Trial reportThe International journal of pharmacy practice2015
A pilot randomised controlled trial to assess the utility of an e-learning package that trains users in adverse drug reaction causality.
Trial report in The International journal of pharmacy practice, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled 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.
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
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Online Digital Education for Postregistration Training of Medical Doctors: Systematic Review by the Digital Health Education Collaboration.Journal of medical Internet research · 2019Pooled it
- Continuous Education of Basic Life Support (BLS) through Social Media; a Quasi-Experimental Study.Archives of academic emergency medicine · 2019Article
- Article
- Article
- Knowledge of professional healthcare providers about sickle cell disease: Impact of a distance education course.Hematology, transfusion and cell therapyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
objectivesCausality assessment of adverse drug reactions (ADRs) by healthcare professionals is often informal which can lead to inconsistencies in practice. The Liverpool Causality Assessment Tool (LCAT) offers a systematic approach. An interactive, web-based, e-learning package, the Liverpool ADR Causality Assessment e-learning Package (LACAeP), was designed to improve causality assessment using the LCAT. This study aimed to (1) get feedback on usability and usefulness on the LACAeP, identify areas for improvement and development, and generate data on effect size to inform a larger scale study; and (2) test the usability and usefulness of the LCAT.
methodsA pilot, single-blind, parallel-group, randomised controlled trial hosted by the University of Liverpool was undertaken. Participants were paediatric medical trainees at specialty training level 1+ within the Mersey and North-West England Deaneries. Participants were randomised (1 : 1) access to the LACAeP or no training. The primary efficacy outcome was score by correct classification, predefined by a multidisciplinary panel of experts. Following participation, feedback on both the LCAT and the LACAeP was obtained, via a built in survey, from participants. KEY
findingsOf 57 randomised, 35 completed the study. Feedback was mainly positive although areas for improvement were identified. Seventy-four per cent of participants found the LCAT easy to use and 78% found the LACAeP training useful. Sixty-one per cent would be unlikely to recommend the training. Scores ranged from 4 to 13 out of 20. The LACAeP increased scores by 1.3, but this was not significant.
conclusionsImproving the LACAeP before testing it in an appropriately powered trial, informed by the differences observed, is required. Rigorous evaluation will enable a quality resource that will be of value in healthcare professional training.
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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.