AI-assisted qualitative analysis: postnatal diabetes SDoH

According to the PLOS One protocol by Phonyiam et al. (2026) (PLOS One), an explanatory sequential mixed-methods study will translate a postnatal well-being scale into Thai, survey 50 postnatal women with type 2 diabetes, and conduct 12 follow-up interviews to triangulate social determinants of health (SDoH) with lived experience.

• 50 survey participants will be recruited, and 12 semi-structured interviews will be nested from that sample, according to Phonyiam et al. (2026).
• The protocol was published on July 29, 2026, and recruitment began in September 2025 with data collection expected to finish by December 2026, per Phonyiam et al. (2026).
• The Thai translation validation reported that “the I-CVI and S-CVI were both 1.0, ” indicating unanimous expert agreement in July 2026, per Phonyiam et al. (2026).

The PLOS One protocol by Phonyiam et al. (2026) answers how to design an explanatory sequential mixed-methods study that links quantitative scores to qualitative narratives.

According to Phonyiam et al. (2026), Phase 1 produced a culturally adapted Thai version of the Postnatal Well-being in Transition scale using a six-stage Beaton translation process and expert validation.

According to Phonyiam et al. (2026), Phase 2 will recruit 50 postnatal women (delivered within the past six weeks) for a survey covering demographics, five SDoH domains, and a 30-item well-being questionnaire, and then select 12 participants for semi-structured phone interviews based on extreme scores.

According to Phonyiam et al. (2026), the study will integrate findings with side-by-side joint displays and a three-step interpretive framework to generate meta-inferences across quantitative and qualitative strands.

Phonyiam et al. (2026) state explicitly that “we expect to complete data collection by December 2026, and the results are projected to be finalized by June 2027, ” and they also report that “the I-CVI and S-CVI were both 1.0, ” both quotes from the protocol (Phonyiam et al., 2026).

Researchers should treat nested sampling as a design lever to connect numeric patterns to rich narratives, as recommended in the PLOS One protocol by Phonyiam et al. (2026).

• Design: Phonyiam et al. (2026) show that embedding 12 interviews inside a 50-person survey provides manageable depth for triangulation without overextending resources.
• Measurement: Phonyiam et al. (2026) demonstrate that forward/back translation and expert review can yield unanimous content validity (I-CVI and S-CVI = 1.0), but they caution that formal psychometric validation remains necessary for cultural equivalence.
• Integration: Phonyiam et al. (2026) recommend statistics-by-themes joint displays and a three-step interpretive framework to classify convergence, expansion, and discordance for trustworthy meta-inferences.

The PLOS One protocol by Phonyiam et al. (2026) provides a clear, reproducible exemplar for explanatory sequential mixed-methods work on SDoH and postnatal wellbeing in type 2 diabetes.

AI-assisted qualitative analysis can accelerate transcription, coding, and joint-display construction while preserving the human interpretation steps the protocol requires, according to Phonyiam et al. (2026).

If you are running a mixed-methods study or planning a nested interview sample, consider tools that combine accurate speech-to-text, secure data handling, and exportable code-to-case matrices.

To experiment with an AI platform built for qualitative research, Try Evidano for free.