Evidence map›Paper›PMID 35223222›Full record

ArticleCureus2022

Differences in Knowledge and Perspectives on the Usage of Artificial Intelligence Among Doctors and Medical Students of a Developing Country: A Cross-Sectional Study.

Rohin Kansal, Ashvind Bawa, Arpit Bansal, Shubam Trehan, Kashish Goyal, Naresh Goyal, Kashish Malhotra

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 2 pooled it
3.9field-weighted citation impact, top 6% of its field
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

49 citing papers in PubMed, 2 syntheses or guidelines pooled it, 64 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

Rohin KansalDepartment of General Surgery, Dayanand Medical College and Hospital, Ludhiana, IND.
Ashvind BawaDepartment of General Surgery, Dayanand Medical College and Hospital, Ludhiana, IND.
Arpit BansalDepartment of Internal Medicine, Narayana Medical College, Nellore, IND.
Shubam TrehanDepartment of Internal Medicine, Dayanand Medical College and Hospital, Ludhiana, IND.
Kashish GoyalDepartment of Internal Medicine, Dayanand Medical College and Hospital, Ludhiana, IND.
Naresh GoyalDepartment of Cardiology, Delhi Heart Institute and Multispeciality Hospital, Bathinda, IND.
Kashish MalhotraDepartment of Internal Medicine, Dayanand Medical College and Hospital, Ludhiana, IND.
Narayana Dental College and Hospital · INMidas Multispeciality Hospital · INDayanand Medical College & Hospital · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Rapid advancements are being made in the field of Artificial Intelligence (AI) to support digital healthcare transformation and provide evidence-based care. The aim of this cross-sectional study was to evaluate the knowledge of basic principles, limitations, and applications of AI in healthcare among medical students and doctors of a developing country. Methods Two free webinars were hosted for doctors and medical students in northern India (Punjab state) to create awareness about the role of AI in healthcare and the recent advancements made in various medical specialties. The delegates' perceptions about their knowledge and interest in AI were ascertained using the Likert scale (1 = low, 5 = high) in the post-event questionnaire. Using Chi-square and cross-tabulation analysis, associations were examined between knowledge of AI, gender, medical experience, and other variables. Results Out of the total of 621 registrants, 367 filled the post-event questionnaire and were included in the analysis. Although the majority felt that AI will play an important role in delivering healthcare services in the future (74.4%), they did not feel knowledgeable about the applications (79.6%) and limitations of AI (82.8%). A relatively lesser proportion of doctors (51.6%) felt interested to learn more about AI than medical students (69.3%). Furthermore, a lesser proportion of doctors (65.2%) felt that AI will be beneficial for their career as a doctor as compared with medical students (84.4%). The majority of medical students (83.5%) had never attended any webinar/lecture or course on AI in healthcare and felt that they have received minimal advice (80.7%) from their medical school on teaching about AI and its applications. A significantly (P = 0.001) higher proportion of female medical students were unknowledgeable about the principles and applications of AI than male respondents. However, female medical students were significantly (P = 0.004) more interested than male medical students to learn about AI. Conclusions Formal training courses to teach about AI should be focused on to facilitate coherent and scientifically supported dissemination of knowledge in medical schools and hospitals. Further large-scale studies are needed to understand the perception and attitude of medical students and doctors regarding AI to steer policy development and medical education curriculum changes to spark an interest in emerging technologies and drive innovation.

Indexed as

aiartificial intelligencegender disparitymedical educationmedical training

Identifiers

PMID35223222
PMCPMC8860704
OpenAlexW4206072520

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.