Evidence map›Paper›PMID 38459476›Full record

ArticleBMC medical education2024

Medical students' awareness of overdiagnosis and implications for preventing overdiagnosis.

Lucinda Colbert, Iman Hegazi, Kath Peters, Natalie Edmiston

Open access · goldAbstract 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 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 14% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. 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

4 authors at 2 institutions in 1 country.

Lucinda ColbertHervey Bay Hospital, Wide Bay Hospital and Health Service, Hervey Bay, QLD, Australia.
Iman HegaziSchool of Medicine, Western Sydney University, Campbelltown, NSW, Australia.
Kath PetersSchool of Nursing and Midwifery, Western Sydney University, Campbelltown, NSW, Australia.
Natalie EdmistonUniversity Centre for Rural Health, Lismore, NSW, Australia. n.edmiston@westernsydney.edu.au.
Western Sydney University · AULismore Base Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Overdiagnosis is a growing health issue, yet our understanding of medical students' exposure to this concept within medical education is limited. Our aim was to explore students' experience of diagnostic learning to identify how overdiagnosis may be understood by students. During in-person and online semi-structured interviews throughout 2021, we explored the education experience of twelve Western Sydney University medical students in years 3-5. Through inductive thematic analysis we identified four themes. These themes encompassed student commitment to learning about diagnosis, lack of certainty surrounding diagnosis and emotional factors of medical care, overdiagnosis as seen through the lens of high and low-value care during clinical placements and student-identified missed learning opportunities related to overdiagnosis. This study found that medical students develop inherent knowledge of overdiagnosis through an interplay of personal factors, medical school curriculum and the setting in which their training takes place. Our findings allow insight for future improvement of medical curriculum to produce exceptional medical graduates.

Indexed as

Education, MedicalStudents, MedicalCurriculumHumansLearningOverdiagnosisClinical placementsDiagnosisMedical educationMedical studentOverdiagnosis

Identifiers

PMID38459476
PMCPMC10921797
OpenAlexW4392597314

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.