Evidence map›Paper›PMID 37578934›Full record

ArticleJMIR medical education2023

Assessing Health Students' Attitudes and Usage of ChatGPT in Jordan: Validation Study.

Malik Sallam, Nesreen A Salim, Muna Barakat, Kholoud Al-Mahzoum, Ala'a B Al-Tammemi, Diana Malaeb, Rabih Hallit, Souheil Hallit

Abstract read
In one paragraph

Article in JMIR medical education, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
69citing 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

69 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  10. Preschool Teachers' Intentions to Use GenAI: Extending UTAUT.Behavioral sciences (Basel, Switzerland) · 2026
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9 more citing papers are in PubMed but not listed here.

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

8 authors.

Malik SallamDepartment of Pathology, Microbiology and Forensic Medicine, School of Medicine, The University of Jordan, Amman, Jordan.ORCID https://orcid.org/0000-0002-0165-9670
Nesreen A SalimProsthodontic Department, School of Dentistry, The University of Jordan, Amman, Jordan.ORCID https://orcid.org/0000-0002-5355-2269
Muna BarakatDepartment of Clinical Pharmacy and Therapeutics, Faculty of Pharmacy, Applied Science Private University, Amman, Jordan.ORCID https://orcid.org/0000-0002-7966-1172
Kholoud Al-MahzoumDepartment of Pathology, Microbiology and Forensic Medicine, School of Medicine, The University of Jordan, Amman, Jordan.ORCID https://orcid.org/0009-0002-0143-7645
Ala'a B Al-TammemiMigration Health Division, International Organization for Migration, The United Nations Migration Agency, Amman, Jordan.ORCID https://orcid.org/0000-0003-0862-0186
Diana MalaebCollege of Pharmacy, Gulf Medical University, Ajman, United Arab Emirates.ORCID https://orcid.org/0000-0002-2436-850X
Rabih HallitSchool of Medicine and Medical Sciences, Holy Spirit University of Kaslik, Jounieh, Lebanon.ORCID https://orcid.org/0000-0003-1817-6146
Souheil HallitSchool of Medicine and Medical Sciences, Holy Spirit University of Kaslik, Jounieh, Lebanon.ORCID https://orcid.org/0000-0001-6918-5689

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChatGPT is a conversational large language model that has the potential to revolutionize knowledge acquisition. However, the impact of this technology on the quality of education is still unknown considering the risks and concerns surrounding ChatGPT use. Therefore, it is necessary to assess the usability and acceptability of this promising tool. As an innovative technology, the intention to use ChatGPT can be studied in the context of the technology acceptance model (TAM).

objectiveThis study aimed to develop and validate a TAM-based survey instrument called TAME-ChatGPT (Technology Acceptance Model Edited to Assess ChatGPT Adoption) that could be employed to examine the successful integration and use of ChatGPT in health care education.

methodsThe survey tool was created based on the TAM framework. It comprised 13 items for participants who heard of ChatGPT but did not use it and 23 items for participants who used ChatGPT. Using a convenient sampling approach, the survey link was circulated electronically among university students between February and March 2023. Exploratory factor analysis (EFA) was used to assess the construct validity of the survey instrument.

resultsThe final sample comprised 458 respondents, the majority among them undergraduate students (n=442, 96.5%). Only 109 (23.8%) respondents had heard of ChatGPT prior to participation and only 55 (11.3%) self-reported ChatGPT use before the study. EFA analysis on the attitude and usage scales showed significant Bartlett tests of sphericity scores (P<.001) and adequate Kaiser-Meyer-Olkin measures (0.823 for the attitude scale and 0.702 for the usage scale), confirming the factorability of the correlation matrices. The EFA showed that 3 constructs explained a cumulative total of 69.3% variance in the attitude scale, and these subscales represented perceived risks, attitude to technology/social influence, and anxiety. For the ChatGPT usage scale, EFA showed that 4 constructs explained a cumulative total of 72% variance in the data and comprised the perceived usefulness, perceived risks, perceived ease of use, and behavior/cognitive factors. All the ChatGPT attitude and usage subscales showed good reliability with Cronbach α values >.78 for all the deduced subscales.

conclusionsThe TAME-ChatGPT demonstrated good reliability, validity, and usefulness in assessing health care students' attitudes toward ChatGPT. The findings highlighted the importance of considering risk perceptions, usefulness, ease of use, attitudes toward technology, and behavioral factors when adopting ChatGPT as a tool in health care education. This information can aid the stakeholders in creating strategies to support the optimal and ethical use of ChatGPT and to identify the potential challenges hindering its successful implementation. Future research is recommended to guide the effective adoption of ChatGPT in health care education.

Indexed as

artificial intelligenceeducationhealthcareKAPknowledgemachine learningopinionpracticessurveytechnology

Identifiers

PMID37578934
PMCPMC10509747

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.