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Notes-For-Research-Test-converted.pdf - http\/ggaging.com\/details\/381\/en-US\/creating-a-research-idea-steps-and-challenges
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FINER FINER stands for feasible, interesting, novel, ethical, and relevant The FINER* mnemonic is a framework used for formulating research questions (feasible, interesting, novel, ethical, and relevant). FINER allows researchers to ponder the philosophical, logical, and scientific implications of writing research questions. Researchers have to evaluate their immediate empirical and clinical environment when planning to answer a research question. Researchers also have to be introspective in terms of how much time and effort they are willing to invest in a research study from inception to publication. In order to meet all of the FINER criteria, researchers MUST become vested in the empirical literature. Research questions are grounded in the empirical literature. Mastery of the literature allows researchers to know what questions have been asked and which questions need answers. Other important questions that researchers work through with the FINER framework include: 1. Will the question fill a meaningful "gap" in the knowledge base? 2. What new evidence will the research question yield? 3. How will study participants be protected from harm? How will confidentiality and anonymity be upheld? Informed consent? 4. How will answering the research question impact clinical practice? Quality improvement? Protocols? Policy? Feasible research questions Feasible in FINER focuses on time, scope, resources, expertise, and funding When using the FINER framework, writing feasible research questions ensures that researchers are taking on a research project that can actually be completed. Feasible research questions can be answered. The feasibility of research questions focuses on objective aspects of the immediate empirical or clinical environment (time, scope, resources, expertise, funding, etc.). Statistical power is also a central focus of feasibility. Researchers need to have access to a large enough pool of participants to sample from to conduct meaningful research. Without a large enough sample size, statistical power will decrease, meaning that researchers will be less likely to detect significant treatment effects. Collaboration with other researchers is highly suggested to share the work load and integrate
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TAGS researcher, Empirical research
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Network analysis is a graphical statistical technique that allows rapid visualization and interpretation of associations between multiple variables. There are still few theoretical studies on this method, especially in the areas of geriatrics and gerontology research, which cover the study of different social, clinical, or physical and mental health variables. The objectives of this study were to present the main theoretical aspects of network analysis and demonstrate its applicability by analyzing studies that used this technique, offering an accessible language for all levels of knowledge in statistics. The main characteristics of the graphs, basic theoretical concepts, and scientific articles that used networks were demonstrated. This methodological study can help the reader to understand this analytical method, which is still little explored in national research. There is a scarcity of research on this subject in the areas of geriatrics and gerontology; however, technological advances, the availability of statistical programs with new data analysis resources, and the dissemination of information are relevant factors for the expansion of knowledge and the use of network analysis in this context.
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