Evidence map›Paper›PMID 39107733›Full record

ArticleBMC medical education2024

Competencies required to make use of Information Science and Technology among Japanese medical students: a cross-sectional study.

Yuma Ota, Yoshikazu Asada, Makiko Mieno, Yasushi Matsuyama

Abstract read
In one paragraph

Article in BMC medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Yuma OtaMedical Education Center, Jichi Medical University Graduate School of Medicine, Tochigi, Japan.
Yoshikazu AsadaMedical Education Center, Jichi Medical University, Tochigi, Japan.
Makiko MienoCenter for Information, Jichi Medical University, Tochigi, Japan.
Yasushi MatsuyamaMedical Education Center, Jichi Medical University, Tochigi, Japan. yasushim@jichi.ac.jp.

Funding

Japan Society for the Promotion of Science 20K10384
6 · The paper itself

Abstract

backgroundCompetency in the use of information science and technology (IST) is essential for medical students. This study identified learning objectives and competencies that correspond with low self-assessment related to use of IST and factors that improve such self-assessment among medical students.

methodsA questionnaire was administered to sixth-year medical students across 82 medical schools in Japan between November 2022 and February 2023.

resultsThree learning objectives were identified as difficult for the students to achieve: (1) provide an overview of the regulations, laws, and guidelines related to IST in medicine; (2) discuss ethical issues, such as social disparities caused by the digital divide that may arise in the use of IST in medicine; and (3) understand IST related to medical care. Further, problem-based learning, engaging with IST beyond class, and learning approach impacted the students' acquisition of competencies related to IST. Furthermore, it was recognized that the competencies required by medical students may change over the course of an updated medical school curriculum.

conclusionsIt is important for medical students to recognize the significance of learning, establishing active learning methods, and gaining experience in practically applying these competencies.

Indexed as

Students, MedicalClinical CompetenceCross-Sectional StudiesCurriculumEast Asian PeopleEducation, Medical, UndergraduateFemaleHumansInformation TechnologyJapanMaleSurveys and QuestionnairesCross-sectional studyInformation science and technologyMedical studentsUndergraduate

Identifiers

PMID39107733
PMCPMC11302297

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.