ArticleBMJ open2022
Effectiveness of a web-based virtual journal club to promote medical education (Web-Ed): protocol of a multicentre pragmatic randomised trial.
Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed, 5 citations in OpenAlex.
- A Journal Club Format That Combines Literature Reading and Clinical Cases Is More Conducive to Improving Senior Undergraduate Medical Students' Overall Competence.Advances in medical education and practice · 2025Article
- Impact of implementing virtual journal club on developing competencies for critical appraisal among post-graduate nursing students.BMC nursing · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 13 institutions in 1 country.
Funding
Abstract
introductionA journal club (JC) is a commonly used medical educational tool. Videoconferencing technology can facilitate the delivery of JCs, however, there remains no evidence on the role of web-based virtual JCs in promoting the acquisition and retention of medical knowledge. The Web-Ed trial aims to evaluate the educational benefits, feasibility and acceptability of web-based virtual JCs compared with traditional face-to-face ones. METHODS AND ANALYSIS: Web-Ed is a multicentre pragmatic parallel-group randomised trial across teaching hospitals within the UK National Health Service (NHS). We will enrol qualified doctors or medical students who are >18 years old, proficient in English and able to use online videoconferencing software. Block randomisation will be used to allocate participants in 1:1 ratio to either intervention group. Both groups will be presented with the same educational material and follow a standardised JC structure hosted by nominated moderators and medical faculty members.The primary outcome is the difference in participants' knowledge acquisition and retention 7 days after the JCs evaluated using standardised multiple-choice questions. We will report secondarily on the feasibility and acceptability of the JCs using Likert scale questionnaires. Assuming a 30% drop-out rate, we aim to enrol 75 participants to detect a 20% improvement in knowledge acquisition at 80% power and 5% significance. We will report using mean difference or risk ratio with 95% CIs and assess significance using parametric/non-parametric testing. Where relevant, we will adjust for predetermined characteristics (age, grade of training and session duration) using multivariate regression analyses. ETHICS AND DISSEMINATION: Web-Ed was designed by doctors in training to address their learning needs and evaluate the preferred mode of learning. The trial results will be published in peer-reviewed journals and presented at relevant scientific conferences. The trial has been approved by the NHS Health Regulation Authority (21/HRA/3361). TRIAL REGISTRATION NUMBER: ISRCTN18036769.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.