From Stories to Evidence: AI Qualitative Research

According to the 2026 PLOS Neglected Tropical Diseases study, participatory storytelling in Karachi was associated with reduced self-stigma, greater confidence, and stronger individual empowerment among people affected by leprosy, although wider community stigma remained.

• The PLOS study involved 17 total participants, including 16 photovoice participants and 14 in-depth interview participants, with data collected in June 2025.
• The PLOS study found that the strongest reported changes occurred at the individual level, especially movement from shame and concealment toward self-acceptance, openness, and confidence.
• The PLOS study reported that peer groups, creative storytelling, and organisational endorsement strengthened solidarity, belonging, communication skills, and public visibility.
• The PLOS study found that gender norms, visible disability, community misconceptions, travel costs, and economic constraints limited broader social change.
• AI qualitative research can support this type of work by organizing transcripts, translations, photographs descriptions, and survey responses into traceable themes for human review.

The 2026 PLOS study used a qualitative design to understand how a participatory storytelling intervention influenced stigma and empowerment among people affected by leprosy in Pakistan. The intervention began as a one-year pilot in Karachi in 2024 and combined storytelling, photovoice, peer-support activities, health education, advocacy, and contact-based engagement.

The PLOS research team recruited participants purposively between May 30 and June 20, 2025, and collected data during a four-week period in June 2025. Sixteen participants joined photovoice activities, 14 completed in-depth interviews, and 13 took part in both methods. Participants were aged 30 to 65 years.

The PLOS researchers conducted 60 to 90 minute interviews in person, using live Urdu interpretation, audio recording, and field notes. Participants also took photographs over approximately three weeks, selected images, developed captions, and discussed the images in facilitated groups.

The PLOS analysis combined deductive and inductive coding. The preliminary codebook drew on stigma, empowerment, and Social Ecological Model concepts, while additional codes emerged from the data. The researchers used thematic analysis supported by NVivo 14, reviewed a subset of coded transcripts, and triangulated interview and photovoice findings.

The PLOS article cautions that the study measured perceived impact rather than causal effect because it had no baseline or comparison group. The researchers also note that women represented 4 of the 17 participants, which limited the breadth of gender-specific findings.

The PLOS study suggests that storytelling interventions can produce their clearest gains in self-stigma and intrapersonal empowerment before they produce broader community change. Participants described moving toward confidence, self-acceptance, openness, and a stronger sense of purpose.

The PLOS study also shows why qualitative analysis must preserve mechanisms, not only outcomes. Participants connected change to psychological safety, peer support, creative expression, communication practice, public recognition, and institutional endorsement. A frequency count alone would not explain how those elements interacted.

For health researchers, the PLOS findings support combining thematic analysis with cross-segment analysis. Comparing accounts by gender, visible disability, employment, age, and participation in photovoice can show which benefits were shared and which barriers were concentrated in specific groups.

For programme evaluators, the PLOS study highlights the importance of coding limitations alongside positive findings. Episodic community contact, persistent misconceptions, gender restrictions, transport costs, and the absence of a comparison group all affect how confidently researchers should interpret reported change.

For qualitative researchers, AI should function as an analysis aid rather than an automatic author of conclusions. Human researchers should define the research question, assess context and power, validate translations, review quotations, and decide whether a theme is supported by the evidence.

The 2026 PLOS study shows that participatory storytelling can help people affected by leprosy move from shame and concealment toward confidence, openness, and individual empowerment, while broader stigma may persist.

The study also demonstrates why rigorous qualitative analysis must connect participant quotations to mechanisms, segments, intervention components, and limitations. AI-enabled analysis can reduce the manual workload involved in organizing and comparing that evidence, but human researchers must retain interpretive and ethical responsibility.

Teams analyzing interviews, photovoice narratives, open-ended surveys, or health programme documents can use Evidano to structure evidence and investigate themes across segments. Try Evidano for free and turn complex qualitative data into a clearer starting point for research decisions.