Evidence map›Paper›PMID 36498065›Full record

ArticleInternational journal of environmental research and public health2022

Beyond the Digital Competencies of Medical Students: Concerns over Integrating Data Science Basics into the Medical Curriculum.

Diana Lungeanu, Alina Petrica, Raluca Lupusoru, Adina Maria Marza, Ovidiu Alexandru Mederle, Bogdan Timar

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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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

6 authors.

Diana LungeanuCenter for Modeling Biological Systems and Data Analysis, "Victor Babes" University of Medicine and Pharmacy, 300041 Timisoara, Romania.ORCID 0000-0002-0274-1377
Alina PetricaDepartment of Surgery, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, 300041 Timisoara, Romania.
Raluca LupusoruCenter for Modeling Biological Systems and Data Analysis, "Victor Babes" University of Medicine and Pharmacy, 300041 Timisoara, Romania.ORCID 0000-0002-7405-4779
Adina Maria MarzaDepartment of Surgery, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, 300041 Timisoara, Romania.ORCID 0000-0001-8978-3168
Ovidiu Alexandru MederleDepartment of Surgery, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, 300041 Timisoara, Romania.ORCID 0000-0002-2242-7764
Bogdan Timar"Pius Brinzeu" Emergency County Clinical Hospital, 300723 Timisoara, Romania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction. Data science is becoming increasingly prominent in the medical profession, in the face of the COVID-19 pandemic, presenting additional challenges and opportunities for medical education. We retrospectively appraised the existing biomedical informatics (BMI) and biostatistics courses taught to students enrolled in a six-year medical program. Methods. An anonymous cross-sectional survey was conducted among 121 students in their fourth year, with regard to the courses they previously attended, in contrast with the ongoing emergency medicine (EM) course during the first semester of the academic year 2020−2021, when all activities went online. The questionnaire included opinion items about courses and self-assessed knowledge, and questions probing into the respondents’ familiarity with the basics of data science. Results. Appreciation of the EM course was high, with a median (IQR) score of 9 (7−10) on a scale from 1 to 10. The overall scores for the BMI and biostatistics were 7 (5−9) and 8 (5−9), respectively. These latter scores were strongly correlated (Spearman correlation coefficient R = 0.869, p < 0.001). We found no correlation between measured and self-assessed knowledge of data science (R = 0.107, p = 0.246), but the latter was fairly and significantly correlated with the perceived usefulness of the courses. Conclusions. The keystone of this different perception of EM versus data science was the courses’ apparent value to the medical profession. The following conclusions could be drawn: (a) objective assessments of residual knowledge of the basics of data science do not necessarily correlate with the students’ subjective appraisal and opinion of the field or courses; (b) medical students need to see the explicit connection between interdisciplinary or complementary courses and the medical profession; and (c) courses on information technology and data science would better suit a distributed approach across the medical curriculum.

Indexed as

COVID-19Students, MedicalCross-Sectional StudiesCurriculumData ScienceHumansPandemicsRetrospective Studiesbiomedical informaticsbiostatisticscontextual learninginformation and communications technologymedical education

Identifiers

PMID36498065
PMCPMC9739359

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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.