Non-random sampling is commonly applied when qualitative methods e. Non-random sampling deliberately targets individuals within a population. There are three main techniques.
Finally, 3 snowballing: the sample is identified as the survey progresses; as one individual is surveyed he or she is invited to recommend others to be surveyed. It is important to use the right method of sampling and to be aware of the limitations and statistical implications of each. The need to ensure that the sample is representative of the larger population was highlighted earlier and, alongside the sampling method, the degree of sampling error should be considered.
Sampling error is the probability that any one sample is not completely representative of the population from which it has been drawn [ 9 ]. Although sampling error cannot be eliminated entirely, the sampling technique chosen will influence the extent of the error. Simple random sampling will give a closer estimate of the population than a convenience sample of individuals who just happened to be in the right place at the right time.
What sample size is required for a survey? There is no definitive answer to this question: large samples with rigorous selection are more powerful as they will yield more accurate results, but data collection and analysis will be proportionately more time consuming and expensive.
Essentially, the target sample size for a survey depends on three main factors: the resources available, the aim of the study, and the statistical quality needed for the survey.
If statistical analysis is to be performed on the data then sample size calculations should be conducted. For practical recommendations on sample size, the set of survey guidelines developed by the UK Department of Health [ 11 ] should be consulted. Larger samples give a better estimate of the population but it can be difficult to obtain an adequate number of responses.
It is rare that everyone asked to participate in the survey will reply. To ensure a sufficient number of responses, include an estimated non-response rate in the sample size calculations. Response rates are a potential source of bias. The results from a survey with a large non-response rate could be misleading and only representative of those who replied.
French [ 12 ] reported that non-responders to patient satisfaction surveys are less likely to be satisfied than people who reply. In any study, the final response rate should be reported with the results; potential differences between the respondents and non-respondents should be explicitly explored and their implications discussed.
There are techniques to increase response rates. A questionnaire must be concise and easy to understand, reminders should be sent out, and method of recruitment should be carefully considered.
A most useful review of methods to maximize response rates in postal surveys has recently been published [ 14 ]. Researchers should approach data collection in a rigorous and ethical manner. The following information must be clearly recorded:. How, where, how many times, and by whom potential respondents were contacted. How many people were approached and how many of those agreed to participate. How did those who agreed to participate differ from those who refused with regard to characteristics of interest in the study, for example how were they identified, where were they approached, and what was their gender, age, and features of their illness or health care.
What was the response rate i. Researchers must prepare to spend substantial time on the data analysis phase of a survey and this should be built into the project plan. When analysis is rushed, often important aspects of the data are missed and sometimes the wrong analyses are conducted, leading to both inaccurate results and misleading conclusions [ 16 ].
However, and this point cannot be stressed strongly enough, researchers must not engage in data dredging, a practice that can arise especially in studies in which large numbers of dependent variables can be related to large numbers of independent variables outcomes.
The method of data analysis will depend on the design of the survey and should have been carefully considered in the planning stages of the survey. Data collected by qualitative methods should be analysed using established methods such as content analysis [ 18 ], and where quantitative methods have been used appropriate statistical tests can be applied.
Describing methods of analysis here would be unproductive as a multitude of introductory textbooks and on-line resources are available to help with simple analyses of data e. For advanced analysis a statistician should be consulted. When reporting survey research, it is essential that a number of key points are covered though the length and depth of reporting will be dependent upon journal style.
Explain the purpose or aim of the research, with the explicit identification of the research question. Explain why the research was necessary and place the study in context, drawing upon previous work in relevant fields the literature review. Describe in proportionate detail how the research was done. State the chosen research method or methods, and justify why this method was chosen.
Describe the research tool. If an existing tool is used, briefly state its psychometric properties and provide references to the original development work. If a new tool is used, you should include an entire section describing the steps undertaken to develop and test the tool, including results of psychometric testing. Describe how the sample was selected and how data were collected, including:. Present the results of the research.
The results section should be clear, factual, and concise. Interpret and discuss the findings. The discussion should assess how well the study met the research question, should describe the problems encountered in the research, and should honestly judge the limitations of the work. The expectations of the specific audience for whom the work is being written. The conventions that operate at a general level with respect to the production of reports on research in the social sciences.
Any survey should be conducted in an ethical manner and one that accords with best research practice. Two important ethical issues to adhere to when conducting a survey are confidentiality and informed consent.
The professional bodies listed below, among many others, provide guidance on the ethical conduct of research and surveys. Survey research demands the same standards in research practice as any other research approach, and journal editors and the broader research community will judge a report of survey research with the same level of rigour as any other research report. This is not to say that survey research need be particularly difficult or complex; the point to emphasize is that researchers should be aware of the steps required in survey research, and should be systematic and thoughtful in the planning, execution, and reporting of the project.
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We are able to remove any duplicates to clean up the data. To weed out straight liners who may be suffering from survey fatigue, consider shortening the questionnaire or use more routing where possible so that respondents only answer the questions relevant to them. This is particularly relevant now that an increasing number of people are using mobile devices to respond to surveys, meaning their attention span is likely to be even shorter.
Our own research shows that mobile responses accounted for 46 per cent of all responses in the last year and are likely to overtake desktop responses in the next six months. This allows respondents to complete a survey in more than one session, by saving the answers already given and allowing the respondent to continue where they left off at another time. Drop-out rates also increase with survey length.
Having fewer responses will make your data less statistically robust so do give the issue of survey length serious consideration. Any longer than that and the quality of response is likely to be compromised, if indeed respondents even get to the end of the survey and submit their answers. A well-structured and clear survey design will give you better chances of attracting honest responses from the first question to the last.
Where you have questions with a long list of options, say in a multiple choice or matrix question, consider rotating the answer options. This should eliminate any bias to the top answers or fall out for lower rows due to respondent fatigue or survey-speeding.
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