Meta-Analysis of Nurses’ Job Satisfaction

Job fulfillment in nursing fronts a decisive test to healthcare institutions since the outlay of work is elevated and shortages are widespread. The supplies are not adequate to meet the necessities as the nurses’ demands augment. As anticipated by the Bureau of Labor statistics (2005), supplementary jobs of regarding 703,000 would be put into place for listed nurses between 2004 and 2014, which is above the number of those by now employed by 29%. As the baby boomers begin to stop working, there will be a deficit of nurses anticipated to be roughly 400,000 to look after the populace. A number of factors that add to job contentment and preservation of nurses recognized to recount in numerous work fulfillment theories, instruments and abstract models (Best & Thurston, 2004). The relationships between work contentment and the interrelated factors contrast from research to research and the person study results appear disagreeing with each other. This is for the reason that the current research investigation carried out on nursing work contentment was done about a decade ago, while remarkable alterations has been experienced in the healthcare business. The meta-analysis study carried out was to offer a better perceptive to the factors that link with work contentment.

Meta-analysis is a geometric course of action which allows the fusion of the results of quantitative research to progress the expansion of theory and comprehension, patient heed guide, and strategy improvement (Anderson & Beck, 2003). The meta-analysis recognizes the associations of the stated job contentment variables across lessons that are probable to put forward a better inference of populace than any single research (Cooper & Hedges, 1994).

Two forms of data compilation are used to conceptual and code information – a data generalization form identifying the information to extort and a quality rating scale evaluating the study quality. The data coding form extracted the characteristics of the study, such as design, measures, and size effect from each of the studies. The coded items for each study were sample size and characteristics that included mean age, sex, education, years of experience, and area of nursing specialty. In overall, there were 95% agreements in the coding for the studies with consensus reached for the items where disagreement existed.

A fundamental constituent of the meta-analysis known as qualitative evaluation examined probable coercions to legality of the conclusions. The definitions of a quality study be predisposed to be expressive, and a scale developed to calculate quality refers to the effectiveness trials that focus on randomized controlled trials and highlights internal soundness. Even though eminence evaluation is important for meta-analysis, more work needs to make out the norm for insertion in such appraisal. In addition, meta-analyses information needs to offer images of the dealings of quality review used so that a conclusion can be made on the legitimacy of the procedure. The calculating measure for the study superiority used pointers that were expected to be appropriate to the articles type included in the meta-analysis. Because all the reports in the meta-analysis had a descriptive correlation design and indicators of quality assessment for this meta-analysis were developed to be consistent and relevant to this type of design.

A software package of Inclusive Meta-Analysis was used to demeanor the information examination (Borenstein & Rothstein, 1999). The connections between job contentment and other linked constructs were removed from the researches and examined using the Z and Q-statistics for the correlation. Fisher’s r-to-z conversion produced the normalized distributions and stabilized variances. A mean z-value, weighted by the sample size, was calculated using 95% con?dence intervals (CIs). The Q-statistic determined if the dispersion sizes of effect around the mean were greater than the expected from sampling error. The Q-statistic allocates as a Chi-square with k-1 degrees of freedom, where k becomes the number of effect sizes (Cooper & Hedges, 1994). The z-to-r conversion was then performed and the mean-weighted r-value reported with 95% CIs.

To verify the subsistence of periodical bias, the fail-safe N calculation was used. Publication bias can be safely discarded when the fail-safe N exceeds 5K + 10, where K is the number of studies (Rosenthal, 1984). The fail-safe N for sovereignty was 95, job stress – 234, and for nurse–physician group effort – 40. These results specified that the periodical partiality in the meta-analysis was improbable.

A number of limitations are nearby in this meta-analysis. For example, only published studies were included in the studies. Exclusions of the renegade literature may guide to the relations to be over-calculated, even though researchers have found no differences associated to the insertion or elimination of unpublished literature (Conn, Valentine, Cooper, & Rantz, 2003). Likewise, the results are contradictory because including only studies published in English leads to overestimation. In this meta-analysis, publication bias was tested using the fail-safe N technique, which is a statistical method indicating that publication bias was unlikely. In addition, because of increased time and costs, there were no attempts made to contact authors for additional information.

The outcomes from the studies only link to the registered nurses in inpatient and outpatient settings. However, the findings can be accommodating for inpatient and outpatient nurse practitioners, nurse educators preparing clinical experiences for nursing students and nurse leaders interested in humanizing the working environment of nurses. The meta-analysis may have been preventive in its inclusion criteria, but the illustration included a wide group of nurses from different surroundings and countries that made it potentially pertinent to a wider population.