Evidence map›Paper›PMID 39053615›Full record

ArticleApplied clinical informatics2024

Increasing Generative Artificial Intelligence Competency among Students Enrolled in Doctoral Nursing Research Coursework.

Meghan Reading Turchioe, Sergey Kisselev, Liesbet Van Bulck, Suzanne Bakken

Abstract read
In one paragraph

Article in Applied clinical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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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

4 authors.

Meghan Reading TurchioeColumbia University School of Nursing, New York, New York, United States.
Sergey KisselevColumbia University School of Nursing, New York, New York, United States.
Liesbet Van BulckDepartment of Public Health and Primary Care, KU Leuven - University of Leuven, Leuven, Belgium.
Suzanne BakkenColumbia University School of Nursing, New York, New York, United States.

Funding

Data-driven shared decision-making to reduce symptom burden in atrial fibrillationR00NR019124 · NINR · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI TURCHIOE, MEGHAN READING · 2022 to 2024
$732k
NINR NIH HHS grant no.: R00NR019124NINR NIH HHS R00 NR019124
6 · The paper itself

Abstract

backgroundGenerative artificial intelligence (AI) tools may soon be integrated into health care practice and research. Nurses in leadership roles, many of whom are doctorally prepared, will need to determine whether and how to integrate them in a safe and useful way.

objectiveThis study aimed to develop and evaluate a brief intervention to increase PhD nursing students' knowledge of appropriate applications for using generative AI tools in health care.

methodsWe created didactic lectures and laboratory-based activities to introduce generative AI to students enrolled in a nursing PhD data science and visualization course. Students were provided with a subscription to Chat Generative Pretrained Transformer (ChatGPT) 4.0, a general-purpose generative AI tool, for use in and outside the class. During the didactic portion, we described generative AI and its current and potential future applications in health care, including examples of appropriate and inappropriate applications. In the laboratory sessions, students were given three tasks representing different use cases of generative AI in health care practice and research (clinical decision support, patient decision support, and scientific communication) and asked to engage with ChatGPT on each. Students (

resultsStudents were able to identify the strengths and limitations of ChatGPT in completing all three tasks and developed opinions on whether they would feel comfortable using ChatGPT for similar tasks in the future. All of them reported increasing their self-rated competency in generative AI by one to two points on a five-point rating scale.

conclusionThis brief educational intervention supported doctoral nursing students in understanding the appropriate uses of ChatGPT, which may support their ability to appraise and use these tools in their future work.

Indexed as

Artificial IntelligenceEducation, Nursing, GraduateStudents, NursingCurriculumHumansNursing Research

Identifiers

PMID39053615
PMCPMC11483171

What OpenQuestion holds

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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.