Interviews on Group KB

Pre-study

Fri, 01 May 2026 00:00:00 +0000

Interviews: Pre-study#

This page covers the work before data collection: data protection, guide design, IRB filing, recruiting, consent, and pilot logistics.

Data Protection#

Data protection and privacy is very important in interview studies. Stick to the following points when doing interview studies to ensure that you will not violate data protection and privacy.

Everyone in the project (all student assistants, all PhDs, all collaborators) should be introduced to data protection and privacy in the project and all its processes during onboarding — before actually collecting the sensitive data.

Study

Fri, 01 May 2026 00:00:00 +0000

Interviews: Study#

This page covers the work during and after interview sessions: running interviews, recording, transcription, and analysis.

IRB Required: Do not start external pilot interviews, recruitment, or data collection before IRB approval.

For filing, see –> Submitting IRB.

Conducting Interviews#

Being a fairly interactive research approach, probably no other results’ quality is as dependent on researcher behaviour as interviews.

Best Practices#

Below you can find some hints that might help you conducting an effective interview. They are partially inspired / taken from the listed references.

Reporting

Fri, 01 May 2026 00:00:00 +0000

Interviews: Reporting#

This page covers how to write up interview studies, including methods structure, quotes, demographics, reporting ranges, and saturation.

Reporting#

Reporting interviews in method sections.

For documenting analysis decisions before writing up results, see the Data Analysis Plan. For reporting and packaging publishable study materials, see Replication & Artifacts.

Writing Style#

When reporting interviews, always keep in mind that the results are:

Not from a representative sample of a population, but from a small subset of people who shared their subjective experiences with you.
Based on self-report, which may be subject to various biases, including over- and under-reporting, sample bias, and social-desirability bias.

In practice this means writing in a way that does not suggest any quantitative or generalized results, but rather describes the experiences of the participants in your study:

Submission

Mon, 04 May 2026 00:00:00 +0000

Interviews: Submission#

Ethics#

See the article currently in Drafts folder

Open Science#

TODO

Participant Follow-up#

If you have promised to give participants a chance to give feedback and veto quotes (usually in consent form or similar), you should follow up with them after the paper has been accepted (but before the camera ready deadline). Similarly, if you plan on publishing a preprint, you should also follow up with participants and give them the opportunity to provide feedback before posting the preprint online.