|Type of paper:||Essay|
|Categories:||Health and Social Care Data analysis Statistics|
Frequency of the sample = 7+7 =14
Percentage of the total sample which were still employed = [total percentage - retired] = [100-61] = 39%
Percentage of the sample with a smoking history is given both by those still smoking and former smokers still smoking = 13+12=25, former smokers = 28+35=63; Sample smokers = 25+63 = 88. Percentage of the sample smoking history = 88/91 100 = 97% The smoking history is clinically important in order to determine pack year smoking.
Moderate packs are 29.1 severe packs smokers 34.0. According to the research the people with severe airflow limitation opposed to moderate airflow have close range in percentage due to quantity of packs smoked per day. The percentage between the 2 is only 4.6%. There's no difference between the two, because both types of smokers have caused damage to their lung tissues
The four psychological symptoms were difficulty sleeping (52%), worrying (33%), Feeling irritable (28%) and feeling sad (22%). There were no significant differences between patients with moderate and severe airflow limitation groups for psychological symptoms. (Reported result: mental health, P=0.628 which is > 0.05 level.)
#. Of moderate airflow limitations in sample (n1) =42 Frequency of total sample used short-acting B2-agonists in moderate airflow limitations(x1) x1=13 Proportion of total sample used short-actingB2-agonists in moderate airflow limitations(p1) p1=x1/n1=13/42=0.3095~_0.31 total percentage of sample used short-acting B2-agonists in moderate airflow limitations is 31%
#. Of severe airflow limitations in sample (n2) =49 Frequency of total sample used short-acting B2-agonists in severe airflow limitations (p2) P2=x2/n2=32/49=0.6531~0.65 The total percentage of sample used short-acting B2-agonists in severe airflow limitations is 65%
P=n1p1+n2p2/n1+n2= 42(0.31) +49(0.65)/42+49= 0.49
We want to test whether the significant difference between the moderate and severe airflow limitation groups regarding the use of short-acting B2-agonists.
Null and alternative hypothesis are
H 0: P1-P2 versus H1:P1#P2
Level of significance(a) = 0.05
Under, the null hypothesis the test statistic value can be defined as
Z=|P1-P2|/P(1-P) [1/n1+1/n2] =|0.31-0.65|/0.49(1-0.49) [1/42+1/49] =3.2344
We critical value using Excel function
Z1-(0.05/2) =Z0.975=Normsinv (0.975) =1.96
Decision and Conclusion:
Here we observe that the test statistic value (3.2344) is greater than critical value (1.96), so we reject the null hypothesis. Therefore, we conclude that there is a sufficient evidence to support that there is a significant difference between the moderate and severe airflow limitation groups regarding the use of short-acting B2-agonists.
In this case study, 31% of the COPD patients with moderate airflow limitation and 65% of the COPD patients with severe airflow limitation were treated using short-acting v 2 -agonists.
Mean percent = (31 + 65) / 2 =48%
The use of short-acting v 2 -agonists is more common for the COPD patients with severe airflow limitation.
Whereas the use of short-acting v 2 -agonists is rare for the COPD patients with moderate airflow limitation.
So, we might not expect that a large percent of COPD patients in this case study are using short-acting v 2 -agonists.
Short acting and long acting used together will allow the short acting to begin working now and the long acting to kick in where it left off. This will equal a greater effect on the use of the bronchodilator.
Mean=sum of variable/N = (520+563+563+577+ 593+606+610)/7=576 Median (MD)=(N+1)/2=8/2=4th number when sorted in ascending order. Hence, median is 577. 2) Mode is number occurring most often in distribution. Hence, mode is 563.
The mode for the variable inpatient complications in Table 2 of the Winkler et al. (2014) study is AMI post admission for patients admitted with UA. The percentage of the study participants had this complication is 8%.
The distribution of inpatient complications has a single mode which indicates a normal distribution.
Chest pain with frequency of 255 and percent of 92%, Shortness of breath with frequency of189 and percentage 68%, and jaw, neck, arm, or back pain with frequency of 152 and percentage of 55%. This is clinically important because nurses and other healthcare providers need to assess for these symptoms, diagnose the problem, and appropriately manage patients presenting with ACS at the ED.
The mean is 5.37 days and median lengths of stay (LOS) for the study participants is 4
The mean and median for Length of stay is different. The distribution of the length of stay is the right slowed of the sample. Since the mean is greater than median.
If the mean is greater than mean, then the distribution of the sample is right skewed
Distribution otherwise left skewed distribution or symmetrical
Mode for the age is,
Mode = 3Me-2M = 3(66)-2(66) =198-132=66
Mode for the ECG
Mode = 3Me-2M = 3(24)-2(21) = 72-42 = 30
Mode for the LOS
Mode = 3Me-2M = 3(4)-2(537) = 12-10.74 = 1.26
Yes. This result is significant.
Age greater than 65 years and final diagnosis of acute myocardial infraction (AMI) were independently predictive of the 50 premature ventricular contractions (PVCs) per hour
White is the mode (highest frequency, 143 out of 278). This study findings may not be generalized to American Indians with ACS because this American Indians constitutes only 8% of the sample.
The name and type of measurement is Likert scale. It is used to measure the attitude of people on a topic.
The level of measurement is 5 point Likert scale. It contains 5 levels with each level contains a reason.
The subscales included in the CNPISS used to measure RN's perceptions of their caring practice are overall rating, clinical care, relational care, and comforting care. These subscales seem to be relevant as they come under caring practices.
The subscale for caring practices with the lowest mean is Relational care (2.90). This result indicates that the relational care between nurse and patient is not that much good.
The dispersion result is indicated by standard deviation. Here the standard deviation of relation care is 1.01. This says that the population means of relational care lies within 1 standard deviation of the mean.
Clinical care of caring practices has the lowest dispersion or variation of scores because Range of clinical care is
Standard Deviation (SD)=0.57
Range and Standard Deviation of Clinical care of Caring practices subscales is less than the other (Overall rating, Relational care, Confounding care)
Thus, the score for Clinical care had the lowest dispersion of the Caring practices subscales.
Comforting care has highest mean in caring practices subscales.
Mean of Comforting care is 4.08
When compared with the other subscales in caring practices.
Comforting care had the highest mean. Indicating this is most positive perceived of the subscales cover by caring practices sub scales. The highest mean the more positive the comforting care.
Mean of overall rating in Organizational Climate (x1) =3.13
Standard deviation of overall rating in Organization climate (q1) =0.56
Coefficient of variation of overall rating in Organization climate (C. V1) is
C.V1= Standard Deviation (q1)/Mean(x1) *100 = 0.56/3.13*100=17.89
Range of overall rating in Organization climate (R)=4.67-1.75=2.92
Mean of overall rating in Caring practices(x2) =3.62
Standard Deviation of overall rating in caring practices (q2) =0.66
Range of overall rating in caring practices (R) =5.00-1.95=3.05
Coefficient of variation of overall rating in Caring practices (C. V2) is
C.V2 = Standard Deviation (q2)/Mean(x2) *100 = 0.66/3.62*100=18.23
We compare Coefficient of variation for both subscales Overall rating in Organizational climate has less coefficient variation than caring practices.
Range of overall rating in Organizational climate is less than the overall rating in caring practices.
Thus, the Overall rating in Organizational climate is more homogeneous than overall rating in Caring Practices
In this study is a strength, the response rate for the study was 45%. An increased sample size might provide a stronger description of the hospital's organization climate and caring practices.
The organizational climate in healthcare settings influences patient outcomes, but its effect on nursing care delivery remains poorly understood. In this mixed-methods study, nurse surveys (N = 292) were combined with a qualitative case study of 15 direct-care registered nurses (RNs), nursing personnel, and managers. Organizational climate explained 11% of the variation in RNs' reported frequency of caring practices. Qualitative data suggested that caring practices were affected by the interplay of organizational climate dimensions with patients and nurse's characteristics. Workload intensity and role ambiguity led RNs to leave many caring practices to practical nurses and assistive personnel. Systemic interventions are needed to improve organizational climate and to support RNs' involvement in a full range of caring practices.
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