Digital gender exclusion is the persistent gap between men’s and women’s access to and use of digital technologies; this post explains how researchers can apply AI-enabled qualitative analysis to study and design interventions for that gap. The primary keyword for this piece is digital gender exclusion qualitative analysis, aimed at qualitative researchers, program designers, and policy teams working on inclusion in low-resource settings. The evidence we analyze comes from a PLOS One study protocol published on August 20, 2026, which lays out a community-based participatory research (CBPR) design in Azam Basti, Karachi, Pakistan and specifies sample sizes, timelines, and co-design methods. The payoff is practical: concrete steps for faster transcription, reliable bilingual translation, thematic coding at scale, and cross-segment comparisons that preserve community voice while producing policy-ready evidence.
Key Takeaways
According to the PLOS One study protocol, engaging family gatekeepers and community leaders is central to understanding why marginalized women in Azam Basti, Pakistan, remain offline and to co-design workable solutions (PLOS One).
- The PLOS One protocol was published on August 20, 2026 and reports a two-year project scheduled to begin in February 2026, with participant recruitment planned for August–November 2026.
- According to the Global System for Mobile Communications Association’s Mobile Gender Gap Report 2024, women in Pakistan were 38% less likely than men to own a mobile phone or access mobile internet in 2024, a statistic cited by the PLOS One authors.
- The PLOS One protocol plans for approximately 36–45 participants across FGDs and interviews, and the project received a SSHRC Insight Development Grant of $70, 626.00.
What happened: the PLOS One protocol and methods
Answer: The PLOS One paper is a study protocol that describes a CBPR qualitative project in Azam Basti to investigate sociocultural drivers of women’s digital exclusion and to co-design interventions, as detailed in the publication (PLOS One).
The PLOS One protocol states the project follows Technofeminism and community-based participatory research principles, and it is organized in three phases: formation of a Community Advisory Committee, focus group discussions and in-depth interviews using photo-elicitation and role-play, and co-design workshops to generate community-informed solutions, according to PLOS One.
The PLOS One protocol specifies that FGDs and interviews will be conducted in Urdu (or Sindhi where required) and transcribed and translated by bilingual researchers, with reflexive thematic analysis and NVivo-assisted coding, according to PLOS One.
The PLOS One protocol explicitly identifies sociocultural barriers as central, quoting the study team that the problem includes “deeply entrenched sociocultural barriers, ” and it references the United Nations definition of digital inclusion as “equitable, meaningful, and safe access to use, lead, and design of digital technologies, services, and associated opportunities for everyone, everywhere, ” as reported in PLOS One.
Findings snapshot
| Date / Source | Metric | Value / Detail | Implication |
|---|---|---|---|
| August 20, 2026 / PLOS One | Project timeline | Two-year study beginning February 2026; data collection Feb 2026–Apr 2027 | Results expected late 2027 to inform policy and community materials |
| 2024 / GSMA (cited in PLOS One) | Mobile ownership gap | Women in Pakistan 38% less likely than men to own a mobile or access mobile internet in 2024 | Interventions must address social constraints beyond device distribution |
| 2024 / World Economic Forum (cited in PLOS One) | Global Gender Gap Index | Pakistan ranked 145th out of 146 countries in 2024 | Context shows structural gender inequality influencing digital access |
| Project grant report / PLOS One | Funding | SSHRC Insight Development Grant $70, 626.00 (2025 competition) | Fund supports CBPR activities, compensations, and analysis |
| PLOS One protocol | Sample size planned | Approximately 36–45 participants across FGDs and interviews | Qualitative depth with theoretical saturation, not population estimates |
Implications for qualitative researchers
Answer: The PLOS One protocol shows that rigorous qualitative work on digital gender exclusion requires participatory methods, bilingual transcription and translation, and careful ethical procedures, according to PLOS One.
The PLOS One protocol models three practical design choices researchers can replicate: using a Community Advisory Committee to co-lead recruitment and guide materials; pairing photo-elicitation and role-play to surface norms; and planning co-design workshops to move from findings to locally owned solutions, as described in PLOS One.
The PLOS One protocol indicates researchers should plan for 90–120 minute co-design workshops with 8–10 participants each, provide compensation (the protocol specifies PKR 4500 or about 16 USD for CAC sessions) and build time for translation, transcription, and reflexive thematic analysis, according to PLOS One.
Ethics note: The PLOS One protocol obtained ethics approvals from Western University, Aga Khan University, and Pakistan’s National Bioethics Committee, and the protocol emphasizes informed consent procedures in local languages, as described in PLOS One.
How Evidano helps: mapping qualitative research needs to AI features
Problem: Slow transcription and translation in bilingual fieldwork → Solution
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
The PLOS One protocol requires Urdu and Sindhi transcription plus English translation for reflexive thematic analysis, and Evidano’s transcription and translation features reduce turnaround by producing accurate automated transcripts, supporting custom dictionaries for local terms, and preserving PII with redaction options (Evidano speech-to-text).
Problem: Managing multi-modal data from photo-elicitation and role-play → Solution
The PLOS One protocol collects visual anchors and role-play transcripts that need tagging and cross-comparison, and Evidano supports ingesting documents and images and performing thematic and co-occurrence analyses to link visual cues to coded themes (Evidano features).
Evidano’s ability to produce hierarchical codes and cross-segment frequency tables helps teams move from 36–45 qualitative cases, as planned in the PLOS One protocol, to policy-ready summaries that compare marginalized women, male gatekeepers, and community leader perspectives.
Problem: Co-design and community validation require fast turnarounds → Solution
The PLOS One protocol schedules iterative CAC reviews and workshops across 2026–2027; Evidano’s AI chat over your documents can generate draft policy briefs and stakeholder reports from coded data in hours rather than weeks, enabling rapid rounds of community validation (Evidano features).
Evidano encrypts data and does not share user data to third-party model training, which supports ethical commitments the PLOS One team emphasizes when handling sensitive community transcripts (Evidano data-security).
FAQ: digital gender exclusion qualitative analysis
How many participants does the PLOS One protocol plan to include and why?
Answer: The PLOS One protocol plans approximately 36–45 participants across FGDs and interviews to reach theoretical saturation, as stated in PLOS One.
The PLOS One protocol explains the final number will depend on saturation and includes two FGDs per participant group (4–5 participants per FGD) plus 4–5 in-depth interviews per group to capture sensitive perspectives.
What methods will the PLOS One team use to surface sociocultural norms?
Answer: The PLOS One protocol uses photo-elicitation for marginalized women and role-play for family gatekeepers and community leaders to surface norms, according to PLOS One.
The PLOS One protocol describes a three-step photo ladder (describe, relate, interpret) and structured role-play scenarios about household decision-making and emergencies to elicit norms and power dynamics.
Can AI tools safely handle bilingual transcripts from Pakistan?
Answer: Yes, AI tools can assist but require human-in-the-loop review for accuracy and cultural nuance, and the PLOS One protocol relies on bilingual researchers for final translations, according to PLOS One.
The PLOS One protocol specifies translation by bilingual researchers; combining AI transcription and human verification accelerates workflows while preserving fidelity to local phrasing and culturally loaded terms.
When will the PLOS One study report results?
Answer: The PLOS One protocol expects results to be available beginning in late 2027, after data collection and analysis are complete, as reported in PLOS One.
The PLOS One protocol outlines a February 2026 project start, participant recruitment August–November 2026, data collection completed by April 2027, and analysis through January 2028.
Conclusion & Next Steps
The PLOS One protocol published on August 20, 2026 demonstrates how CBPR, photo-elicitation, and role-play can reveal the sociocultural drivers of women’s digital exclusion and then co-design contextually appropriate interventions, according to PLOS One.
AI-enabled qualitative analysis accelerates the labor-intensive steps the PLOS One team describes: transcription, bilingual translation, thematic coding, and cross-segment comparisons while keeping community voice central.
Researchers and program teams planning similar studies can pilot AI-assisted workflows during Phase 1 preparation to shorten turnaround and increase transparency when working with advisory committees and co-design groups.
To explore how Evidano can support your next digital inclusion study, Try Evidano for free.
Topics
- digital gender exclusion qualitative analysis
- gender digital divide Pakistan
- AI qualitative research tools
- qualitative analysis tools
- co-design workshops digital inclusion
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- Commentary on NewsCo-designing Digital Gender Inclusion: Qualitative Research MethodsHow to use qualitative methods to study digital gender inclusion: methods from a PLOS One protocol, key stats, and AI-enabled analysis workflows for researchers.
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