Last updated on May 27th, 2025 at 03:24 pm
Select a research article oth
Select a research article, oth
TOPIC 2 DQ 1: Effectiveness of Sampling Method Used
Overview of the Study
The article by Griffiths et al. involves a study that investigates the relationship between nurse staffing and the occurrence of omissions. The objective of the study is to assess nursing care that is missed frequently in acute inpatient adult wards, and to determine the linkage between missed care and the levels of staffing (Griffiths et al., 2018). The background of the study is that there are numerous adverse patient outcomes that are directly associated with nurse staffing levels. The study utilizes a systematic review design, with the data sources being several databases including CINAHL and EMBASE (Griffiths et al., 2018). The study shows that there is a high level of association between low nurse staffing and high reports of missed care.
Effectiveness of the Sampling Method Selected
Systematic random sampling was applied when collecting data, and it was effective in collecting data from various databases to be used in the study. In this method, researchers select elements from a sampling frame that is ordered, which in this case is the databases (Javaid, Noor-ul-Amin, & Hanif, 2019). The method of sampling is easy to understand, and it helps in bringing a greater control of the sense of the process (Javaid, Noor-ul-Amin, & Hanif, 2019). Because of using this method, the researchers in the study were also able to reduce the risks through elimination of clustered selections. Given a chance to redo the study, I would be sure to use systematic random sampling method, as it is the only method that can give optimal results in a study of this nature.
References
Griffiths, P., Recio‐Saucedo, A., Dall’Ora, C., Briggs, J., Maruotti, A., Meredith, P., & Missed Care Study Group. (2018). The association between nurse staffing and omissions in nursing care: a systematic review. Journal of advanced nursing, 74(7), 1474-1487.
Javaid, A., Noor-ul-Amin, M., & Hanif, M. (2019). Modified Ratio Estimator in Systematic Random Sampling Under Non-response. Proceedings of the National Academy of Sciences, India Section A: Physical Sciences, 89(4), 817-825.
TOPIC 2 DQ 2: Key Questions When Reading the Article
What are the researchers’ hypotheses?
Asking oneself about the hypotheses of the researchers helps to study the mind of the researchers before and after the study is conducted. This question also allows one to put themselves into the perspective of the study as intended by the authors of the article. In some of the cases, asking oneself about the hypotheses of the researchers can help to identify the possibility of biases in a research.
In this study Griffith et al. (2018) hypothesize that low levels of staffing are linked with poor patient outcomes, and the hypothesis is confirmed in the results. The fact that the hypothesis matches to outcomes could lead to questions of whether or not there is biases, but in this case, it is clear from the research procedure that there is no data manipulation.
What is the unit of analysis?
Asking oneself about the unit of analysis also helps to ensure effectiveness in managing the interpretations of the results. A failure to consider the units of a study would imply that the researcher does not understand the exact parameters being applied.
How generalizable are the results?
The generalizability of results is another aspect that is evident in studies that sound ‘too obvious (Pearl & Bareinboim, 2019).’ I would ask myself about the generalizability of the results as it would help me to assess whether or not the article is useful enough for me to make different inferences from the study topic. The article by Griffiths et al. does not have generalizable results as the results are full of details to describe the outcome of the study.
References
Griffiths, P., Recio‐Saucedo, A., Dall’Ora, C., Briggs, J., Maruotti, A., Meredith, P., & Missed Care Study Group. (2018). The association between nurse staffing and omissions in nursing care: a systematic review. Journal of advanced nursing, 74(7), 1474-1487.
Pearl, J., & Bareinboim, E. (2019). Note on ‘‘Generalizability of Study Results ‘‘. Epidemiology, 30(2), 186-188.
Alternative Expert Answer
Artificial Neural Networks
The article by Nina Shahid, Tim Rappon and Whitney Berta is about, “Applications of Artificial Neural Networks in Health Care Organizational Decision-Making: A Scoping Review.” According to the article, the healthcare industry is gradually evolving towards a patient-centered model of care delivery and, at the same time advocating for value-based practices (Shahid, Rappon, & Berta, 2019).
Artificial neural networks (ANN) are essential in health care organizational decision-making through leveraging machine-learning techniques. With the advent of technology, healthcare facilities are increasingly adopting the use of ANN to inform health care decisions. Artificial intelligence is at the center of technology and potential future of technology as it holds the potential to offer health care delivery that is not only appropriate but also cost-effective.
With the increased uptake of artificial intelligence in the healthcare industry, different health care management problems can be addressed (Shahid, Rappon, & Berta, 2019). To address the AI applications in healthcare, the research paper makes use of different research questions and sampling methods to collect data for analysis.
The research paper makes use of the Arksey & O’Malley framework of 2005 to come up with the sampling methods used in the paper. The topic can be related to different multi-disciplinary subjects, and the frameworks used to identify the sampling methods identifies literature related to healthcare but from different databases.
This method is effective as it is able to distinguish materials that are specific to health care organizations and disregards information from other subjects such as computer science (Shahid, Rappon, & Berta, 2019). The research model makes use of essential keywords that the query has to return once a successful search is conducted. The researcher also has the option to add additional information that would further refine the search so that the sampling methods are specific to health care.
Reference
Shahid, N., Rappon, T., & Berta, W. (2019). Applications of artificial neural networks in health care organizational decision-making: A scoping review. PloS one, 14(2). https://www.doi.org/10.1371/journal.pone.0212356
Topic 2 DQ 2: Research Questions
Research questions are essential in helping the researcher or the reader anticipate the contents of the research. For instance, a reader is able to know the type of research and expected content the research will offer through the research questions (Shahid, Rappon, & Berta, 2019).
In the article “Applications of Artificial Neural Networks in Health Care Organizational Decision-Making: A Scoping Review” by Nina Shahid, Tim Rappon, and Whitney Berta, one can also have a set of questions derived from the topic and anticipate that the article would answer the questions.
Three key questions that I would ask and asker when reading through the research study include the following. (i) what is the relationship between Artificial Neural Network and health care? (ii) what are the different applications of Artificial Neural Networks in the health care decision-making process?
And (iii) What are the impacts that Artificial Neural Network has on the overall performance of a health care facility? These questions are important as they provide an overview of what the reader is anticipating to achieve from the article (Shahid, Rappon, & Berta, 2019). The question offers guidelines and pointers of key areas that the article focuses on and focuses on the
The first question first informs the reader that the article is about Artificial Neural Network in relation to health care. In this way, the reader will be able to read the article with the aim of identifying the relationship that exists between the two subjects.
The second question, on the other hand, allows the reader to anticipate the analysis of different applications of ANN in health care. The third question is important as it facilitates the explanation of the various impacts of Artificial Neural Network on health care facilities.
Reference
Shahid, N., Rappon, T., & Berta, W. (2019). Applications of artificial neural networks in health care organizational decision-making: A scoping review. PloS one, 14(2). https://www.doi.org/10.1371/journal.pone.0212356
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How to write a research question
Writing a research question involves identifying a topic that you want to explore and then formulating a question that will guide your investigation. Here are the steps to follow when writing a research question:
- Identify your topic: Choose a topic that you are interested in and want to investigate. This could be a broad area or a specific issue.
- Brainstorm: Write down everything you know about the topic and any questions you have. Consider what you want to learn or discover.
- Narrow your focus: Refine your topic and identify the specific aspect you want to investigate.
- Determine the type of question: Decide whether you want to ask an exploratory, descriptive, comparative, or evaluative question. Each type of question serves a different purpose and requires a different approach.
- Formulate the question: Write a clear and concise question that is specific enough to guide your research but broad enough to allow for exploration.
- Revise and refine: Review your question to ensure it is clear, focused, and feasible. Revise as needed to ensure it aligns with your research goals.
Example:
Topic: The impact of social media on mental health Type of question: Descriptive Question: What is the relationship between social media use and mental health among teenagers in the United States?
