Cultural Insight: AI Qualitative Analysis of Leprosy

The November 11, 2026 PLOS Neglected Tropical Diseases study found that leprosy perceptions in French Guiana were shaped by local terminology, spiritual and familial explanations, misconceptions about transmission, stigma, and strong community support.

AI qualitative analysis can help healthcare researchers organize interview transcripts, compare cultural segments, and identify recurring themes, but culturally sensitive interpretation must remain grounded in participants’ language and context.

• According to the study, researchers interviewed 20 patients and 37 community members across 37 interviews between April and September 2025.
• According to the study, the Maroon terms “kokobe” and “gwasi” referred primarily to deformities and skin patches, but neither term mapped exactly to the biomedical category of leprosy.
• According to the study, bacterial causation was rarely mentioned, while spiritual explanations involving taboo transgression or curses were common among Maroon and Haitian participants.
• According to the study, local plant-based remedies were widely used, but the researchers reported that these remedies did not appear to compromise adherence to multidrug therapy.
• According to the study, participants reported both stigma and social support, showing why qualitative analysis must capture contradictory experiences rather than reduce findings to a single sentiment score.

The study found that cultural representations of leprosy influenced how participants named the disease, explained its cause, disclosed their diagnosis, and navigated care.

According to the study, researchers used semi-structured interviews because French Guiana has substantial linguistic and cultural diversity, varied literacy levels, and overlapping biomedical and local explanations of illness. Patient interviews were conducted in French or with language mediation, while community interviews frequently relied on cultural mediation and field notes.

According to the study, researchers combined deductive and inductive thematic analysis. Initial codes followed the interview guide and perception framework, while inductive coding identified culturally specific meanings that emerged from the interviews.

The study reported that only 2 patients and 1 community member referred to bacteria as the cause of leprosy. The study also reported frequent references to food, animals, family lineage, environmental exposure, curses, and inherited taboos.

One community participant described the relationship between visible symptoms and progression by saying, “It starts with spots... If you don't treat it, your fingers can bend.” The study attributed this quotation to a Western French Guiana community member.

The study also documented a communication gap around transmission. One participant said, “I don't think it's a disease that can be transmitted, ” while the study explained that prolonged human-to-human contact through respiratory droplets remains the main scientifically established transmission route.

The study’s findings should be interpreted as a diversity of perspectives rather than generalizable characteristics of every cultural group in French Guiana because the number of participants in each cultural group was limited.

Healthcare and public health researchers should treat cultural language and explanatory models as analytic data because the French Guiana study connected those factors with disclosure, diagnosis, communication, and care pathways.

The study’s use of “kokobe” and “gwasi” illustrates why direct translation is not enough. The study reported that “gwasi” was mainly associated with skin lesions and “kokobe” with deformities or amputations, while also noting that the terms could describe a wider continuum of visible illness.

Researchers should code biomedical beliefs and local beliefs as potentially coexisting rather than mutually exclusive. According to the study, participants could use plant-based remedies or spiritual practices while also trusting and adhering to multidrug therapy.

Researchers should also preserve negative and positive experiences in the same dataset. According to the study, some participants described discrimination, nondisclosure, self-isolation, transport barriers, and interrupted care, while many others described family, religious, or community support.

For health communication teams, the practical priority is to identify which misconceptions require clarification and which local concepts can help establish dialogue. The study concluded that culturally sensitive communication, clearer explanations of person-to-person transmission, and attention to local practices could improve understanding and care.

Medical and public health analysis must remain non-diagnostic and research-focused. AI-generated themes should support, not replace, clinical judgment, community consultation, ethical review, or participant confidentiality.

The French Guiana leprosy study shows that culturally grounded qualitative research can reveal how terminology, spiritual beliefs, stigma, treatment trust, and community support shape health experiences.

AI qualitative analysis can make this kind of work more manageable by organizing multilingual transcripts, surfacing themes, comparing segments, and connecting interpretations to source evidence.

Evidano gives healthcare, public health, and social research teams a focused workspace for analyzing sensitive qualitative data while keeping human interpretation central.

To explore AI-assisted thematic and cross-segment analysis, Try Evidano for free.