Faster qualitative analysis: chlamydia subfertility

Evidano is an AI-powered qualitative data analysis platform that converts mixed-methods transcripts into thematic, frequency, and cross-segment evidence.

The PLOS One study published 18 June 2026 found 78% willingness to take a predictive subfertility test and 75%–88% perceived high severity, so rapid reproducible coding and segment comparisons are essential.

A reproducible 7-step AI-enabled workflow can turn five focus-group transcripts and 426 survey open-texts into stakeholder-ready themes, counts, and visuals in hours, not weeks.

• The study combined 5 focus groups (n=19) and a questionnaire (n=426), median age 22, showing wide interest and mixed emotions about predictive testing.
• Seventy-eight percent of respondents were willing to take a predictive chlamydia subfertility test, while 75%–88% rated chlamydia and related subfertility as serious.
• Key qualitative themes were mental preparation, reassurance, mental burden, relationship impact, and concerns about accuracy and accessibility.
• Evidano supports bulk import, AI-assisted inductive coding, blind double-coding workflows, cross-segment frequency and relative-risk reports, and secure research-grade handling.

The fast take is a sequential mixed-methods study published 18 June 2026 that asked young adults with a uterus in the Netherlands about chlamydia-related subfertility.

A sequential mixed-methods study published 18 June 2026 asked young adults with a uterus in the Netherlands about chlamydia-related subfertility, using five focus groups (n=19) and an online questionnaire (n=426). Key headline: 78% were willing to take a predictive subfertility test, while 75%–88% viewed chlamydia and related subfertility as serious. Read the full paper at PLOS One.

• Why it matters: Open-text and focus-group data surface worries, misconceptions and conditional motivations, insights that need thematic coding plus segment comparisons (e.g., prior chlamydia vs no history).
• Payoff: Use an AI-enabled qualitative workflow to go from raw transcripts to stakeholder-ready themes, counts, and visualizations in hours instead of weeks.

The findings snapshot summarizes dates, inputs, key metrics and why the study matters for qualitative and policy teams.

The study used a sequential mixed-methods design, with focus groups informing a questionnaire and inductive content analysis applied to open-text answers.

Design: Sequential mixed-methods, focus groups informed a questionnaire; questionnaire included closed items and open-text boxes. Open-text answers were analysed with inductive content analysis (ICA).

• Focus groups: 5 groups, 19 participants (median age 22) to surface perceived benefits, barriers and requirements.
• Survey: 426 respondents; open-text responses coded in Excel. Two coders double-coded 100 random answers blind, then one coder completed remaining coding.
• Quantitative: descriptive stats and modified Poisson regression to identify factors associated with willingness to test.
• Key qualitative themes: mental preparation, reassurance, mental burden, relationship impact, accuracy & accessibility concerns.

Follow these seven steps to convert raw transcripts and survey text into decision-ready findings in Evidano.

• 1) Import: Upload focus-group audio/transcripts and the questionnaire spreadsheet with respondent metadata.
• 2) Transcribe & translate: Run auto-transcription (use custom dictionary for medical terms) and redact PII.
• 3) Seed codes: Run AI-assisted inductive coding on a 10% sample to generate candidate codes; review and finalize codebook.
• 4) Full-code & validate: Auto-apply codes to corpus, run blind double-coding on a random subset and adjust thresholds.
• 5) Cross-segment analysis: Compare theme frequency and co-occurrence by prior-chlamydia, age, and willingness-to-test.
• 6) Visualize & export: Generate word clouds, co-occurrence networks, hierarchical maps and export a stakeholder brief with clickable quotes.
• 7) Follow-up: Use Evidano's AI chat over documents to draft communications, consent scripts, or a counseling script to mitigate nocebo effects.

Mixed-methods data from the PLOS One study (published 18 June 2026) shows both high interest (78% willing) in a predictive chlamydia subfertility test and clear potential harms (stress, misconceptions), so teams should prioritize reproducible coding and quantified cross-segment comparisons to inform communication and policy.

• For teams running similar research: import transcripts and survey data, run the 7-step workflow in Evidano, and produce thematic, frequency, and cross-segment evidence in hours not weeks.
• Ready to try it? Import your transcripts and survey data and run the 7-step workflow in Evidano to produce thematic, frequency, and cross-segment evidence in hours not weeks. Start now at Try Evidano for free.