NR 505 Week 7: Data Collection, Analysis, Evaluation, Dissemination of Results, and Conclusion
NR 505 Week 7: Data Collection, Analysis, Evaluation, Dissemination of Results, and Conclusion
NR 505 Week 7: Data Collection, Analysis, Evaluation, Dissemination of Results, and Conclusion
The restated PICo question is: “What are nurse practitioners (NPs) experiences in providing care to patients who have fallen in an LTC and fractured bones in the United States?” The data collection method that applies the best for my research topic is a quantitative survey/ questionnaire (Choy, 2014). Surveys are cost effective and can be mailed or emailed to participants. Disseminating the surveys by email is a much faster process than mailing the surveys to participants, but each method will all participants are provided an equal opportunity to join in the survey process. The online option allows for a large, diverse population of NPs to be sampled. The ability to survey large numbers of respondents reduces geographical dependence. The strength of the survey or questionnaire is that it contains closed-ended questions and the answer options are provided. A weakness with the survey/questionnaire is the questions and answers are basic and lack detail. However, the researcher can ask numerous questions about a subject, allowing for flexibility in data analysis. The researcher can also add a section of open -ended questions that allow for short answers. According to Choy (2014), open-ended survey questions can be turned into qualitative data. The best thing about surveys or questionnaires is that from the collected data, researchers can infer respondents’ attitudes, opinions, beliefs, values, and behavior and can generalize or transfer this information across multiple situations (Choy, 2014). The survey/questionnaire will have a pre-test/post-test design. With this method, the same research participants are surveyed on the same variables at multiple times during the study.
To collect the data, researchers will assemble a team of two or three people. This team will call the selected research participants and ask if they would prefer to receive the survey by mail or via email. The team will then send out the first survey (pre-test) to each participant via each respective method chosen. Once the completed surveys have been returned, data collection team members will file the first set of surveys under “completed surveys: phase one.” This process will need to be duplicated three times. Data collection team members will contact participants who did not return completed surveys to ask if they still want to be a part of the study and schedule a time for completed surveys to be returned.
Data Collection Points and Length of Data Collection
As established by pre-test/post-test design, the survey data will be collected at three separate times during the study: at the start of the study, the midpoint of the study, and the end of the study. The survey format and questions will remain the same during each time of dissemination. Ponto (2015) states to guarantee that some data is gathered from as many participants as possible and to ensure consistency of answers per survey participant, collecting data at multiple times is necessary. Ponto (2015) also maintains passing out surveys at three points will address the issue of getting participants to return the surveys on time, allow researchers to compare respondents first set of answers to their second and third set of answers, and provide a measure to safeguard against respondents rushing through the questions. With such a wealth of data, researchers will be able to formulate a more comprehensive view of how to implement fall prevention programs in LTC settings, as well as get an understanding of fall prevention program participants’ attitudes and opinions. The estimated length of time to collect the data for this EBP proposal is twelve weeks. Participants will be given surveys at the beginning of the project, at the six-week mark, and at the 12-week mark.
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Sources of Data
Commonly used quantitative sources of data are found in the form of self-reports like structured interviews, surveys, and tests; structured or recorded observations; In vivo and In vitro biophysiologic methods (Sutton & Austin, 2015). Conducting literature reviews of scholarly articles, documents, and records is also a quantitative source of data (Sutton & Austin, 2015). Self-reports are defined as detailed verbal communications between participants and designated research recorders, usually disseminated in the form of interviews and surveys (Sutton & Austin, 2015). The format for interview must be structured, allowing the interviewer to ask the same questions in the same order and offering no explanation for questions respondents do not understand (Sutton & Austin, 2015). Surveys/questionnaires are self-reports that have been developed to collect written responses from participants (Sutton & Austin, 2015). Quantitative surveys should contain closed-ended, structured questions; some common formats of closed-ended questions are as multiple choice, rank-order, true or false; Likert scale, and differential scale (Sutton & Austin, 2015). The purpose of the questionnaire for this EBP proposed plan is to obtain information about whether participants utilize holistic and complementary cancer treatment effect care plans designed by family nurse practitioners (FNP). If participants do, researchers aim to examine which therapies participants use and their attitudes, beliefs, and opinions regarding these care therapies.
Observational sources of data are collected through visual and auditory methods, should be structured and have a distinct format for how researchers will carry out the observations; furthermore, all observations should be coded to minimize corruption and manipulation of data (Sutton & Austin, 2015). An example of how a structured observation would fit into this research EBP proposal is to create categories of questions for fall prevention program participants to answer. One such category might describe the behavior of participants after they finish a fall prevention program activity in their LTC settings. Observation formats should also contain rating scales to rate participants characteristics and behaviors (Sutton & Austin, 2015). Biophysiologic data collection methods are ideal for nurses. Biophysiologic self-report methods allow nurses to evaluate their how their actions and nursing interventions determine or affect patient outcomes (Sutton & Austin, 2015). Biophysiologic data collection methods also allow nurses to test hypothesis and relates patients’ physiologic functions to common health illnesses (Sutton & Austin, 2015). Conducting a literature review of published correlational studies and relevant health demographic documents and records provides researchers opportunities to compare their study results with the results of similar research studies.
Ensuring Quality Data
To guarantee quality data, I will design a survey or questionnaire that eliminates unnecessary questions by defining the goals of the research then forming those goals into survey questions. While there are no statistical tests for validity, Walonick (2018) suggests the following steps to maintain validity and reliability: Find a participant who agrees to act as a respondent and ask the person to complete the survey. Take note of any clarifying questions the respondent asks about the survey. Take time to note which questions need “fixing” as these are defective. In real life, respondents do not have the chance to ask the survey developer questions. Once the original questions that have clarification issues have been modified, repeat the survey completion process with a new test respondent. Continue this process until there are no more questions from test respondents. This also allows me to keep the survey as short as possible, which safeguards against respondent boredom like skipping over questions. Another way to ensure quality data is to train research staff how to disseminate study information, collect data, and interact with participants (Chen et al., 2014).
Descriptive statistics are the outcome of analyzing and summarizing data. Descriptive statistics “describe” raw data so that it become easier to understand and more meaningful to the purpose of the study (Hayat, Powell, Johnson, Cadwell, 2017). Raw data are just numbers and figures, but with descriptive statistics methods, researchers interpret data to create patterns. Descriptive data methods are limiting because there is no agreed upon format that allows researchers to develop supported conclusions for hypotheses beyond analyzed data (Hayat et al., 2017). Descriptive statistics brings facts, figures, graphs and charts to life. There are two components of descriptive statistics: measures of central tendency and spread are generally utilized to summarize the qualities of the sample population (Hayat et al., 2017). In this EBP proposal, researchers can use descriptive statistics to format raw data about how many nurses have experience in implementing fall prevention and injury programs in clinical settings. Other raw data that can be designed into graphs, charts, and statistics are the ages and injuries of fall prevention program participants. For this EBP proposal, formulating relevant descriptive statistics begins with the development of the survey questions. Researchers can use the information gathered from collected surveys to identify any standard deviations before creating descriptive statistics.
Inferential statistics not only describe but also make inferences, which are predictions about a sample population based on the data collected from the sample population (Hayat et al., 2017). Inferential statistics allow researchers to hypothesize and develop logical conclusions about the research data and correlate it to the sample population (Hayat et al., 2017). Inferential statistics help researchers consider aspects like probability judgements, variation of the same data within the sample population, even question how dependable their observations are (Hayat et al., 2017). The advantage to inferential statistics is they apply to more general conditions and larger populations. Within this EBP proposal, inferential statistics can assist NPs decide with fall prevention techniques are best applied to different age groups and in which settings.
The stakeholders in this EBP proposal are the sample participants, researchers conducting the study, health organizations who have a vested and financial interest in the research project, and anyone in the larger population agreeing or disagreeing with the study and its purpose. Implementing this EBP proposal will improve outcomes for sample participants. Research conducted by Harrison (2017) shows that NPs who collaborate to implement fall prevention programs help reduce fall risk and improve health outcomes for patients. Li et al., (2013) show that implementing the Tai Ji Quan program maximizes senior participation in community-based fall prevention programs. 61% of senior participants who completed the program reported they continue weekly Tai Ji Quan practice on their own. Also, research by Breimaier, Halfens, & Lohrmann (2015) show that nurses’ knowledge on fall prevention increased 4.1% and how to access the Falls Clinical Practice Guideline (CPG)
Researchers experience improvements since they can now share credible results and outcomes with colleagues, sample participants, and research funders. This EBP proposal can help establish which fall prevention program data is generalizable and transferable to larger populations. It also provides a template for sound quantitative research design for understanding fall related fractures phenomenon. Researchers have established sound criteria on how NPs in LTC settings can implement or improve fall prevention initiatives and created a reason for LTC organizational boards to structure policies that support EBP fall prevention programs. Health based associations and clinical organizations experience better outcomes when research such as this gives credibility their research and platforms. The result is that these organizations use this information to lobby on a legislative level and to develop NP best practices and standards.
Dissemination of Results
The biggest barriers to implementing fall prevention programs in LTC setting are lack of information and motivation. NP leaders play a significant role in overcoming these barriers. NP leaders can inform nursing staff about falls prevention EBP practices during staff meetings and start of shift meetings. NPs can lead open discussions that allow staff to provide feedback on the status of at risk patients, as well as whether benchmarks and goals have been reached. The results of this EBP project can also be shared with study participants. Once these stakeholders receive the results, they may contact the research team to add valuable follow-up information (Curtis, Fry, Shaban, & Considine, 2016). Two feasible ways to share the outcomes with participant stakeholders are through social media and the local newspaper. Data findings can be put in pamphlets to be disseminated at rehabilitation therapy clinics, LTC settings, or assisted living communities. Gerontology practitioners can also play a role is disseminating the findings to participant and patient stakeholders. Sharing results with health organizations and colleagues can be achieved through passing out information pamphlets at health conferences, publishing the study is a scholarly or peer-reviewed publication. Health care industry magazines and health care organization websites are also good places to publish validated research outcomes (Curtis et al., 2016).
Disseminating information to state and national policymakers has different dynamics because these stakeholders have very little time and need the information presented to them in a condensed format. So, researchers must decide what part of the information to disseminate and by which medium. Dodson, Geary, and Brownson (2015) state that policymakers on the national and state levels use EBP research results to shape health policies and create standards for health access and equity. Geary, & Brownson, 2015). Polled legislators stated they prefer receiving health-based research results that include financial cost of implementation in the format of statistics, graphs, and charts (Dodson, Geary, & Brownson, 2015). When disseminating information to policymaker stakeholders on the state and national levels, researchers should post findings on government and university websites, in health care advocacy group publications, and on health lobbyist websites (Dodson, Geary, & Brownson, 2015).
The contribution of EBP to professional nursing is vast. Since its professional inception, nursing has evolved the way nurses provide optimal patient care and the way in which they are educated. Over the past decade, EBP has been garnering more attention from nursing professionals and has slowly emerged as an excellent standard by which to provide clinical care Quantitative research is objective and conclusive and aids in the implementation of evidence-based treatment interventions (Choy, 2014). The quantitative research approach provides the format and methodology to distinguish and quantify multiple reasons why patient’s fall in clinical settings, as well as apply the same methods to determining which NP designed fall- and injury-prevention programs are effective and which programs are ineffective. Furthermore, quantitative research will allow me to compare my findings with data from clinical settings that do not have NP designed fall- and injury-prevention programs and determine if NPs even inform patients about fall prevention strategies. Since quantitative research is comprised of methods that allow for the comprehensive examination of the actions of a small or large group of participants, I will then be able to understand how prevalent the results are to small and large populations. The preferred sample population of nurses is nurse practitioners; however, experiences of registered nurses (RNs) and licensed practical nurses (LPNs) will be considered. Nursing patients must be adult males and females, ranging in age from 21 years old and above (around or above 90 years old). Study participants must be in a long-term care or acute care facility for more than 48 hours. These facilities include but are not limited to nursing homes, acute care hospitals, and LTC rehabilitation facilities.
All research participants have rights that include knowing why the research is being conducted, being informed of the risks or side effects that will or may occur, asking questions during any phase of the research, requesting that personal information be kept private, and dropping out of the research project at any time. Participants should be well informed about patient rights regarding confidentiality and anonymity, protection from harm, and informed consent. The biggest barriers to implementing fall prevention programs in LTC setting are lack of information and motivation. NP leaders play a significant role in overcoming these barriers. To motivate nurses to stay diligent about helping patients avoid falls, NP leaders can institute a merit-based program that rewards the nurse with the least patient falls per month. Once nurses feel comfortable they will be supported by management if they implement EBP falls prevention strategies, the clinical setting will change to a more patient centered environment. Supporting EBP practices is an organizational effort. NP leaders can improve access to falls prevention resources by having these resources available onsite for nurses to interact with.
Breimaier, H. E., Halfens, R., & Lohrmann, C. (2015). Effectiveness of multifaceted and tailored
strategies to implement a fall-prevention guideline into acute care nursing practice: A before-and-after, mixed-method study using a participatory action research approach. BMC Nursing, 14(18). Retrieved from https://bmcnurs.biomedcentral.com/articles/10.1186/s12912-015-0064-z
Chen, H., Hailey, D., Wang, N., & Yu, P. (2014). A review of data quality assessment methods
for public health information systems. International Journal of Environmental Research and Public Health, 11(5), 5170–5207. Retrieved from http://doi.org/10.3390/ijerph110505170
Choy, L. T. (2014). The strengths and weaknesses of research methodology: Comparison and
complimentary between qualitative and quantitative approaches. IOSR Journal Of Humanities And Social Science (IOSR -JHSS), 19(4), 99-104. Retrieved from https://s3.amazonaws.com/academia.edu.documents/37208325/N0194399104.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1527688542&Signature=1kSmo8tbMB1e8VxJp5c6szw0NAo%3D&response-content-disposition=inline%3B%20filename%3DThe_Strengths_and_Weaknesses_of_Research.pdf
Curtis, K., Fry, M., Shaban, R. Z., & Considine, J. (2016). Translating research findings to
clinical nursing practice. Journal of Clinical Nursing, 26(5-6), 862-872. Retrieved from https://doi.org/10.1111/jocn.13586
Dodson, E. A., Geary, N. A., & Brownson, R. C. (2015). State legislators’ sources and use of
information: bridging the gap between research and policy. Health Education Research, 30(6), 840–848. http://doi.org/10.1093/her/cyv044
Harrison, B. E. (2017). Fall prevention program in the community: A nurse practitioner’s
contribution. The Journal for Nurse Practitioners, 13(8), e395–e397. Retrieved from DOI:
Hayat, M. J., Powell, A., Johnson, T., & Cadwell, B. L. (2017). Statistical methods used in the public health literature and implications for training of public health professionals. PLoS ONE, 12(6), e0179032. Retrieved from http://doi.org/10.1371/journal.pone.0179032
Li, F., Harmer, P., Stock, R., Fitzgerald, K., Stevens, J., Gladieux, M., … Voit, J. (2013).
Implementing an Evidence-Based Fall Prevention Program in an Outpatient Clinical Setting. Journal of the American Geriatrics Society, 61(12), 2142–2149. Retrieved from http://doi.org/10.1111/jgs.12509
Ponto, J. (2015). Understanding and evaluating survey research. Journal of the Advanced
Practitioner in Oncology, 6(2), 168–171.Retrieved from
Sutton, J., & Austin, Z. (2015). Qualitative Research: Data Collection, Analysis, and
Management. The Canadian Journal of Hospital Pharmacy, 68(3), 226–231. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4485510/
Walonick, D. S. (2018). Survey design guidelines. Retrieved from https://www.statpac.com/survey-design-guidelines.htm