NR 505 DeVry Week 1 Discussion Latest

Ask a PICO(T) Question (graded)

Write a quantitative research question using the PICO(T) model about a health or safety issue observed in the Iron ridge or Summerville community or your practice setting. Conduct a search of the literature for the quantitative research question. (Remember you can use this topic and quantitative research article as part of your Research Summary Table assignment).Provide a brief summary of your quantitative research article. You will not be able to see other’s posts for this forum until you have posted your response to the threaded discussion thread.

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Writing a quantitative research question using the PICO(T) model

Introduction

Learning how to write a good research question is a skill that will help you on your way to becoming a great researcher. It’s not just about knowing what the questions are and being able to answer them, but also about writing them in such a way that others can understand what you’re trying to find out through your research project. In this article we’ll discuss how you can use the PICO (Patient/Problem/Intervention/Comparison) model as an outline for developing your own quantitative research questions so they can be understood by other researchers who may want to work with your data set later on down the line!

Overview

The purpose of writing a research question is to help you understand the problem that your research will be addressing. A good question should be concise, clear and easy for people to answer. It should also be focused on one specific aspect or idea that is important in your study.

A PICO (Problem, Implication, Cause/Effect, Outcome) model can help you create a good quantitative question by focusing on what causes something rather than how it works or why it matters. This makes writing quantitative questions easier because they are focused on one issue at hand rather than trying not only figure out what has happened but also why it happened!

Patient or Problem

The patient or problem is the population of interest. In this case, it’s patients with diabetes.

Example: Patients with knee arthritis and back pain are examples of problems that could be addressed through a clinical trial investigating new therapies for treating those illnesses.

Intervention

Now that you have a good understanding of the problem and its context, it’s time to start thinking about how an intervention could help.

The intervention itself is your answer to the question “What would make this issue better?” In other words: What is the solution? The goal here isn’t just any old solution; it has to be one that actually works. So what kind of changes can we expect from this approach? After all, if our main goal is simply finding out whether something works or not (as opposed to making sure no harm comes from using it), then we won’t know if anything will work unless we try out some ideas first!

Comparison Intervention

The comparison intervention is the one that you will compare with the control. The difference between these two interventions is what you want to measure, and how you will do this in your research question. For example, if one group receives a treatment that increases profits by 20% and another group receives a training program that increases profits by 10%, then we could measure which made more impact on profit by comparing them after they have been implemented (i.e., before or after). The second question would be: “Which treatment made more impact on profit?”

Outcome(s)

The outcome measures should be objective, quantifiable and observable.

The outcome should be specific to the question being asked.

For example, in a study on the effect of an intervention on cholesterol levels in patients with hyperlipidemia (high cholesterol), we would expect our results to show that those who received the treatment had lower-than-normal levels of LDL (the bad kind) and HDL (the good kind). In this case, it would not be useful for us to know whether or not all patients experienced improvement over time or whether some did better than others—we want our results so we can make decisions about what needs improving next time around!

Types of Questions

The PICO(T) model is a useful tool for writing research questions and hypotheses. In this section, we’ll look at how to apply it to a variety of different types of questions:

• How can we measure the effectiveness of an antibiotic?

• What are the main causes of depression among women over age 45?

• How effective are online dating sites at matching people with similar interests?

Example question and answer from the literature

This section discusses examples of good, bad and neutral research questions.

• Good: “How do I best teach my students?”

• Bad: “What do people think about the quality of my product/service?”

• Neutral: “What are some reasons why people would prefer to buy this product over another one?”

Writing a good research question can be a difficult task.

Writing a good research question can be a difficult task. There are many factors to consider when coming up with one, including the purpose of your study and what questions you want answered. The PICO(T) model is a good way to start thinking about how your task will be structured, but it’s important that you don’t simply copy other people’s examples and try to pass them off as yours. You’ll want to make sure that whatever questions or hypotheses you choose for this project are relevant for both yourself and others reading it!

Here are some examples of good questions:

Conclusion

Writing a good research question is difficult. The PICO model can help you to develop a research question that’s clear, precise and easy to answer.

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