Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents. According to PLOS One (Taluja et al., 2026), a cognitive interviewing study in rural Uttar Pradesh tested 118 draft survey questions with 101 participants between 01/04/2023 and 27/04/2023 to improve measurement of mobile phone access and use. This post explains the PLOS One findings and shows how AI-enabled qualitative research workflows can speed transcription, translation, coding, and iterative question revision for survey teams.
Key Takeaways
According to PLOS One, cognitive interviewing in rural Uttar Pradesh revealed that many draft survey questions were incomprehensible and required revision before large-scale surveying.
- PLOS One (published July 28, 2026) reports the research team conducted 101 cognitive interviews between 01/04/2023 and 27/04/2023 to test 118 draft questions.
- PLOS One (Taluja et al., 2026) identified seven categories of question problems, including inappropriate terminology and low resonance of digital concepts.
- PLOS One (2026) found that all male respondents and 81% of female respondents in the sample reported owning their own phones, while 84% of men and 56% of women owned smartphones in the study sample.
What happened and how the study worked
Answer: PLOS One (Taluja et al., 2026) ran three rounds of cognitive interviews in rural Uttar Pradesh to test and revise a 118-question instrument for measuring digital access and use.
According to PLOS One, the team selected adults with lower formal education, conducted 101 interviews (n = 44 men, n = 57 women), and revised questions after daily debriefs between 01/04/2023 and 27/04/2023.
According to PLOS One, each draft question was asked exactly as written, followed by qualitative probes, and the researchers iterated through versions 2, 3 and 4 until comprehension improved.
"Please speak in Hindi. What does the question mean? " is a verbatim respondent quote captured by PLOS One (F27) illustrating how formal translations failed to match local speech.
According to PLOS One, interviews averaged 52 minutes and 70 interviews were transcribed and translated to English for systematic coding while 31 were analyzed from debrief notes.
Findings Snapshot
| Date / Source | Metric | Value | Implication |
|---|---|---|---|
| 01/04/2023–27/04/2023, PLOS One (2026) | Cognitive interviews conducted | 101 interviews | Iterative testing revealed pervasive comprehension issues |
| PLOS One (2026) | Draft questions tested | 118 questions | Almost all questions required revision |
| PLOS One (2026) | Sample composition | 44 men, 57 women; ages 18–47; avg age 30 | Gendered patterns in comprehension and phone access informed revisions |
| PLOS One (2026) | Smartphone ownership in sample | 84% men, 56% women | Smartphone-specific questions needed separate testing and explanations |
Implications for survey designers and field researchers
Answer: PLOS One (Taluja et al., 2026) shows cognitive interviewing is essential when adapting digital access measures across languages and sociocultural contexts.
According to PLOS One, seven failure types emerged: (1) inappropriate terminology, (2) overly complex wording, (3) low resonance of digital concepts, (4) confusion about permission/supervision, (5) problematic question structures and response options, (6) self-practice bias, and (7) unclear time frames.
According to PLOS One, simplifying language, using event-anchored time frames (for example 'yesterday' or 'in the last seven days'), and testing explainer boxes referencing local apps improved comprehension.
According to PLOS One, standard Likert scales often confused respondents and binary or three-point response options performed better in this rural Hindi-speaking sample.
How Evidano helps: AI-enabled qualitative workflows for cognitive interviewing
Problem: Slow transcription and inconsistent translations → Solution: Fast, accurate transcripts and custom dictionaries
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 (Taluja et al., 2026), 70 interviews were transcribed and translated for analysis, a process that required careful retention of key Hindi terms; AI-assisted transcription with a custom dictionary can speed this step while preserving local terms.
Use Evidano’s speech-to-text features to auto-transcribe audio, apply a custom Hindi dictionary, and redact PII before human review.
Problem: Manual coding delays iteration → Solution: Rapid thematic and frequency analysis
According to PLOS One, daily debriefs were central to iterating question language; automated thematic and frequency analyses can surface recurring comprehension failures faster.
Use Evidano’s features for thematic coding, co-occurrence networks, and cross-segment comparisons to identify which questions and terms repeatedly fail for women versus men or by education level.
Problem: Revisions need traceability and rapid re-testing → Solution: Integrated workflow for transcripts, translations, and chat-driven synthesis
According to PLOS One, the team iterated three versions of the questionnaire and used debriefs to make immediate edits; Evidano’s document ingestion plus AI chat over analyses lets teams ask targeted questions like “Which items triggered 'please speak in Hindi' between rounds 1 and 2? ”
Evidano preserves audit trails for revisions so field teams can map which phrasing changes led to improved comprehension.
FAQ: cognitive interviewing for digital access
What is cognitive interviewing and why does it matter for digital access surveys?
Answer: Cognitive interviewing is a qualitative method that tests how respondents understand and respond to draft survey questions, and it matters because PLOS One (Taluja et al., 2026) shows unreadable translations and low concept resonance can invalidate survey items.
According to PLOS One, cognitive interviews combine scripted quantitative prompts with qualitative probes to reveal misunderstandings and guide revisions.
How many cognitive interviews are enough?
Answer: Enough to reach thematic saturation; PLOS One (Taluja et al., 2026) used 101 interviews across three rounds for robust iteration.
According to PLOS One, the team reduced sample size per round as questions improved, a practical approach when resources are limited.
Which survey problems are most likely in low-resource digital contexts?
Answer: Inappropriate terminology, low resonance of digital concepts, and unclear time frames are the most common problems, as reported by PLOS One (2026).
According to PLOS One, respondents often used local words like 'touch phone' for smartphones and did not map everyday apps to abstract terms like 'internet' or 'privacy policy'.
Can AI replace human-led cognitive interviews?
Answer: No, AI cannot replace the human interviewer but AI can accelerate transcription, translation, coding, and synthesis so human teams can run more, faster cycles.
According to PLOS One, tailored probing by experienced qualitative researchers was essential to uncovering the seven problem types, a task that still requires human judgment.
Conclusion & Next Steps
According to PLOS One, cognitive interviewing uncovered pervasive comprehension gaps in 118 draft questions and improved measurement of digital access in rural Uttar Pradesh.
According to PLOS One (Taluja et al., 2026), iterative testing, simpler response options, and locally resonant wording drove improvements in question clarity and validity.
If your team needs to scale cognitive interviewing workflows, combine human probing with AI-assisted transcription, translation, and thematic analysis to accelerate iteration and maintain data quality.
Try this approach with an AI-enabled qualitative platform such as Evidano: Try Evidano for free.