Journal of the Medical Library Association Integrating PICO principles into generative artificial intelligence prompt engineering to enhance information retrieval for medical librarians
Type
Publication
Category
AI & Librarianship
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Publication Year
2025
Volume
113
Tags
Series Name
Abstract
Prompt engineering, an emergent discipline at the intersection of Generative Artificial Intelligence (GAI), library science, and user experience design, presents an opportunity to enhance the quality and precision of information retrieval. An innovative approach applies the widely understood PICO framework, traditionally used in evidence-based medicine, to the art of prompt engineering. This approach is illustrated using the “Task, Context, Example, Persona, Format, Tone” (TCEPFT) prompt framework as an example. TCEPFT lends itself to a systematic methodology by incorporating elements of task specificity, contextual relevance, pertinent examples, personalization, formatting, and tonal appropriateness in a prompt design tailored to the desired outcome. Frameworks like TCEPFT offer substantial opportunities for librarians and information professionals to streamline prompt engineering and refine iterative processes. This practice can help information professionals produce consistent and high-quality outputs. Library professionals must embrace a renewed curiosity and develop expertise in prompt engineering to stay ahead in the digital information landscape and maintain their position at the forefront of the sector.
Description
Open Access
Biblio Notes
Robinson, K., Bontekoe, K., & Muellenbach, J. (2025). Integrating PICO principles into generative artificial intelligence prompt engineering to enhance information retrieval for medical librarians. Journal of the Medical Library Association, 113(2), Article 2. https://doi.org/10.5195/jmla.2025.2022
Number of Copies
1
| Library | Accession No | Call No | Copy No | Edition | Location | Availability |
|---|---|---|---|---|---|---|
| Main | 30 | 1 | Yes |