Evidence-Based Practice and the Importance of Descriptive Research
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These designs are especially important when little is known about a phenomenon and the researcher needs to collect sufficient information before proposing experimental studies. These designs are used simply to describe what is observed or to compare different observations. For example, a researcher administers a survey to a sample of first-year teachers in order to describe the characteristics of novice teachers.
Simple descriptive studies include ethnographies, journals, qualitative case studies, and interviews.
Evidence-Based Practice Glossary
This research, a form of quantitative descriptive research, receives much attention in the media. It is used to describe the statistical association between two or more variables. Because the method relies on quantitative data, conclusions are easily summarized for presentation to the public. It is important to note that correlational studies have low internal validity and cannot establish a cause-effect relationship between the variables. Correlational research is valuable in guiding researchers as to where more rigorous methods of research should be employed.
RCT is an experimental method in which investigators randomly assign eligible subjects into groups to receive or not receive one or more interventions that are being compared. It is considered the gold standard for establishing internal validity when the goal is to assess the cause-effect relationships between an intervention and its outcomes. This is an experimental method very effective in establishing internal validity with a single individual or a small group of individuals.
Evidence-Based Practice Glossary
SSD is limited in its ability to make statements of external validity. This experimental method is a pretest-posttest comparison group design. The unique characteristic that separates this method from randomized controlled trial is how participants are assigned to the comparison groups. RDD assigns participants to comparison groups on the basis of a cutoff score on a pre-intervention measure, whereas RCT randomly assign participants to groups.
In short, the lack of rigorous assignment introduces the potential for selection bias that weakens the ability to make strong claims of cause-effect. In an evidence-based culture, we interpret the results of research on continua of evidence to determine if the conclusions exceed the threshold we require for making smart decisions. The continuums consist of two qualities: the quantity of the evidence and the quality of the evidence.
In looking at the quality of a study, we are determining the strength of its evidence as measured by internal validity. As educators, we want to know how likely we are to achieve similar results when we implement the practice. This confidence increases in the quality continua as internal validity increases, beginning with non-experimental methods such as ones calling for personal observations and culminating in the gold standard of designs, the randomized controlled trial. One study does not offer conclusive evidence of the effectiveness of a practice.
Scientists gain confidence in their knowledge by replicating findings through multiple studies, conducted by independent researchers, over time to show that results were not a fluke or due to an error.
One of the great challenges for educators in using knowledge derived from research is how to wade through the volume of studies available as well as the information within a study. Fortunately, over the past 30 years two valuable tools have been developed to assist educators understand the available research: effect size and meta-analysis. Rather than a research design or a method to establish cause-effect relationships, effect size is used to understand the results derived from research. Effect sizes range from minus to positive. The terms "small," "medium," and "large" are relative. Researchers accept the risk of using relative terms in the belief that they have more to gain than lose by offering a common conventional frame of reference when no better way to estimate the impact of a practice of intervention is available.
A meta-analysis is a literature review that integrates individual studies of a single subject using statistical techniques to combine the results into an overall effect size.
This is extremely helpful to educators in making sense of multiple studies on a single topic. Meta-analysis is not itself a research design or an actual scientific study. Its purpose is only to act as a method to statistically examine scientific studies. Evidence Based Education. Applied Social Research Methods Series, no. Most social scientists seek causal explanations that reflect tests of hypotheses. Causal effect nomothetic perspective occurs when variation in one phenomenon, an independent variable, leads to or results, on average, in variation in another phenomenon, the dependent variable.
Conditions necessary for determining causality:. Beach, Derek and Rasmus Brun Pedersen.
Chapter 5, Causation and Research Designs. Neil J. Salkind, editor. Thousand Oaks, CA: Sage, , pp. Chapter 11, Nonexperimental Research: Correlational Designs. Often used in the medical sciences, but also found in the applied social sciences, a cohort study generally refers to a study conducted over a period of time involving members of a population which the subject or representative member comes from, and who are united by some commonality or similarity. Using a quantitative framework, a cohort study makes note of statistical occurrence within a specialized subgroup, united by same or similar characteristics that are relevant to the research problem being investigated, r ather than studying statistical occurrence within the general population.
Using a qualitative framework, cohort studies generally gather data using methods of observation. Cohorts can be either "open" or "closed. Healy P, Devane D. Cohort Analysis. Evidence-Based Dentistry 7 : 51—52; Payne, Geoff.
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Cross-sectional research designs have three distinctive features: no time dimension; a reliance on existing differences rather than change following intervention; and, groups are selected based on existing differences rather than random allocation. The cross-sectional design can only measure differences between or from among a variety of people, subjects, or phenomena rather than a process of change.
As such, researchers using this design can only employ a relatively passive approach to making causal inferences based on findings. Bethlehem, Jelke. London, England: Sage, , pp. Michael S. Thousand Oaks, CA: , pp. Paul J. Lavrakas, ed. Healthknowledge, Cross-Sectional Study. Descriptive research designs help provide answers to the questions of who, what, when, where, and how associated with a particular research problem; a descriptive study cannot conclusively ascertain answers to why. Descriptive research is used to obtain information concerning the current status of the phenomena and to describe "what exists" with respect to variables or conditions in a situation.
Anastas, Jeane W. Chapter 5, Flexible Methods: Descriptive Research. Salkind and Kristin Rasmussen, editors. Descriptive Research Methodologies. Powerpoint Presentation; Shuttleworth, Martyn. Descriptive Research Design , September 26, A blueprint of the procedure that enables the researcher to maintain control over all factors that may affect the result of an experiment.
In doing this, the researcher attempts to determine or predict what may occur. Experimental research is often used where there is time priority in a causal relationship cause precedes effect , there is consistency in a causal relationship a cause will always lead to the same effect , and the magnitude of the correlation is great. The classic experimental design specifies an experimental group and a control group. The independent variable is administered to the experimental group and not to the control group, and both groups are measured on the same dependent variable.