Evidence map›Paper›PMID 38368332›Full record

ArticleBMC medical ethics2024

Evaluating the understanding of the ethical and moral challenges of Big Data and AI among Jordanian medical students, physicians in training, and senior practitioners: a cross-sectional study.

Abdallah Al-Ani, Abdallah Rayyan, Ahmad Maswadeh, Hala Sultan, Ahmed Alhammouri, Hadeel Asfour, Tariq Alrawajih, Sarah Al Sharie, Fahed Al Karmi, Ahmed Mahmoud Al-Azzam and 2 more

Erratum issuedAbstract read
In one paragraph

Article in BMC medical ethics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Abdallah Al-AniOffice of Scientific Affairs and Research, King Hussein Cancer Center, Amman, Jordan.
Abdallah RayyanOffice of Scientific Affairs and Research, King Hussein Cancer Center, Amman, Jordan.
Ahmad MaswadehOffice of Scientific Affairs and Research, King Hussein Cancer Center, Amman, Jordan.
Hala SultanOffice of Scientific Affairs and Research, King Hussein Cancer Center, Amman, Jordan.
Ahmed AlhammouriFaculty of Medicine, University of Jordan, Amman, Jordan.
Hadeel AsfourOffice of Scientific Affairs and Research, King Hussein Cancer Center, Amman, Jordan.
Tariq AlrawajihOffice of Scientific Affairs and Research, King Hussein Cancer Center, Amman, Jordan.
Sarah Al SharieFaculty of Medicine, Yarmouk University, Irbid, Jordan.
Fahed Al KarmiFaculty of Medicine, University of Jordan, Amman, Jordan.
Ahmed Mahmoud Al-AzzamOffice of Scientific Affairs and Research, King Hussein Cancer Center, Amman, Jordan.
Asem MansourOffice of Director General, King Hussein Cancer Center, Amman, Jordan.
Maysa Al-HussainiDepartment of Pathology and Laboratory Medicine, King Hussein Cancer Center, 202 Queen Rania Street, Amman, 11941, Jordan. mhussaini@khcc.jo.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsTo examine the understanding of the ethical dilemmas associated with Big Data and artificial intelligence (AI) among Jordanian medical students, physicians in training, and senior practitioners.

methodsWe implemented a literature-validated questionnaire to examine the knowledge, attitudes, and practices of the target population during the period between April and August 2023. Themes of ethical debate included privacy breaches, consent, ownership, augmented biases, epistemology, and accountability. Participants' responses were showcased using descriptive statistics and compared between groups using t-test or ANOVA.

resultsWe included 466 participants. The greater majority of respondents were interns and residents (50.2%), followed by medical students (38.0%). Most participants were affiliated with university institutions (62.4%). In terms of privacy, participants acknowledged that Big Data and AI were susceptible to privacy breaches (39.3%); however, 59.0% found such breaches justifiable under certain conditions. For ethical debacles involving informed consent, 41.6% and 44.6% were aware that obtaining informed consent posed an ethical limitation in Big Data and AI applications and denounced the concept of "broad consent", respectively. In terms of ownership, 49.6% acknowledged that data cannot be owned yet accepted that institutions could hold a quasi-control of such data (59.0%). Less than 50% of participants were aware of Big Data and AI's abilities to augment or create new biases in healthcare. Furthermore, participants agreed that researchers, institutions, and legislative bodies were responsible for ensuring the ethical implementation of Big Data and AI. Finally, while demonstrating limited experience with using such technology, participants generally had positive views of the role of Big Data and AI in complementing healthcare.

conclusionJordanian medical students, physicians in training and senior practitioners have limited awareness of the ethical risks associated with Big Data and AI. Institutions are responsible for raising awareness, especially with the upsurge of such technology.

Indexed as

PhysiciansStudents, MedicalArtificial IntelligenceBig DataCross-Sectional StudiesHumansJordanMoralsAccountabilityArtificial intelligenceBiasBig dataEpistemologyEthicsJordanMedical studentsOwnershipPrivacy

Identifiers

PMID38368332
PMCPMC10873950

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.