Evidence map›Paper›PMID 39137029›Full record

ArticleJMIR medical education2024

Understanding Health Care Students' Perceptions, Beliefs, and Attitudes Toward AI-Powered Language Models: Cross-Sectional Study.

Ivan Cherrez-Ojeda, Juan C Gallardo-Bastidas, Karla Robles-Velasco, María F Osorio, Eleonor Maria Velez Leon, Manuel Leon Velastegui, Patrícia Pauletto, F C Aguilar-Díaz, Aldo Squassi, Susana Patricia González Eras and 6 more

Abstract read
In one paragraph

Article in JMIR medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 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

17 citing papers in PubMed, 1 synthesis or guideline 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

16 authors.

Ivan Cherrez-Ojeda *Universidad Espiritu Santo, Samborondon, Ecuador.ORCID 0000-0002-1610-239X
Juan C Gallardo-Bastidas *School of Dentistry, Universidad Católica de Santiago de Guayaquil, Guayaquil, Ecuador.ORCID 0000-0002-5880-9617
Karla Robles-Velasco *Universidad Espiritu Santo, Samborondon, Ecuador.ORCID 0000-0001-7780-1015
María F Osorio *Universidad Espiritu Santo, Samborondon, Ecuador.ORCID 0000-0003-2012-5620
Eleonor Maria Velez Leon *Facultad de Odontología Universidad Católica de Cuenca, Cuenca, Ecuador.ORCID 0000-0001-7002-9990
Manuel Leon Velastegui *Universidad Nacional de Chimborazo, Riobamba, Ecuador.ORCID 0000-0002-6387-9337
Patrícia Pauletto *Universidad de Las Américas (UDLA), Quito, Ecuador.ORCID 0000-0002-1762-7059
F C Aguilar-Díaz *Departamento Salud Pública, Escuela Nacional de Estudios Superiores, Universidad Nacional Autónoma de México, Guanajuato, Mexico.ORCID 0000-0002-6505-5737
Aldo Squassi *Universidad de Buenos Aires, Facultad de Odontologìa, Cátedra de Odontología Preventiva y Comunitaria, Buenos Aires, Argentina.ORCID 0000-0001-7687-5805
Susana Patricia González Eras *Universidad Nacional de Loja, Loja, Ecuador.ORCID 0000-0001-9519-1150
Erita Cordero Carrasco *Departamento de cirugía y traumatología bucal y maxilofacial, Universidad de Chile, Santiago, Chile.ORCID 0000-0002-0378-5291
Karol Leonor Chavez Gonzalez *Universidad Politécnica Salesiana Sede Guayaquil, Guayaquil, Ecuador.ORCID 0000-0002-1386-732X
Juan C Calderon *Universidad Espiritu Santo, Samborondon, Ecuador.ORCID 0000-0003-3889-9309
Jean Bousquet *Institute of Allergology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.ORCID 0000-0002-4061-4766
Anna Bedbrook *MASK-air, Montpellier, France.ORCID 0000-0001-9226-7762
Marco Faytong-Haro *Respiralab Research Group, Guayaquil, Ecuador.ORCID 0000-0002-4238-1767

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChatGPT was not intended for use in health care, but it has potential benefits that depend on end-user understanding and acceptability, which is where health care students become crucial. There is still a limited amount of research in this area.

objectiveThe primary aim of our study was to assess the frequency of ChatGPT use, the perceived level of knowledge, the perceived risks associated with its use, and the ethical issues, as well as attitudes toward the use of ChatGPT in the context of education in the field of health. In addition, we aimed to examine whether there were differences across groups based on demographic variables. The second part of the study aimed to assess the association between the frequency of use, the level of perceived knowledge, the level of risk perception, and the level of perception of ethics as predictive factors for participants' attitudes toward the use of ChatGPT.

methodsA cross-sectional survey was conducted from May to June 2023 encompassing students of medicine, nursing, dentistry, nutrition, and laboratory science across the Americas. The study used descriptive analysis, chi-square tests, and ANOVA to assess statistical significance across different categories. The study used several ordinal logistic regression models to analyze the impact of predictive factors (frequency of use, perception of knowledge, perception of risk, and ethics perception scores) on attitude as the dependent variable. The models were adjusted for gender, institution type, major, and country. Stata was used to conduct all the analyses.

resultsOf 2661 health care students, 42.99% (n=1144) were unaware of ChatGPT. The median score of knowledge was "minimal" (median 2.00, IQR 1.00-3.00). Most respondents (median 2.61, IQR 2.11-3.11) regarded ChatGPT as neither ethical nor unethical. Most participants (median 3.89, IQR 3.44-4.34) "somewhat agreed" that ChatGPT (1) benefits health care settings, (2) provides trustworthy data, (3) is a helpful tool for clinical and educational medical information access, and (4) makes the work easier. In total, 70% (7/10) of people used it for homework. As the perceived knowledge of ChatGPT increased, there was a stronger tendency with regard to having a favorable attitude toward ChatGPT. Higher ethical consideration perception ratings increased the likelihood of considering ChatGPT as a source of trustworthy health care information (odds ratio [OR] 1.620, 95% CI 1.498-1.752), beneficial in medical issues (OR 1.495, 95% CI 1.452-1.539), and useful for medical literature (OR 1.494, 95% CI 1.426-1.564; P<.001 for all results).

conclusionsOver 40% of American health care students (1144/2661, 42.99%) were unaware of ChatGPT despite its extensive use in the health field. Our data revealed the positive attitudes toward ChatGPT and the desire to learn more about it. Medical educators must explore how chatbots may be included in undergraduate health care education programs.

Indexed as

Health Knowledge, Attitudes, PracticeAdultAttitude of Health PersonnelCross-Sectional StudiesFemaleHumansMaleStudents, Health OccupationsStudents, MedicalSurveys and QuestionnairesYoung Adultartificial intelligenceChatGPTeducationhealth carestudents

Identifiers

PMID39137029
PMCPMC11350293

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.