NRS 433 Topic 2 DQ 1 Discuss two strategies that would help a researcher manage and organize the data
NRS 433 Topic 2 DQ 1
The purpose of qualitative research is to understand individuals lives and figure out what the central meaning is (Renjith 2021). To analyze different phenomena in this context, researchers gather many different views from different individuals to see how the phenomenon effects their life (Maxwell 2020). An example of this would be mothers with children who have leukemia (Renjith 2021). The research would surround every life aspect, from wearing a mask everywhere to staying home on lock down basically to keep infection minimum during treatments (Renjith 2021). Grounded theory is to discovery in the context of the social process being studied. This theory uses comparative analysis, theoretical sampling, theoretical coding, and theoretical saturation. An example of this would be an analysis of the relationship between women and anorexia. The study analysis showed a development of a theoretical framework on the nature of the relationship between the self and anorexia nervosa (Renjith 2021). Ethnographic research studies the anthropology of culture specific areas. Knowledge and behaviors are used in this type of study (Renjith 2021). An example of this type of research study would be “The aim of the ethnographic study by LeBaron et al. was to explore the barriers to opioid availability and cancer pain management in India. The researchers collected data from fifty-nine participants using in-depth semi-structured interviews, participant observation, and document review. The researchers identified significant barriers by open coding and thematic analysis of the formal interview” (Renjith 2021).
Qualitative data has been described as voluminous and sometimes overwhelming to the researcher. Discuss two strategies that would help a researcher manage and organize the data.
Review this article about how social media was used as a resource for coding with qualitative data.
Nadelson, S. & Nadelson, L. (2019). Making qualitative research real to students: Using social media postings to teach qualitative data coding. Worldviews on Evidence-Based Nursing,16(2). 169–171. 10.1111/wvn.12356
Review this image for a better understadning of qualitative data analysis
https://www.formpl.us/blog/image_serve/qualitative-data-analysis
Interactive research methods map
This research methods map is great.
Please review!
http://methods.sagepub.com/methods-map/qualitative-data-collection
The National Database of Nursing Quality Indicators and the VA Nursing Affairs Outcome Database are two software programs that collect and store information to be evaluated and used by professional nurses as strategies to store research data that will be used to delivery evidence-based care. These databases were “designed for evaluating nursing care in the acute setting” (Montalvo, 2007). When this data is retrieved, it is referred to as data mining. “Data mining technology can search for potentially valuable knowledge from a large amount of data, mainly divided into data preparation and data mining, and expression and analysis of results” (Yang, 2020).
Professional nurse researchers are no longer having to manage their own data because information technology manages them electronically. Because nursing demands ethical professional guidelines in EBP, whatever strategy a nurse chooses to use, they must pull from a trusted research database otherwise, they may risk unethical outcomes. When searching for strategies to store and retrieve data, nurses must be aware of the possibility of “scientific misconduct, particularly as it pertains to falsification, fabrication, and plagiarism” (Ulrich, 2015). In cancer epidemiology studies a program often used is SEERS, or Surveillance, epidemiology, and end results. This clinical information helps clinical researchers provide efficient, convenient, and clear access to data. Strategies for managing data in 2022 include advanced technologies. Respectfully, Jana
Montalvo I. (2007). The National Database of Nursing Quality Indicators (NDNQI). Online Journal of Issues in Nursing, 12(3), 13p.
Ulrich, C. M., Wallen, G. R., Cui, N., Chittams, J., Sweet, M., & Plemmons, D. (2015). Establishing good collaborative research practices in the responsible conduct of research in nursing science. Nursing outlook, 63(2), 171–180. https://doi.org/10.1016/j.outlook.2014.10.007
Check Out Also: NRS 433 Topic 2 DQ 2 Compare the differences and similarities between two of the three types of qualitative studies and give an example of each
Yang, J., Li, Y., Liu, Q., Li, L., Feng, A., Wang, T., Zheng, S., Xu, A., & Lyu, J. (2020). Brief introduction of medical database and data mining technology in big data era. Journal of evidence-based medicine, 13(1), 57–69. https://doi.org/10.1111/jebm.12373
Hi Jana, Themes analysis, grounded theory, and literature reviews are some of the approaches used in qualitative research, and evaluating qualitative data may be overwhelming and complex. The examination of huge amounts of data in order to identify meaningful patterns and rules is an essential aspect of scientific discovery because patterns are required for the development of scientific hypotheses and causal models (Berber & Berber, 2004). Qualitative research results are useful because they provide a better understanding of the facts that describe people’s behaviors, routines, lives, and minds. Data mining tries to explain and clarify behavioral patterns in massive volumes of data. A large volume of data is extracted (mined) for useful knowledge. Such knowledge will allow for the establishment of relationships between attributes or data sets, the clustering of similar data, the classification of attribute relationships, and the display of information that would otherwise be hidden or lost in a massive amount of data if data mining were not used (Pastrana et al., 2019).
When working with large amounts of data, particularly data from nursing research, the task of analyzing can be difficult to manage and organize. In nursing research, data mining as a method of data analysis can aid in the finding of causal factors and the demonstration of outcome effectiveness (Berger & Berger, 2004). This technique can turn a huge amount of data into useful information that can improve clinical practice. It is critical to recognize the value of data that can enhance the lives of others when we are able to locate it. The opportunity for nurse researchers to acquire useful insight into patterns and trends has the potential to improve nursing knowledge and progress.
Reference
Berger, A.M., and Berger, C.R. (2004). Data mining as a tool for research and knowledge development in nursing. CIN: Computers, Informatics, Nursing. 22(3), 123-131. https://doi.org/10.1097/00024665-200405000-00006
Pastrana, J.L., Reigal, R.E., Morales-Sanchez, V., Morillo-Baro, J.P., Juarez-Ruiz de Mier, R., Alves, J., and Hernandez-Mendo, A. (2019). Data mining in the mixed methods: Application to the study of the psychological profiles of athletes.
Thank you for responding to my post. Data mining in research was especially important during the Covid-19 pandemic because it was and still is imperative that the public are health care literate to understand Covid-19 and prevention measures. However, the “pandemic of COVID-19 shows that low health literacy is a public health problem that has long been underestimated worldwide” (Qi, 2021). It is the responsibility of Public Health professionals to present education on Covid-19 in a manner that the public will understand and review the results to prove that education is useful and more importantly that the public is utilizing the information to prevent the spread of infection.
Data mining is used in this process. Countries with low health literacy would require more education and perhaps more field work from Public Health officials. Data mining has shown researchers that “a systematic approach is needed to address health literacy issues, together with a strengthened framework of collaborative networks for health literacy at all regional, national and global levels” (Qi, 2021). Researchers use data mining to determine country by country and region by regions what implementations are needed to help the public understand the Covid-19 disease. The information gathered by data mining keeps us all safer when strategies are developed to prevent the spread of infection based on the publics level of understanding. Thank you, Jana
Qi, S., Hua, F., Xu, S., Zhou, Z., & Liu, F. (2021). Trends of global health literacy research (1995–2020): Analysis of mapping knowledge domains based on citation data mining. PLoS ONE, 16(8), 1–23. https://doi-org.lopes.idm.oclc.org/10.1371/journal.pone.0254988
Thanks for your post.
An area of concern came to mind with thought of using data management services and software for storage of a research project. Accuracy of the information that will be found in this data system as although it is a computer-based program it is humans that enter the information into the system. It is great to have assistance in managing the information that has be collected by the researcher as organizing data can be very time consuming if using interviews, charts, graphs, and visuals as your process (Guetterman, et al., 2021). I can imagine a researcher being very possessive over their work, making sure everything is in order. They would have to have extensive training and knowledge in the use of the data management software and services. There are many libraries within the academic world investing in research data management services and piloting programs for information on its usefulness in the academic world (Muellenbach, 2021).
It is very important that all software services and researchers maintain ethical behavior as it relates to patients, society, and the healthcare profession. Maintaining privacy, dignity, having informed consent and insuring participants understand the use and storage of their information (Dimitrios & Antigoni, 2018). The use of a research software and data base may give access to others if not properly secured and this could pose an ethical issue of breach in confidentiality.
References:
Dimitrios, T., & Antigoni, F. (2018). Ethics and Deontology in Nursing Research: A Discussion Paper. International Journal of Caring Sciences, 11(3), 1982–1989. https://eds-p-ebscohost-com.lopes.idm.oclc.org/eds/pdfviewer/pdfviewer?vid=21&sid=e6838c31-ba45-4a98-9cda-d4c45ecaba01%40redis
Guetterman, T. C., Fàbregues, S., & Sakakibara, R. (2021). Visuals in Joint Displays to Represent
Integration in Mixed Methods Research: A Methodological Review. Methods in Psychology, 5. https://doi-org.lopes.idm.oclc.org/10.1016/j.metip.2021.100080
Joanne M. Muellenbach. (2021). A Pilot to Initiate Research Data Management Services Within Academic Libraries Helps Librarians to Learn About, Engage With, and Enhance Skills Within Their Research Communities. Evidence Based Library and Information Practice, 16(1). https://doi-org.lopes.idm.oclc.org/10.18438/eblip29879
Thank you for responding to my post. When misinformation is spread, its affects all of us. This is why ethical research is imperative. When in the process of literature reviews, it’s important to always consider the “discussions” portion which includes ethical considerations. This gives us, the reader, and opportunity to weight potential issues within the research itself while giving the researcher an opportunity to “promote the responsible conduct of research and to prevent misconduct” (Astedt, 2018). Code of Conduct in research is established to provide guidelines for “reviewing, evaluating and editing, such as stating the seriously of researchers’ commitment to the research community by participating in the important work of referring, reviewing and evaluation” (Astedt, 2018).
Misrepresentation an unethical research skews vital information that can cause injury to patients, for that reason, the reader must understand ethics in research. Furthermore, when nurses review literature and see potential misrepresentations or holes in research, it’s a clear indication that we should look to another research review especially when changing practice and policies. Thank you, Jana
Åstedt, K. P., & Kaunonen, M. (2018). Ethics in nursing research and research publications. Scandinavian Journal of Caring Sciences, 32(2), 449–450. https://doi-org.lopes.idm.oclc.org/10.1111/scs.12593
Researchers using qualitative data must develop effective strategies to manage and organize it due to its voluminous nature. The collected responses during surveys are not structured properly and may create problems in storage and organizations. Therefore, the researchers must have a method that would allow them collect and store the data in an organized manner. Organized data lowers the researcher’s confusion and assists them collect as much data as they can (Bansal et al., 2018). One strategy that the researcher can deploy is the use of technology through software systems and programs. Software programs like SAS, SPSS, and STRATA can help collect, organize, assign meaning, store, and retrieve data obtained through qualitative research. The implication is that the researcher will manage the collected data streams from the database created for effective analysis to meet their research needs.
The second strategy that the researcher can deploy to manage and organize the data is creation of proper teams behind them with assigned types of data to manage (Woff et al., 2018). A researcher can promote and attain consistency of a study and strengthen its credibility through triangulation of data sources, debriefing and conducting detailed conversations with colleagues concerning data and its interpretations, check members by presenting preliminary findings to the participants to get their feedback and interpretation (Cypress, 2018). The researcher can also review study procedures and decisions using the teams to have organized data. Through this strategy, the researcher not only manages and organizes data but also reduces pressure one individual doing all the activities and includes checks and balances through different people which creates precision, validity, and reliability. The implication is that the application of these approaches can help the researcher organize and manage data effectively given it voluminous nature.
References
Bansal, P., Smith, W. K., & Vaara, E. (2018). New ways of seeing through qualitative research.
Academy of Management Journal, 61(4), 1189-1195. https://doi.org/10.5465/amj.2018.4004
Cypress, B. (2018). Qualitative research methods: A phenomenological focus. Dimensions of
Critical Care Nursing, 37(6), 302-309. DOI: 10.1097/DCC.0000000000000322.
Woff, B., Mahoney, F., Lohiniva, A. L., & Corkum, M. (2018). Collecting and Analyzing
Qualitative Data. Epidemic Intelligence Service. https://www.cdc.gov/eis/field-epi-manual/chapters/Qualitative-Data.html
Software programs are one of the most effective ways to sort through the excess of qualitative research. There have been questions about whether or not a computer program can accurately depict an individual’s personal experience or situation. Darmody & Byrne explain that the reason why analyzing qualitative data is so labor intensive is because it is not a mechanical process. They described evaluating qualitative data as a creative and dynamic undertaking that requires intuition and thinking (Darmody & Byrne, 2006).
These seem to be extremely human and personal processes to undertake. So if a software is going to be used, it needs to be programmed to pick out specifics and words that are relevant. Organizing qualitative data starts from the beginning. If a researcher is planning to use a software system, they need to input interview transcripts and information gathered directly into the software. The software can then take over and code the information looking for specific words and phrases that can be categorized and used (Darmody & Byrne, 2006).
Qualitative data refers to non-numerical data that is collected through observations, interviews, focus groups, and other forms of inquiry that seek to understand complex phenomena. Qualitative data are often voluminous and complex, making it challenging for researchers to manage and organize the data effectively. In nursing research, qualitative data are frequently collected to explore the experiences, perspectives, and meanings of individuals in relation to health and illness.
Two strategies that can help researchers manage and organize qualitative data are coding and memoing. Coding is the process of systematically identifying themes and patterns within the data, while memoing involves writing down personal reflections and interpretations of the data as the researcher progresses through the analysis process (Hsieh & Shannon, 2005). These strategies can help researchers to reduce the complexity of the data, identify key concepts and themes, and develop a deeper understanding of the research participants’ experiences.
In nursing research, coding and memoing are commonly used to manage and organize qualitative data. For example, in a study exploring the experiences of cancer patients receiving chemotherapy, researchers used coding and memoing to analyze interview data and identify themes related to the patients’ emotional experiences (Pereira et al., 2019). The researchers found that coding and memoing helped them to organize the data, identify key themes, and develop a more nuanced understanding of the patients’ experiences.
Managing and organizing qualitative data can be challenging for researchers due to the complexity and volume of the data. Strategies such as coding and memoing can help researchers to reduce complexity, identify key themes, and develop a deeper understanding of the research participants’ experiences. These strategies are particularly useful in nursing research, where qualitative data are often collected to explore the experiences of patients and healthcare providers in relation to health and illness.
References:
Hsieh, H. F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative health research, 15(9), 1277-1288.
Pereira, M. G., Roque, A. T., Maroco, J., & Monteiro, E. (2019). Emotional experiences of chemotherapy: A qualitative study with breast cancer patients. European Journal of Cancer Care, 28(3), e13044.
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Qualitative research can sometimes be massive in its data and overwhelming. It can include methods like interviews, focus groups, diaries and journals, and observation (Falkner et al., 2022).
Data collected in qualitative studies are usually in the form of text or visual image. This can provide great sources of insight but also can be bulky and very time consuming to analyze and code. Developing a clear organization system for qualitative data is crucial. Naming conventions for original data files and more analysis should be recorded in a data dictionary file which includes dates, locations, the individual defined or group characteristics, interview details and other important defining features. Condensing can help the process of managing the data. Condensing refers to the process of selecting, focusing, and simplifying and abstracting the data available at the time of the first observation. Then the data is transformed into condensed data that can be analyzed. Reading and rereading can help manage the data. Repeated reading of text to identify consistent themes and interconnections emerging from the data can help to manage it. Repeated reading can yield new themes, connections, and deeper meanings from the first reading. Coding can also help manage the data. Developing codes for labeling sections of text for selective retrieval in later stages of analysis and verification can help immensely (Wolff et al., 2019).
Reference:
Wolff, Brent, et al. “Collecting and Analyzing Qualitative Data.” CDC, 2019, www.cdc.gov/eis/field-epi-manual/chapters/Qualitative-Data.html.
Falkner, A., Green, S. Z., Helbig, J., Johnson, J., McNiff, P., Petrick, M., & Schmidt, M. (2022). Nursing research: Understanding methods for best practice. Grand Canyon University (Ed.). https://bibliu.com/app/#/view/books/1000000000588/epub/Chapter2.html#page_68