Qualitative analysis of research participation: workflow

This post describes a two-week, repeatable workflow to turn freelist data (n=101, May–Sep 2023) into actionable recruitment tactics, prioritizing people never previously asked and neutralizing fear and burden signals.

Use freelisting to detect culturally salient terms, then follow up with interviews, salience and sentiment analyses, and AI-enabled cleaning and visualization to iterate messaging quickly.

• PLOS freelisting (n=101) found mixed sentiments about research and universally salient fear-related terms including “scary” (published July 1, 2026).
• Prior research experience (32% previously participated) was associated with more positive sentiment; 58% of respondents reported never being asked to participate.
• Operational levers: ask more people (especially those never approached) and address fear/burden with plain-language onboarding and low-effort incentives.
• Evidano ingests text and spreadsheets, auto-groups synonyms, builds editable parent-term dictionaries, runs salience-style and cross-segment analyses, and exports stakeholder-ready deliverables.

The PLOS freelisting study found mixed sentiments about clinical research with salient fear-related terms across demographic groups.

In brief: the PLOS study used web-based freelisting (May–Sep 2023) to probe perceptions of clinical research among underrepresented groups; 101 participants completed the freelists (56% Black, 23% Hispanic/Latinx, 80% women, 46% rural). Key, shared salient terms included “study, ” “knowledge, ” “search, ” and worryingly, “scary.” Full paper: PLOS.

• Publication: July 1, 2026; data collection: May–Sep 2023; n=101
• Core finding: mixed sentiments overall; more negative sentiment among people never previously asked to participate
• Unique signal: “research misconduct” salient among Black respondents, a trust cue that recruitment must address

The study ran a web-based freelisting survey at five health systems and a community organization across Philadelphia, Atlanta, and Washington, DC between May–Sep 2023.

The team ran a web-based freelisting survey at five health systems and a community organization across Philadelphia, Atlanta, and Washington, DC (May–Sep 2023). Participants listed terms in response to three prompts: “research, ” “being asked to participate, ” and “being a participant.” Responses were cleaned into parent terms and analysed with Smith’s salience index to identify the most culturally salient items.

• Salience combines frequency and order in lists; investigators used scree plots to select salient terms.
• Sentiment coding (positive/neutral/negative) showed overall neutral views of the word “research, ” positive sentiment when asked to participate, and mixed or negative sentiments about being a participant, especially for those never asked before.
• Contextual gap: freelisting identifies priorities but not deep reasons, authors recommend follow-up interviews or concept mapping.

This two-week, 10-step runbook reproduces the study’s insights and converts them into recruitment tactics.

Follow this 10-step, two-week plan to reproduce the study’s insights and convert them into recruitment tactics.

• Day 1: Import freelists and survey CSVs into Evidano; attach metadata (age, race, prior participation).
• Day 2–3: Auto-clean and review parent-term dictionary; confirm merges for local vocabulary.
• Day 4: Run frequency and salience-style ordering; generate scree plots and pick salient elbow terms.
• Day 5–6: Tag sentiment and validate on a 10% sample; correct mismatches.
• Day 7: Compare segments (for example, never asked vs. previously participated) and export top divergent terms.
• Day 8–10: Build visuals (co-occurrence network, hierarchical codes) and extract representative quotes.
• Day 11: Draft targeted outreach scripts and FAQ language with Evidano’s AI chat.
• Day 12–14: Pilot two messaging variants with community partners; collect quick feedback and rerun freelisting to measure signal change.

The PLOS study was IRB-approved, and teams must secure consent and local approvals before recruitment or data collection.

Ethics: the PLOS study was IRB-approved; recommendations here are research-focused and non-diagnostic. Always secure consent and local approvals before recruitment or data collection.

• Freelisting is fast but shallow, use interviews for context before policy changes.
• Be mindful of priming, the authors noted their example prompt may have amplified fear-related terms.

Turn freelists into equitable recruitment by asking more people and neutralizing fear and burden signals with clear, low-effort onboarding and trust-building steps.

The PLOS freelisting study (published July 1, 2026) highlights two operational levers: ask more people (especially those never approached) and neutralize fear and burden signals with clear, low-effort onboarding. AI-enabled qualitative workflows compress cleaning, cross-segment comparison, and visualization into days, letting teams test messaging and access changes iteratively.

• Next step: replicate the study pattern on your cohort, import freelists or exit-survey text, run salience and sentiment, then pilot targeted outreach.
• Ready to try it? Start a pilot and accelerate synthesis with Evidano: Try Evidano for free.