Researchers and program teams need reproducible ways to turn mixed-method protocols into decisions. The BMJ Open protocol (published 1 Aug 2025) studying oral vs blood HIV self-testing among MSM and transgender women in Greater Manila offers a clear dataset: n=480 MSM, n=478 TGW, and 80 in-depth interviews. This post shows how to run a rapid qualitative analysis of HIV self-testing preferences from that protocol: what to extract, how to triangulate with the survey, and how to operationalise findings using AI-enabled qualitative research on www.evidano.com. Read on for a compact workflow you can apply to similar HIVST or public-health mixed-methods studies. Note: research-only guidance, non-diagnostic and aligned with ethics approvals cited in the protocol.
Fast take, source & what to expect
The BMJ Open protocol evaluates acceptability and preferences for oral (OraQuick) vs blood-based (Chembio) HIV self-testing among MSM and TGW in Greater Manila (published 1 Aug 2025). Full protocol: www.bmjopen.bmj.com/content/15/8/e095272.
- Design: Explanatory sequential mixed-methods (cross-sectional survey → IDIs).
- Planned samples: 480 MSM, 478 TGW, 80 IDIs.
- Analysis: Multinomial logistic regression (quant) + inductive thematic analysis and joint displays (qual).
Findings snapshot (protocol numbers)
| Date | Metric | Value | Source | Implication |
|---|---|---|---|---|
| 1 Aug 2025 | Study type | Explanatory sequential mixed-methods | www.bmjopen.bmj.com/content/15/8/e095272 | Survey → targeted IDIs enables explanation of quantitative choices |
| 2025 planned | Survey sample | 480 MSM; 478 TGW | www.bmjopen.bmj.com/content/15/8/e095272 | Sufficient power for subgroup multinomial models |
| 2025 planned | Qualitative sample | ≈80 IDIs (8 per group/modality) | www.bmjopen.bmj.com/content/15/8/e095272 | Designed to reach thematic saturation across modalities |
| 2012–2023 | Epidemic context | 411% increase in daily incidence (Philippines) | www.bmjopen.bmj.com/content/15/8/e095272 | Urgency to expand acceptable, low‑barrier testing options |
What the protocol does (plain English)
The team will present participants with four testing options (oral HIVST via OraQuick, blood HIVST via Chembio, community-based testing, facility-based testing). Participants complete a pre-test survey indicating preferences, take their chosen test (assisted or unassisted), then complete a post-test survey. A purposive subsample completes IDIs to explain why they picked one modality over others.
- Quantitative outputs: modality choice as a 4-level outcome, covariates (age, testing history, sexual behaviour), multinomial logistic regression to estimate associations.
- Qualitative outputs: inductive thematic analysis of IDIs, coding frame developed iteratively, translation & PII redaction built into workflow.
- Integration: joint displays to triangulate where quant and qual converge, complement or contradict.
Implications for researchers: qualitative analysis of HIV self-testing preferences
For UX and field researchers
Focus transcriptions on decision moments: reasons for choosing assisted vs unassisted, location preferences, perceived accuracy and comfort with oral vs blood sampling.
Code by practical usability themes (ease, privacy, pain/needle aversion, trust in result) to map back to product uptake levers.
For policy & program teams
Prioritise themes that link directly to linkage-to-care barriers: reporting rates, confirmatory testing uptake and referral friction noted in post-test follow-up.
Use cross-segment analysis (never-tested vs ever-tested; MSM vs TGW) to tailor distribution channels (hotspots, courier, CBOs).
For qualitative methodologists
The explanatory sequential design requires rigorous joint displays: align code frequencies with regression-predicted probabilities and surface discrepancies as theory-generating findings.
Document translation choices and inter-coder agreement as part of audit logs.
Do more, faster with Evidano (mapped to this protocol)
Problem: Dispersed mixed-method inputs → Solution: Unified ingestion
Evidano ingests Qualtrics CSVs, interview transcripts, and protocol documents so you can analyse survey responses and IDI text together in one workspace (see www.evidano.com).
Problem: Manual transcription & privacy risks → Solution: Secure transcription with PII redaction
Auto-transcribe Zoom audio, apply a custom dictionary for local Filipino/English terms, and redact PII before coding, reducing manual QA time.
Problem: Slow thematic coding → Solution: AI-assisted coding + codebook import
Upload an initial coding frame derived from the protocol (e.g., usability, privacy, willingness-to-pay). Evidano auto-suggests codes, applies them at scale, and surfaces inter-coder discrepancies.
Problem: Comparing segments (MSM vs TGW; never vs ever) → Solution: Cross-segment analysis & join displays
Run frequency and co-occurrence analyses, create joint displays that link regression outputs to quote-level evidence, and export figures for policy briefs.
Problem: Explaining results to stakeholders → Solution: Clickable visualizations & AI chat over your corpus
Generate co-occurrence networks, hierarchical code trees, and clickable quotes. Use AI chat to ask questions like “show me reasons needle aversion was more frequent in never-tested MSM” and get source-linked answers.
Security & compliance
Data encrypted at rest/in transit; Evidano models are proprietary and your data is never used to train third-party models, important for sensitive HIV research.
7-step checklist: reproducible qualitative analysis for this protocol
Follow these steps to get from raw protocol + data to an actionable report:
- 1) Import Qualtrics exports, audio files, and the protocol into Evidano.
- 2) Auto-transcribe audio with a Filipino/English custom dictionary; redact PII.
- 3) Draft an initial codebook from the IDI guide (usability, accuracy perception, privacy, location preference, willingness-to-pay).
- 4) Apply AI-assisted coding, review 10–20% of segments for quality, and resolve inter-coder differences.
- 5) Run cross-segment frequency tables (MSM vs TGW; never/ever-tested) and map to multinomial outputs.
- 6) Build joint displays in Evidano linking quantitative effect sizes to exemplar quotes and co-occurrence visuals.
- 7) Export a stakeholder brief with visuals and an appendix of coded quotes for program design and policy decisions.
Ethics note
This guidance supports analysis of research-approved data only. The BMJ protocol reports UPMREB approval (UPMREB 2023-0579-01). Use secure workflows, informed consent, and avoid re-identification when sharing outputs.
Conclusion, next steps and CTA
If you’re running or evaluating HIVST studies like the BMJ protocol, convert mixed-methods inputs into reproducible themes, segment comparisons, and joint displays in hours rather than weeks.
- Start a pilot: upload one Qualtrics export + 10 transcripts to test the workflow on www.evidano.com.
- Need help mapping the protocol to an analysis plan? Contact Evidano for a demo and a template for explanatory sequential mixed-methods.
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