This post describes how to perform a rigorous qualitative analysis of menstrual health, using the July 24, 2026 PLOS One study of Khulna Railway Slum as a worked example for researchers and program teams. The primary keyword for this post is qualitative analysis of menstrual health and the audience is qualitative researchers, NGOs, and WASH program planners who want an AI-enabled workflow that preserves participant confidentiality and speeds thematic synthesis.
Key Takeaways
According to the PLOS One study published on July 24, 2026, women and adolescent girls in Khulna Railway Slum face intersecting WASH shortages, socio-cultural stigma, and gendered resource constraints that shape menstrual practices and dignity. According to the same PLOS One study, a small purposive qualitative sample (18 in-depth interviews and five key informant interviews) collected between 1 September 2025 and 31 October 2025 yields concrete, actionable themes for program design.
- 18 IDIs and 5 KIIs were conducted between 1 September 2025 and 31 October 2025, according to the PLOS One study.
- Participants were aged 15–45 years and 39% of participants fell in the 20–30 age band, according to the PLOS One study.
- 72% of participants had lived in the slum for more than eight years, according to the PLOS One study.
- The PLOS One study found three core domains shaping experience: structural-environmental constraints, socio-cultural stigma, and gendered inequities in resource access.
What happened and how the study measured it
The PLOS One study explored lived menstrual experiences in Khulna Railway Slum using in-depth interviews and key informant interviews, according to the PLOS One article.
According to the PLOS One article, researchers collected data from 18 women and adolescent girls aged 15–45 years and five stakeholders between 1 September 2025 and 31 October 2025, then analyzed transcripts with a combined deductive and inductive thematic approach using Braun and Clarke’s six-phase framework and NVivo v.12, according to the PLOS One article.
- Sampling: purposive plus limited convenience sampling to recruit diverse, information-rich participants, according to the PLOS One article.
- Ethics: Institutional Review Board approval (Approval No. 473478-FY 2024–2025; Approval Date: 10 August 2025), according to the PLOS One article.
- Data: interviews were audio-recorded in Bengali, transcribed, and translated with back-checking to preserve meaning, according to the PLOS One article.
Findings snapshot
| Date / Item | Metric | Value | Implication (for programs) |
|---|---|---|---|
| 1 Sep 2025–31 Oct 2025 | Interviews | 18 IDIs + 5 KIIs | Small, saturation-driven sample produced rich contextual themes for local interventions, according to PLOS One |
| Published 24 Jul 2026 | Publication | PLOS One article | Open-access peer-reviewed evidence to cite in proposals, according to PLOS One |
| Participant demographics | Age range | 15–45 years; 39% aged 20–30 | Design age-tailored messages and products, according to PLOS One |
| Residence | Duration in slum | 72% lived in slum >8 years | Prioritize long-term WASH fixes and maintenance, according to PLOS One |
| Education | Literacy levels | 39% minimal/no schooling, 33% secondary, 28% primary | Use low-literacy materials and community outreach, according to PLOS One |
Implications for qualitative researchers and program designers
Qualitative researchers should triangulate interviews, key informants, and contextual observation when studying menstrual health, according to the PLOS One study.
Program designers should combine hardware (gender-responsive WASH) and software (school and community menstrual education) because the PLOS One study shows infrastructural gaps and stigma act together to limit agency.
- Design WASH upgrades with women’s safety in mind: lockable cubicles, lighting, continuous water, and covered disposal, because the PLOS One study links lack of privacy to absenteeism and avoidance.
- Prioritize adolescent support: the PLOS One study documents multiple first-menstruation stories where girls lacked prior knowledge, so integrate pre-menarche education in schools and community sessions.
- Measure impact with mixed methods: the PLOS One study’s thematic findings can be tracked with monthly service usage metrics and follow-up qualitative interviews to assess stigma reduction.
How Evidano helps: AI-enabled thematic synthesis for menstrual health research
Definition-first: What is Evidano and why it fits this workflow
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
The PLOS One study relied on manual transcription, translation checks, and NVivo coding, and Evidano can complement that workflow by accelerating transcription, supporting translation checks, and producing initial thematic code suggestions that researchers can refine.
Problem: Slow transcription and translation
The PLOS One study transcribed Bengali interviews and back-checked translations, which is time-consuming and error-prone, according to PLOS One.
Solution: Evidano offers secure transcription and translation with custom dictionaries and PII redaction, which reduces turnaround time while preserving confidentiality, see the speech-to-text and translation features.
Problem: Manual coding and limited cross-segment checks
The PLOS One article used NVivo v.12 and independent coders to reach consensus, which can be resource intensive, according to PLOS One.
Solution: Evidano generates thematic, frequency, and cross-segment analyses and visual code trees to show where themes like 'water scarcity' and 'shame' co-occur, enabling researchers to validate and iterate codes faster, see features.
Problem: Protecting sensitive qualitative data
The PLOS One study restricted full transcript sharing for ethical reasons, which is common in sensitive MHH work, according to PLOS One.
Solution: Evidano encrypts data end to end and does not share customer data to third-party model training, supporting safe collaborative analysis and controlled export of de-identified excerpts, see data security.
Problem: Producing policy-ready evidence quickly
The PLOS One study produced nuanced policy recommendations but required long turnaround, according to PLOS One.
Solution: Evidano creates exportable evidence packs (quotations, theme prevalence, and segment comparisons) that translate qualitative depth into program metrics for donors and city planners, enabling faster, defensible policy briefs.
FAQ: qualitative analysis of menstrual health
How many interviews are enough for a qualitative analysis of menstrual health?
+
Answer: Enough interviews to reach thematic saturation is the guiding principle, not a fixed number, according to the PLOS One study.
Support: The PLOS One study reports that after 15 IDIs no new concepts emerged and researchers ran three more interviews to confirm saturation, for a total of 18 IDIs and five KIIs collected between 1 September 2025 and 31 October 2025, according to PLOS One.
Which analysis methods suit menstruation studies in informal settlements?
+
Answer: A combined deductive and inductive thematic analysis is appropriate for capturing pre-existing frameworks and emergent local meanings, according to the PLOS One study.
Support: The PLOS One study used the Feminist Political Ecology framework deductively and added inductive codes from participant narratives, analyzed with Braun and Clarke’s six-phase approach and NVivo v.12, according to PLOS One.
How should researchers handle sensitive transcripts and data sharing?
+
Answer: De-identify transcripts and restrict full-access sharing; provide minimal supporting datasets on request under IRB-approved conditions, according to the PLOS One study.
Support: The PLOS One article reports that full transcripts are withheld for confidentiality while a minimal de-identified dataset and coding framework are available by request to the institutional data access committee, according to PLOS One.
Can AI tools safely accelerate menstrual health qualitative work?
+
Answer: Yes, when tools provide secure transcription, custom dictionaries for local terms, and researcher-in-the-loop coding, according to best-practice guidance and the PLOS One study context.
Support: The PLOS One study shows the cost of manual workflows in time and translation checks; AI-assisted transcription and thematic suggestions can speed iteration while human researchers retain analytic control, which is the approach Evidano supports, see speech-to-text.
What ethics note should appear in menstrual health research?
+
Answer: Menstrual health studies should follow IRB approvals, obtain informed consent, protect minors with guardian consent and assent, and withhold identifiable transcripts, according to the PLOS One study.
Support: The PLOS One article documents IRB approval (Approval No. 473478-FY 2024–2025; Approval Date: 10 August 2025) and procedures for consent and adolescent assent, and recommends restricted sharing to protect participants, according to PLOS One.
Conclusion & Next Steps
The PLOS One study published on July 24, 2026 documents how water scarcity, poor sanitation, disposal gaps, social stigma, and poverty intersect to shape menstrual experiences in Khulna Railway Slum, according to PLOS One.
Researchers and program teams can use these PLOS One findings to prioritize gender-responsive WASH, pre-menarche education, and subsidized product access, according to PLOS One.
Evidano accelerates this work by providing secure transcription, translation, thematic and cross-segment analysis, and exportable evidence packs that convert qualitative nuance into program metrics, see features.
Get started by converting interview transcripts into action: Try Evidano for free.
Topics
- qualitative analysis of menstrual health
- menstrual health qualitative study
- AI-enabled qualitative research
- menstrual hygiene Khulna
- thematic analysis menstruation
Keep reading
- Commentary on NewsMenstrual Health Qualitative Analysis: Khulna StudyPractical synthesis of the PLoS One Khulna study (Jul 24, 2026) for qualitative analysis of menstrual health. Learn methods, numbers, and how Evidano speeds thematic research.
- Commentary on NewsAI-enabled Qualitative Analysis of Menstrual HealthAI-enabled qualitative analysis reveals menstrual health barriers in Khulna slums from a PLOS One study; methods, stats, and actionable tools for researchers. Try Evidano.
- Commentary on NewsAI Synthesis: Qualitative Analysis of Menstrual HealthHow AI speeds thematic synthesis of qualitative menstrual health studies like the PLOS One Khulna study; methods, stats, and practical next steps for researchers.