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Critical appraisal of a quantitative paper (RCT)

This guide, aimed at health students, provides basic level support for appraising quantitative research papers. It's designed for students who have already attended lectures on critical appraisal. One framework for appraising quantitative research (based on reliability, internal and external validity) is provided and there is an opportunity to practise the technique on a sample article.

Please note this framework is for appraising one particular type of quantitative research a Randomised Controlled Trial (RCT) which is defined as 

a trial in which participants are randomly assigned to one of two or more groups: the experimental group or groups receive the intervention or interventions being tested; the comparison group (control group) receive usual care or no treatment or a placebo.  The groups are then followed up to see if there are any differences between the results.  This helps in assessing the effectiveness of the intervention.(CASP, 2020)

Absolute Risk (AR) = incidence

The observed or calculated probability of an event in the population under study.

Experimental Event Rate (EER) = a/a+b  [i.e. Risk in exposed]

Control Event Rate (CER) = c/c+d [i.e. Risk in unexposed]

Relative Risk (RR) = EER/CER = (a/a+b)/(c/c+d) =

The ratio of the probability of developing, in a specified period of time, an outcome among those receiving the treatment of interest or exposure to a risk factor, compared with the probability of developing the outcome if the intervention or risk factor is not present.

Relative Risk Reduction (RRR) = CER-EER/CER or = 1-RR

The extent to which a treatment reduces a risk, in comparison with patients not receiving the treatment of interest.

Absolute Risk Reduction (ARR) = CER-EER [also referred to as the risk difference (RD)]

The difference in the absolute risk (rates of adverse events) between study and control populations.

Number Needed to Treat (NNT) = 1/ARR  Video by Terry Shaneyfelt

The number of patients who must be exposed to an intervention before the clinical outcome of interest occurred; for example, the number of patients who must be treated to prevent one adverse outcome. NNT is a value that can permit all stakeholders in the clinical decision to better understand the likelihood of developing the outcome if a patient has a given intervention or condition.

Odds

A proportion in which the numerator contains the number of times an event occurs and the denominator includes the number of times the event does not occur.

Odd Ratio (OR) = (a/b)/(c/d)=ad/bc

A measure of the degree of association; for example, the odds of exposure among the cases compared with the odds of exposure among the controls. Note: OR and RR can be very similar when outcomes or events are rare. As the outcomes or event rate increase, the value will diverge.

Confidence Interval (CI)   Video by Terry Shaneyfelt

The range in which the true effects lies with a given degree of certainty. In other words, the CI provides clinicians a range of values in which they can be reasonably confident (e.g., 95%) that they will find a result when implementing the study findings. In general, narrower CIs are more favorable than wider CIs; where confidence intervals are wide, they indicate less precise estimates of effect. When the confidence interval crosses the point of no effect (e.g., for OR or RR, no effect=1; for effect size, no effect=0), it demonstrates no statistical significance.

p Value

The probability that any particular outcome would have occurred by chance. A p value of 0.05 or less would be considered a statistically significant result in healthcare research. Considered to be inferior to Confidence Intervals in determining significance of studies.

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