NUR 699 GC Week 3 Discussion1: Levels of evidence

What levels of evidence are present in relation to research and practice, and why it is important regardless of the method you use?

NUR 699 GC Week 3 Discussion 2

What factors must be assessed when critically appraising quantitative studies (e.g., validity, reliability, and applicability)? Which is the most important? Why?

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Use a standard 10 to 12 point (10 to 12 characters per inch) typeface. Smaller or compressed type and papers with small margins or single-spacing are hard to read. It is better to let your essay run over the recommended number of pages than to try to compress it into fewer pages.

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What factors must be assessed when critically appraising quantitative studies

Introduction

Quantitative research has been an important tool in understanding human behaviour. It’s also been used to inform policy makers and medical professionals about causes of disease, or how best to treat patients. The problem is that many studies are not well-designed and so may lead us astray in our quest for knowledge. This guide will help you critically appraise quantitative studies so that you can make better decisions about where your money goes – and avoid being misled by bad science!

The PICO question

The PICO question is a research design that uses four main questions to guide the study. It stands for:

• Population (who is included in the study?)

• Intervention (what are the interventions? How do they compare to one another?)

• Comparison (who did not participate in an intervention, and what were their characteristics?)

• Outcome (what happened after treatment completion?)

Critical Appraisal of Quantitative Studies

Critical appraisal is the process of critically evaluating research. It involves the application of a set of principles, including:

• knowing your own criteria for determining the validity and reliability of a study;

• making sure that you have understood what was actually measured in any given study;

• understanding how different variables may affect each other (for example, if one variable has been measured before another);

• using statistical tests to analyze data from multiple studies or samples (for example, comparing mean scores).

Was the research question clearly defined?

When you’re critically appraising quantitative studies, it’s important to make sure that the research question is clearly defined. The research question should be answerable and relevant to the study, as well as meaningful for the audience of your article or review.

You can use these questions as a guide when considering whether or not a study is valid:

• Is there enough information in the article? If something doesn’t seem right about this section, then there might not be enough information available for you to properly evaluate its validity (which could lead into another problem area). For example, if one part mentions an experiment with 10 participants but only lists seven names instead of listing all 10 names with their IDs (which would mean that at least one participant was left out), this may indicate sloppy writing or even poor organization on behalf of whoever wrote this section! This would suggest poor quality control measures have been taken during development stages too—something else worth looking into further later on down our journey together here today….

Objectives were not clearly stated

The first step in critically appraising quantitative studies is to determine the objectives of the study. If a research question or hypothesis has not been clearly defined, it will be difficult for you to assess its quality. The objectives should be clear whether you are considering a qualitative or quantitative study.

In addition, if any of your own assumptions about what counts as good science are being questioned by a study’s approach and conclusions, then consider whether those concerns might apply equally well to other methods as well (e.g., using experiments instead of surveys).

Research methods were not appropriate for the scientific question

It is important to note that the study design was not appropriate for the research question. For example, if you have a hypothesis about whether people with diabetes are more likely to develop heart disease, then you would use a randomized control trial (RCT) in which participants are randomly assigned to either receive treatment or not. However, if your question is whether patients who receive acupuncture treatment have lower rates of complications than those who do not receive acupuncture treatment, then an RCT would probably not be appropriate because it could take months before any results could be obtained from such an experiment and no one knows how long after treatment begins until complications arise. In this case, some type of retrospective study design might work better because it can provide information about what happened prior to onset of complications as well as possibly detect changes in outcomes over time by comparing data from multiple points along this trajectory rather than relying solely on information collected during a single point in time

Statistical analysis

You must be able to evaluate the statistical analysis used in a study. This includes whether the statistical tests were appropriate for the type of data and analysis, as well as whether they were appropriate for your research question.

For example, if you were conducting an experiment on how people respond to different types of music, it would be unreasonable to use one-way ANOVA when examining whether people are more likely to dance alone or with others after hearing certain songs. In this case, instead you’d need something called a “two-way” or “multivariate” ANOVA because you’re looking at two variables at once (dance vs no-dance).

Clinical importance of findings was not described.

The clinical importance of findings was not described.

Clinical relevance of findings: What are the potential implications for patients? For example, if a new drug is found to produce significant side effects in some people, this may affect how it is used by doctors and patients. Clinical significance of findings: How important are these results compared to other studies that have been done on similar topics (eg, medication effectiveness)? Does their study design differ from previous studies in other ways or were they given special treatment by researchers so as not to be as rigorous as others? They should also explain why they chose these specific methods/interventions and what outcome measures were used – e.g., self-reported vs objective measures like blood pressure readings or heart rate monitors). Clinical significance can be assessed objectively by asking experts who know about this area specifically whether there are any reasons why these results would matter more than others which could inform future research efforts towards improving patient care without having too many biases towards certain areas over others.”

What kind of study design was used?

When you look at the study design, ask yourself:

• How was it conducted? Was it a randomized controlled trial (RCT)? Did they use a questionnaire to collect data? Or did they do an observational study and then analyze what happened in their sample of people who had been given different interventions?

• What kind of data were collected during the study? Did they measure blood pressure before and after eating broccoli, or did they measure blood pressure before and after eating candy bars? There are many ways in which studies can be conducted—and many different kinds of conclusions that can be drawn from them—so it’s important to make sure you understand exactly what was being measured by each method used in order to evaluate whether or not there were any biases present in their findings

What type of statistical test was used?

The first step in evaluating a quantitative study is to determine what type of statistical test was used. This can be done by reviewing the methods section and/or results section of an article, or by reviewing it yourself by reading through all relevant information provided in your copy of the paper.

The next thing to consider is whether or not assumptions made during data analysis were met. Assumptions are necessary because they help ensure that results produced using one particular method are generally valid (i.e., consistent), as well as allowing us to make generalizations about our knowledge based on those specific findings. If they aren’t met, then we may have more confidence in our understanding when interpreting this particular piece of research; however, it may also lead us down some unexpected paths that could lead us astray if we don’t understand why these assumptions were made in the first place!

Finally comes limitations—these are often overlooked during critical appraisal due largely because they’re difficult for most people interested in doing scientific research themselves). Limitations could include: sample size; lack thereof; selection bias; lack thereof (even though some would argue otherwise); confounding variables such as age group differences between groups being compared statistically against each other

Takeaway:

The takeaway is the most important point.

The takeaway is the conclusion.

The takeaway is the main point, and it should be clearly stated in your abstract, introduction, and discussion sections.

Conclusion

A critical appraisal of a quantitative study is an important part of the research process, but it can be time-consuming. In this article we will look at the various factors that must be considered when critically appraising quantitative studies and help you decide whether or not to use them in your own work.