Researchers and program teams studying Infant and Young Child Feeding (IYCF) interventions need fast, reproducible ways to turn interviews, monitoring logs and diet cards into decision-ready evidence. This post shows how to run a rigorous qualitative analysis of IYCF interventions (using the Palghar tribal block protocol, published 15 July 2026) and how to operationalize the findings with Evidano. You will find a concise study snapshot (n=460 mother–infant dyads), a 7-step workflow for analyzing IDIs, process indicators and WhatsApp logs, and concrete feature mappings to speed synthesis and stakeholder-ready reporting. See the source protocol at PLoS One.
Key Takeaways
Evidano is an AI-powered qualitative data analysis platform that streamlines transcript ingestion, thematic and frequency analysis, cross-segment comparisons, and secure sharing for program teams and researchers.
The Palghar protocol (CTRI/2024/06/068427), published 15 July 2026, is a 24-month quasi-experimental mixed-methods intervention (baseline → 12-month intervention → endline) with qualitative components that show how SBCC, hot cooked complementary feeds and frontline capacity-building target IYCF outcomes.
- The Palghar study uses cluster sampling across 44 AWCs with 460 mother–infant (6–12 months) dyads per survey and embedded IDIs, process logs, diet cards and WhatsApp coordination for qualitative triangulation.
- Use Evidano to ingest audio IDIs, registers, diet-card spreadsheets and WhatsApp exports, apply auto-transcription and PII redaction, and import or iterate NVivo-style codebooks for reproducible coding.
- Automated thematic extraction, frequency and co-occurrence analyses, and cross-segment comparisons (AWW vs ASHA vs mothers) reveal pragmatic fixes: which AWCs need supervision, which SBCC messages work, and which recipes are acceptable.
- Rapid, shareable artifacts (co-occurrence maps, quote decks, one-page briefs) accelerate operational decisions and policy-ready evidence for supervisors and funders.
Fast take + source
Fast take: The PLoS One protocol lays out a 24-month, quasi-experimental mixed-methods intervention in Ganjad PHC, Palghar District, Maharashtra with baseline and endline surveys and embedded qualitative work to strengthen IYCF via frontline workers.
The clinical trial is registered CTRI/2024/06/068427 (registered 06 June 2024) and the full protocol is available from PLoS One.
- Why it matters: tribal areas show higher undernutrition; this study pairs SBCC, hot cooked complementary feeds at Anganwadi Centres and frontline capacity-building to improve IYCF.
- Quick payoff for you: extract themes from IDIs, monitor weekly process indicators, and compare segments (AWWs vs ASHAs vs mothers) to prioritize program fixes.
Study snapshot
| Metric | Value | Source / Note |
|---|---|---|
| Publication date | 15 July 2026 | PLoS One |
| CTRI registration | 06 June 2024 (CTRI/2024/06/068427) | Protocol metadata |
| Design | Quasi-experimental mixed-methods (pre/post + qualitative) | Baseline → 12-month intervention → Post-intervention |
| Sample (quantitative) | 460 mother–infant (6–12 months) dyads per survey | Cluster sampling across 44 AWCs |
| Qual data | In-depth interviews (IDIs) with AWWs, ASHAs, supervisors; process logs; diet cards; WhatsApp groups | Transcription → thematic analysis (NVivo v13) planned |
| Intervention components | SBCC trainings, pictorial IEC, hot cooked complementary feeds, micronutrient supplements | Process indicators tracked weekly |
| Primary outcomes | IYCF core indicators (MDD, MMF, MAD), complementary feeding at 6 months, micronutrient uptake | Measured pre/post |
Qualitative analysis of IYCF interventions: what the Palghar protocol offers
This section explains how the Palghar protocol combines structured quantitative surveys with purposive qualitative sampling to inform IYCF program design and monitoring.
The protocol schedules IDIs with frontline workers and stakeholders during a situational analysis (Feb–Sep 2024), process monitoring during the 12-month intervention (Oct 2024 onward), and endline qualitative checks by Jan 2026.
Qualitative inputs in the protocol include recorded IDIs, AWW/ASHA field notes, diet card entries, weekly registers of feeds, and WhatsApp messages used for coordination.
- Planned analytic tools: verbatim transcription, NVivo thematic coding, development of codes/themes, triangulation with process indicators and anthropometry.
- Key analytic needs for teams: rapid codebook iteration, cross-segment comparisons (e.g., high- vs low-performing AWCs), frequency and co-occurrence counts, and exportable evidence for supervisors and policy briefs.
Implications for researchers & program teams
For qualitative researchers
For qualitative researchers: expect multi-source data (audio IDIs, field registers, WhatsApp) and prioritize consistent transcription, reproducible coding, and transparent memos linking quotes to process indicators.
The protocol requires linking verbatim quotes to process indicators and maintaining reproducible codebooks for transparent thematic reporting.
For program managers
For program managers: the key operational questions are which AWCs are achieving MAD/MMF, what counselling gaps persist, and which SBCC activities change behaviours.
Rapid cross-tabbed outputs let managers reallocate supervision and supplies and target training to frontline workers who need it most.
For policy analysts
For policy analysts: the protocol can feed evidence on hot cooked meals versus THR by pairing outcome indicators with qualitative themes on cultural barriers and food acceptability.
Paired qualitative themes strengthen arguments for policy adaptation and scale by showing acceptability and operational challenges alongside quantitative outcomes.
Do more, faster with Evidano
Ingest diverse field data
Evidano ingests audio IDIs, diet-card spreadsheets and WhatsApp exports so teams can centralize mixed-source field data quickly.
Auto-transcription (with custom dictionary for local terms) and PII redaction prepare data for coding in minutes.
Reproducible thematic + frequency analysis
Evidano runs automated thematic extraction, frequency counts, and cross-segment comparisons to surface which messages correlate with improved MDD/MMF.
Teams can import NVivo-style codebooks or iterate codebooks inside Evidano for reproducible outputs.
Visualize and validate
Evidano generates co-occurrence networks, hierarchical code→subcode views and shareable quote decks to align supervisors and funders quickly.
Exportable visualizations and CSVs enable verification in SPSS or other quantitative tools.
Secure, research-first platform
Evidano stores data encrypted and does not use project data to train third-party models, making it suitable for vulnerable populations.
Evidano supports codebook import (NVivo-style) and offers an AI chat over your documents for rapid synthesis.
Collect follow-up data with AI avatars
Evidano can run autonomous AI-avatar interviews to collect short process checks or diet-card confirmations at scale when teams need scalable follow-ups.
Autonomous follow-ups can be used to collect short process indicators, but teams should confirm consent and IRB alignment before fielding.
7-step checklist: reproduce the Palghar qualitative analysis in Evidano
This checklist shows pragmatic steps to go from field audio and registers to a stakeholder brief using Evidano workflows.
- 1) Centralize inputs: import IDI audio, weekly registers, diet-card spreadsheets and WhatsApp export into one project.
- 2) Auto-transcribe + clean: run Evidano transcription with a custom dictionary for local food/role terms; apply PII redaction.
- 3) Auto-scan & seed codes: let Evidano suggest themes, then import your NVivo codebook or refine iteratively.
- 4) Run thematic, frequency & co-occurrence analyses: identify top barriers, accepted recipes, and supervision gaps.
- 5) Cross-segment comparisons: filter by AWC, frontline worker, or village to spot high-performer practices.
- 6) Visualize and export: build co-occurrence maps, quote decks and CSV exports for SPSS verification.
- 7) Produce decision artifacts: one-page briefs + slide deck for district officials and operational next steps.
Ethics note
Ethics note: this analysis approach is research-oriented and non-diagnostic, and teams must maintain informed consent and anonymize transcripts.
Follow local IRB and CTRI commitments when handling data from vulnerable tribal populations as described in the original protocol.
Wrapping up & next steps
This section summarizes how the Palghar protocol demonstrates a concrete use-case for mixed-methods IYCF evaluations and how AI-enabled qualitative analysis speeds program fixes.
The Palghar protocol (n=460, published 15 July 2026) combines behaviour change, food provision and frontline capacity-building; for teams running similar field studies, AI-enabled qualitative analysis converts iterative IDIs, process logs and diet cards into prioritized program fixes quickly.
- Ready to try it? Create a pilot project in Evidano: upload a small batch of IDIs and registers, run an automated thematic sweep, and generate a 1-page evidence brief for stakeholders.
- Start a trial: Try Evidano for free.
FAQ: AI-enabled qualitative analysis
What does the Palghar protocol study measure?
Answer: The Palghar protocol measures IYCF core indicators and program process through mixed-methods data collection.
The protocol records IYCF core indicators (MDD, MMF, MAD), complementary feeding at 6 months, micronutrient uptake, and collects qualitative data via IDIs, process logs, diet cards and WhatsApp coordination for triangulation.
Which qualitative data sources does the protocol use?
Answer: The protocol uses in-depth interviews, field registers, diet cards and WhatsApp messages as qualitative data sources.
Specifically, the protocol lists IDIs with AWWs, ASHAs and supervisors, AWW/ASHA field notes, diet card entries, weekly registers of feeds, and WhatsApp groups used for coordination.
How can teams reproduce the Palghar qualitative analysis in Evidano?
Answer: Teams can reproduce the Palghar qualitative analysis by following the 7-step checklist to centralize inputs, auto-transcribe, seed codes, run analyses and export decision artifacts.
The checklist includes centralizing IDI audio, registers and WhatsApp exports; auto-transcribing with custom dictionaries and PII redaction; importing or iterating NVivo codebooks; running thematic, frequency and co-occurrence analyses; and exporting quote decks and one-page briefs.
When are the qualitative components scheduled in the protocol?
Answer: The protocol schedules situational analysis IDIs from Feb–Sep 2024, process monitoring from Oct 2024 onward, and endline qualitative checks by Jan 2026.
These timelines allow teams to triangulate baseline qualitative findings with process monitoring during the 12-month intervention and final endline checks.