Week 5 Discussion: T-Tests and ANOVA in Clinical Practice

Nursing research is an important area that refreshes knowledge in nursing practice,
ensuring nurse practitioners used the most recent, advanced, and relevant information. Besides,
the findings of nursing inquiry can shape health policy and advance global healthcare. However,
scientific research is a complex process that starts with problem identification, progresses to
determine the study design and methodology and data collection, and ends with an analysis of
the collected data and interpretation of the results (Moule, Aveyard, & Goodman, 2016). Failure
to select appropriate data collection and analysis techniques can impair the validity and
reliability of the inquiry findings. Inferential statistics (such as ANOVA and t-test) are often
needed to address validity and reliability issues (Gray & Groove, 2020). Inferential statistical
methods allow researchers to draw conclusions and extrapolate outcomes to real-life nursing
scenarios.
In that regard, this discussion seeks to analyze Gray & Kim’s (2020) study through the
lens of scientific inquiry by examining the purpose, sample, sources of data, inferential statistics,
findings, and the impact inferential statistics have on the applicability of the results to evidence-
based practice.

Purpose

In the study, Gray & Kim (2020) examine the training needs and experiences of direct
care workers (DCWs) involved in caring for individuals suffering from developmental and
intellectual disabilities. For the sake of the study, these patients are referred to as PWIDD or
people with intellectual and developmental disabilities. The term palliative care refers to the
holistic approach to alleviating pain and suffering among terminally ill patients experiencing
excruciating pain or extreme sorrow. The idea is to lower suffering and provide the best quality

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of life for these individuals. Usually, direct care workers are involved in the care of PWIDDs
when their developmental and intellectual abilities decline dramatically.

Study Sample

A total of 149 direct care workers trained in PWIDD were selected in seven community-
based (not-for-profit) institutions in the rural and suburban neighborhoods in a Midwestern state
in the United States. The organizations were identified through convenience sampling. The
workers recruited for the survey either presently serving as DSPs (direct support professionals)
or those that previously served in the same capacity or managerial or supervisory position but
with training in DSP were recruited.

Sources of Data

The 149 participants filled self-administered survey questionnaires, including both online
(n = 31; 21 percent) and hard copy (n = 118; 79 percent). The research team “physically” visited
those that preferred paper-based surveys. Those that preferred online surveys provided their
emails to the research team, who then emailed them back with a link to the survey. The survey
comprised of three parts: palliative-care related data like palliative care education and training
needs and previous training skills; work-related and demographic; such as education level,
gender, age, job title, race/ethnicity; and preferred training approaches in terms of delivery
technique, length, and format.

Inferential Statistics Used in Data Analysis (t-test or ANOVA)
The researchers used a range of inferential statistics to analyze data, including non-
parametric methods (such as chi-Square tests, Fisher’s exact tests, Pearson’s correction, and
Scheffe’s tests) and parametric approaches, including ANOVA and t-test. Specifically, ANOVA
and t-tests measured the differences in the main result scores by race, location, and job title. T-

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tests and chi-square tests were also used to examine the difference in internet access and sample
characteristics by location (suburban vs. rural). Parametric inferential statistics (t-tests and
ANOVA) are preferred to non-parametric ones when sample sizes are greater (n > 30). Besides
inferential statistics, the researchers also measured test variables using means and percentages.

Findings

Regarding perceived training needs and previous training, the researchers found that
logistics after a patient’s death to be the least trained area at 30.2 percent. Other least-trained
dimensions included PWIDD’s unique hospice needs (38.3 percent) and advance directives (35.6
percent). The highest ‘trained areas’ were coping skills (73.2 percent), grief stages/patterns (76.5
percent), and training on Alzheimer’s disease/dementia (69.8 percent). The findings also found a
high perceived training need, with 70-80 percent of participants still expressing the desire for
more training in PWIDD. Additionally, experiences in palliative care differed by job title
(ANOVA p<0.05). Rural area participants also reported less palliative care training (t-tests
p<0.0005) and experience (t-tests p<0.05).
Purpose and Value of the Study to the Topic and Whether Using Inferential Statistics
Strengthened or Weakened the Study’s Application to Evidence-Based Practice
The study outcomes provide an invaluable pool of knowledge to the care of PWIDD,
highlighting DCW training gaps and specific areas that educators must focus on. Besides these
training needs, the study outcomes also demonstrate that stakeholders must prioritize training in
rural/remote regions. Indubitably, whereas descriptive statistics (percentages and means) give
comparable figures, ANOVA and t-tests (p-values) allow researchers to determine whether or
not the means of two groups are statistically significant. For example, Gray & Kim found that
direct care workers (rural vs. suburban) experiences differed by job position/title (ANOVA

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p<0.05). The use of these inferential statistics strengthened the application and extrapolation of
the study outcomes to the topic. For example, this p-value shows that the rural vs. urban
comparison of experiences of direct care workers in PWIDD by job titles is statistically
significant.

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References

Gray, J. A., & Kim, J. (2020). Palliative care needs of direct care workers caring for people with
intellectual and developmental disabilities. British Journal of Learning Disabilities,
48(6), 69-77. doi:10.1111/bld.12318
Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research:
Appraisal, synthesis, and generation of evidence (9 th ed.). Elsevier.
Moule, P., Aveyard, H., & Goodman, M. (2016). Nursing research: An introduction. SAGE.