Frontline-worker-led interventions to improve Infant and Young Child Feeding (IYCF) in Palghar, Maharashtra provide a mixed-methods dataset including 460 mother–infant dyads, IDIs with AWWs and ASHAs, and weekly process registers under trial CTRI/2024/06/068427. The protocol outlines a 24-month, three-phase evaluation using structured surveys, anthropometry, weekly monitoring and thematic analysis of in-depth interviews. This post shows a repeatable AI-enabled workflow from transcript ingestion to segment comparisons and stakeholder-ready visuals, and maps platform capabilities onto each protocol step. First source: PLoS One.
Key Takeaways
Evidano is an AI-powered qualitative data analysis platform that maps the Palghar IYCF mixed-methods protocol into a reproducible workflow, ingesting transcripts, registers, and surveys to produce thematic analysis and segment comparisons. The Palghar study combines n=460 baseline/endline mother–infant dyads, IDIs with frontline workers, and weekly monitoring across 44 Anganwadi Centres under trial CTRI/2024/06/068427. This post describes a two-week reproducible workflow to convert raw transcripts and registers into decision-ready visuals and segment comparisons using secure, research-ready tools.
- The Palghar protocol is a pre/post quasi-experimental design across 44 Anganwadi Centres with three phases over 24 months and a sample of 460 dyads for baseline and endline.
- The qualitative component uses in-depth interviews with AWWs, ASHAs, and supervisors, transcribed and thematically analyzed (NVivo v13) alongside weekly process data.
- The protocol targets a 10% absolute improvement in timely complementary feeding (from 48.3% to 58.3%) and uses SPSS for quantitative analysis with p<0.05 thresholds.
- A compact two-week runbook converts collected files into thematic maps, cross-segment comparisons, representative quotes, and a one-page decision brief for stakeholders.
Fast take: why this study matters for field researchers
This study matters because it tests a multicomponent IYCF intervention across 44 Anganwadi Centres in Ganjad PHC, Palghar and combines quantitative and qualitative data to produce actionable findings for program design and frontline-worker capacity building.
- Design: pre/post quasi-experimental, three phases over 24 months (prep, 12‑month intervention, post-intervention).
- Qualitative inputs: in-depth interviews (IDIs) with AWWs, ASHAs, supervisors, thematic analysis with NVivo v13.
- Primary promise: actionable thematic insights tied to measurable IYCF indicators (MDD, MMF, MAD).
Findings snapshot
| Metric | Value / Detail | Source / Note |
|---|---|---|
| Published | 15 July 2026 | PLoS One |
| Trial registration | CTRI/2024/06/068427 (06 June 2024) | Protocol |
| Sample size | 460 mother–infant (6–12 mo) dyads (pre and post) | Cluster sampling across 44 AWCs |
| Qualitative data | IDIs with frontline workers; process registers; diet cards; WhatsApp group content | Transcribed and analyzed thematically (NVivo v13) |
| Study area / population | Ganjad PHC, Palghar District, tribal communities (multiple castes listed) | Context: geographic access & cultural feeding norms |
| Timeline (key dates) | Situational analysis Feb–Sep 2024; intervention start Oct 2024; projected post data by Jan–Feb 2026 | Study framework (24 months total) |
Methods in plain English
The protocol uses a mixed-methods pipeline combining structured baseline/endline surveys, weekly process monitoring, and qualitative IDIs to capture barriers, beliefs, and counselling practices.
- Structured measures include 8 WHO IYCF indicators and anthropometry, with sample calculations targeting a 10% absolute improvement in timely complementary feeding (from 48.3% to 58.3%), yielding approximately 460 participants after accounting for non-response.
- Qualitative sampling uses convenient sampling for IDIs with CDPO, supervisors, AWWs, ASHAs and uses saturation to determine interview counts; interviews are transcribed verbatim, coded and thematically analyzed in NVivo v13.
- Quantitative analysis uses SPSS with significance threshold p<0.05; intervention components include SBCC training, pictorial booklets and videos, hot-cooked complementary feeds at AWCs, micronutrient supplements, and monitoring via diet cards and WhatsApp groups.
So what for researchers, qualitative analysis of IYCF practices
For UX / implementation researchers
UX and implementation researchers can use IDIs from this protocol to identify counselling gaps, local food taboos, and low-uptake drivers and to prototype IEC iterations.
Researchers should map co-occurrence and sequence relationships from frontline-worker advice to caregiver action and to feeding outcomes to support iterative design of behaviour-change materials.
For program managers & policy analysts
Program managers and policy analysts should combine thematic findings with process indicators such as weekly feeds and diet-card adherence to prioritize scalable elements of the intervention.
Segment comparisons by village/pada and AWC help allocate supervisory resources and plan targeted refresher trainings efficiently.
Ethics note
The study secured ICMR ethics approval (13 Nov 2023) and uses informed consent for participants.
The authors note that AI-enabled analysis referenced in this post is for research use only and is not a clinical diagnostic tool.
How Evidano helps (mapped to this protocol)
Ingest & standardize messy field data
Evidano ingests audio, interview transcripts, diet-card spreadsheets and WhatsApp exports and standardizes them for analysis.
Users can apply custom dictionaries (local names, foods, tribal terms) to improve transcription and tokenization accuracy.
Automate thematic + frequency analysis
Evidano automates thematic clustering and frequency counts to reproduce NVivo-style themes alongside quantitative tag counts for each AWC or cadre.
Evidano produces code hierarchies and AI-suggested themes that teams can review and merge with their protocol codebook.
Cross-segment comparisons
Evidano enables cross-segment queries by village, AWC, or mother’s education to surface differential barriers to MDD and MMF.
Users can test hypothesised drivers from the protocol using comparative frequency and co-occurrence outputs.
Trace quotes to metrics
Evidano links illustrative quotes to process indicators to show, for example, mothers reporting hot-cooked meals alongside observed upticks in MMF.
Teams can export stakeholder-ready excerpts that map qualitative evidence to quantitative changes.
Faster visualizations for decision-making
Evidano provides one-click exports for word clouds, co-occurrence networks, hierarchical code views and segment heatmaps for district-level presentations.
These visualizations are formatted to speed interpretation by frontline supervisors and planners.
Secure, compliant research workspace
Evidano stores data encrypted in transit and at rest and does not use customer data to train third-party models, making it suitable for sensitive fieldwork with vulnerable populations.
The platform is presented as a secure workspace aligned with research ethics and data protection needs.
Two-week reproducible workflow (checklist)
The checklist below converts protocol data into insights in two weeks for a pilot.
- Day 1–2: Gather files, audio IDIs, transcripts, baseline survey CSVs, weekly registers, and diet-card images.
- Day 3–4: Upload files to Evidano; apply a custom dictionary (local foods, tribe names) and run batch transcription and PII redaction.
- Day 5–7: Auto-code with an initial codebook (import codes from the protocol), review and merge AI-suggested themes.
- Day 8–10: Run cross-segment frequency and co-occurrence analyses (AWC-level, mother education, uptake of hot meals).
- Day 11–12: Extract representative quotes and compile visualizations (theme heatmap, quote matrix) for stakeholders.
- Day 13–14: Produce a one-page decision brief and slide pack and plan targeted refresher trainings or resource shifts based on gaps found.
Wrapping up & next steps
The Palghar protocol combines standard IYCF indicators with rich qualitative data and represents a model use case for AI-accelerated qualitative analysis.
- The study protocol and published article provide the primary source material for the methods and findings summary: PLoS One.
- Ready to test this workflow on a pilot dataset? Start at Evidano to upload a small corpus and see thematic maps and segment comparisons in hours.
- Try Evidano for free to accelerate coding, exports, and secure handling of sensitive field data for implementation teams and evaluators.
FAQ: qualitative analysis of IYCF practices
What dataset does the Palghar IYCF study use?
+
The Palghar IYCF study uses a mixed-methods dataset of approximately 460 mother–infant (6–12 month) dyads with baseline and endline surveys, IDIs with frontline workers, and weekly process monitoring registers across 44 Anganwadi Centres.
The dataset includes diet cards, WhatsApp group content, and transcribed interviews that are analyzed thematically alongside quantitative indicators.
How long is the Palghar study timeline?
+
The Palghar study runs a 24-month framework with a situational analysis from Feb–Sep 2024, intervention start in Oct 2024, and projected post data collection by Jan–Feb 2026.
The design includes a preparation phase, a 12-month intervention, and a post-intervention evaluation phase.
What methods combine qualitative and quantitative data in this protocol?
+
The protocol combines structured surveys covering 8 WHO IYCF indicators and anthropometry with weekly process monitoring and in-depth interviews to capture contextual barriers and counselling practices.
Qualitative data are transcribed verbatim and analyzed thematically (NVivo v13) while quantitative data are analyzed in SPSS with significance assessed at p<0.05.
How does Evidano support reproducible qualitative workflows for this study?
+
Evidano supports reproducible workflows by ingesting transcripts and registers, applying custom dictionaries, auto-coding with an initial codebook, and producing cross-segment frequency and co-occurrence analyses.
Evidano also links illustrative quotes to process indicators and exports visuals and quote matrices for stakeholder reporting.
Topics
- IYCF qualitative analysis
- Palghar IYCF
- Evidano
- thematic analysis
- mixed-methods workflow
Keep reading
- Commentary on NewsQualitative Analysis of SLP Job ReadinessTurn PLOS One (Jul 21, 2026) SLP focus-group findings into reproducible thematic evidence with AI transcription, translation, coding, and secure audit trails.
- Commentary on NewsRoadmap: Qualitative analysis of youth digital mental healthPractical roadmap to synthesize qualitative evidence on youth digital mental health, reproduce thematic analysis, and run cross-segment pilots using Evidano.
- Commentary on NewsFaster Qualitative Analysis of PreprintsConvert preprints into section-labeled corpora with preprint-fulltext and ingest them into Evidano for reproducible thematic and cross-segment analysis.