In a study about obesity, obesity health risks, resilience, and acculturation in black African immigrants dependent and independent variables were present.
Responses to Discussion Posts
Response to the posts in about 150-170 and no references required – DISCUSSION RESPONSES
CheReg
1 – The two main variables in an experiment are the independent and dependent variable. An independent variable is the variable that is changed or controlled in a scientific experiment to test the effects on the dependent variable. A dependent variable is the variable being tested and measured in a scientific experiment. The dependent variable is ‘dependent’ on the independent variable. As the experimenter changes the independent variable, the effect on the dependent variable is observed and recorded. For example, a scientist wants to see if the brightness of light has any effect on a moth being attracted to the light. The brightness of the light is controlled by the scientist. This would be the independent variable. How the moth reacts to the different light levels (distance to light source) would be the dependent variable (ThoughtCo, 2019).
Extraneous variables are any variables that you are not intentionally studying in your experiment or test. When you run an experiment, you’re looking to see if one variable (the independent variable) has an effect on another variable (the dependent variable). In an ideal world you’d run the experiment, check the results, and voila. Extraneous variables could include prior knowledge of statistics; you would have to make sure that group A roughly matched group B with prior knowledge before starting the study. Other extraneous variables could include amount of support in the home, socio-economic income, or temperature of the testing room (Statistics How To, 2019).
Extraneous variables should be controlled if possible by: 1) Randomization: In this approach, treatments are randomly assigned to the experimental groups. It is assumed that the extraneous factors are present equally in all the groups. This technique is only workable when the sample size is very large.
2)Matching: Another important technique is to match the different groups of confounding variables. Different confounding variables like gender, age, income etc. could be distributed equally amongst the group. It sometimes does become difficult to extend matching within all the groups and another drawback of the same is that, sometime the matched characteristics may be irrelevant to the dependant variable.
If these extraneous variables are not controlled they may become confounding variables, because they could go on to affect the results of the experiment.
Wilcro
2- The two main variables in an experiment are the independent and dependent variable. An independent variable is the variable that is changed or controlled in a scientific experiment to test the effects on the dependent variable. A dependent variable is the variable being tested and measured in a scientific experiment. The dependent variable is ‘dependent’ on the independent variable. As the experimenter changes the independent variable, the effect on the dependent variable is observed and recorded. For example, a scientist wants to see if the brightness of light has any effect on a moth being attracted to the light. The brightness of the light is controlled by the scientist. This would be the independent variable. How the moth reacts to the different light levels (distance to light source) would be the dependent variable (ThoughtCo, 2019).
Extraneous variables are any variables that you are not intentionally studying in your experiment or test. When you run an experiment, you’re looking to see if one variable (the independent variable) has an effect on another variable (the dependent variable). In an ideal world you’d run the experiment, check the results, and voila. Extraneous variables could include prior knowledge of statistics; you would have to make sure that group A roughly matched group B with prior knowledge before starting the study. Other extraneous variables could include amount of support in the home, socio-economic income, or temperature of the testing room (Statistics How To, 2019).
Extraneous variables should be controlled if possible by: 1) Randomization: In this approach, treatments are randomly assigned to the experimental groups. It is assumed that the extraneous factors are present equally in all the groups. This technique is only workable when the sample size is very large.
2)Matching: Another important technique is to match the different groups of confounding variables. Different confounding variables like gender, age, income etc. could be distributed equally amongst the group. It sometimes does become difficult to extend matching within all the groups and another drawback of the same is that, sometime the matched characteristics may be irrelevant to the dependant variable.
If these extraneous variables are not controlled they may become confounding variables, because they could go on to affect the results of the experiment.
Heacor
3 – Independent variables are things in a study that are expected to influence dependent variables. These variables are controlled or changed by the person completing the research. Dependent variables are the result of the effect of independent variables. These variables are the ones being studied and measured for the study. Extraneous variables are variables that occur during the study; however, they are ones that you did not anticipate happening. They can influence the outcome of your research since they are unexpected variables. There are four types of extraneous variables seen in research studies; characteristics: environmental clues, experimenter / investigator effects, participant variables, and situational variables.
There are several ways that extraneous variables are controlled in research studies. Randomization is when treatments are randomly assigned to the experimental groups. The extraneous factors are assumed to be present equally in all the groups. This method is used for large sample groups. Experimental designs is when the effects of extraneous variables are reduced or completely removed from the study.
In a study about obesity, obesity health risks, resilience, and acculturation in black African immigrants dependent and independent variables were present. The study examines the acculturation, resilience, obesity health risks, and obesity outcomes among Black African immigrants. Independent variables such as weight along with other variables such as obesity health risk symptoms, and obesity were a factor in the study. Some participants in the study did not report weight accurately which created extraneous variables.
Jaubro
4 – Independent variables are changed by the researcher to observe effects on dependent variables. Dependent variables are not changed by the researcher but instead are possibly changed by independent variables (Schmidt, 2018). Extraneous variables can possibly affect dependent variables but are not classified as independent variables because they are unexpected.
Researchers can try to control extraneous or confounding variables by restriction, and matching (Pourhoseingholi, Bangestani, & Vahedi, 2012). Restriction controls extraneous variables when researchers only select same variables and eliminate other variables that do not fit within their scope (Pourhoseingholi et al. 2012). For example, only participants of the same gender and age are selected as the sample. According to Pourhoseingholi et al. (2012), extraneous variables can be controlled by matching when researchers match variables like age and gender to a control that has the same variables. The example provided is a study about coffee and lung cancer. If participants who have lung cancer are coffee drinkers and they smoke, smoking would be an extraneous variable. Researchers can control this extranous variable by altering their research method when selecting a sample to exclude participants who smoke (Pourhoseinghoi et al., 2012)
Chargun
5.2 – The “levels of evidence” are usually presented in the form of a pyramid in order to show the reader as the research articles climb the pyramid the stronger the evidence presented is. The higher you climb on the pyramid the fewer the articles there are, but the evidence in those articles with be the most accurate and you should strive to find those type of articles when doing research. The levels of the pyramid are as follows; the bottom is background information/expert opinion, then case-controlled studies, case series/reports, cohort studies, randomized controlled trials (RCTs), critically-appraised topics (evidence syntheses), and the top of the pyramid is systematic reviews, which gives the strongest quality evidence (Winona state university (WSU), 2020).
The bottom of the pyramid includes background info and expert opinions, which can be explained by animal research/lab studies and handbooks, encyclopedias, and textbooks. This information that is found from this level is generalized and it provides a summary. An example of practice change from this level is development of therapies and diagnostic tools. The next level of the pyramid is case-control studies which identifies cases and then controls patient’s outcome and looks for exposure of interest (WSU, 2020). An example of this practice is results of prevention programs for diseases. This level is followed by cohort studies, which takes two groups of patients one with exposure of interest and one without and studies them for the patient outcomes. Example of this would be a drug trail to examine a new drug to treat cancer, where one group gets the med and the other doesn’t and study the outcome of the medication. The next level is RCTs, which randomized groups of patients and the variables/outcomes of interest are followed. This level is used to examine quality improvement problems and design prevention programs from the results. The next two levels of the pyramid are similar and are critically appraised articles and topics. The difference between these two levels is that the articles are dealing with individual research studies, whereas the topics examine multiple research studies. Both of these levels are used to examine evidence-based practices and keep the medical field up to date with the latest and greatest ways to care for our patients. The top of the pyramid examines the best of the best research out there. Systematic reviews are on topics that have been searched for, appraised and summarized with all the medical literature for that specific topic. An example of a systematic review is meta-analysis with uses quantitative methods to summarize the results (WSU, 2020). An example of this level is clinical questions in the medical field like, how likely is the patient to develop a disease if they participate in certain behaviors.
Jaubro
6.2 – The levels of evidence are important factors that must be considered when reviewing evidence to implement Evidence-Based Practice (EBP). These levels can be organized in a pyramid or hierarchy from weakest evidence being at the bottom and the strongest evidence being at the top. Brower (2017), discussed that there are different types of pyramids within healthcare professions. She describes the basic pyramid levels from bottom to top which are expert opinion, cohort studies, non-experimental studies such as qualitative, experimental studies, randomized control trials, and systematic reviews (Brower, 2017).
Expert opinion: A medical professional may observe that a boot produced by a certain manufacturer, is made from materials of better quality and receives less complaints from clients regarding comfort. The professional starts using that specific boot for clients instead of the other boots available going forward.
Cohort & Non-experimental studies: “… a study design surveying prenatal habits of new mothers of infants who are having difficulty breast feeding, in an attempt to identify a common cause” (Brower, 2017). With these results, medical professionals may ask questions to clients to pinpoint if the causes identified from this study are the same for all new mothers.
Experimental studies: A medical facility does a study on a new system for physician’s orders to determine if the new system has is an effect on medication errors or not. Depending on the results, the facility will either roll out the system facility wide or scrap the new system all together.
Randomized control trial (RCT): A study involving a new pain medication and its effect on client’s pain. Groups are randomized; one is a control group & the other is the experimental group. The experimental group receives the medication and the control group receives a placebo. Based on results, an organization may start prescribing the medication after it has gone through the appropriate approvals if it is shown to be effective.
Systematic review/meta-analysis: A condensed review of multiple RCTs on pain medications and the effects on a client’s pain. These reviews can influence organizations to create guidelines of practice (Brower, 2017).
Subject: Nursing
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