Part I: Background and Problem Statement
Patient outcomes in care provision have, for a long time, been connected to expert experience. However, with older professional retiring, it is emerging more and more difficult to maintain a high-tier experience among healthcare providers in ICU departments ( Boling & Hardin-Pierce, 2016) . Various innovative training techniques that enhance expert confidence and knowledge may manage to cater for deficiencies in healthcare experience ( McDonnell, 2008) . Also, various training sessions have mimicked clinical experience and has been exclusively research in the training of various skills, but the impact of this form of training on confidence and knowledge have not been adequately addressed ( Figueroa et al., 2013) . To address this question, this paper conducts a quantitative analysis of training on the enhancement of level of confidence and knowledge on healthcare providers.
Part II: Sample
The study variables are selected in terms of gender, qualification, age, years in practice/experience, degree of knowledge before training, level of knowledge after training, worksite (location of work), confidence in knowledge, and certification in knowledge. Gender is categorized as male or female (1 or 2 respectively), qualification is categorized as nonprofessional, paraprofessional and professional (3, 2, or 1 respectively), and worksite/location of work grouped as 1 (on-site) and 2 (off-site). Knowledge is classified on a scale of 1-10, with high knowledge ranking higher than limited knowledge, both for before and after training.
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The descriptive statistics for the continuous/scale variables is provided in the table below:
|
Age |
Knowledge1 |
Knowledge 2 |
Years |
Confidence |
Exam |
||||||
| Mean |
0.463 |
Mean |
5.7 |
Mean |
7.4 |
Mean |
4.5 |
Mean |
7 |
Mean |
6.3 |
| Standard Error |
0.08668 |
Standard Error |
0.7 |
Standard Error |
0.4 |
Standard Error |
0.98036 |
Standard Error |
0.29814 |
Standard Error |
0.51747 |
| Median |
0.425 |
Median |
6 |
Median |
7.5 |
Median |
4 |
Median |
7 |
Median |
6 |
| Mode |
#N/A |
Mode |
6 |
Mode |
8 |
Mode |
4 |
Mode |
7 |
Mode |
5 |
| Standard Deviation |
0.27411 |
Standard Deviation |
2.21359 |
Standard Deviation |
1.26491 |
Standard Deviation |
3.10018 |
Standard Deviation |
0.94281 |
Standard Deviation |
1.63639 |
| Sample Variance |
0.07513 |
Sample Variance |
4.9 |
Sample Variance |
1.6 |
Sample Variance |
9.61111 |
Sample Variance |
0.88889 |
Sample Variance |
2.67778 |
| Kurtosis |
0.11461 |
Kurtosis |
-0.69 |
Kurtosis |
-0.026 |
Kurtosis |
-0.3826 |
Kurtosis |
1.18527 |
Kurtosis |
-1.0929 |
| Skewness |
0.86438 |
Skewness |
-0.295 |
Skewness |
-0.5435 |
Skewness |
0.72716 |
Skewness |
-0.9944 |
Skewness |
0.34992 |
| Range |
0.85 |
Range |
7 |
Range |
4 |
Range |
9 |
Range |
3 |
Range |
5 |
| Minimum |
0.15 |
Minimum |
2 |
Minimum |
5 |
Minimum |
1 |
Minimum |
5 |
Minimum |
4 |
| Maximum |
1 |
Maximum |
9 |
Maximum |
9 |
Maximum |
10 |
Maximum |
8 |
Maximum |
9 |
| Sum |
4.63 |
Sum |
57 |
Sum |
74 |
Sum |
45 |
Sum |
70 |
Sum |
63 |
| Count |
10 |
Count |
10 |
Count |
10 |
Count |
10 |
Count |
10 |
Count |
10 |
| Largest(1) |
1 |
Largest(1) |
9 |
Largest(1) |
9 |
Largest(1) |
10 |
Largest(1) |
8 |
Largest(1) |
9 |
| Smallest(1) |
0.15 |
Smallest(1) |
2 |
Smallest(1) |
5 |
Smallest(1) |
1 |
Smallest(1) |
5 |
Smallest(1) |
4 |
| Confidence Level(95.0%) |
0.19608 |
Confidence Level(95.0%) |
1.58351 |
Confidence Level(95.0%) |
0.90486 |
Confidence Level(95.0%) |
2.21773 |
Confidence Level(95.0%) |
0.67444 |
Confidence Level(95.0%) |
1.1706 |
In the results above, the means for age, years, and exam are greater than the medians. This indicates that the data seems to be skewed to the right. However, the means for knowledge before and after training and exam score are less than the medians, an indication of leftward skewness of the data. There is symmetry in the data describing confidence as represented by the same value for both the mean and median. The results of the standard deviations are 0.27411 for age, 2.21359 for knowledge 1, 1.26491 for knowledge 2, 3.10018 for years, 0.94281 for confidence, and 1.63639 for exam. This means that the data is normally distributed. Normally distributed data are characterized by observations which are spread within 2sdvs on each side of population mean ( Fine et al., 2017) .
In terms of skewness, that data is fairly symmetrical for the knowledge acquired after training (Knowledge 2 with -0.5435 skewness). The data is moderately skewed for Knowledge 1 and Exam (with skewness of -0.295 and 0.34992 respectively). Moderate skewness is also evident in age and confidence. All the kurtosis values are close to 0, a confirmation of normal distribution of the data.
Frequency distribution table for the scale variables
|
Bin |
Frequency |
Bin |
Frequency |
|
0.5 |
1 |
More |
5 |
|
1 |
0 |
0.5 |
1 |
|
1.5 |
0 |
1 |
0 |
|
2 |
0 |
1.5 |
0 |
| More |
5 |
2 |
0 |
Part III: Variable Relationship
First, correlation coefficient indicates how strongly two variables are connected to each other. Coefficients above 1 are described to be in perfect correlation. That is, as Y increases, X also rises. Correlation coefficients nearing 0 show no correlation. Coefficients of -1 show a perfect negative correlation. The resulting correlation for the variables is presented below.
|
Age |
Knowledge1 |
Knowledge2 |
Years |
Confidence |
Exam |
|
| Age |
1 |
|||||
| Knowledge1 |
-0.3518 |
1 |
||||
| Knowledge2 |
-0.2057 |
0.92063 |
1 |
|||
| Years |
0.06472 |
0.12143 |
0.39668 |
1 |
||
| Confidence |
-0.129 |
0.47916 |
0.37268 |
-0.3801 |
1 |
|
| Exam |
-0.2054 |
0.70244 |
0.79446 |
0.36138 |
0.50413 |
1 |
From the correlation table above, age and exam show a perfect negative correlation (-0.21), age and confidence have a perfect negative correlation (-0.13), age and years shows no correlation (0.06), age and knowledge after training have negative correlation (-0.21), and age and knowledge before training have negative correlation (-0.35). Knowledge before training and knowledge after training are correlated (0.92), knowledge after training and exam are correlated (0.8). Strong correlations are knowledge after training and exam score, knowledge before training and exam score, knowledge before training and knowledge after training. Weak correlations are knowledge before training and years of experience, and age and years of experience.
Part IV: Regression and Analysis
Question 1:
| SUMMARY OUTPUT | ||||||||
|
Regression Statistics |
||||||||
| Multiple R |
0.428571 |
|||||||
| R Square |
0.183673 |
|||||||
| Adjusted R Square |
0.081633 |
|||||||
| Standard Error |
0.505076 |
|||||||
| Observations |
10 |
|||||||
| ANOVA | ||||||||
|
df |
SS |
MS |
F |
Significance F |
||||
| Regression |
1 |
0.459184 |
0.459184 |
1.8 |
0.216547 |
|||
| Residual |
8 |
2.040816 |
0.255102 |
|||||
| Total |
9 |
2.5 |
||||||
|
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
|
| Intercept |
2.081633 |
0.462009 |
4.505606 |
0.001987 |
1.016237 |
3.147028 |
1.016237 |
3.147028 |
| X Variable 1 |
-0.10204 |
0.076057 |
-1.34164 |
0.216547 |
-0.27743 |
0.073346 |
-0.27743 |
0.073346 |
There is no statistical difference between on-site and off-site workers before they commence training as indicated by the adjusted r-square value and the resulting p-value.
Question 2:
| SUMMARY OUTPUT | ||||||||
|
Regression Statistics |
||||||||
| Multiple R |
0.920635 |
|||||||
| R Square |
0.847569 |
|||||||
| Adjusted R Square |
0.828515 |
|||||||
| Standard Error |
0.916667 |
|||||||
| Observations |
10 |
|||||||
| ANOVA | ||||||||
|
df |
SS |
MS |
F |
Significance F |
||||
| Regression |
1 |
37.37778 |
37.37778 |
44.48264 |
0.000158 |
|||
| Residual |
8 |
6.722222 |
0.840278 |
|||||
| Total |
9 |
44.1 |
||||||
|
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
|
| Intercept |
-6.22222 |
1.810916 |
-3.43595 |
0.008877 |
-10.3982 |
-2.04624 |
-10.3982 |
-2.04624 |
| X Variable 1 |
1.611111 |
0.241563 |
6.669531 |
0.000158 |
1.054066 |
2.168156 |
1.054066 |
2.168156 |
There is a significant rise in the level of knowledge as a result of training. This means there is a perfect positive correlation between training and increase in the level of expertise for the participants involved in the program ( Coppens et al., 2014) .
Question 3:
| SUMMARY OUTPUT | ||||||||
|
Regression Statistics |
||||||||
| Multiple R |
0.907304 |
|||||||
| R Square |
0.8232 |
|||||||
| Adjusted R Square |
0.8011 |
|||||||
| Standard Error |
0.390499 |
|||||||
| Observations |
10 |
|||||||
| ANOVA | ||||||||
|
df |
SS |
MS |
F |
Significance F |
||||
| Regression |
1 |
5.680083 |
5.680083 |
37.24898 |
0.000288 |
|||
| Residual |
8 |
1.219917 |
0.15249 |
|||||
| Total |
9 |
6.9 |
||||||
|
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
|
| Intercept |
4.958506 |
0.516122 |
9.60723 |
1.14E-05 |
3.768326 |
6.148687 |
3.768326 |
6.148687 |
| X Variable 1 |
-0.48548 |
0.079545 |
-6.10319 |
0.000288 |
-0.66891 |
-0.30205 |
-0.66891 |
-0.30205 |
There is a difference in performance of the professionals, paraprofessionals, and non-professionals in the training outcome. This is confirmed by the correlation of the data, the p-value, t-stat, and adjusted r-square output outlined in the table above.
Question 4:
|
|||||||||
|
Regression Statistics |
|||||||||
| Multiple R |
0.734847 |
||||||||
| R Square |
0.54 |
||||||||
| Adjusted R Square |
0.408571 |
||||||||
| Standard Error |
0.725062 |
||||||||
| Observations |
10 |
||||||||
| ANOVA | |||||||||
|
df |
SS |
MS |
F |
Significance F |
|||||
| Regression |
2 |
4.32 |
2.16 |
4.108696 |
0.066016 |
||||
| Residual |
7 |
3.68 |
0.525714 |
||||||
| Total |
9 |
8 |
|||||||
|
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
||
| Intercept |
8.32 |
0.833032 |
9.987608 |
2.16E-05 |
6.350192 |
10.28981 |
6.350192 |
10.28981 |
|
| X Variable 1 |
0.6 |
0.512696 |
1.170284 |
0.280183 |
-0.61233 |
1.812333 |
-0.61233 |
1.812333 |
|
| X Variable 2 |
-1.44 |
0.502337 |
-2.8666 |
0.024109 |
-2.62784 |
-0.25216 |
-2.62784 |
-0.25216 |
|
There is no significant difference in the gender and the level of confidence.
Worksite experience affects the level of confidence an individual possesses.
There is a string interaction between worksite and gender in their influence on the level of an individual’s confidence.
Part V: Summary of Findings
This study focused on understanding how various demographic factors affect the delivery of effective services in the workplace, with particular focus on clinical settings. The main emphasis of the paper was on assessing how training, knowledge before training, knowledge after training, age, gender, worksite, and confidence are correlated. The study finds that the level of confidence and service delivery improves significantly after training. Gender and age do not determine the level of confidence and acquired knowledge after training ( Hughes et al., 2008) . Therefore, staff training has the capacity to allow clinical care providers gain better techniques to manage patients because of improved expert belief, knowledge, support, and coping.
References
Boling, B., & Hardin-Pierce, M. (2016). The effect of high-fidelity simulation on knowledge and confidence in critical care training: An integrative review. Nurse education in practice , 16 (1), 287-293.
Coppens, E., Van Audenhove, C., Iddi, S., Arensman, E., Gottlebe, K., Koburger, N., ... & Székely, A. (2014). Effectiveness of community facilitator training in improving knowledge, attitudes, and confidence in relation to depression and suicidal behavior: Results of the OSPI-Europe intervention in four European countries. Journal of affective disorders , 165 , 142-150.
Figueroa, M. I., Sepanski, R., Goldberg, S. P., & Shah, S. (2013). Improving teamwork, confidence, and collaboration among members of a pediatric cardiovascular intensive care unit multidisciplinary team using simulation-based team training. Pediatric cardiology , 1-8.
Fine, P., Louca, C., & Leung, A. (2017). The Impact of a Postgraduate Learning Experience on the Confidence of General Dental Practitioners. Dentistry Journal , 5 (2), 16.
Hughes, J., Bagley, H., Reilly, S., Burns, A., & Challis, D. (2008). Care staff working with people with dementia: training, knowledge and confidence. Dementia , 7 (2), 227-238.
McDonnell, A., Sturmey, P., Oliver, C., Cunningham, J., Hayes, S., Galvin, M., ... & Cunningham, C. (2008). The effects of staff training on staff confidence and challenging behavior in services for people with autism spectrum disorders. Research in Autism Spectrum Disorders , 2 (2), 311-319.
