digital gender inclusion qualitative research is tested in a new PLOS ONE study protocol that uses community-based participatory research to co-design solutions with marginalized women, family gatekeepers, and community leaders. Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. According to Shahil-Feroz et al. in PLOS ONE (2026), the project will run from February 2026 with participant recruitment beginning in August 2026, making it a useful blueprint for researchers planning participatory qualitative work in constrained settings. According to Shahil-Feroz et al. in PLOS ONE (2026), the study will use photo-elicitation, role-play, 4–5 in-depth interviews per group, and 2 focus groups per participant group to reach an overall sample of approximately 36–45 participants, providing clear, actionable methods and timelines for teams designing similar projects.
Key Takeaways
According to PLOS ONE, this 2026 study protocol tests a three‑phase participatory qualitative design to identify sociocultural barriers and co-design community-led strategies for digital gender inclusion in Azam Basti, Karachi.
- Phase structure: Shahil-Feroz et al. (PLOS ONE, 2026) outline three phases: (1) a Community Advisory Committee, (2) FGDs and in-depth interviews, and (3) co-design workshops, with data analysed by reflexive thematic analysis.
- Sample and timeline: Shahil-Feroz et al. (PLOS ONE, 2026) plan approximately 36–45 participants, project start February 2026, recruitment August–November 2026, and data collection completed by April 2027.
- Contextual stats: Shahil-Feroz et al. (PLOS ONE, 2026) cite the GSMA Mobile Gender Gap Report 2024 showing women in Pakistan are 38% less likely than men to own a mobile phone or access mobile internet and the World Economic Forum Global Gender Gap 2024 ranking Pakistan 145th of 146 countries.
- Analytic focus: Shahil-Feroz et al. (PLOS ONE, 2026) will use Braun and Clarke’s reflexive thematic analysis with NVivo and co-analysis with the advisory committee to surface sociocultural norms described as "deeply entrenched sociocultural barriers."
What the PLOS ONE protocol does and how it works
Answer: Shahil-Feroz et al. (PLOS ONE, 2026) propose a community-based participatory research (CBPR) study that combines photo-elicitation, role-play, focus group discussions, in-depth interviews, and co-design workshops to investigate and address gendered digital exclusion.
According to Shahil-Feroz et al. in PLOS ONE (2026), the study site is Azam Basti, Karachi, and the research is grounded in Judy Wajcman’s Technofeminism framework to examine how gender and technology shape each other.
According to Shahil-Feroz et al. in PLOS ONE (2026), Phase 1 forms a Community Advisory Committee (CAC) that meets quarterly and includes two community leaders, two marginalized women, and three family gatekeepers; Phase 2 conducts two FGDs per participant group and 4–5 in-depth interviews per group; Phase 3 holds 3 co-design workshops with 8–10 participants each.
According to Shahil-Feroz et al. in PLOS ONE (2026), data will be collected in Urdu, transcribed, translated to English, coded independently by two researchers, and analysed using reflexive thematic analysis with NVivo, with the CAC reviewing themes for cultural validity.
Findings Snapshot
| Date | Metric (source) | Value | Implication |
|---|---|---|---|
| August 20, 2026 | PLOS ONE study protocol publication | Study protocol published online | Provides a replicable CBPR qualitative design for digital gender inclusion |
| 2024 | GSMA Mobile Gender Gap (cited in PLOS ONE) | Women in Pakistan 38% less likely than men to own mobile/access mobile internet | Indicates a large access gap to target in interventions |
| 2024 | Global Gender Gap Index (cited in PLOS ONE) | Pakistan ranked 145/146 | Signals structural gender inequality context for digital inclusion work |
| Feb 2026–Jan 2028 | Project timeline (PLOS ONE, 2026) | Two-year project; recruitment Aug–Nov 2026; data collection complete Apr 2027 | Offers a practical schedule for planning fieldwork and analysis |
| Phase 2 | Planned sample (PLOS ONE, 2026) | Approximately 36–45 participants across groups | Enables focused, saturation-oriented qualitative analysis |
Implications for qualitative researchers and program designers
Answer: Shahil-Feroz et al. (PLOS ONE, 2026) show that studying digital gender inclusion requires methods that surface household power relations as well as women's experiences.
According to Shahil-Feroz et al. in PLOS ONE (2026), including family gatekeepers and community leaders is essential because household decision-making and community norms strongly shape women’s access to devices.
According to Shahil-Feroz et al. in PLOS ONE (2026), participatory methods such as photo-elicitation and role-play reveal tacit norms: the authors note that men may control access out of concerns that internet use brings shame, and that older women can also enforce restrictions.
According to Shahil-Feroz et al. in PLOS ONE (2026), co-design workshops that iterate on Phase 2 findings can produce culturally appropriate interventions, but the authors caution that changing "deeply entrenched sociocultural barriers" requires sustained engagement beyond a single study.
How Evidano helps: AI-enabled qualitative workflows for digital gender inclusion studies
Problem: multi-modal field data and slow synthesis → Solution: thematic + cross-segment analysis
Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.
Feature mapping: For multi-modal data like the PLOS ONE protocol’s photo-elicitation, role-play transcripts, and FGDs, Evidano ingests transcripts and images, auto-transcribes audio with custom dictionaries, and produces reflexive thematic outputs that can be cross-segmented by participant type; see Evidano features for capabilities.
Method note: According to Shahil-Feroz et al. in PLOS ONE (2026), co-analysis with a community advisory committee strengthens validity; Evidano supports collaborative codebooks and exportable audit trails to document reflexive analytic decisions.
Problem: transcription, translation and PII risk → Solution: secure speech-to-text and translation
According to Shahil-Feroz et al. in PLOS ONE (2026), the study will transcribe Urdu audio and translate to English for analysis; Evidano’s speech-to-text and translation features support bilingual workflows with custom dictionaries and PII redaction.
Operational benefit: Using Evidano to transcribe, translate, and anonymize reduces manual workload so researchers can focus on reflexive coding and community validation as outlined in the PLOS ONE protocol.
Problem: demonstrating impact to policymakers → Solution: reproducible visuals and exportable policy briefs
According to Shahil-Feroz et al. in PLOS ONE (2026), the project will produce policy briefs for agencies like the Pakistan Telecommunication Authority; Evidano exports frequency tables, co-occurrence networks, and hierarchical code maps to support evidence-based recommendations.
Collaboration: Evidano preserves encrypted project data and provides collaborative review features appropriate for co-analysis with advisory committees, aligning with the participatory validation steps described by Shahil-Feroz et al. (PLOS ONE, 2026).
FAQ: digital gender inclusion qualitative research
What qualitative methods does the PLOS ONE protocol use to study digital gender inclusion?
Answer: Shahil-Feroz et al. (PLOS ONE, 2026) use photo-elicitation, role-play, focus group discussions, in-depth interviews, and co-design workshops.
Supporting detail: According to Shahil-Feroz et al. in PLOS ONE (2026), photo-elicitation uses 5–6 curated images reviewed by the Community Advisory Committee, and role-play scenarios include family decision-making about phone access and household emergencies.
How large is the planned sample and how is saturation addressed?
Answer: The protocol plans approximately 36–45 participants and will stop based on theoretical saturation as described by Shahil-Feroz et al. (PLOS ONE, 2026).
Supporting detail: According to Shahil-Feroz et al. in PLOS ONE (2026), two FGDs per group with 4–5 participants each and 4–5 individual interviews per group provide depth while allowing comparative analysis across marginalized women, family gatekeepers, and community leaders.
When will study results be available?
Answer: Shahil-Feroz et al. (PLOS ONE, 2026) expect results beginning in late 2027 after analysis and dissemination activities.
Supporting detail: According to Shahil-Feroz et al. in PLOS ONE (2026), the two-year project begins February 2026, with recruitment August–November 2026 and data collection completed by April 2027.
Can AI tools like Evidano be used to analyse participatory qualitative data ethically?
Answer: Yes, AI tools can accelerate transcription, coding, and visualization when used with community validation and secure data practices.
Supporting detail: According to Shahil-Feroz et al. in PLOS ONE (2026), co-analysis with advisory committees is essential; Evidano supports encrypted data, PII redaction, and collaborative codebooks so AI-assisted outputs can be reviewed and validated by community partners.
Conclusion & Next Steps
The PLOS ONE study protocol by Shahil-Feroz et al. (2026) provides a clear, replicable CBPR design for addressing digital gender exclusion through participatory methods, co-design, and reflexive thematic analysis.
According to Shahil-Feroz et al. in PLOS ONE (2026), tackling the 38% mobile access gap cited from GSMA 2024 and the wider structural gender context requires household and community engagement rather than awareness campaigns alone, a shift the authors describe as an effort that "moves beyond awareness-based approaches."
If you run qualitative research on digital inclusion, use AI tools to speed transcription, translation, and thematic synthesis while preserving community co‑analysis; see Evidano features for relevant workflows.
Next step: pilot the analytic pipeline on a small set of translated transcripts and visual prompts, then scale to full co-analysis with advisory committees.
Ready to accelerate your qualitative analysis? Try Evidano for free.
Topics
- digital gender inclusion qualitative research
- gender digital inclusion Pakistan
- qualitative analysis digital inclusion
- AI qualitative research tools
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