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Faster Qualitative Analysis of IYCF Interventions

Evidano7 min read

The July 15, 2026 PLoS One protocol describes a quasi-experimental mixed-methods test of a frontline-worker intervention to improve Infant and Young Child Feeding (IYCF) in Palghar, Maharashtra (n=460 mother–infant dyads; CTRI/2024/06/068427). For program evaluators, implementation researchers and policy teams, qualitative analysis of IYCF interventions is the fastest route from interview transcripts, cook-demo notes and monitoring logs to operational decisions. This post shows pragmatic ways to: (1) extract themes and stakeholder quotes, (2) compare segments (AWWs vs. mothers, padas/villages), and (3) produce visual reports for ICDS/POSHAN stakeholders, using AI workflows (transcription with custom dictionaries, PII redaction, thematic and cross-segment analyses) available on Evidano.

Key Takeaways

Key Takeaways: The July 15, 2026 PLoS One protocol describes a 24-month quasi-experimental IYCF study in Palghar that combines SBCC, pictorial IEC, hot-cooked complementary feeds at Anganwadi Centres, and micronutrient supplementation, with quantitative samples of 460 infants per round and rich qualitative inputs to guide adaptation.

  • The Palghar protocol (published 15 July 2026) is a 24-month, pre/post quasi-experimental mixed-methods study with quantitative samples of 460 infants per round (age 6–12 months) and registered as CTRI/2024/06/068427.
  • Qualitative data (IDIs with AWWs, ASHAs and supervisors, plus process logs and recipe demo notes) are used to surface local barriers and acceptability and are triangulated with weekly process indicators and diet-card records.
  • Evidano automates transcription, PII redaction, AI-assisted coding, cross-segment frequency analysis, and stakeholder-ready outputs to accelerate synthesis and policy reporting.

Fast take & source

Fast take: PLoS One published a protocol on July 15, 2026 for a 24-month quasi-experimental study in Ganjad PHC, Palghar that combines SBCC training, pictorial IEC, hot-cooked complementary feeds at Anganwadi Centres, and micronutrient supplementation, and the full protocol is available from PLoS One.

  • Design: Pre/post quasi-experimental mixed methods (baseline, 12-month intervention, post-intervention).
  • Qualitative inputs: IDIs with AWWs, ASHAs, supervisors, and process notes from recipe demos and group sessions (Feb–Sep 2024 situational analysis).
  • Quantitative: Independent baseline and endline samples of 460 infants (6–12 months) across 44 AWCs.
  • Why it matters: Tribal areas show persistent gaps (NFHS-5 notes ~35.5% stunting nationally) and contextualized qualitative insights are essential to adapt scalable ICDS strategies.

Study snapshot (key numbers & timeline)

ItemValueSource / Note
Publication date15 July 2026PLoS One protocol
Study areaGanjad PHC, Palghar District, MaharashtraTribal populations across 77 padas / 44 AWCs
Sample (quant)460 infants per round (pre and post)Age 6–12 months; cluster sampling across 44 AWCs
Study duration24 months (6m prep, 12m intervention, 6m follow-up)Prep: Feb–Sep 2024; intervention start Oct 2024
Primary qualitative inputsIn-depth interviews, process logs, focus sessions, recipe demosIDIs with AWWs, ASHAs, supervisors; convenience sampling
Trial registrationCTRI/2024/06/068427Registered 06 June 2024

What the protocol does (plain English)

What the protocol does: The protocol combines behaviour change (SBCC) with hands-on supports including pictorial booklets, live cooking demos, weekly food charts, hot-cooked complementary feeds at Anganwadi Centres, and iron/calcium/vitamin D supplements, while building capacity of frontline workers and engaging mothers through group sessions and diet cards.

  • Mixed methods: quantitative KAP and anthropometry (pre/post) plus qualitative IDIs and process monitoring.
  • Process monitoring includes weekly indicators (feeds served, MDD/MMF/MAD attainment, readouts from diet cards).
  • Implementation is culturally explicit: IEC materials and recipes use locally available foods and pictorial aids suitable for low literacy.

Ethics note: the study received ICMR-NIRRCH ethics clearance (Nov 13, 2023) and uses anonymization and consent; findings are research-focused and non-diagnostic.

So what for researchers and program teams? (implications)

What should implementation researchers take away?

Implementation researchers should use thematic analysis of IDIs to surface operable barriers such as seasonal food availability, cultural taboos, and staff time constraints that explain uptake variation across padas.

Triangulate themes with weekly process indicators and diet-card records to test hypotheses about fidelity versus acceptability and to link qualitative findings to measurable process metrics.

What should program managers and ICDS officers do with these findings?

Program managers and ICDS officers should use qualitative excerpts and co-occurrence visuals to justify operational choices, for example hot-cooked feeds versus THR, by showing caregiver acceptability and logistical bottlenecks.

Cross-segment analysis (AWW versus mother responses) identifies where refresher training or supervision is most needed to improve implementation fidelity.

How can monitoring and evaluation teams apply this protocol?

Monitoring and evaluation teams should convert hundreds of IDI transcripts and monitoring logs into dashboards that measure theme prevalence and permit drill-down by village or worker.

Use process indicators as triggers for adaptive changes during the 12-month intervention, for example modifying recipe lists when MDD stalls.

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

What does Evidano do for multilingual, low-literacy transcription problems?

Evidano is an AI-powered qualitative data analysis platform that automates transcription with custom dictionaries for local terms, reducing manual correction time while preserving domain vocabulary such as regional foods and tribal community names.

How does Evidano handle sensitive quotes and PII in field notes?

Evidano provides PII redaction and controlled export so teams can keep data research-ready and compliant before sharing with stakeholders.

How does Evidano address inconsistent coding across coders?

Evidano imports a codebook and runs AI-assisted coding to produce hierarchical theme→subtheme maps and co-occurrence networks that reveal clusters like caregiver constraints versus supply gaps.

How does Evidano enable cross-segment frequency and comparison?

Evidano generates frequency tables and cross-segment analyses (AWW versus mothers; site A versus site B) and produces exportable visual reports suited for ICDS and POSHAN briefs.

How does Evidano produce stakeholder-ready artifacts?

Evidano extracts clickable quotes, word clouds, and short AI-generated summaries with citations to verbatim text to speed report drafting and policy memos; learn more at Evidano.

Reproducible 10-step workflow to analyze IYCF qualitative data in two weeks

Reproducible 10-step workflow: This checklist converts existing IDIs, process logs and diet cards into a rapid qualitative synthesis within two weeks when using automated tools and a structured process.

  • 1) Ingest audio files and field notes into Evidano; add a custom dictionary for local food names and tribal terms.
  • 2) Run automated transcription; review and correct using searchable timestamps.
  • 3) Redact PII automatically and tag speaker roles (AWW, ASHA, mother, supervisor).
  • 4) Upload baseline/endline structured data for cross-segmentation (village, AWC, role).
  • 5) Import a draft codebook (IYCF core indicators plus emergent codes) and run AI-assisted coding.
  • 6) Review auto-suggested themes; merge or split into hierarchies.
  • 7) Generate cross-segment frequency matrices (for example, theme prevalence by AWC) and co-occurrence networks.
  • 8) Extract 20 stakeholder-ready quotes and a one-page thematic brief; auto-format for slide decks.
  • 9) Validate key themes with a two-hour stakeholder workshop and tag matched quotes in Evidano.
  • 10) Export visuals and a reproducible analysis package for policy submission and program adaptation.

FAQ: qualitative analysis of IYCF interventions

How do you compare themes across villages reliably?

Compare themes across villages by using a standardized codebook combined with AI-assisted coding to ensure consistent application of codes, then run frequency and significance tests on code prevalence by segment.

Can AI preserve cultural nuance in low-literacy settings?

AI can preserve cultural nuance when teams supply a custom dictionary and provide iterative coder feedback, which keeps local terms intact in themes and quotes; Evidano supports that loop.

Is this safe for sensitive health data?

Using Evidano is appropriate for sensitive health data because Evidano provides PII redaction, end-to-end encryption, and does not use customer data to train third-party models, matching the needs of research with vulnerable communities.

Wrapping up & next steps

Wrapping up: The Palghar protocol (published 15 July 2026) is a model of context-sensitive IYCF implementation, and its operational value depends on rapid, reproducible qualitative synthesis that links frontline narratives to measurable process indicators (n=460 per round).

  • Ready to pilot? Start by uploading a small set of transcripts and diet-card logs to validate codebooks and dictionary entries.
  • For teams running IYCF pilots, Evidano speeds insight-to-decision cycles so you can adapt recipes, IEC, or supervision within months, not a year.

Get a demo and test this workflow with your data by signing up: Try Evidano for free.

Topics

  • IYCF qualitative analysis
  • Palghar IYCF protocol
  • qualitative data analysis
  • Evidano transcription and coding
  • IDIs thematic analysis

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