Artificial Intelligence Applications to Aid Qualitative Research in Animal-Assisted Therapies With Farm Animals

Artificial intelligence (AI) is increasingly used in qualitative research to support tasks such as coding, thematic identification, and pattern recognition. While AI enhances productivity in processing large volumes of unstructured data, it presents challenges that include limited contextual understanding, algorithmic bias, ethical concerns, and potential privacy issues.

This article aims to explore the integration of AI-assisted tools into qualitative content analysis, focusing on methodological rigor, ethical standards, and how AI tools can effectively support, rather than replace, human insight.

We designed an AI-assisted, thematic content analysis study of an animal-assisted therapy with farm animal's intervention involving domesticated ducks to support individuals with traumatic brain injury. We utilized Insight7, an AI software, chosen for its thematic detection capabilities and robust data security. Human researchers and the AI independently analyzed semistructured exit interview transcripts to allow for comparative validation of findings.

There was general agreement between human and AI-generated themes. However, the AI occasionally misclassified typical participant experiences as challenges, highlighting the tool's limitations in contextual interpretation. Human oversight proved essential in ensuring accurate and nuanced data analysis.

AI offers valuable support in qualitative research, especially in handling large datasets. However, its limitations underscore the importance of human involvement to maintain interpretive accuracy and ethical integrity. Future research should refine AI tools to enhance their contextual sensitivity while preserving the foundational role of human interpretation in qualitative inquiry.