Evidence map›Paper›PMID 36819954›Full record

ArticleCureus2023

ChatGPT Output Regarding Compulsory Vaccination and COVID-19 Vaccine Conspiracy: A Descriptive Study at the Outset of a Paradigm Shift in Online Search for Information.

Malik Sallam, Nesreen A Salim, Ala'a B Al-Tammemi, Muna Barakat, Diaa Fayyad, Souheil Hallit, Harapan Harapan, Rabih Hallit, Azmi Mahafzah

Abstract read
In one paragraph

Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 2 pooled it
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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

52 citing papers in PubMed, 2 syntheses or guidelines 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

9 authors.

Malik SallamDepartment of Pathology, Microbiology and Forensic Medicine, School of Medicine, University of Jordan, Amman, JOR.
Nesreen A SalimDepartment of Prosthodontics, Jordan University Hospital, Amman, JOR.
Ala'a B Al-TammemiInfectious Disease, Applied Science Research Center, Applied Science Private University, Amman, JOR.
Muna BarakatSchool of Pharmacy, Applied Science Private University, Amman, JOR.
Diaa FayyadDepartment of Biological Sciences, Faculty of Science, Yarmouk University, Irbid, JOR.
Souheil HallitFaculty of Medicine and Medical Sciences, Holy Spirit University of Kaslik (USEK), Jounieh, LBN.
Harapan HarapanDepartment of Epidemiology and Public Health, Syiah Kuala University, Banda Aceh, IDN.
Rabih HallitDepartment of Infectious Disease, School of Medicine and Medical Sciences, Holy Spirit University of Kaslik (USEK), Jounieh, LBN.
Azmi MahafzahDepartment of Pathology, Microbiology and Forensic Medicine, School of Medicine, The University of Jordan, Amman, JOR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBeing on the verge of a revolutionary approach to gathering information, ChatGPT (an artificial intelligence (AI)-based language model developed by OpenAI, and capable of producing human-like text) could be the prime motive of a paradigm shift on how humans will acquire information. Despite the concerns related to the use of such a promising tool in relation to the future of the quality of education, this technology will soon be incorporated into web search engines mandating the need to evaluate the output of such a tool. Previous studies showed that dependence on some sources of online information (e.g., social media platforms) was associated with higher rates of vaccination hesitancy. Therefore, the aim of the current study was to describe the output of ChatGPT regarding coronavirus disease 2019 (COVID-19) vaccine conspiracy beliefs. and compulsory vaccination.

methodsThe current descriptive study was conducted on January 14, 2023 using the ChatGPT from OpenAI (OpenAI, L.L.C., San Francisco, CA, USA). The output was evaluated by two authors and the degree of agreement regarding the correctness, clarity, conciseness, and bias was evaluated using Cohen's kappa.

resultsThe ChatGPT responses were dismissive of conspiratorial ideas about severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) origins labeling it as non-credible and lacking scientific evidence. Additionally, ChatGPT responses were totally against COVID-19 vaccine conspiracy statements. Regarding compulsory vaccination, ChatGPT responses were neutral citing the following as advantages of this strategy: protecting public health, maintaining herd immunity, reducing the spread of disease, cost-effectiveness, and legal obligation, and on the other hand, it cited the following as disadvantages of compulsory vaccination: ethical and legal concerns, mistrust and resistance, logistical challenges, and limited resources and knowledge.

conclusionsThe current study showed that ChatGPT could be a source of information to challenge COVID-19 vaccine conspiracies. For compulsory vaccination, ChatGPT resonated with the divided opinion in the scientific community toward such a strategy; nevertheless, it detailed the pros and cons of this approach. As it currently stands, the judicious use of ChatGPT could be utilized as a user-friendly source of COVID-19 vaccine information that could challenge conspiracy ideas with clear, concise, and non-biased content. However, ChatGPT content cannot be used as an alternative to the original reliable sources of vaccine information (e.g., the World Health Organization [WHO] and the Centers for Disease Control and Prevention [CDC]).

Indexed as

artificial intelligence in medicinecovid-19 vaccinemachine learningmandatory vaccinationvaccine promotion

Identifiers

PMID36819954
PMCPMC9931398

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.