ArticleFrontiers in research metrics and analytics2026
Navigating artificial intelligence in qualitative research: ethical and practical considerations from concept to publication.
Article in Frontiers in research metrics and analytics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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2 authors.
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Abstract
The qualitative research field is evolving as artificial intelligence (AI) and its applications gain broader attention. While these new technologies may be of help to some aspects of the qualitative research process, they also pose several challenges that must be reflected upon, addressed, and documented. Some of the techniques offered by AI for qualitative analysis have existed for a long time, but hallucinated outputs and the more nuanced predictive abilities that may violate privacy and ethical aspects are of major concern. As this is an emerging field, there is a need for a synthesis of recommendations on AI use for qualitative work to reduce risks to rigor and reproducibility. In this paper, we identify key ethical and practical concerns and provide recommendations across five key stages of the qualitative research process so researchers and stakeholders can safely leverage AI to complement their human expertise.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.