Why LARC/PM Uptake Is Low: Qualitative Analysis in Bangladesh

This post explains how to do a rigorous qualitative analysis of LARC uptake using the PLOS One study as a worked example, aimed at qualitative researchers and program teams. The primary keyword "qualitative analysis of LARC uptake" guides the methods and recommendations below. According to the PLOS One study published on August 25, 2026, researchers used 28 in-depth interviews and 9 key informant interviews in Cumilla district to map multilevel barriers to long-acting reversible and permanent contraceptive methods (LARC/PM). The payoff is practical: how to structure transcripts, code for embodied concerns and provider bias, and use AI-enabled tools to accelerate thematic synthesis while protecting participant rights.

Key Takeaways

According to the PLOS One study published on August 25, 2026, multilevel barriers, knowledge gaps, embodied side-effect experiences, gendered decision-making, stigma, religious beliefs, provider bias, and health-system shortages, explain persistently low LARC/PM uptake in rural Cumilla, Bangladesh.

The PLOS One study collected 28 in-depth interviews with married women and men and 9 key informant interviews between January 21 and February 20, 2023.
According to the PLOS One authors, Cumilla reported 13.6% LARC/PM use in 2022 while Chattogram Division showed 6.1% LARC/PM uptake as of 2022, and national LARC/PM share declined to 8% in 2022 from 12.1% in 1991.
The PLOS One study documented widespread method misperceptions and tangible embodied fears, illustrated by quotes such as, "Look, sister, we are uneducated people. We don’t know or understand these methods" (participant W 02, PLOS One).
The PLOS One findings highlight institutional harms including brief counselling, privacy deficits, coercive practices, and workforce shortages that undermine informed choice.

What Happened and how the study was done

The PLOS One study conducted a one-time qualitative inquiry in Cumilla to identify why LARC/PM uptake is low and how barriers interact across levels.

According to the PLOS One article (Shoma and Barden-O’Fallon, published August 25, 2026), researchers purposively sampled two Upazilas and used 28 in-depth interviews (22 women, 6 men) plus 9 key informant interviews with providers and one religious leader to reach thematic saturation between January 21 and February 20, 2023.

The PLOS One team analyzed Bengali transcripts using Braun and Clarke’s thematic analysis framed by the socio-ecological model, coding iteratively with a hybrid inductive-deductive approach and cross-checking English translations for fidelity.

Findings snapshot

Date / Source	Metric	Value	Implication
Data collection (PLOS One)	Interviews completed	28 IDIs (22 women, 6 men) and 9 KIIs	Sufficient depth to map individual to health-system barriers
Published (PLOS One)	Publication date	25 August 2026	Recent qualitative evidence for program design
DGFP / PLOS One citation	Local LARC/PM coverage (2022)	Cumilla 13.6%; Chattogram Division 6.1%; National LARC/PM share 8% in 2022	Confirms program-level low uptake and geographic disparity
Sample demographics (PLOS One)	Women with 3–5 children	17 of 28 participants reported 3–5 children	High parity common; male child preference and parity norms relevant
Service delivery (PLOS One)	Reported provider practices	Brief counselling (often <5 minutes), irregular field visits, workforce shortages	Quality-of-care gaps and rights violations require system fixes

Implications for qualitative researchers and program teams

The PLOS One study implies that qualitative researchers must design interviews and coding schemes to capture embodied experiences, rumor networks, and institutional abuses rather than only knowledge scores.

According to the PLOS One findings, researchers should sample beyond women to include husbands, mothers-in-law, religious leaders, and frontline providers to trace how social norms and provider behavior propagate misperceptions.

According to the PLOS One authors, methodologists should treat LARC and PM as analytically distinct where reversibility, consent, and stigma differ, and code for both anticipated and vicarious side-effect narratives.

According to the PLOS One study, research ethics in family planning require careful consent, privacy, and post-interview referral protocols because interviewees reported coercive or non-consensual service experiences.

How Evidano helps: mapping the study's analytic needs to AI-enabled features

Problem: Long, untranslated transcripts and multilingual coding

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

Solution: Evidano offers secure transcription with custom dictionaries and translation support to convert Bengali audio into searchable English and Bengali transcripts, which matches the PLOS One workflow that required careful translation and cross-checking.

Problem: Capturing embodied side-effect narratives and rumor co-occurrence

Solution: Evidano’s thematic and co-occurrence network visualizations let teams tag 'embodied experience', 'rumor', and 'provider dismissal' codes and then surface which narratives cluster with gender, age, or migration status.

According to the PLOS One themes, tagging narratives like "excessive bleeding" or "device migration" enables rapid extraction of high-impact quotes and frequency counts for program briefs.

Problem: Rapid synthesis for rights-based program design

Solution: Evidano supports thematic summaries, cross-segment comparisons (for example women vs. men, or households with migrants vs. non-migrants), and exportable analytic tables that map barriers to levels of the socio-ecological model.

You can learn more about these capabilities on the Evidano features page.

Problem: Protecting participant privacy and reproducibility

Solution: Evidano provides PII redaction, encrypted storage, and an auditable coding history that supports ethical reporting and reproducibility when analyzing sensitive family planning interviews as documented in the PLOS One study.

Solution: Evidano’s AI chat over your documents helps non-technical stakeholders query evidence (quotes, counts, coded segments) while preserving source traceability.

FAQ: qualitative analysis of LARC uptake

How can AI help analyze qualitative interviews about contraceptive uptake?

Answer: AI accelerates coding, summarization, and cross-segment comparison while preserving researcher oversight.

Supporting detail: According to the PLOS One study, interviews include embodied and rumor-based narratives that benefit from human-in-the-loop AI workflows which surface candidate themes and extract verbatim quotes for researcher validation.

What sample and data details did the PLOS One study use that I should emulate?

Answer: The PLOS One study used 28 IDIs and 9 KIIs collected between January 21 and February 20, 2023, with purposive sampling across two Upazilas.

Supporting detail: According to PLOS One, include variation in parity, migration status, and provider type to enable cross-segment analysis of norms, service barriers, and rights violations.

How do I code for 'embodied' versus 'misinformation' narratives ethically?

Answer: Code embodied experiences (reported bleeding, pain, weakness) as distinct from circulating misinformation (device migration, organ removal) and preserve contextual notes on source credibility.

Supporting detail: According to the PLOS One findings, participants often anchored beliefs in personal or vicarious bodily experience, so coding must preserve whether a claim was lived experience, vicarious report, or rumor to avoid dismissing legitimate concerns.

How should researchers respond when interviews reveal coercive provider practices?

Answer: Prioritize participant safety, document the account with verbatim quotes and timestamps, and follow pre-specified referral and reporting protocols.

Supporting detail: The PLOS One article reported instances of non-consensual insertions and refusals to remove methods, so ethical protocols and institutional review plans must include pathways for participant support and anonymized reporting.

Conclusion & Next Steps

The PLOS One study (published August 25, 2026) shows that low LARC/PM uptake in rural Bangladesh is produced by entwined sociocultural, institutional, and system-level factors, not by knowledge gaps alone.

For qualitative teams, the analytic priority is to preserve context: tag embodied effects, map rumor networks, and cross-segment responses by gender and migration status.

Evidano helps teams operationalize these priorities with secure transcription, translation, thematic and cross-segment analytics, and auditable coding exports for program design and rights-based advocacy.

To try an AI-enabled qualitative workflow on your data, Try Evidano for free.

Topics

qualitative analysis of LARC uptake
LARC uptake Bangladesh qualitative
AI-enabled qualitative research
long-acting contraception qualitative

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