This post explains how to turn a field qualitative study into reproducible, AI-enabled thematic evidence for program design and policy. The primary keyword, qualitative analysis of menstrual health, guides practical steps for researchers, program managers, and UX teams. According to the PLOS ONE article published July 24, 2026, researchers conducted 18 in-depth interviews and five key informant interviews between September 1 and October 31, 2025, in Khulna Railway Slum to surface barriers to menstrual dignity. The payoff is actionable guidance: how to preserve context and participant voice while using AI to speed coding, cross-segment comparisons, and safe transcription/translation.
Key Takeaways
According to the PLOS ONE article published July 24, 2026, the study of Khulna Railway Slum shows menstrual experiences are shaped by three domains: structural-environmental constraints, socio-cultural stigma, and gendered inequities in resource access (PLOS ONE).
- The PLOS ONE study collected 18 in-depth interviews and five key informant interviews between 01 September and 31 October 2025, providing rich, contextual accounts for thematic analysis.
- The PLOS ONE article reports participant ages ranged 15–45 years with 39% aged 20–30 and education levels of 39% non-literate, 33% secondary, and 28% primary schooling as of data collection in 2025.
- The PLOS ONE study documents direct impacts of inadequate WASH and disposal systems, exemplified by the quote, "When water stops coming from the tap, I wait for hours. If it doesn’t come, I can’t clean myself properly." (IDI-08, Housewife).
- The PLOS ONE study was published on July 24, 2026, and recommends integrated WASH, education, product access, and stigma-reduction policies for informal urban settlements.
What happened and how the study was measured
Answer: The PLOS ONE study used qualitative interviews to map lived menstrual experiences in Khulna’s informal settlements and to produce thematic findings ready for synthesis.
According to the PLOS ONE article (Alam & Al-Mamun, published July 24, 2026), data collection occurred between 01 September and 31 October 2025 and included 18 in-depth interviews (IDIs) and five key informant interviews (KIIs).
According to the PLOS ONE article, the authors used a Feminist Political Ecology framework and combined deductive coding (three pre-defined domains) with inductive coding to capture emergent sub-themes, and they used NVivo v12 for coding.
According to the PLOS ONE article, participants described specific operational constraints: communal toilets without doors, intermittent water supply, lack of disposal bins, and single-room overcrowding that constrained private washing and drying of materials.
According to the PLOS ONE article, ethical approval was granted (IRB Approval No. 473478-FY 2024–2025; Approval Date: 10 August 2025) and interviews were conducted in Bengali then translated into English with back-checking for accuracy.
Findings snapshot
| Date | Metric | Value | Implication |
|---|---|---|---|
| 01–31 Oct 2025 | In-depth interviews | 18 IDIs | Rich participant narratives for thematic coding |
| 01–31 Oct 2025 | Key informant interviews | 5 KIIs | Stakeholder context for program implications |
| Data collection 2025 | Participant age distribution | Ages 15–45; 39% aged 20–30 | Enables age-stratified analysis (adolescents vs adults) |
| Published 24 July 2026 | Main themes | 3 domains: structural-environmental, socio-cultural, gendered inequities | Design multi-sectoral interventions combining WASH and social change |
| Khulna context (2025) | Slum population share | Khulna district ~2.61M; ~20% in slums (as cited in study) | Scale indicates urban planning and WASH implications |
Implications for qualitative analysis of menstrual health
Answer: The PLOS ONE study shows that qualitative analysis must preserve local language nuance, stigma markers, and spatial context to produce program-relevant insights.
According to the PLOS ONE article, transcripts were collected in Bengali and translated with back-checking, which indicates the importance of preserving linguistic nuance in qualitative analysis to avoid losing culturally specific stigma terms.
According to the PLOS ONE article, the combined deductive-inductive coding approach produced both pre-specified domain comparators and emergent sub-themes, which researchers should replicate when analyzing menstrual health in other informal settlements.
According to the PLOS ONE article, concrete steps for analysts include: (1) separate adolescent and adult strata for cross-segment comparison, (2) tag environmental constraints (water, toilets, disposal) as distinct codes, and (3) retain verbatim shame-language for stigma-focused interventions.
How Evidano helps translate interviews into action
Problem: Time-consuming transcription and translation
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Feature mapping: use Evidano’s speech-to-text for Bengali transcription with custom dictionary entries for local terms cited in the PLOS ONE study, then apply Evidano’s translation module to preserve meaning.
Why it matters: the PLOS ONE article transcribed in Bengali and back-checked; using Evidano’s tools preserves accuracy and speeds the step that the original study took manually.
Problem: Manual coding slows synthesis across small samples
Answer: Evidano speeds thematic and cross-segment coding while preserving audit trails and verbatim quotes.
Feature mapping: Evidano’s thematic and frequency analyses can import NVivo exports or raw transcripts to auto-suggest codes aligned with the three domains used by the PLOS ONE study, and then let researchers confirm, merge, or split codes.
Why it matters: the PLOS ONE authors used a combined inductive-deductive approach; Evidano replicates that workflow with AI-suggested codes plus human validation for trustworthiness.
Problem: Safe handling of sensitive qualitative data
Answer: Evidano supports PII redaction, encrypted storage, and does not share user data with third-party model training.
Feature mapping: apply Evidano’s PII redaction and project-level encryption to protect the confidentiality strategies the PLOS ONE study used (pseudonyms like IDI-08).
Contextual link: learn more on Evidano’s features page for secure workflows and audit trails.
FAQ: qualitative analysis of menstrual health
How many interviews are enough for thematic saturation in a study like Khulna's?
Answer: The PLOS ONE study reached thematic saturation after 15 IDIs and confirmed with three extra interviews, totaling 18 IDIs and five KIIs during September–October 2025.
Supporting note: According to the PLOS ONE article, the research team monitored coding iteratively and stopped when new interviews yielded no new conceptual themes, a standard qualitative saturation practice.
Should transcripts be coded in the source language or in translation?
Answer: Code first in the source language when possible, then validate codes in translation, as recommended by the PLOS ONE authors who transcribed in Bengali and back-checked English translations.
Supporting note: According to the PLOS ONE article, this two-step process preserved local stigma terms and improved validity during final thematic synthesis.
Which coding approach fits menstrual health research in informal settlements?
Answer: Use a combined deductive-inductive approach, starting with theoretical domains and adding emergent codes, as done in the PLOS ONE study.
Supporting note: According to the PLOS ONE article, the team used Feminist Political Ecology as the deductive scaffold and then incorporated inductive codes for context-specific practices such as hidden cloth-drying and improvised waste disposal.
How can AI help reduce bias while analyzing sensitive topics like stigma?
Answer: AI can surface candidate codes and frequency patterns but should be coupled with human reflexivity and team consensus to limit confirmation bias, following the PLOS ONE study’s reflexivity practices.
Supporting note: According to the PLOS ONE article, the authors used reflexive field notes and team discussions to avoid overfitting data to theoretical expectations; AI-assisted coding should reproduce that human oversight.
Conclusion & Next Steps
Recap: According to the PLOS ONE article published July 24, 2026, menstrual health in Khulna’s informal settlements is shaped by environmental scarcity, stigma, and gendered resource gaps, evidenced by 18 IDIs and five KIIs collected in late 2025.
Next steps for researchers: replicate the study’s mixed deductive-inductive coding, preserve source-language nuance, and integrate WASH and stigma codes into program metrics.
If you want to operationalize these steps, Evidano can speed transcription, translation, thematic coding, and cross-segment comparison while protecting participant confidentiality.
Start a project and test the workflow today: Try Evidano for free