In association with

  • Bristol, North Somerset and South Gloucestershire Integrated Care Board
  • West of England Academic Health Science NetworkWest
  • National Institute for Health Research



Case-control study

The observational epidemiologic study of persons with the disease (or other outcome variable) of interest, and a suitable control (comparison, reference) group of persons without the disease. The relationship of an attribute to the disease is examined by comparing the diseased and non-diseased with regard to how frequently the attribute is present or, if quantitative, the levels of the attribute, in each of the groups.


A group or series of case reports involving patients who were given similar treatment. Reports of case series usually contain detailed information about the individual patients. This includes demographic information (for example, age, gender, ethnic origin) and information on diagnosis, treatment, response to treatment, and follow-up after treatment.


The relating of causes to the effects they produce. Most of epidemiology concerns causality and several types of causes can be distinguished. It must be emphasized, however, that epidemiological evidence by itself is insufficient to establish causality, although it can provide powerful circumstantial evidence.


Control event rate (see event rate)


The Cinahl® database is a comprehensive and authoritative source of information for nurses, allied health professionals, and others interested in health care.


ARC stands for Applied Research Collaborative and Care. ARCs are funded by National Institute of Health Research (NIHR), and there are 13 of these pioneering research teams across the country. ARC West covers the West of England and is based in Bristol. University Hospitals Bristol NHS Foundation Trust hosts ARC West.

Clinical vs. Statistical Significance

It is important to ask whether statistically significant differences are also clinically significant.

Statistical significance is a mathematical technique to measure whether the results of a study are likely to be true, or whether they could have occurred by chance. Statistical significance is calculated as the probability that an effect observed in a research study is occurring because of chance. Statistical significance is usually expressed as a P-value. The smaller the P-value, the less likely it is that the results are due to chance (and more likely that the results are true). Researchers generally believe the results are probably true if the statistical significance is a P-value less than 0.05 (p<.05).
In a large study, a small difference may be statistically significant. For example, does a 1- or 2-point difference on a 100-point dementia scale matter to your patients?

Statistically significant does not necessarily mean important. Size of effect determines clinical importance not the presence of statistical significance. Conversely, if a study finds no difference, it is important to ask whether it was large enough to detect a clinically important difference and if a difference actually existed. A study with too few patients is said to lack the power to detect a difference.

Cochrane Collaboration

The Cochrane Collaboration is a worldwide association of groups who create and maintain systematic reviews of research literature for specific topic areas.

Cohort study

The analytic method of epidemiologic study in which subsets of a defined population can be identified who are, have been, or in the future may be exposed/not exposed/ exposed in different degrees, to a factor or factors hypothesized to influence the probability of occurrence of a given disease or other outcome. The main feature of cohort study is observation of large numbers over a long period (commonly years) with comparison of incidence rates in groups that differ in exposure levels.

Confidence interval (CI)

The range around a study’s result within which we would expect the true value to lie. CIs account for the sampling error between the study population and the wider population the study is supposed to represent.

Conflict of interest

A conflict of interest occurs when those who are involved with the conduct or reporting of research also have financial or other interests, or where they can benefit in some other way, depending on the results of the research. The obvious example is where a pharmaceutical company reports results of a trial of its product. Conflict of interest statements often accompany published papers. It is a statement by a contributor to a report or review of personal financial or other interests that could have influenced the findings or their interpretation. Conflicts of interest are the norm, and not the exception.


“Confounding refers to a situation in which a measure of the effect of an intervention or exposure is distorted because of the association of exposure with other factor(s) that influence the outcome under investigation. This can lead to erroneous conclusions being drawn, particularly in observational studies”.

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