Voluntary response sample is defined as a sample made up of self-selected participants. This is a type of non-probability sampling. In stark contrast to random sampling, voluntary sampling yields a response bias as members are self-selected. The responses received through this type of sampling are commonly biased towards a particular topic.
A person chooses to volunteer for the survey because they may have a particularly strong opinion towards the subject or due to convenience and ethical reasons.
Often, we come across surveys on social media regarding topics like ‘gun control,’ ‘abortion,’ ‘immigration policies,’ ‘police brutality,’ etc. The respondents are not directly contacted or urged to answer the survey. It depends purely on the individual’s willingness and awareness of the topic to participate in the study. The factors that encourage a person to respond to a survey are mostly – ease of responding, strong opinion about the topic, ethical reasons, etc.
Another example of a voluntary response sample is polling through call-in radio shows. Here, only a part of the population that listens to the particular radio station (and who chooses to answer by dialing in) participate in the poll. The responses collected do not accurately reflect the feelings of the entire population as only those people who choose to call in and take part in the study will bother to respond.
Uses of voluntary response sampling:
Frankly speaking, this type of sampling method is not useful in many cases when the study conducted is of high importance or big decisions have to be made based on the outcome of the results. The result of the study only reflects one aspect of the whole story. You are better off by applying random sampling. This method, however, may be deployed by TV show hosts or radio show hosts who want to affirm their opinion on a specific topic or topics where the volunteers also tend to lean towards the same opinion as the survey host.
An example of this method is when questions about evolution are asked to viewers/followers of a religious tv show, they will always answer based on the influence of the TV show and put away ideas of evolution even though there is ample scientific proof to support the theory of evolution. The outcome here is totally biased, unreasonable and unusable in the real world.
With everything said and done, there is hope and scope for adopting voluntary response sampling to your study. Organizations use this method as a marketing tool to advertise their products all the time. Voluntary response sampling can help turn your existing customers into advocates of your brand thereby potentially increasing your brand awareness and also the revenue and sales of your product.
Attributes of a voluntary response sample
The attributes of a voluntary response sample are:
- Undercoverage: It occurs when most members of the population are insufficiently represented in the sample. Only people who follow the talk show/ radio show/ TV show or those who belong to the community are able to take the survey. Persons who may have a different view or a neutral view about the subject may not be able to participate in the study as they do not follow the talk/radio/TV shows.
- Biased responses: Response bias occurs when sample members are self-selected volunteers, as involuntary samples. The respondents tend to answer questions based on strong opinions about the subject. A good sample is representative; meaning each sample point represents the attributes of a known number of population elements. The end result of the survey may not be accurate.
- Easy to gather data and access: Finding respondents for the survey is easy as persons who have a strong opinion about the subject tend to give their feedback about the topic. The individuals choose to be involved as motivation is high regarding the topic.
- Errors in data quality: This goes without saying; responses will tend to lean towards a specific idea compromising the data quality and making the data received very biased and unusable.
A voluntary response sample in most cases will yield biased responses. Response bias is also caused by an inability or absence of desire to respond to questions correctly. The reason being, respondents already favor a specific type of outcome and will answer according to that outcome. If you are a researcher seeking quality, varied responses, always avoid this method. But if taking this approach is unavoidable, here are a few factors you must keep in mind to avoid bias as much as possible.
- Keep your questions short and clear: Half the battle of avoiding response bias is won by framing the right survey questions. A clearly understood question is more likely to be answered correctly compared to a long complicated question.
- Avoid leading questions: While designing your questionnaire, avoid asking hypothetical questions. Also, avoid forthright questions. For the question, ‘are you happy with the product or service?’, instead of giving a yes/no option, give them a variety of options to capture data more accurately. Example answer statements may be – ‘I enjoy using this product/service,’ ‘This product/service meets my needs,’ ‘I wish I could get more out of the product/service,’ ‘The product/service is below my expectation.’
- Break down difficult concepts: To capture true data, break down and simplify the questions for the respondent. Long questions cause fatigue and may not capture the actual feeling of the respondent.
- Provide simple, exhaustive answer options: As you do with simple, direct questions, keep the answer options simple too. Respondents will tend to answer questions better if they have easy options laid down in front of them.
- Use precise simple language: Always avoid the use of difficult/high language in questions and answer options. Your respondent will choose the most accurate answer based on his understanding of the question and answer.
- Do not influence the answers: Never influence the answers. This will add no value to the study. You may receive many responses on your survey but they will all be influenced by your approach and data captured at the end will be irrelevant.
- A simple way to conduct a study
- Data easy to gather
- Easy to access
- Requires little effort by the researcher
- Has scope to provide rich, qualitative information
- Minimal effort required
- No control over sample
- Comprised of strongly opinionated people.
- Inaccurate data
- Biased responses
- Not advisable to make inferences
- Favors a certain outcome
- Drops the idea of an unbiased survey
- Outcome influenced by the researcher
- Affects the reliability of the study
One way to assure that the sample has a fair chance of mirroring the population is to apply randomness. The most basic random method is simple random sampling. It means that each member of the population has an equal chance of being chosen. In this method, you immediately overcome the problem of biased responses. You will learn from both sides of the population i.e. you will hear the negatives and the positives of the given topic. This will help you understand the topic better and come up with more accurate strategies compared to voluntary responses. While setting up the survey, you can also set up screener questions to identify and segregate the persons taking the survey.
Although adopting voluntary response sampling has his pitfalls, the ease of creating and deploying surveys are non-expensive; thus are widely used.