Evidence map›Paper›PMID 41918678›Full record

ArticleCureus2026

Knowledge, Perception, and Willingness to Use Artificial Intelligence for Personalized Health Recommendations Among Undergraduate Health Students: A Cross-Sectional Study.

Munrerah Almulhem, Ameerah Almusailem, Mona Alayesh, Alzahraa Bu Najimah, Hawra Bin Karam, Hala Alsaleem, Haylah Almajhad, Zainab Alessa, Manahil Alfridan

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

9 authors.

Munrerah AlmulhemPublic Health, King Faisal University, Hofuf, SAU.
Ameerah AlmusailemPublic Health, King Faisal University, Hofuf, SAU.
Mona AlayeshPublic Health, King Faisal University, Hofuf, SAU.
Alzahraa Bu NajimahPublic Health, King Faisal University, Hofuf, SAU.
Hawra Bin KaramPublic Health, King Faisal University, Hofuf, SAU.
Hala AlsaleemPublic Health, King Faisal University, Hofuf, SAU.
Haylah AlmajhadPublic Health, King Faisal University, Hofuf, SAU.
Zainab AlessaPublic Health, King Faisal University, Hofuf, SAU.
Manahil AlfridanHealth Informatics, King Faisal University, Hofuf, SAU.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Artificial intelligence (AI) is increasingly integrated into healthcare, with uses including personalized health recommendations. Understanding the knowledge, perceptions, and willingness of future healthcare professionals to engage with AI is essential for supporting its effective adoption. This study examined the knowledge, perception, and willingness to use AI among undergraduate students in the health colleges at King Faisal University. Methods A descriptive cross-sectional study was conducted, including 417 undergraduate students from 5 health colleges. A structured electronic questionnaire was used to assess students' knowledge of AI, their perception of its use in healthcare, and their willingness to use AI-based personalized health recommendations. Associations between variables were evaluated using descriptive statistics and logistic regression analysis. Results Among the 417 participants, 67.87% had a high level of knowledge about AI, 57.07% had a positive perception, and 74.82% reported willingness to use AI for personalized health recommendations. Logistic regression analysis showed that students with high knowledge were more likely to be willing to use AI (adjusted odds ratio (AOR) = 3.647; 95% confidence interval (CI): 2.204-6.036; p < 0.001). A positive perception also significantly predicted willingness (AOR = 5.442; 95% CI: 3.248-9.118; p < 0.001). Age and gender were not significant predictors. Conclusion Undergraduate health science students demonstrated a high level of knowledge, positive perceptions, and a high willingness to use AI for personalized health recommendations. Knowledge and perception were significant factors associated with willingness, emphasizing the importance of integrating AI-related education into health-science curricula to support digital transformation in healthcare.

Indexed as

artificial intelligencehealthcare technologyhealth studentspersonalized healthwillingness to use ai

Identifiers

PMID41918678
PMCPMC13034493

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.