This post explains how researchers can apply AI-enabled qualitative analysis to study gender digital exclusion qualitative analysis in Pakistan and turn community interviews into actionable co-designed solutions. The target audience is qualitative researchers and program teams planning participatory studies; the payoff is a clear mapping from methods used in the PLOS ONE study protocol to AI-supported workflows that speed transcription, coding, cross-segment comparisons, and co-design synthesis.
Key Takeaways
According to the PLOS ONE study protocol, the research will use community-based participatory research and reflexive thematic analysis to understand why marginalized women in Azam Basti, Karachi, lack meaningful digital access, and the protocol frames this as social rather than purely technical exclusion (PLOS ONE).
- The PLOS ONE protocol (published August 20, 2026) plans ~36–45 participants across FGDs and interviews, with data collection scheduled to run from August 2026 to April 2027.
- The PLOS ONE authors cite the GSMA Mobile Gender Gap Report 2024 showing that, in 2024, women in Pakistan were 38% less likely than men to own a mobile phone or access mobile internet, a structural gap the study seeks to explain in context.
- The PLOS ONE protocol will form a Community Advisory Committee and run three co-design workshops to move beyond awareness-raising to community-led solutions; the project received SSHRC funding of $70, 626 and was scheduled to start in February 2026.
What happened and how the study works
The PLOS ONE protocol describes a three-phase community-based participatory research (CBPR) design to probe gendered barriers to technology access in Azam Basti, Karachi, and to co-design interventions with community gatekeepers (PLOS ONE).
According to the PLOS ONE authors, Phase 1 creates a Community Advisory Committee with community leaders, two marginalized women, and three family gatekeepers to co-lead the study; Phase 2 runs focus group discussions (FGDs) and 4–5 in-depth interviews per group; Phase 3 holds 3 co-design workshops to develop local strategies.
According to the PLOS ONE protocol, FGDs use photo-elicitation and role-play to surface ‘"deeply entrenched sociocultural barriers"’ (Shahil-Feroz et al., PLOS ONE 2026) that quantitative surveys miss, and transcripts will be analysed using Braun and Clarke’s reflexive thematic analysis with NVivo support.
Findings Snapshot
| Date | Metric | Value | Implication |
|---|---|---|---|
| August 20, 2026 | Manuscript published | PLOS ONE | Protocol and methods publicly available for replication |
| 2024 | Mobile gender gap (Pakistan) | Women 38% less likely to own or use mobile internet (GSMA 2024) | Structural access gap motivates sociocultural inquiry |
| Project timeline (Feb 2026 start) | Planned participants | Approximately 36–45 participants | Qualitative sample sized for theoretical saturation |
| 2025 Competition (funding awarded) | SSHRC grant | $70, 626 CAD | Funds community engagement, CAC, and co-design activities |
| Aug 2026–Apr 2027 | Data collection window | FGDs, interviews, co-design workshops | Provides timeline for transcription and analysis planning |
Implications for qualitative researchers and program teams
Researchers should prioritise social context over device counts: the PLOS ONE protocol argues that sociocultural norms shape access even where devices exist, so qualitative methods are essential to explain the 38% access gap reported by GSMA in 2024 (PLOS ONE).
Program teams planning evaluations should budget for iterative community engagement: the PLOS ONE authors schedule quarterly CAC meetings and three co-design workshops to ensure solutions are culturally appropriate and feasible.
Field teams should plan language and translation workflows: the PLOS ONE protocol requires Urdu (and Sindhi as needed) transcription and translation before reflexive thematic analysis, so teams must factor in bilingual transcription and back-translation verification.
How Evidano Helps: from CBPR transcripts to co-designed findings
What Evidano is and why it matters here
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, the study will produce multi-language transcripts, photo-elicitation artifacts, and role-play notes that require integrated parsing, coding, and cross-segment comparison (PLOS ONE).
Evidano accelerates this work by combining accurate transcription, bilingual translation support, thematic coding, and cross-segment frequency analysis so teams can iterate with Community Advisory Committees and co-design groups faster.
Problem: multi-language transcription and translation
The PLOS ONE protocol requires Urdu transcription and English translation for analysis, which is time-consuming and error prone (PLOS ONE).
Evidano feature: use Evidano's speech-to-text for staged transcription with custom dictionaries and PII redaction, then Evidano's translation tools to produce validated bilingual transcripts for reflexive coding.
Problem: coding consistency and participatory validation
The PLOS ONE team plans two independent coders and advisory committee validation, a labour-intensive process that can delay co-design workshops (PLOS ONE).
Evidano feature: thematic and hierarchical coding with co-analysis dashboards helps teams compare coder overlap, produce code co-occurrence networks, and export audit trails for CAC review, matching the protocol's requirement for reflexive memos and transparency.
Problem: turning themes into co-design inputs
The PLOS ONE protocol uses co-design workshops to translate findings into interventions, requiring concise, shareable outputs for participants and policymakers (PLOS ONE).
Evidano feature: create shareable visualizations (word clouds, co-occurrence maps, and frequency tables) and evidence summaries that community advisory committees can review during workshops, shortening the time from analysis to actionable design.
Learn more about relevant tools
See how Evidano's integrated workflows map to the PLOS ONE protocol features on our Evidano Features page.
Teams using Evidano can reduce manual transcription and early-stage coding time, freeing researcher hours for participatory engagement and iterative co-design as recommended in the PLOS ONE study.
FAQ: gender digital exclusion qualitative analysis
How can qualitative research explain a 38% mobile access gap in Pakistan?
Direct answer: Qualitative research reveals sociocultural mechanisms behind numeric gaps, such as family gatekeeping and norms, which surveys alone cannot explain.
Supporting detail: The PLOS ONE protocol specifies FGDs, photo-elicitation, and role-play with family gatekeepers to surface norms that create the GSMA-reported 38% gap in 2024, enabling interventions that target household power dynamics rather than only device provision (PLOS ONE).
What sample size is appropriate for this type of CBPR study?
Direct answer: The PLOS ONE protocol plans approximately 36–45 participants across FGDs and interviews, sized for theoretical saturation.
Supporting detail: The PLOS ONE authors cite saturation guidance and propose 4–5 in-depth interviews per group plus two FGDs per group, which is consistent with qualitative sampling approaches referenced in their protocol (PLOS ONE).
Can AI tools bias qualitative interpretation in community studies?
Direct answer: AI tools can introduce bias if used without human oversight, but when paired with participatory validation they can increase rigor and transparency.
Supporting detail: The PLOS ONE protocol emphasises co-analysis with a Community Advisory Committee and reflexive memos; similarly, AI-assisted coding should be validated by human coders and community members to align with CBPR principles (PLOS ONE).
How quickly can teams convert transcripts into co-designable insights?
Direct answer: With structured AI-assisted workflows, teams can move from transcription to initial thematic summaries in days rather than weeks.
Supporting detail: The PLOS ONE study schedules co-design workshops soon after Phase 2 analysis, and platforms that combine transcription, translation, and thematic extraction reduce turnaround time so advisory committees can validate themes in scheduled workshops (PLOS ONE).
Conclusion & Next Steps
The PLOS ONE protocol shows that understanding and addressing gender digital exclusion requires participatory qualitative methods that interrogate household norms as well as device access (PLOS ONE).
Researchers and program teams can adopt AI-enabled qualitative analysis to speed transcription, bilingual translation, and comparative coding while preserving participatory validation steps recommended by the protocol.
If you run FGDs, in-depth interviews, or co-design workshops and want to reduce analysis time while keeping community validation central, Try Evidano for free.
Topics
- gender digital exclusion qualitative analysis
- digital gender gap Pakistan
- AI qualitative research
- co-design digital inclusion
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