Back to search

Article

The quality of data-driven hypotheses generated by inexperienced clinical researchers: A case study

2024-08-13

Abstract excerpt

<h4>Objectives</h4> We invited inexperienced clinical researchers to analyze coded health datasets and develop hypotheses. We recorded and analyzed their hypothesis generation process. All the hypotheses generated in the process were rated by the same group of seven experts by using the same metrics. This case study examines the higher quality (i.e., higher ratings) and lower quality of hypotheses and participants...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
a08ecf39-ebef-582e-ab93-72de02193354
DOI
10.1101/2024.08.12.24311877
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
The quality of data-driven hypotheses generated by inexperienced clinical researchers: A case studyDOI 10.1101/2024.08.12.24311877
How do clinical researchers generate data-driven scientific hypotheses? Cognitive events using think-aloud protocolSemantic proximity
Scientific hypothesis generation process in clinical research: a secondary data analytic tool versus experience study protocolSemantic proximity
Data-driven hypothesis generation among inexperienced clinical researchers: A comparison of secondary data analyses with visualization (VIADS) and other toolsSemantic proximity
Large Language Models for Thematic Analysis in Healthcare Research: A Blinded Mixed-Methods Comparison with Human AnalystsSemantic proximity
Development, validation, and usage of metrics to evaluate the quality of clinical research hypothesesSemantic proximity
Prototyping a Generative AI-powered Person-centered Digital Health Tool to Mitigate Risk of Preventable Adverse Drug EventsSemantic proximity
Systematic post-publication accuracy assessment in medical educational content: development and pilot validation of a five-category taxonomic frameworkSemantic proximity
Development of a Video-based Evidence Synthesis Knowledge Translation Resource: Applying a User-Centred ApproachSemantic proximity
Atomic Fact-Checking Increases Clinician Trust in Large Language Model Recommendations for Oncology Decision Support: A Randomized Controlled TrialSemantic proximity
Clinical Informatics Researcher's Desiderata for the Data Content of the Next Generation Electronic Health Record.Semantic proximity
A double-blind, crossover, non-inferiority randomized controlled trial where primary care providers and patients compare human- and AI-generated digital health messages: the AI-CARE study protocolSemantic proximity
Disagreement as a signal: an auditable dual-LLM and human-arbitrated workflow for methodological quality assessment in preclinical complex-intervention evidenceSemantic proximity
Select a neighboring publication to make it the new centre.