AI Qualitative Analysis: Gender Digital Exclusion

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 protocol by Shahil-Feroz et al. (2026) PLOS One, gender-based digital exclusion in Pakistan is driven by sociocultural norms, household gatekeepers, and structural barriers. According to the PLOS One study authors (2026), women in Pakistan remain far less likely than men to own or use mobile internet, with GSMA reporting in 2024 that women were 38% less likely than men to own a mobile phone or access mobile internet. According to the PLOS One protocol (2026), the research will run from February 2026 through January 2028 and use participatory methods to co-design local solutions with community advisory members. This post shows how AI-enabled qualitative research can speed reflexive thematic analysis, preserve community voice, and produce actionable recommendations for policymakers and implementers.

Key Takeaways

According to the PLOS One study protocol by Shahil-Feroz et al. (2026) PLOS One, sociocultural norms and household gatekeepers are central drivers of gender digital exclusion in Azam Basti, Karachi, and the study will use photo-elicitation, role play, and co-design workshops to develop community-led solutions. The study authors write that these barriers include "deeply entrenched sociocultural barriers" and that the project "moves beyond awareness-based approaches to co-develop sustainable strategies for digital inclusion" (Shahil-Feroz et al., 2026).

According to GSMA (2024), women in Pakistan were 38% less likely than men to own a mobile phone or access mobile internet in 2024.
According to the World Economic Forum Global Gender Gap report (2024), Pakistan ranked 145 out of 146 countries in 2024.
According to the PLOS One protocol (2026), the field study will sample approximately 36–45 participants across FGDs and interviews, with participant recruitment scheduled for August–November 2026 and data collection completed by April 2027.
According to the PLOS One protocol (2026), the research received a Social Sciences and Humanities Research Council grant of $70, 626 (2025 competition).

What the PLOS One study will do and how it works

Answer: The PLOS One protocol by Shahil-Feroz et al. (2026) outlines a three-phase community-based participatory research (CBPR) project in Azam Basti, Karachi that combines advisory committees, focus groups, interviews, and co-design workshops to document and address gender digital exclusion.

According to Shahil-Feroz et al. (2026), Phase 1 will form a Community Advisory Committee (CAC) with community leaders, marginalized women, and family gatekeepers to co-lead methods and materials; Phase 2 will run 2 FGDs per participant group plus 4–5 in-depth interviews per group, with a projected total sample of about 36–45 participants; Phase 3 will convene 3 co-design workshops with 25–30 participants to generate locally appropriate interventions.

According to Shahil-Feroz et al. (2026), qualitative data will be collected in Urdu (and Sindhi where required), transcribed, translated to English, and analysed using reflexive thematic analysis with NVivo support and CAC validation.

According to Shahil-Feroz et al. (2026), ethical approvals were obtained from Western University NMREB, Aga Khan University, and the National Bioethics Committee in Pakistan, and the study timeline begins February 2026 with results expected from late 2027.

Findings snapshot

Date	Metric	Value	Implication
2024	GSMA mobile gender gap (Pakistan)	Women 38% less likely to own mobile/access mobile internet	Signals a large access gap to explore in qualitative interviews
2024	Global Gender Gap rank (Pakistan)	145 of 146 countries	Contextualizes severe gender inequality affecting digital inclusion
2025	Research funding	$70, 626 SSHRC Insight Development Grant	Resources to support two-year CBPR project and co-design
Feb 2026–Jan 2028	Study timeline	2-year project; recruitment Aug–Nov 2026; data through Apr 2027	Provides clear milestones for data collection, analysis, and policy outputs
Phase 2 (planned)	Planned sample	Approximately 36–45 participants across FGDs and interviews	Enables in-depth thematic exploration and saturation checks

Implications for qualitative researchers and program designers

Answer: The PLOS One protocol (Shahil-Feroz et al., 2026) demonstrates that qualitative projects aiming to address gender digital exclusion must combine community advisory roles, participatory methods, and co-design to surface actionable social-norm interventions.

According to Shahil-Feroz et al. (2026), involving family gatekeepers and community leaders helps move interventions from awareness to norm change and is essential where patriarchal dynamics constrain technology use.

According to the PLOS One protocol (2026), photo-elicitation and role-play can elicit tacit norms and household decision-making patterns that surveys miss, which means researchers should budget for visual data transcription and bilingual translation in similar CBPR projects.

According to Shahil-Feroz et al. (2026), co-design workshops with iterative validation from advisory committees improve cultural fit and uptake, suggesting funders and implementers should finance extended engagement rather than one-off training.

How Evidano helps: from raw transcripts to policy-ready themes

Problem: Long, manual transcription and translation

Solution: Evidano provides automated transcription with custom dictionaries and PII redaction, which speeds data preparation while preserving participant confidentiality.

According to best practice for multilingual CBPR cited in the PLOS One protocol (2026), transcripts must be checked by bilingual researchers; Evidano supports human-in-the-loop corrections so teams can meet that standard without retyping entire transcripts.

Problem: Reflexive thematic analysis requires iteration and stakeholder validation

Solution: Evidano supports thematic coding, co-occurrence networks, and hierarchical code trees that speed initial code generation and let research teams iteratively refine themes with advisory committees.

According to Shahil-Feroz et al. (2026), the CAC will validate themes; Evidano’s exportable theme summaries and visualizations make it faster to present findings to advisory committees and co-design workshops.

Problem: Translating findings into tailored materials for communities and policymakers

Solution: Evidano’s AI chat over documents and visual exports help teams produce stakeholder reports, policy briefs, and accessible knowledge translation artifacts more quickly.

Teams running CBPR like Shahil-Feroz et al. (2026) can use Evidano features to iterate messaging for community videos, infographics, or voice messages that the PLOS One protocol plans to produce.

Relevant product links

Learn more about the platform in context on the Evidano features page.

Use Evidano’s speech-to-text for Urdu transcription and human-in-the-loop corrections to match the multilingual workflow described in Shahil-Feroz et al. (2026).

FAQ: gender digital exclusion qualitative analysis

How will the PLOS One study collect qualitative data in Azam Basti?

Answer: The PLOS One protocol (Shahil-Feroz et al., 2026) will collect data via community advisory input, photo-elicitation FGDs, role-play FGDs with gatekeepers, and 4–5 in-depth interviews per group.

According to Shahil-Feroz et al. (2026), FGDs will be conducted in Urdu with 4–5 participants per group and last 60–90 minutes, and interviews will last 40–60 minutes to explore sensitive issues privately.

What sample size and timeline does the study plan to use?

Answer: The study plans for approximately 36–45 participants with recruitment from August–November 2026 and data collection completed by April 2027, according to the PLOS One protocol (2026).

According to Shahil-Feroz et al. (2026), the overall project spans February 2026 to January 2028 with analysis and policy brief development in the final eight months.

How can AI speed reflexive thematic analysis without losing rigor?

Answer: AI can accelerate initial coding and pattern detection while human analysts retain reflexive judgment, as recommended by methodological sources cited in the PLOS One protocol (Braun and Clarke, various years).

According to Braun and Clarke’s guidance cited in the PLOS One protocol (2026), reflexive thematic analysis depends on researcher interpretation; Evidano’s AI assists by surfacing candidate codes, frequency counts, and co-occurrence maps that analysts then refine and validate with advisory committees.

Can the methods in this protocol be adapted to other LMIC settings?

Answer: Yes, Shahil-Feroz et al. (2026) argue that the CBPR and technofeminist approach is transferable to other marginalized communities but requires local CAC participation for cultural relevance.

According to Shahil-Feroz et al. (2026), the single-site design limits direct generalizability, but the participatory process and co-design outputs are intended as adaptable models for similar settings.

Conclusion & Next Steps

Answer: The PLOS One protocol by Shahil-Feroz et al. (2026) sets a clear, participatory blueprint for uncovering how sociocultural norms and household gatekeepers shape gender digital exclusion in a marginalized Pakistan community, and AI-enabled qualitative tools can shorten the path from transcripts to policy-ready recommendations.

According to Shahil-Feroz et al. (2026), the study’s participatory design and co-design workshops aim to produce culturally appropriate strategies that "move beyond awareness-based approaches to co-develop sustainable strategies for digital inclusion" (Shahil-Feroz et al., 2026).

If your team runs CBPR or needs multilingual transcription, consider piloting an AI-enabled qualitative workflow to accelerate coding, cross-segment comparisons, and stakeholder reporting using platforms built for qualitative rigor. Learn more about Evidano on the features page and Try Evidano for free.

Topics

gender digital exclusion
digital gender inclusion
qualitative analysis of digital exclusion
AI-enabled thematic analysis

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