Peer-assisted versus expert-assisted learning in virtual chest x-ray interpretation: A randomized controlled trial.

Saudi Med J

From the College of Medicine (Alsulmi, Alqarni, Althaqfi, Bosy, Azher, Sabbagh, Bahakeem, Tashkandi), Umm Al-Qura University, Al-Abdia, Makkah; and from the Department of Meidcal Oncology (Tashkandi), King Abdullah Medical City, Oncology Center, Makkah, Kingdom of Saudi Arabia.

Published: February 2022

Objectives: To compare the effectiveness of peer-assisted learning (PAL) and expert-assisted learning (EAL) in terms of knowledge gain in virtual chest x-ray (CXR) interpretations. The secondary objective was to assess students' satisfaction levels between both groups.

Methods: In this randomized controlled trial, second-year medical students who met the inclusion criteria were randomly assigned to the PAL and EAL groups. The study was carried out from December 2020 to February 2021 at Umm Al-Qura University, Makkah, Saudi Arabia. The primary endpoint was the difference in the students' scores, which were determined by an independent reviewer. The secondary endpoint was students' satisfaction levels.

Results: A total of 166 second year medical students were included. The standard deviation and mean age of the population were 19.73±0.66 (males: 79 [47.6%]; females: 87 [52.4%]). Participants were allocated equally into two groups (83 in each group). Student scores did not differ significantly between the two groups (=0.507). Students in the PAL group thought the session was useful (=0.01), kept on time (=0.043), and the tutor facilitated their learning process (=0.011). They also felt that online teaching was as effective as traditional teaching (=0.03). There was no significant difference in satisfaction scores on the other aspects of the questionnaire.

Conclusion: Peer-assisted learning has equivalent efficacy compared to EAL in a virtual setting. The Students in the PAL group had higher level of satisfaction.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9127908PMC
http://dx.doi.org/10.15537/smj.2022.43.2.20210535DOI Listing

Publication Analysis

Top Keywords

expert-assisted learning
8
virtual chest
8
chest x-ray
8
randomized controlled
8
controlled trial
8
peer-assisted learning
8
students' satisfaction
8
medical students
8
students pal
8
pal group
8

Similar Publications

Integrated procedures for accelerating, deepening, and leading genetic inquiry: A first application on human muscle secretome.

Mol Genet Metab

November 2023

Department of Neuroscience, Imaging and Clinical Sciences, University "G. d'Annunzio" Chieti - Pescara, Chieti, Italy; Interuniversity Institute of Myology (IIM), Perugia, Italy. Electronic address:

Purpose: Beyond classical procedures, bioinformatic-assisted approaches and computational biology offer unprecedented opportunities for scholars. However, these amazing possibilities still need epistemological criticism, as well as standardized procedures. Especially those topics with a huge body of data may benefit from data science (DS)-assisted methods.

View Article and Find Full Text PDF

Chest X-ray (CXR) is a common tool used in medical practice. Medical students and interns should acquire knowledge of CXR interpretation, as it is an essential diagnostic tool for a large spectrum of diseases. This systematic review aimed to compare the effect of different intervention techniques on the competency of medical students and interns to demonstrate the level of confidence and competence in interpreting common presentations of CXRs.

View Article and Find Full Text PDF

Active Learning Methodology for Expert-Assisted Anomaly Detection in Mobile Communications.

Sensors (Basel)

December 2022

Instituto de Telecomunicación (TELMA), Universidad de Málaga, CEI Andalucía TECH E.T.S. Ingeniería de Telecomunicación, Bulevar Louis Pasteur 35, 29010 Málaga, Spain.

Due to the great complexity, heterogeneity, and variety of services, anomaly detection is becoming an increasingly important challenge in the operation of new generations of mobile communications. In many cases, the underlying relationships between the multiplicity of parameters and factors that can cause anomalous behavior are only determined by human expert knowledge. On the other hand, although automatic algorithms have a great capacity to process multiple sources of information, they are not always able to correctly signal such abnormalities.

View Article and Find Full Text PDF

Peer-assisted versus expert-assisted learning in virtual chest x-ray interpretation: A randomized controlled trial.

Saudi Med J

February 2022

From the College of Medicine (Alsulmi, Alqarni, Althaqfi, Bosy, Azher, Sabbagh, Bahakeem, Tashkandi), Umm Al-Qura University, Al-Abdia, Makkah; and from the Department of Meidcal Oncology (Tashkandi), King Abdullah Medical City, Oncology Center, Makkah, Kingdom of Saudi Arabia.

Objectives: To compare the effectiveness of peer-assisted learning (PAL) and expert-assisted learning (EAL) in terms of knowledge gain in virtual chest x-ray (CXR) interpretations. The secondary objective was to assess students' satisfaction levels between both groups.

Methods: In this randomized controlled trial, second-year medical students who met the inclusion criteria were randomly assigned to the PAL and EAL groups.

View Article and Find Full Text PDF

Objective: To determine the effectiveness of peer-assisted learning against expert-assisted learning in terms of scores achieved by medical students, and to assess the perceptions of students about peer-assisted learning.

Methods: The mixed-method study was conducted at Wah Medical College, Wah Cantonment, Pakistan, from October 2017 to December 2018, and comprised fourth year medical students who were randomised into groups A and B. In the first session the topic 'Data' was taught to group A by a peer and to group B by an expert teacher.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!