AI Insight: Qualitative Analysis of Menstrual Health

According to the PLOS One study published on 24 July 2026, qualitative fieldwork in Khulna Railway Slum used 18 in-depth interviews and 5 key informant interviews collected between 01 September 2025 and 31 October 2025 to identify three core domains shaping menstrual experience: structural-environmental constraints, socio-cultural stigma, and gendered inequities in resource access (PLOS One).

• 18 IDIs and 5 KIIs were conducted from 01 September 2025 to 31 October 2025, enabling thematic saturation by interview 15, according to the authors.
• The study reports participant age range 15–45 years and states that 72% of participants had lived in the slum for over eight years (PLOS One, 24 July 2026).
• Researchers found practical barriers like unreliable water, communal toilets without doors, and no sanitary waste disposal, which led to unsafe practices and social isolation (PLOS One, 24 July 2026).
• Direct testimony in the study captures daily trade-offs: “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, quoted in PLOS One).

The study documented lived menstrual experiences in Khulna Railway Slum using qualitative methods, and the data were collected between 01 September 2025 and 31 October 2025, according to PLOS One (published 24 July 2026).

The authors conducted 18 in-depth interviews (IDIs) with women and adolescent girls aged 15–45 years and 5 key informant interviews (KIIs) with health workers, teachers, and NGO staff, and they report achieving thematic saturation by the fifteenth IDI (PLOS One, 24 July 2026).

Interviews were audio-recorded in Bengali, transcribed, translated to English, double-checked, and analyzed with a combined deductive and inductive thematic approach using Braun and Clarke’s six-phase framework and NVivo v.12, as described in PLOS One (24 July 2026).

If your research question is how infrastructure and stigma shape menstruation, then prioritize contextual sampling and combined IDI/KII designs as PLOS One did in its July 24, 2026 publication.

Researchers should record interview language and transcription choices explicitly: PLOS One conducted interviews in Bengali, transcribed and translated to English with back-checks, which supports transparency and reproducibility (PLOS One, 24 July 2026).

Coding strategies should mix deductive domains and inductive emergence: PLOS One used three predefined domains from Feminist Political Ecology and added emergent subcodes during NVivo coding, a pattern AI tools can accelerate by suggesting candidate themes from raw transcripts.

The PLOS One study published 24 July 2026 shows that qualitative data from 18 IDIs and 5 KIIs can reveal how water, sanitation, stigma, and poverty interact to shape menstrual health in urban informal settlements (PLOS One).

AI-enabled qualitative research platforms can accelerate transcription, suggest thematic codes, and produce cross-segment analyses while preserving ethical safeguards described in the study.

If you run qualitative studies on menstrual health or other sensitive topics, try turning raw audio and transcripts into reproducible, auditable findings with Evidano.

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