News Media Accountability and Trust Survey
Assesses how news consumers judge the accountability practices of the outlets they follow — corrections, sourcing, transparency about ownership and conflicts of interest — and prioritizes which practices matter most to trust. An AI follow-up interview reconstructs a specific incident where trust in a news source was gained or lost. Built for newsrooms, media watchdogs, and researchers studying press credibility.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
In the last 30 days, how often have you come across a news story you suspected was inaccurate or misleading?
- Never
- Once or twice
- Several times
- Almost every time I checked the news
- Not sure
Thinking about the mainstream news outlets you follow, how would you rate them on each of the following?
- Issuing prompt, visible corrections when they get something wrong
- Citing original sources clearly
- Disclosing conflicts of interest
- Distinguishing opinion content from straight news reporting
- Disclosing who owns and funds them
How confident are you that major news outlets correct their mistakes when errors are pointed out?
The last time you noticed a factual error in a news story, what did you do?
- Contacted the outlet directly
- Posted about it on social media
- Mentioned it to friends or family
- Looked for confirmation from another source
- Stopped trusting that outlet
- Nothing, I let it go
From the accountability practices below, which matters most to you and which matters least when deciding whether to trust a news outlet?
- Issuing prompt, visible corrections
- Clearly citing original sources
- Disclosing conflicts of interest
- Distinguishing opinion from news reporting
- Disclosing ownership and funding
- Having an accessible corrections or complaints process
- Explaining how a story was reported
- Using independent fact-checking
If you had 100 points to spend on improving how much you trust a news outlet, how would you divide them across these factors?
- Prompt, visible corrections when errors occur
- Clear citation of sources
- Transparent ownership and funding
- Clear labeling of opinion vs. news content
- An accessible way to report errors or complaints
Read the correction notice below. Highlight the parts that make you more confident in the outlet, and the parts that make you less confident.
Correction: An earlier version of this article incorrectly stated that the new policy took effect in March. It took effect in April. This version has been updated, and we regret the error. (Template n…
Reconstruct a specific, recent incident where the respondent's trust in a news outlet was gained or lost over an accountability issue — what happened, whether the outlet acknowledged it, and how the respondent reacted. Anchor on their confidence rating and the action they said they took after noticing an error, and probe what specifically the outlet would have needed to do to restore or strengthen trust. If they say they 'let it go,' probe whether that was resignation or genuine indifference.
That covers the accountability questions — thank you for the thoughtful answers. Just a few optional background questions to help us compare views across groups.
What is your age range?
- Under 18
- 18-24
- 25-34
- 35-44
- 45-54
- 55-64
- 65+
- Prefer not to say
Where do you primarily get your news? (select all that apply)
- Social media
- Television
- Print newspapers or magazines
- Online news sites or apps
- Radio
- Podcasts
- Prefer not to say
Which best describes your political leaning?
- Left
- Center-left
- Center
- Center-right
- Right
- Prefer not to say
All done — thank you! Your responses will be combined with others to build a report on which accountability practices actually move audience trust, shared with newsroom and research partners.
What’s included
AI follow-ups
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Attention checks
Built-in safeguards against rushed answers and low-quality respondents.
AI-drafted copy
Wording, ordering, and branching written by the AI — tuned to your research goal.
Auto report
Themes, quotes, and a plain-English summary write themselves once responses come in.
How it compares
We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.
Why this template
- Goes beyond static rating questions with an AI follow-up interview that reconstructs a specific incident where the respondent's trust in a news outlet was gained or lost, surfacing concrete stories rather than just abstract scores.
- Uses a max-diff exercise and a constant-sum allocation to force real trade-offs between accountability practices (corrections, sourcing, ownership transparency) instead of letting everything score 'important.'
- Includes a text-highlight exercise where respondents mark which parts of an actual correction notice build their confidence, giving qualitative, evidence-level detail on what 'good' transparency looks like.
- Combines matrix ratings, an opinion-scale trust-in-corrections item, and behavioral recall questions (what did you do the last time you spotted an error) with an auto-generated report, on a platform with a free tier and transparent prompts.
QuestionPro
Media Accountability Survey Questions + Sample Questionnaire TemplateThis is a sample questionnaire/guide page listing example media accountability questions rather than an interactive, fielding-ready survey experience. It's a reasonable starting point for question wording but reads as static reference content. There's no indication of adaptive follow-up or built-in scoring on the page.
What it does well
- Provides ready-made sample question wording specifically on media accountability topics
- Backed by a large, established survey platform with broad question-type support
- Useful as a quick-start question bank for researchers drafting their own instrument
Where it falls short
- Presents fixed sample questions with no adaptive AI follow-up to probe individual incidents or reasoning
- No mention of automated per-response quality scoring or transparent, published prompt methodology
- Appears to be a static questionnaire template/guide rather than a voice- or chat-based interview experience
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.