Qualitative Analysis of Patient Decision Aid

Researchers and UX teams analyzing interviews and usability feedback from a new fertility preservation patient decision aid (PtDA) for boys and young men (published 1 Aug 2025) need a reproducible, secure workflow to turn transcripts into actionable themes. This post shows how to run a rigorous qualitative analysis of patient decision aid feedback (from import to cross‑segment synthesis) and where Evidano (www.evidano.com) speeds every step. Full protocol: www.bmjopen.bmj.com/content/15/8/e104475.

Study snapshot

Item	Value	Source / implication
Protocol published	1 August 2025	BMJ Open protocol (see link above)
Target age	11–25 years	PtDA tailored to boys & young men
Alpha testing sample	12 past patients; 10 HCPs; 10 stakeholders	Months 15–23: face/remote reviews + QQ-10
Beta testing (pilot)	Opportunistic cohort across 7 UK centres; ~166 eligible over 5 months; qualitative n≈24 patients + 10 staff	Months 24–33; interviews transcribed and analysed
Primary analysis methods	Content analysis (alpha); reflexive thematic analysis (beta) using NVivo	Deductive+inductive coding; quote-driven themes
Ethics & registration	REC 24/WM/0141; Research Registry 10273	Ethical approvals in place; public dissemination planned

What the study collects and how it's analysed

The CFM PtDA protocol defines a four‑stage development and evaluation pipeline: stage 1 development (months 1–14), stage 2 alpha testing (months 15–23), stage 3 beta/pilot testing (months 24–33) and stage 4 production/dissemination (months 34–36). Data sources include remote and in‑person interviews, QQ‑10 questionnaires, and stakeholder feedback.

Alpha testing: purposive sampling for diversity (age, cancer type, ethnicity, literacy needs); qualitative feedback + QQ‑10 face validity scores.
Beta testing: opportunistic recruitment across 7 UK sites; interview windows within 4 months post‑recruitment; target qualitative n≈24 patients and ~10 staff for in‑depth thematic analysis.
Analysis approach: digitise audio, transcribe verbatim, apply deductive framework for attractiveness/comprehension/self‑efficacy/cultural acceptability/persuasion/usability, and run inductive coding in parallel. NVivo and reflexive thematic analysis are the chosen tools/methods.

Note (ethics): This is research‑focused, non‑diagnostic work. Consent protocols (including Gillick competence for minors) and HRA approvals are documented in the protocol.

Implications for qualitative researchers and UX teams

For qualitative researchers

Design: The protocol shows a clear ladder from prototype to field test; replicate the alpha→beta iterative loop when testing PtDAs to identify usability and cultural issues early.

Sampling: Purposive diversity and dyadic interviews are used to surface family dynamics, plan for transcription complexity and paired‑interview coding rules.

Analysis: Combine deductive frameworks (QQ‑10 domains) with inductive theme generation to keep patient language central.

For UX / product teams

Deliverables: Expect a PDF/web PtDA, an option grid, and short AV summaries. Capture usability micro‑issues during alpha testing (readability, dyslexia needs, visual hierarchy).

Metrics to track: QQ‑10 domain scores, time‑to‑comprehension in user testing, and frequency of misunderstood terms across segments (age bands).

For clinical teams & policy analysts

Implementation: The referral model (provide PtDA at first consultation) minimizes delay but requires simple clinician prompts and brief training.

Evaluation endpoints: Acceptability and decision quality (confidence, knowledge) are immediate; health outcomes require later effectiveness trials as the protocol notes.

Do more, faster with Evidano (mapped to this protocol)

Problem: Audio + messy transcripts

Solution: Automated transcription with custom dictionaries (medical terms like 'sperm cryopreservation', 'testicular tissue freezing'), speaker separation and PII redaction. Save transcription hours and ensure compliant exports for analysis.

Problem: Inconsistent coding across coders/sites

Solution: Import a deductive codebook (QQ‑10 domains + provisional codes) and let Evidano auto‑apply codes, then review conflicts in a single interface. Use hierarchical codes→subcodes to preserve the inductive themes flagged during coding meetings.

Problem: Cross‑site comparisons (age, site, treatment)

Solution: Cross‑segment analysis: filter by age band (11–15, 16–20, 21–25), site, or FP choice and automatically generate frequency tables, co‑occurrence networks and side‑by‑side theme comparisons.

Problem: Extracting stakeholder quotations and visual reports

Solution: One‑click quote pulls linked to codes, exportable summary reports and visualizations (word cloud, network graph, hierarchical code map) to use in dissemination and steering‑group meetings.

Problem: Data security & governance concerns

Solution: Evidano uses end‑to‑end encryption, supports PII redaction, and does not use customer data to train third‑party models, a critical point for clinical research datasets.

7‑step workflow: from interview to insight

Use this short workflow to reproduce the CFM PtDA analysis pattern and accelerate it with Evidano.

1) Capture: Record interviews with clear metadata (site, age band, dyadic vs single, consent status).
2) Transcribe: Auto‑transcribe, apply custom dictionary for clinical/FP terms, and PII redaction.
3) Preprocess: Clean speaker labels, attach QQ‑10 scores and questionnaire responses as attributes.
4) Code: Import QQ‑10 deductive codebook, run auto-coding, then perform a pass for inductive codes (team review).
5) Synthesize: Generate themes using co‑occurrence networks and hierarchical code maps; compare segments (e.g., 11–15 vs 21–25).
6) Validate: Hold team reflexive sessions to agree final themes and pull illustrative quotes; check face validity with PPI reps.
7) Report & deploy: Export visual summaries, site‑specific findings, and a short decision memo for clinicians; upload anonymised outputs to the project webpage.

Wrapping up, next steps

The BMJ Open protocol (published 1 Aug 2025) lays out a rigorous plan to develop and test the first PtDA for boys and young men facing fertility decisions. If you're running similar alpha/beta cycles or handling multi‑site interview work, apply a structured qualitative analysis pipeline (deductive + inductive) and use tools that speed transcription, ensure consistent coding, and enable cross‑segment synthesis.

Ready to accelerate your qualitative analysis of patient decision aid feedback? See how Evidano automates transcription, standardises coding across teams, and produces the visual summaries decision makers want: www.evidano.com.

Ethics reminder: This guidance is research‑focused and non‑diagnostic. Always follow local consent, data governance and ethics approvals when handling clinical interviews.

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