Study design
Choosing the proper study design is an essential skill for researchers to estimate the intervention outcome with the best possible and most reliable outcome (Garg, 2016). There are several different types of study design. Mainly, an intervention study such as a randomised controlled trial or an observational study such as a cross-sectional study (Goldberg, McManus and Allison, 2013).
Cross-sectional study is a method to examine the outcome and the exposure at the same time for data collection from the study population at a specific point in time. In this study, the target population is selected by considering the inclusion and exclusion criteria set out for the study and then the information from the gathered data is investigated for
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It is relatively faster and easy to perform without additional follow-up activities. Also it is relatively inexpensive and it does not require a lot of time. Data can be only collected once in a specific point in time. It provides the prevalence of the outcome throughout the investigation. Estimating the prevalence outcome is important in public health. This is because the prevalence of disease or other health correlated characteristics enables to investigate the associations between risk factors of disease and the outcome of interest. In addition to this, it can investigate the burden of disease in a specified population and in forming the arrangement and assignment of health resources. Furthermore, it provides the ability to evaluate various outcomes, exposures and risk factors. Therefore, it is equally beneficial for public health planning in, understanding the cause of the disease. Additionally, it is appropriate for descriptive analyses and for the generation of hypotheses. Moreover, the data can be used for various types of research and many findings and outcomes can be analysed to create new theories or studies (Levin, 2006; Detels, et al., 2011; Setia,
In response to the question set, I will go into detail of the study, consisting of the background, main hypotheses, as well the aims, procedure and results gathered from the study; explaining the four research methods chosen to investigate, furthering into the three methods actually tested.
...the data did not involve member checking thus reducing its robustness and enable to exclude researcher’s bias. Although a constant comparative method was evident in the discussion which improved the plausibility of the final findings. Themes identified were well corroborated but not declared was anytime a point of theoretical saturation Thus, the published report was found to be particularly strong in the area of believability and dependability; less strong in the area of transferability; and is weak in the area of credibility and confirmability, although, editorial limitations can be a barrier in providing a detailed account (Craig & Smyth, 2007; Ryan, Coughlan, & Cronin, 2007).
“Epidemiology is the study of distributing in determinants of disease and disability and populations” (Mausner & Bahn 1974). It’s a basic science of the public’s health and is a measured scientific control that relies heavily on data and study design. Those who study epidemiology focus on specific population and how disabilities and disease affect them. Epidemiological methods have been applied to infectious disease outbreak investigations, but also to studies of longer-term chronic disease investigations. The Behavioral Risk Factor Surveillance System is the largest telephone survey in the world. It’s used to determine the commandments of many health risk behaviors among populations. Surveys were developed and conducted to mon...
A good design begins with a creation or plan for the making of an object or service. It is a strategic approach towards a person’s (usually a client or target audience) required unique expectations. A design generally defines the specifications and parameters in achieving its main objectives. Often there are no key attributes as to what would make a design successful and interesting. Products and peoples needs and wants or taste often change and revolve around time. This brings a definite change in the market and its emerging’s trends. This cycle of evolution will always exist, but finally it is the factor of emotional response with the customer that will determine whether a product is successful or not. Whether the design is an object or it is a concept, the design that we see is an accumulation of various concepts and decisions that have been brought together from a variety of disciplines. In order for a consumer to view the design as something that is good it takes a unique combination of aesthetics, quality and ergonomics to make a design successful. Often we recognize a bad design at its first glance and a bad design often forces one to take in many confusing and conflicted content. So what makes our design/ product fail?
The pretest-posttest design, crossover design, placebo, quasi-experiments (lack randomization but involve intervention and is usually found to be more acceptable to a broader group of people who are not always willing to be randomized in clinical trials). The RCT study known as the “gold standard” (for interventional studies, controlled and randomized for comparing a controlled and interventional group variable) and The Cohort (prospective) design research (analysis or the observational design with cohort, it starts with a recognized cause and then goes forward to the recognized effect). The clarification of the outcomes of the statistical analysis in quantitative research, understanding the research practice and the identification of the basis of evidence-based practice contained by the sections of research and critiques of that research. By graining an understanding of these steps and knowing how to rethink research and revise my views of the research will aid in success of my practicing these tactics (Polit, & Beck,
Considering that the researcher protects himself or herself and the participants, a lot of unwanted circumstances including new infections on both sides are prevented thus limiting the miscellaneous costs in the research budget. It also assures the participants that they are protected and thus will come to no harm during the study. This ensures that they are willing to cooperate and thus help the scientific community and humanity as a whole by providing the relevant data for a given investigation. Safety here also prevents errors by ensuring that the possible errors are caught on time. This then translates into results that are not only very reliable but also largely replicable onto another sample population, making them relevant in drawing a generalized
We would visit the garden in the school and finally, watch a video with audio on plants. I will use mixed ability grouping for group activities for the students to identify plant types by the leaves and discuss among each other each type. The long time learning activities for the class will be for the student to learn how to plant, water, give nutrition to plant by planting a beans in a pot and we all watch it grow. The students Knowledge will be accessed by giving the students the option of either search the internet for more facts about plant and write a short paragraph about what they learned, or draw and label a picture of a plant and taking a quiz they discuss their answer in
I chose this study because it has a large cohort which eliminates sample bias. High quality data could be obtained from this longitudinal epidemiological ...
Of which the hypothesizes that do not have enough data would be dismissed and the hypothesizes that have enough data would be analyzed more closely (Kranacher, Riley & Wells,
The father of quantitative analysis, Rene Descartes, thought that in order to know and understand something, you have to measure it (Kover, 2008). Quantitative research has two main types of sampling used, probabilistic and purposive. Probabilistic sampling is when there is equal chance of anyone within the studied population to be included. Purposive sampling is used when some benchmarks are used to replace the discrepancy among errors. The primary collection of data is from tests or standardized questionnaires, structured interviews, and closed-ended observational protocols. The secondary means for data collection includes official documents. In this study, the data is analyzed to test one or more expressed hypotheses. Descriptive and inferential analyses are the two types of data analysis used and advance from descriptive to inferential. The next step in the process is data interpretation, and the goal is to give meaning to the results in regards to the hypothesis the theory was derived from. Data interpretation techniques used are generalization, theory-driven, and interpretation of theory (Gelo, Braakmann, Benetka, 2008). The discussion should bring together findings and put them into context of the framework, guiding the study (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). The discussion should include an interpretation of the results; descriptions of themes, trends, and relationships; meanings of the results, and the limitations of the study. In the conclusion, one wants to end the study by providing a synopsis and final comments. It should include a summary of findings, recommendations, and future research (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). Deductive reasoning is used in studies...
The resulting inferences are only as good as the combination of these factors. Statistical analysis, however, can suffer from a lack of theoretical and conceptual underpinnings (Achen 2002: 424, Johnson 2006: 238). Minimalist definitions of a concept include the largest number of cases, but risk conceptual stretching, whereas maximalist definitions would include so many descriptive attributes, the number of cases dwindles. Statistical analysis tends to include the most cases possible and thus risks conceptual stretching (Sartori 1970, Munck and Verkuilen 2002). Statistical models can be underspecified and not include independent variables that impact the change in the dependent
This article review forms part of a report, the intention of this literature is to review five articles namely; “Socially Responsive design: Thinking beyond the triple bottom line to socially responsive and sustainable product design” by Gavin Melles, Ian de Vere & Vanja Misic, published in 2011, CoDesign, Vol. 7, No. 2-4, “A “Social Model” of Design: Issues of Practice and Research” By Victor Margolin and Sylvia Margolin, published in 2002, MIT Press, Vol. 18, No.4, “Rethinking Design Policy in the Third World” by Sulfikar Amir, published in 2004, MIT Press, Vol. 20, No. 4, “Design for Children’s Behaviours in Daycare Playgrounds” By Nathan H. Perkins and George Antoniuk, published in 1999, Alexandrine Press, Vol. 25, No. 1, lastly “The Politics of the Artificial” By Victor Margolin, Published in 1995, MIT Press, Vol. 28, No. 5. By reviewing these articles this paper will expose the social responsibilities of a ‘product’ designer, by looking into the history and context of social design. This paper will further bring forth the “ideal” characteristics of a socially responsible ‘product’ designer, and look into participatory design as a methodology for the socially responsible design process.
But human rights is a complex social concept. The quantity or intensity of violations is only one of several relevant dimensions.
Traditional research may use quantitative or qualitative research method. According to Hendricks (2009), quantitative research is a general conclusion based on hard data. Hen-dricks describe quantitativ...
Research methodology should be understood as a whole, consisting of tools, methods of collecting, interpreting and analysing the data collected. These include: