Nursing 360: More Study Designs

Spotting the Study Design

The type of study can generally be worked at by looking at three questions:

Q1. What was the aim of the study?

1. To simply describe a population (PO questions) descriptive
2. To quantify the relationship between factors (PICO questions) analytic.

Q2. If analytic, was the intervention randomly allocated?

1. Yes? RCT
2. No? Observational study

For observational studies, the main types will depend on the timing of the measurement of outcomes, so our third question is:

Q3. When were the outcomes determined?

1. Some time after the exposure or intervention? cohort study (‘prospective study’)
2. At the same time as the exposure or intervention? cross sectional study or survey
3. Before the exposure was determined? case-control study (‘retrospective study’ based on recall of the exposure)

Download an article on study design by Jeremy Hawick.

Categorical (nominal) tests
This category of tests can be used when the dependent, or outcome, variable is categorical (nominal), such as the dif­ference between two wound treatments and the healing of the wound (healed versus non­healed). One of the most used tests in this category is the chi­squared test (χ2). The chi­squared statistic is calculated by comparing the differences between the observed and the expected frequencies. The expected frequencies are the frequencies that would be found if there was no relationship between the two variables. 

Based on the calculated χ2 statistic, a probability (p ­value) is given, which indicates the probability that the two means are not different from each other. Researchers are often satisfied if the probability is 5% or less, which means that the researchers would conclude that for p < 0.05, there is a significant difference. A p ­value ≥ 0.05 suggests that there is no significant difference between the means.

Halfens, R. G., & Meijers, J. M. (2013). Back to basics: an introduction to statistics. Journal Of Wound Care, 22(5), 248-251.

A confidence interval (CI) can be used to show within which interval the population's mean score will probably fall.  Most reseachers use a CI of 95%.  By using a CI of 95%, researchers accept there is a 5% chance they have made the wrong decision in treatment.  Therefore if 0 falls within the agreed CI, it can be concluded that there is no significant difference between the two treatments.  When 0 lies outside the CI, researchers will conclude that there is a statistically significant difference.

Halfens, R. G., & Meijers, J. M. (2013). Back to basics: an introduction to statistics. Journal Of Wound Care, 22(5), 248-251.