Study on the Implementation of RNAO Best Practice Guideline

A STUDY ON THE IMPLEMEMENTATION OF RNAO BEST PRACTICE GUIDELINE
A STUDY ON THE IMPLEMEMENTATION OF RNAO BEST PRACTICE GUIDELINE
Name of the Student:
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A STUDY ON THE IMPLEMEMENTATION OF RNAO BEST PRACTICE GUIDELINE
Executive Summary
The Registered Nurses’ Association of Ontario (RNAO) delightfully presents their
clinical best practice guideline: Delirium, Dementia and Depression in Older Adults: Assessment
and Care. A group of researchers wants to investigate the implementation of this guideline in a
non-teaching hospital in South Ontario. They collected demographic data on the nursing staff.
There were 80 nurses on the unit. However the participation in the study was voluntary and
confidential; therefore, not all of them were eligible for the study. A sample of 60 nurses is taken
here for this case. The descriptive study shows that there are 46 female and 14 male nurses in the
study. Maximum nurses belong to the age group 36-54 years depicting the fact that the hospital
is more interested in recruiting experienced nurses. The correlation coefficient between the
variables perceived value of patient wishes in adaptation of best practice and authoritarian score
is 0.78 which indicates a strong positive correlation. This implies that if the patients are enough
convinced about the best practice guideline, then they will highly cooperate with the system.
Then a dependent sample t-test is conducted to find if there is any difference in opinion towards
change due to gender (Benjamin et al., 2018). The test result shows that the reaction score to the
change in hospital environment is independent of gender. Further a One-way ANOVA test is
conducted which shows that there is no difference in opinion of nurses belonging to different age
groups. However, the study shows that the nursing staff is dominated by females. Therefore the
results are incapable for giving a general conclusion. Hence it is suggested to increase the sample
size for obtaining a better result. The relevant calculations are done in MS Excel and the outputs
are attached in this document (Abbott,2014).

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Table of Contents
Introduction......................................................................................................................................5
Discussion........................................................................................................................................6
Data Description..........................................................................................................................6
Section 1..........................................................................................................................................7
Analysis of table1 age group and gender...................................................................................10
Nursing Implication...................................................................................................................11
Research Question.....................................................................................................................11
Section 2........................................................................................................................................12
Standard Error and Sample Means............................................................................................14
Null Hypothesis.........................................................................................................................14
Alternative Hypothesis..............................................................................................................15
Pearson’s Correlation Coefficient..............................................................................................15
Coefficient of Determination.....................................................................................................16
Scatterplot..................................................................................................................................17
Implication for Nursing Research..............................................................................................18
Discussion of the demographic data in previous assignment....................................................18
Section 3........................................................................................................................................18
Null hypothesis..........................................................................................................................18
Research hypothesis...................................................................................................................19

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Target population.......................................................................................................................19
Sample population.....................................................................................................................19
Independent variable and level of measure...............................................................................19
Dependent variable and level of measure..................................................................................20
Relevant test...............................................................................................................................20
Level of Significance.................................................................................................................20
Two-tailed t test.........................................................................................................................20
Test Statistic...............................................................................................................................20
Degrees of Freedom...................................................................................................................22
Critical value..............................................................................................................................22
Comparison of calculated test statistic and null hypothesis......................................................22
Interpretation of the findings.....................................................................................................22
Nursing practice and research implication................................................................................23
Discussion of demographic data from previous assignment.....................................................23
Section 4........................................................................................................................................24
Null Hypothesis.........................................................................................................................24
Research hypothesis...................................................................................................................24
Target population.......................................................................................................................24
Sample population.....................................................................................................................25
Independent variable and level of measure...............................................................................25

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Dependent variable and level of measure..................................................................................25
Test to be done...........................................................................................................................25
Level of significance..................................................................................................................25
Test............................................................................................................................................26
Degrees of Freedom...................................................................................................................27
Critical Value.............................................................................................................................27
Comparison of calculated statistic and null hypothesis.............................................................27
Interpretation of findings...........................................................................................................27
Nursing implication...................................................................................................................28
Discussion of demographic data from previous assignment.....................................................28
Conclusion.....................................................................................................................................29
References......................................................................................................................................31

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A STUDY ON THE IMPLEMEMENTATION OF RNAO BEST PRACTICE GUIDELINE
Introduction
A group of researchers want to find the effectiveness of RNAO best practice guideline in
a South Ontario hospital (Antunes et al.,2018). The dataset consists of demographic records of
60 nurses. At first four pivot tables are constructed (Cosma, 2019). First table shows the
frequency distribution of age group and gender of the nurses. Second table shows the frequencies
of age group and professional designation of the nurses. The frequency distribution of
professional designation based on gender is displayed in the third table. The fourth table shows
the relation between employment category and gender of the nurses. Now a descriptive analysis
is worked out for the variables–perceived value of the patient wishes in adaptation of best
practice recommendation and authoritarian/collaboration score (Johnson, 2014). A correlation
analysis is also performed to find out the relationship between these two variables (Cumming, &
Calin-Jageman, 2016). Section 3 studies the effect of change in hospital environment. Here the
objective is to find whether the response towards the change in hospital environment is
independent of the gender of a nurse. Since the study revolves around the difference in opinion
of two groups, it is reasonable to use the paired t-test or the dependent sample t-test. Before
conducting the test, the null and alternate hypothesis, independent and dependent variables, level
of significance are all clearly stated to avoid any confusion. Then the t-test is performed and
based on the result the decision about the research question is taken. The last section of this
entire study shows the relation between attitude score and age groups. Here the researcher wants
to know if the reaction to the change is dependent on the age of a nurse. Since age is a
continuous variable it is converted into three age groups for ease of calculations. A one way
ANOVA test is conducted to check if there is any significant difference in opinion of a young
and an experienced nurse. The result is then interpreted to find out relevant conclusion.

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Discussion
Data Description
The dataset contains records of 60 individuals based on fifteen parameters. These variables are-
 Age of an individual
 Age group (21-35 years, 36-54 years, 55+ years)
 Gender (Male, Female)
 Professional Designation (RPN, RN diploma, RN degree)
 Employment category (full-time, part-time)
 Perceived relevance of research evidence to practice score
 Attitude towards change score
 Years of nursing experience
 Perceived relevance of clinical expertise to best practice
 Self-perception of clinical expertise to care delirium dementia depression
 Perceived value of patient wishes in adaptation of best practice recommendation
 Authoritarian/Collaboration score
 Female attitude towards change
 Male attitude towards change
 Attitude towards change for different age groups
 Perception of environment support
 Pre delirium dementia depression course quiz scores
 Post delirium dementia depression course quiz scores
 Score on basic research exam

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 Willingness to search for any evidence informed guideline
Section 1
A contingency table shows the frequency distribution of the variables. It is also known as
cross tabulation or crosstab. With the help of contingency table, one can find the association
between the variables considered. Here four contingency tables are constructed based on the
categorical variables in the dataset (Dan, 2018).
Table1
Pivot Table for Age Group and Gender
Age group
Gender
Female Male Total
Group1: 21 to 35 years old 12 7 19
Group2: 36 to 54 years old 26 6 32
Group3: 55 years or more 8 1 9
Total 46 14 60
Table 1 shows the frequency distribution of the variables age group and gender. Here
gender is independent variable and age group is taken as dependent variable. There are 12 female
and 7 male nurses in the age group 21-35 years, 26 female and 6 male nurses in 36-54 years, 8
female and 1 male nurses having age equal or more than 55 years. It can be observed that
number of female nurses (46) is more than male nurses (14).

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Table 2
Pivot table for Age Group and Professional Designation
Age Group
Professional Designation
RPN RN Diploma RN Degree Total
Group1: 21 to 35 years old 8 1 10 19
Group 2: 36 to 54 years old 8 8 16 32
Group 3: 55 years or more 8 1 9
Total 16 17 27 60
Note. No nurse with 55 years or more age have RPN designation.
The table describes the frequency distribution of the independent variable professional
designation and dependent variable age groups of nurses (Fagerland, Lydersen & Laake, 2017).
It can be observed that there are no nurse who are 55 or more years old and having RPN
designation. Maximum nurses are having RN degree (27), 17 nurses have RN diploma and 16
have RPN. For age groups, maximum frequency is obtained in the group 36-54 years. Group1
has 19 nurses where 8 have RPN, 1 has RN Diploma and 10 have RN degree. Group 2 has 32
nurses with 8 having RPN, 8 RN diploma and 16 RN degree. In group 3, 8 nurses have RN
diploma and only one has RN degree.

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Table 3
Pivot Table for Professional Designation and Gender
Professional Designation
Gender
Female Male Total
RPN 12 4 16
RN Diploma 12 5 17
RN Degree 22 5 27
Total 46 14 60
In table 3, gender is taken as independent variable and professional designation as
dependent variable. There are 46 female nurses; among them 12 are having RPN, 12 RN diploma
and 22 RN degree designation. Out of 14 male nurses, 4 nurses have RPN, 5 have RN diploma
and 5 have RN degree. There are 16 nurses with RPN, 17 nurses with RN diploma and 27 nurses
with RN degree.

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Table 4
Pivot table for Employment Category and Gender
Employment Category
Gender
Female Male Total
Full time 30 11 41
Part time 16 3 19
Total 46 14 60
Table 4 displays the frequency distribution of the variables employment category and
gender of nurses. Here gender is the independent and employment category is the dependent
variable. There are 46 female nurses and 14 male nurses. 30 female and 11 male nurses are
employed for full time and 16 female and 3 male nurses are working as part time employees. Out
of 60 nurses, 41 are having full-time employment and 19 are having part-time employment.
Analysis of table1 age group and gender
From table 1, it can be seen that there are 46 female and 14 male nurses in the study.
Among the female nurses, 12 belong to the age group 21-35 years, 26 belong to the group 36-54
years and only 8 belong to group 55 years or more. There are 7 male nurses who have ages

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between 21-35 years, 6 between 36-54 and only one has age 55 years or above. Out of 60 nurses,
19 belong to first age group, 32 belong to the second group and 9 belong to the third group.
Nursing Implication
It is evident from the table 1 that the study has around 76.67% female nurses and 23.33%
male nurses. Hence the percentage of female nurses is quite higher than that of male ones. It
exhibits two scenarios- either the recruitment of male nurse is lower than that of female nurse or
the female nurses are more capable in their task than male nurses. Maximum frequency is
obtained in the age group 36-54 years. This shows that percentage of young nurses is noticeably
low in the field. It suggests that the older nurses are more proficient in this field. In other words,
it can be implied that nurses having greater experience are more efficient in handling older adults
suffering from Delirium, Dementia or Depression. However, the older nurses are often get
discredited as they are not quite comfortable with modern nursing technologies. Since they are
having more experience, older nurses can give better guidance to the young teams. Therefore, the
proportion of young nurses will also be increased.
Research Question
Based on the contingency table given in table 1, a research query can be constructed as-
Is there any difference in effects of age and gender on a nurse’s efficiency?
In other words, it can be studied whether age and gender have different impacts on the
productivity of a nurse.

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Section 2
The descriptive study of the variables- perceived value of the patient wishes in adaptation
of best practice recommendation and authoritarian/collaboration score are given below
(Holcomb, 2016).
Table 5
Summary Statistics for Perceived Value of the Patient wishes in Adaptation of Best Practice
Recommendation
Perceived value of patient wishes in adaptation of best practice recommendations
Mean 5.82
Standard Error 0.21
Median 6
Mode 6
Standard Deviation 1.60
Sample Variance 2.56
Kurtosis 0.25
Skewness 0.13
Range 8
Minimum 2

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Maximum 10
Sum 349
Count 60
Note. Rounded to nearest hundredth decimal places.
Table 6
Summary Statistics of Authoritarian/Collaboration Score
Authoritarian / collaboration score
Mean 5.72
Standard Error 0.21
Median 6
Mode 6
Standard Deviation 1.65
Sample Variance 2.71
Kurtosis -0.32
Skewness 0.03
Range 7
Minimum 2

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Maximum 9
Sum 343
Count 60
Note. Rounded to nearest hundredth decimal places.
Standard Error and Sample Means
Standard error of mean (SEM) shows how much the sample mean is deviated from the
population mean (Hinton, 2014). Standard error is nothing but the standard deviation of the
sample. Here the SEM for both the variables are 0.21. The sample means for perceived value and
collaboration score are 5.82 and 5.72 respectively. This implies that there is 21% chance when
the sample mean (5.82) does not represent the population mean of perceived value of patient.
Moreover, there are 21% cases where the sample mean 5.72 does not represent the true
collaboration score mean (Plonsky, 2015).
Null Hypothesis
A null hypothesis is a general statement claiming that there is no existence of any
significant effect between two characteristics (Murphy, Myors & Wolach, 2014). The null
hypothesis is considered true until there is enough evidence against it. Here the variables of
interest are perceived value of the patient wishes in adaptation of best practice recommendation
and authoritarian score. Hence the dependent variable will be the collaboration score and
independent variable will be the perceived value. To check whether these two variables share a

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bond or not, a testing procedure can be conducted based on the null hypothesis. The null
hypothesis can be taken as-
There is no significant relation between the perceived value of patient wishes in
adaptation of best practice recommendation and authoritarian score.
Alternative Hypothesis
An alternative hypothesis is taken as contrary to the null hypothesis. It generally assumes
that there is significant relation between the variables concerned. If the testing results shows
existence of association, then the null hypothesis is rejected and the alternative hypothesis is
accepted. For testing the null hypothesis stated above, the alternative hypothesis can be taken as-
There is positive association between perceived value of patient wishes in adaptation of
best practice recommendation and collaboration score.
The perceived value shows that how much a patient is convinced to adopt the best
practice recommendation. If the perceived value increases then the authoritarian score also
increases. Therefore it is a directional hypothesis showing a positive relationship between the
variables.
Pearson’s Correlation Coefficient
The Pearson’s correlation coefficient shows the extent to which two variables are linearly
correlated. It is calculated as the ratio of covariance between the variables to product of square
roots of the variances (Solutions, 2016). The value of the correlation ranges from -1 to +1 where
-1 indicates perfectly negative linear relationship and +1 gives perfectly positive linear
relationship. The correlation for the study variables is given below.

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Table 7
Correlation between the perceived value of patient wishes in adaptation of best practice
recommendation and collaboration score
Perceived value of patient wishes in
adaptation of best practice
recommendations
Authoritarian /
collaboration
score
Perceived value of patient wishes in
adaptation of best practice
recommendations 1
Authoritarian / collaboration score 0.78 1
Note. Pearson’s r=0.78
The Pearson’s correlation coefficient is 0.78. This implies that perceived value of
adaptation is linearly related with authoritarian/collaboration score. Moreover, the value is close
to +1, which indicates a strong positive linear association (Puth, Neuhäuser & Ruxton, 2014).
Therefore, it can be concluded that as the perceived value of patients wishes in adaptation of best
practice increases, the authoritarian/collaboration score also increases.
Coefficient of Determination
The coefficient of determination shows the percentage of variability of the dependent
variable explained by the independent variables (Nakagawa, Johnson & Schielzeth, 2017). It is
calculated as the square of the correlation coefficient. Here the coefficient of determination is
0.782 =0.6084 .Hence it can be concluded that 60.84% variability in the
authoritarian/collaboration score can be explained by the perceived value of patients in adapting
best practice.

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Scatterplot
The relation between the variables is graphically represented below.
Graph 1
Scatterplot between the perceived value of patient wishes in adaptation of best practice
recommendation and authoritarian score
The scatterplot shows that the authoritarian/collaboration score is highly associated with
perceived value of patient wishes to adopt best practice. It also shows an upward trend which
indicates a positive relation. In other word, it can be concluded that if patients are more
interested in adopting the recommended best practice guideline then the authoritarian score
increases and tends to be collaboration score.

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Implication for Nursing Research
The above study shows the association between perceived value and authoritarian score.
The correlation is found to be 0.78 which indicates a strong positive correlation between the
variables. The null hypothesis assumed that there is no association between the variables, but the
correlation is found to be positive (Schober, Boer & Schwarte, 2018). Hence, the null hypothesis
is rejected and it can be concluded that there is strong interconnection between them. It seems
that if a patient is enough convinced to adopt the best practice recommended by the nurse, then
the authoritarian score will be higher. They will be more cooperative with the nursing staff.
Discussion of the demographic data in previous assignment
Previous study shows that the South Ontario Hospital recruits maximum nurses who are
highly qualified and having impressive experience (Brown et al., 2019). They are very much
expert in the field. Hence it can be said that they are much more capable of handling Delirium,
Dementia and Depression affected patients. They can convince them to adopt the hospital
guideline. Hence more patients will be convinced in adaptation of best clinical practice provided
by the hospital and their nursing staff.
Section 3
Here the main objective is to check whether the male and female nurses have different
attitude towards the change score.
Null hypothesis
The null hypothesis for this case can be considered as-

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There is no significant difference in attitudes towards change between males and females.
In other words, it is assumed that male and female nurses react equally to the change
score.
Research hypothesis
The researcher wants to know if the attitude towards change is dependent on gender or
not. Hence the research hypothesis can be taken as-
The attitude of male and female nurses towards change differ significantly.
Target population
Since the study revolves around male and female nurses, the target population will
contain records on both male and female nurses.
Sample population
The sample population for this study consists records of 60 nurses. Among them, 46 are
female and 14 are male nurses.
Independent variable and level of measure
The independent variable is gender of a nurse which is a categorical variable. It has two
categories- male and female. This variable is measured in nominal scale and the assigned
numerical values are 1(female) and 2(male). The categories do not have any specific order hence
they can be interchanged.

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Dependent variable and level of measure
The dependent variable is the attitude towards change score. It is measured in a ratio
scale from 0 to 10 with interval 1 and has a meaningful order of reaction. Here 0 indicates a
negative attitude towards the change whereas 10 implies positive reaction.
Relevant test
A paired sample t- test is would be an appropriate tool for testing the above hypothesis.
Paired sample t-test or the dependent sample test is used to test whether the mean
difference of observations of two groups is zero or not. Here the null hypothesis assumes that the
difference in opinion of males and females is zero. Hence, a paired t test would be most suitable
for the analysis.
Level of Significance
The significance level gives the probability of rejecting a null hypothesis when it is
actually true. Rejection of a true null hypothesis is known as type-I error (Sedgwick, 2015). A
level of significance 5% implies that there is 5% chance of rejecting a null hypothesis when it is
actually true. For this study, it is reasonable to take the significance level as 5%.
Two-tailed t test
Rejection of null hypothesis can lead to two type of conclusion-male nurses showing
greater positive reaction than the female nurses or vice versa. Hence, it is appropriate to use two
tailed test. The alpha level ir significance level is 0.025 in each tail end of the normal
distribution.

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Test Statistic
Now a paired t-test is performed and the relevant outputs are given below.
Table 8
Paired sample t-test for attitude towards change between male and female nurses
t-Test: Two-Sample Assuming Equal Variances
female attitudes towards
change
male attitudes
towards change
Mean 5.87 5.21
Variance 3.14 1.87
Observations 46 14
Pooled Variance 2.85
Hypothesized Mean Difference 0
df 58
t Stat 1.27
P(T<=t) one-tail 0.10
t Critical one-tail 1.67
P(T<=t) two-tail 0.21
t Critical two-tail 2.00
Note. Rounded to nearest hundredth decimal place.

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Degrees of Freedom
For a paired t-test, the degrees of freedom of the test statistic is n-2, where n is the sample
size and 2 is subtracted from n since two groups are involved. Here n=60, thus the degrees of
freedom of the test statistic will be 60-2=58.
Critical value
A critical value determines whether to reject or accept a null hypothesis (Altman &
Krzywinski, 2017). Here the critical value for a two tailed test at 5% level of significance with
58 degrees of freedom is calculated as ±2.00. the calculation of the critical value can be obtained
directly from the excel output.
Comparison of calculated test statistic and null hypothesis
Table 8 shows that the value of t-statistic= 1.27, d.f.=58, p-value=0.21. It is evident that
the calculated test statistic is greater than the p-value ate 5% level of significance. Thus the null
hypothesis is accepted and it can be deduced that there is no significant difference in the opinion
about the changed scores between male and female nurses. Further, it can be observed that the
value of the test statistic does not exceed the critical value for two-tailed test which is 2.00 in this
case. Therefore, it can be concluded that male and female nurses react to the changed score in
similar way. In other words, the attitude towards the changed score is independent of the gender
of nursing staff.
Interpretation of the findings
From table 8, it can be observed that the average score of female attitude towards
changed score is 5.87 which is greater than the mean score for male nurses that is 5.21. Thus it is
evident that the reaction of female nurses is more positive than the male nurses. The variances of

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score for female and male nurses are 3.14 and 1.87 respectively. The pooled variance is found to
be 2.85. since the null hypothesis assumes no difference in opinions between male and female
staff, the hypothesized mean difference is considered as 0. It can be noted that the number of
female nurses is quite large than the male nurses. Hence the assumption of equal variance may
be violated because of unequal sample size. Hence the deduction will be exposed to bias and any
generalized conclusion will not be appropriate.
Nursing practice and research implication
For this study, the variable of interest is attitude towards changed score which determines
how nurses are responding to the changes in the hospital environment and their working
practices (Zhao et al., 2017).. They gave ratings in a 0-10 scale where 0 indicates the negative
view and 10 indicates a positive view of the nurse. Since the nursing staff is dominated by
females, the sample size for the two groups will be different. Thus the testing of equality in mean
opinion of male and female nurses is exposed to error. The test statistic value(1.27) is greater
than the p-value(0.21). Hence it can be deduced that there is no significant difference in reaction
of female and male nurses towards the change in working environment. Since the sample size is
unequal for the two groups, the comparison of mean fails to give a generalised conclusion.
Hence it can be suggested that if the total sample size increases, then the proportion of female
and male nurses may be equal and the test result will be more suitable for any deduction.
Discussion of demographic data from previous assignment
The previous assignment showed the descriptive study of the change score. This variable
shows how nurses are responding to the change in their workplace environment. The study
shows that on average, female nurse gives a rating 5.87 whereas for male nurse it is 5.21(Pyrczak
& Oh, 2018). . Since the number of female nurse is much more than the male nurse, it is

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reasonable to find a higher mean score for females. The test result shows that there is no
significant difference in opinion towards changed environment between male and female nurses
(Schenck, 2015). However, the test assumes equal variances which is not satisfied in this case
due to unequal proportion of females and males. Hence, the test is suitable for the sample but it is
not much appropriate for general deduction about the population.
Section 4
The objective of this section is to find whether there is any change in opinion of nurses
coming from different age groups.
Null Hypothesis
For this research, the null hypothesis can be taken as-
There is no significant difference in attitude towards change among nurses from various age
groups.
Research hypothesis
The researcher wants to verify if the opinion for changed environment is dependent on
the age groups. Hence the research question will be-
There is significant difference in opinion of nurses having different age groups.
Target population
The target population for this study will include all the nurses from various age groups.

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Sample population
The sample consists of 60 nurses. Among them, 19 nurses are from the age group 21-35
years, 32 belong to the group 36-54 years and 9 nurses have age 55 years or more.
Independent variable and level of measure
The independent variable is the age group in this case. Since age is a continuous variable
it is convenient to categorize them into different age groups. Here the independent variable is
measured in a nominal scale and has three levels-21-35 years, 36-54 years , 55 years or more.
Dependent variable and level of measure
The dependent variable is the opinion score given by the nurses. It is measured on a ratio
scale from 0 to 10 with interval 1. Here a value 0 means negative impression about the change
and 10 means positive impression about the change in work environment.
Test to be done
A One-way ANOVA test will be most appropriate in this situation (Chambers, Freeny, &
Heiberger, 2017).
A one-way ANOVA test is a statistical method that helps to determine whether there is a
difference in characteristics among different groups (Islam & Al-Shiha, 2018). It can be referred
as a generalised version of two-tailed test where the number of groups is 3 or more.
Level of significance
The level of significance or alpha gives the measurement of risk to which a true null
hypothesis get rejected. Here the significance level is taken as 5%. This means that the
researcher will allow 5% risk to reject a true null hypothesis.

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Test
A One-way ANOVA test is performed to test the difference in opinion among various
age groups (Winston, 2016). The necessary outputs are shown below.
Table 9.1
ANOVA for single factor: Summary
Groups Count Sum Average Variance
attitudes towards change age group 1 19 114 6 2.33
attitudes towards change age group 2 32 177 5.53 2.52
attitudes towards change age group 3 9 56 6.22 2.69
Note. Rounded to nearest hundredth decimal palce.
Table 9.2
ANOVA Table
Source of Variation SS df MS F P-value F crit
Between Groups 4.66 2 2.33 0.94 0.40 3.16
Within Groups 141.52 57 2.48
Total 146.18 59
Note. Rounded to nearest hundredth decimal place.

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Degrees of Freedom
The degrees of freedom of the F-statistic for a One-way ANOVA is calculated as (k-1),
(n-k) where n=sample size, k=number of levels in the factor. Here the factor age group has 3
levels and sample size is 60. Hence, the degrees of freedom will be (2, 57).
Critical Value
The critical value is a point on the test distribution that helps one to decide whether to
reject or accept a null hypothesis. Here the critical F-value is 3.16. the value can be obtained
directly from the excel table.
Comparison of calculated statistic and null hypothesis
The value of F-statistic=0.94, d.f.=(2,57),p-value=0.40. It is evident that the value of the
test statistic is greater than the p-value at 5% level of significance. Thus the null hypothesis is
accepted and based on the data it can be deduced that there is no significant difference in opinion
among nurses from various age groups (MacRae, 2019). It other way, the attitude towards
change is not dependent on the age of a nurse.
Interpretation of findings
Table 9.1 show that nurses having age in 21-35 years give 6 rating to the change on
average with variance 2.33. Nurses who belong to the group 36-54 years have mean score 5.53
with variance 2.52. Nurses who are 55 years old or more rates the change as 6.22 on average.
Hence nurses who belong to senior most group have positive reaction to the change (Young &
Wessnitzer, 2016). There are 19 nurses from age group 1, 32 from group 2 and 9 from group 3.
The calculated F-value is 0.94 which is non-significant at 5% level. It does not exceed the critical

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value which is 3.16 in this case. Thus it can be deduced that there is no significant difference in
opinion of nurses based on their age groups.
Nursing implication
In this section, the difference in opinion about the change in hospital environment is
studied. The test results shows that there is no notable difference in reaction of nurses coming
from different age groups toward the change(Prowd et al., 2018). However the proportion of
nurses more than 55 years age is comparatively much smaller than any of the two other groups.
The ANOVA test assumes equal variances among the groups which is not satisfied in this case.
Hence the test fails to give a general conclusion.
Discussion of demographic data from previous assignment
The demographic study of the age group variable shows that the maximum number of
nurses belong to the age group 36-54 years implying that that have a quite stable experience in
their workplaces. Hence it can be said that these experienced nurses will have a positive attitude
towards the changes happening in the hospitals. However the test shows that there is no
difference in opinions of nurses regardless their age. In other words, a young nurse and a senior
nurse have same attitude towards the change (Burkoski et al., 2019). It can be seen that the
sample contains unequal proportion of various age groups. Hence the test result may be suitable
for the sample but it is not perfect for giving any general deduction. Therefore it is suggested to
increase the sample size for obtaining a better result.

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Conclusion
The pivot table for age group vs gender shows that there are 46 female and 14 male
nurses in the sample (Grech, 2018). Maximum number of nurses belong to the age group 36-54
years. There are very few nurses who have age above 55 years. The pivot table for age group vs
professional designation shows that maximum nurses hold RN degree. This implies that the
hospital is more interested in recruiting more educated and experienced nurses (Marciales et al.,
2017). Table 3 shows that 22 female nurses have RN degree whereas only 5 male nurse have that
degree. The low proportion of male nurse in the sample indicates female domination in nursing
association. From table 4, it can be seen that there are 41 nurses who are employed for full-time
job whereas only 19 are part-time employer. The perceived value of patient in adapting the
recommended guideline has an average 5.82. The median shows that 50% cases have value less
than 6. The authoritarian score has a mean 5.72 and median 6. The correlation between these two
variables is found to be 0.78. This implies that the variables are having a strong positive
correlation (Lane et al., 2017). In other way, it can be said that if a patient is sufficiently
convinced to adopt the recommended guideline, then they will be much more cooperative with
the hospital and nursing team for utilising the best practice guideline. The coefficient of
determination shows that 60.84% variability in authoritarian score can be explained by the
perceived value (Lowry, 2014). Section 3 shows whether the attitude of a nurse towards the
change in workplace environment depends on his gender. The value of the test statistic is 1.27
with p-value 0.21. Thus, the test result shows that there is no significant difference in opinion of
the female and male nurses. Finally, difference in opinion of nurses due to their age groups is
studied. A one-way ANOVA test is performed to check if there is any significant difference in
reaction due to various age groups (Fomin & Dik, 2015). The calculated value of F-statistic is

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A STUDY ON THE IMPLEMEMENTATION OF RNAO BEST PRACTICE GUIDELINE
0.94 with the p-value (0.40). Hence, the null hypothesis is accepted and it is concluded that there
is no significant difference in response given by the nurses from different age groups. Since the
sample size is dominated by female nurses, the results are incapable of finding a general
conclusion. Hence it is recommended to increase the sample size for an improvised result.

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References
Abbott, M. L. (2014). Understanding educational statistics using Microsoft Excel and SPSS.
John Wiley & Sons.
Altman, N., & Krzywinski, M. (2017). Points of significance: interpreting P values.
doi.org/10.1038/nmeth.4210
Antunes, V., Valentim, O., Pereira, F., Frade, F., Firmino, C., Marques, J., ... & Sousa, L. (2018).
RNAO’S best practice guidelines in the nursing curriculum.
Bajnok, I., McConnell, H., Grinspun, D., & Stewart-Pyne, A. (2014). An Evidence-Based
Approach to Successful Practice Change,'the Toolkit: Implementation of Best Practice
Guidelines.
Benjamin, D. J., Berger, J. O., Johannesson, M., Nosek, B. A., Wagenmakers, E. J., Berk, R., ...
& Cesarini, D. (2018). Redefine statistical significance. Nature Human Behaviour, 2(1), 6.
doi.org/10.1038/s41562-017-0189-z
Brown, K. T., Abdul-Kareem, K. N., Kahwa, E., & Anderson-Johnson, P. (2019). Strategies for
Successful Implementation of Best Practices Guidelines in a Nursing Curriculum.
Burkoski, V., Yoon, J., Farshait, N., Hutchinson, D., Collins, B., Solomon, S., & Grinspun, D.
(2019). Optimizing Nursing Practice through Integration of Best Practice Guidelines into
Electronic Medical Records. Can J Nurs Leadersh [Internet], 98-107.
Chambers, J. M., Freeny, A. E., & Heiberger, R. M. (2017). Analysis of variance; designed
experiments. In Statistical models in S (pp. 145-193). Routledge.

32
A STUDY ON THE IMPLEMEMENTATION OF RNAO BEST PRACTICE GUIDELINE
Cosma, E. (2019). Pivot Table: A Tool to Calculate, Summarize, and Analyze Data. Ovidius
University Annals, Economic Sciences Series, 19(1), 161-166.
Cumming, G., & Calin-Jageman, R. (2016). Introduction to the new statistics: Estimation, open
science, and beyond. Routledge.
Dan, N. (2018). Excel Pivot Tables: Easy practical guide for everyone. CreateSpace Independent
Publishing Platform.
Fagerland, M., Lydersen, S., & Laake, P. (2017). Statistical analysis of contingency tables. CRC
press.
Fomin, V. N., & Dik, A. V. (2015). Using one-way analysis of variance in the stochastic
determinated design of experiment.
Grech, V. (2018). WASP (Write a Scientific Paper) using Excel–2: Pivot tables. Early human
development, 117, 104-109.
Hinton, P. R. (2014). Statistics explained. Routledge.
Holcomb, Z. C. (2016). Fundamentals of descriptive statistics. Routledge.
Hopkins, W. G. (2017). Spreadsheets for analysis of validity and reliability. Sportscience, 21.
Islam, M. A., & Al-Shiha, A. (2018). Analysis of Variance. In Foundations of Biostatistics (pp.
345-371). Springer, Singapore.
Johnson, D. E. (2014). 14 Descriptive statistics. Research methods in linguistics, 288.
Lane, D. M., Scott, D., Hebl, M., Guerra, R., Osherson, D., & Zimmer, H. (2017). An
Introduction to Statistics. Rice University.

33
A STUDY ON THE IMPLEMEMENTATION OF RNAO BEST PRACTICE GUIDELINE
Lowry, R. (2014). Concepts and applications of inferential statistics.
MacRae, A. W. (2019). Descriptive and inferential statistics. Companion Encyclopedia of
Psychology: Volume Two, 1099.
Marciales, A. P. B., Valencia, M. L. J., Gómez, S. E. S., Luna, G. I. A., García, C. I. P., &
Morales, M. L. C. (2017). Implementación de la guía de valoración y manejo del dolor, de la
Registered Nurses' Association of Ontario (RNAO) en el programa de Enfermería de la
Universidad Autónoma de Bucaramanga. MedUNAB, 20(2), 148-164.
Mindrila, D., & Balentyne, P. One-Way Analysis of Variance: Comparing Several Means.
Murphy, K. R., Myors, B., & Wolach, A. (2014). Statistical power analysis: A simple and
general model for traditional and modern hypothesis tests. Routledge.
Nakagawa, S., Johnson, P. C., & Schielzeth, H. (2017). The coefficient of determination R 2 and
intra-class correlation coefficient from generalized linear mixed-effects models revisited and
expanded. Journal of the Royal Society Interface, 14(134), 20170213.
Pagana, K. D. (2019). Etiquette & Communication Strategies for Nurses (Vol. 3). Sigma.
Plonsky, L. (2015). Statistical power, p values, descriptive statistics, and effect sizes: A “back-
to-basics” approach to advancing quantitative methods in L2 research. In Advancing quantitative
methods in second language research (pp. 23-45). Routledge.
Prowd, L., Leach, D., Lynn, H., & Tao, M. (2018). An Interdisciplinary Approach to
Implementing a Best Practice Guideline in Public Health. Health promotion practice, 19(5), 645-
653.

34
A STUDY ON THE IMPLEMEMENTATION OF RNAO BEST PRACTICE GUIDELINE
Puth, M. T., Neuhäuser, M., & Ruxton, G. D. (2014). Effective use of Pearson's product–moment
correlation coefficient. Animal behaviour, 93, 183-189.
Pyrczak, F., & Oh, D. M. (2018). Making sense of statistics: A conceptual overview. Routledge.
Roberts, M., & Russo, R. (2014). A student's guide to analysis of variance. Routledge.
Schenck, T. (2015). Sustaining Health Care Practice Change: The Experience of Best Practice
Spotlight Organizations Implementing and Sustaining RNAO Best Practice Guidelines.
Schober, P., Boer, C., & Schwarte, L. A. (2018). Correlation coefficients: appropriate use and
interpretation. Anesthesia & Analgesia, 126(5), 1763-1768.
Sedgwick, P. (2015). Confidence intervals, P values, and statistical significance. Bmj, 350,
h1113. doi: https://doi.org/10.1136/bmj.h1113
Solutions, S. (2016). Correlation. Pearson, Kendall, Spearman). Accessed October, 18, 2016.
Van der Walt, C., Vasuthevan, S., Lubbe, J. C. I., & Smith, P. J. Integrating evidence-based
practice in a nursing curriculum based on the RNAO Guidelines using action research.
Winston, W. (2016). Microsoft Excel data analysis and business modeling. Microsoft press.
Young, J., & Wessnitzer, J. (2016). Descriptive statistics, graphs, and visualisation. In Modern
statistical methods for HCI (pp. 37-56). Springer, Cham.
Zhao, J., Wang, J., Liu, X., Han, L., Jiang, Y., Gao, S., & Hao, Y. (2017). Exploring on nursing
educational innovation with best practice guidelines to cultivate evidence-informed practice.
Journal of Nursing Education and Practice, 7(1), 6.

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A STUDY ON THE IMPLEMEMENTATION OF RNAO BEST PRACTICE GUIDELINE