundwork for studying MBIs’ effects on ICU
nurses’ stress and well-being, improving critical care patient care.
Sampling Information
ICU nurses from different healthcare institutions will be sampled for this research,
ranging in age, gender, and experience. ICU nurses who have worked in critical care for at least a
year will be included in the research. The sample size will be based on statistical power analysis,
aiming for a large sample to discover important effects while considering time and resource
restrictions. Correct statistical procedures will be used to calculate sample size for statistical
power. Relevance to the research topic and aims makes the sample suitable for the study. ICU
nurses are suitable for studying the stress-reduction effects of mindfulness-based therapies
because they are immediately exposed to the high-stress situation. The inclusion of nurses from
different demographics and experience levels will further improve the study’s generalizability to
ICU nurses. The chosen sample is well-suited to fulfill the study goals and provide useful
insights into MBIs’ stress-reduction effects on ICU nurses.
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Reliability
Several methods will ensure data collecting reliability. To ensure data collecting
consistency, standardized processes will be created and executed. To reduce data collecting
variability, research assistants and participants will get explicit instructions. Staff will also
receive frequent training on data collecting tools and methods to ensure they can accurately
administer assessments and record data. Data will be collected at consistent times and under
similar settings to reduce extraneous variables that could affect measurement results. Periodic
inter-rater reliability tests will verify data collection consistency between observers or raters to
improve reliability. The ICU nurse stress assessment instrument will undergo comprehensive
psychometric validation to ensure reliability. Izah et al. (2023) will analyze internal consistency
using Cronbach’s alpha coefficient, which measures instrument item correlation. Test-retest
reliability shows measurement stability by giving the same people the instrument twice and
comparing their responses (Soltani et al., 2023). To improve reliability, the measurement tool’s
validity will be evaluated to verify it measures the construct of interest. The study uses rigorous
data collection methods and trustworthy measurement devices to provide consistent and accurate
data to evaluate mindfulness-based therapies for ICU nurses’ stress.
Validity
Verifying sample validity assures population representation and research aims. Determine
which ICU nurses are directly exposed to the high-stress situation under study. Participants’ job
and critical care experience will be confirmed to ensure study relevance. Generalizability will be
improved by recruiting a diverse age, gender, and experience sample. Selecting participants from
multiple hospitals reduces sample biases and avoids overreliance on one. Complete psychometric
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testing will evaluate the tool’s ICU nurse stress measurement validity. Content and face validity
will be checked to ensure that the instrument’s items accurately represent the topic and that target
participants find it relevant and understandable. Comparing the measurement instrument to
validated questionnaires or clinical stress assessments will assess construct validity (Roy et al.,
2023). The measuring tool’s scores will be compared to ICU nurses’ self-reported symptoms or
objective stress outcomes to determine contemporaneous and predictive validity. Mindfulness-
based therapies’ stress-reduction benefits on ICU nurses will be rigorously investigated to assure
sample selection and measurement validity.
Conclusion
Mindfulness-based interventions (MBIs) may lower ICU nurse stress, according to one
study. This study reviewed relevant literature and considered sampling, reliability, and validity to
find that MBIs may increase ICU nurses’ well-being. The initiative targets a large sample of
nurses and uses strong data collection methods to verify that MBIs reduce stress and improve
mental health in critical care providers. Beyond nurse well-being, these findings may alter
intensive care patient treatment. By integrating mindfulness into nursing practice, healthcare
organizations can minimize ICU nurse stress and burnout, improving work conditions and
patient outcomes.
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References
Izah, S. C., Sylva, L., & Hait, M. (2023). Cronbach’s alpha: A cornerstone in ensuring reliability
and validity in environmental health assessment. ES Energy & Environment, Volume 23
(March 2024) In Progress(0), 1057. https://www.espublisher.com/journals/articledetails/
1057
Roy, R., Sukumar, G. M., Philip, M., & Gopalakrishna, G. (2023). Face, content, criterion and
construct validity assessment of a newly developed tool to assess and classify work–
related stress (TAWS– 16). PLOS ONE, 18(1), e0280189. https://doi.org/10.1371/
journal.pone.0280189
Soltani, T., Flynn, J. M., Ang, D., & Cendán, J. (2023). Reliability study. Elsevier EBooks, 261–
265. https://doi.org/10.1016/b978-0-323-90300-4.00104-x
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