COVID-19 Vaccine Perceptions from De-Identified Focus Group Transcripts

Excerpts from de-identified focus group transcripts on COVID-19 vaccine effectiveness and barriers to vaccination. It was authored by Saskia Shuman and hosted by Harvard Dataverse, with a last update in February 2026. The dataset is tagged for Medicine, Health, and Life Sciences.

Use Cases

• Analyze qualitative themes in de-identified focus group transcripts to understand perceptions of vaccine effectiveness.
• Identify and categorize barriers to vaccination mentioned within the de-identified focus group excerpts.
• Compare sentiment and argumentation patterns in de-identified transcripts based on the vaccination status of participants.

Strengths

• Data originates from Harvard Dataverse, a recognized academic repository.
• The dataset was last updated in February 2026, indicating recent maintenance.
• Content is explicitly de-identified, addressing privacy concerns for qualitative research.

Limitations

• The dataset consists of excerpts, not full transcripts, which may limit contextual analysis.
• Sample size, demographic details, and geographic scope of the focus groups are unknown.
• The lack of structured columns (e.g., speaker ID, coded themes) requires manual qualitative coding for analysis.

Provenance

Source

Harvard Dataverse

Collection Method

Excerpts from de-identified focus group transcript(s).

Freshness

Last updated 2026-02-17.