NRS 433 Topic 4 DQ 1
DQ: Compare independent variables, dependent variables, and extraneous variables
Experimental studies are crucial in nursing practice as they help in determining how different phenomena are interrelated in evidence-based practice. The main variables that are used in an experimental investigation are dependent and independent. On the one hand, independent variables are the variables that are changed or manipulated by the researcher to determine their relationship with a phenomenon being observed. The experimenter manipulates independent variables and observes whether there are any observable changes in the dependent variable (Titler, 2018). On the other hand, a dependent variable is what the experimenter is measuring in the experiment. A dependent variable is a phenomenon or variable being tested in an experiment (Eldawlatly and Meo, 2019). Changes in this variable are dependent on the independent variable. In an experiment, independent variables can be thought of as the cause while the dependent variable is the effect because they change depending on the alterations made in independent variables. For instance, in a study to investigate if a low-calorie diet reduces cholesterol levels in overweight patients, low-calorie intake is the independent variable while cholesterol level is the dependent variable.
Extraneous variables are any other variables in an experiment that are not under investigation and could potentially affect the internal validity of the study thus giving inaccurate research outcomes (Eldawlatly and Meo, 2019). Thus, the experimenter should always control for extraneous variables failure which could lead to inaccurate conclusions about the correlation between dependent and independent variables. In the example above, factors such as the age of the patient and other comorbid diseases could alter the results of the study if not controlled.
One of the ways that researchers control extraneous variables is through randomization. In random sampling, the researcher assigns treatments randomly to the experimental and control groups to ensure possible extraneous variables are equally distributed between the study groups, especially when the sample size is relatively large (Falkner et al., 2018). The second approach involves the use of blinding whereby, treatments are kept unknown to both the participant and the researcher.
DQ: Compare independent variables, dependent variables, and extraneous variables
References
Eldawlatly, A. and Meo, S. (2019). Writing the methods section. Saudi Journal of Anesthesia. 13(Suppl 1): S20–S22. doi: 10.4103/sja.SJA_805_18
Falkner, A. Et al. (2018). Nursing Research: Understanding Methods for Best Practice (1st Edition). Grand Canyon University Press.
Titler, M.G., (May 31, 2018) Translation Research in Practice: An Introduction. The Online Journal of Issues in Nursing, 23(2).
Wanda Felder
Posted Date
May 1, 2022, 6:42 PM
Please review the chart below to gain more understanding of extraneous variables.
Wanda Felder
Posted Date
May 1, 2022, 6:41 PM
I like the breakdown of the variables in this example.
What do you think? Do you find this helpful?
DQ: Compare independent variables, dependent variables, and extraneous variables
https://www.psychologywizard.net/uploads/2/6/6/4/26640833/7182277_orig.jpg
Wanda Felder
Posted Date
Apr 30, 2022, 7:14 PM
Hi Class,
Dependent and independent variables are more commonly discussed than extraneous variables (Sheppard, 2020). Extraneous variables are important to consider in research, as they can ultimately affect the results of a research study. Sheppard (2020) asserts that the integrity of a research study could be compromised secondary to extraneous variables. As a researcher, completing comprehensive research, yet it lacks integrity is not desired. Furthermore, the credibility of the researcher is also diminished (Coates, 2014).
Click here to ORDER an A++ paper from our MASTERS and DOCTORATE WRITERS: DQ: Compare independent variables, dependent variables, and extraneous variables
In an attempt to ensure the research is credible, the researcher should implement the necessary controls. Furthermore, maintaining
the integrity of the research is also associated with making necessary controls. In research, if an outcome occurs because of an extraneous variable, it is then called a confounding variable (Sheppard, 2020). What is a way to control research to reduce extraneous variables?
Coates, H. (2014). Ensuring research integrity: The role of data management in current crises. College & Research Libraries News, 75(11), 598–601. https://doi.org/10.5860/crln.75.11.9224
Sheppard, V. (2020). Research methods for the social sciences: An introduction. Retrieved from https://pressbooks.bccampus.ca/jibcresearchmethods/chapter/4-6-extraneous-variables/
Wanda Felder
Posted Date
Apr 30, 2022, 7:13 PM
Your discussion of variables is informative. To enhance your understanding, please review the following example.
DQ: Compare independent variables, dependent variables, and extraneous variables
As a class, let us review this example to look at the differences between dependent and independent variables. I found this example to be easier to understand given its relation to healthcare.
https://ori.hhs.gov/node/1218/printable/print
Wanda Felder
Posted Date
Apr 30, 2022, 7:13 PM
Replies to Mireille Ulysse
Hi Class,
Is there an unanswered question that remains regarding variables?
Jana Garcia
replied toWanda Felder
May 1, 2022, 6:38 PM
- Replies to Wanda Felder
Dr. Felder,
I believe there is unanswered questions in research variables, and these are these lead to information gaps. An example in nursing research could include pregnant mothers who start a research trial, and they represent the variable of pregnant mothers who smoke. If she and others in her variable group abandoned the trial, the data that would be collected is not going to be accurate. This can occur when there is a lack of participation in research studies. This can cause a “problem for the overall reliability and generalizability of results when recruitment goals are missed, or participants are lost to follow-up” (Brunsdon, 2019). There are a few ways to avoid this gap. One is to increase the sample size and the other is to improve retention of participants. In regard to variables, they must be considered operational variable or having “some properties such as good reliability and validity, low bias, feasibility/practicality, low cost, objectivity, clarity, and acceptance” (Kaliyadan, 2019). If these variables are low on the validity scale, there outcome of research will not be reliable leading to unanswered questions in research. Thank you, Jana
Brunsdon, D., Biesty, L., Brocklehurst, P. et al. What are the most important unanswered research questions in trial retention? A James Lind Alliance Priority Setting Partnership: the PRioRiTy II (Prioritising Retention in Randomised Trials) study. Trials 20, 593 (2019). https://doi.org/10.1186/s13063-019-3687-7
Kaliyadan, F., & Kulkarni, V. (2019). Types of Variables, Descriptive Statistics, and Sample Size. Indian dermatology online journal, 10(1), 82–86. https://doi.org/10.4103/idoj.IDOJ_468_18
Tracy Tibbs-Briggs
Posted Date
Apr 27, 2022, 11:08 PM
Replies to Mireille Ulysse
When conducting research, the researcher manipulates a variable to see the outcome in another variable. The variable that the researcher can control is the independent variable. The independent variable can directly affect the result of the dependent variable. The extraneous variable is the unwanted issue of things that can skew the data in an experiment. The extraneous variable is why all studies are likely to be incorrect because every experiment has a bias (Helbig & Ambrose, 2018).
There are three categories of extraneous variables: situation, personal, and researcher-based. Situations are issues that can personally happen to the subjects in research that could not be determined before the study and are personal only to the subject or community, such as death or a natural disaster. A personal extraneous variable is an individual trait that makes every subject different such as other medical diagnoses and personal life experiences. The final and third type is the researcher-based extraneous variable. This variable is something that the researcher does that creates inconsistency from one subject, group, or community that may change collected data (Helbig & Ambrose, 2018). What makes research valuable is controlling the variable in an experiment and giving quality data and information. Researchers try their best to keep extraneous variables out of a study to provide validity and consistency to the study, but this can be close to impossible to achieve.
DQ: Compare independent variables, dependent variables, and extraneous variables
Keeping extraneous variables out of a study makes the study reliable and accurate. However, there is no way to make an experiment 100% free of extraneous variables because people conduct these experiments, and error is human.
However, researchers try to limit extraneous variables in experiments to include strategies such as the purification principle. The purification principle acknowledges the bias and produces a biased estimate. In addition, the purification principle recognizes the error percentage of skewed data and the percentage of data omitted in the study (Bernerth et al., 2018). Acknowledging this bias and calculating the potential of error is how researchers can control the probability of inaccurate data and skewed information from the experiment.
The control in an experiment is the version of the experiment that can be used for comparison. In many cases, the control is the unmanipulated version of the experiment, or the “normal” condition of the subject of the experiment. If experimenting to determine the effect of salt on freezing point of water, the control version of the experiment would be freezing water without any salt. If experimenting to determine if plants grow faster in red light, the control version would be plants grown in full-spectrum light.
Unfortunately, experimental terminology can get a little confusing. The control in an experiment isn’t the same as the controlled variables. The controlled variable definition science uses essentially states that controlled variables include all the variables the experimenter controls or keeps constant to prevent interference with the experimental results.
For example, in the water-and-salt freezing experiment controlling the variables would mean using the same type of water for all experiments, using the same amount of water, the same size and shape of container to freeze the water, the same freezer, and the same measurement tool and technique. Every factor of the control (plain water) and the experiment (water One responding variable definition says the responding variable is what will be measured in the experiment. The responding variable, also called the dependent variable, is what the scientist measures as the experiment progresses. The responding variable is the response of the experimental subject to the manipulated variable. The dependent variable depends on what happens during the experiment. The two terms, responding variable and dependent variable, describe the same aspect of the experiment.
Although the experiment should only have one manipulated variable, there may be more than one responding variable. For example, the addition of salt to water may change the freezing temperature or the freezing time or both, or neither. The effect of changing the light wavelength on plant growth might be plant height, chlorophyll production, new leaf production or a combination of these factors. The scientist may define what outcome will be observed, but a good scientist should also collect observations of other outcomes as well. For example, if the scientist sets out to test the effect of light color on plant growth, a lack of growth or negative result in the experimental group would be recorded, but if the experimental group also has reduced leaf growth (all compared to the control group, of course), the researcher should also record this data.
Responding variables need to be measured using objective criteria. Results must be taken without bias or speculation by the scientist. Saying that the plants in full-spectrum light “look healthier” than plants grown in red light doesn’t provide a measurable or objective outcome. Without objective and measurable outcomes, the experiment’s results can’t be authenticated.
-
- Judd, C.M. & Kenny, D.A. (1981). Estimating the effects of social interventions. Cambridge, MA: Cambridge University Press. ↵
- Morling, B. (2014, April). Teach your students to be better consumers. APS Observer. Retrieved from http://www.psychologicalscience.org/index.php/publications/observer/2014/april-14/teach-your-students-to-be-better-consumers.html ↵
- Bauman, C.W., McGraw, A.P., Bartels, D.M., & Warren, C. (2014). Revisiting external validity: Concerns about trolley problems and other sacrificial dilemmas in moral psychology. Social and Personality Psychology Compass, 8/9, 536-554. ↵
- Fredrickson, B. L., Roberts, T.-A., Noll, S. M., Quinn, D. M., & Twenge, J. M. (1998). The swimsuit becomes you: Sex differences in self-objectification, restrained eating, and math performance. Journal of Personality and Social Psychology, 75, 269–284. ↵