Evidence map›Paper›PMID 31699073›Full record

ArticleBMC medical education2019

OncoSim and OncoWiki: an authentic learning approach to teaching cancer genomics.

Priska Schoenborn, Richard Osborne, Nick Toms, Karen Johnstone, Chlöe Milsom, Reema Muneer, Michael A Jarvis, Robert Belshaw

Open access · goldAbstract read
In one paragraph

Article in BMC medical education, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 25% of its field
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

4 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
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

8 authors at 1 institution in 1 country.

Priska SchoenbornEducational Development, University of Plymouth, Plymouth, UK. p.schoenborn@plymouth.ac.uk.
Richard OsborneCatalysed Ltd, Silverton, UK.
Nick TomsPeninsula Medical School, Faculty of Health: Medicine, Dentistry and Human Sciences, University of Plymouth, Plymouth, UK.
Karen JohnstonePeninsula Medical School, Faculty of Health: Medicine, Dentistry and Human Sciences, University of Plymouth, Plymouth, UK.
Chlöe MilsomPeninsula Medical School, Faculty of Health: Medicine, Dentistry and Human Sciences, University of Plymouth, Plymouth, UK.
Reema MuneerEducational Development, University of Plymouth, Plymouth, UK.
Michael A JarvisSchool of Biomedical Sciences, Faculty of Health: Medicine, Dentistry and Human Sciences, University of Plymouth, Plymouth, UK.
Robert BelshawSchool of Biomedical Sciences, Faculty of Health: Medicine, Dentistry and Human Sciences, University of Plymouth, Plymouth, UK. robert.belshaw@plymouth.ac.uk.ORCID http://orcid.org/0000-0001-6234-3947
University of Plymouth · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPersonalised medicine is rapidly changing the clinical environment, especially in regard to the management of cancer. However, for the large part, methods used to educate undergraduate students as future biomedical scientists and medical doctors have not reflected these changes. In order to make effective use of advances in cancer genomic knowledge, there is a need to expose students to the challenges of genomic medicine and to do so in a manner that makes this complex information accessible.

methodsThe teaching method developed, OncoSim, is a scaffolded 'Personal Research' module option for final year biomedical undergraduate students. It uses an authentic learning approach to teach cancer genomics via simulated cancer patient case studies that have identifiable potential therapeutic targets with associated drug therapies (so-called targeted therapy/precision oncology). In addition, these simulated case studies can be uploaded to a dedicated learning website (OncoWiki) where they can be freely downloaded and used to teach medical students the principles of targeted therapy. A preliminary evaluation of OncoSim was carried out using 3 research tools: (1) online questionnaires; (2) semi-structured interviews; and (3) analysis of whole cohort mark ranges. Thematic analysis was used to code and categorise interview data.

resultsThe teaching materials for OncoSim and the OncoWiki site are freely accessible at https://www.oncowiki.co.uk. Questionnaire data and comparison of whole cohort marks showed OncoSim was at least as effective as alternative choices, and suggested OncoSim provided a valued alternative to traditional laboratory-based projects. No barriers to receptiveness were found. Interview analysis provided 5 broad themes (authentic learning experience; individual challenges; interest in cancer; positive learning experience; supportive structure) supporting the authentic learning aspect of the project, the strong scaffolding provided and the overall effectiveness of the approach.

conclusionsOur preliminary, proof-of-concept, evaluation suggests that OncoSim will be effective in supporting the teaching of genomic medicine to undergraduate students. We plan and hope our study will encourage further formal evaluation in a larger cohort of students, including a control group. The OncoWiki site has the capacity to grow independently as future students create and upload simulated case studies for other students to then download and analyse.

Indexed as

GenomicsLearningEducation, Medical, UndergraduateHumansInterviews as TopicMedical OncologyPrecision MedicineSimulation TrainingStudents, MedicalSurveys and QuestionnairesActive learningAuthentic learningCancerEducationGenomicsOncologyPersonalised medicineSimulationTraining

Identifiers

PMID31699073
PMCPMC6836658
OpenAlexW2986732597

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.