Analysis Of Work Commitment And Intention To Leave Among Nurses

Inferential Statistics and Hypotheses

In the present assignment we use inferential statistics to evaluate the intention to leave of the nurses. For the inferential statistics we use t-test, ANOVA and regression analysis.

Null Hypothesis: There is no difference in work commitment of nurses across Gender

Alternate Hypothesis: There are differences in work commitment of nurses across Gender

Decision Rule: The decision rule at the alpha level of 0.05 level of significance that is beyond 95 % confidence interval is to accept the null hypothesis if p value < 0.05 or equal to 0.05. However, if the test statistic value falls within the 95 % confidence interval then null hypothesis should be rejected and alternate hypothesis should be accepted. It will be interpreted that there exists enough statistical evidence regarding the fact that work related stress has statistically significant impact upon the intention to leave off the nurses (Black, 2016).

t-test: To test the hypothesis independent sample t-test is used.

Table 1: Independent Samples Test

	Commitment
Equal variances assumed	Equal variances not assumed
Levene’s Test for Equality of Variances	F	1.462
Sig.	.228
t-test for Equality of Means	T	.808	.755
Df	184	69.016
Sig. (2-tailed)	.420	.453
Mean Difference	2.282	2.282
Std. Error Difference	2.824	3.023
95% Confidence Interval of the Difference	Lower	-3.289	-3.748
Upper	7.854	8.313

Interpretation: From table 1 it is found that t(184) = 0.808, p-value = 0.420. Since p-value (0.420) is more than the significance level (0.05) hence we do not reject the Null Hypothesis.

Discussion: Thus it can be inferred that there is no significant difference in intention to leave between male and female nurses.

Null Hypothesis: There is no difference in work commitment of nurses across Ethnicity

Alternate Hypothesis: There are differences in work commitment of nurses across Ethnicity

Decision Rule: The decision rule at the alpha level of 0.05 level of significance that is beyond 95 % confidence interval is to accept the null hypothesis if p value < 0.05 or equal to 0.05. However, if the test statistic value falls within the 95 % confidence interval then null hypothesis should be rejected and alternate hypothesis should be accepted. It will be interpreted that there exists enough statistical evidence regarding the fact that work related stress has statistically significant impact upon the intention to leave off the nurses.

One-way ANOVA : To test the hypothesis one-way ANOVA is used.

Table 2: ANOVA

Commitment
	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	354.463	3	118.154	.425	.735
Within Groups	50626.276	182	278.166
Total	50980.739	185

Interpretation: From table 2 it is found that F(3,182) = 0.425, p-value = 0.735. Since p-value (0.735) is more than the significance level (0.05) hence we do not reject the Null Hypothesis. Discussion: Thus it can be interpreted that there is no significant difference in intention to leave between ethnicity of nurses.

Research Questions: The research question is concerns with the ability of work related stress to influence the intention to leave of the nurses. Thus the relevant research question can be highlighted as follows:

• To what extent work related stress renders impact upon the intention to leave of the nurses?

t-test results

Null Hypothesis (H₀) = Work related stress renders significant impact upon the intention to leave of the nurses.

Alternate Hypothesis (H₁) = Work related stress has no impact upon the intention to leave of the nurses.

Decision Rule: The decision rule at the alpha level of 0.05 level of significance that is beyond 95 % confidence interval is to accept the null hypothesis if p value < 0.05 or equal to 0.05. However, if the test statistic value falls within the 95 % confidence interval then null hypothesis should be rejected and alternate hypothesis should be accepted. It will be interpreted that there exists enough statistical evidence regarding the fact that work related stress has statistically significant impact upon the intention to leave off the nurses (Anderson et al., 2017).

Analysis:

Table 3: Descriptive Statistics

	Mean	Std. Deviation	N
Commitment	66.07	16.600	186
Work  Related Stress	15.92	4.363	186

The statistical valuations incorporate the fact that mean values of work related stress is 15.92 and the mean of 66.07. While the respective standard deviation is 4.363 and 16.600. The total number of sample population 186.

Table 4: Correlations

	Commitment	Work Related Stress
Pearson Correlation	Commitment	1.000	-.206
Work Related Stress	-.206	1.000
Sig. (1-tailed)	Commitment	.	.002
Work Related Stress	.002	.
N	Commitment	186	186
Work Related Stress	186	186

From the correlation table it is seen that the Pearson correlation between work related stress and that of work commitment is -0.206. This reflects the fact that the correlation that exists between work commitment and work related stress is negatively and moderately correlated.

Based on the sample population there is statistically significant evidence that shows that the 1 tailed significance is 0.002 which is lower than the alpha level of the p value taken under consideration which is 0.05. Due to the reason that 0.002 < 0.05 hence, the correlation between work commitment and that of work related stress is – 0.206 which shows that the correlation is negative and the correlation is statistically significant as there exists enough evidence that supports the fact that there is prevalence of significant correlation between work related stress and work commitment within the nurses.

Table 5: Model Summary

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.206a	.042	.037	16.289
a. Predictors: (Constant), Work Related Stress

The R square value represent the percentage of variation of the dependent variable that is explainable by the independent or explanatory variable which is the work related stress. R square is thus considered as the coefficient of determination and the correlation measurement is considered to be the goodness of fit. It is been seen that the value of R square is 0.042 and hence nearby 4.2 % of work commitment is predictable by the work related stress. Thus about 4.2 % of variation in the work commitment is due to the work related stress.

ANOVA results

Table 6: ANOVA

Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	2160.626	1	2160.626	8.143	.005b
Residual	48820.113	184	265.327
Total	50980.739	185
a. Dependent Variable: Commitment

Table 7: Coefficients

Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	78.538	4.530		17.338	.000
WorkRelatedStress	-.783	.274	-.206	-2.854	.005
a. Dependent Variable: Commitment

Based on the values the regression equation can be formulated as follows:

• Y = 78.538 – 0.783*Work Related Stress

Where the coefficient is – 0.783 and the intercept is 78.538. -0.783 is the slope of the line and 78.538 is the intercept.

Research Questions

The research question is concerns with the ability of Work competency level to influence the intention to leave of the nurses. Based on the purpose of the research, the research questions are incorporated in order to predict the variation and impact upon nurses’ work commitment by one of the parametric factors of intention to leave which is Work competency level. Thus the relevant research question can be highlighted as follows:

• To what extent Work competency level renders impact upon the intention to leave of the nurses?

Null Hypothesis

The null and the alternate hypothesis are:

Null Hypothesis (H₀) = Work competency level renders significant impact upon the intention to leave/work commitment of the nurses.

Alternate Hypothesis (H₁) = Work competency level has no impact upon the intention to leave/ work commitment of the nurses.

Decision Rule

Based on the null and alternate hypotheses, the respective decision rule can be reflected as follows:

Decision Rule: The decision rule at the alpha level of 0.05 level of significance that is beyond 95 % confidence interval is to accept the null hypothesis if p value < 0.05 or equal to 0.05. However, if the test statistic value falls within the 95 % confidence interval then null hypothesis should be rejected and alternate hypothesis should be accepted. It will be interpreted that there exists enough statistical evidence regarding the fact that Work competency level has statistically significant impact upon the intention to leave off the nurses.

Table 8: Descriptive Statistics

	Mean	Std. Deviation	N
Commitment	66.07	16.600	186
Work Competency Level	20.85	5.144	186

The statistical valuations incorporates the fact that mean values of Work competency level is 20.85 and the mean of 66.07. While the respective standard deviation is 5.144 and 16.600. The total number of sample population 186.

Table 9: Correlations

	Commitment	Work Competency Level
Pearson Correlation	Commitment	1.000	-.151
Work Competency Level	-.151	1.000
Sig. (1-tailed)	Commitment	.	.020
Work Competency  Level	.020	.
N	Commitment	186	186
Work Competency Level	186	186

From the correlation table it is seen that the correlation coefficient in case of Work competency level and that of work commitment is – 0.151. This reflects the fact that the correlation that exists between work commitment and Work competency level is negatively and moderately correlated.

Based on the sample population there is statistically significant evidence that shows that the 1 tailed significance is 0.02 which is lower than the alpha level of the p value taken under consideration which is 0.05. Due to the reason that 0.02 < 0.05 hence, the correlation between work commitment and that of Work competency level is – 0.151 which shows that the correlation is negative and the correlation is statistically significant as there exists enough evidence that supports the fact that there is prevalence of significant correlation between Work competency level and work commitment within the nurses.

Correlation analysis

The dependent variable in the analysis is the work commitment and hence the impact of the Work competency level upon that of the work commitment of the nurses is being evaluated. Hence the response variable is work commitment and the explanatory variable is Work competency level.

Table 10: Model Summary

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.151a	.023	.018	16.454
a. Predictors: (Constant), Work Competency Level

The R square value represent the percentage of variation of the dependent variable that is explainable by the independent or explanatory variable which is the Work competency level. R square is thus considered as the coefficient of determination and the correlation measurement is considered to be the goodness of fit. It is been seen that the value of R square is 0.023 and hence nearby 2.3 % of work commitment is predictable by the Work competency level. Thus about 2.3 % of variation in the work commitment is due to the Work competency level.

Table 11: ANOVA

Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	1166.111	1	1166.111	4.307	.039b
Residual	49814.628	184	270.732
Total	50980.739	185
a. Dependent Variable: Commitment
b. Predictors: (Constant), Work Competency Level

Table 12: Coefficients

Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	76.244	5.049		15.100	.000
Work Competency Level	-.488	.235	-.151	-2.075	.039
a. Dependent Variable: Commitment

Based on the values the regression equation can be formulated as follows:

• Y = 76.244 – 0.488* Work Competency Level

Where the coefficient is -0.488 and the intercept is 76.244.

Research Questions

The research question is concerns with the ability of Opportunities for development to influence the intention to leave of the nurses. Based on the purpose of the research, the research questions are incorporated in order to predict the variation and impact upon nurses’ work commitment by one of the parametric factors of intention to leave which is Opportunities for development. Thus the relevant research question can be highlighted as follows:

• To what extent Opportunities for development renders impact upon the intention to leave of the nurses?

Null Hypothesis

The null and the alternate hypothesis are:

Null Hypothesis (H₀) = Opportunities for development renders significant impact upon the intention to leave/work commitment of the nurses.

Alternate Hypothesis (H₁) = Opportunities for development has no impact upon the intention to leave/work commitment of the nurses.

Decision Rule

Based on the null and alternate hypotheses, the respective decision rule can be reflected as follows:

Decision Rule: The decision rule at the alpha level of 0.05 level of significance that is beyond 95 % confidence interval is to accept the null hypothesis if p value < 0.05 or equal to 0.05. However, if the test statistic value falls within the 95 % confidence interval then null hypothesis should be rejected and alternate hypothesis should be accepted. However, if it be found to have its presence within the 5 % level of significance then null hypothesis will be accepted and the alternative hypothesis will be accepted. It will be interpreted that there exists enough statistical evidence regarding the fact that Opportunities for development has statistically significant impact upon the intention to leave off the nurses.

Regression analysis

Univariate Data Analysis

Table 13: Descriptive Statistics

	Mean	Std. Deviation	N
Commitment	66.07	16.600	186
Opportunities for Development	18.51	4.843	186

The statistical valuations incorporates the fact that mean values of Opportunities for development is 18.51 and the mean of 66.07. While the respective standard deviation is 4.843 and 16.600. The total number of sample population 186.

Table 14: Correlations

	Commitment	Opportunities for Development
Pearson Correlation	Commitment	1.000	-.088
Opportunities for Development	-.088	1.000
Sig. (1-tailed)	Commitment	.	.115
Opportunities for Development	.115	.
N	Commitment	186	186
Opportunities for  Development	186	186

The value of the correlation coefficient in case of Opportunities for development and that of work commitment is -0.088. This reflects the fact that the correlation that exists between work commitment and Opportunities for development is negatively and moderately correlated.

Based on the sample population there is statistically significant evidence that shows that the 1 tailed significance is 0.115 which is higher than the alpha level of the p value taken under consideration which is 0.05. Due to the reason that 0.115 > 0.05 hence, the correlation between work commitment and that of Opportunities for development is – 0.115 which shows that the correlation is negative and the correlation is statistically insignificant as there does not exists enough evidence that supports the fact that there is prevalence of significant correlation between Opportunities for development and work commitment within the nurses.

The dependent variable in the analysis is the work commitment and hence the impact of the Opportunities for development upon that of the work commitment of the nurses is being evaluated. Hence the response variable is work commitment and the explanatory variable is Opportunities for development.

Table 15: Model Summary

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.088a	.008	.002	16.580
a. Predictors: (Constant), Opportunities for Development

The R square value represent the percentage of variation of the dependent variable that is explainable by the independent or explanatory variable which is the Opportunities for development. R square is thus considered as the coefficient of determination and the correlation measurement is considered to be the goodness of fit. It is been seen that the value of R square is 0.008 and hence nearby 0.8 % of work commitment is predictable by the Opportunities for development. Thus about 0.8 % of variation in the work commitment is due to the Opportunities for development.

Table 16: ANOVA

ANOVAa
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	398.994	1	398.994	1.451	.230b
Residual	50581.745	184	274.901
Total	50980.739	185
a. Dependent Variable: Commitment
b. Predictors: (Constant), Opportunities for Development

Table 17: Coefficients

Coefficients
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	71.682	4.816		14.886	.000
Opportunities for Development	-.303	.252	-.088	-1.205	.230
a. Dependent Variable: Commitment

Based on the values the regression equation can be formulated as follows:

• Y = 71.682 – 0.303*Opportunities for Development

Where the coefficient is – 0.303 and the intercept is 71.682.

-0.303 is the slope of the line and 71.682 is the intercept.

Research Questions

The research question is concerns with the ability of Professional support received to influence the intention to leave of the nurses. Based on the purpose of the research, the research questions are incorporated in order to predict the variation and impact upon nurses’ work commitment by one of the parametric factors of intention to leave which is  Professional support received. Thus the relevant research question can be highlighted as follows:

• To what extent Professional support received renders impact upon the work commitment/ intention to leave of the nurses?

Impact of Work Competency Level

Null Hypothesis

The null and the alternate hypothesis are:

Null Hypothesis (H₀) = Professional support received renders significant impact upon the work commitment/ intention to leave of the nurses.

Alternate Hypothesis (H₁) = Professional support received has no impact upon the work commitment/intention to leave of the nurses.

Decision Rule

Based on the null and alternate hypotheses, the respective decision rule can be reflected as follows:

Decision Rule: The decision rule at the alpha level of 0.05 level of significance that is beyond 95 % confidence interval is to accept the null hypothesis if p value < 0.05 or equal to 0.05. However, if the test statistic value falls within the 95 % confidence interval then null hypothesis should be rejected and alternate hypothesis should be accepted. It will be interpreted that there exists enough statistical evidence regarding the fact that Professional support received has statistically significant impact upon the intention to leave off the nurses.

Univariate Data Analysis

Table 18: Descriptive Statistics

	Mean	Std. Deviation	N
Commitment	66.07	16.600	186
Professional Support Received	21.26	4.874	186

The statistical valuations incorporates the fact that mean values of Professional support received is 21.26 and the mean of 66.07. While the respective standard deviation is 4.874 and 16.600. The total number of sample population 186.

Table 19: Correlations

Correlations
	Commitment	Professional Support Received
Pearson Correlation	Commitment	1.000	-.138
Professional Support Received	-.138	1.000
Sig. (1-tailed)	Commitment	.	.030
Professional Support Received	.030	.
N	Commitment	186	186
Professional Support Received	186	186

The value of the correlation coefficient in case of Professional support received and that of work commitment is -0.138. This reflects the fact that the correlation that exists between work commitment and Professional support received is negatively and moderately correlated.

Based on the sample population there is statistically significant evidence that shows that the 1 tailed significance is 0.03 which is lower than the alpha level of the p value taken under consideration which is 0.05. Due to the reason that 0.03 < 0.05 hence, the correlation between work commitment and that of  Professional support received is – 0.138 which shows that the correlation is negative and the correlation is statistically significant as there exists enough evidence that supports the fact that there is prevalence of significant correlation between  Professional support received and work commitment within the nurses.

The dependent variable in the analysis is the work commitment and hence the impact of the Professional support received upon that of the work commitment of the nurses is being evaluated. Hence the response variable is work commitment and the explanatory variable is Professional support received.

Table 20: Model Summary

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.138a	.019	.014	16.485
a. Predictors: (Constant), Professional Support Received

The R square value represent the percentage of variation of the dependent variable that is explainable by the independent or explanatory variable which is the Professional support received. R square is thus considered as the coefficient of determination and the correlation measurement is considered to be the goodness of fit. It is been seen that the value of R square is 0.019 and hence nearby 1.9 % of work commitment is predictable by the Professional support received. Thus about 1.9 % of variation in the work commitment is due to the Professional support received.

Conclusion

Table 21: ANOVA

ANOVAa
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	977.255	1	977.255	3.596	.059b
Residual	50003.484	184	271.758
Total	50980.739	185
a. Dependent Variable: Commitment
b. Predictors: (Constant), Professional Support Received

Table 22: Coefficients

Coefficients
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	76.092	5.422		14.034	.000
Professional Support Received	-.472	.249	-.138	-1.896	.059
a. Dependent Variable: Commitment

Based on the values the regression equation can be formulated as follows:

• Y = 76.092 – 0.472 * Professional Support Received

Where the coefficient is – 0.472 and the intercept is 76.092. -0.472 is the slope of the line and 76.092 is the intercept.

Moreover, the p value reflects that beyond 95 % confidence interval and 5 % level of significance the p value of Professional support received is 0.059 which is more than 0.05. Hence, the null hypothesis is rejected that Professional support received possess weak impact upon the work commitment and the relationship that exists between professional supports received and work commitment of the nurses is insignificant.

Table 23: Descriptive Statistics 

	Mean	Std. Deviation	N
Commitment	66.07	16.600	186
Work Related Stress	15.92	4.363	186
Work Competency Level	20.85	5.144	186
Opportunities for Development	18.51	4.843	186
Professional Support Received	21.26	4.874	186

It is been seen that the lowest standard deviation from mean is observed in case of work related stress where the value is 4.363.

Table 24: Model Summaru

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.231a	.053	.033	16.328
a. Predictors: (Constant), Professional Support Received, Work Related Stress, Work Competency Level, Opportunities for Development

The R square value represent the percentage of variation of the dependent variable that is explainable by the independent or explanatory variable. R square is thus considered as the coefficient of determination and the correlation measurement is considered to be the goodness of fit. It is been seen that the value of R square is 0.53 and hence nearby 53 % of work commitment is predictable by the Opportunities for development. Thus about 53 % of variation in the work commitment is due to the explanatory variables. The adjusted R square is a more reliable test statistic since it takes under consideration the population sample size which interprets the fact that about 33 % of the variation in the work commitment. The standard error measures the variability of the actual work commitment from the predicted value of the work commitment whose value came out to be 16.328.

Table 25: ANOVA

ANOVAa
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	2724.501	4	681.125	2.555	.041b
Residual	48256.238	181	266.609
Total	50980.739	185
a. Dependent Variable: Commitment
b. Predictors: (Constant), Professional Support Received, Work Related Stress, Work Competency Level, Opportunities for Development

Table 26: Coefficients

Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 78.957 5.652 13.971 .000 Work Related Stress -.886 .412 -.233 -2.152 .033 Work Competency Level -.246 .407 -.076 -.604 .547 Opportunities  for Development .636 .441 .186 1.444 .150 Professional Support Received -.256 .396 -.075 -.646 .519

Based on the values the regression equation can be formulated as follows:

• Commitment = 78.957 – 0.886*Work Related Stress – 0.246 *Work Competency Level – 0.636*Opportunities for Development – 0.256*Professional Support Received

Interpretation 

Thus the test is has passed. Moreover, the p value reflects that beyond 95 % confidence interval and 5 % level of significance the p value of work related stress is 0.033 which is less than 0.05. Hence, the null hypothesis is accepted that work related possess strong impact upon the work commitment and the relationship that exists between works related stress and work commitment of the nurses is strongly significant.

Conclusion

In order to understand the relation between Commitment to work and Work Related Stress, Work Competency Level, Opportunities for Development and Professional Support Received both univariate as well multivariate regression analysis was used. In addition, correlation analysis was also used.

The correlation analysis shows that all the four factors Work Related Stress, Work Competency Level, Opportunities for Development and Professional Support Received are negatively correlated with commitment. Moreover, all the four variables are weekly correlated.

The relation of work related stress with commitment shows that with increase in stress, there is a decrease in commitment towards work. Moreover, the coefficient of work related stress is statistically significant. In addition, the predictability of commitment from work related stress is also very weak.

The relation of work competency level with commitment shows that with increase in competency level, there is a decrease in commitment towards work. Moreover, the coefficient of work competency level is statistically significant. In addition, the predictability of commitment from work competency level is also very weak.  

The relation of opportunities for development with commitment shows that with increase in opportunities, there is a decrease in commitment towards work. Moreover, the coefficient of opportunities for development is statistically not significant. In addition, the predictability of commitment from opportunities for development is negligible.

 The relation of professional support received with commitment shows that with increase in professional support, there is a decrease in commitment towards work. Moreover, the coefficient for professional support received is statistically not significant. In addition, the predictability of commitment from professional support received is negligible.

The multivariate analysis shows that four variables can significantly predict commitment. However, the coefficients of Work Competency Level, Opportunities for Development and Professional Support Received are not statistically significant. Moreover, the predictability of commitment from the four variables is also poor. 

References

Black, K. (2016). Business statistics: for contemporary decision making. 9^th Edition. John Wiley & Sons.

Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., & Cochran, J. J. (2017). Essentials of Modern Business Statistics With Microsoft Excel.. South–Western Pub.