Evidence map›Paper›PMID 39703400›Full record

ArticleFrontiers in research metrics and analytics2024

Paradigm shifts: exploring AI's influence on qualitative inquiry and analysis.

Ryan Thomas Williams

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. The online survey in qualitative research: can AI act as a probing tool?Frontiers in research metrics and analytics · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Ryan Thomas WilliamsTeesside University International Business School, TU Online, Teesside University, Middlesbrough, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

artificial intelligenceinterpretivismlanguage processingparadigmsqualitative data analysis

Identifiers

PMID39703400
PMCPMC11656929

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.