Evidence map›Paper›PMID 42149782›Full record

ArticleJMIR AI2026

Evaluating Medical Students' Perceptions of AI-Assisted Clinical Documentation (CarePilot): Cross-Sectional Study.

Jonathan Bindi, Taylor Jamali, Talia Danze, Iza Zabaneh, Marisa Fat, Joseph Tutera, James Cox

Abstract read
In one paragraph

Article in JMIR AI, 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

7 authors.

Jonathan BindiBurnett School of Medicine at Texas Christian University, 1651 W Rosedale St, Fort Worth, TX, 76104, United States, 1 9258182512.ORCID http://orcid.org/0009-0006-6141-9800
Taylor JamaliBurnett School of Medicine at Texas Christian University, 1651 W Rosedale St, Fort Worth, TX, 76104, United States, 1 9258182512.ORCID http://orcid.org/0009-0001-3107-3881
Talia DanzeBurnett School of Medicine at Texas Christian University, 1651 W Rosedale St, Fort Worth, TX, 76104, United States, 1 9258182512.ORCID http://orcid.org/0009-0000-2523-1647
Iza ZabanehBurnett School of Medicine at Texas Christian University, 1651 W Rosedale St, Fort Worth, TX, 76104, United States, 1 9258182512.ORCID http://orcid.org/0009-0007-1483-3627
Marisa FatBurnett School of Medicine at Texas Christian University, 1651 W Rosedale St, Fort Worth, TX, 76104, United States, 1 9258182512.ORCID http://orcid.org/0009-0007-6597-5158
Joseph TuteraBurnett School of Medicine at Texas Christian University, 1651 W Rosedale St, Fort Worth, TX, 76104, United States, 1 9258182512.ORCID http://orcid.org/0009-0008-0807-4203
James CoxBurnett School of Medicine at Texas Christian University, 1651 W Rosedale St, Fort Worth, TX, 76104, United States, 1 9258182512.ORCID http://orcid.org/0009-0003-6055-9391

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial intelligence (AI) is increasingly being integrated into health care to streamline documentation and improve clinician efficiency. AI-powered documentation tools, such as CarePilot, may reduce administrative burdens and help mitigate burnout. However, their usability and perceived value among medical trainees remain underexplored. Objective: This study aims to evaluate medical students' perceptions of usability, efficiency, and satisfaction when using an AI-powered documentation system in a simulated clinical setting. Methods: This cross-sectional study was conducted at the Burnett School of Medicine at Texas Christian University. A total of 44 third- and fourth-year medical students participated in a standardized patient encounter for a headache. Using CarePilot, participants documented patient history, physical examination findings, clinical reasoning, and management decisions. Afterward, they completed a 27-item Likert scale survey assessing ease of use, documentation efficiency, organization, and overall satisfaction. Results: The majority of respondents rated ease of use, learnability, interface likability, and documentation organization positively (with over 75% of respondents reporting satisfaction for each item). However, a subset reported neutral or dissatisfied opinions regarding overall satisfaction (13/44, 29.5%), citing workflow interruptions and limited functionality that could affect patient interaction. Conclusions: CarePilot was generally perceived as user-friendly and effective for organizing documentation. Nonetheless, areas for refinement, particularly workflow integration and expanded functionalities, may enhance satisfaction and clinical applicability. These findings inform future design and implementation strategies for AI-powered documentation tools in health care education and beyond.

Indexed as

artificial intelligencedocumentationmedical educationsatisfactionworkflow efficiency

Identifiers

PMID42149782
PMCPMC13182772

What OpenQuestion holds

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Registered trials

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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.