Survey monkey tool was used facilitate responses of the questionnaire instrument. This has its unique data analysis technique. Specific to Monkey Surveys’ retrieval and processing of data are five steps, which ought to be followed distinctly. First it is viewing the survey responses. All responses pertaining to each page are saved. They are then displayed in the analyze section when the navigation button is clicked by respondents. After this mechanism the next survey page shows up. Here three types of data are be scrutinized. They are the response summary; individual responses (where the research has access to soft that can delete invalid responses) and the custom report which eventually is surfaces after editing and deleting ( SurveyMonkey Help Center, 2013).
Secondly, responses have to be filtered. This can be accessed using the filter button. Filtering assists the researcher in organizing and viewing subsets of data for advanced analysis. Importantly this data will only display the set of full responses which matches the filter criteria. This facilitates finding patterns in the database. Three types of filters are available for application. They are filter by response, filter by properties and filter by collector (SurveyMonkey Help Center, 2013).
Thirdly is analyzing responses through crossfading. This device can be activated by clicking on the crosstab survey response button. The process offers comparative analysis of responses by establishing side by side columns in a table format. In the fourth phase the research can now download responses. A professional absorbed in PDF, HTML, XML, CSV, XLS and *SPSS (*GOLD/PLATINUM only) are available upon request for use (SurveyMonkey Help Center, 2013). .
In the fifth stage data is analyzed and can be shared. Sharing is advocated since it allows access to survey results without giving the public entry into the researcher’s Survey Monkey account (SurveyMonkey Help Center, 2013). After completing this online data processing procedure other data software programs could be applied for efficacy.
The data analysis technique adapted in this research project emerges from a quantitative research design. This type of design is applied in scientific models where theories are generated and hypotheses must be tested. Instruments must be developed as was done previously in the early sections of this proposal. The specific instrument is a questionnaire with items. There must also be a method of measurement. In this case it is application of ANOVA. Some quantitative models encompass experimental control and manipulation of variables. The variables contained in this research are amplified in 19 research questions tendered to be answered (Belle, Gerald, 2008)
However, there will be no experimental control in this study since it is a survey, but collection will embrace retrieval of empirical data. Eventually, a data processing and analysis model will be adapted consistent with a quantitative design.
Techniques for analyzing data
(ANOVA) will be employed as the data analysis technique model. Usually, ANOVA is used in the analysis of comparative experiments especially, when the researcher predicts different outcomes in the hypothesis. However, the technique would be applied here to analyze data retrieved from a survey. Also, ‘the statistical significance of an experiment is determined by a ratio of two variances. This ratio is independent of several possible alterations to the experimental observations: Adding a constant to all observations does not alter significance. Multiplying all observations by a constant does not alter significance. So ANOVA statistical significance results are independent of constant bias and scaling errors as well as the units used in expressing observations’ (Boanas & and Renton, 2000).
The difference in application of ANOVA to this research is applying its logic whereby calculations can be demonstrated as computing a number of means and variances, by dividing two variances and comparing the ratio to a handbook value in determining statistical significance. The variances will emerge from questionnaire responses after data analysis software is applied to facilitate classification, differentiation and assembling of data (Boanas & and Renton, 2000).
Beside survey monkey peculiar data analysis process other recommended software for analyzing questionnaire responses in this project, is the Statistical Product and Service Solutions (SPSS).This software is reliable and very popular among quantitative researchers. Even though, it is extremely powerful the software is very easy to manipulate. Programs are files designed with a help menu to guide students into coding questionnaire responses in preparation for calculation of means, standard deviation and variances, chi-square; t-tests and a variety of other statistical applications including ANOVA. Designing of graphs as well as data charting is facilitated on this software program too (Boanas & and Renton, 2000).
Rationale for Analysis chosen
The objective of this research paper is to elucidate the causes of the nursing shortage in the healthcare sector. The data will be organized into three different platforms. Questionnaires will be used in seeking responses from participants. For these reasons, the chosen data analysis procedure (ANOVA) will be essential in showcasing the level of differences in the variables under study.
After application of the SPSS software to the initial data analysis process ANOVA adaptations will be applied because analysis of variance occurring in the hypothesis and 19 research questions must be clarified. These clarifications can be achieved only through ANOVA in this specific case when the research seeks to describe as phenomenon such as nursing shortage among a population of nurses.
An important advantage of ANOVA is its computational ability in software programs such as SPSS. Essentially, its structural additive model facilitates solution of additive coefficients through simple algebra rather than by matrix calculations. Twenty-first century mechanical calculators welcome this simplicity. Also, statistical significance determination requires access to F function tables, which are all found in software programs (Boanas & and Renton, 2000).
Interpretation of Analysis Results
The analysis results will be interpreted through graphical display and explanation of descriptive statistics. The hypothesis will be tested for its significance. Depending on the statistical results it will be proven valid or invalid. This can only be interpreted based on the findings of ANOVA calculations. Research questions will also be tendered for variance level identifications. Variances occurring in each question will be compared for an overall interpretation of results based on the statistical test results. These results will, predict the causes of nursing shortages as it pertains to responses retrieved from this survey.
Scope of the Study
The student population pursuing or interested in nursing course will be targeted touching on relevant causes of the nursing shortage that should be addressed. This will include the relevance of the nursing training curriculum, methodologies that the trainers use in training the nurses, retention efforts for the registered nurses, staffing models that hospitals and employment authority’s use, and increasing the revenue that governments allocate to the relevant ministries associated with nursing. The survey shall be conducted within the university environment.
Recommendations
Research has indicated that the major causes of the nursing shortages accrue mostly from human errors in various decision-making aspects. The decisions that people make concerning the field of nursing lead to shortfalls of various degrees in the field. Here are some of the recommendations that will help different authorities and relevant stakeholders in determining on how to deal with the issue.
First, it is imperative to increase the quality of reimbursement in the health division in order to promote the worth of nurses. This would lure individuals to train as professional nurses, and it will make the field as lucrative as other fields of career (Cohen & Sherrod, 2003).
Secondly, it is necessary to improve and increase recruitment of nurses. This will help to subsidize the high ratio of nurse to patient. Recruitment of nurses will help to pull down the rates of shortages. Retention is also an aspect that should be considered at all costs. There should be strategies that will ensure that registered nurses do not leave the profession for other lucrative professions. Various strategies can help in achieving this point, like remuneration, and reviewing the nursing working conditions, among others.
Further, there are radical reforms that need to be evaluated within the next few years in order to improve the situation in the nursing field. The reforms regard intervention in the policies regarding healthcare provision. Some of the reforms are macroeconomic and healthcare sector financing, positive practice environment, and recruitment and retention of healthcare workers and nurses (Feldman, 2003). The focus on recruitment and retention strategies may concentrate on retaining nurses who are likely to retire at an average age of 44.5 years by 2010. This will ameliorate the projected shortage about 260,000 nurses by 2025 (Buerhaus, Auerbach & Staiger, 2009). In most cases, effort to retain nurses will ease on cost of turnover and increase better and quality.
All countries around the world have to strive to attain self-sufficiency in terms of the healthcare workforce without creating adverse effects in other countries. For instance, over the past few years, Philippine has been producing many nurses, a situation that has led to many of them migrating to the United States of America. Self-sufficiency regards to the ability of a country, or a state, to supply the number of required healthcare providers at a given time, and the ability to retain and sustain the providers conveniently (Sobon-Sensor, 2012). Many countries have failed to retain such a status, and have ended up on either side of importing or exporting nurses.
Federal legislation has provided funding to all manner of nursing profession. The U.S congress in 2009 passed Nurse Education Expansion and Development act (NEED). At policy level, the American Association of Colleges has taken upon itself to address the root cause of nursing shortage by giving college resources to impart more skills to new nurses (AACC, 2009). According to the Federation of Nurses and Health Professionals survey, potential solutions to the nursing problem lay with increased staffing (43%); less administrative roles performed by nurses (34%); high wages (27%); more involvement and engagement in decision making (14%); more flexibility (8%); limits of floating (8%) and better hours schedule; other job progression issues were refresher courses (56%); more staff support (55%); listening bodies like unions, performance based salary and work place childcare (44%) (Federation of Nurses and Health Professionals, 2001). The inter-departmental health council offers a suggestion that degree holders should provide nursing care in complicated clinical situations. They argue that there should be a team of captains performing think tank functions for planning and directing or giving personal or group care to individuals.
Higher learning institutions like colleges and universities should reduce age and nursing training college period to rejuvenate nursing recruitment. This will allow a reservoir of potential nurses interested in simple care of the sick to perform nursing practice. The government should provide enough subsidies for training of nurses. Expand training institutions to allow other institutions like technical institutes, junior and community colleges. Another option would be making training in nursing mandatory. The nursing profession continues to face an ever-growing challenge in the global village across the world. While the challenges are acute in the U.S, the same scenario is replicated in Europe and developing countries (Nursing, 2010).
Andrist, Patrice and Wolf (2006) jointly indicate that nursing shortages varydepending on each country’s characteristics of its care needs. However, the shortage is ultimately universal and same in all nations of the world. This is because as one can see from the above discussion, the causes and possible interventions are identical. It is possible for the United Nations to intervene and pass professional guidelines that will influence the field hence bring in changes that will ensure resuscitation of the nursing profession. There is the need for incentives in the field in order to entice the young generations to get into the field. This will ensure the security of the work force in the future of the nursing field. Each country of the world understands the consequences of understaffed nursing field, and should stress on maintaining workers and strife to retain those already in the field.
Conclusion
This research proposal has been an unforgettable tremendous learning experience. It taught me how scientific research techniques must be applied for knowledge to be added as evidence in any discipline. In this case it was nursing shortage and its impact on the nursing profession as it relates of quality of care received from inadequate staffing.
For the next project I would write a plan and work with it. Components that were most challenging pertained data analysis. Collecting the data using a soft ware such a survey monkey tool sounds intriguing, but what next? Here is where research begins into finding out how to assessable, display and interpret. The intriguing part obviously was the literature review looking at previous studies and what is already known about nursing shortage. I plan using this proposal to conduct an actual research and have it published in a nursing journal.
References
American Association of Colleges of Nursing (2010). "The President Offers Sustained Support for Nursing Education and." 1 February 2010. American Association of Colleges of Nursing. 3 March 2010. Retrieved on 7 June 2012 from www.aacn.nche.edu/Government.
Buchan, J., & Aiken, L. (2008).Solving nursing shortages: a common priority. Journal of
Clinical Nursing, 17(24), 3262-3268.
Bureaus, P., Auer Bach, D. and Stagier, D. (2009). The Recent Surge In Nursing Employment: Causes and Implications. Health Affairs. 657-668.
Boanas, G., & and Renton, F (2000). Quantitative Data Analysis Software
for Student Home Use. Retrieved on August 12th, 2013 from
http://www.gold.ac.uk/media/d702.pdf
Belle, Gerald van (2008). Statistical rules of thumb (2nd ed.). Hoboken, N.J: Wiley
Federation of Nurses and Health Professionals, (2001). The Nurse Shortage: Perspectives
Houser, J. (2008). Nursing research: Reading, Using, and Creating Evidence. Sudbury, MA:
Jones and Bartlett Publishers.
Littlejohn, L., et al (2012). Nursing Shortage: A Comparative Analysis.International
McDonald, G. M. (2000). Cross-Cultural Methodological Issues in Ethical Research, Journal of Business Ethics, 27, 89–104.
Miyazaki, A. & Taylor. K. (2008). Research Interaction Biases and Business Ethics
Research: Respondent Reactions, Business Ethics, 81, 779-795.
Survey monkey help center (2013).Retreieved on August 20th 2013 from
https://www.surveymonkey.com/login.aspx?pid=G24N
Appendix – Research questionnaire posted on Monkey Survey
1. What is your level of involvement in the nursing community?
[ ] Very Involved [ ] Involved [ ] Neutral [ ] Seldom Involved [ ] Never Involved
2. Have you witnessed or experienced conditions in your line of work that have caused deterioration or a contribution to turnover?
[ ] Strongly Disagree [ ] Disagree [ ] Neutral [ ] Agree [ ] Strongly Agree
3. What is the magnitude and extent of nursing shortage in your workplace?
[ ] Excellent [ ] Good [ ] Neutral [ ] Bad [ ] Very Bad
4. How long have you been in a working relationship with the nursing community?
[ ] Less than 1 year [ ] 1-5 years [ ] 6-10 years [ ] 11-15 years [ ] More than 16 years
5. What is the likely effect of increased enrollment into nursing education in relation to a decreased level of anxiety on nurses in your workplace?
[ ] Somewhat Likely [ ] Not Likely [ ] Neutral [ ] Likely [ ] Strongly Likely
6. Do you remember having special difficulty as you attempted to enroll in nursing programs?
[ ] Strongly Disagree [ ] Disagree [ ] Neutral [ ] Agree [ ] Strongly Agree
7. How many nursing schools have turned you down initially or for advanced practice nursing?
[ ] None [ ] One [ ] Two [ ] Three [ ] Four
8. How far outside your community did you have to travel to pursue nursing education?
[ ] 5-10 miles [ ] 15-20 miles [ ] 25-30 miles [ ] 35-40 miles [ ] 45-50 miles
9. Does your employer encourage or offer advance nursing education opportunities in your present job description?
[ ] Always [ ] Usually [ ] Half the time [ ] Seldom [ ] Never
10. Do you experience value at your work place?
[ ] Strongly Disagree [ ] Disagree [ ] Neutral [ ] Agree [ ] Strongly Agree
11. Is your line of work either supportive of nursing or do you actually do the job?
[ ] Somewhat Likely [ ] Not Likely [ ] Neutral [ ] Likely [ ] Strongly Likely
12. Which level of nursing would you describe yourself in?
[ ] CNA [ ] Diploma in Nursing [ ] Associates Degree in Nursing [ ] Bachelor of Science in Nursing [ ] Master of Science of Nursing
13. Do you participate in decision making policy, governing nursing education, employment or training at your workplace?
[ ] Always [ ] Usually [ ] Half the time [ ] Seldom [ ] Never
14. What is the closest category of your age?
[ ] 20-25 [ ] 26-31 [ ] 32-37 [ ] 38-43 [ ] 48-53
15. What most closely describes your ethnicity?
[ ] White [ ] African- American [ ] Hispanic [ ] Chinese [ ] Other
16. How long was your training for the level of nursing that you have accomplished?
[ ] 3-6 months [ ] 9-12 months [ ] 14-24months [ ] 26-36 months [ ] 37-48 months
17. How many people do you know that wanted to be a nurse and was turned down?
[ ] 0-2 [ ] 3-4 [ ] 5-6 [ ] 7-8 [ ] 9-10
18. Are you support personnel or administrator or policy maker of nursing activities?
[ ] Yes [ ] No [ ] Sometimes [ ] Never
19. What level of administration do you participate in concerning nursing policy?
[ ] Front line supervisor [ ] Middle management [ ] Executive management [ ] None
