Trial reportBMJ evidence-based medicine2024
Interpretation and use of a decision support tool for multiple treatment options: a combined randomised controlled trial and survey of medical students.
Trial report in BMJ evidence-based medicine, 2024. 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.
- Digital health competences and AI beliefs as conditions for the practice of evidence-based medicine: a study of prospective physicians in Canada.Medical education online · 2025Article
- MATCH-IT: A decision support tool for multiple comparisons presenting data from network meta-analysis to facilitate guideline development.Clinical and public health guidelines · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo investigate medical students' ability to interpret evidence, as well as their self-assessed understandability, perceived usefulness and preferences for design alternatives in an interactive decision support tool, displaying GRADE evidence summaries for multiple treatment options (Making Alternative Treatment CHoices Intuitive and Trustworthy, MATCH-IT).
designA combined randomised controlled trial and survey. Participants were presented with a clinical scenario and randomised to one of two versions of the MATCH-IT tool (A/B), instructed to explore the evidence and decide on a recommendation. Participants answered a questionnaire assessing interpretation, treatment recommendation self-assessed understandability and perceived usefulness before exposure to the other MATCH-IT version and asked questions on design preferences.
settingOnline lecture in an evidence-based medicine (EBM) introductory course.
participants149 third-year medical students. 52% (n=77) had 6 months of clinical training and 48% (n=72) had preclinical training only.
interventionsThe MATCH-IT tool version A uses colour coding to categorise interventions by magnitude and direction of effects and displays all outcomes in a table on entry. Version B has no colour coding, and the user must decide which outcomes to display in the table.
main outcome measuresInterpretation of evidence, treatment recommendation, perceived usefulness and understandability, preference for format and design alternatives.
results82.5% (n=123) of medical students correctly answered ≥4 out of 5 multiple choice questions assessing interpretation of data. 75.8% (n=114) of students made a treatment recommendation in accordance with an expert panel for the same clinical scenario. 87.2% (n=130) found the tool understandable while 91.9% perceived the tool as useful in addressing the clinical scenario.
conclusionMedical students with no prior training in EBM can interpret and use the MATCH-IT tool. Certain design alternatives were preferred but had no bearing on interpretation of evidence or understandability of the tool.
Indexed as
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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.