Menstrual Health Qualitative Analysis: Khulna Study

Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. According to the PLoS One study published July 24, 2026, women and adolescent girls in Khulna Railway Slum face menstrual challenges shaped by environmental constraints, socio-cultural stigma, and gendered inequities. According to the PLoS One study published July 24, 2026, the research collected 18 in-depth interviews and 5 key informant interviews between 01/09/2025 and 31/10/2025 and used thematic analysis with NVivo v12. This post explains the study findings, gives extractable analytic steps for qualitative researchers, and shows how AI-enabled tools can accelerate thematic synthesis while protecting sensitive transcripts.

Key Takeaways

The PLoS One study published July 24, 2026, found that menstrual experiences in Khulna’s informal settlements are driven by three interacting domains: structural-environmental constraints, socio-cultural stigma, and gendered inequities in resource access (PLOS One).

Data collection occurred between 01/09/2025 and 31/10/2025 and included 18 in-depth interviews (IDIs) and 5 key informant interviews (KIIs), according to the PLoS One study published July 24, 2026.
According to the PLoS One study published July 24, 2026, participant demographics included ages 15–45, with 39% aged 20–30 and 72% living in the slum for over eight years.
According to the PLoS One study published July 24, 2026, participants reported inadequate water, communal toilets lacking privacy, and no formal menstrual waste disposal, summarized by one participant: "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).

What happened: qualitative analysis of menstrual health in Khulna

According to the PLoS One study published July 24, 2026, researchers conducted a purposive sample of 18 women and adolescent girls and 5 key informants to explore lived menstrual experiences between 01/09/2025 and 31/10/2025.

According to the PLoS One study published July 24, 2026, interviews were semi-structured, conducted in Bengali, audio recorded with consent, transcribed into English, and analyzed using a combined inductive-deductive thematic approach guided by Feminist Political Ecology.

According to the PLoS One study published July 24, 2026, the coding process used NVivo v12, two independent coders, and iterative consensus meetings to establish three primary themes and multiple subthemes.

According to the PLoS One study published July 24, 2026, ethical safeguards included IRB approval (Approval No. 473478-FY 2024–2025; Approval Date: 10 August 2025) and pseudonymization of transcripts to protect participants.

Findings snapshot

Date / Range	Metric	Value	Implication
01/09/2025–31/10/2025	Data collected	18 IDIs, 5 KIIs	Sufficient for thematic saturation in a focused qualitative study (authors stopped after no new themes).
24/07/2026	Publication	PLOS One article	Peer-reviewed dissemination of context-specific findings for Khulna slums.
Participant demographics (as reported)	Age and education distribution	Ages 15–45; 39% aged 20–30; 39% non-literate, 33% secondary, 28% primary	Highlights need to tailor MHH interventions by literacy and life-stage.
Reported WASH issues (participant quotes)	Qualitative evidence	No private toilets, intermittent water, informal disposal	Design WASH upgrades with gendered privacy and disposal in mind.

Implications for qualitative researchers: qualitative analysis of menstrual health

Researchers should treat menstruation as a socio-ecological phenomenon, not only a hygiene problem, according to the PLoS One study published July 24, 2026.

Researchers should collect contextual metadata, because the PLoS One study published July 24, 2026, shows that residence duration (72% > 8 years) and household composition shape privacy and disposal practices.

Researchers should use combined inductive and deductive coding, because the PLoS One study published July 24, 2026, successfully used a pre-defined Feminist Political Ecology framework plus emergent codes to surface both expected and novel themes.

Researchers should plan ethics and data governance proactively, because the PLoS One study published July 24, 2026, restricted full transcripts for confidentiality and provided a minimal de-identified dataset on request.

How Evidano helps

Problem: Small, sensitive samples require secure transcription and nuanced coding

Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.

Evidano provides encrypted transcription with PII redaction and a custom dictionary, addressing the PLoS One study’s ethical requirement to protect participant identity (IRB Approval No. 473478-FY 2024–2025; Approval Date: 10 August 2025).

Evidano also offers speech-to-text capabilities to convert audio interviews into time-stamped transcripts while preserving speaker labels for rigorous thematic coding.

Problem: Iterative, mixed inductive-deductive coding is slow and prone to inconsistency

Evidano automates code suggestion, hierarchical code management, co-occurrence networks, and frequency tables to accelerate the Braun and Clarke six-phase workflow used in the PLoS One study published July 24, 2026.

Evidano’s thematic and cross-segment analyses let teams compare adolescents versus adult women (as the PLoS One study did with ages 15–45) and document code reliability across coders.

Evidano’s visualizations and exports make it easier to present COREQ-aligned trustworthiness strategies used in the PLoS One study, including audit trails and codebook documentation.

Problem: Sensitive qualitative data needs controlled sharing

Evidano encrypts data and uses models tuned for qualitative research; Evidano does not use customer data to train third-party models, addressing the confidentiality practices emphasized by the PLoS One study published July 24, 2026.

Evidano supports role-based access and project-level permissions so de-identified minimal datasets can be shared with institutional committees consistent with the PLoS One study’s data access statement.

Want to try the workflow used here?

See how features map to the Khulna study workflow in Evidano’s features page and test secure transcription on the speech-to-text demo.

FAQ: qualitative analysis of menstrual health

How did the PLoS One Khulna study collect and analyze qualitative data?

Answer: The study collected 18 in-depth interviews and 5 key informant interviews between 01/09/2025 and 31/10/2025 and analyzed them thematically using NVivo v12, according to the PLoS One study published July 24, 2026.

According to the PLoS One study published July 24, 2026, the team used semi-structured interviews in Bengali, back-checked translations, and combined inductive and deductive coding under a Feminist Political Ecology framework.

What were the primary themes the study identified?

Answer: The primary themes were structural-environmental constraints, socio-cultural stigma, and gendered inequities in access to menstrual resources, as reported in the PLoS One study published July 24, 2026.

According to the PLoS One study published July 24, 2026, subthemes included water scarcity, lack of private toilets, hidden disposal practices, shame and taboos, and household-level financial control of menstrual products.

How can AI help analyze sensitive qualitative interviews like these?

Answer: AI can speed transcription, suggest codes, and surface co-occurrence patterns while preserving confidentiality when tools enforce encryption and PII redaction, consistent with ethical guidance cited in the PLoS One study published July 24, 2026.

According to established best practices summarized by UNICEF and UNESCO guidance, AI-assisted workflows that include human validation preserve rigor and reduce coder bias while accelerating analytic cycles.

Can findings from the Khulna study be generalized to other settings?

Answer: The Khulna findings are context-rich and intended for analytical transferability rather than statistical generalization, according to the PLoS One study published July 24, 2026.

According to the PLoS One study published July 24, 2026, the authors recommend complementary mixed-methods and wider sampling if the goal is broader generalizability.

Conclusion & Next Steps

According to the PLoS One study published July 24, 2026, addressing menstrual dignity in informal settlements requires combined WASH upgrades, education, affordable products, and stigma reduction.

According to the PLoS One study published July 24, 2026, qualitative methods paired with secure, auditable analysis tools produce the contextual evidence policymakers need to design gender-responsive services.

If you run qualitative research on sensitive topics and want an AI-enabled workflow that preserves confidentiality and speeds thematic synthesis, Try Evidano for free.

Topics

qualitative analysis of menstrual health
menstrual health qualitative study
menstrual hygiene research methods
AI-enabled qualitative analysis

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Menstrual Health Qualitative Analysis: Khulna Study

Key Takeaways

What happened: qualitative analysis of menstrual health in Khulna

Findings snapshot

Implications for qualitative researchers: qualitative analysis of menstrual health

How Evidano helps

Problem: Small, sensitive samples require secure transcription and nuanced coding

Problem: Iterative, mixed inductive-deductive coding is slow and prone to inconsistency

Problem: Sensitive qualitative data needs controlled sharing

Want to try the workflow used here?

FAQ: qualitative analysis of menstrual health

How did the PLoS One Khulna study collect and analyze qualitative data?

What were the primary themes the study identified?

How can AI help analyze sensitive qualitative interviews like these?

Can findings from the Khulna study be generalized to other settings?

Conclusion & Next Steps

Topics

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