Evidence map›Paper›PMID 39472857›Full record

ArticleBMC medical education2024

'What is the most important lesson you learnt as a neuroscience master's student?' A single-question study in postgraduate neuroscience education.

Stefano Sandrone

Abstract read
In one paragraph

Article in BMC medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

1 author.

Stefano SandroneDepartment of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK. sandrone.stefano@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionNeuroscience is a young discipline and an expanding field of study and research. The number of neuroscience postgraduate courses has risen much more rapidly than in any other field of biomedical research. However, from a scholarship perspective, the master's experience has been understudied. This work focuses on the answers given by a group of neuroscience alumni, a rarely examined academic cohort, to a straightforward question: 'What is the most important lesson you learnt as a master's student?'.

methodsThematic analysis was performed on 27 entries hosted by a public-facing blog of a STEM-intense university across four academic years.

resultsFour themes emerged: Skills, Theoretical knowledge, Attitudes and Community. Beyond replicating previous findings on the importance of skills and theoretical knowledge, an 'imbalance' between them has been reported for the first time. What emerges in our work is the overwhelming importance the alumni place in attitudes, especially resilience, and in the social/community aspects of learning, along with the role played by fellow students, faculty and laboratory colleagues. DISCUSSION: The master's level can be the ideal one for increasing awareness of resilience and learning how to make the most of it. Institutions should consider strategies for strengthening informal learning and supporting the development of professional identities. These findings can be of interest to a wide range of neuroscience educators and provide useful insights for designing effective postgraduate training courses. Future works can investigate the how beyond the what and explore the roles played by attitudes, emotions and feelings across neuroscientists' career stages.

Indexed as

Education, GraduateNeurosciencesFemaleHumansLearningMaleAttitudesCommunityIdentityKnowledgeMedical educationNeuroscience educationNeuroscience teachingSkills

Identifiers

PMID39472857
PMCPMC11520777

What OpenQuestion holds

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LicenceCC BY
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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.