BLOG: CRITIQUING SOURCES OF ERROR IN POPULATION RESEARCH TO ADDRESS GAPS IN NURSING PRACTICE Epidemiology &

  

BLOG: CRITIQUING SOURCES OF ERROR IN POPULATION RESEARCH TO ADDRESS GAPS IN NURSING PRACTICE


Epidemiology & Population Health

DUE APRIL 1st

SOURCES OF ERROR IN POPULATION-BASED RESEARCH

INTRODUCTION

This week, you will review different sources of error in population-based research, focusing on bias and confounding. Bias refers to deviations of results, or inferences, from the truth (Friis & Sellers, 2021). There are two overarching types of bias: information bias and selection bias. Both types can be detrimental to the validity and reliability of results. Several strategies exist to help prevent bias, but it is virtually impossible to eliminate bias altogether.

In addition to bias, confounding variables can pose challenges for epidemiologists. Confounding is the masking of an association between an exposure and an outcome because of the influence of a third variable that was not considered in the study design or analysis. For example, if weight loss is the topic of study and exercise is the only variable considered, diet could mask the results of the study.

LEARNING OBJECTIVES

Students will:

· Analyze nursing practice implications of bias, confounding, and random error in epidemiologic and population health research

· Propose strategies to minimize sources of error in population research

· Differentiate epidemiologic measures and measurement errors 

This is a graded discussion: 100 points possible

Week 6: Blog

BLOG: CRITIQUING SOURCES OF ERROR IN POPULATION RESEARCH TO ADDRESS GAPS IN NURSING PRACTICE

As a DNP-educated nurse, part of your role will be to identify the differences, or gaps, between current knowledge and practice and opportunities for improvement leading to an ideal state of practice. Being able to recognize and evaluate sources of error in population research is an important skill that can lead to better implementation of evidence-based practice.

In order to effectively critique and apply population research to practice, you should be familiar with the following types of error:

Selection Bias

Selection bias in epidemiological studies occurs when study participants do not accurately represent the population for whom results will be generalized, and this results in a measure of association that is distorted (i.e., not close to the truth). For example, if persons responding to a survey tend to be different (e.g., younger) than those who do not respond, then the study sample is not representative of the general population, and study results may be misleading if generalized.

Information Bias

Information bias results from errors made in the collection of information obtained in a study. For example, participants’ self-report of their diet may be inaccurate for many reasons. They may not remember what they ate, or they may want to portray themselves as making healthier choices than they typically make. Regardless of the reason, the information collected is not accurate and therefore introduces bias into the analysis.

Confounding

Confounding occurs when a third variable is really responsible for the association you think you see between two other variables. For example, suppose researchers detect a relationship between consumption of alcohol and occurrence of lung cancer. The results of the study seem to indicate that consuming alcohol leads to a higher risk of developing lung cancer. However, when researchers take into account that people who drink alcohol are much more likely to smoke than those who do not, it becomes clear that the real association is between smoking and lung cancer and the reason that those who consume alcohol had a higher risk of lung cancer was because they were also more likely to be smokers. In this example, smoking was a confounder of the alcohol-lung cancer relationship.

Random Error

The previous three types of errors all fall under the category of 
systematic errors, which are reproducible errors having to do with flaws in study design, sampling, data collection, analysis, or interpretation. 
Random errors, on the other hand, are fluctuations in results that arise from naturally occurring differences in variables or samples. While unavoidable to a small degree even under the most careful research parameters, these types of errors can still affect the validity of studies.

RESOURCES

Be sure to review the Learning Resources before completing this activity.
Click the weekly resources link to access the resources. 



WEEKLY RESOURCES

LEARNING RESOURCES


Required Readings

· Curley, A. L. C. (Ed.). (2020). 
Population-based nursing: Concepts and competencies for advanced practice (3rd ed.). Springer.

· Chapter 4, “Epidemiological Methods and Measurements in Population-Based Nursing Practice: Part II”

Friis, R. H., & Sellers, T. A. (2021). 
Epidemiology for public health practice (6th ed.). Jones & Bartlett.

· Chapter 10, “Data Interpretation Issues”

· Enzenbach, C., Wicklein, B., Wirkner, K., & Loeffler, M. (2019). 

Evaluating selection bias in a population-based cohort study with low baseline participation: The LIFE-Adult-StudyLinks to an external site.

BMC Medical Research Methodology
19(1), Article 135.

· Khalili, P., Nadimi, A. E., Baradaran, H. R., Janani, L., Rahimi-Movaghar, A., Rajabi, Z., Rahmani, A., Hojati, Z., Khalagi, K., & Motevalian, S. A. (2021). 

Validity of self-reported substance use: Research setting versus primary health care settingLinks to an external site.

Substance abuse Treatment, Prevention, and Policy
16(1), Article 66.

· Karr, J. E., Iverson, G. L., Isokuortti, H., Kataja, A., Brander, A., Öhman, J., & Luoto, T. M. (2021). 

Preexisting conditions in older adults with mild traumatic brain injuries. 
Brain Injury, 1–9



 Download Preexisting conditions in older adults with mild traumatic brain injuries. Brain Injury, 1–9
. Advance online publication.

TO PREPARE:

· Review this week’s Learning Resources, focusing on how to recognize and distinguish selection bias, information bias, confounding, and random error in research studies.

· Select a health issue and population relevant to your professional practice and a practice gap that may exist related to this issue.

· Consider how each type of measurement error may influence data interpretation in epidemiologic literature and how you might apply the literature to address the identified practice gap.

· Consider strategies you might use to recognize these errors and the implications they may have for addressing gaps in practice relevant to your selected issue.

Post a cohesive scholarly response that addresses the following:

· Describe your selected practice gap.

· Explain how your treatment of this population/issue could be affected by having awareness of bias and confounding in epidemiologic literature.

· Explain two strategies researchers can use to minimize these types of bias in studies, either through study design or analysis considerations.

· Finally, explain the effects these biases could have on the interpretation of study results if not minimized.

Assignment Rubric Details

Close

Rubric

NURS_8310_Week6_Blog_Rubric

NURS_8310_Week6_Blog_Rubric

Criteria

Ratings

Pts

This criterion is linked to a Learning OutcomeMain Posting: Idea and Content

60 to >49.0 pts

Excellent

• Thoroughly responds to the blog prompt/s. • Post provides comprehensive insight, understanding, or reflection about the topic through a focused analysis of the topic supported by personal experiences and/or examples. • Personal opinions are expressed and are clearly related to the topic, activity or process identified in blog prompts. • The post reflects in-depth engagement with the topic. • Posts main blog by due date.

49 to >38.0 pts

Good

• Responds to all of the blog prompt/s. • Post provides insight, understanding, or reflection about the topic through a reasonably focused analysis of the topic supported by personal experiences and/or examples. • Personal opinions are expressed and are but not fully developed to align with blog prompts. • The post reflects moderate engagement with the topic. • Posts main blog by due date.

38 to >27.0 pts

Fair

• Partially responds to the blog prompt/s. • Posts are typically short and may contain some irrelevant material. • The post is mostly description or summary without connections or analysis between ideas. • The post reflects minimal engagement with the topic. • Posts main blog by due date.

27 to >0 pts

Poor

• Does not respond to the blog prompt/s or entries lack insight, depth or are superficial. • The entries are short and are frequently irrelevant to the events. • They do not express opinion clearly and show little understanding. • The post does not reflect engagement with the topic. • Does not post main blog by due date.

60 pts

This criterion is linked to a Learning OutcomeFirst Response: Post to colleague’s main blogpost shows evidence of insight, understanding, or reflective thought about the topic. NOTE: Responses to faculty are not counted as first or second colleague responses.

20 to >11.0 pts

Excellent

• Presents a focused and cohesive viewpoint in addressing this response. • Response includes focused questions or examples related to colleague’s post. • Response stimulates dialogue and commentary. • Posts by due date.

11 to >6.0 pts

Good

• Presents a specific viewpoint that is focused and cohesive. • Response includes at least one focused question or example related to colleague’s post. • There is some attempt to stimulate dialogue and commentary. • Posts by due date.

6 to >2.0 pts

Fair

• Presents a specific viewpoint but lacks supporting examples or focused questions related to colleague’s post. • The posting is brief and reflects minimal effort to connect with colleague. • Posts by due date.

2 to >0 pts

Poor

• Response lacks a specific viewpoint and supporting examples or focused questions related to colleague’s post. • The post does not stimulate dialogue or connect with the colleague. • Does not post by due date.

20 pts

This criterion is linked to a Learning OutcomeSecond Response: Post to second colleague blog post shows evidence of insight, understanding, or reflective thought about the topic.

20 to >11.0 pts

Excellent

• Presents a focused and cohesive viewpoint in addressing this response. • Response includes focused questions or examples related to colleague’s post. • Response stimulates dialogue and commentary. • Posts by due date.

11 to >6.0 pts

Good

• Presents a specific viewpoint that is focused and cohesive. • Response includes at least one focused question or example related to colleague’s post. • There is some attempt to stimulate dialogue and commentary. • Posts by due date.

6 to >2.0 pts

Fair

• Presents a specific viewpoint but lacks supporting examples or focused questions related to colleague’s post. • The posting is brief and reflects minimal effort to connect with colleague. • Posts by due date.

2 to >0 pts

Poor

• Response lacks a specific viewpoint and supporting examples or focused questions related to colleague’s post. • The does not stimulate dialogue or connect with the colleague. • Does not post by due date.

20 pts

Total Points: 100

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