Obesity Diagnosis: Dependent and Independent Variables

Extraneous Variables

Extraneous variables are those that are unnecessary for the experiment and cannot be predicted in advance in the majority of cases. Unless their influence on the relationship between the dependent and independent variables is neutralized or minimized, they produce an undesirable effect on the outcomes of the experiment adding error (Grove, Burns, & Gray, 2014). The research question I am going to answer in my proposed study runs as follows: “In adults, aged 20-65 diagnosed with obesity, will a nurse-led educational intervention as compared to standard medical care decrease obesity rates?” Therefore, it is possible to identify several extraneous variables (as the ways to control them):

  1. Experimenter effects: The results of the experiment may be affected by the researcher’s subjectivity (e.g. positive or negative perception of the region, hospital staff, etc.). The researcher must be able to separate his/her attitude from objective results to eliminate these variables.
  2. Demand characteristics: The participants’ behavior may be influenced if they know what answer the researcher wants to obtain. That is why they should not have any preliminary data about the expected outcome of the intervention.
  3. Participant variables: Some of the obesity cases may be aggravated by other health conditions (which is especially applicable to patients over 55). This means that nurse-led educational intervention may give other results than expected. Thus, the researcher must consider all other patients’ conditions.
  4. Situational variables: Since all health care units are located in different regions, obesity rates may be affected by ecological, economic, social, etc. factors specific to the community. The influence of these factors can be minimized by random sampling.

Instruments: Validity and Reliability Testing

About 10 medical care units across the state have been chosen to trace whether, in adults, aged 20-65 diagnosed with obesity, a nurse-led educational intervention as compared to standard medical care is capable of decreasing obesity rates. While choosing an appropriate instrument, the preference should be given to those that ensure higher validity and reliability. That is why this study will rely upon measures of physical activity, body mass index, and self-reported health habits of patients suffering from obesity in different health care units.

Objective indicators are more reliable than self-reported data that should be used only as an additional source of information (Tucker & Lanningham-Foster, 2015). The experiment is to trace statistically significant increases in levels of physical activity, decreases of the body mass index, and improvements in health habits in both controls (standard medical care) and intervention group (receiving a nurse-led educational intervention).

Description of the Intervention

The study is going to find out whether the nurse-led educational intervention can decrease obesity rates in patients aged 20-65 more effectively than standard medical care. The selected health care units are located in different regions and are characterized by a different environment. Yet, a need for additional education to improve patients’ outcomes is common to all units. The research will be a quantitative study focusing on the investigation of a causal impact of this educational intervention on obesity rates. Thus, the participants will be divided into the control and intervention groups. While the former will receive conventional care, the latter will combine standard treatment with educational intervention provided by nursing staff. At the end of the experiment (in 3 months), the results will be measured for both groups.

Data Collection Procedures

The following steps are to be taken to collect data:

  • selecting a random sample of patients aged from 20 to 65 diagnosed with obesity;
  • explaining the purpose of the research to the participants and getting their informed consent (written and signed);
  • dividing the participants into the control and intervention groups;
  • measuring levels of PA and body mass index and collecting patient-reported information concerning health habits;
  • organizing a 3-month educational intervention for the intervention group;
  • performing all measures for the second time in both groups to be able to estimate the effectiveness of the intervention;
  • comparing results across hospitals in different regions.

References

Grove, S. K., Burns, N., & Gray, J. (2014). Understanding nursing research: Building an-based practice. Amsterdam, Netherlands: Elsevier Health Sciences.

Tucker, S., & Lanningham-Foster, L. M. (2015). Nurse-led school-based child obesity prevention. The Journal of School Nursing, 31(6), 450-466.

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NursingBird. (2022, March 25). Obesity Diagnosis: Dependent and Independent Variables. https://nursingbird.com/obesity-diagnosis-dependent-and-independent-variables/

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"Obesity Diagnosis: Dependent and Independent Variables." NursingBird, 25 Mar. 2022, nursingbird.com/obesity-diagnosis-dependent-and-independent-variables/.

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NursingBird. (2022) 'Obesity Diagnosis: Dependent and Independent Variables'. 25 March.

References

NursingBird. 2022. "Obesity Diagnosis: Dependent and Independent Variables." March 25, 2022. https://nursingbird.com/obesity-diagnosis-dependent-and-independent-variables/.

1. NursingBird. "Obesity Diagnosis: Dependent and Independent Variables." March 25, 2022. https://nursingbird.com/obesity-diagnosis-dependent-and-independent-variables/.


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NursingBird. "Obesity Diagnosis: Dependent and Independent Variables." March 25, 2022. https://nursingbird.com/obesity-diagnosis-dependent-and-independent-variables/.