Electronic surveys: how to maximise success.
OBJECTIVE
To draw on the researchers' experience of developing and distributing a UK-wide electronic survey. The evolution of electronic surveys in healthcare research will be discussed, as well as simple techniques that can be used to improve response rates for this type of data collection.


BACKGROUND
There is an increasing use of electronic survey methods in healthcare research. However, in recent published research, electronic surveys have had lower response rates than traditional survey methods, such as postal and telephone surveys.


METHODS
This is a methodology paper.


CONCLUSIONS
Electronic surveys have many advantages over traditional surveys, including a reduction in cost and ease of analysis. Drawbacks to this type of data collection include the potential for selection bias and poorer response rates. However, research teams can use a range of simple strategies to boost response rates. These approaches target the different stages of achieving a complete response: initial attraction through personalisation, engagement by having an easily accessible link to the survey, and transparency of survey length and completion though targeting the correct, and thereby interested, population.


CONCLUSIONS
The fast, efficient and often 'free' electronic survey has many advantages over the traditional postal data collection method, including ease of analysis for what can be vast amounts of data. However, to capitalise on these benefits, researchers must carefully consider techniques to maximise response rates and minimise selection bias for their target population.


CONCLUSIONS
Researchers can use a range of strategies to improve responses from electronic surveys, including sending up to three reminders, personalising each email, adding the updated response rate to reminder emails, and stating the average time it would take to complete the survey in the title of the email.
Critical care, Glasgow Royal Infirmary, Nursing and Health Care School, University of Glasgow, College of Medical, Veterinary and Life Sciences, University of Glasgow.
Joanne
J
McPeake
Meghan
M
Bateson
Anna
A
O'Neill
D003625:Data Collection / Q000379:methods* / Q000706:statistics & numerical data; D034742:Electronic Mail; D006801:Humans; D015399:Nursing Research / Q000379:methods* / Q000706:statistics & numerical data; D015983:Selection Bias; D011795:Surveys and Questionnaires