Qualitative analysis of research participation: 2026 insights

The PLOS freelisting study (n=101) found fear and perceived burden are common barriers to research participation, and prior participation shifts sentiment positively.

Evidano is an AI-powered qualitative data analysis platform that can convert freelist outputs into reproducible dictionaries, salience rankings, and visual reports in a two-week pilot.

• PLOS ONE freelisting (data May–Sep 2023) with 101 completers across Philadelphia, Atlanta, and DC metro areas identified shared and group-specific sentiments; published 1 Jul 2026.
• Only 32% of respondents had prior research experience, and those with prior experience expressed more positive views.
• Shared salient words included “study, ” “knowledge, ” “search, ” and “scary”; “research misconduct” was uniquely salient among Black respondents.
• Follow a two-week, seven-step pilot to translate freelist signals into outreach actions and measure sentiment shift.

This table summarizes the study date, sample, key signals, and the original source for quick reference.

This section explains the freelisting instrument, data collection timeline, sample size, and analysis steps in plain language.

• Data collection: May–Sep 2023 across five health systems and one community organization, using an online freelisting instrument in Qualtrics.
• Completed freelists: 101 respondents; median age 38 (IQR 31–52); 32% previously participated in research.
• Analysis steps: participants typed lists in order; the research team grouped similar responses into parent terms, built a dictionary, and calculated Smith’s S salience indices in Visual Anthropac to identify the most important terms per group, then applied consensus sentiment tagging.

This checklist is a two-week pilot to translate freelist outputs into outreach actions.

• 1) Design prompts (use the same three freelist prompts) and run a small online collection (n~100 per target area).
• 2) Import raw lists into Evidano and run automated cleaning plus suggested parent-term dictionary generation.
• 3) Approve or edit the dictionary in the workspace; export it for reproducibility and audit trail.
• 4) Auto-code for sentiment and compute term frequency and salience-like ranking across segments.
• 5) Produce visualizations: word cloud, co-occurrence, and hierarchical codes→subcodes.
• 6) Draft targeted messaging: (a) for never-asked groups, emphasize low burden and concrete logistics; (b) for Black communities, pair outreach with transparent oversight and clear benefit descriptions.
• 7) Re-run freelists or short avatar interviews after outreach to measure sentiment shift and conversion metrics.

The PLOS freelisting study (n=101) gives clear, actionable signals: fear and perceived burden are common across groups, and prior participation shifts sentiment positively.

For teams that recruit, design, or measure trial equity, the most direct lever is asking more people and then measuring whether first contacts reduce fear.

Ready to operationalize? Try Evidano for free and run the seven-step pilot to share reproducible dictionaries, segment comparisons, and visual reports with stakeholders.

Ethics note: this is research-focused guidance, not clinical advice; ensure IRB review and informed consent for new participant data collection.