Structured prompt engineering for LLM-assisted inductive thematic analysis

Khalid and Witmer review LLM-assisted inductive thematic analysis and propose a structured four-step prompt-engineering process, with discussion of advanced prompting techniques and research directions. This listing describes the proposal, not a reproduced recipe or validated performance gain.

Workflow level n/a Source Peer-reviewed source Outcome Not empirically evaluated here

Evidence & verification

Source level

Peer-reviewed source
Grounded in a peer-reviewed publication. This describes the source; it does not mean the reported results have been independently reproduced.

Outcome verification

Not empirically evaluated here
A documented resource or intended workflow, not a demonstrated academic outcome. No empirical benefit is established by its inclusion.

Sources checked

2026-10-17 (UTC)

AI editorial review, abstract-only. Institutional record explicitly classifies journal article as peer-review.

Source-checked does not mean independently reproduced. See the Method page for how these labels are assigned.

Sources (1)

Research applicability

Methodological guidance for qualitative researchers seeking a structured, transparent approach to prompting during inductive thematic analysis.

Getting started

Editorial, untested guidance: read the full method before attempting its four steps; the abstract alone is not an executable recipe. Document prompts and retain researcher responsibility for coding decisions.

Maintenance

Article, not a maintained software-service claim.

License

Source reuse rights must be checked separately; no open licence admission requirement.

Workflow & human oversight

Researcher-supervised process; automation level intentionally unspecified. No autonomous research or clinical deployment asserted.

Workflow level is not an evidence score; higher is not better evidence.

Approach

Limitations

Abstract-only review of the author-institution Illinois Experts record; publisher DOI extraction returned HTTP403. The four steps, exact prompts, models, datasets and any quantitative evaluation were not available in the reviewed abstract. Benefits are methodological intentions, not verified outcomes.

Reproducibility

No code, data analysis or model outcomes reproduced in this review.

Adoption requirements

Qualitative-methods expertise, access to the detailed method, an institutionally permitted LLM environment and consent/privacy safeguards for interview data. No code, model subscription or open licence established by this abstract.

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