Paraphrasing in Research Surveys: Everything You Need to Know

If you have ever phrased questions for a survey, you know that sometimes there’s already a hypothesis in your mind of how respondents are going to answer them. That’s why you can often see questions that delicately (or not so much) push you towards one of the available choices. Nonetheless, the goal of every research is to receive reliable results, and the formulation of every question plays a crucial role in this process. Therefore, paraphrasing in surveys is an essential skill you need to master.

There can also be other reasons why you might need to rewrite questions, including the adaptation of your questionnaire to different audiences or the simplification of complex language. On top of that, you might need to create surveys in different languages and rely on tools like a free Spanish paraphraser, for example. All in all, the main challenge is to preserve the original meaning while reducing bias in survey questions that could compromise your data.

Let’s explore practical strategies that will help your questions become clearer and remain valid.

What Kind of Bias Is There?

Before diving deep into questionnaire rewriting techniques, let’s review several forms of bias that can distort your research findings.

Leading questions

We’ve mentioned briefly this form in the introductory paragraphs. It contains assumptions or suggests that certain answers are more acceptable.

Example: If one of your questions looks like this: "How satisfied are you with our excellent customer service?", it presupposes that the service is excellent and doesn’t give a respondent any chance to indicate that the service might actually be bad. That’s why it’s better to go for a neutral version: "How would you rate our customer service?"

Loaded language

When you use strong adjectives that have a clear positive or negative emotional trigger, you might get biased results.

Example: "Do you support the government's reckless spending policies?" versus "What is your opinion on current government spending levels?"

Double-barreled questions

You can recognize these questions right away because they ask about two issues simultaneously and make responses ambiguous.

Example:  "How satisfied are you with the price and quality of our products?" cannot be answered meaningfully by someone satisfied with quality but not price.

Acquiescence bias

Respondents, especially those who are in a hurry or don’t get that much engaged in the process, tend to agree with statements simply to complete the task faster.

Social desirability bias

People are social creatures and have a natural desire to be accepted by others. That’s why respondents can often consciously or subconsciously present themselves in a favorable light and skew answers toward perceived societal norms. When you word a question poorly, they will claim to exercise more or read more frequently than they actually do.

How Not to Make Things Worse

The most important thing to remember about survey question paraphrasing is that every word change carries the risk of changing what the question really measures. When you aim to simplify the language to make the question easier for respondents to understand, you should always check if it still has the same meaning.

For instance, if after paraphrasing you end up with this version: "Have you been feeling sad lately?" instead of the initial one - "Over the past two weeks, how often have you felt down, depressed, or hopeless?", you haven’t done a great job. The paraphrased version no longer measures the same construct because the timeframe becomes vague, and the frequency measure disappears entirely.

The key is recognizing when paraphrasing serves the research and when it serves convenience. You should generally avoid changing standardized instruments unless you're developing a new version that will undergo its own validation process. Your goal is always to maintain construct validity while eliminating bias.

When and Why to Paraphrase: Bias-Specific Strategies

We have finally got to the fun part - specific principles that help you avoid bias in survey questions.

Polarity switch

The most direct attack on the questions that people tend to agree with to manage the task as fast as possible is creating positively and negatively worded items within the same scale.

Here are two quick examples of statements measuring customer satisfaction with a service:

●       Original (Positive): "I am always satisfied with this service."

●       Paraphrased (Negative): "I sometimes feel disappointed by this service."

By forcing the respondent to alternate between agreeing to a positive statement and disagreeing with a negative one (or vice versa), you compel them to read and process the content of each item. Then, you can break this behavioral pattern.

Note that negative wording naturally increases the cognitive load. Therefore, when you reverse polarity, ensure the phrasing remains unambiguous and straightforward. Otherwise, there’s a high risk of confusing the respondent and creating a different kind of error entirely.

Indirect approach

To avoid bias in survey questions on sensitive topics, you can rely on the indirect approach through paraphrasing. This involves two main strategies: depersonalizing the question or softening the language.

Depersonalizing involves asking about most people or others in similar situations to give the respondent psychological distance and allow them to answer more truthfully:

●       Original (Direct): "Have you ever exaggerated your income on a tax form?"

●       Paraphrased (Indirect): "In today's economy, how common is it for people you know to under-report cash earnings?"

Randomization Element

Sometimes, the bias isn't in the question itself but in the questions that immediately precede it. Subtle changes in the phrasing of earlier questions can prepare the respondent and cause a context effect that biases their responses.

In these situations, you want to create parallel forms with semantically equivalent questions that you phrase differently. The next step is to randomize these parallel forms across respondents in a split-sample design to prevent any bias introduced by a specific phrasing from impacting the overall findings.

No embedded assumptions

When you ask your respondents about how often they exercise, you assume they exercise at all. But what if they don’t? A better approach is to ask them how many days they engage in physical exercise in a typical week first, and make sure to include a "0 days" option. When paraphrasing, look for assumptions about behavior or knowledge as well.

Symmetrical balance

No matter what paraphrasing techniques you use, ensure the endpoints of rating scales carry equal weight. There should be no scales ranging from "Strongly disagree" to "Agree" because they lack symmetry and bias responses toward agreement.

Careful simplification

Without a doubt, you might need to replace technical language with more common terms. However, it doesn’t mean you should choose evaluative wording instead of neutral one. After you change the question "What is your assessment of the efficacy of the intervention?" to "Did the program work well?", you introduce positive bias. To avoid this, your paraphrased question can be "How effective was the program?" Similarly, replace jargon systematically: "socioeconomic status" becomes "income and education level" rather than loaded phrases like "class position" or "social standing."

Multiple versions

Even when you believe that all the questions are bias-free after you’ve paraphrased them, there still might be some points that you’ve missed. Therefore, the most effective approach involves creating several versions. It will help you understand whether different wordings produce significantly different response patterns when they shouldn't.

Pre-testing and cognitive interviewing

It’s always a bad idea to make paraphrasing decisions in a vacuum, as you need to validate them using the combination of these two options:

●       Cognitive interviews are when you sit down with a small group of test respondents and ask them what they think the question means. Make sure to ask them to think aloud while answering. If a respondent interprets the paraphrased item differently from the original item, you have identified semantic drift and must revise the item.

●       Pilot studies follow this stage and check for empirical differences in mean scores. If the original item and the paraphrased item yield significantly different means in a pilot, it suggests the meaning has been lost.

Only when both the cognitive and statistical checks pass can you use the paraphrased item in your survey.

Validation and Responsibility

Although the process of paraphrasing is quite creative, you still need to use a methodological approach. Here’s how to do it.

Documentation

Record and document every paraphrasing decision, no matter how small, to have the audit trail of your actions. There should be information on the original item, the paraphrased item, and the reason for rewriting. This non-negotiable step ensures that the instrument's evolution is easy to trace and justify.

Statistical validation

Confirmatory factor analysis is the correct standard to use when you want to make sure that paraphrased items measure the same underlying trait. It allows you to test whether the original set of items and the newly paraphrased set all load reliably onto the hypothesized single latent factor. If the model fit statistics are poor, it confirms that the fidelity was lost. Furthermore, you should also run simple correlation checks between the original and modified items.

Final Remarks

As you develop your surveys, invest enough time in question development and testing. The hours you spend carefully paraphrasing and validating questions will save countless hours later trying to explain unexpected results.