Evidence map›Paper›PMID 35135909›Full record

ArticleFukushima journal of medical science2022

Impact of general practice / family medicine clerkships on Japanese medical students: Using text mining to analyze reflective writing.

Koki Nakamura, Satoshi Kanke, Goro Hoshi, Yoshihiro Toyoda, Kazutaka Yoshida, Ryuki Kassai

Abstract read
In one paragraph

Article in Fukushima journal of medical science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Koki NakamuraDepartment of Community and Family Medicine, Fukushima Medical University.
Satoshi KankeDepartment of Community and Family Medicine, Fukushima Medical University.
Goro HoshiHoshi Yokozuka Clinic.
Yoshihiro ToyodaKitakata Centre for Community and Family Medicine.
Kazutaka YoshidaDepartment of Community and Family Medicine, Fukushima Medical University.
Ryuki KassaiDepartment of Community and Family Medicine, Fukushima Medical University.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn order for general practice / family medicine clerkships to be improved in undergraduate medical education, it is necessary to clarify the impacts of general practice / family medicine clerkships. Using text mining to analyze the reflective writing of medical students may be useful for further understanding the impacts of clinical clerkships on medical students.

methodsThe study involved 125 fifth-year Fukushima Medical University School of Medicine students in the academic year 2018-2019. The settings were three clinics and the study period was 5 days. The clerkships included outpatient and home visits. Students' reflective writing on their clerkship experience was collected on the final day. Text mining was used to extract the most frequent words (nouns) from the reflective writing. A co-occurrence network map was created to illustrate the relationships between the most frequent words.

results124 students participated in the study. The total number of sentences extracted was 321 and the total number of words was 10,627. The top five frequently-occurring words were patient, home-visit, medical practice, medical care, and family. From the co-occurrence network map, a co-occurrence relationship was recognized between home-visit and family.

conclusionData suggest that medical students may learn the necessity of care for the family as well as the patient in a home-care setting.

Indexed as

General PracticeStudents, MedicalData MiningFamily PracticeHumansJapanWritingclinical clerkshipscommunity medicinemedical educationreflective writingtext mining

Identifiers

PMID35135909
PMCPMC9071354

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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Registered trials

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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.