Evidence map›Paper›PMID 36627667›Full record

ArticleBMC medical education2023

How do medical students learn in an online community diagnostics program?

Junji Haruta, Takayuki Ando, Seitaro Fujishima

Open access · goldAbstract read
In one paragraph

Article in BMC medical education, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.2field-weighted citation impact, top 13% 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, 10 citations in OpenAlex.

  1. Article
  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

3 authors at 2 institutions in 1 country.

Junji HarutaMedical Education Center, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan. junharujp@keio.jp.
Takayuki AndoCenter for General Medicine Education, School of Medicine, Keio University, Tokyo, Japan.
Seitaro FujishimaCenter for General Medicine Education, School of Medicine, Keio University, Tokyo, Japan.
Keio University · JPKeio University Hospital · JP

Funding

Grant-in-Aid for Scientific Research (B) 22H03320
6 · The paper itself

Abstract

backgroundThe need to engage medical students in understanding the social and environmental determinants of health in disparate communities is increasing. However, previous reviews have noted the limited community diagnosis programs and program evaluation. Given the feasibility of the programs, it is expected to be widely available online. Therefore, this study used a realist approach to identify learning patterns through an online community diagnosis program, namely context (C), mechanism (M), and outcomes (O) patterns.

methodsA 2-week general medicine clinical practice program was conducted for 4

resultsFirst, the medical students, who spent most of their time in the limited residential areas they lived in, discovered the characteristics of their own community by discovery learning and comparison among peers. Second, they increased their intrinsic interest in the community by discerning specific issues in their familiar community through community diagnosis. Third, they valued community diagnosis by identifying relationships between local data on health issues under their learning responsibility. Fourth, they become more flexible in their thinking and created new knowledge that would fit the local community, and their reflection on themselves was encouraged.

conclusionIn this online community diagnosis program, medical students learned about the community through four types of learning patterns. Medical students may develop an understanding of community with interest using variation theory as a program development perspective and cognitive flexibility theory surrounding the essential ambiguity and abstraction of community.

Indexed as

Students, MedicalConcept FormationHumansLearningProgram DevelopmentProgram EvaluationCommunity diagnosisCommunity-orientedEvaluationLearning mechanismLearning outcomesRealist approach

Identifiers

PMID36627667
PMCPMC9830126
OpenAlexW4315486860

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.