AI-enabled Qualitative Analysis: Digital Gender Exclusion

The primary challenge in studying why women are not online is that sociocultural norms and household gatekeepers shape access more than infrastructure alone. The primary keyword for this post is qualitative analysis of digital gender exclusion, aimed at qualitative researchers, program designers, and policy teams who will analyze interviews, focus groups, and co-design workshop outputs. 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. (published August 20, 2026), participatory methods that engage family gatekeepers and community leaders are central to understanding exclusion in Azam Basti, Karachi. This post shows concrete, reproducible steps to convert that protocol’s text, audio, and workshop artifacts into rigorously coded themes and cross-segment findings using AI-enabled qualitative analysis tools.

Key Takeaways

According to PLOS One, Shahil-Feroz et al.'s study protocol (published August 20, 2026) treats household gatekeepers and sociocultural norms as primary drivers of women's digital exclusion in Azam Basti, Karachi.

The PLOS One protocol plans approximately 36–45 participants across focus groups, interviews, and co-design workshops, with participant recruitment scheduled for August–November 2026.
According to the GSMA Mobile Gender Gap Report 2024, women in Pakistan were 38% less likely than men to own a mobile phone or access mobile internet (GSMA, 2024).
The PLOS One protocol cites PTA survey results showing in 2024 that 16% of female respondents and 23% of male respondents believed women should not use mobile phones at all.
The PLOS One protocol is funded by an SSHRC Insight Development Grant of $70, 626 and schedules results to be available beginning in late 2027.

What Happened: the PLOS One study protocol in brief

Answer: The PLOS One protocol describes a community-based participatory research (CBPR) qualitative study to explore sociocultural drivers of digital gender exclusion and co-design local solutions in Azam Basti, Karachi.

According to Shahil-Feroz et al. in PLOS One (published August 20, 2026), the study has three phases: (1) form a Community Advisory Committee (CAC), (2) conduct focus group discussions (FGDs) and 4–5 in-depth interviews per group using photo-elicitation and role-play, and (3) run 3 co-design workshops to produce interventions.

According to the PLOS One protocol, the total sample across participant groups will be approximately 36–45 people, the project begins in February 2026, recruitment is planned August–November 2026, data collection is expected to finish by April 2027, and results are expected beginning in late 2027.

According to the PLOS One protocol, analysis uses Braun and Clarke’s reflexive thematic analysis coded independently by two researchers and organized with NVivo, and visual/arts-based materials will support local knowledge translation.

Findings Snapshot

Date	Metric	Value	Implication
2024	Global Gender Gap Index (Pakistan)	Pakistan ranked 145/146	Highlights systemic gender inequality that frames digital exclusion, cited in the PLOS One protocol
2024	Mobile Gender Gap (GSMA)	Women 38% less likely to own a phone or access mobile internet	Structural access gap to prioritize in recruitment and interpretation, cited by Shahil-Feroz et al.
2024	PTA survey belief about women using phones	16% of female respondents, 23% of male respondents said women should not use phones	Documents household and normative resistance to women’s phone use, used as context in the protocol
Feb 2026–Jan 2028	Study timeline	2-year project (start Feb 2026), recruitment Aug–Nov 2026, data collection by Apr 2027	Operational timeline researchers should map to analysis milestones
2025 Competition	Funding	$70, 626 SSHRC Insight Development Grant	Budget scale for a participatory qualitative project with community compensation

Implications for qualitative researchers and practitioners

Answer: Researchers must treat household gatekeepers and sociocultural norms as core analytical strata, not peripheral context.

According to Shahil-Feroz et al. in PLOS One, the protocol explicitly engages male partners, brothers, elderly women, and community leaders to co-design interventions because household decision-making governs women’s technology access.

According to the PLOS One protocol, participatory tools such as photo-elicitation and role-play generate multi-modal data (images, transcripts, enactments) that require integrated analysis across data types, and reflexive thematic analysis is recommended to surface how "deeply entrenched sociocultural barriers" shape behaviors.

According to the GSMA report (2024), quantitative prevalence (for example, a 38% mobile gender gap) should be used alongside qualitative findings to prioritize groups for intervention and to triangulate causes and feasible solutions.

How Evidano Helps

Problem: Multi-modal, multilingual data slow analysis → Solution: automated transcription and translation

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

According to the PLOS One protocol, FGDs and interviews will be conducted in Urdu (and Sindhi when required) and translated into English for coding; Evidano’s transcription and translation features reduce manual time by providing accurate, timestamped transcripts and custom-dictionary translations.

Use case: upload audio from FGDs, apply Evidano’s speech-to-text with PII redaction and a custom Urdu dictionary, then export verified transcripts for NVivo import or code directly in Evidano. See the Evidano speech-to-text and Evidano features pages for specifics.

Problem: Slow thematic synthesis across participant groups → Solution: AI-assisted thematic and cross-segment analysis

Answer: Evidano speeds thematic synthesis by auto-suggesting codes, clustering similar excerpts, and running frequency and cross-segment comparisons.

Practical mapping: apply reflexive thematic analysis workflows by uploading transcripts, let Evidano generate initial code suggestions, then refine codes collaboratively with the Community Advisory Committee as the PLOS One protocol recommends for co-analysis and validation.

Problem: Co-design artifacts and role-play outputs are hard to code → Solution: multimodal annotation and visualization

Answer: Evidano supports image and transcript linkage, so photo-elicitation prompts and role-play debriefs can be analyzed together.

Practical mapping: tag segments from workshop transcripts to associated images, run co-occurrence networks to show which gatekeeper types and norms appear together, and export visuals for stakeholder briefs as the PLOS One protocol envisions for policy translation.

FAQ: qualitative analysis of digital gender exclusion

What qualitative methods does the PLOS One protocol use and why?

Answer: The protocol uses community-based participatory research with focus group discussions, in-depth interviews, photo-elicitation, role-play, and co-design workshops to surface household and community norms.

According to Shahil-Feroz et al. in PLOS One, these methods are chosen because they engage family gatekeepers and produce both sensitive personal narratives and public enactments of norms that drive digital exclusion.

How large is the planned sample and how was it chosen?

Answer: The protocol plans approximately 36–45 participants selected purposively across marginalized women, family gatekeepers, and community leaders.

According to the PLOS One protocol, purposive sampling and theoretical saturation will determine the final counts, with FGDs sized at 4–5 participants per group and 4–5 individual interviews per participant category.

How can AI practically accelerate the analysis of these data?

Answer: AI can accelerate transcription, translation, initial coding, code clustering, and cross-segment frequency analysis, while preserving researcher reflexivity.

According to the PLOS One protocol, transcripts will be translated and analyzed with reflexive thematic methods; Evidano’s AI-assisted features can generate initial code proposals and visual summaries that researchers then confirm and refine, shortening time to actionable findings.

What ethical safeguards does the PLOS One protocol include?

Answer: The protocol obtained ethical approvals and builds informed consent procedures and confidentiality protections into fieldwork.

According to Shahil-Feroz et al. in PLOS One, ethics approval was obtained from Western University NMREB, Aga Khan University, and the National Bioethics Committee Pakistan, and consent procedures include Urdu-language forms, thumbprint options, and group confidentiality discussions.

Conclusion & Next Steps

Answer: Combining the PLOS One participatory protocol with AI-enabled qualitative analysis yields faster, more defensible insights into digital gender exclusion and produces shareable outputs for policy and community partners.

According to Shahil-Feroz et al. in PLOS One, engaging gatekeepers and co-designing solutions is essential; AI tools reduce the time from data collection to co-designed recommendations without replacing community validation.

If you are preparing to analyze FGDs, interviews, and co-design workshops like those in the Azam Basti protocol, consider a workflow that combines careful transcription and translation, reflexive thematic coding, and visual cross-segment reports.

To experiment with those workflows, Try Evidano for free.

Topics

qualitative analysis of digital gender exclusion
digital gender gap Pakistan
AI qualitative research
thematic analysis digital inclusion

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