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Participant Preferences for Anonymized Data Sharing & Licensing

Measures research participants' comfort with anonymized data sharing, preferred licensing models, repository preferences, and required safeguards. Designed for IRB-compliant studies where researchers need informed consent data on secondary data use.

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AI-Powered Questions

Intelligent follow-up questions based on responses

Automated Analysis

Real-time sentiment and insight detection

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Detailed Reports

Comprehensive insights and recommendations

Template Overview

21

Questions

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This professionally designed survey template helps you gather valuable insights with intelligent question flow and automated analysis.

Sample Survey Items

Q1
Chat Message
Welcome to this survey on anonymized data sharing and licensing. The purpose of this survey is to understand your preferences and concerns regarding sharing anonymized research data. Your responses will help inform data management and sharing practices. • Participation is entirely voluntary. You may stop at any time without penalty. • There are no right or wrong answers — we are interested in your honest opinions. • Your responses are confidential and will be reported only in aggregate. • Estimated completion time: 6–8 minutes. By proceeding, you confirm that you have read and understood this information and consent to participate.
Q2
Multiple Choice
How familiar are you with Creative Commons or other data-sharing licenses?
  • Very familiar
  • Somewhat familiar
  • Heard of them but not sure what they mean
  • Not familiar at all
Q3
Multiple Choice
Have you previously contributed data to a research study that was later shared or deposited in a public repository?
  • Yes
  • No
  • Not sure
Q4
Opinion Scale
How comfortable are you with sharing anonymized data from this study with other researchers?
Range: 1 7
Min: Not at all comfortableMid: NeutralMax: Very comfortable
Q5
Opinion Scale
How concerned are you about the possibility that anonymized data could be linked back to you (re-identification)?
Range: 1 7
Min: Not at all concernedMid: NeutralMax: Extremely concerned
Q6
Multiple Choice
Which types of data would you be comfortable sharing in anonymized form? Select all that apply.
  • Survey responses
  • Interview transcripts (de-identified)
  • Audio or video recordings (voice/face removed or altered)
  • Physiological or sensor data
  • Location or time-stamped activity data
  • Code or analysis scripts
  • None of the above
Q7
Multiple Choice
If this anonymized dataset were shared, which license type would you most prefer?
  • CC BY (attribution required)
  • CC BY-NC (non-commercial use only)
  • CC0 (no restrictions / public domain)
  • Other (please specify)
  • Not sure / no preference
Q8
Opinion Scale
When choosing a data license, how important is it to you that others must give proper attribution when using the data?
Range: 1 7
Min: Not at all importantMid: NeutralMax: Extremely important
Q9
Opinion Scale
How important is it to you that the data cannot be used for commercial purposes?
Range: 1 7
Min: Not at all importantMid: NeutralMax: Extremely important
Q10
Opinion Scale
How important is it to you that reuse of the data is as easy and unrestricted as possible for other researchers?
Range: 1 7
Min: Not at all importantMid: NeutralMax: Extremely important
Q11
Ranking
Please rank the following repository types in order of your preference for depositing this anonymized dataset (1 = most preferred).
Drag to order (top = most important)
  1. Institutional repository (university/organization)
  2. Domain/discipline-specific repository
  3. Generalist repository (e.g., Zenodo, Figshare)
  4. Controlled-access repository (application and review required)
  5. Private storage (no public sharing)
Q12
Multiple Choice
Which safeguards do you believe should be in place before anonymized data are shared? Select all that apply.
  • Data use agreement (DUA) or terms of use
  • Access committee review/approval
  • Only aggregate or highly de-identified data released
  • Embargo period before release
  • User authentication (e.g., two-factor authentication)
  • Citation and attribution requirements
  • Access logs and audit trails
  • None of the above
Q13
Multiple Choice
After your data have been deposited in a repository, which best describes your preference for data withdrawal?
  • I should be able to request withdrawal at any time
  • Withdrawal should be allowed until public release, then no longer possible
  • Withdrawal should not be possible after anonymization
  • Not sure / it depends on the circumstances
Q14
Long Text
Based on your responses in this survey, please share any additional conditions, concerns, or thoughts that would affect your comfort with anonymized data sharing and licensing.
Max chars
Q15
AI Interview
We'd like to explore your views on anonymized data sharing in a bit more depth. An AI moderator will ask you a couple of follow-up questions based on your earlier responses.
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Reference questions: 6
Q16
Dropdown
What is your age group?
  • 18–24
  • 25–34
  • 35–44
  • 45–54
  • 55–64
  • 65+
  • Prefer not to say
Q17
Multiple Choice
How do you describe your gender?
  • Woman
  • Man
  • Non-binary
  • Prefer to self-describe
  • Prefer not to say
Q18
Dropdown
What is the highest level of education you have completed?
  • Less than high school
  • High school or equivalent
  • Some college / Associate degree
  • Bachelor's degree
  • Master's degree
  • Doctorate (PhD/EdD)
  • Professional degree (MD/JD)
  • Prefer not to say
Q19
Multiple Choice
What is your current employment status?
  • Employed full-time
  • Employed part-time
  • Self-employed
  • Student
  • Not employed
  • Retired
  • Prefer not to say
Q20
Dropdown
In which region do you currently reside?
  • Africa
  • Asia
  • Europe
  • North America
  • Oceania
  • South America
  • Prefer not to say
Q21
Chat Message
Thank you for completing this survey. Your responses have been recorded and will be used in aggregate to inform data-sharing policies. If you have any questions, please contact the research team.

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