If you want to create a press release based on survey results, you need to make sure your survey questions are neutral and unbiased. Otherwise, you risk losing credibility, alienating your audience, and undermining your message. Here are some best practices for using neutral language in survey questions.
A leading question is one that suggests a desired answer or implies a certain opinion. For example, "Do you agree that our product is the best in the market?" is a leading question that assumes the respondent already likes the product. Leading questions can skew the results and make your press release look biased or manipulative. Instead, use neutral and open-ended questions that allow respondents to express their own views. For example, "How would you rate our product compared to other options in the market?"
Loaded words are words that have strong emotional or value judgments attached to them. For example, "How do you feel about the outrageous price increase of our competitor?" is a question that uses loaded words to influence the respondent's attitude. Loaded words can trigger emotional reactions and distort the data. Instead, use neutral and factual words that describe the situation without implying any judgment. For example, "How do you feel about the 20% price increase of our competitor?"
Below are some examples that show the difference between sentences with loaded words and their neutral counterparts: Loaded: Why do you always act so recklessly? Neutral: Can you explain your decision-making process in that situation? Loaded: The senator's decision was a disaster. Neutral: The senator's decision had unforeseen consequences. Loaded: That criminal's horrific acts are indefensible. Neutral: That individual's actions led to legal consequences. Loaded: Your aggressive approach isn’t helping. Neutral: Your approach might benefit from a different perspective. Loaded: She's too lazy to get the job done. Neutral: She hasn't completed the task yet.
A double-barreled question is one that asks two or more questions in one, but only allows one answer. For example, "How satisfied are you with the quality and delivery of our service?" is a double-barreled question that confuses the respondent and makes the data unclear. Double-barreled questions can hide important differences and reduce the validity of your press release. Instead, use single and specific questions that focus on one aspect at a time. For example, "How satisfied are you with the quality of our service?" and "How satisfied are you with the delivery of our service?"
Here are examples of double-barreled questions and their revised, clearer simple specific versions: Double-Barreled: Do you think our website is attractive and user-friendly? Single: a. Do you think our website is attractive? b. Do you find our website user-friendly? Double-Barreled: Is the teacher knowledgeable and approachable? Single: a. Do you think the teacher is knowledgeable? b. Do you find the teacher approachable? Double-Barreled: Do you support the new tax policy and healthcare reform? Single: a. Do you support the new tax policy? b. Do you support the healthcare reform?
Confusing or ambiguous terms are terms that have different meanings or interpretations for different people. For example, "How often do you use our product?" is a question that uses a confusing term that could mean daily, weekly, monthly, or something else. Confusing or ambiguous terms can create confusion and inconsistency in the data. Instead, use clear and precise terms that define the scope and scale of the question. For example, "How many times per week do you use our product?"
Avoiding confusing or ambiguous terms is crucial for clear communication. Here are some examples that demonstrate how to rephrase or clarify such terms: Ambiguous: "Do you enjoy light reading?" Clearer: "Do you enjoy reading books that are not academically or intellectually challenging, such as romance or beach novels?" Ambiguous: "How do you feel about current events?" Clearer: "How do you feel about recent political developments in your country?" Ambiguous: "Please provide your latest educational experience." Clearer: "Please specify the most recent educational degree you've completed or the current degree program you're enrolled in."
Assumptions or stereotypes are beliefs or generalizations that may not apply to all respondents or situations. For example, "How do you balance your work and family responsibilities?" is a question that assumes that all respondents have work and family responsibilities, and that they need to balance them. Assumptions or stereotypes can exclude or offend some respondents and affect their responses. Instead, use inclusive and respectful questions that acknowledge the diversity and complexity of your audience. For example, "How do you manage your time and priorities?"
Being aware of potential assumptions or stereotypes and crafting questions that are neutral and inclusive can lead to better and more authentic responses. Here are more examples illustrating how to rephrase questions or statements to avoid assumptions and stereotypes: Assumption/Stereotype: Asking a woman, "How do you handle your career and kids?" Inclusive Question: "What does your daily routine look like?" Assumption/Stereotype: Asking an older employee, "Are you comfortable with technology?" Inclusive Question: "Are you familiar with this specific software or tool?" Assumption/Stereotype: Asking someone of Asian descent, "Where are you really from?" Inclusive Question: "Can you tell me about your background or heritage?"
The final best practice for using neutral language in survey questions is to test and revise your questions before launching your survey. Testing your questions can help you identify any problems or errors that may affect the data quality and reliability. You can test your questions by conducting a pilot survey with a small sample of your target audience, or by asking for feedback from experts or colleagues. Based on the test results, you can revise your questions to make them more neutral, clear, and relevant for your press release.
Testing questions is prudent but doesn't guarantee neutrality. Pilot surveys, while helpful, may not unveil all biases. Expert feedback, though valuable, is subjective. Data quality, a perpetual challenge, persists. Neutrality, a lofty goal, can be elusive. In the pursuit of unbiased survey questions, the real challenge lies not just in testing and revising but in navigating the inherent subjectivity that colors language, where even the most meticulous revisions may inadvertently carry subtle biases that defy the structured pursuit of neutrality in survey design.