L7 21/02

Question 1

What is a survey?

Answer 1

A non-experimental quantitative research design. It is a study design that may use a questionnaire.

Question 2

What form can a survey adopt?

Answer 2

A questionnaire or based on another means of gathering data from people

Question 3

Why is a survey quantitative?

Answer 3

• Each participant has the same questions (the process does not change – it remains the same)
• It produces numbers that can be subjected to statistical analysis
• We can assign numbers to people answers by manipulating data

Question 4

Open questions elicit what kind of data?

Answer 4

Qualitative (textual)

Question 5

Limitation of survey

Answer 5

Often misused in health research

Question 6

Useful survey applications in healthcare

Answer 6

• Service evaluation – good or bad within healthcare
• Patient experience/opinion studies
• Service redesign

Question 7

5 things to maximise survey validity

Answer 7

• Use a clear research question – survey focused on research question
• Identify the population and a relevant, representative sample
• Choose a method of distribution to maximise response
• Plan the coding method: Variables labels for categorised answers
• Test the survey tool: Expert consensus groups, piloting

Question 8

Survey advantages

Answer 8

• Simple measure of attitudes, beliefs, values, understandings
• Easy access to most human populations
• Can address sensitive topics – anonymous
• Effective at collecting large amounts of information
• Collects highly standardised data – provided not asking lots of open questions
• Efficient; cheap and non-resource-intensive

Question 9

Survey challenges

Answer 9

• Response/completion rates are poor > around 30-40%: Particular issue with postal surveys, may need for ‘reminders’, must be short to ensure completion rate, small amount of data gathered
• No researcher control over sample: possible bias with who chooses to participate
• No control over data quality or accuracy: misunderstandings can affect accuracy
• Responses have to be retrospectively coded

Question 10

Demographic data (background information about participants)

Answer 10

• Gender
• Age Group
• Ethnic group
• Height, weight etc.
• Length of time having health conditions

Question 11

In order to maximise accuracy, data quality (and participation) closed response questions need to be what 4 things?

Answer 11

• Accurate (clearly linked to the point of the survey)
• Exhaustive (all possible options are covered)
• Mutually exclusive (so that only one answer is accurate)
• One dimensional (so that only one answer is possible)

Question 12

What are the 5 question types?

Answer 12

• Fixed Alternative Responses / Multiple Choice Questions (MCQ)
• Likert scales (agree, strongly agree etc)
• Multiple responses
• Filter questions (yes/no and follow up if answered yes)
• Open questions

Question 13

Other design considerations

Answer 13

• Document appearance
• Aesthetic and layout
• Use of white space
• Clarity of instructions for completion
• Grouping of questions into sections

Question 14

What is coding?

Answer 14

Coding is the practice of assigning a numerical value to fixed response alternatives so that it can be easily managed.

Question 15

Advantages of coding

Answer 15

• Useful in descriptive or evaluative designs
• Easy way to study attitudes, values, beliefs
• Useful in almost all populations
• Standardised data
• Gather large amounts of data
• Efficient
• Anonymous

Question 16

Limitations of coding

Answer 16

• Potential for response biases
• Low response rates, particularly in postal surveys
• Risk of misunderstanding
• Incomplete responses
• Potential inaccuracy
• Often badly designed

Question 17

Health designs often used validated scales such as..

Answer 17

• Hospital anxiety and depression (HAD) scale

- General Health Questionnaire (GHQ)

Question 18

Indicators of validity are…

Answer 18

• Focussed research question and purpose
• Clear identification of population and sample
• Piloting and revising the survey tool and coding method
• Accuracy, ease of use, relevance to aims of survey
• Logical and appropriate recruitment method
• Reliable data collection method (Self report; Face to face; Postal distribution; E-survey)
• Sound data analysis methods (ideally conducted by 2 independent researchers0

Question 19

Evaluating the survey tool

Answer 19

• Check that the survey tool relates to the research question
• Check what demographic data has been collected (NOT intrusive and always relevant to the issue)
• Consider if a previously validated tool has been used; if not then “why not”?
• Has the tool been piloted or validated

Question 20

Evaluating Sampling and Recruitment

Answer 20

• Population and sample should be related to the question
• Sampling technique should be related to the aims and NOT just what is easiest to achieve
• Is a random sample needed or will convenience sampling suffice?
• Recruitment will always be related to the sampling strategy and invitations to participate
• Issues surrounding sampling and recruitment should be discussed in the write-up

Question 21

Data collection methods (4)

Answer 21

• Self report
• Postal
• E-survey
• Face to face

Question 22

Evaluation of data analysis

Answer 22

• Analysis should use the data to answer the research question(s)
• Check for rigorous coding (preferably repeated by independent researcher)
• Data should be entered into a data management system (Excel, SPSS etc.)
• Descriptive statistics should describe the data (look for diagrams to clarify)
• Analysis should identify patterns
• Inferential statistics may be used; check their validity
• Interpretation should relate to the survey aims
• Beware of “fishing” techniques

Question 23

Advantages of surveys

Answer 23

• Useful in exploratory, descriptive or evaluative research designs
• Good for measuring attitudes, beliefs, values, understandings
• Can potentially access a wide population
• Useful for sensitive topics
• Provides anonymity
• Only appropriate if data can be standardised

Question 24

Disadvantages of surveys

Answer 24

• No researcher control over sample
• No control over data quality or accuracy
• Incomplete responses/data sets
• Risk of misunderstandings or ambiguities
• No opportunity for clarification (except face to face)
• Poor response rates