ArticleFrontiers in research metrics and analytics2024
Paradigm shifts: exploring AI's influence on qualitative inquiry and analysis.
Article in Frontiers in research metrics and analytics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Economic insecurity, access to menstrual materials, and sexual coercion: a qualitative study among adolescent schoolgirls in Ibadan, Nigeria.Reproductive health · 2026Article
- Navigating artificial intelligence in qualitative research: ethical and practical considerations from concept to publication.Frontiers in research metrics and analytics · 2026Article
- Using machine-assisted topic analysis to expedite thematic analysis of free-text data: Exemplar investigation of factors influencing health behaviours and wellbeing during the COVID-19 pandemic.British journal of health psychology · 2025Article
- Operator stress factors and cell contamination risks in cell processing facilities: An online survey-based analysis.Regenerative therapy · 2025Article
- The online survey in qualitative research: can AI act as a probing tool?Frontiers in research metrics and analytics · 2025Article
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Abstract
Technology has mostly been embraced in qualitative research as it has not directly conflicted with qualitative methods' paradigmatic underpinnings. However, Artificial Intelligence (AI), and in particular the process of automating the analysis of qualitative research, has the potential to be in conflict with the assumptions of interpretivism. The short article aims to explore how AI technologies, such as Natural Language Processing (NLP), have started to be used to analyze qualitative data. While this can speed up the analysis process, it has also sparked debates within the interpretive paradigm about the validity and ethics of these methods. I argue that research underpinned by the human researcher for contextual understanding and final interpretation should mostly remain with the researcher. AI might overlook the subtleties of human communication. This is because automated programmes with clear rules and formulae do not work well-under interpretivism's assumptions. Nevertheless, AI may be embraced in qualitative research in a partial automation process that enables researchers to conduct rigorous, rapid studies that more easily incorporate the many benefits of qualitative research. It is possible that AI and other technological advancements may lead to new research paradigms that better underpin the contemporary digital researcher. For example, we might see the rise of a "computational" paradigm. While AI promises to enhance efficiency and rigor in data analysis, concerns remain about its alignment with interpretivism.
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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.