TL; DR: Tunisia’s MHCP‑t validation protocol (published Jul 8, 2026) provides a practical mixed‑methods route to test content validity, feasibility and acceptability in real settings, see PLOS ONE. If your team runs interviews, policy inventories or multi‑language surveys and needs to speed synthesis without losing rigor, this post explains how to reproduce the MHCP‑t validation workflow and where AI-enabled qualitative research removes bottlenecks, from multilingual transcription and translation to thematic mapping, cross‑segment comparisons and visual reports. Expect concrete steps and key metrics from the protocol (sample n=40–50; focus groups n≈10–15; completion ≈5 hours).
Key Takeaways
Evidano is an AI-powered qualitative data analysis platform that speeds multilingual transcription, thematic coding, and cross-segment synthesis. Tunisia’s MHCP‑t validation protocol (published Jul 8, 2026) demonstrates a pragmatic mixed-methods workflow that balances item-level psychometrics and qualitative feedback to validate migrant health tools. The protocol targets sample n=40–50, nested focus groups ≈10–15, and estimates respondent burden at ≈5 hours.
- Use both item-level (I‑CVI thresholds) and tool-level assessments to test relevance, comprehensiveness and comprehensibility.
- Plan for staged completion and incentives, the protocol estimates ~5 hours per respondent spread across stages.
- Combine numeric cutoffs (e.g., I‑CVI ≥0.78; S‑CVI/Ave ≥0.90) with thematic feedback before dropping or revising items.
Findings snapshot
The findings snapshot summarizes the protocol dates, recruitment targets, sample sizes and analytic tools used.
Findings snapshot
| Date / Phase | Metric | Value | Source / Note |
|---|---|---|---|
| Protocol published | Publication date | Jul 8, 2026 | PLOS ONE |
| Recruitment | Window started | 19 Sep 2025 – Feb 2026 (target) | National expert working group |
| Sample | Experts per tool | ≈40–50 (purposive) | Stratified by geography, role, disease area |
| Qual depth | Focus groups | ≈10–15 participants total (nested) | Topic guides + field notes |
| Burden | Estimated completion | ~5 hours per respondent (stages allowed) | RedCap platform; gift voucher to encourage completion |
| Tools | Languages | Arabic, English, French | Dynamic question routing by expertise |
| Analysis | Quant & Qual | I‑CVI, S‑CVI, Krippendorff's α; thematic NVivo 14 | STATA 18 used for statistics |
What the MHCP‑t validation protocol does (plain English)
The MHCP‑t validation protocol evaluates three interlinked survey instruments that map migrant health data sources (Data), national policies (Policy), and service provision (Provision). The study combines structured item-level ratings (relevance, comprehensiveness, comprehensibility) with focus groups to capture practical and contextual issues.
- Item-level validation: applied to MHCP‑t: Provision and key sections of MHCP‑t: Policy using 5-point Likert ratings and I‑CVI thresholds (0.78).
- Tool-level validation: all three tools assessed for overall content validity, feasibility and acceptability with a second questionnaire (4-point Likert/binary items).
- Mixed methods: quantitative psychometrics (I‑CVI, S‑CVI/Ave, Krippendorff’s α) plus thematic analysis of field notes and open responses in NVivo 14.
The approach is pragmatic: train national teams, recruit purposive experts, give a two-week window on RedCap, and combine numeric cutoffs with participant narratives to decide which items to keep, revise or remove.
So what for qualitative researchers and policy analysts?
Why this matters
The MHCP‑t protocol matters because migration status is rarely captured in health data at scale, and validated inventories and indicators help policymakers compare across regions. Using clear psychometric cutoffs (for example, I‑CVI ≥0.78; S‑CVI/Ave ≥0.90) together with qualitative feedback helps balance statistical rigor with real-world feasibility.
Key takeaways for teams
Prioritise who answers which tool: data experts should complete the Data tool, policymakers should complete the Policy tool, and frontline staff should complete the Provision tool.
Expect participant burden, the protocol estimates approximately 5 hours; plan staged completion windows and incentives to maximise completion.
Combine numeric thresholds and thematic evidence before making item decisions; do not drop items solely on marginal I‑CVI without reviewing qualitative context.
Do more, faster with AI-enabled qualitative research
Problem: Long transcripts, multilingual inputs
Manual transcription and translation across Arabic, French and English slows analysis and introduces inconsistencies.
Solution: Automated transcription and custom dictionaries using Evidano
Automated transcription with a custom dictionary for domain terms (for example, 'MHCP‑t' and disease‑specific nomenclature) speeds secure processing and reduces manual error. Evidano supports multi-language transcription and translation, preserving original text and translated versions to unify coding across Arabic, French and English responses while providing built-in PII redaction.
Problem: Item-level ratings produce many open comments
Manual coding of hundreds of free-text justifications is time consuming and inconsistent across coders.
Solution: Thematic, frequency and cross-segment analyses using Evidano
Import survey exports (RedCap CSVs) and focus group transcripts into Evidano to produce thematic maps, frequency tables, and cross-segment comparisons (for example, policy versus provision perspectives). Use hierarchical codes, subcodes and co-occurrence networks to surface which concepts cluster with low I‑CVI items and guide targeted revisions.
Problem: Stakeholder buy-in and reporting
Policymakers typically prefer concise, actionable briefs rather than lengthy appendices.
Solution: Clickable quotes, visuals and reproducible reports using Evidano
Generate exportable visualisations (for example, word clouds and co-occurrence networks) and a clickable quote bank for policy briefs; Evidano's AI chat lets non-analysts query findings over the actual documents to speed decision making. Evidano encrypts data and does not use customer data to train third-party models, which is important when working with sensitive migrant datasets.
Checklist: Run a two‑week pilot to validate a tool (adapted from the MHCP‑t protocol)
This checklist gives a compact runbook to mirror the MHCP‑t protocol in one pilot site.
- Day 0: Assemble a working group (policy, data, frontline) and map respondent roles.
- Day 1–3: Translate and adapt the tool and upload to RedCap (or export to Evidano), include a consent page and estimated completion time.
- Days 4–7: Train participants remotely and open a two‑week window for staged completion.
- Days 8–14: Run item-level rating survey and collect open comments, then export CSVs and transcripts.
- Day 15–20: Load materials into Evidano for automated transcription (if needed), thematic coding, I‑CVI helper reports and cross-segment dashboards.
- Day 21–28: Convene one to two focus groups, integrate qualitative themes, and produce a concise policy brief with visuals.
FAQ: qualitative analysis of migrant health tools
What is content validity and why use it here?
Content validity checks whether items capture the intended construct, in this case the integration of migrants into health systems. The MHCP‑t uses both item-level and tool-level assessments to ensure questions are relevant, comprehensive and understandable.
How do I compare segments (policy vs provision) reliably?
Use numeric agreement metrics and cross-segment thematic comparisons to surface divergent concerns. Apply I‑CVI and Krippendorff’s α for numeric agreement, and run cross-segment thematic analyses to identify where policy and provision perspectives diverge; Evidano automates segmented frequency and co-occurrence analyses.
Is it ethical to use AI on migrant data?
Using AI on migrant data is ethical when you follow approvals, obtain consent and use secure platforms. The MHCP‑t stores data on a RedCap server (Institut Pasteur, Tunisia) and the protocol requires consent and confidentiality safeguards; Evidano encrypts data and does not use customer data to train third-party models.
Wrapping up & next steps
The MHCP‑t validation protocol offers a practical template for turning policy inventories and service mapping into validated, actionable instruments. The mixed-methods design, combining numeric thresholds with participant narratives, ensures both rigor and relevance.
If your team runs similar validations or wants to scale content validity work across languages and sites, combine RedCap-style collection with an AI research platform to remove bottlenecks in transcription, coding and cross-segment synthesis. Explore how Evidano integrates secure transcription, multilingual translation, thematic and cross-segment analyses, and visual exports to turn MHCP‑t style inputs into policy-ready outputs: Try Evidano for free.