Evidence map›Paper›PMID 42819609›Full record

ArticleCureus2026

The Verification Gap: Artificial Intelligence Adoption, Hallucination Awareness, and Verification Practices Among Medical Trainees and Professionals in Pakistan.

Mobeen Sajjad, Sammeullah Mirza, Ahsan Sajjad, Rida Amer

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Mobeen SajjadDepartment of Medicine, Saad Hospital and Cardiac Care Center, Daska, PAK.
Sammeullah MirzaDepartment of Medicine, Saad Hospital and Cardiac Care Center, Daska, PAK.
Ahsan SajjadDepartment of Medicine, Ibn Sina Wilcrest Community Medical Clinic, Houston, USA.
Rida AmerDepartment of Internal Medicine, Prolato Clinical Research Center, Houston, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Artificial intelligence (AI) tools have been rapidly adopted by medical researchers, yet whether medical trainees and professionals in low- and middle-income countries possess the awareness and habits needed to use these tools safely remains poorly documented. This study characterized AI adoption, hallucination awareness, and verification and disclosure practices among medical trainees and professionals in Pakistan. Methods A cross-sectional anonymous online survey was conducted among medical students, house officers, residents, physicians, and faculty involved in research or academic work across Pakistan (May 2026). Descriptive statistics and chi-square tests were applied to 373 eligible responses. Results AI use was near-universal (99.7%), with 60.3% using AI daily. The most commonly reported tool was Claude (Anthropic, San Francisco, CA) (40.5%), followed by ChatGPT (OpenAI, San Francisco, CA) (29.2%), and Perplexity (Perplexity AI, Inc., San Francisco, CA) (26.0%), though this ranking likely reflects sampling characteristics. Despite high adoption, 59.2% (95% CI: 54.2-64.1%) typically did not verify AI outputs before use, and 40.2% had never heard that AI can generate fabricated references. In behavioral vignettes, 36.5% assumed convincing AI-generated references were authentic, and 54.2% would continue using remaining AI content after discovering one fabricated reference. Formal research training was strongly associated with consistent disclosure (51.7% vs. 17.1%; χ²(1) = 48.43, p < 0.001, Cramer's V = 0.36). Role was significantly associated with both verification behavior (χ²(4) = 17.22, p = 0.0018, Cramer's V = 0.22) and hallucination awareness (χ²(4) = 13.44, p = 0.0093, Cramer's V = 0.19), with non-verification highest among medical students and unawareness highest among physicians. Daily use frequency, research training, and publication count showed no other significant associations. Conclusions Medical trainees and professionals in Pakistan demonstrate high AI adoption alongside incomplete hallucination awareness and infrequent verification - a pattern that may carry implications for research integrity. Formal training was the only factor significantly associated with consistent disclosure. Integration of AI literacy into medical curricula and institutional governance frameworks merits consideration.

Indexed as

ai literacyartificial intelligencehallucinationlarge language modelslmicmedical researchpakistanresearch integrityverification

Identifiers

PMID42819609
PMCPMC13626389

What Socratic holds

Textmetadata
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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 Socratic graph.