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Validity and reliability in quantitative studies
  1. Roberta Heale1,
  2. Alison Twycross2
  1. 1School of Nursing, Laurentian University, Sudbury, Ontario, Canada
  2. 2Faculty of Health and Social Care, London South Bank University, London, UK
  1. Correspondence to: Dr Roberta Heale,
    School of Nursing, Laurentian University, Ramsey Lake Road, Sudbury, Ontario, Canada P3E2C6; rheale{at}

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Evidence-based practice includes, in part, implementation of the findings of well-conducted quality research studies. So being able to critique quantitative research is an important skill for nurses. Consideration must be given not only to the results of the study but also the rigour of the research. Rigour refers to the extent to which the researchers worked to enhance the quality of the studies. In quantitative research, this is achieved through measurement of the validity and reliability.1


Validity is defined as the extent to which a concept is accurately measured in a quantitative study. For example, a survey designed to explore depression but which actually measures anxiety would not be considered valid. The second measure of quality in a quantitative study is reliability, or the accuracy of an instrument. In other words, the extent to which a research instrument consistently has the same results if it is used in the same situation on repeated occasions. A simple example of validity and reliability is an alarm clock that rings at 7:00 each morning, but is set for 6:30. It is very reliable (it consistently rings the same time each day), but is not valid (it is not ringing at the desired time). It's important to consider validity and reliability of the data collection tools (instruments) when either conducting or critiquing research. There are three major types of validity. These are described in table 1.

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Table 1

Types of validity

The first category is content validity. This category looks at whether the instrument adequately covers …

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